diff --git a/docs/_posts/DevinTDHa/2024-11-02-Nomic_Embed_Text_v1.5.Q8_0.gguf_en.md b/docs/_posts/DevinTDHa/2024-11-02-Nomic_Embed_Text_v1.5.Q8_0.gguf_en.md
new file mode 100644
index 00000000000000..c84e7a24ead170
--- /dev/null
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@@ -0,0 +1,115 @@
+---
+layout: model
+title: nomic-embed-text-v1.5.Q8_0.gguf
+author: John Snow Labs
+name: Nomic_Embed_Text_v1.5.Q8_0.gguf
+date: 2024-11-02
+tags: [gguf, nomic, embeddings, open_source, en, llamacpp]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.2
+spark_version: 3.4
+supported: true
+engine: llamacpp
+annotator: AutoGGUFEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+nomic-embed-text is a 8192 context length text encoder that surpasses OpenAI text-embedding-ada-002 and text-embedding-3-small performance on short and long context tasks.
+
+This model is the updated 1.5 version.
+
+Original model from https://huggingface.co/nomic-ai/nomic-embed-text-v1.5
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/Nomic_Embed_Text_v1.5.Q8_0.gguf_en_5.5.2_3.4_1730556912139.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/Nomic_Embed_Text_v1.5.Q8_0.gguf_en_5.5.2_3.4_1730556912139.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+import sparknlp
+from sparknlp.base import *
+from sparknlp.annotator import *
+from pyspark.ml import Pipeline
+document = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+autoGGUFModel = AutoGGUFModel.pretrained() \
+    .setInputCols(["document"]) \
+    .setOutputCol("completions") \
+    .setBatchSize(4) \
+    .setNPredict(20) \
+    .setNGpuLayers(99) \
+    .setTemperature(0.4) \
+    .setTopK(40) \
+    .setTopP(0.9) \
+    .setPenalizeNl(True)
+pipeline = Pipeline().setStages([document, autoGGUFModel])
+data = spark.createDataFrame([[The moons of Jupiter are 77 in total, with 79 confirmed natural satellites and 2 man-made ones."]]).toDF("text")
+result = pipeline.fit(data).transform(data)
+result.select("completions").show(truncate = False)
+```
+```scala
+import com.johnsnowlabs.nlp.base._
+import com.johnsnowlabs.nlp.annotator._
+import org.apache.spark.ml.Pipeline
+import spark.implicits._
+
+val document = new DocumentAssembler().setInputCol("text").setOutputCol("document")
+
+val autoGGUFModel = AutoGGUFEmbeddings
+  .pretrained()
+  .setInputCols("document")
+  .setOutputCol("embeddings")
+  .setBatchSize(4)
+  .setPoolingType("MEAN")
+
+val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel))
+
+val data = Seq(
+  "The moons of Jupiter are 77 in total, with 79 confirmed natural satellites and 2 man-made ones.")
+  .toDF("text")
+val result = pipeline.fit(data).transform(data)
+result.select("embeddings.embeddings").show(truncate = false)
+
+```
+</div>
+
+## Results
+
+```bash
++--------------------------------------------------------------------------------+
+|                                                                      embeddings|
++--------------------------------------------------------------------------------+
+|[[-0.034486726, 0.07770534, -0.15982522, -0.017873349, 0.013914132, 0.0365736...|
++--------------------------------------------------------------------------------+
+```
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|Nomic_Embed_Text_v1.5.Q8_0.gguf|
+|Compatibility:|Spark NLP 5.5.2+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|140.7 MB|
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-autotrain_ecb_uncertainty_deberta_v3_large_en.md b/docs/_posts/ahmedlone127/2024-12-18-autotrain_ecb_uncertainty_deberta_v3_large_en.md
new file mode 100644
index 00000000000000..12cc3dd6b393ca
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@@ -0,0 +1,94 @@
+---
+layout: model
+title: English autotrain_ecb_uncertainty_deberta_v3_large DeBertaForSequenceClassification from jjonas313
+author: John Snow Labs
+name: autotrain_ecb_uncertainty_deberta_v3_large
+date: 2024-12-18
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_ecb_uncertainty_deberta_v3_large` is a English model originally trained by jjonas313.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_ecb_uncertainty_deberta_v3_large_en_5.5.1_3.0_1734561918485.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_ecb_uncertainty_deberta_v3_large_en_5.5.1_3.0_1734561918485.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("autotrain_ecb_uncertainty_deberta_v3_large","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("autotrain_ecb_uncertainty_deberta_v3_large", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_ecb_uncertainty_deberta_v3_large|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/jjonas313/autotrain-ecb-uncertainty-deberta-v3-large
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-autotrain_ecb_uncertainty_deberta_v3_large_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-autotrain_ecb_uncertainty_deberta_v3_large_pipeline_en.md
new file mode 100644
index 00000000000000..4dad2ef3fcb6e0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-autotrain_ecb_uncertainty_deberta_v3_large_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English autotrain_ecb_uncertainty_deberta_v3_large_pipeline pipeline DeBertaForSequenceClassification from jjonas313
+author: John Snow Labs
+name: autotrain_ecb_uncertainty_deberta_v3_large_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_ecb_uncertainty_deberta_v3_large_pipeline` is a English model originally trained by jjonas313.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_ecb_uncertainty_deberta_v3_large_pipeline_en_5.5.1_3.0_1734562060583.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_ecb_uncertainty_deberta_v3_large_pipeline_en_5.5.1_3.0_1734562060583.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("autotrain_ecb_uncertainty_deberta_v3_large_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("autotrain_ecb_uncertainty_deberta_v3_large_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_ecb_uncertainty_deberta_v3_large_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/jjonas313/autotrain-ecb-uncertainty-deberta-v3-large
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-baai_bge_large_english_v1_5_fine_tuned_fold1_20241117_105432_boosting_2_en.md b/docs/_posts/ahmedlone127/2024-12-18-baai_bge_large_english_v1_5_fine_tuned_fold1_20241117_105432_boosting_2_en.md
new file mode 100644
index 00000000000000..9f488dfc9942dd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-baai_bge_large_english_v1_5_fine_tuned_fold1_20241117_105432_boosting_2_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English baai_bge_large_english_v1_5_fine_tuned_fold1_20241117_105432_boosting_2 BGEEmbeddings from marumarukun
+author: John Snow Labs
+name: baai_bge_large_english_v1_5_fine_tuned_fold1_20241117_105432_boosting_2
+date: 2024-12-18
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`baai_bge_large_english_v1_5_fine_tuned_fold1_20241117_105432_boosting_2` is a English model originally trained by marumarukun.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/baai_bge_large_english_v1_5_fine_tuned_fold1_20241117_105432_boosting_2_en_5.5.1_3.0_1734563845660.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/baai_bge_large_english_v1_5_fine_tuned_fold1_20241117_105432_boosting_2_en_5.5.1_3.0_1734563845660.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("baai_bge_large_english_v1_5_fine_tuned_fold1_20241117_105432_boosting_2","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("baai_bge_large_english_v1_5_fine_tuned_fold1_20241117_105432_boosting_2","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|baai_bge_large_english_v1_5_fine_tuned_fold1_20241117_105432_boosting_2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/marumarukun/BAAI-bge-large-en-v1.5_fine_tuned_fold1_20241117_105432_boosting_2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-baai_bge_large_english_v1_5_fine_tuned_fold1_20241117_105432_boosting_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-baai_bge_large_english_v1_5_fine_tuned_fold1_20241117_105432_boosting_2_pipeline_en.md
new file mode 100644
index 00000000000000..0f6203e05b52ed
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-baai_bge_large_english_v1_5_fine_tuned_fold1_20241117_105432_boosting_2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English baai_bge_large_english_v1_5_fine_tuned_fold1_20241117_105432_boosting_2_pipeline pipeline BGEEmbeddings from marumarukun
+author: John Snow Labs
+name: baai_bge_large_english_v1_5_fine_tuned_fold1_20241117_105432_boosting_2_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`baai_bge_large_english_v1_5_fine_tuned_fold1_20241117_105432_boosting_2_pipeline` is a English model originally trained by marumarukun.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/baai_bge_large_english_v1_5_fine_tuned_fold1_20241117_105432_boosting_2_pipeline_en_5.5.1_3.0_1734563915419.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/baai_bge_large_english_v1_5_fine_tuned_fold1_20241117_105432_boosting_2_pipeline_en_5.5.1_3.0_1734563915419.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("baai_bge_large_english_v1_5_fine_tuned_fold1_20241117_105432_boosting_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("baai_bge_large_english_v1_5_fine_tuned_fold1_20241117_105432_boosting_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|baai_bge_large_english_v1_5_fine_tuned_fold1_20241117_105432_boosting_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/marumarukun/BAAI-bge-large-en-v1.5_fine_tuned_fold1_20241117_105432_boosting_2
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-baai_bge_large_english_v1_5_fine_tuned_fold2_20241115_191836_en.md b/docs/_posts/ahmedlone127/2024-12-18-baai_bge_large_english_v1_5_fine_tuned_fold2_20241115_191836_en.md
new file mode 100644
index 00000000000000..7fa9ba5473933b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-baai_bge_large_english_v1_5_fine_tuned_fold2_20241115_191836_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English baai_bge_large_english_v1_5_fine_tuned_fold2_20241115_191836 BGEEmbeddings from marumarukun
+author: John Snow Labs
+name: baai_bge_large_english_v1_5_fine_tuned_fold2_20241115_191836
+date: 2024-12-18
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`baai_bge_large_english_v1_5_fine_tuned_fold2_20241115_191836` is a English model originally trained by marumarukun.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/baai_bge_large_english_v1_5_fine_tuned_fold2_20241115_191836_en_5.5.1_3.0_1734562676508.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/baai_bge_large_english_v1_5_fine_tuned_fold2_20241115_191836_en_5.5.1_3.0_1734562676508.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("baai_bge_large_english_v1_5_fine_tuned_fold2_20241115_191836","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("baai_bge_large_english_v1_5_fine_tuned_fold2_20241115_191836","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|baai_bge_large_english_v1_5_fine_tuned_fold2_20241115_191836|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/marumarukun/BAAI-bge-large-en-v1.5_fine_tuned_fold2_20241115_191836
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-baai_bge_large_english_v1_5_fine_tuned_fold2_20241115_191836_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-baai_bge_large_english_v1_5_fine_tuned_fold2_20241115_191836_pipeline_en.md
new file mode 100644
index 00000000000000..b8986ade47d013
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-baai_bge_large_english_v1_5_fine_tuned_fold2_20241115_191836_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English baai_bge_large_english_v1_5_fine_tuned_fold2_20241115_191836_pipeline pipeline BGEEmbeddings from marumarukun
+author: John Snow Labs
+name: baai_bge_large_english_v1_5_fine_tuned_fold2_20241115_191836_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`baai_bge_large_english_v1_5_fine_tuned_fold2_20241115_191836_pipeline` is a English model originally trained by marumarukun.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/baai_bge_large_english_v1_5_fine_tuned_fold2_20241115_191836_pipeline_en_5.5.1_3.0_1734562745937.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/baai_bge_large_english_v1_5_fine_tuned_fold2_20241115_191836_pipeline_en_5.5.1_3.0_1734562745937.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("baai_bge_large_english_v1_5_fine_tuned_fold2_20241115_191836_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("baai_bge_large_english_v1_5_fine_tuned_fold2_20241115_191836_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|baai_bge_large_english_v1_5_fine_tuned_fold2_20241115_191836_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/marumarukun/BAAI-bge-large-en-v1.5_fine_tuned_fold2_20241115_191836
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-baai_bge_large_english_v1_5_fine_tuned_fold3_20241115_191836_en.md b/docs/_posts/ahmedlone127/2024-12-18-baai_bge_large_english_v1_5_fine_tuned_fold3_20241115_191836_en.md
new file mode 100644
index 00000000000000..24191ca2f15bab
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-baai_bge_large_english_v1_5_fine_tuned_fold3_20241115_191836_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English baai_bge_large_english_v1_5_fine_tuned_fold3_20241115_191836 BGEEmbeddings from marumarukun
+author: John Snow Labs
+name: baai_bge_large_english_v1_5_fine_tuned_fold3_20241115_191836
+date: 2024-12-18
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`baai_bge_large_english_v1_5_fine_tuned_fold3_20241115_191836` is a English model originally trained by marumarukun.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/baai_bge_large_english_v1_5_fine_tuned_fold3_20241115_191836_en_5.5.1_3.0_1734564164487.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/baai_bge_large_english_v1_5_fine_tuned_fold3_20241115_191836_en_5.5.1_3.0_1734564164487.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("baai_bge_large_english_v1_5_fine_tuned_fold3_20241115_191836","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("baai_bge_large_english_v1_5_fine_tuned_fold3_20241115_191836","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|baai_bge_large_english_v1_5_fine_tuned_fold3_20241115_191836|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/marumarukun/BAAI-bge-large-en-v1.5_fine_tuned_fold3_20241115_191836
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-baai_bge_large_english_v1_5_fine_tuned_fold3_20241115_191836_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-baai_bge_large_english_v1_5_fine_tuned_fold3_20241115_191836_pipeline_en.md
new file mode 100644
index 00000000000000..643378b8cfb541
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-baai_bge_large_english_v1_5_fine_tuned_fold3_20241115_191836_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English baai_bge_large_english_v1_5_fine_tuned_fold3_20241115_191836_pipeline pipeline BGEEmbeddings from marumarukun
+author: John Snow Labs
+name: baai_bge_large_english_v1_5_fine_tuned_fold3_20241115_191836_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`baai_bge_large_english_v1_5_fine_tuned_fold3_20241115_191836_pipeline` is a English model originally trained by marumarukun.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/baai_bge_large_english_v1_5_fine_tuned_fold3_20241115_191836_pipeline_en_5.5.1_3.0_1734564238842.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/baai_bge_large_english_v1_5_fine_tuned_fold3_20241115_191836_pipeline_en_5.5.1_3.0_1734564238842.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("baai_bge_large_english_v1_5_fine_tuned_fold3_20241115_191836_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("baai_bge_large_english_v1_5_fine_tuned_fold3_20241115_191836_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|baai_bge_large_english_v1_5_fine_tuned_fold3_20241115_191836_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/marumarukun/BAAI-bge-large-en-v1.5_fine_tuned_fold3_20241115_191836
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-bge_base_english_v1_5_65_keys_phase_5_exp_v1_en.md b/docs/_posts/ahmedlone127/2024-12-18-bge_base_english_v1_5_65_keys_phase_5_exp_v1_en.md
new file mode 100644
index 00000000000000..4739a92a8e5f58
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-bge_base_english_v1_5_65_keys_phase_5_exp_v1_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_base_english_v1_5_65_keys_phase_5_exp_v1 BGEEmbeddings from RishuD7
+author: John Snow Labs
+name: bge_base_english_v1_5_65_keys_phase_5_exp_v1
+date: 2024-12-18
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_english_v1_5_65_keys_phase_5_exp_v1` is a English model originally trained by RishuD7.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_65_keys_phase_5_exp_v1_en_5.5.1_3.0_1734564307470.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_65_keys_phase_5_exp_v1_en_5.5.1_3.0_1734564307470.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_base_english_v1_5_65_keys_phase_5_exp_v1","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_base_english_v1_5_65_keys_phase_5_exp_v1","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_english_v1_5_65_keys_phase_5_exp_v1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|392.4 MB|
+
+## References
+
+https://huggingface.co/RishuD7/bge-base-en-v1.5-65-keys-phase-5-exp_v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-bge_base_english_v1_5_65_keys_phase_5_exp_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-bge_base_english_v1_5_65_keys_phase_5_exp_v1_pipeline_en.md
new file mode 100644
index 00000000000000..73502876ac352d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-bge_base_english_v1_5_65_keys_phase_5_exp_v1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_base_english_v1_5_65_keys_phase_5_exp_v1_pipeline pipeline BGEEmbeddings from RishuD7
+author: John Snow Labs
+name: bge_base_english_v1_5_65_keys_phase_5_exp_v1_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_english_v1_5_65_keys_phase_5_exp_v1_pipeline` is a English model originally trained by RishuD7.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_65_keys_phase_5_exp_v1_pipeline_en_5.5.1_3.0_1734564332192.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_65_keys_phase_5_exp_v1_pipeline_en_5.5.1_3.0_1734564332192.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_base_english_v1_5_65_keys_phase_5_exp_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_base_english_v1_5_65_keys_phase_5_exp_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_english_v1_5_65_keys_phase_5_exp_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|392.4 MB|
+
+## References
+
+https://huggingface.co/RishuD7/bge-base-en-v1.5-65-keys-phase-5-exp_v1
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-bge_base_english_v1_5_course_recommender_v4python_en.md b/docs/_posts/ahmedlone127/2024-12-18-bge_base_english_v1_5_course_recommender_v4python_en.md
new file mode 100644
index 00000000000000..419c1435a8525a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-bge_base_english_v1_5_course_recommender_v4python_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_base_english_v1_5_course_recommender_v4python BGEEmbeddings from datasocietyco
+author: John Snow Labs
+name: bge_base_english_v1_5_course_recommender_v4python
+date: 2024-12-18
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_english_v1_5_course_recommender_v4python` is a English model originally trained by datasocietyco.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_course_recommender_v4python_en_5.5.1_3.0_1734563229379.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_course_recommender_v4python_en_5.5.1_3.0_1734563229379.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_base_english_v1_5_course_recommender_v4python","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_base_english_v1_5_course_recommender_v4python","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_english_v1_5_course_recommender_v4python|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|375.9 MB|
+
+## References
+
+https://huggingface.co/datasocietyco/bge-base-en-v1.5-course-recommender-v4python
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-bge_base_english_v1_5_course_recommender_v4python_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-bge_base_english_v1_5_course_recommender_v4python_pipeline_en.md
new file mode 100644
index 00000000000000..82836b629bf60f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-bge_base_english_v1_5_course_recommender_v4python_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_base_english_v1_5_course_recommender_v4python_pipeline pipeline BGEEmbeddings from datasocietyco
+author: John Snow Labs
+name: bge_base_english_v1_5_course_recommender_v4python_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_english_v1_5_course_recommender_v4python_pipeline` is a English model originally trained by datasocietyco.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_course_recommender_v4python_pipeline_en_5.5.1_3.0_1734563260689.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_course_recommender_v4python_pipeline_en_5.5.1_3.0_1734563260689.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_base_english_v1_5_course_recommender_v4python_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_base_english_v1_5_course_recommender_v4python_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_english_v1_5_course_recommender_v4python_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|375.9 MB|
+
+## References
+
+https://huggingface.co/datasocietyco/bge-base-en-v1.5-course-recommender-v4python
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-bge_base_english_v1_5_ft_en.md b/docs/_posts/ahmedlone127/2024-12-18-bge_base_english_v1_5_ft_en.md
new file mode 100644
index 00000000000000..9ed9b1adfbfee8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-bge_base_english_v1_5_ft_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_base_english_v1_5_ft BGEEmbeddings from aritrasen
+author: John Snow Labs
+name: bge_base_english_v1_5_ft
+date: 2024-12-18
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_english_v1_5_ft` is a English model originally trained by aritrasen.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_ft_en_5.5.1_3.0_1734562918563.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_ft_en_5.5.1_3.0_1734562918563.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_base_english_v1_5_ft","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_base_english_v1_5_ft","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_english_v1_5_ft|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|376.0 MB|
+
+## References
+
+https://huggingface.co/aritrasen/bge-base-en-v1.5-ft
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-bge_base_english_v1_5_ft_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-bge_base_english_v1_5_ft_pipeline_en.md
new file mode 100644
index 00000000000000..3aaa30fa8b8cfe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-bge_base_english_v1_5_ft_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_base_english_v1_5_ft_pipeline pipeline BGEEmbeddings from aritrasen
+author: John Snow Labs
+name: bge_base_english_v1_5_ft_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_english_v1_5_ft_pipeline` is a English model originally trained by aritrasen.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_ft_pipeline_en_5.5.1_3.0_1734562949247.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_ft_pipeline_en_5.5.1_3.0_1734562949247.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_base_english_v1_5_ft_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_base_english_v1_5_ft_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_english_v1_5_ft_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|376.0 MB|
+
+## References
+
+https://huggingface.co/aritrasen/bge-base-en-v1.5-ft
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_abinj30_en.md b/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_abinj30_en.md
new file mode 100644
index 00000000000000..19d94c4931071f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_abinj30_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_base_financial_matryoshka_abinj30 BGEEmbeddings from abinj30
+author: John Snow Labs
+name: bge_base_financial_matryoshka_abinj30
+date: 2024-12-18
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_abinj30` is a English model originally trained by abinj30.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_abinj30_en_5.5.1_3.0_1734562913004.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_abinj30_en_5.5.1_3.0_1734562913004.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_abinj30","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_abinj30","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_financial_matryoshka_abinj30|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|387.1 MB|
+
+## References
+
+https://huggingface.co/abinj30/bge-base-financial-matryoshka
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_abinj30_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_abinj30_pipeline_en.md
new file mode 100644
index 00000000000000..9f57cc1394fa32
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_abinj30_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_base_financial_matryoshka_abinj30_pipeline pipeline BGEEmbeddings from abinj30
+author: John Snow Labs
+name: bge_base_financial_matryoshka_abinj30_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_abinj30_pipeline` is a English model originally trained by abinj30.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_abinj30_pipeline_en_5.5.1_3.0_1734562940508.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_abinj30_pipeline_en_5.5.1_3.0_1734562940508.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_base_financial_matryoshka_abinj30_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_base_financial_matryoshka_abinj30_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_financial_matryoshka_abinj30_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|387.1 MB|
+
+## References
+
+https://huggingface.co/abinj30/bge-base-financial-matryoshka
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_amietheace_en.md b/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_amietheace_en.md
new file mode 100644
index 00000000000000..6551999433449d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_amietheace_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_base_financial_matryoshka_amietheace BGEEmbeddings from amietheace
+author: John Snow Labs
+name: bge_base_financial_matryoshka_amietheace
+date: 2024-12-18
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_amietheace` is a English model originally trained by amietheace.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_amietheace_en_5.5.1_3.0_1734563870103.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_amietheace_en_5.5.1_3.0_1734563870103.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_amietheace","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_amietheace","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_financial_matryoshka_amietheace|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|387.1 MB|
+
+## References
+
+https://huggingface.co/amietheace/bge-base-financial-matryoshka
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_amietheace_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_amietheace_pipeline_en.md
new file mode 100644
index 00000000000000..c5ed3d4d1c431b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_amietheace_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_base_financial_matryoshka_amietheace_pipeline pipeline BGEEmbeddings from amietheace
+author: John Snow Labs
+name: bge_base_financial_matryoshka_amietheace_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_amietheace_pipeline` is a English model originally trained by amietheace.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_amietheace_pipeline_en_5.5.1_3.0_1734563897131.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_amietheace_pipeline_en_5.5.1_3.0_1734563897131.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_base_financial_matryoshka_amietheace_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_base_financial_matryoshka_amietheace_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_financial_matryoshka_amietheace_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|387.1 MB|
+
+## References
+
+https://huggingface.co/amietheace/bge-base-financial-matryoshka
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_baljee_en.md b/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_baljee_en.md
new file mode 100644
index 00000000000000..95e71d76df592a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_baljee_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_base_financial_matryoshka_baljee BGEEmbeddings from Baljee
+author: John Snow Labs
+name: bge_base_financial_matryoshka_baljee
+date: 2024-12-18
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_baljee` is a English model originally trained by Baljee.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_baljee_en_5.5.1_3.0_1734564144003.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_baljee_en_5.5.1_3.0_1734564144003.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_baljee","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_baljee","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_financial_matryoshka_baljee|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|387.1 MB|
+
+## References
+
+https://huggingface.co/Baljee/bge-base-financial-matryoshka
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_baljee_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_baljee_pipeline_en.md
new file mode 100644
index 00000000000000..821d2c476d4c7f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_baljee_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_base_financial_matryoshka_baljee_pipeline pipeline BGEEmbeddings from Baljee
+author: John Snow Labs
+name: bge_base_financial_matryoshka_baljee_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_baljee_pipeline` is a English model originally trained by Baljee.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_baljee_pipeline_en_5.5.1_3.0_1734564171090.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_baljee_pipeline_en_5.5.1_3.0_1734564171090.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_base_financial_matryoshka_baljee_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_base_financial_matryoshka_baljee_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_financial_matryoshka_baljee_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|387.1 MB|
+
+## References
+
+https://huggingface.co/Baljee/bge-base-financial-matryoshka
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_felipehsilveira_en.md b/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_felipehsilveira_en.md
new file mode 100644
index 00000000000000..6ad424b7988fea
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_felipehsilveira_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_base_financial_matryoshka_felipehsilveira BGEEmbeddings from felipehsilveira
+author: John Snow Labs
+name: bge_base_financial_matryoshka_felipehsilveira
+date: 2024-12-18
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_felipehsilveira` is a English model originally trained by felipehsilveira.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_felipehsilveira_en_5.5.1_3.0_1734564247950.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_felipehsilveira_en_5.5.1_3.0_1734564247950.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_felipehsilveira","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_felipehsilveira","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_financial_matryoshka_felipehsilveira|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|387.1 MB|
+
+## References
+
+https://huggingface.co/felipehsilveira/bge-base-financial-matryoshka
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_felipehsilveira_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_felipehsilveira_pipeline_en.md
new file mode 100644
index 00000000000000..912223a045bf24
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_felipehsilveira_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_base_financial_matryoshka_felipehsilveira_pipeline pipeline BGEEmbeddings from felipehsilveira
+author: John Snow Labs
+name: bge_base_financial_matryoshka_felipehsilveira_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_felipehsilveira_pipeline` is a English model originally trained by felipehsilveira.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_felipehsilveira_pipeline_en_5.5.1_3.0_1734564277087.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_felipehsilveira_pipeline_en_5.5.1_3.0_1734564277087.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_base_financial_matryoshka_felipehsilveira_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_base_financial_matryoshka_felipehsilveira_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_financial_matryoshka_felipehsilveira_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|387.1 MB|
+
+## References
+
+https://huggingface.co/felipehsilveira/bge-base-financial-matryoshka
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_girijesh_en.md b/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_girijesh_en.md
new file mode 100644
index 00000000000000..7ae3b78fe2cc2e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_girijesh_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_base_financial_matryoshka_girijesh BGEEmbeddings from girijesh
+author: John Snow Labs
+name: bge_base_financial_matryoshka_girijesh
+date: 2024-12-18
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_girijesh` is a English model originally trained by girijesh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_girijesh_en_5.5.1_3.0_1734563074310.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_girijesh_en_5.5.1_3.0_1734563074310.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_girijesh","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_girijesh","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_financial_matryoshka_girijesh|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|387.1 MB|
+
+## References
+
+https://huggingface.co/girijesh/bge-base-financial-matryoshka
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_girijesh_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_girijesh_pipeline_en.md
new file mode 100644
index 00000000000000..b58639ccd92a04
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_girijesh_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_base_financial_matryoshka_girijesh_pipeline pipeline BGEEmbeddings from girijesh
+author: John Snow Labs
+name: bge_base_financial_matryoshka_girijesh_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_girijesh_pipeline` is a English model originally trained by girijesh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_girijesh_pipeline_en_5.5.1_3.0_1734563101399.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_girijesh_pipeline_en_5.5.1_3.0_1734563101399.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_base_financial_matryoshka_girijesh_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_base_financial_matryoshka_girijesh_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_financial_matryoshka_girijesh_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|387.1 MB|
+
+## References
+
+https://huggingface.co/girijesh/bge-base-financial-matryoshka
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_macfooty_en.md b/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_macfooty_en.md
new file mode 100644
index 00000000000000..14384223c2a567
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_macfooty_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_base_financial_matryoshka_macfooty BGEEmbeddings from macfooty
+author: John Snow Labs
+name: bge_base_financial_matryoshka_macfooty
+date: 2024-12-18
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_macfooty` is a English model originally trained by macfooty.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_macfooty_en_5.5.1_3.0_1734563685103.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_macfooty_en_5.5.1_3.0_1734563685103.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_macfooty","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_macfooty","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_financial_matryoshka_macfooty|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|387.1 MB|
+
+## References
+
+https://huggingface.co/macfooty/bge-base-financial-matryoshka
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_macfooty_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_macfooty_pipeline_en.md
new file mode 100644
index 00000000000000..27f01a29b5baa9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_macfooty_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_base_financial_matryoshka_macfooty_pipeline pipeline BGEEmbeddings from macfooty
+author: John Snow Labs
+name: bge_base_financial_matryoshka_macfooty_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_macfooty_pipeline` is a English model originally trained by macfooty.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_macfooty_pipeline_en_5.5.1_3.0_1734563712394.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_macfooty_pipeline_en_5.5.1_3.0_1734563712394.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_base_financial_matryoshka_macfooty_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_base_financial_matryoshka_macfooty_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_financial_matryoshka_macfooty_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|387.1 MB|
+
+## References
+
+https://huggingface.co/macfooty/bge-base-financial-matryoshka
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_prateek_genpact_en.md b/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_prateek_genpact_en.md
new file mode 100644
index 00000000000000..3a48be2c76de7f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_prateek_genpact_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_base_financial_matryoshka_prateek_genpact BGEEmbeddings from prateek-genpact
+author: John Snow Labs
+name: bge_base_financial_matryoshka_prateek_genpact
+date: 2024-12-18
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_prateek_genpact` is a English model originally trained by prateek-genpact.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_prateek_genpact_en_5.5.1_3.0_1734562428964.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_prateek_genpact_en_5.5.1_3.0_1734562428964.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_prateek_genpact","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_prateek_genpact","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_financial_matryoshka_prateek_genpact|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|387.1 MB|
+
+## References
+
+https://huggingface.co/prateek-genpact/bge-base-financial-matryoshka
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_prateek_genpact_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_prateek_genpact_pipeline_en.md
new file mode 100644
index 00000000000000..08dd8dc69f97f7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_prateek_genpact_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_base_financial_matryoshka_prateek_genpact_pipeline pipeline BGEEmbeddings from prateek-genpact
+author: John Snow Labs
+name: bge_base_financial_matryoshka_prateek_genpact_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_prateek_genpact_pipeline` is a English model originally trained by prateek-genpact.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_prateek_genpact_pipeline_en_5.5.1_3.0_1734562458686.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_prateek_genpact_pipeline_en_5.5.1_3.0_1734562458686.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_base_financial_matryoshka_prateek_genpact_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_base_financial_matryoshka_prateek_genpact_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_financial_matryoshka_prateek_genpact_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|387.1 MB|
+
+## References
+
+https://huggingface.co/prateek-genpact/bge-base-financial-matryoshka
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_rakshit0041_en.md b/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_rakshit0041_en.md
new file mode 100644
index 00000000000000..c8cc7a7fa43d11
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_rakshit0041_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_base_financial_matryoshka_rakshit0041 BGEEmbeddings from Rakshit0041
+author: John Snow Labs
+name: bge_base_financial_matryoshka_rakshit0041
+date: 2024-12-18
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_rakshit0041` is a English model originally trained by Rakshit0041.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_rakshit0041_en_5.5.1_3.0_1734562977683.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_rakshit0041_en_5.5.1_3.0_1734562977683.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_rakshit0041","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_rakshit0041","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_financial_matryoshka_rakshit0041|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|387.1 MB|
+
+## References
+
+https://huggingface.co/Rakshit0041/bge-base-financial-matryoshka
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_rakshit0041_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_rakshit0041_pipeline_en.md
new file mode 100644
index 00000000000000..f04305c53ebc52
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_rakshit0041_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_base_financial_matryoshka_rakshit0041_pipeline pipeline BGEEmbeddings from Rakshit0041
+author: John Snow Labs
+name: bge_base_financial_matryoshka_rakshit0041_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_rakshit0041_pipeline` is a English model originally trained by Rakshit0041.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_rakshit0041_pipeline_en_5.5.1_3.0_1734563004710.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_rakshit0041_pipeline_en_5.5.1_3.0_1734563004710.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_base_financial_matryoshka_rakshit0041_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_base_financial_matryoshka_rakshit0041_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_financial_matryoshka_rakshit0041_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|387.1 MB|
+
+## References
+
+https://huggingface.co/Rakshit0041/bge-base-financial-matryoshka
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_siddarth_pattnaik_en.md b/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_siddarth_pattnaik_en.md
new file mode 100644
index 00000000000000..c044ef106c134e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_siddarth_pattnaik_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_base_financial_matryoshka_siddarth_pattnaik BGEEmbeddings from Siddarth-Pattnaik
+author: John Snow Labs
+name: bge_base_financial_matryoshka_siddarth_pattnaik
+date: 2024-12-18
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_siddarth_pattnaik` is a English model originally trained by Siddarth-Pattnaik.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_siddarth_pattnaik_en_5.5.1_3.0_1734564520768.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_siddarth_pattnaik_en_5.5.1_3.0_1734564520768.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_siddarth_pattnaik","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_siddarth_pattnaik","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_financial_matryoshka_siddarth_pattnaik|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|387.1 MB|
+
+## References
+
+https://huggingface.co/Siddarth-Pattnaik/bge-base-financial-matryoshka
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_siddarth_pattnaik_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_siddarth_pattnaik_pipeline_en.md
new file mode 100644
index 00000000000000..d2bbab136ca5f7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_siddarth_pattnaik_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_base_financial_matryoshka_siddarth_pattnaik_pipeline pipeline BGEEmbeddings from Siddarth-Pattnaik
+author: John Snow Labs
+name: bge_base_financial_matryoshka_siddarth_pattnaik_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_siddarth_pattnaik_pipeline` is a English model originally trained by Siddarth-Pattnaik.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_siddarth_pattnaik_pipeline_en_5.5.1_3.0_1734564548018.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_siddarth_pattnaik_pipeline_en_5.5.1_3.0_1734564548018.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_base_financial_matryoshka_siddarth_pattnaik_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_base_financial_matryoshka_siddarth_pattnaik_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_financial_matryoshka_siddarth_pattnaik_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|387.1 MB|
+
+## References
+
+https://huggingface.co/Siddarth-Pattnaik/bge-base-financial-matryoshka
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_vinaykumarsoni_en.md b/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_vinaykumarsoni_en.md
new file mode 100644
index 00000000000000..b77567f98e0341
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_vinaykumarsoni_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_base_financial_matryoshka_vinaykumarsoni BGEEmbeddings from vinaykumarsoni
+author: John Snow Labs
+name: bge_base_financial_matryoshka_vinaykumarsoni
+date: 2024-12-18
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_vinaykumarsoni` is a English model originally trained by vinaykumarsoni.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_vinaykumarsoni_en_5.5.1_3.0_1734562429454.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_vinaykumarsoni_en_5.5.1_3.0_1734562429454.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_vinaykumarsoni","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_vinaykumarsoni","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_financial_matryoshka_vinaykumarsoni|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|387.1 MB|
+
+## References
+
+https://huggingface.co/vinaykumarsoni/bge-base-financial-matryoshka
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_vinaykumarsoni_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_vinaykumarsoni_pipeline_en.md
new file mode 100644
index 00000000000000..c5fd55950869b8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_vinaykumarsoni_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_base_financial_matryoshka_vinaykumarsoni_pipeline pipeline BGEEmbeddings from vinaykumarsoni
+author: John Snow Labs
+name: bge_base_financial_matryoshka_vinaykumarsoni_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_vinaykumarsoni_pipeline` is a English model originally trained by vinaykumarsoni.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_vinaykumarsoni_pipeline_en_5.5.1_3.0_1734562460299.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_vinaykumarsoni_pipeline_en_5.5.1_3.0_1734562460299.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_base_financial_matryoshka_vinaykumarsoni_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_base_financial_matryoshka_vinaykumarsoni_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_financial_matryoshka_vinaykumarsoni_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|387.1 MB|
+
+## References
+
+https://huggingface.co/vinaykumarsoni/bge-base-financial-matryoshka
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_vivintiger_en.md b/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_vivintiger_en.md
new file mode 100644
index 00000000000000..695a1f1b8b50a1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_vivintiger_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_base_financial_matryoshka_vivintiger BGEEmbeddings from VivinTiger
+author: John Snow Labs
+name: bge_base_financial_matryoshka_vivintiger
+date: 2024-12-18
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_vivintiger` is a English model originally trained by VivinTiger.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_vivintiger_en_5.5.1_3.0_1734563976835.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_vivintiger_en_5.5.1_3.0_1734563976835.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_vivintiger","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_vivintiger","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_financial_matryoshka_vivintiger|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|387.1 MB|
+
+## References
+
+https://huggingface.co/VivinTiger/bge-base-financial-matryoshka
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_vivintiger_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_vivintiger_pipeline_en.md
new file mode 100644
index 00000000000000..2c9e2825602483
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_vivintiger_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_base_financial_matryoshka_vivintiger_pipeline pipeline BGEEmbeddings from VivinTiger
+author: John Snow Labs
+name: bge_base_financial_matryoshka_vivintiger_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_vivintiger_pipeline` is a English model originally trained by VivinTiger.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_vivintiger_pipeline_en_5.5.1_3.0_1734564003730.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_vivintiger_pipeline_en_5.5.1_3.0_1734564003730.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_base_financial_matryoshka_vivintiger_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_base_financial_matryoshka_vivintiger_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_financial_matryoshka_vivintiger_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|387.1 MB|
+
+## References
+
+https://huggingface.co/VivinTiger/bge-base-financial-matryoshka
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_wu_tz_en.md b/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_wu_tz_en.md
new file mode 100644
index 00000000000000..832bde5317a53d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_wu_tz_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_base_financial_matryoshka_wu_tz BGEEmbeddings from wu-tz
+author: John Snow Labs
+name: bge_base_financial_matryoshka_wu_tz
+date: 2024-12-18
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_wu_tz` is a English model originally trained by wu-tz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_wu_tz_en_5.5.1_3.0_1734562479833.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_wu_tz_en_5.5.1_3.0_1734562479833.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_wu_tz","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_wu_tz","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_financial_matryoshka_wu_tz|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|256.0 MB|
+
+## References
+
+https://huggingface.co/wu-tz/bge-base-financial-matryoshka
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_wu_tz_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_wu_tz_pipeline_en.md
new file mode 100644
index 00000000000000..0cfa31881d0862
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-bge_base_financial_matryoshka_wu_tz_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_base_financial_matryoshka_wu_tz_pipeline pipeline BGEEmbeddings from wu-tz
+author: John Snow Labs
+name: bge_base_financial_matryoshka_wu_tz_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_wu_tz_pipeline` is a English model originally trained by wu-tz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_wu_tz_pipeline_en_5.5.1_3.0_1734562553460.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_wu_tz_pipeline_en_5.5.1_3.0_1734562553460.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_base_financial_matryoshka_wu_tz_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_base_financial_matryoshka_wu_tz_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_financial_matryoshka_wu_tz_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|256.0 MB|
+
+## References
+
+https://huggingface.co/wu-tz/bge-base-financial-matryoshka
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-bge_base_finetune_embedder_en.md b/docs/_posts/ahmedlone127/2024-12-18-bge_base_finetune_embedder_en.md
new file mode 100644
index 00000000000000..773c4622b59263
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-bge_base_finetune_embedder_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_base_finetune_embedder BGEEmbeddings from GenAIGirl
+author: John Snow Labs
+name: bge_base_finetune_embedder
+date: 2024-12-18
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_finetune_embedder` is a English model originally trained by GenAIGirl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_finetune_embedder_en_5.5.1_3.0_1734563694214.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_finetune_embedder_en_5.5.1_3.0_1734563694214.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_base_finetune_embedder","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_base_finetune_embedder","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_finetune_embedder|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|383.9 MB|
+
+## References
+
+https://huggingface.co/GenAIGirl/bge-base-finetune-embedder
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-bge_base_finetune_embedder_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-bge_base_finetune_embedder_pipeline_en.md
new file mode 100644
index 00000000000000..f630047eef5a45
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-bge_base_finetune_embedder_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_base_finetune_embedder_pipeline pipeline BGEEmbeddings from GenAIGirl
+author: John Snow Labs
+name: bge_base_finetune_embedder_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_finetune_embedder_pipeline` is a English model originally trained by GenAIGirl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_finetune_embedder_pipeline_en_5.5.1_3.0_1734563722149.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_finetune_embedder_pipeline_en_5.5.1_3.0_1734563722149.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_base_finetune_embedder_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_base_finetune_embedder_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_finetune_embedder_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|383.9 MB|
+
+## References
+
+https://huggingface.co/GenAIGirl/bge-base-finetune-embedder
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-bge_embedding_finetune_v2_en.md b/docs/_posts/ahmedlone127/2024-12-18-bge_embedding_finetune_v2_en.md
new file mode 100644
index 00000000000000..c3834461b3e086
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-bge_embedding_finetune_v2_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_embedding_finetune_v2 BGEEmbeddings from himanshu23099
+author: John Snow Labs
+name: bge_embedding_finetune_v2
+date: 2024-12-18
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_embedding_finetune_v2` is a English model originally trained by himanshu23099.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_embedding_finetune_v2_en_5.5.1_3.0_1734563192107.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_embedding_finetune_v2_en_5.5.1_3.0_1734563192107.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_embedding_finetune_v2","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_embedding_finetune_v2","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_embedding_finetune_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|116.4 MB|
+
+## References
+
+https://huggingface.co/himanshu23099/bge_embedding_finetune_v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-bge_embedding_finetune_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-bge_embedding_finetune_v2_pipeline_en.md
new file mode 100644
index 00000000000000..51aff3ed5733c7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-bge_embedding_finetune_v2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_embedding_finetune_v2_pipeline pipeline BGEEmbeddings from himanshu23099
+author: John Snow Labs
+name: bge_embedding_finetune_v2_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_embedding_finetune_v2_pipeline` is a English model originally trained by himanshu23099.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_embedding_finetune_v2_pipeline_en_5.5.1_3.0_1734563200283.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_embedding_finetune_v2_pipeline_en_5.5.1_3.0_1734563200283.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_embedding_finetune_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_embedding_finetune_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_embedding_finetune_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|116.4 MB|
+
+## References
+
+https://huggingface.co/himanshu23099/bge_embedding_finetune_v2
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-bge_large_mpnet_base_all_nli_triplet_final_en.md b/docs/_posts/ahmedlone127/2024-12-18-bge_large_mpnet_base_all_nli_triplet_final_en.md
new file mode 100644
index 00000000000000..609915e6bff8b6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-bge_large_mpnet_base_all_nli_triplet_final_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_large_mpnet_base_all_nli_triplet_final BGEEmbeddings from gavinqiangli
+author: John Snow Labs
+name: bge_large_mpnet_base_all_nli_triplet_final
+date: 2024-12-18
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_large_mpnet_base_all_nli_triplet_final` is a English model originally trained by gavinqiangli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_large_mpnet_base_all_nli_triplet_final_en_5.5.1_3.0_1734562742025.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_large_mpnet_base_all_nli_triplet_final_en_5.5.1_3.0_1734562742025.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_large_mpnet_base_all_nli_triplet_final","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_large_mpnet_base_all_nli_triplet_final","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_large_mpnet_base_all_nli_triplet_final|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/gavinqiangli/bge-large-mpnet-base-all-nli-triplet-final
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-bge_large_mpnet_base_all_nli_triplet_final_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-bge_large_mpnet_base_all_nli_triplet_final_pipeline_en.md
new file mode 100644
index 00000000000000..5955dc1daf30ad
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-bge_large_mpnet_base_all_nli_triplet_final_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_large_mpnet_base_all_nli_triplet_final_pipeline pipeline BGEEmbeddings from gavinqiangli
+author: John Snow Labs
+name: bge_large_mpnet_base_all_nli_triplet_final_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_large_mpnet_base_all_nli_triplet_final_pipeline` is a English model originally trained by gavinqiangli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_large_mpnet_base_all_nli_triplet_final_pipeline_en_5.5.1_3.0_1734562826835.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_large_mpnet_base_all_nli_triplet_final_pipeline_en_5.5.1_3.0_1734562826835.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_large_mpnet_base_all_nli_triplet_final_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_large_mpnet_base_all_nli_triplet_final_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_large_mpnet_base_all_nli_triplet_final_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/gavinqiangli/bge-large-mpnet-base-all-nli-triplet-final
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-bge_mnsr_en.md b/docs/_posts/ahmedlone127/2024-12-18-bge_mnsr_en.md
new file mode 100644
index 00000000000000..a318bd9c559c37
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-bge_mnsr_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_mnsr BGEEmbeddings from jebish7
+author: John Snow Labs
+name: bge_mnsr
+date: 2024-12-18
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_mnsr` is a English model originally trained by jebish7.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_mnsr_en_5.5.1_3.0_1734563476385.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_mnsr_en_5.5.1_3.0_1734563476385.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_mnsr","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_mnsr","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_mnsr|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|114.0 MB|
+
+## References
+
+https://huggingface.co/jebish7/bge_MNSR
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-bge_mnsr_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-bge_mnsr_pipeline_en.md
new file mode 100644
index 00000000000000..d42ade5869bc81
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-bge_mnsr_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_mnsr_pipeline pipeline BGEEmbeddings from jebish7
+author: John Snow Labs
+name: bge_mnsr_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_mnsr_pipeline` is a English model originally trained by jebish7.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_mnsr_pipeline_en_5.5.1_3.0_1734563485713.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_mnsr_pipeline_en_5.5.1_3.0_1734563485713.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_mnsr_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_mnsr_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_mnsr_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|114.0 MB|
+
+## References
+
+https://huggingface.co/jebish7/bge_MNSR
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-bge_pairs_en.md b/docs/_posts/ahmedlone127/2024-12-18-bge_pairs_en.md
new file mode 100644
index 00000000000000..fcac13a8dcbe16
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-bge_pairs_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_pairs BGEEmbeddings from smokxy
+author: John Snow Labs
+name: bge_pairs
+date: 2024-12-18
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_pairs` is a English model originally trained by smokxy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_pairs_en_5.5.1_3.0_1734563096313.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_pairs_en_5.5.1_3.0_1734563096313.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_pairs","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_pairs","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_pairs|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|116.1 MB|
+
+## References
+
+https://huggingface.co/smokxy/bge_pairs
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-bge_pairs_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-bge_pairs_pipeline_en.md
new file mode 100644
index 00000000000000..5c5cdadf2c52c7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-bge_pairs_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_pairs_pipeline pipeline BGEEmbeddings from smokxy
+author: John Snow Labs
+name: bge_pairs_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_pairs_pipeline` is a English model originally trained by smokxy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_pairs_pipeline_en_5.5.1_3.0_1734563104562.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_pairs_pipeline_en_5.5.1_3.0_1734563104562.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_pairs_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_pairs_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_pairs_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|116.1 MB|
+
+## References
+
+https://huggingface.co/smokxy/bge_pairs
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-bge_small_bioasq_1epoch_batch32_en.md b/docs/_posts/ahmedlone127/2024-12-18-bge_small_bioasq_1epoch_batch32_en.md
new file mode 100644
index 00000000000000..97b7b703741bd3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-bge_small_bioasq_1epoch_batch32_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_small_bioasq_1epoch_batch32 BGEEmbeddings from juanpablomesa
+author: John Snow Labs
+name: bge_small_bioasq_1epoch_batch32
+date: 2024-12-18
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_small_bioasq_1epoch_batch32` is a English model originally trained by juanpablomesa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_small_bioasq_1epoch_batch32_en_5.5.1_3.0_1734564025738.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_small_bioasq_1epoch_batch32_en_5.5.1_3.0_1734564025738.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_small_bioasq_1epoch_batch32","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_small_bioasq_1epoch_batch32","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_small_bioasq_1epoch_batch32|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|115.7 MB|
+
+## References
+
+https://huggingface.co/juanpablomesa/bge-small-bioasq-1epoch-batch32
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-bge_small_bioasq_1epoch_batch32_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-bge_small_bioasq_1epoch_batch32_pipeline_en.md
new file mode 100644
index 00000000000000..5351ed8adf6864
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-bge_small_bioasq_1epoch_batch32_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_small_bioasq_1epoch_batch32_pipeline pipeline BGEEmbeddings from juanpablomesa
+author: John Snow Labs
+name: bge_small_bioasq_1epoch_batch32_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_small_bioasq_1epoch_batch32_pipeline` is a English model originally trained by juanpablomesa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_small_bioasq_1epoch_batch32_pipeline_en_5.5.1_3.0_1734564034634.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_small_bioasq_1epoch_batch32_pipeline_en_5.5.1_3.0_1734564034634.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_small_bioasq_1epoch_batch32_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_small_bioasq_1epoch_batch32_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_small_bioasq_1epoch_batch32_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|115.7 MB|
+
+## References
+
+https://huggingface.co/juanpablomesa/bge-small-bioasq-1epoch-batch32
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-bge_small_english_v1_5_mnsr_15_en.md b/docs/_posts/ahmedlone127/2024-12-18-bge_small_english_v1_5_mnsr_15_en.md
new file mode 100644
index 00000000000000..910a051c691647
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-bge_small_english_v1_5_mnsr_15_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_small_english_v1_5_mnsr_15 BGEEmbeddings from jebish7
+author: John Snow Labs
+name: bge_small_english_v1_5_mnsr_15
+date: 2024-12-18
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_small_english_v1_5_mnsr_15` is a English model originally trained by jebish7.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_small_english_v1_5_mnsr_15_en_5.5.1_3.0_1734562925716.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_small_english_v1_5_mnsr_15_en_5.5.1_3.0_1734562925716.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_small_english_v1_5_mnsr_15","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_small_english_v1_5_mnsr_15","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_small_english_v1_5_mnsr_15|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|114.0 MB|
+
+## References
+
+https://huggingface.co/jebish7/bge-small-en-v1.5_MNSR_15
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-bge_small_english_v1_5_mnsr_15_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-bge_small_english_v1_5_mnsr_15_pipeline_en.md
new file mode 100644
index 00000000000000..2131569078565b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-bge_small_english_v1_5_mnsr_15_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_small_english_v1_5_mnsr_15_pipeline pipeline BGEEmbeddings from jebish7
+author: John Snow Labs
+name: bge_small_english_v1_5_mnsr_15_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_small_english_v1_5_mnsr_15_pipeline` is a English model originally trained by jebish7.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_small_english_v1_5_mnsr_15_pipeline_en_5.5.1_3.0_1734562935501.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_small_english_v1_5_mnsr_15_pipeline_en_5.5.1_3.0_1734562935501.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_small_english_v1_5_mnsr_15_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_small_english_v1_5_mnsr_15_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_small_english_v1_5_mnsr_15_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|114.0 MB|
+
+## References
+
+https://huggingface.co/jebish7/bge-small-en-v1.5_MNSR_15
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-bge_small_english_v1_5_mnsr_9_en.md b/docs/_posts/ahmedlone127/2024-12-18-bge_small_english_v1_5_mnsr_9_en.md
new file mode 100644
index 00000000000000..d5500e89573fa9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-bge_small_english_v1_5_mnsr_9_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_small_english_v1_5_mnsr_9 BGEEmbeddings from jebish7
+author: John Snow Labs
+name: bge_small_english_v1_5_mnsr_9
+date: 2024-12-18
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_small_english_v1_5_mnsr_9` is a English model originally trained by jebish7.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_small_english_v1_5_mnsr_9_en_5.5.1_3.0_1734564431193.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_small_english_v1_5_mnsr_9_en_5.5.1_3.0_1734564431193.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_small_english_v1_5_mnsr_9","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_small_english_v1_5_mnsr_9","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_small_english_v1_5_mnsr_9|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|114.0 MB|
+
+## References
+
+https://huggingface.co/jebish7/bge-small-en-v1.5_MNSR_9
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-bge_small_english_v1_5_mnsr_9_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-bge_small_english_v1_5_mnsr_9_pipeline_en.md
new file mode 100644
index 00000000000000..77328b38ebbdd2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-bge_small_english_v1_5_mnsr_9_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_small_english_v1_5_mnsr_9_pipeline pipeline BGEEmbeddings from jebish7
+author: John Snow Labs
+name: bge_small_english_v1_5_mnsr_9_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_small_english_v1_5_mnsr_9_pipeline` is a English model originally trained by jebish7.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_small_english_v1_5_mnsr_9_pipeline_en_5.5.1_3.0_1734564440823.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_small_english_v1_5_mnsr_9_pipeline_en_5.5.1_3.0_1734564440823.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_small_english_v1_5_mnsr_9_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_small_english_v1_5_mnsr_9_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_small_english_v1_5_mnsr_9_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|114.0 MB|
+
+## References
+
+https://huggingface.co/jebish7/bge-small-en-v1.5_MNSR_9
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-burmese_awesome_opus_books_model_cotysong113_en.md b/docs/_posts/ahmedlone127/2024-12-18-burmese_awesome_opus_books_model_cotysong113_en.md
new file mode 100644
index 00000000000000..e9e67567485013
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-burmese_awesome_opus_books_model_cotysong113_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_opus_books_model_cotysong113 T5Transformer from cotysong113
+author: John Snow Labs
+name: burmese_awesome_opus_books_model_cotysong113
+date: 2024-12-18
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_opus_books_model_cotysong113` is a English model originally trained by cotysong113.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_cotysong113_en_5.5.1_3.0_1734566087582.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_cotysong113_en_5.5.1_3.0_1734566087582.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("burmese_awesome_opus_books_model_cotysong113","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("burmese_awesome_opus_books_model_cotysong113", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_opus_books_model_cotysong113|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|282.2 MB|
+
+## References
+
+https://huggingface.co/cotysong113/my_awesome_opus_books_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-burmese_awesome_opus_books_model_cotysong113_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-burmese_awesome_opus_books_model_cotysong113_pipeline_en.md
new file mode 100644
index 00000000000000..0f2747761f1f70
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-burmese_awesome_opus_books_model_cotysong113_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_opus_books_model_cotysong113_pipeline pipeline T5Transformer from cotysong113
+author: John Snow Labs
+name: burmese_awesome_opus_books_model_cotysong113_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_opus_books_model_cotysong113_pipeline` is a English model originally trained by cotysong113.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_cotysong113_pipeline_en_5.5.1_3.0_1734566104051.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_cotysong113_pipeline_en_5.5.1_3.0_1734566104051.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_opus_books_model_cotysong113_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_opus_books_model_cotysong113_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_opus_books_model_cotysong113_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|282.2 MB|
+
+## References
+
+https://huggingface.co/cotysong113/my_awesome_opus_books_model
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-burmese_awesome_opus_books_model_maydogdu_en.md b/docs/_posts/ahmedlone127/2024-12-18-burmese_awesome_opus_books_model_maydogdu_en.md
new file mode 100644
index 00000000000000..e4d0bbfbdd711c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-burmese_awesome_opus_books_model_maydogdu_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_opus_books_model_maydogdu T5Transformer from maydogdu
+author: John Snow Labs
+name: burmese_awesome_opus_books_model_maydogdu
+date: 2024-12-18
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_opus_books_model_maydogdu` is a English model originally trained by maydogdu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_maydogdu_en_5.5.1_3.0_1734565889359.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_maydogdu_en_5.5.1_3.0_1734565889359.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("burmese_awesome_opus_books_model_maydogdu","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("burmese_awesome_opus_books_model_maydogdu", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_opus_books_model_maydogdu|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|148.0 MB|
+
+## References
+
+https://huggingface.co/maydogdu/my_awesome_opus_books_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-burmese_awesome_opus_books_model_maydogdu_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-burmese_awesome_opus_books_model_maydogdu_pipeline_en.md
new file mode 100644
index 00000000000000..f00950108d9880
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-burmese_awesome_opus_books_model_maydogdu_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_opus_books_model_maydogdu_pipeline pipeline T5Transformer from maydogdu
+author: John Snow Labs
+name: burmese_awesome_opus_books_model_maydogdu_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_opus_books_model_maydogdu_pipeline` is a English model originally trained by maydogdu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_maydogdu_pipeline_en_5.5.1_3.0_1734565938445.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_maydogdu_pipeline_en_5.5.1_3.0_1734565938445.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_opus_books_model_maydogdu_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_opus_books_model_maydogdu_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_opus_books_model_maydogdu_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|148.0 MB|
+
+## References
+
+https://huggingface.co/maydogdu/my_awesome_opus_books_model
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-deberta_base_en.md b/docs/_posts/ahmedlone127/2024-12-18-deberta_base_en.md
new file mode 100644
index 00000000000000..a88e0ab79b0377
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-deberta_base_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_base DeBertaForSequenceClassification from binh230
+author: John Snow Labs
+name: deberta_base
+date: 2024-12-18
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_base` is a English model originally trained by binh230.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_base_en_5.5.1_3.0_1734560707096.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_base_en_5.5.1_3.0_1734560707096.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_base","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_base", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_base|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|665.9 MB|
+
+## References
+
+https://huggingface.co/binh230/deberta-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-deberta_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-deberta_base_pipeline_en.md
new file mode 100644
index 00000000000000..cc4850e255cd2b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-deberta_base_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_base_pipeline pipeline DeBertaForSequenceClassification from binh230
+author: John Snow Labs
+name: deberta_base_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_base_pipeline` is a English model originally trained by binh230.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_base_pipeline_en_5.5.1_3.0_1734560743848.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_base_pipeline_en_5.5.1_3.0_1734560743848.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|665.9 MB|
+
+## References
+
+https://huggingface.co/binh230/deberta-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-deberta_reward_model_en.md b/docs/_posts/ahmedlone127/2024-12-18-deberta_reward_model_en.md
new file mode 100644
index 00000000000000..9e91eb511bcfb5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-deberta_reward_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_reward_model DeBertaForSequenceClassification from cheonkamjeong
+author: John Snow Labs
+name: deberta_reward_model
+date: 2024-12-18
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_reward_model` is a English model originally trained by cheonkamjeong.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_reward_model_en_5.5.1_3.0_1734560760534.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_reward_model_en_5.5.1_3.0_1734560760534.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_reward_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_reward_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_reward_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/cheonkamjeong/deberta-reward-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-deberta_reward_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-deberta_reward_model_pipeline_en.md
new file mode 100644
index 00000000000000..cd6749eedf53b2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-deberta_reward_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_reward_model_pipeline pipeline DeBertaForSequenceClassification from cheonkamjeong
+author: John Snow Labs
+name: deberta_reward_model_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_reward_model_pipeline` is a English model originally trained by cheonkamjeong.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_reward_model_pipeline_en_5.5.1_3.0_1734560903334.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_reward_model_pipeline_en_5.5.1_3.0_1734560903334.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_reward_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_reward_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_reward_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/cheonkamjeong/deberta-reward-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-deberta_v3_base_3epoch_en.md b/docs/_posts/ahmedlone127/2024-12-18-deberta_v3_base_3epoch_en.md
new file mode 100644
index 00000000000000..b7019f9dd63e65
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-deberta_v3_base_3epoch_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_base_3epoch DeBertaForSequenceClassification from dianamihalache27
+author: John Snow Labs
+name: deberta_v3_base_3epoch
+date: 2024-12-18
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_3epoch` is a English model originally trained by dianamihalache27.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_3epoch_en_5.5.1_3.0_1734560827375.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_3epoch_en_5.5.1_3.0_1734560827375.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_base_3epoch","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_3epoch", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_3epoch|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|567.4 MB|
+
+## References
+
+https://huggingface.co/dianamihalache27/deberta-v3-base_3epoch
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-deberta_v3_base_3epoch_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-deberta_v3_base_3epoch_pipeline_en.md
new file mode 100644
index 00000000000000..455b9fdef39d3b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-deberta_v3_base_3epoch_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_base_3epoch_pipeline pipeline DeBertaForSequenceClassification from dianamihalache27
+author: John Snow Labs
+name: deberta_v3_base_3epoch_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_3epoch_pipeline` is a English model originally trained by dianamihalache27.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_3epoch_pipeline_en_5.5.1_3.0_1734560905203.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_3epoch_pipeline_en_5.5.1_3.0_1734560905203.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_base_3epoch_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_base_3epoch_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_3epoch_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|567.4 MB|
+
+## References
+
+https://huggingface.co/dianamihalache27/deberta-v3-base_3epoch
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-deberta_v3_base_quality_v2_en.md b/docs/_posts/ahmedlone127/2024-12-18-deberta_v3_base_quality_v2_en.md
new file mode 100644
index 00000000000000..e406f1e7d6acef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-deberta_v3_base_quality_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_base_quality_v2 DeBertaForSequenceClassification from agentlans
+author: John Snow Labs
+name: deberta_v3_base_quality_v2
+date: 2024-12-18
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_quality_v2` is a English model originally trained by agentlans.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_quality_v2_en_5.5.1_3.0_1734560274082.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_quality_v2_en_5.5.1_3.0_1734560274082.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_base_quality_v2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_quality_v2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_quality_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|646.6 MB|
+
+## References
+
+https://huggingface.co/agentlans/deberta-v3-base-quality-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-deberta_v3_base_quality_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-deberta_v3_base_quality_v2_pipeline_en.md
new file mode 100644
index 00000000000000..09d9c00a1c7993
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-deberta_v3_base_quality_v2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_base_quality_v2_pipeline pipeline DeBertaForSequenceClassification from agentlans
+author: John Snow Labs
+name: deberta_v3_base_quality_v2_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_quality_v2_pipeline` is a English model originally trained by agentlans.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_quality_v2_pipeline_en_5.5.1_3.0_1734560319064.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_quality_v2_pipeline_en_5.5.1_3.0_1734560319064.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_base_quality_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_base_quality_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_quality_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|646.7 MB|
+
+## References
+
+https://huggingface.co/agentlans/deberta-v3-base-quality-v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-deberta_v3_base_readability_v2_en.md b/docs/_posts/ahmedlone127/2024-12-18-deberta_v3_base_readability_v2_en.md
new file mode 100644
index 00000000000000..7c989aa687ab2f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-deberta_v3_base_readability_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_base_readability_v2 DeBertaForSequenceClassification from agentlans
+author: John Snow Labs
+name: deberta_v3_base_readability_v2
+date: 2024-12-18
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_readability_v2` is a English model originally trained by agentlans.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_readability_v2_en_5.5.1_3.0_1734560158782.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_readability_v2_en_5.5.1_3.0_1734560158782.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_base_readability_v2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_readability_v2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_readability_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|676.0 MB|
+
+## References
+
+https://huggingface.co/agentlans/deberta-v3-base-readability-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-deberta_v3_base_readability_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-deberta_v3_base_readability_v2_pipeline_en.md
new file mode 100644
index 00000000000000..508323e126fc71
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-deberta_v3_base_readability_v2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_base_readability_v2_pipeline pipeline DeBertaForSequenceClassification from agentlans
+author: John Snow Labs
+name: deberta_v3_base_readability_v2_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_readability_v2_pipeline` is a English model originally trained by agentlans.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_readability_v2_pipeline_en_5.5.1_3.0_1734560197405.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_readability_v2_pipeline_en_5.5.1_3.0_1734560197405.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_base_readability_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_base_readability_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_readability_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|676.0 MB|
+
+## References
+
+https://huggingface.co/agentlans/deberta-v3-base-readability-v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-deberta_v3_xsmall_qnli_en.md b/docs/_posts/ahmedlone127/2024-12-18-deberta_v3_xsmall_qnli_en.md
new file mode 100644
index 00000000000000..45b32487b09e93
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-deberta_v3_xsmall_qnli_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_xsmall_qnli DeBertaForSequenceClassification from cliang1453
+author: John Snow Labs
+name: deberta_v3_xsmall_qnli
+date: 2024-12-18
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_xsmall_qnli` is a English model originally trained by cliang1453.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_qnli_en_5.5.1_3.0_1734561404338.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_qnli_en_5.5.1_3.0_1734561404338.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_xsmall_qnli","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_xsmall_qnli", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_xsmall_qnli|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|239.7 MB|
+
+## References
+
+https://huggingface.co/cliang1453/deberta-v3-xsmall-qnli
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-deberta_v3_xsmall_qnli_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-deberta_v3_xsmall_qnli_pipeline_en.md
new file mode 100644
index 00000000000000..b9ec8e8b7ceee6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-deberta_v3_xsmall_qnli_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_xsmall_qnli_pipeline pipeline DeBertaForSequenceClassification from cliang1453
+author: John Snow Labs
+name: deberta_v3_xsmall_qnli_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_xsmall_qnli_pipeline` is a English model originally trained by cliang1453.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_qnli_pipeline_en_5.5.1_3.0_1734561427974.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_qnli_pipeline_en_5.5.1_3.0_1734561427974.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_xsmall_qnli_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_xsmall_qnli_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_xsmall_qnli_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|239.8 MB|
+
+## References
+
+https://huggingface.co/cliang1453/deberta-v3-xsmall-qnli
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-deberta_v3_xsmall_qqp_en.md b/docs/_posts/ahmedlone127/2024-12-18-deberta_v3_xsmall_qqp_en.md
new file mode 100644
index 00000000000000..f6f34954884260
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-deberta_v3_xsmall_qqp_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_xsmall_qqp DeBertaForSequenceClassification from cliang1453
+author: John Snow Labs
+name: deberta_v3_xsmall_qqp
+date: 2024-12-18
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_xsmall_qqp` is a English model originally trained by cliang1453.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_qqp_en_5.5.1_3.0_1734560230537.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_qqp_en_5.5.1_3.0_1734560230537.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_xsmall_qqp","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_xsmall_qqp", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_xsmall_qqp|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|245.2 MB|
+
+## References
+
+https://huggingface.co/cliang1453/deberta-v3-xsmall-qqp
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-deberta_v3_xsmall_qqp_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-deberta_v3_xsmall_qqp_pipeline_en.md
new file mode 100644
index 00000000000000..b924373eb281c7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-deberta_v3_xsmall_qqp_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_xsmall_qqp_pipeline pipeline DeBertaForSequenceClassification from cliang1453
+author: John Snow Labs
+name: deberta_v3_xsmall_qqp_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_xsmall_qqp_pipeline` is a English model originally trained by cliang1453.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_qqp_pipeline_en_5.5.1_3.0_1734560250832.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_qqp_pipeline_en_5.5.1_3.0_1734560250832.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_xsmall_qqp_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_xsmall_qqp_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_xsmall_qqp_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|245.2 MB|
+
+## References
+
+https://huggingface.co/cliang1453/deberta-v3-xsmall-qqp
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-deberta_v3_xsmall_tweet_sentiment_en.md b/docs/_posts/ahmedlone127/2024-12-18-deberta_v3_xsmall_tweet_sentiment_en.md
new file mode 100644
index 00000000000000..f5cf2a8b4cf867
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-deberta_v3_xsmall_tweet_sentiment_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_xsmall_tweet_sentiment DeBertaForSequenceClassification from agentlans
+author: John Snow Labs
+name: deberta_v3_xsmall_tweet_sentiment
+date: 2024-12-18
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_xsmall_tweet_sentiment` is a English model originally trained by agentlans.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_tweet_sentiment_en_5.5.1_3.0_1734560882670.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_tweet_sentiment_en_5.5.1_3.0_1734560882670.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_xsmall_tweet_sentiment","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_xsmall_tweet_sentiment", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_xsmall_tweet_sentiment|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|236.0 MB|
+
+## References
+
+https://huggingface.co/agentlans/deberta-v3-xsmall-tweet-sentiment
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-deberta_v3_xsmall_tweet_sentiment_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-deberta_v3_xsmall_tweet_sentiment_pipeline_en.md
new file mode 100644
index 00000000000000..c75556033bf988
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-deberta_v3_xsmall_tweet_sentiment_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_xsmall_tweet_sentiment_pipeline pipeline DeBertaForSequenceClassification from agentlans
+author: John Snow Labs
+name: deberta_v3_xsmall_tweet_sentiment_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_xsmall_tweet_sentiment_pipeline` is a English model originally trained by agentlans.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_tweet_sentiment_pipeline_en_5.5.1_3.0_1734560903282.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_tweet_sentiment_pipeline_en_5.5.1_3.0_1734560903282.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_xsmall_tweet_sentiment_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_xsmall_tweet_sentiment_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_xsmall_tweet_sentiment_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|236.0 MB|
+
+## References
+
+https://huggingface.co/agentlans/deberta-v3-xsmall-tweet-sentiment
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-debertav3large_ft_pref_1000_en.md b/docs/_posts/ahmedlone127/2024-12-18-debertav3large_ft_pref_1000_en.md
new file mode 100644
index 00000000000000..05c3a9984c1797
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-debertav3large_ft_pref_1000_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English debertav3large_ft_pref_1000 DeBertaForSequenceClassification from SeppeV
+author: John Snow Labs
+name: debertav3large_ft_pref_1000
+date: 2024-12-18
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`debertav3large_ft_pref_1000` is a English model originally trained by SeppeV.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/debertav3large_ft_pref_1000_en_5.5.1_3.0_1734561830506.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/debertav3large_ft_pref_1000_en_5.5.1_3.0_1734561830506.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("debertav3large_ft_pref_1000","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("debertav3large_ft_pref_1000", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|debertav3large_ft_pref_1000|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/SeppeV/debertav3large_ft_pref_1000
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-debertav3large_ft_pref_1000_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-debertav3large_ft_pref_1000_pipeline_en.md
new file mode 100644
index 00000000000000..74acb23f42b86d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-debertav3large_ft_pref_1000_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English debertav3large_ft_pref_1000_pipeline pipeline DeBertaForSequenceClassification from SeppeV
+author: John Snow Labs
+name: debertav3large_ft_pref_1000_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`debertav3large_ft_pref_1000_pipeline` is a English model originally trained by SeppeV.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/debertav3large_ft_pref_1000_pipeline_en_5.5.1_3.0_1734561972074.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/debertav3large_ft_pref_1000_pipeline_en_5.5.1_3.0_1734561972074.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("debertav3large_ft_pref_1000_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("debertav3large_ft_pref_1000_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|debertav3large_ft_pref_1000_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/SeppeV/debertav3large_ft_pref_1000
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-dutch_query_w_context2json_filter_en.md b/docs/_posts/ahmedlone127/2024-12-18-dutch_query_w_context2json_filter_en.md
new file mode 100644
index 00000000000000..0b432d490ca767
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-dutch_query_w_context2json_filter_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English dutch_query_w_context2json_filter T5Transformer from mezanass
+author: John Snow Labs
+name: dutch_query_w_context2json_filter
+date: 2024-12-18
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dutch_query_w_context2json_filter` is a English model originally trained by mezanass.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dutch_query_w_context2json_filter_en_5.5.1_3.0_1734565889217.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dutch_query_w_context2json_filter_en_5.5.1_3.0_1734565889217.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("dutch_query_w_context2json_filter","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("dutch_query_w_context2json_filter", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dutch_query_w_context2json_filter|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|147.8 MB|
+
+## References
+
+https://huggingface.co/mezanass/nl_query_w_context2json_filter
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-dutch_query_w_context2json_filter_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-dutch_query_w_context2json_filter_pipeline_en.md
new file mode 100644
index 00000000000000..8aac59b3a6ccf6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-dutch_query_w_context2json_filter_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English dutch_query_w_context2json_filter_pipeline pipeline T5Transformer from mezanass
+author: John Snow Labs
+name: dutch_query_w_context2json_filter_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dutch_query_w_context2json_filter_pipeline` is a English model originally trained by mezanass.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dutch_query_w_context2json_filter_pipeline_en_5.5.1_3.0_1734565936909.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dutch_query_w_context2json_filter_pipeline_en_5.5.1_3.0_1734565936909.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dutch_query_w_context2json_filter_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dutch_query_w_context2json_filter_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dutch_query_w_context2json_filter_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|147.8 MB|
+
+## References
+
+https://huggingface.co/mezanass/nl_query_w_context2json_filter
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-fine_tuned_t5_small_model_abhimanyu9539_en.md b/docs/_posts/ahmedlone127/2024-12-18-fine_tuned_t5_small_model_abhimanyu9539_en.md
new file mode 100644
index 00000000000000..3dc51b19a1db59
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-fine_tuned_t5_small_model_abhimanyu9539_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English fine_tuned_t5_small_model_abhimanyu9539 T5Transformer from Abhimanyu9539
+author: John Snow Labs
+name: fine_tuned_t5_small_model_abhimanyu9539
+date: 2024-12-18
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_t5_small_model_abhimanyu9539` is a English model originally trained by Abhimanyu9539.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_small_model_abhimanyu9539_en_5.5.1_3.0_1734566074539.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_small_model_abhimanyu9539_en_5.5.1_3.0_1734566074539.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("fine_tuned_t5_small_model_abhimanyu9539","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("fine_tuned_t5_small_model_abhimanyu9539", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_t5_small_model_abhimanyu9539|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|266.1 MB|
+
+## References
+
+https://huggingface.co/Abhimanyu9539/fine_tuned_t5_small_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-fine_tuned_t5_small_model_abhimanyu9539_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-fine_tuned_t5_small_model_abhimanyu9539_pipeline_en.md
new file mode 100644
index 00000000000000..8b741b16da0ae4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-fine_tuned_t5_small_model_abhimanyu9539_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English fine_tuned_t5_small_model_abhimanyu9539_pipeline pipeline T5Transformer from Abhimanyu9539
+author: John Snow Labs
+name: fine_tuned_t5_small_model_abhimanyu9539_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_t5_small_model_abhimanyu9539_pipeline` is a English model originally trained by Abhimanyu9539.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_small_model_abhimanyu9539_pipeline_en_5.5.1_3.0_1734566094332.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_small_model_abhimanyu9539_pipeline_en_5.5.1_3.0_1734566094332.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fine_tuned_t5_small_model_abhimanyu9539_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fine_tuned_t5_small_model_abhimanyu9539_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_t5_small_model_abhimanyu9539_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|266.1 MB|
+
+## References
+
+https://huggingface.co/Abhimanyu9539/fine_tuned_t5_small_model
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-fine_tuned_t5_small_model_sec_5_v7_en.md b/docs/_posts/ahmedlone127/2024-12-18-fine_tuned_t5_small_model_sec_5_v7_en.md
new file mode 100644
index 00000000000000..7bfdf68363d59e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-fine_tuned_t5_small_model_sec_5_v7_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English fine_tuned_t5_small_model_sec_5_v7 T5Transformer from miasetya
+author: John Snow Labs
+name: fine_tuned_t5_small_model_sec_5_v7
+date: 2024-12-18
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_t5_small_model_sec_5_v7` is a English model originally trained by miasetya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_small_model_sec_5_v7_en_5.5.1_3.0_1734565945052.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_small_model_sec_5_v7_en_5.5.1_3.0_1734565945052.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("fine_tuned_t5_small_model_sec_5_v7","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("fine_tuned_t5_small_model_sec_5_v7", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_t5_small_model_sec_5_v7|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|265.9 MB|
+
+## References
+
+https://huggingface.co/miasetya/fine_tuned_t5_small_model_sec_5_v7
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-fine_tuned_t5_small_model_sec_5_v7_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-fine_tuned_t5_small_model_sec_5_v7_pipeline_en.md
new file mode 100644
index 00000000000000..2b874ec27cbc1b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-fine_tuned_t5_small_model_sec_5_v7_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English fine_tuned_t5_small_model_sec_5_v7_pipeline pipeline T5Transformer from miasetya
+author: John Snow Labs
+name: fine_tuned_t5_small_model_sec_5_v7_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_t5_small_model_sec_5_v7_pipeline` is a English model originally trained by miasetya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_small_model_sec_5_v7_pipeline_en_5.5.1_3.0_1734565963672.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_small_model_sec_5_v7_pipeline_en_5.5.1_3.0_1734565963672.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fine_tuned_t5_small_model_sec_5_v7_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fine_tuned_t5_small_model_sec_5_v7_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_t5_small_model_sec_5_v7_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|265.9 MB|
+
+## References
+
+https://huggingface.co/miasetya/fine_tuned_t5_small_model_sec_5_v7
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-finetuned_bge_bai_en.md b/docs/_posts/ahmedlone127/2024-12-18-finetuned_bge_bai_en.md
new file mode 100644
index 00000000000000..2e4266e95a9463
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-finetuned_bge_bai_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English finetuned_bge_bai BGEEmbeddings from ivanleomk
+author: John Snow Labs
+name: finetuned_bge_bai
+date: 2024-12-18
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_bge_bai` is a English model originally trained by ivanleomk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_bge_bai_en_5.5.1_3.0_1734563397214.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_bge_bai_en_5.5.1_3.0_1734563397214.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("finetuned_bge_bai","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("finetuned_bge_bai","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_bge_bai|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|375.2 MB|
+
+## References
+
+https://huggingface.co/ivanleomk/finetuned-bge-bai
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-finetuned_bge_bai_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-finetuned_bge_bai_pipeline_en.md
new file mode 100644
index 00000000000000..b905f5621d3ed2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-finetuned_bge_bai_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English finetuned_bge_bai_pipeline pipeline BGEEmbeddings from ivanleomk
+author: John Snow Labs
+name: finetuned_bge_bai_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_bge_bai_pipeline` is a English model originally trained by ivanleomk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_bge_bai_pipeline_en_5.5.1_3.0_1734563428134.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_bge_bai_pipeline_en_5.5.1_3.0_1734563428134.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuned_bge_bai_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuned_bge_bai_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_bge_bai_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|375.2 MB|
+
+## References
+
+https://huggingface.co/ivanleomk/finetuned-bge-bai
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-flan_t5_base_finetuned_juliatsk_en.md b/docs/_posts/ahmedlone127/2024-12-18-flan_t5_base_finetuned_juliatsk_en.md
new file mode 100644
index 00000000000000..c796e7e820a0ec
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-flan_t5_base_finetuned_juliatsk_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English flan_t5_base_finetuned_juliatsk T5Transformer from JuliaTsk
+author: John Snow Labs
+name: flan_t5_base_finetuned_juliatsk
+date: 2024-12-18
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_base_finetuned_juliatsk` is a English model originally trained by JuliaTsk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_base_finetuned_juliatsk_en_5.5.1_3.0_1734566180602.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_base_finetuned_juliatsk_en_5.5.1_3.0_1734566180602.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("flan_t5_base_finetuned_juliatsk","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("flan_t5_base_finetuned_juliatsk", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_base_finetuned_juliatsk|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/JuliaTsk/flan-t5-base-finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-flan_t5_base_finetuned_juliatsk_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-flan_t5_base_finetuned_juliatsk_pipeline_en.md
new file mode 100644
index 00000000000000..5608703f130aec
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-flan_t5_base_finetuned_juliatsk_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English flan_t5_base_finetuned_juliatsk_pipeline pipeline T5Transformer from JuliaTsk
+author: John Snow Labs
+name: flan_t5_base_finetuned_juliatsk_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_base_finetuned_juliatsk_pipeline` is a English model originally trained by JuliaTsk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_base_finetuned_juliatsk_pipeline_en_5.5.1_3.0_1734566232579.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_base_finetuned_juliatsk_pipeline_en_5.5.1_3.0_1734566232579.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("flan_t5_base_finetuned_juliatsk_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("flan_t5_base_finetuned_juliatsk_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_base_finetuned_juliatsk_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/JuliaTsk/flan-t5-base-finetuned
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-indonesian_bge_small_en.md b/docs/_posts/ahmedlone127/2024-12-18-indonesian_bge_small_en.md
new file mode 100644
index 00000000000000..334f33b8a098af
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-indonesian_bge_small_en.md
@@ -0,0 +1,89 @@
+---
+layout: model
+title: English indonesian_bge_small BGEEmbeddings from ingtech
+author: John Snow Labs
+name: indonesian_bge_small
+date: 2024-12-18
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indonesian_bge_small` is a English model originally trained by ingtech.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indonesian_bge_small_en_5.5.1_3.0_1734562379443.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indonesian_bge_small_en_5.5.1_3.0_1734562379443.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("indonesian_bge_small","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("indonesian_bge_small","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|indonesian_bge_small|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|117.1 MB|
+
+## References
+
+References
+
+https://huggingface.co/ingtech/indonesian-bge-small
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-indonesian_bge_small_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-indonesian_bge_small_pipeline_en.md
new file mode 100644
index 00000000000000..5d1810ed53b950
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-indonesian_bge_small_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English indonesian_bge_small_pipeline pipeline BGEEmbeddings from ingtech
+author: John Snow Labs
+name: indonesian_bge_small_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indonesian_bge_small_pipeline` is a English model originally trained by ingtech.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indonesian_bge_small_pipeline_en_5.5.1_3.0_1734562388032.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indonesian_bge_small_pipeline_en_5.5.1_3.0_1734562388032.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("indonesian_bge_small_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("indonesian_bge_small_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|indonesian_bge_small_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|117.1 MB|
+
+## References
+
+References
+
+https://huggingface.co/ingtech/indonesian-bge-small
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-joejoinerr_en.md b/docs/_posts/ahmedlone127/2024-12-18-joejoinerr_en.md
new file mode 100644
index 00000000000000..86234caf5bd380
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-joejoinerr_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English joejoinerr GPT2Transformer from huggingtweets
+author: John Snow Labs
+name: joejoinerr
+date: 2024-12-18
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`joejoinerr` is a English model originally trained by huggingtweets.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/joejoinerr_en_5.5.1_3.0_1734559307422.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/joejoinerr_en_5.5.1_3.0_1734559307422.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("joejoinerr","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("joejoinerr","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|joejoinerr|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/huggingtweets/joejoinerr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-joejoinerr_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-joejoinerr_pipeline_en.md
new file mode 100644
index 00000000000000..c766441a1e436f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-joejoinerr_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English joejoinerr_pipeline pipeline GPT2Transformer from huggingtweets
+author: John Snow Labs
+name: joejoinerr_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`joejoinerr_pipeline` is a English model originally trained by huggingtweets.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/joejoinerr_pipeline_en_5.5.1_3.0_1734559331080.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/joejoinerr_pipeline_en_5.5.1_3.0_1734559331080.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("joejoinerr_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("joejoinerr_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|joejoinerr_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/huggingtweets/joejoinerr
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-judge_answer___29_deberta_v3_base_msmarco_answerability_en.md b/docs/_posts/ahmedlone127/2024-12-18-judge_answer___29_deberta_v3_base_msmarco_answerability_en.md
new file mode 100644
index 00000000000000..3ea17b1dc56006
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-judge_answer___29_deberta_v3_base_msmarco_answerability_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English judge_answer___29_deberta_v3_base_msmarco_answerability DeBertaForSequenceClassification from tom-010
+author: John Snow Labs
+name: judge_answer___29_deberta_v3_base_msmarco_answerability
+date: 2024-12-18
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`judge_answer___29_deberta_v3_base_msmarco_answerability` is a English model originally trained by tom-010.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/judge_answer___29_deberta_v3_base_msmarco_answerability_en_5.5.1_3.0_1734561400710.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/judge_answer___29_deberta_v3_base_msmarco_answerability_en_5.5.1_3.0_1734561400710.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("judge_answer___29_deberta_v3_base_msmarco_answerability","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("judge_answer___29_deberta_v3_base_msmarco_answerability", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|judge_answer___29_deberta_v3_base_msmarco_answerability|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|687.7 MB|
+
+## References
+
+https://huggingface.co/tom-010/judge_answer___29_deberta_v3_base_msmarco_answerability
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-judge_answer___29_deberta_v3_base_msmarco_answerability_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-judge_answer___29_deberta_v3_base_msmarco_answerability_pipeline_en.md
new file mode 100644
index 00000000000000..a0ddd04c93ddf8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-judge_answer___29_deberta_v3_base_msmarco_answerability_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English judge_answer___29_deberta_v3_base_msmarco_answerability_pipeline pipeline DeBertaForSequenceClassification from tom-010
+author: John Snow Labs
+name: judge_answer___29_deberta_v3_base_msmarco_answerability_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`judge_answer___29_deberta_v3_base_msmarco_answerability_pipeline` is a English model originally trained by tom-010.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/judge_answer___29_deberta_v3_base_msmarco_answerability_pipeline_en_5.5.1_3.0_1734561438333.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/judge_answer___29_deberta_v3_base_msmarco_answerability_pipeline_en_5.5.1_3.0_1734561438333.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("judge_answer___29_deberta_v3_base_msmarco_answerability_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("judge_answer___29_deberta_v3_base_msmarco_answerability_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|judge_answer___29_deberta_v3_base_msmarco_answerability_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|687.7 MB|
+
+## References
+
+https://huggingface.co/tom-010/judge_answer___29_deberta_v3_base_msmarco_answerability
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-mdeberta_v3_base_autext2024_06_12_2024_detection_en.md b/docs/_posts/ahmedlone127/2024-12-18-mdeberta_v3_base_autext2024_06_12_2024_detection_en.md
new file mode 100644
index 00000000000000..b3bb7057652ce3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-mdeberta_v3_base_autext2024_06_12_2024_detection_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mdeberta_v3_base_autext2024_06_12_2024_detection DeBertaForSequenceClassification from jorgefg03
+author: John Snow Labs
+name: mdeberta_v3_base_autext2024_06_12_2024_detection
+date: 2024-12-18
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_autext2024_06_12_2024_detection` is a English model originally trained by jorgefg03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_autext2024_06_12_2024_detection_en_5.5.1_3.0_1734561308619.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_autext2024_06_12_2024_detection_en_5.5.1_3.0_1734561308619.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_autext2024_06_12_2024_detection","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_autext2024_06_12_2024_detection", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_autext2024_06_12_2024_detection|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|871.1 MB|
+
+## References
+
+https://huggingface.co/jorgefg03/mdeberta-v3-base-autext2024_06-12-2024_detection
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-mdeberta_v3_base_autext2024_06_12_2024_detection_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-mdeberta_v3_base_autext2024_06_12_2024_detection_pipeline_en.md
new file mode 100644
index 00000000000000..a609f5be6621ba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-mdeberta_v3_base_autext2024_06_12_2024_detection_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mdeberta_v3_base_autext2024_06_12_2024_detection_pipeline pipeline DeBertaForSequenceClassification from jorgefg03
+author: John Snow Labs
+name: mdeberta_v3_base_autext2024_06_12_2024_detection_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_autext2024_06_12_2024_detection_pipeline` is a English model originally trained by jorgefg03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_autext2024_06_12_2024_detection_pipeline_en_5.5.1_3.0_1734561419052.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_autext2024_06_12_2024_detection_pipeline_en_5.5.1_3.0_1734561419052.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mdeberta_v3_base_autext2024_06_12_2024_detection_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mdeberta_v3_base_autext2024_06_12_2024_detection_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_autext2024_06_12_2024_detection_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|871.1 MB|
+
+## References
+
+https://huggingface.co/jorgefg03/mdeberta-v3-base-autext2024_06-12-2024_detection
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-mdeberta_v3_base_autext2024_isegura_en.md b/docs/_posts/ahmedlone127/2024-12-18-mdeberta_v3_base_autext2024_isegura_en.md
new file mode 100644
index 00000000000000..c9f83f00241021
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-mdeberta_v3_base_autext2024_isegura_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mdeberta_v3_base_autext2024_isegura DeBertaForSequenceClassification from ISEGURA
+author: John Snow Labs
+name: mdeberta_v3_base_autext2024_isegura
+date: 2024-12-18
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_autext2024_isegura` is a English model originally trained by ISEGURA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_autext2024_isegura_en_5.5.1_3.0_1734560645825.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_autext2024_isegura_en_5.5.1_3.0_1734560645825.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_autext2024_isegura","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_autext2024_isegura", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_autext2024_isegura|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|878.9 MB|
+
+## References
+
+https://huggingface.co/ISEGURA/mdeberta-v3-base-autext2024
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-mdeberta_v3_base_autext2024_isegura_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-mdeberta_v3_base_autext2024_isegura_pipeline_en.md
new file mode 100644
index 00000000000000..a115f99cdf9255
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-mdeberta_v3_base_autext2024_isegura_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mdeberta_v3_base_autext2024_isegura_pipeline pipeline DeBertaForSequenceClassification from ISEGURA
+author: John Snow Labs
+name: mdeberta_v3_base_autext2024_isegura_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_autext2024_isegura_pipeline` is a English model originally trained by ISEGURA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_autext2024_isegura_pipeline_en_5.5.1_3.0_1734560753136.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_autext2024_isegura_pipeline_en_5.5.1_3.0_1734560753136.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mdeberta_v3_base_autext2024_isegura_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mdeberta_v3_base_autext2024_isegura_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_autext2024_isegura_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|878.9 MB|
+
+## References
+
+https://huggingface.co/ISEGURA/mdeberta-v3-base-autext2024
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-mdeberta_v3_base_readability_en.md b/docs/_posts/ahmedlone127/2024-12-18-mdeberta_v3_base_readability_en.md
new file mode 100644
index 00000000000000..7551b090b96e96
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-mdeberta_v3_base_readability_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mdeberta_v3_base_readability DeBertaForSequenceClassification from agentlans
+author: John Snow Labs
+name: mdeberta_v3_base_readability
+date: 2024-12-18
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_readability` is a English model originally trained by agentlans.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_readability_en_5.5.1_3.0_1734560543647.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_readability_en_5.5.1_3.0_1734560543647.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_readability","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_readability", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_readability|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|898.7 MB|
+
+## References
+
+https://huggingface.co/agentlans/mdeberta-v3-base-readability
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-mdeberta_v3_base_readability_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-mdeberta_v3_base_readability_pipeline_en.md
new file mode 100644
index 00000000000000..e85108afc828b7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-mdeberta_v3_base_readability_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mdeberta_v3_base_readability_pipeline pipeline DeBertaForSequenceClassification from agentlans
+author: John Snow Labs
+name: mdeberta_v3_base_readability_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_readability_pipeline` is a English model originally trained by agentlans.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_readability_pipeline_en_5.5.1_3.0_1734560631294.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_readability_pipeline_en_5.5.1_3.0_1734560631294.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mdeberta_v3_base_readability_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mdeberta_v3_base_readability_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_readability_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|898.7 MB|
+
+## References
+
+https://huggingface.co/agentlans/mdeberta-v3-base-readability
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-mdeberta_v3_base_sentiment_en.md b/docs/_posts/ahmedlone127/2024-12-18-mdeberta_v3_base_sentiment_en.md
new file mode 100644
index 00000000000000..0a60308925d67d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-mdeberta_v3_base_sentiment_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mdeberta_v3_base_sentiment DeBertaForSequenceClassification from agentlans
+author: John Snow Labs
+name: mdeberta_v3_base_sentiment
+date: 2024-12-18
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_sentiment` is a English model originally trained by agentlans.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_sentiment_en_5.5.1_3.0_1734561598948.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_sentiment_en_5.5.1_3.0_1734561598948.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_sentiment","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_sentiment", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_sentiment|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|863.5 MB|
+
+## References
+
+https://huggingface.co/agentlans/mdeberta-v3-base-sentiment
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-mdeberta_v3_base_sentiment_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-mdeberta_v3_base_sentiment_pipeline_en.md
new file mode 100644
index 00000000000000..bd48d4792873bd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-mdeberta_v3_base_sentiment_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mdeberta_v3_base_sentiment_pipeline pipeline DeBertaForSequenceClassification from agentlans
+author: John Snow Labs
+name: mdeberta_v3_base_sentiment_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_sentiment_pipeline` is a English model originally trained by agentlans.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_sentiment_pipeline_en_5.5.1_3.0_1734561695339.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_sentiment_pipeline_en_5.5.1_3.0_1734561695339.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mdeberta_v3_base_sentiment_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mdeberta_v3_base_sentiment_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_sentiment_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|863.5 MB|
+
+## References
+
+https://huggingface.co/agentlans/mdeberta-v3-base-sentiment
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-medical_bge_large_english_v1_5_en.md b/docs/_posts/ahmedlone127/2024-12-18-medical_bge_large_english_v1_5_en.md
new file mode 100644
index 00000000000000..1e27656436076f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-medical_bge_large_english_v1_5_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English medical_bge_large_english_v1_5 BGEEmbeddings from Codingchild
+author: John Snow Labs
+name: medical_bge_large_english_v1_5
+date: 2024-12-18
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`medical_bge_large_english_v1_5` is a English model originally trained by Codingchild.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/medical_bge_large_english_v1_5_en_5.5.1_3.0_1734563750315.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/medical_bge_large_english_v1_5_en_5.5.1_3.0_1734563750315.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("medical_bge_large_english_v1_5","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("medical_bge_large_english_v1_5","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|medical_bge_large_english_v1_5|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/Codingchild/medical-bge-large-en-v1.5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-medical_bge_large_english_v1_5_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-medical_bge_large_english_v1_5_pipeline_en.md
new file mode 100644
index 00000000000000..efba87a66446bf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-medical_bge_large_english_v1_5_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English medical_bge_large_english_v1_5_pipeline pipeline BGEEmbeddings from Codingchild
+author: John Snow Labs
+name: medical_bge_large_english_v1_5_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`medical_bge_large_english_v1_5_pipeline` is a English model originally trained by Codingchild.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/medical_bge_large_english_v1_5_pipeline_en_5.5.1_3.0_1734563822474.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/medical_bge_large_english_v1_5_pipeline_en_5.5.1_3.0_1734563822474.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("medical_bge_large_english_v1_5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("medical_bge_large_english_v1_5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|medical_bge_large_english_v1_5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/Codingchild/medical-bge-large-en-v1.5
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-meetingbank_qa_summary_model_finetuned_on_reduced_data_en.md b/docs/_posts/ahmedlone127/2024-12-18-meetingbank_qa_summary_model_finetuned_on_reduced_data_en.md
new file mode 100644
index 00000000000000..9afdf3adc01612
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-meetingbank_qa_summary_model_finetuned_on_reduced_data_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English meetingbank_qa_summary_model_finetuned_on_reduced_data T5Transformer from ZaidZia
+author: John Snow Labs
+name: meetingbank_qa_summary_model_finetuned_on_reduced_data
+date: 2024-12-18
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`meetingbank_qa_summary_model_finetuned_on_reduced_data` is a English model originally trained by ZaidZia.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/meetingbank_qa_summary_model_finetuned_on_reduced_data_en_5.5.1_3.0_1734566233665.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/meetingbank_qa_summary_model_finetuned_on_reduced_data_en_5.5.1_3.0_1734566233665.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("meetingbank_qa_summary_model_finetuned_on_reduced_data","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("meetingbank_qa_summary_model_finetuned_on_reduced_data", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|meetingbank_qa_summary_model_finetuned_on_reduced_data|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|268.8 MB|
+
+## References
+
+https://huggingface.co/ZaidZia/meetingbank_qa_summary_model_finetuned_on_reduced_data
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-meetingbank_qa_summary_model_finetuned_on_reduced_data_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-meetingbank_qa_summary_model_finetuned_on_reduced_data_pipeline_en.md
new file mode 100644
index 00000000000000..2f41561c117cc4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-meetingbank_qa_summary_model_finetuned_on_reduced_data_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English meetingbank_qa_summary_model_finetuned_on_reduced_data_pipeline pipeline T5Transformer from ZaidZia
+author: John Snow Labs
+name: meetingbank_qa_summary_model_finetuned_on_reduced_data_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`meetingbank_qa_summary_model_finetuned_on_reduced_data_pipeline` is a English model originally trained by ZaidZia.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/meetingbank_qa_summary_model_finetuned_on_reduced_data_pipeline_en_5.5.1_3.0_1734566251284.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/meetingbank_qa_summary_model_finetuned_on_reduced_data_pipeline_en_5.5.1_3.0_1734566251284.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("meetingbank_qa_summary_model_finetuned_on_reduced_data_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("meetingbank_qa_summary_model_finetuned_on_reduced_data_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|meetingbank_qa_summary_model_finetuned_on_reduced_data_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|268.8 MB|
+
+## References
+
+https://huggingface.co/ZaidZia/meetingbank_qa_summary_model_finetuned_on_reduced_data
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-results_mosalma_en.md b/docs/_posts/ahmedlone127/2024-12-18-results_mosalma_en.md
new file mode 100644
index 00000000000000..a4a54f2362af89
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-results_mosalma_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English results_mosalma T5Transformer from MoSalMa
+author: John Snow Labs
+name: results_mosalma
+date: 2024-12-18
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_mosalma` is a English model originally trained by MoSalMa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_mosalma_en_5.5.1_3.0_1734565905736.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_mosalma_en_5.5.1_3.0_1734565905736.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("results_mosalma","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("results_mosalma", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_mosalma|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|349.8 MB|
+
+## References
+
+https://huggingface.co/MoSalMa/results
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-results_mosalma_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-results_mosalma_pipeline_en.md
new file mode 100644
index 00000000000000..05a51eb1274f33
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-results_mosalma_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English results_mosalma_pipeline pipeline T5Transformer from MoSalMa
+author: John Snow Labs
+name: results_mosalma_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_mosalma_pipeline` is a English model originally trained by MoSalMa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_mosalma_pipeline_en_5.5.1_3.0_1734565923962.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_mosalma_pipeline_en_5.5.1_3.0_1734565923962.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("results_mosalma_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("results_mosalma_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_mosalma_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|349.8 MB|
+
+## References
+
+https://huggingface.co/MoSalMa/results
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-rgb_language_cap_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-rgb_language_cap_pipeline_en.md
new file mode 100644
index 00000000000000..b4c5555eea48a6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-rgb_language_cap_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English rgb_language_cap_pipeline pipeline VisionEncoderDecoderForImageCaptioning from voxreality
+author: John Snow Labs
+name: rgb_language_cap_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: Image Captioning
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained VisionEncoderDecoderForImageCaptioning, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rgb_language_cap_pipeline` is a English model originally trained by voxreality.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rgb_language_cap_pipeline_en_5.5.1_3.0_1734540372195.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rgb_language_cap_pipeline_en_5.5.1_3.0_1734540372195.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("rgb_language_cap_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("rgb_language_cap_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rgb_language_cap_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/voxreality/rgb_language_cap
+
+## Included Models
+
+- ImageAssembler
+- VisionEncoderDecoderForImageCaptioning
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-small_multi_news_model_en.md b/docs/_posts/ahmedlone127/2024-12-18-small_multi_news_model_en.md
new file mode 100644
index 00000000000000..325dd4e0905a01
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-small_multi_news_model_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English small_multi_news_model T5Transformer from tjjdoherty
+author: John Snow Labs
+name: small_multi_news_model
+date: 2024-12-18
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`small_multi_news_model` is a English model originally trained by tjjdoherty.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/small_multi_news_model_en_5.5.1_3.0_1734566144482.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/small_multi_news_model_en_5.5.1_3.0_1734566144482.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("small_multi_news_model","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("small_multi_news_model", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|small_multi_news_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|280.9 MB|
+
+## References
+
+https://huggingface.co/tjjdoherty/small-multi-news-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-small_multi_news_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-small_multi_news_model_pipeline_en.md
new file mode 100644
index 00000000000000..4cf2a1ae11675c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-small_multi_news_model_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English small_multi_news_model_pipeline pipeline T5Transformer from tjjdoherty
+author: John Snow Labs
+name: small_multi_news_model_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`small_multi_news_model_pipeline` is a English model originally trained by tjjdoherty.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/small_multi_news_model_pipeline_en_5.5.1_3.0_1734566160327.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/small_multi_news_model_pipeline_en_5.5.1_3.0_1734566160327.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("small_multi_news_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("small_multi_news_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|small_multi_news_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|280.9 MB|
+
+## References
+
+https://huggingface.co/tjjdoherty/small-multi-news-model
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-t5_small_fine_tuned_en.md b/docs/_posts/ahmedlone127/2024-12-18-t5_small_fine_tuned_en.md
new file mode 100644
index 00000000000000..16483780c7f2c2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-t5_small_fine_tuned_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_small_fine_tuned T5Transformer from clee9
+author: John Snow Labs
+name: t5_small_fine_tuned
+date: 2024-12-18
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_fine_tuned` is a English model originally trained by clee9.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_fine_tuned_en_5.5.1_3.0_1734566074433.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_fine_tuned_en_5.5.1_3.0_1734566074433.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_small_fine_tuned","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_small_fine_tuned", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_fine_tuned|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|279.4 MB|
+
+## References
+
+https://huggingface.co/clee9/T5_small_fine_tuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-t5_small_fine_tuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-t5_small_fine_tuned_pipeline_en.md
new file mode 100644
index 00000000000000..808183481e873e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-t5_small_fine_tuned_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_small_fine_tuned_pipeline pipeline T5Transformer from clee9
+author: John Snow Labs
+name: t5_small_fine_tuned_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_fine_tuned_pipeline` is a English model originally trained by clee9.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_fine_tuned_pipeline_en_5.5.1_3.0_1734566093153.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_fine_tuned_pipeline_en_5.5.1_3.0_1734566093153.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_small_fine_tuned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_small_fine_tuned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_fine_tuned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|279.4 MB|
+
+## References
+
+https://huggingface.co/clee9/T5_small_fine_tuned
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-text2pandas_t5_en.md b/docs/_posts/ahmedlone127/2024-12-18-text2pandas_t5_en.md
new file mode 100644
index 00000000000000..1dbd5c16625573
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-text2pandas_t5_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English text2pandas_t5 T5Transformer from zeyadusf
+author: John Snow Labs
+name: text2pandas_t5
+date: 2024-12-18
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`text2pandas_t5` is a English model originally trained by zeyadusf.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/text2pandas_t5_en_5.5.1_3.0_1734565967808.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/text2pandas_t5_en_5.5.1_3.0_1734565967808.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("text2pandas_t5","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("text2pandas_t5", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|text2pandas_t5|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|907.1 MB|
+
+## References
+
+https://huggingface.co/zeyadusf/text2pandas-T5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-text2pandas_t5_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-text2pandas_t5_pipeline_en.md
new file mode 100644
index 00000000000000..3563f7cec2f634
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-text2pandas_t5_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English text2pandas_t5_pipeline pipeline T5Transformer from zeyadusf
+author: John Snow Labs
+name: text2pandas_t5_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`text2pandas_t5_pipeline` is a English model originally trained by zeyadusf.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/text2pandas_t5_pipeline_en_5.5.1_3.0_1734566017373.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/text2pandas_t5_pipeline_en_5.5.1_3.0_1734566017373.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("text2pandas_t5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("text2pandas_t5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|text2pandas_t5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|907.1 MB|
+
+## References
+
+https://huggingface.co/zeyadusf/text2pandas-T5
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-trocr_medieval_castilian_hybrida_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-trocr_medieval_castilian_hybrida_pipeline_en.md
new file mode 100644
index 00000000000000..0700770e121e64
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-trocr_medieval_castilian_hybrida_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English trocr_medieval_castilian_hybrida_pipeline pipeline VisionEncoderDecoderForImageCaptioning from medieval-data
+author: John Snow Labs
+name: trocr_medieval_castilian_hybrida_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: Image Captioning
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained VisionEncoderDecoderForImageCaptioning, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`trocr_medieval_castilian_hybrida_pipeline` is a English model originally trained by medieval-data.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/trocr_medieval_castilian_hybrida_pipeline_en_5.5.1_3.0_1734541656904.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/trocr_medieval_castilian_hybrida_pipeline_en_5.5.1_3.0_1734541656904.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("trocr_medieval_castilian_hybrida_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("trocr_medieval_castilian_hybrida_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|trocr_medieval_castilian_hybrida_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.4 GB|
+
+## References
+
+https://huggingface.co/medieval-data/trocr-medieval-castilian-hybrida
+
+## Included Models
+
+- ImageAssembler
+- VisionEncoderDecoderForImageCaptioning
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-trocr_medieval_humanistica_pipeline_fr.md b/docs/_posts/ahmedlone127/2024-12-18-trocr_medieval_humanistica_pipeline_fr.md
new file mode 100644
index 00000000000000..a0fc9e4348e41e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-trocr_medieval_humanistica_pipeline_fr.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: French trocr_medieval_humanistica_pipeline pipeline VisionEncoderDecoderForImageCaptioning from medieval-data
+author: John Snow Labs
+name: trocr_medieval_humanistica_pipeline
+date: 2024-12-18
+tags: [fr, open_source, pipeline, onnx]
+task: Image Captioning
+language: fr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained VisionEncoderDecoderForImageCaptioning, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`trocr_medieval_humanistica_pipeline` is a French model originally trained by medieval-data.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/trocr_medieval_humanistica_pipeline_fr_5.5.1_3.0_1734540511942.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/trocr_medieval_humanistica_pipeline_fr_5.5.1_3.0_1734540511942.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("trocr_medieval_humanistica_pipeline", lang = "fr")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("trocr_medieval_humanistica_pipeline", lang = "fr")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|trocr_medieval_humanistica_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|fr|
+|Size:|1.4 GB|
+
+## References
+
+https://huggingface.co/medieval-data/trocr-medieval-humanistica
+
+## Included Models
+
+- ImageAssembler
+- VisionEncoderDecoderForImageCaptioning
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-trocr_medieval_print_pipeline_la.md b/docs/_posts/ahmedlone127/2024-12-18-trocr_medieval_print_pipeline_la.md
new file mode 100644
index 00000000000000..7d469013bbe641
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-trocr_medieval_print_pipeline_la.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Latin trocr_medieval_print_pipeline pipeline VisionEncoderDecoderForImageCaptioning from medieval-data
+author: John Snow Labs
+name: trocr_medieval_print_pipeline
+date: 2024-12-18
+tags: [la, open_source, pipeline, onnx]
+task: Image Captioning
+language: la
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained VisionEncoderDecoderForImageCaptioning, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`trocr_medieval_print_pipeline` is a Latin model originally trained by medieval-data.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/trocr_medieval_print_pipeline_la_5.5.1_3.0_1734540636612.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/trocr_medieval_print_pipeline_la_5.5.1_3.0_1734540636612.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("trocr_medieval_print_pipeline", lang = "la")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("trocr_medieval_print_pipeline", lang = "la")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|trocr_medieval_print_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|la|
+|Size:|1.4 GB|
+
+## References
+
+https://huggingface.co/medieval-data/trocr-medieval-print
+
+## Included Models
+
+- ImageAssembler
+- VisionEncoderDecoderForImageCaptioning
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-trocr_medieval_textualis_pipeline_nl.md b/docs/_posts/ahmedlone127/2024-12-18-trocr_medieval_textualis_pipeline_nl.md
new file mode 100644
index 00000000000000..67ef7178051e31
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-trocr_medieval_textualis_pipeline_nl.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Dutch, Flemish trocr_medieval_textualis_pipeline pipeline VisionEncoderDecoderForImageCaptioning from medieval-data
+author: John Snow Labs
+name: trocr_medieval_textualis_pipeline
+date: 2024-12-18
+tags: [nl, open_source, pipeline, onnx]
+task: Image Captioning
+language: nl
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained VisionEncoderDecoderForImageCaptioning, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`trocr_medieval_textualis_pipeline` is a Dutch, Flemish model originally trained by medieval-data.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/trocr_medieval_textualis_pipeline_nl_5.5.1_3.0_1734541038391.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/trocr_medieval_textualis_pipeline_nl_5.5.1_3.0_1734541038391.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("trocr_medieval_textualis_pipeline", lang = "nl")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("trocr_medieval_textualis_pipeline", lang = "nl")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|trocr_medieval_textualis_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|nl|
+|Size:|1.4 GB|
+
+## References
+
+https://huggingface.co/medieval-data/trocr-medieval-textualis
+
+## Included Models
+
+- ImageAssembler
+- VisionEncoderDecoderForImageCaptioning
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-18-vit_gpt2_verifycode_caption_thekog_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-18-vit_gpt2_verifycode_caption_thekog_pipeline_en.md
new file mode 100644
index 00000000000000..e5c9ecb8b0a13f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-18-vit_gpt2_verifycode_caption_thekog_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_gpt2_verifycode_caption_thekog_pipeline pipeline VisionEncoderDecoderForImageCaptioning from TheKOG
+author: John Snow Labs
+name: vit_gpt2_verifycode_caption_thekog_pipeline
+date: 2024-12-18
+tags: [en, open_source, pipeline, onnx]
+task: Image Captioning
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained VisionEncoderDecoderForImageCaptioning, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_gpt2_verifycode_caption_thekog_pipeline` is a English model originally trained by TheKOG.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_gpt2_verifycode_caption_thekog_pipeline_en_5.5.1_3.0_1734540378630.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_gpt2_verifycode_caption_thekog_pipeline_en_5.5.1_3.0_1734540378630.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_gpt2_verifycode_caption_thekog_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_gpt2_verifycode_caption_thekog_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_gpt2_verifycode_caption_thekog_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/TheKOG/vit-gpt2-verifycode-caption
+
+## Included Models
+
+- ImageAssembler
+- VisionEncoderDecoderForImageCaptioning
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-amharicnewscharacternormalized_en.md b/docs/_posts/ahmedlone127/2024-12-19-amharicnewscharacternormalized_en.md
new file mode 100644
index 00000000000000..ce910b7120dacd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-amharicnewscharacternormalized_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English amharicnewscharacternormalized XlmRoBertaForSequenceClassification from akiseid
+author: John Snow Labs
+name: amharicnewscharacternormalized
+date: 2024-12-19
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`amharicnewscharacternormalized` is a English model originally trained by akiseid.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/amharicnewscharacternormalized_en_5.5.1_3.0_1734596332792.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/amharicnewscharacternormalized_en_5.5.1_3.0_1734596332792.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("amharicnewscharacternormalized","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("amharicnewscharacternormalized", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|amharicnewscharacternormalized|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|840.4 MB|
+
+## References
+
+https://huggingface.co/akiseid/AmharicNewsCharacterNormalized
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-amharicnewscharacternormalized_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-amharicnewscharacternormalized_pipeline_en.md
new file mode 100644
index 00000000000000..e7425bb9102056
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-amharicnewscharacternormalized_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English amharicnewscharacternormalized_pipeline pipeline XlmRoBertaForSequenceClassification from akiseid
+author: John Snow Labs
+name: amharicnewscharacternormalized_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`amharicnewscharacternormalized_pipeline` is a English model originally trained by akiseid.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/amharicnewscharacternormalized_pipeline_en_5.5.1_3.0_1734596416495.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/amharicnewscharacternormalized_pipeline_en_5.5.1_3.0_1734596416495.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("amharicnewscharacternormalized_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("amharicnewscharacternormalized_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|amharicnewscharacternormalized_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.4 MB|
+
+## References
+
+https://huggingface.co/akiseid/AmharicNewsCharacterNormalized
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-autotrain_sentiment_analysis_project_705021428_en.md b/docs/_posts/ahmedlone127/2024-12-19-autotrain_sentiment_analysis_project_705021428_en.md
new file mode 100644
index 00000000000000..3689758f098f8b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-autotrain_sentiment_analysis_project_705021428_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English autotrain_sentiment_analysis_project_705021428 XlmRoBertaForSequenceClassification from ramnika003
+author: John Snow Labs
+name: autotrain_sentiment_analysis_project_705021428
+date: 2024-12-19
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_sentiment_analysis_project_705021428` is a English model originally trained by ramnika003.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_sentiment_analysis_project_705021428_en_5.5.1_3.0_1734596471435.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_sentiment_analysis_project_705021428_en_5.5.1_3.0_1734596471435.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("autotrain_sentiment_analysis_project_705021428","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("autotrain_sentiment_analysis_project_705021428", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_sentiment_analysis_project_705021428|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/ramnika003/autotrain-sentiment_analysis_project-705021428
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-autotrain_sentiment_analysis_project_705021428_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-autotrain_sentiment_analysis_project_705021428_pipeline_en.md
new file mode 100644
index 00000000000000..5e2f767fedb2f9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-autotrain_sentiment_analysis_project_705021428_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English autotrain_sentiment_analysis_project_705021428_pipeline pipeline XlmRoBertaForSequenceClassification from ramnika003
+author: John Snow Labs
+name: autotrain_sentiment_analysis_project_705021428_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_sentiment_analysis_project_705021428_pipeline` is a English model originally trained by ramnika003.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_sentiment_analysis_project_705021428_pipeline_en_5.5.1_3.0_1734596524218.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_sentiment_analysis_project_705021428_pipeline_en_5.5.1_3.0_1734596524218.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("autotrain_sentiment_analysis_project_705021428_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("autotrain_sentiment_analysis_project_705021428_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_sentiment_analysis_project_705021428_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/ramnika003/autotrain-sentiment_analysis_project-705021428
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-azerbaijani_spell_corrector_az.md b/docs/_posts/ahmedlone127/2024-12-19-azerbaijani_spell_corrector_az.md
new file mode 100644
index 00000000000000..85dc79c24ebe81
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-azerbaijani_spell_corrector_az.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Azerbaijani azerbaijani_spell_corrector T5Transformer from LocalDoc
+author: John Snow Labs
+name: azerbaijani_spell_corrector
+date: 2024-12-19
+tags: [az, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: az
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`azerbaijani_spell_corrector` is a Azerbaijani model originally trained by LocalDoc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/azerbaijani_spell_corrector_az_5.5.1_3.0_1734568546042.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/azerbaijani_spell_corrector_az_5.5.1_3.0_1734568546042.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("azerbaijani_spell_corrector","az") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("azerbaijani_spell_corrector", "az")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|azerbaijani_spell_corrector|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|az|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/LocalDoc/azerbaijani_spell_corrector
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-azerbaijani_spell_corrector_pipeline_az.md b/docs/_posts/ahmedlone127/2024-12-19-azerbaijani_spell_corrector_pipeline_az.md
new file mode 100644
index 00000000000000..74630727d542ec
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-azerbaijani_spell_corrector_pipeline_az.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Azerbaijani azerbaijani_spell_corrector_pipeline pipeline T5Transformer from LocalDoc
+author: John Snow Labs
+name: azerbaijani_spell_corrector_pipeline
+date: 2024-12-19
+tags: [az, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: az
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`azerbaijani_spell_corrector_pipeline` is a Azerbaijani model originally trained by LocalDoc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/azerbaijani_spell_corrector_pipeline_az_5.5.1_3.0_1734568700753.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/azerbaijani_spell_corrector_pipeline_az_5.5.1_3.0_1734568700753.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("azerbaijani_spell_corrector_pipeline", lang = "az")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("azerbaijani_spell_corrector_pipeline", lang = "az")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|azerbaijani_spell_corrector_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|az|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/LocalDoc/azerbaijani_spell_corrector
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-bert_bahasa_sentiment_en.md b/docs/_posts/ahmedlone127/2024-12-19-bert_bahasa_sentiment_en.md
new file mode 100644
index 00000000000000..7ddcc4358313eb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-bert_bahasa_sentiment_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_bahasa_sentiment BertForSequenceClassification from techthiyanes
+author: John Snow Labs
+name: bert_bahasa_sentiment
+date: 2024-12-19
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_bahasa_sentiment` is a English model originally trained by techthiyanes.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_bahasa_sentiment_en_5.5.1_3.0_1734571520332.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_bahasa_sentiment_en_5.5.1_3.0_1734571520332.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("bert_bahasa_sentiment","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("bert_bahasa_sentiment", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_bahasa_sentiment|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|627.8 MB|
+
+## References
+
+https://huggingface.co/techthiyanes/Bert_Bahasa_Sentiment
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-bert_bahasa_sentiment_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-bert_bahasa_sentiment_pipeline_en.md
new file mode 100644
index 00000000000000..b93f36561bb12e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-bert_bahasa_sentiment_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_bahasa_sentiment_pipeline pipeline BertForSequenceClassification from techthiyanes
+author: John Snow Labs
+name: bert_bahasa_sentiment_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_bahasa_sentiment_pipeline` is a English model originally trained by techthiyanes.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_bahasa_sentiment_pipeline_en_5.5.1_3.0_1734571552763.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_bahasa_sentiment_pipeline_en_5.5.1_3.0_1734571552763.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_bahasa_sentiment_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_bahasa_sentiment_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_bahasa_sentiment_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|627.8 MB|
+
+## References
+
+https://huggingface.co/techthiyanes/Bert_Bahasa_Sentiment
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-bert_base_ai_content_detector_en.md b/docs/_posts/ahmedlone127/2024-12-19-bert_base_ai_content_detector_en.md
new file mode 100644
index 00000000000000..4cc8c471e0c1ef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-bert_base_ai_content_detector_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_ai_content_detector BertForSequenceClassification from shahxeebhassan
+author: John Snow Labs
+name: bert_base_ai_content_detector
+date: 2024-12-19
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_ai_content_detector` is a English model originally trained by shahxeebhassan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_ai_content_detector_en_5.5.1_3.0_1734571899794.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_ai_content_detector_en_5.5.1_3.0_1734571899794.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("bert_base_ai_content_detector","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_ai_content_detector", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_ai_content_detector|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/shahxeebhassan/bert_base_ai_content_detector
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-bert_base_ai_content_detector_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-bert_base_ai_content_detector_pipeline_en.md
new file mode 100644
index 00000000000000..33c4a4ee79c128
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-bert_base_ai_content_detector_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_ai_content_detector_pipeline pipeline BertForSequenceClassification from shahxeebhassan
+author: John Snow Labs
+name: bert_base_ai_content_detector_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_ai_content_detector_pipeline` is a English model originally trained by shahxeebhassan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_ai_content_detector_pipeline_en_5.5.1_3.0_1734571922895.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_ai_content_detector_pipeline_en_5.5.1_3.0_1734571922895.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_ai_content_detector_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_ai_content_detector_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_ai_content_detector_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/shahxeebhassan/bert_base_ai_content_detector
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-bert_base_arabic_camelbert_catalan_tydi_tafseer_pairs_en.md b/docs/_posts/ahmedlone127/2024-12-19-bert_base_arabic_camelbert_catalan_tydi_tafseer_pairs_en.md
new file mode 100644
index 00000000000000..ce786155acd1b1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-bert_base_arabic_camelbert_catalan_tydi_tafseer_pairs_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_arabic_camelbert_catalan_tydi_tafseer_pairs BertForSequenceClassification from MatMulMan
+author: John Snow Labs
+name: bert_base_arabic_camelbert_catalan_tydi_tafseer_pairs
+date: 2024-12-19
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_arabic_camelbert_catalan_tydi_tafseer_pairs` is a English model originally trained by MatMulMan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_arabic_camelbert_catalan_tydi_tafseer_pairs_en_5.5.1_3.0_1734572188333.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_arabic_camelbert_catalan_tydi_tafseer_pairs_en_5.5.1_3.0_1734572188333.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("bert_base_arabic_camelbert_catalan_tydi_tafseer_pairs","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_arabic_camelbert_catalan_tydi_tafseer_pairs", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_arabic_camelbert_catalan_tydi_tafseer_pairs|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|408.8 MB|
+
+## References
+
+https://huggingface.co/MatMulMan/bert-base-arabic-camelbert-ca-tydi-tafseer-pairs
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-bert_base_arabic_camelbert_catalan_tydi_tafseer_pairs_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-bert_base_arabic_camelbert_catalan_tydi_tafseer_pairs_pipeline_en.md
new file mode 100644
index 00000000000000..4e22c52a587e98
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-bert_base_arabic_camelbert_catalan_tydi_tafseer_pairs_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_arabic_camelbert_catalan_tydi_tafseer_pairs_pipeline pipeline BertForSequenceClassification from MatMulMan
+author: John Snow Labs
+name: bert_base_arabic_camelbert_catalan_tydi_tafseer_pairs_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_arabic_camelbert_catalan_tydi_tafseer_pairs_pipeline` is a English model originally trained by MatMulMan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_arabic_camelbert_catalan_tydi_tafseer_pairs_pipeline_en_5.5.1_3.0_1734572209064.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_arabic_camelbert_catalan_tydi_tafseer_pairs_pipeline_en_5.5.1_3.0_1734572209064.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_arabic_camelbert_catalan_tydi_tafseer_pairs_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_arabic_camelbert_catalan_tydi_tafseer_pairs_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_arabic_camelbert_catalan_tydi_tafseer_pairs_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|408.9 MB|
+
+## References
+
+https://huggingface.co/MatMulMan/bert-base-arabic-camelbert-ca-tydi-tafseer-pairs
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-bert_base_multilingual_cased_finetuned_hate_speech_ptbr_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-12-19-bert_base_multilingual_cased_finetuned_hate_speech_ptbr_pipeline_xx.md
new file mode 100644
index 00000000000000..244e1686c8b0e8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-bert_base_multilingual_cased_finetuned_hate_speech_ptbr_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual bert_base_multilingual_cased_finetuned_hate_speech_ptbr_pipeline pipeline BertForSequenceClassification from GuiTap
+author: John Snow Labs
+name: bert_base_multilingual_cased_finetuned_hate_speech_ptbr_pipeline
+date: 2024-12-19
+tags: [xx, open_source, pipeline, onnx]
+task: Text Classification
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_cased_finetuned_hate_speech_ptbr_pipeline` is a Multilingual model originally trained by GuiTap.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_hate_speech_ptbr_pipeline_xx_5.5.1_3.0_1734571526325.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_hate_speech_ptbr_pipeline_xx_5.5.1_3.0_1734571526325.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_multilingual_cased_finetuned_hate_speech_ptbr_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_multilingual_cased_finetuned_hate_speech_ptbr_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_multilingual_cased_finetuned_hate_speech_ptbr_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|667.3 MB|
+
+## References
+
+https://huggingface.co/GuiTap/bert-base-multilingual-cased-finetuned-hate-speech-ptbr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-bert_base_multilingual_cased_finetuned_hate_speech_ptbr_xx.md b/docs/_posts/ahmedlone127/2024-12-19-bert_base_multilingual_cased_finetuned_hate_speech_ptbr_xx.md
new file mode 100644
index 00000000000000..36db3c4d502180
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-bert_base_multilingual_cased_finetuned_hate_speech_ptbr_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual bert_base_multilingual_cased_finetuned_hate_speech_ptbr BertForSequenceClassification from GuiTap
+author: John Snow Labs
+name: bert_base_multilingual_cased_finetuned_hate_speech_ptbr
+date: 2024-12-19
+tags: [xx, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_cased_finetuned_hate_speech_ptbr` is a Multilingual model originally trained by GuiTap.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_hate_speech_ptbr_xx_5.5.1_3.0_1734571493058.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_hate_speech_ptbr_xx_5.5.1_3.0_1734571493058.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("bert_base_multilingual_cased_finetuned_hate_speech_ptbr","xx") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_multilingual_cased_finetuned_hate_speech_ptbr", "xx")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_multilingual_cased_finetuned_hate_speech_ptbr|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|xx|
+|Size:|667.3 MB|
+
+## References
+
+https://huggingface.co/GuiTap/bert-base-multilingual-cased-finetuned-hate-speech-ptbr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-bert_base_uncased_reuters21578_reducedto15_2_gram_en.md b/docs/_posts/ahmedlone127/2024-12-19-bert_base_uncased_reuters21578_reducedto15_2_gram_en.md
new file mode 100644
index 00000000000000..8820bfff1478b7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-bert_base_uncased_reuters21578_reducedto15_2_gram_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_uncased_reuters21578_reducedto15_2_gram BertForSequenceClassification from ardi555
+author: John Snow Labs
+name: bert_base_uncased_reuters21578_reducedto15_2_gram
+date: 2024-12-19
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_reuters21578_reducedto15_2_gram` is a English model originally trained by ardi555.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_reuters21578_reducedto15_2_gram_en_5.5.1_3.0_1734570947845.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_reuters21578_reducedto15_2_gram_en_5.5.1_3.0_1734570947845.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("bert_base_uncased_reuters21578_reducedto15_2_gram","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_reuters21578_reducedto15_2_gram", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_reuters21578_reducedto15_2_gram|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/ardi555/bert_base_uncased_reuters21578_reducedto15_2-gram
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-bert_base_uncased_reuters21578_reducedto15_2_gram_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-bert_base_uncased_reuters21578_reducedto15_2_gram_pipeline_en.md
new file mode 100644
index 00000000000000..d6dc9528763a7d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-bert_base_uncased_reuters21578_reducedto15_2_gram_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_uncased_reuters21578_reducedto15_2_gram_pipeline pipeline BertForSequenceClassification from ardi555
+author: John Snow Labs
+name: bert_base_uncased_reuters21578_reducedto15_2_gram_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_reuters21578_reducedto15_2_gram_pipeline` is a English model originally trained by ardi555.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_reuters21578_reducedto15_2_gram_pipeline_en_5.5.1_3.0_1734570969036.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_reuters21578_reducedto15_2_gram_pipeline_en_5.5.1_3.0_1734570969036.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_reuters21578_reducedto15_2_gram_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_reuters21578_reducedto15_2_gram_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_reuters21578_reducedto15_2_gram_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.5 MB|
+
+## References
+
+https://huggingface.co/ardi555/bert_base_uncased_reuters21578_reducedto15_2-gram
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-bert_large_finetuned_phishing_hoanganhvu_en.md b/docs/_posts/ahmedlone127/2024-12-19-bert_large_finetuned_phishing_hoanganhvu_en.md
new file mode 100644
index 00000000000000..752bf1910eda19
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-bert_large_finetuned_phishing_hoanganhvu_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_large_finetuned_phishing_hoanganhvu BertForSequenceClassification from hoanganhvu
+author: John Snow Labs
+name: bert_large_finetuned_phishing_hoanganhvu
+date: 2024-12-19
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_finetuned_phishing_hoanganhvu` is a English model originally trained by hoanganhvu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_finetuned_phishing_hoanganhvu_en_5.5.1_3.0_1734571535756.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_finetuned_phishing_hoanganhvu_en_5.5.1_3.0_1734571535756.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("bert_large_finetuned_phishing_hoanganhvu","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_finetuned_phishing_hoanganhvu", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_large_finetuned_phishing_hoanganhvu|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/hoanganhvu/bert-large-finetuned-phishing
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-bert_large_finetuned_phishing_hoanganhvu_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-bert_large_finetuned_phishing_hoanganhvu_pipeline_en.md
new file mode 100644
index 00000000000000..2fb4e99e3dcdd7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-bert_large_finetuned_phishing_hoanganhvu_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_large_finetuned_phishing_hoanganhvu_pipeline pipeline BertForSequenceClassification from hoanganhvu
+author: John Snow Labs
+name: bert_large_finetuned_phishing_hoanganhvu_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_finetuned_phishing_hoanganhvu_pipeline` is a English model originally trained by hoanganhvu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_finetuned_phishing_hoanganhvu_pipeline_en_5.5.1_3.0_1734571601437.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_finetuned_phishing_hoanganhvu_pipeline_en_5.5.1_3.0_1734571601437.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_large_finetuned_phishing_hoanganhvu_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_large_finetuned_phishing_hoanganhvu_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_large_finetuned_phishing_hoanganhvu_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/hoanganhvu/bert-large-finetuned-phishing
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-biobart_large_en.md b/docs/_posts/ahmedlone127/2024-12-19-biobart_large_en.md
new file mode 100644
index 00000000000000..d2fa75f7d6fa32
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-biobart_large_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English biobart_large BartTransformer from GanjinZero
+author: John Snow Labs
+name: biobart_large
+date: 2024-12-19
+tags: [en, open_source, onnx, text_generation, bart]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BartTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biobart_large` is a English model originally trained by GanjinZero.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biobart_large_en_5.5.1_3.0_1734578487242.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biobart_large_en_5.5.1_3.0_1734578487242.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = BartTransformer.pretrained("biobart_large","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = BartTransformer.pretrained("biobart_large","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|biobart_large|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/GanjinZero/biobart-large
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-biobart_large_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-biobart_large_pipeline_en.md
new file mode 100644
index 00000000000000..4e90b420dc7416
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-biobart_large_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English biobart_large_pipeline pipeline BartTransformer from GanjinZero
+author: John Snow Labs
+name: biobart_large_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biobart_large_pipeline` is a English model originally trained by GanjinZero.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biobart_large_pipeline_en_5.5.1_3.0_1734578819088.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biobart_large_pipeline_en_5.5.1_3.0_1734578819088.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("biobart_large_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("biobart_large_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|biobart_large_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/GanjinZero/biobart-large
+
+## Included Models
+
+- DocumentAssembler
+- BartTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-book_reviews_model_en.md b/docs/_posts/ahmedlone127/2024-12-19-book_reviews_model_en.md
new file mode 100644
index 00000000000000..41f764cf34053a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-book_reviews_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English book_reviews_model BertForSequenceClassification from Newvel
+author: John Snow Labs
+name: book_reviews_model
+date: 2024-12-19
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`book_reviews_model` is a English model originally trained by Newvel.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/book_reviews_model_en_5.5.1_3.0_1734571892259.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/book_reviews_model_en_5.5.1_3.0_1734571892259.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("book_reviews_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("book_reviews_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|book_reviews_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/Newvel/book_reviews_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-book_reviews_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-book_reviews_model_pipeline_en.md
new file mode 100644
index 00000000000000..894884ff52cfbb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-book_reviews_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English book_reviews_model_pipeline pipeline BertForSequenceClassification from Newvel
+author: John Snow Labs
+name: book_reviews_model_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`book_reviews_model_pipeline` is a English model originally trained by Newvel.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/book_reviews_model_pipeline_en_5.5.1_3.0_1734571913476.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/book_reviews_model_pipeline_en_5.5.1_3.0_1734571913476.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("book_reviews_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("book_reviews_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|book_reviews_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/Newvel/book_reviews_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-bsc_bio_ehr_spanish_medprocner_es.md b/docs/_posts/ahmedlone127/2024-12-19-bsc_bio_ehr_spanish_medprocner_es.md
new file mode 100644
index 00000000000000..2b5451a1cd0479
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-bsc_bio_ehr_spanish_medprocner_es.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Castilian, Spanish bsc_bio_ehr_spanish_medprocner RoBertaForTokenClassification from BSC-NLP4BIA
+author: John Snow Labs
+name: bsc_bio_ehr_spanish_medprocner
+date: 2024-12-19
+tags: [es, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: es
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bsc_bio_ehr_spanish_medprocner` is a Castilian, Spanish model originally trained by BSC-NLP4BIA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bsc_bio_ehr_spanish_medprocner_es_5.5.1_3.0_1734594682094.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bsc_bio_ehr_spanish_medprocner_es_5.5.1_3.0_1734594682094.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("bsc_bio_ehr_spanish_medprocner","es") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("bsc_bio_ehr_spanish_medprocner", "es")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bsc_bio_ehr_spanish_medprocner|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|es|
+|Size:|441.8 MB|
+
+## References
+
+https://huggingface.co/BSC-NLP4BIA/bsc-bio-ehr-es-medprocner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-bsc_bio_ehr_spanish_medprocner_pipeline_es.md b/docs/_posts/ahmedlone127/2024-12-19-bsc_bio_ehr_spanish_medprocner_pipeline_es.md
new file mode 100644
index 00000000000000..e57c8c60cbfb64
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-bsc_bio_ehr_spanish_medprocner_pipeline_es.md
@@ -0,0 +1,72 @@
+---
+layout: model
+title: Castilian, Spanish bsc_bio_ehr_spanish_medprocner_pipeline pipeline RoBertaForTokenClassification from BSC-NLP4BIA
+author: John Snow Labs
+name: bsc_bio_ehr_spanish_medprocner_pipeline
+date: 2024-12-19
+tags: [es, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: es
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bsc_bio_ehr_spanish_medprocner_pipeline` is a Castilian, Spanish model originally trained by BSC-NLP4BIA.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bsc_bio_ehr_spanish_medprocner_pipeline_es_5.5.1_3.0_1734594706659.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bsc_bio_ehr_spanish_medprocner_pipeline_es_5.5.1_3.0_1734594706659.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("bsc_bio_ehr_spanish_medprocner_pipeline", lang = "es")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("bsc_bio_ehr_spanish_medprocner_pipeline", lang = "es")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bsc_bio_ehr_spanish_medprocner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|es|
+|Size:|441.8 MB|
+
+## References
+
+References
+
+https://huggingface.co/BSC-NLP4BIA/bsc-bio-ehr-es-medprocner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-burmese_awesome_health_qa_model_en.md b/docs/_posts/ahmedlone127/2024-12-19-burmese_awesome_health_qa_model_en.md
new file mode 100644
index 00000000000000..d8c2f7381ca71f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-burmese_awesome_health_qa_model_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_health_qa_model RoBertaForQuestionAnswering from yashwan2003
+author: John Snow Labs
+name: burmese_awesome_health_qa_model
+date: 2024-12-19
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_health_qa_model` is a English model originally trained by yashwan2003.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_health_qa_model_en_5.5.1_3.0_1734601332080.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_health_qa_model_en_5.5.1_3.0_1734601332080.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("burmese_awesome_health_qa_model","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("burmese_awesome_health_qa_model", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_health_qa_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|463.6 MB|
+
+## References
+
+https://huggingface.co/yashwan2003/my_awesome_health_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-burmese_awesome_health_qa_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-burmese_awesome_health_qa_model_pipeline_en.md
new file mode 100644
index 00000000000000..1ca363cc985b3e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-burmese_awesome_health_qa_model_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_health_qa_model_pipeline pipeline RoBertaForQuestionAnswering from yashwan2003
+author: John Snow Labs
+name: burmese_awesome_health_qa_model_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_health_qa_model_pipeline` is a English model originally trained by yashwan2003.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_health_qa_model_pipeline_en_5.5.1_3.0_1734601356397.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_health_qa_model_pipeline_en_5.5.1_3.0_1734601356397.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_health_qa_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_health_qa_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_health_qa_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|463.6 MB|
+
+## References
+
+https://huggingface.co/yashwan2003/my_awesome_health_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-burmese_awesome_qa_model_yashwan2003_en.md b/docs/_posts/ahmedlone127/2024-12-19-burmese_awesome_qa_model_yashwan2003_en.md
new file mode 100644
index 00000000000000..9c7120d633e69b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-burmese_awesome_qa_model_yashwan2003_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_yashwan2003 RoBertaForQuestionAnswering from yashwan2003
+author: John Snow Labs
+name: burmese_awesome_qa_model_yashwan2003
+date: 2024-12-19
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_yashwan2003` is a English model originally trained by yashwan2003.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_yashwan2003_en_5.5.1_3.0_1734601164433.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_yashwan2003_en_5.5.1_3.0_1734601164433.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("burmese_awesome_qa_model_yashwan2003","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("burmese_awesome_qa_model_yashwan2003", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_yashwan2003|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|463.6 MB|
+
+## References
+
+https://huggingface.co/yashwan2003/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-burmese_awesome_qa_model_yashwan2003_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-burmese_awesome_qa_model_yashwan2003_pipeline_en.md
new file mode 100644
index 00000000000000..751f59461f8d61
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-burmese_awesome_qa_model_yashwan2003_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_yashwan2003_pipeline pipeline RoBertaForQuestionAnswering from yashwan2003
+author: John Snow Labs
+name: burmese_awesome_qa_model_yashwan2003_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_yashwan2003_pipeline` is a English model originally trained by yashwan2003.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_yashwan2003_pipeline_en_5.5.1_3.0_1734601187808.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_yashwan2003_pipeline_en_5.5.1_3.0_1734601187808.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_yashwan2003_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_yashwan2003_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_yashwan2003_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|463.6 MB|
+
+## References
+
+https://huggingface.co/yashwan2003/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-burmese_t5_small_test_tretchian_en.md b/docs/_posts/ahmedlone127/2024-12-19-burmese_t5_small_test_tretchian_en.md
new file mode 100644
index 00000000000000..2f325c1a05a3c5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-burmese_t5_small_test_tretchian_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_t5_small_test_tretchian T5Transformer from Tretchian
+author: John Snow Labs
+name: burmese_t5_small_test_tretchian
+date: 2024-12-19
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_t5_small_test_tretchian` is a English model originally trained by Tretchian.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_t5_small_test_tretchian_en_5.5.1_3.0_1734569543653.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_t5_small_test_tretchian_en_5.5.1_3.0_1734569543653.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("burmese_t5_small_test_tretchian","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("burmese_t5_small_test_tretchian", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_t5_small_test_tretchian|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|282.2 MB|
+
+## References
+
+https://huggingface.co/Tretchian/my_t5_small_test
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-burmese_t5_small_test_tretchian_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-burmese_t5_small_test_tretchian_pipeline_en.md
new file mode 100644
index 00000000000000..03d87f5869d314
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-burmese_t5_small_test_tretchian_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_t5_small_test_tretchian_pipeline pipeline T5Transformer from Tretchian
+author: John Snow Labs
+name: burmese_t5_small_test_tretchian_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_t5_small_test_tretchian_pipeline` is a English model originally trained by Tretchian.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_t5_small_test_tretchian_pipeline_en_5.5.1_3.0_1734569559499.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_t5_small_test_tretchian_pipeline_en_5.5.1_3.0_1734569559499.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_t5_small_test_tretchian_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_t5_small_test_tretchian_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_t5_small_test_tretchian_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|282.2 MB|
+
+## References
+
+https://huggingface.co/Tretchian/my_t5_small_test
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-caribbean_english_sentiment_fine_tuned_bert_mrarish320_en.md b/docs/_posts/ahmedlone127/2024-12-19-caribbean_english_sentiment_fine_tuned_bert_mrarish320_en.md
new file mode 100644
index 00000000000000..104549df2390c9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-caribbean_english_sentiment_fine_tuned_bert_mrarish320_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English caribbean_english_sentiment_fine_tuned_bert_mrarish320 BertForSequenceClassification from mrarish320
+author: John Snow Labs
+name: caribbean_english_sentiment_fine_tuned_bert_mrarish320
+date: 2024-12-19
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`caribbean_english_sentiment_fine_tuned_bert_mrarish320` is a English model originally trained by mrarish320.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/caribbean_english_sentiment_fine_tuned_bert_mrarish320_en_5.5.1_3.0_1734572142716.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/caribbean_english_sentiment_fine_tuned_bert_mrarish320_en_5.5.1_3.0_1734572142716.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("caribbean_english_sentiment_fine_tuned_bert_mrarish320","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("caribbean_english_sentiment_fine_tuned_bert_mrarish320", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|caribbean_english_sentiment_fine_tuned_bert_mrarish320|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/mrarish320/caribbean_english_sentiment_fine_tuned_bert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-caribbean_english_sentiment_fine_tuned_bert_mrarish320_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-caribbean_english_sentiment_fine_tuned_bert_mrarish320_pipeline_en.md
new file mode 100644
index 00000000000000..0a5747f3d9047e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-caribbean_english_sentiment_fine_tuned_bert_mrarish320_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English caribbean_english_sentiment_fine_tuned_bert_mrarish320_pipeline pipeline BertForSequenceClassification from mrarish320
+author: John Snow Labs
+name: caribbean_english_sentiment_fine_tuned_bert_mrarish320_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`caribbean_english_sentiment_fine_tuned_bert_mrarish320_pipeline` is a English model originally trained by mrarish320.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/caribbean_english_sentiment_fine_tuned_bert_mrarish320_pipeline_en_5.5.1_3.0_1734572163715.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/caribbean_english_sentiment_fine_tuned_bert_mrarish320_pipeline_en_5.5.1_3.0_1734572163715.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("caribbean_english_sentiment_fine_tuned_bert_mrarish320_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("caribbean_english_sentiment_fine_tuned_bert_mrarish320_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|caribbean_english_sentiment_fine_tuned_bert_mrarish320_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/mrarish320/caribbean_english_sentiment_fine_tuned_bert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-chatbot_satvikag_en.md b/docs/_posts/ahmedlone127/2024-12-19-chatbot_satvikag_en.md
new file mode 100644
index 00000000000000..57b6324e0bb385
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-chatbot_satvikag_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English chatbot_satvikag GPT2Transformer from satvikag
+author: John Snow Labs
+name: chatbot_satvikag
+date: 2024-12-19
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`chatbot_satvikag` is a English model originally trained by satvikag.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/chatbot_satvikag_en_5.5.1_3.0_1734584538870.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/chatbot_satvikag_en_5.5.1_3.0_1734584538870.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("chatbot_satvikag","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("chatbot_satvikag","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|chatbot_satvikag|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|466.8 MB|
+
+## References
+
+https://huggingface.co/satvikag/chatbot
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-chatbot_satvikag_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-chatbot_satvikag_pipeline_en.md
new file mode 100644
index 00000000000000..d72b813ebe1d23
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-chatbot_satvikag_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English chatbot_satvikag_pipeline pipeline GPT2Transformer from satvikag
+author: John Snow Labs
+name: chatbot_satvikag_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`chatbot_satvikag_pipeline` is a English model originally trained by satvikag.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/chatbot_satvikag_pipeline_en_5.5.1_3.0_1734584562940.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/chatbot_satvikag_pipeline_en_5.5.1_3.0_1734584562940.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("chatbot_satvikag_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("chatbot_satvikag_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|chatbot_satvikag_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.9 MB|
+
+## References
+
+https://huggingface.co/satvikag/chatbot
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-classification_model_house_assistance_phayathaibert_error_en.md b/docs/_posts/ahmedlone127/2024-12-19-classification_model_house_assistance_phayathaibert_error_en.md
new file mode 100644
index 00000000000000..99164b63166d80
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-classification_model_house_assistance_phayathaibert_error_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English classification_model_house_assistance_phayathaibert_error CamemBertForSequenceClassification from lunarlist
+author: John Snow Labs
+name: classification_model_house_assistance_phayathaibert_error
+date: 2024-12-19
+tags: [en, open_source, onnx, sequence_classification, camembert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`classification_model_house_assistance_phayathaibert_error` is a English model originally trained by lunarlist.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/classification_model_house_assistance_phayathaibert_error_en_5.5.1_3.0_1734572643082.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/classification_model_house_assistance_phayathaibert_error_en_5.5.1_3.0_1734572643082.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = CamemBertForSequenceClassification.pretrained("classification_model_house_assistance_phayathaibert_error","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = CamemBertForSequenceClassification.pretrained("classification_model_house_assistance_phayathaibert_error", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|classification_model_house_assistance_phayathaibert_error|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/lunarlist/classification-model-house-assistance-phayathaibert-error
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-classification_model_house_assistance_phayathaibert_error_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-classification_model_house_assistance_phayathaibert_error_pipeline_en.md
new file mode 100644
index 00000000000000..8730b53b66ecf8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-classification_model_house_assistance_phayathaibert_error_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English classification_model_house_assistance_phayathaibert_error_pipeline pipeline CamemBertForSequenceClassification from lunarlist
+author: John Snow Labs
+name: classification_model_house_assistance_phayathaibert_error_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`classification_model_house_assistance_phayathaibert_error_pipeline` is a English model originally trained by lunarlist.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/classification_model_house_assistance_phayathaibert_error_pipeline_en_5.5.1_3.0_1734572692760.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/classification_model_house_assistance_phayathaibert_error_pipeline_en_5.5.1_3.0_1734572692760.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("classification_model_house_assistance_phayathaibert_error_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("classification_model_house_assistance_phayathaibert_error_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|classification_model_house_assistance_phayathaibert_error_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/lunarlist/classification-model-house-assistance-phayathaibert-error
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-comparacion_t5_en.md b/docs/_posts/ahmedlone127/2024-12-19-comparacion_t5_en.md
new file mode 100644
index 00000000000000..93b294c07e5fc8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-comparacion_t5_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English comparacion_t5 T5Transformer from MartinElMolon
+author: John Snow Labs
+name: comparacion_t5
+date: 2024-12-19
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`comparacion_t5` is a English model originally trained by MartinElMolon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/comparacion_t5_en_5.5.1_3.0_1734569041238.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/comparacion_t5_en_5.5.1_3.0_1734569041238.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("comparacion_t5","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("comparacion_t5", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|comparacion_t5|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|927.2 MB|
+
+## References
+
+https://huggingface.co/MartinElMolon/comparacion_T5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-comparacion_t5_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-comparacion_t5_pipeline_en.md
new file mode 100644
index 00000000000000..a50c8c0ce493ca
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-comparacion_t5_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English comparacion_t5_pipeline pipeline T5Transformer from MartinElMolon
+author: John Snow Labs
+name: comparacion_t5_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`comparacion_t5_pipeline` is a English model originally trained by MartinElMolon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/comparacion_t5_pipeline_en_5.5.1_3.0_1734569087484.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/comparacion_t5_pipeline_en_5.5.1_3.0_1734569087484.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("comparacion_t5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("comparacion_t5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|comparacion_t5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|927.2 MB|
+
+## References
+
+https://huggingface.co/MartinElMolon/comparacion_T5
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-distilbart_xsum_12_1_sshleifer_en.md b/docs/_posts/ahmedlone127/2024-12-19-distilbart_xsum_12_1_sshleifer_en.md
new file mode 100644
index 00000000000000..15b92a7e86e454
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-distilbart_xsum_12_1_sshleifer_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilbart_xsum_12_1_sshleifer BartTransformer from sshleifer
+author: John Snow Labs
+name: distilbart_xsum_12_1_sshleifer
+date: 2024-12-19
+tags: [en, open_source, onnx, text_generation, bart]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BartTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbart_xsum_12_1_sshleifer` is a English model originally trained by sshleifer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbart_xsum_12_1_sshleifer_en_5.5.1_3.0_1734577550561.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbart_xsum_12_1_sshleifer_en_5.5.1_3.0_1734577550561.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = BartTransformer.pretrained("distilbart_xsum_12_1_sshleifer","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = BartTransformer.pretrained("distilbart_xsum_12_1_sshleifer","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbart_xsum_12_1_sshleifer|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|777.0 MB|
+
+## References
+
+https://huggingface.co/sshleifer/distilbart-xsum-12-1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-distilbart_xsum_12_1_sshleifer_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-distilbart_xsum_12_1_sshleifer_pipeline_en.md
new file mode 100644
index 00000000000000..3d612c33943452
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-distilbart_xsum_12_1_sshleifer_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbart_xsum_12_1_sshleifer_pipeline pipeline BartTransformer from sshleifer
+author: John Snow Labs
+name: distilbart_xsum_12_1_sshleifer_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbart_xsum_12_1_sshleifer_pipeline` is a English model originally trained by sshleifer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbart_xsum_12_1_sshleifer_pipeline_en_5.5.1_3.0_1734577763095.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbart_xsum_12_1_sshleifer_pipeline_en_5.5.1_3.0_1734577763095.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbart_xsum_12_1_sshleifer_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbart_xsum_12_1_sshleifer_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbart_xsum_12_1_sshleifer_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|777.0 MB|
+
+## References
+
+https://huggingface.co/sshleifer/distilbart-xsum-12-1
+
+## Included Models
+
+- DocumentAssembler
+- BartTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-distilbart_xsum_6_6_sshleifer_en.md b/docs/_posts/ahmedlone127/2024-12-19-distilbart_xsum_6_6_sshleifer_en.md
new file mode 100644
index 00000000000000..2584fbef03e90d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-distilbart_xsum_6_6_sshleifer_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilbart_xsum_6_6_sshleifer BartTransformer from sshleifer
+author: John Snow Labs
+name: distilbart_xsum_6_6_sshleifer
+date: 2024-12-19
+tags: [en, open_source, onnx, text_generation, bart]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BartTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbart_xsum_6_6_sshleifer` is a English model originally trained by sshleifer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbart_xsum_6_6_sshleifer_en_5.5.1_3.0_1734580058245.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbart_xsum_6_6_sshleifer_en_5.5.1_3.0_1734580058245.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = BartTransformer.pretrained("distilbart_xsum_6_6_sshleifer","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = BartTransformer.pretrained("distilbart_xsum_6_6_sshleifer","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbart_xsum_6_6_sshleifer|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|796.1 MB|
+
+## References
+
+https://huggingface.co/sshleifer/distilbart-xsum-6-6
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-distilbart_xsum_6_6_sshleifer_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-distilbart_xsum_6_6_sshleifer_pipeline_en.md
new file mode 100644
index 00000000000000..c66034a42a6f92
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-distilbart_xsum_6_6_sshleifer_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbart_xsum_6_6_sshleifer_pipeline pipeline BartTransformer from sshleifer
+author: John Snow Labs
+name: distilbart_xsum_6_6_sshleifer_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbart_xsum_6_6_sshleifer_pipeline` is a English model originally trained by sshleifer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbart_xsum_6_6_sshleifer_pipeline_en_5.5.1_3.0_1734580273912.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbart_xsum_6_6_sshleifer_pipeline_en_5.5.1_3.0_1734580273912.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbart_xsum_6_6_sshleifer_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbart_xsum_6_6_sshleifer_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbart_xsum_6_6_sshleifer_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|796.1 MB|
+
+## References
+
+https://huggingface.co/sshleifer/distilbart-xsum-6-6
+
+## Included Models
+
+- DocumentAssembler
+- BartTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-distilgpt2_hc3_en.md b/docs/_posts/ahmedlone127/2024-12-19-distilgpt2_hc3_en.md
new file mode 100644
index 00000000000000..fc3a3a4a229ee9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-distilgpt2_hc3_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilgpt2_hc3 GPT2Transformer from pszemraj
+author: John Snow Labs
+name: distilgpt2_hc3
+date: 2024-12-19
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilgpt2_hc3` is a English model originally trained by pszemraj.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilgpt2_hc3_en_5.5.1_3.0_1734585201436.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilgpt2_hc3_en_5.5.1_3.0_1734585201436.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("distilgpt2_hc3","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("distilgpt2_hc3","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilgpt2_hc3|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|308.4 MB|
+
+## References
+
+https://huggingface.co/pszemraj/distilgpt2-HC3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-distilgpt2_hc3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-distilgpt2_hc3_pipeline_en.md
new file mode 100644
index 00000000000000..d7f75c8d6c579a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-distilgpt2_hc3_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilgpt2_hc3_pipeline pipeline GPT2Transformer from pszemraj
+author: John Snow Labs
+name: distilgpt2_hc3_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilgpt2_hc3_pipeline` is a English model originally trained by pszemraj.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilgpt2_hc3_pipeline_en_5.5.1_3.0_1734585217226.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilgpt2_hc3_pipeline_en_5.5.1_3.0_1734585217226.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilgpt2_hc3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilgpt2_hc3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilgpt2_hc3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|308.4 MB|
+
+## References
+
+https://huggingface.co/pszemraj/distilgpt2-HC3
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-distilgpt2_pubmed_cemilcelik_en.md b/docs/_posts/ahmedlone127/2024-12-19-distilgpt2_pubmed_cemilcelik_en.md
new file mode 100644
index 00000000000000..10867c97df7688
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-distilgpt2_pubmed_cemilcelik_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilgpt2_pubmed_cemilcelik GPT2Transformer from cemilcelik
+author: John Snow Labs
+name: distilgpt2_pubmed_cemilcelik
+date: 2024-12-19
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilgpt2_pubmed_cemilcelik` is a English model originally trained by cemilcelik.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilgpt2_pubmed_cemilcelik_en_5.5.1_3.0_1734583663555.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilgpt2_pubmed_cemilcelik_en_5.5.1_3.0_1734583663555.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("distilgpt2_pubmed_cemilcelik","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("distilgpt2_pubmed_cemilcelik","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilgpt2_pubmed_cemilcelik|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|308.4 MB|
+
+## References
+
+https://huggingface.co/cemilcelik/distilgpt2_pubmed
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-distilgpt2_pubmed_cemilcelik_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-distilgpt2_pubmed_cemilcelik_pipeline_en.md
new file mode 100644
index 00000000000000..6858dd6957a7fe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-distilgpt2_pubmed_cemilcelik_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilgpt2_pubmed_cemilcelik_pipeline pipeline GPT2Transformer from cemilcelik
+author: John Snow Labs
+name: distilgpt2_pubmed_cemilcelik_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilgpt2_pubmed_cemilcelik_pipeline` is a English model originally trained by cemilcelik.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilgpt2_pubmed_cemilcelik_pipeline_en_5.5.1_3.0_1734583679333.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilgpt2_pubmed_cemilcelik_pipeline_en_5.5.1_3.0_1734583679333.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilgpt2_pubmed_cemilcelik_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilgpt2_pubmed_cemilcelik_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilgpt2_pubmed_cemilcelik_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|308.4 MB|
+
+## References
+
+https://huggingface.co/cemilcelik/distilgpt2_pubmed
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-distillgpt2cinder_en.md b/docs/_posts/ahmedlone127/2024-12-19-distillgpt2cinder_en.md
new file mode 100644
index 00000000000000..5c43a59f5f6aa7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-distillgpt2cinder_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distillgpt2cinder GPT2Transformer from Josephgflowers
+author: John Snow Labs
+name: distillgpt2cinder
+date: 2024-12-19
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distillgpt2cinder` is a English model originally trained by Josephgflowers.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distillgpt2cinder_en_5.5.1_3.0_1734592177523.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distillgpt2cinder_en_5.5.1_3.0_1734592177523.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("distillgpt2cinder","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("distillgpt2cinder","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distillgpt2cinder|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|308.6 MB|
+
+## References
+
+https://huggingface.co/Josephgflowers/distillgpt2Cinder
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-distillgpt2cinder_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-distillgpt2cinder_pipeline_en.md
new file mode 100644
index 00000000000000..b14b0b3bfce958
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-distillgpt2cinder_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distillgpt2cinder_pipeline pipeline GPT2Transformer from Josephgflowers
+author: John Snow Labs
+name: distillgpt2cinder_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distillgpt2cinder_pipeline` is a English model originally trained by Josephgflowers.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distillgpt2cinder_pipeline_en_5.5.1_3.0_1734592193041.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distillgpt2cinder_pipeline_en_5.5.1_3.0_1734592193041.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distillgpt2cinder_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distillgpt2cinder_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distillgpt2cinder_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|308.6 MB|
+
+## References
+
+https://huggingface.co/Josephgflowers/distillgpt2Cinder
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-dnabert2_h3k27me3_en.md b/docs/_posts/ahmedlone127/2024-12-19-dnabert2_h3k27me3_en.md
new file mode 100644
index 00000000000000..9ea27ff4b93655
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-dnabert2_h3k27me3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dnabert2_h3k27me3 BertForSequenceClassification from zhangtaolab
+author: John Snow Labs
+name: dnabert2_h3k27me3
+date: 2024-12-19
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dnabert2_h3k27me3` is a English model originally trained by zhangtaolab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dnabert2_h3k27me3_en_5.5.1_3.0_1734571420747.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dnabert2_h3k27me3_en_5.5.1_3.0_1734571420747.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("dnabert2_h3k27me3","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("dnabert2_h3k27me3", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dnabert2_h3k27me3|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|333.0 MB|
+
+## References
+
+https://huggingface.co/zhangtaolab/dnabert2-H3K27me3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-dnabert2_h3k27me3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-dnabert2_h3k27me3_pipeline_en.md
new file mode 100644
index 00000000000000..1b13eac905ff9a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-dnabert2_h3k27me3_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dnabert2_h3k27me3_pipeline pipeline BertForSequenceClassification from zhangtaolab
+author: John Snow Labs
+name: dnabert2_h3k27me3_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dnabert2_h3k27me3_pipeline` is a English model originally trained by zhangtaolab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dnabert2_h3k27me3_pipeline_en_5.5.1_3.0_1734571437988.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dnabert2_h3k27me3_pipeline_en_5.5.1_3.0_1734571437988.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dnabert2_h3k27me3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dnabert2_h3k27me3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dnabert2_h3k27me3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|333.0 MB|
+
+## References
+
+https://huggingface.co/zhangtaolab/dnabert2-H3K27me3
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-dnabert2_lncrnas_en.md b/docs/_posts/ahmedlone127/2024-12-19-dnabert2_lncrnas_en.md
new file mode 100644
index 00000000000000..a7a5d42aa17c57
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-dnabert2_lncrnas_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dnabert2_lncrnas BertForSequenceClassification from zhangtaolab
+author: John Snow Labs
+name: dnabert2_lncrnas
+date: 2024-12-19
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dnabert2_lncrnas` is a English model originally trained by zhangtaolab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dnabert2_lncrnas_en_5.5.1_3.0_1734572057531.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dnabert2_lncrnas_en_5.5.1_3.0_1734572057531.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("dnabert2_lncrnas","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("dnabert2_lncrnas", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dnabert2_lncrnas|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|333.0 MB|
+
+## References
+
+https://huggingface.co/zhangtaolab/dnabert2-lncRNAs
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-dnabert2_lncrnas_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-dnabert2_lncrnas_pipeline_en.md
new file mode 100644
index 00000000000000..7b038c3867aed7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-dnabert2_lncrnas_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dnabert2_lncrnas_pipeline pipeline BertForSequenceClassification from zhangtaolab
+author: John Snow Labs
+name: dnabert2_lncrnas_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dnabert2_lncrnas_pipeline` is a English model originally trained by zhangtaolab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dnabert2_lncrnas_pipeline_en_5.5.1_3.0_1734572074510.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dnabert2_lncrnas_pipeline_en_5.5.1_3.0_1734572074510.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dnabert2_lncrnas_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dnabert2_lncrnas_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dnabert2_lncrnas_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|333.0 MB|
+
+## References
+
+https://huggingface.co/zhangtaolab/dnabert2-lncRNAs
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-dnabert2_promoter_en.md b/docs/_posts/ahmedlone127/2024-12-19-dnabert2_promoter_en.md
new file mode 100644
index 00000000000000..a81be65b3bfad2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-dnabert2_promoter_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dnabert2_promoter BertForSequenceClassification from zhangtaolab
+author: John Snow Labs
+name: dnabert2_promoter
+date: 2024-12-19
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dnabert2_promoter` is a English model originally trained by zhangtaolab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dnabert2_promoter_en_5.5.1_3.0_1734571148535.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dnabert2_promoter_en_5.5.1_3.0_1734571148535.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("dnabert2_promoter","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("dnabert2_promoter", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dnabert2_promoter|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|333.0 MB|
+
+## References
+
+https://huggingface.co/zhangtaolab/dnabert2-promoter
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-dnabert2_promoter_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-dnabert2_promoter_pipeline_en.md
new file mode 100644
index 00000000000000..4934a54044e241
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-dnabert2_promoter_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dnabert2_promoter_pipeline pipeline BertForSequenceClassification from zhangtaolab
+author: John Snow Labs
+name: dnabert2_promoter_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dnabert2_promoter_pipeline` is a English model originally trained by zhangtaolab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dnabert2_promoter_pipeline_en_5.5.1_3.0_1734571166388.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dnabert2_promoter_pipeline_en_5.5.1_3.0_1734571166388.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dnabert2_promoter_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dnabert2_promoter_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dnabert2_promoter_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|333.0 MB|
+
+## References
+
+https://huggingface.co/zhangtaolab/dnabert2-promoter
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-elonmusk_huggingtweets_en.md b/docs/_posts/ahmedlone127/2024-12-19-elonmusk_huggingtweets_en.md
new file mode 100644
index 00000000000000..0d0c1f4da1186c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-elonmusk_huggingtweets_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English elonmusk_huggingtweets GPT2Transformer from huggingtweets
+author: John Snow Labs
+name: elonmusk_huggingtweets
+date: 2024-12-19
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`elonmusk_huggingtweets` is a English model originally trained by huggingtweets.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/elonmusk_huggingtweets_en_5.5.1_3.0_1734592589267.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/elonmusk_huggingtweets_en_5.5.1_3.0_1734592589267.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("elonmusk_huggingtweets","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("elonmusk_huggingtweets","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|elonmusk_huggingtweets|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/huggingtweets/elonmusk
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-elonmusk_huggingtweets_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-elonmusk_huggingtweets_pipeline_en.md
new file mode 100644
index 00000000000000..de3d6404007a60
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-elonmusk_huggingtweets_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English elonmusk_huggingtweets_pipeline pipeline GPT2Transformer from huggingtweets
+author: John Snow Labs
+name: elonmusk_huggingtweets_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`elonmusk_huggingtweets_pipeline` is a English model originally trained by huggingtweets.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/elonmusk_huggingtweets_pipeline_en_5.5.1_3.0_1734592625121.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/elonmusk_huggingtweets_pipeline_en_5.5.1_3.0_1734592625121.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("elonmusk_huggingtweets_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("elonmusk_huggingtweets_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|elonmusk_huggingtweets_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/huggingtweets/elonmusk
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-encoder_user_v1_en.md b/docs/_posts/ahmedlone127/2024-12-19-encoder_user_v1_en.md
new file mode 100644
index 00000000000000..54b71e8f56523c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-encoder_user_v1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English encoder_user_v1 XlmRoBertaForSequenceClassification from seregadgl
+author: John Snow Labs
+name: encoder_user_v1
+date: 2024-12-19
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`encoder_user_v1` is a English model originally trained by seregadgl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/encoder_user_v1_en_5.5.1_3.0_1734598310723.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/encoder_user_v1_en_5.5.1_3.0_1734598310723.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("encoder_user_v1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("encoder_user_v1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|encoder_user_v1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/seregadgl/encoder_user_v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-encoder_user_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-encoder_user_v1_pipeline_en.md
new file mode 100644
index 00000000000000..ea889dc52e29c8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-encoder_user_v1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English encoder_user_v1_pipeline pipeline XlmRoBertaForSequenceClassification from seregadgl
+author: John Snow Labs
+name: encoder_user_v1_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`encoder_user_v1_pipeline` is a English model originally trained by seregadgl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/encoder_user_v1_pipeline_en_5.5.1_3.0_1734598380497.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/encoder_user_v1_pipeline_en_5.5.1_3.0_1734598380497.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("encoder_user_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("encoder_user_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|encoder_user_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/seregadgl/encoder_user_v1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-english_tonga_tonga_islands_dzo_helsinki_nlp_m2_norphel_en.md b/docs/_posts/ahmedlone127/2024-12-19-english_tonga_tonga_islands_dzo_helsinki_nlp_m2_norphel_en.md
new file mode 100644
index 00000000000000..4fd58fd2a8a3d7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-english_tonga_tonga_islands_dzo_helsinki_nlp_m2_norphel_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English english_tonga_tonga_islands_dzo_helsinki_nlp_m2_norphel MarianTransformer from Norphel
+author: John Snow Labs
+name: english_tonga_tonga_islands_dzo_helsinki_nlp_m2_norphel
+date: 2024-12-19
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_tonga_tonga_islands_dzo_helsinki_nlp_m2_norphel` is a English model originally trained by Norphel.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/english_tonga_tonga_islands_dzo_helsinki_nlp_m2_norphel_en_5.5.1_3.0_1734588247770.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_tonga_tonga_islands_dzo_helsinki_nlp_m2_norphel_en_5.5.1_3.0_1734588247770.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("english_tonga_tonga_islands_dzo_helsinki_nlp_m2_norphel","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("english_tonga_tonga_islands_dzo_helsinki_nlp_m2_norphel","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|english_tonga_tonga_islands_dzo_helsinki_nlp_m2_norphel|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/Norphel/en_to_dzo_helsinki_nlp_m2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-english_tonga_tonga_islands_dzo_helsinki_nlp_m2_norphel_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-english_tonga_tonga_islands_dzo_helsinki_nlp_m2_norphel_pipeline_en.md
new file mode 100644
index 00000000000000..f583cace8ef3bd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-english_tonga_tonga_islands_dzo_helsinki_nlp_m2_norphel_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English english_tonga_tonga_islands_dzo_helsinki_nlp_m2_norphel_pipeline pipeline MarianTransformer from Norphel
+author: John Snow Labs
+name: english_tonga_tonga_islands_dzo_helsinki_nlp_m2_norphel_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_tonga_tonga_islands_dzo_helsinki_nlp_m2_norphel_pipeline` is a English model originally trained by Norphel.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/english_tonga_tonga_islands_dzo_helsinki_nlp_m2_norphel_pipeline_en_5.5.1_3.0_1734588317620.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_tonga_tonga_islands_dzo_helsinki_nlp_m2_norphel_pipeline_en_5.5.1_3.0_1734588317620.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("english_tonga_tonga_islands_dzo_helsinki_nlp_m2_norphel_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("english_tonga_tonga_islands_dzo_helsinki_nlp_m2_norphel_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|english_tonga_tonga_islands_dzo_helsinki_nlp_m2_norphel_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/Norphel/en_to_dzo_helsinki_nlp_m2
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-english_tonga_tonga_islands_dzo_helsinki_nlp_m2_zeref02210217_cst_en.md b/docs/_posts/ahmedlone127/2024-12-19-english_tonga_tonga_islands_dzo_helsinki_nlp_m2_zeref02210217_cst_en.md
new file mode 100644
index 00000000000000..624125ddaba849
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-english_tonga_tonga_islands_dzo_helsinki_nlp_m2_zeref02210217_cst_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English english_tonga_tonga_islands_dzo_helsinki_nlp_m2_zeref02210217_cst MarianTransformer from Zeref02210217-cst
+author: John Snow Labs
+name: english_tonga_tonga_islands_dzo_helsinki_nlp_m2_zeref02210217_cst
+date: 2024-12-19
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_tonga_tonga_islands_dzo_helsinki_nlp_m2_zeref02210217_cst` is a English model originally trained by Zeref02210217-cst.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/english_tonga_tonga_islands_dzo_helsinki_nlp_m2_zeref02210217_cst_en_5.5.1_3.0_1734588187034.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_tonga_tonga_islands_dzo_helsinki_nlp_m2_zeref02210217_cst_en_5.5.1_3.0_1734588187034.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("english_tonga_tonga_islands_dzo_helsinki_nlp_m2_zeref02210217_cst","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("english_tonga_tonga_islands_dzo_helsinki_nlp_m2_zeref02210217_cst","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|english_tonga_tonga_islands_dzo_helsinki_nlp_m2_zeref02210217_cst|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/Zeref02210217-cst/en_to_dzo_helsinki_nlp_m2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-english_tonga_tonga_islands_dzo_helsinki_nlp_m2_zeref02210217_cst_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-english_tonga_tonga_islands_dzo_helsinki_nlp_m2_zeref02210217_cst_pipeline_en.md
new file mode 100644
index 00000000000000..e613bec26dd2e6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-english_tonga_tonga_islands_dzo_helsinki_nlp_m2_zeref02210217_cst_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English english_tonga_tonga_islands_dzo_helsinki_nlp_m2_zeref02210217_cst_pipeline pipeline MarianTransformer from Zeref02210217-cst
+author: John Snow Labs
+name: english_tonga_tonga_islands_dzo_helsinki_nlp_m2_zeref02210217_cst_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_tonga_tonga_islands_dzo_helsinki_nlp_m2_zeref02210217_cst_pipeline` is a English model originally trained by Zeref02210217-cst.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/english_tonga_tonga_islands_dzo_helsinki_nlp_m2_zeref02210217_cst_pipeline_en_5.5.1_3.0_1734588246130.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_tonga_tonga_islands_dzo_helsinki_nlp_m2_zeref02210217_cst_pipeline_en_5.5.1_3.0_1734588246130.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("english_tonga_tonga_islands_dzo_helsinki_nlp_m2_zeref02210217_cst_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("english_tonga_tonga_islands_dzo_helsinki_nlp_m2_zeref02210217_cst_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|english_tonga_tonga_islands_dzo_helsinki_nlp_m2_zeref02210217_cst_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/Zeref02210217-cst/en_to_dzo_helsinki_nlp_m2
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-english_tonga_tonga_islands_dzo_helsinki_nlp_m_en.md b/docs/_posts/ahmedlone127/2024-12-19-english_tonga_tonga_islands_dzo_helsinki_nlp_m_en.md
new file mode 100644
index 00000000000000..d039deabd28716
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-english_tonga_tonga_islands_dzo_helsinki_nlp_m_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English english_tonga_tonga_islands_dzo_helsinki_nlp_m MarianTransformer from Norphel
+author: John Snow Labs
+name: english_tonga_tonga_islands_dzo_helsinki_nlp_m
+date: 2024-12-19
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_tonga_tonga_islands_dzo_helsinki_nlp_m` is a English model originally trained by Norphel.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/english_tonga_tonga_islands_dzo_helsinki_nlp_m_en_5.5.1_3.0_1734588306825.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_tonga_tonga_islands_dzo_helsinki_nlp_m_en_5.5.1_3.0_1734588306825.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("english_tonga_tonga_islands_dzo_helsinki_nlp_m","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("english_tonga_tonga_islands_dzo_helsinki_nlp_m","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|english_tonga_tonga_islands_dzo_helsinki_nlp_m|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/Norphel/en_to_dzo_helsinki_nlp_m
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-english_tonga_tonga_islands_dzo_helsinki_nlp_m_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-english_tonga_tonga_islands_dzo_helsinki_nlp_m_pipeline_en.md
new file mode 100644
index 00000000000000..647ab0fae908b8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-english_tonga_tonga_islands_dzo_helsinki_nlp_m_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English english_tonga_tonga_islands_dzo_helsinki_nlp_m_pipeline pipeline MarianTransformer from Norphel
+author: John Snow Labs
+name: english_tonga_tonga_islands_dzo_helsinki_nlp_m_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_tonga_tonga_islands_dzo_helsinki_nlp_m_pipeline` is a English model originally trained by Norphel.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/english_tonga_tonga_islands_dzo_helsinki_nlp_m_pipeline_en_5.5.1_3.0_1734588367932.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_tonga_tonga_islands_dzo_helsinki_nlp_m_pipeline_en_5.5.1_3.0_1734588367932.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("english_tonga_tonga_islands_dzo_helsinki_nlp_m_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("english_tonga_tonga_islands_dzo_helsinki_nlp_m_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|english_tonga_tonga_islands_dzo_helsinki_nlp_m_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/Norphel/en_to_dzo_helsinki_nlp_m
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-exp_w2v2t_chinese_cn_hubert_s149_en.md b/docs/_posts/ahmedlone127/2024-12-19-exp_w2v2t_chinese_cn_hubert_s149_en.md
new file mode 100644
index 00000000000000..3297d04b8d448b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-exp_w2v2t_chinese_cn_hubert_s149_en.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: English exp_w2v2t_chinese_cn_hubert_s149 HubertForCTC from jonatasgrosman
+author: John Snow Labs
+name: exp_w2v2t_chinese_cn_hubert_s149
+date: 2024-12-19
+tags: [en, open_source, onnx, asr, hubert]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: HubertForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`exp_w2v2t_chinese_cn_hubert_s149` is a English model originally trained by jonatasgrosman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/exp_w2v2t_chinese_cn_hubert_s149_en_5.5.1_3.0_1734600470470.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/exp_w2v2t_chinese_cn_hubert_s149_en_5.5.1_3.0_1734600470470.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = HubertForCTC.pretrained("exp_w2v2t_chinese_cn_hubert_s149","en") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = HubertForCTC.pretrained("exp_w2v2t_chinese_cn_hubert_s149", "en")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|exp_w2v2t_chinese_cn_hubert_s149|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|en|
+|Size:|2.4 GB|
+
+## References
+
+https://huggingface.co/jonatasgrosman/exp_w2v2t_zh-cn_hubert_s149
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-exp_w2v2t_chinese_cn_hubert_s149_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-exp_w2v2t_chinese_cn_hubert_s149_pipeline_en.md
new file mode 100644
index 00000000000000..e9101c79230388
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-exp_w2v2t_chinese_cn_hubert_s149_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English exp_w2v2t_chinese_cn_hubert_s149_pipeline pipeline HubertForCTC from jonatasgrosman
+author: John Snow Labs
+name: exp_w2v2t_chinese_cn_hubert_s149_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`exp_w2v2t_chinese_cn_hubert_s149_pipeline` is a English model originally trained by jonatasgrosman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/exp_w2v2t_chinese_cn_hubert_s149_pipeline_en_5.5.1_3.0_1734600595730.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/exp_w2v2t_chinese_cn_hubert_s149_pipeline_en_5.5.1_3.0_1734600595730.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("exp_w2v2t_chinese_cn_hubert_s149_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("exp_w2v2t_chinese_cn_hubert_s149_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|exp_w2v2t_chinese_cn_hubert_s149_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|2.4 GB|
+
+## References
+
+https://huggingface.co/jonatasgrosman/exp_w2v2t_zh-cn_hubert_s149
+
+## Included Models
+
+- AudioAssembler
+- HubertForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-exp_w2v2t_chinese_cn_hubert_s449_en.md b/docs/_posts/ahmedlone127/2024-12-19-exp_w2v2t_chinese_cn_hubert_s449_en.md
new file mode 100644
index 00000000000000..a63be5cb24889d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-exp_w2v2t_chinese_cn_hubert_s449_en.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: English exp_w2v2t_chinese_cn_hubert_s449 HubertForCTC from jonatasgrosman
+author: John Snow Labs
+name: exp_w2v2t_chinese_cn_hubert_s449
+date: 2024-12-19
+tags: [en, open_source, onnx, asr, hubert]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: HubertForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`exp_w2v2t_chinese_cn_hubert_s449` is a English model originally trained by jonatasgrosman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/exp_w2v2t_chinese_cn_hubert_s449_en_5.5.1_3.0_1734600340948.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/exp_w2v2t_chinese_cn_hubert_s449_en_5.5.1_3.0_1734600340948.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = HubertForCTC.pretrained("exp_w2v2t_chinese_cn_hubert_s449","en") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = HubertForCTC.pretrained("exp_w2v2t_chinese_cn_hubert_s449", "en")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|exp_w2v2t_chinese_cn_hubert_s449|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|en|
+|Size:|2.4 GB|
+
+## References
+
+https://huggingface.co/jonatasgrosman/exp_w2v2t_zh-cn_hubert_s449
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-exp_w2v2t_chinese_cn_hubert_s449_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-exp_w2v2t_chinese_cn_hubert_s449_pipeline_en.md
new file mode 100644
index 00000000000000..16e3ea1cd82c8a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-exp_w2v2t_chinese_cn_hubert_s449_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English exp_w2v2t_chinese_cn_hubert_s449_pipeline pipeline HubertForCTC from jonatasgrosman
+author: John Snow Labs
+name: exp_w2v2t_chinese_cn_hubert_s449_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`exp_w2v2t_chinese_cn_hubert_s449_pipeline` is a English model originally trained by jonatasgrosman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/exp_w2v2t_chinese_cn_hubert_s449_pipeline_en_5.5.1_3.0_1734600479600.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/exp_w2v2t_chinese_cn_hubert_s449_pipeline_en_5.5.1_3.0_1734600479600.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("exp_w2v2t_chinese_cn_hubert_s449_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("exp_w2v2t_chinese_cn_hubert_s449_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|exp_w2v2t_chinese_cn_hubert_s449_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|2.4 GB|
+
+## References
+
+https://huggingface.co/jonatasgrosman/exp_w2v2t_zh-cn_hubert_s449
+
+## Included Models
+
+- AudioAssembler
+- HubertForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-exp_w2v2t_english_hubert_s877_en.md b/docs/_posts/ahmedlone127/2024-12-19-exp_w2v2t_english_hubert_s877_en.md
new file mode 100644
index 00000000000000..26a411451b42a1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-exp_w2v2t_english_hubert_s877_en.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: English exp_w2v2t_english_hubert_s877 HubertForCTC from jonatasgrosman
+author: John Snow Labs
+name: exp_w2v2t_english_hubert_s877
+date: 2024-12-19
+tags: [en, open_source, onnx, asr, hubert]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: HubertForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`exp_w2v2t_english_hubert_s877` is a English model originally trained by jonatasgrosman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/exp_w2v2t_english_hubert_s877_en_5.5.1_3.0_1734600223864.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/exp_w2v2t_english_hubert_s877_en_5.5.1_3.0_1734600223864.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = HubertForCTC.pretrained("exp_w2v2t_english_hubert_s877","en") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = HubertForCTC.pretrained("exp_w2v2t_english_hubert_s877", "en")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|exp_w2v2t_english_hubert_s877|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|en|
+|Size:|2.4 GB|
+
+## References
+
+https://huggingface.co/jonatasgrosman/exp_w2v2t_en_hubert_s877
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-exp_w2v2t_english_hubert_s877_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-exp_w2v2t_english_hubert_s877_pipeline_en.md
new file mode 100644
index 00000000000000..3d5e32d0765b7f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-exp_w2v2t_english_hubert_s877_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English exp_w2v2t_english_hubert_s877_pipeline pipeline HubertForCTC from jonatasgrosman
+author: John Snow Labs
+name: exp_w2v2t_english_hubert_s877_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`exp_w2v2t_english_hubert_s877_pipeline` is a English model originally trained by jonatasgrosman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/exp_w2v2t_english_hubert_s877_pipeline_en_5.5.1_3.0_1734600338521.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/exp_w2v2t_english_hubert_s877_pipeline_en_5.5.1_3.0_1734600338521.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("exp_w2v2t_english_hubert_s877_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("exp_w2v2t_english_hubert_s877_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|exp_w2v2t_english_hubert_s877_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|2.4 GB|
+
+## References
+
+https://huggingface.co/jonatasgrosman/exp_w2v2t_en_hubert_s877
+
+## Included Models
+
+- AudioAssembler
+- HubertForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-exp_w2v2t_japanese_hubert_s69_ja.md b/docs/_posts/ahmedlone127/2024-12-19-exp_w2v2t_japanese_hubert_s69_ja.md
new file mode 100644
index 00000000000000..6a344b4bafc09a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-exp_w2v2t_japanese_hubert_s69_ja.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Japanese exp_w2v2t_japanese_hubert_s69 HubertForCTC from jonatasgrosman
+author: John Snow Labs
+name: exp_w2v2t_japanese_hubert_s69
+date: 2024-12-19
+tags: [ja, open_source, onnx, asr, hubert]
+task: Automatic Speech Recognition
+language: ja
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: HubertForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`exp_w2v2t_japanese_hubert_s69` is a Japanese model originally trained by jonatasgrosman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/exp_w2v2t_japanese_hubert_s69_ja_5.5.1_3.0_1734599985683.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/exp_w2v2t_japanese_hubert_s69_ja_5.5.1_3.0_1734599985683.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = HubertForCTC.pretrained("exp_w2v2t_japanese_hubert_s69","ja") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = HubertForCTC.pretrained("exp_w2v2t_japanese_hubert_s69", "ja")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|exp_w2v2t_japanese_hubert_s69|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|ja|
+|Size:|2.4 GB|
+
+## References
+
+https://huggingface.co/jonatasgrosman/exp_w2v2t_ja_hubert_s69
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-exp_w2v2t_japanese_hubert_s69_pipeline_ja.md b/docs/_posts/ahmedlone127/2024-12-19-exp_w2v2t_japanese_hubert_s69_pipeline_ja.md
new file mode 100644
index 00000000000000..4f21d28c980f3c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-exp_w2v2t_japanese_hubert_s69_pipeline_ja.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Japanese exp_w2v2t_japanese_hubert_s69_pipeline pipeline HubertForCTC from jonatasgrosman
+author: John Snow Labs
+name: exp_w2v2t_japanese_hubert_s69_pipeline
+date: 2024-12-19
+tags: [ja, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: ja
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`exp_w2v2t_japanese_hubert_s69_pipeline` is a Japanese model originally trained by jonatasgrosman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/exp_w2v2t_japanese_hubert_s69_pipeline_ja_5.5.1_3.0_1734600100619.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/exp_w2v2t_japanese_hubert_s69_pipeline_ja_5.5.1_3.0_1734600100619.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("exp_w2v2t_japanese_hubert_s69_pipeline", lang = "ja")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("exp_w2v2t_japanese_hubert_s69_pipeline", lang = "ja")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|exp_w2v2t_japanese_hubert_s69_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ja|
+|Size:|2.4 GB|
+
+## References
+
+https://huggingface.co/jonatasgrosman/exp_w2v2t_ja_hubert_s69
+
+## Included Models
+
+- AudioAssembler
+- HubertForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-exp_w2v2t_spanish_hubert_s251_es.md b/docs/_posts/ahmedlone127/2024-12-19-exp_w2v2t_spanish_hubert_s251_es.md
new file mode 100644
index 00000000000000..393a68b27b3207
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-exp_w2v2t_spanish_hubert_s251_es.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Castilian, Spanish exp_w2v2t_spanish_hubert_s251 HubertForCTC from jonatasgrosman
+author: John Snow Labs
+name: exp_w2v2t_spanish_hubert_s251
+date: 2024-12-19
+tags: [es, open_source, onnx, asr, hubert]
+task: Automatic Speech Recognition
+language: es
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: HubertForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`exp_w2v2t_spanish_hubert_s251` is a Castilian, Spanish model originally trained by jonatasgrosman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/exp_w2v2t_spanish_hubert_s251_es_5.5.1_3.0_1734599722920.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/exp_w2v2t_spanish_hubert_s251_es_5.5.1_3.0_1734599722920.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = HubertForCTC.pretrained("exp_w2v2t_spanish_hubert_s251","es") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = HubertForCTC.pretrained("exp_w2v2t_spanish_hubert_s251", "es")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|exp_w2v2t_spanish_hubert_s251|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|es|
+|Size:|2.4 GB|
+
+## References
+
+https://huggingface.co/jonatasgrosman/exp_w2v2t_es_hubert_s251
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-exp_w2v2t_spanish_hubert_s251_pipeline_es.md b/docs/_posts/ahmedlone127/2024-12-19-exp_w2v2t_spanish_hubert_s251_pipeline_es.md
new file mode 100644
index 00000000000000..6fa1432c0511a0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-exp_w2v2t_spanish_hubert_s251_pipeline_es.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Castilian, Spanish exp_w2v2t_spanish_hubert_s251_pipeline pipeline HubertForCTC from jonatasgrosman
+author: John Snow Labs
+name: exp_w2v2t_spanish_hubert_s251_pipeline
+date: 2024-12-19
+tags: [es, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: es
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`exp_w2v2t_spanish_hubert_s251_pipeline` is a Castilian, Spanish model originally trained by jonatasgrosman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/exp_w2v2t_spanish_hubert_s251_pipeline_es_5.5.1_3.0_1734599840885.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/exp_w2v2t_spanish_hubert_s251_pipeline_es_5.5.1_3.0_1734599840885.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("exp_w2v2t_spanish_hubert_s251_pipeline", lang = "es")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("exp_w2v2t_spanish_hubert_s251_pipeline", lang = "es")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|exp_w2v2t_spanish_hubert_s251_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|es|
+|Size:|2.4 GB|
+
+## References
+
+https://huggingface.co/jonatasgrosman/exp_w2v2t_es_hubert_s251
+
+## Included Models
+
+- AudioAssembler
+- HubertForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-exp_w2v2t_thai_hubert_s817_pipeline_th.md b/docs/_posts/ahmedlone127/2024-12-19-exp_w2v2t_thai_hubert_s817_pipeline_th.md
new file mode 100644
index 00000000000000..080f9480edf2c7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-exp_w2v2t_thai_hubert_s817_pipeline_th.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Thai exp_w2v2t_thai_hubert_s817_pipeline pipeline HubertForCTC from jonatasgrosman
+author: John Snow Labs
+name: exp_w2v2t_thai_hubert_s817_pipeline
+date: 2024-12-19
+tags: [th, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: th
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`exp_w2v2t_thai_hubert_s817_pipeline` is a Thai model originally trained by jonatasgrosman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/exp_w2v2t_thai_hubert_s817_pipeline_th_5.5.1_3.0_1734599819949.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/exp_w2v2t_thai_hubert_s817_pipeline_th_5.5.1_3.0_1734599819949.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("exp_w2v2t_thai_hubert_s817_pipeline", lang = "th")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("exp_w2v2t_thai_hubert_s817_pipeline", lang = "th")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|exp_w2v2t_thai_hubert_s817_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|th|
+|Size:|2.4 GB|
+
+## References
+
+https://huggingface.co/jonatasgrosman/exp_w2v2t_th_hubert_s817
+
+## Included Models
+
+- AudioAssembler
+- HubertForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-exp_w2v2t_thai_hubert_s817_th.md b/docs/_posts/ahmedlone127/2024-12-19-exp_w2v2t_thai_hubert_s817_th.md
new file mode 100644
index 00000000000000..bb8eef380c06bf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-exp_w2v2t_thai_hubert_s817_th.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Thai exp_w2v2t_thai_hubert_s817 HubertForCTC from jonatasgrosman
+author: John Snow Labs
+name: exp_w2v2t_thai_hubert_s817
+date: 2024-12-19
+tags: [th, open_source, onnx, asr, hubert]
+task: Automatic Speech Recognition
+language: th
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: HubertForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`exp_w2v2t_thai_hubert_s817` is a Thai model originally trained by jonatasgrosman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/exp_w2v2t_thai_hubert_s817_th_5.5.1_3.0_1734599699606.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/exp_w2v2t_thai_hubert_s817_th_5.5.1_3.0_1734599699606.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = HubertForCTC.pretrained("exp_w2v2t_thai_hubert_s817","th") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = HubertForCTC.pretrained("exp_w2v2t_thai_hubert_s817", "th")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|exp_w2v2t_thai_hubert_s817|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|th|
+|Size:|2.4 GB|
+
+## References
+
+https://huggingface.co/jonatasgrosman/exp_w2v2t_th_hubert_s817
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-exp_w2v2t_thai_hubert_s975_pipeline_th.md b/docs/_posts/ahmedlone127/2024-12-19-exp_w2v2t_thai_hubert_s975_pipeline_th.md
new file mode 100644
index 00000000000000..df8bc76f67f427
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-exp_w2v2t_thai_hubert_s975_pipeline_th.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Thai exp_w2v2t_thai_hubert_s975_pipeline pipeline HubertForCTC from jonatasgrosman
+author: John Snow Labs
+name: exp_w2v2t_thai_hubert_s975_pipeline
+date: 2024-12-19
+tags: [th, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: th
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`exp_w2v2t_thai_hubert_s975_pipeline` is a Thai model originally trained by jonatasgrosman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/exp_w2v2t_thai_hubert_s975_pipeline_th_5.5.1_3.0_1734599937371.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/exp_w2v2t_thai_hubert_s975_pipeline_th_5.5.1_3.0_1734599937371.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("exp_w2v2t_thai_hubert_s975_pipeline", lang = "th")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("exp_w2v2t_thai_hubert_s975_pipeline", lang = "th")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|exp_w2v2t_thai_hubert_s975_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|th|
+|Size:|2.4 GB|
+
+## References
+
+https://huggingface.co/jonatasgrosman/exp_w2v2t_th_hubert_s975
+
+## Included Models
+
+- AudioAssembler
+- HubertForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-exp_w2v2t_thai_hubert_s975_th.md b/docs/_posts/ahmedlone127/2024-12-19-exp_w2v2t_thai_hubert_s975_th.md
new file mode 100644
index 00000000000000..99ec0f9ea7682d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-exp_w2v2t_thai_hubert_s975_th.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Thai exp_w2v2t_thai_hubert_s975 HubertForCTC from jonatasgrosman
+author: John Snow Labs
+name: exp_w2v2t_thai_hubert_s975
+date: 2024-12-19
+tags: [th, open_source, onnx, asr, hubert]
+task: Automatic Speech Recognition
+language: th
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: HubertForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`exp_w2v2t_thai_hubert_s975` is a Thai model originally trained by jonatasgrosman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/exp_w2v2t_thai_hubert_s975_th_5.5.1_3.0_1734599807750.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/exp_w2v2t_thai_hubert_s975_th_5.5.1_3.0_1734599807750.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = HubertForCTC.pretrained("exp_w2v2t_thai_hubert_s975","th") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = HubertForCTC.pretrained("exp_w2v2t_thai_hubert_s975", "th")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|exp_w2v2t_thai_hubert_s975|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|th|
+|Size:|2.4 GB|
+
+## References
+
+https://huggingface.co/jonatasgrosman/exp_w2v2t_th_hubert_s975
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-fake_text_detector_model_en.md b/docs/_posts/ahmedlone127/2024-12-19-fake_text_detector_model_en.md
new file mode 100644
index 00000000000000..9626ec6e43a3db
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-fake_text_detector_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English fake_text_detector_model XlmRoBertaForSequenceClassification from TVI
+author: John Snow Labs
+name: fake_text_detector_model
+date: 2024-12-19
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fake_text_detector_model` is a English model originally trained by TVI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fake_text_detector_model_en_5.5.1_3.0_1734596164216.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fake_text_detector_model_en_5.5.1_3.0_1734596164216.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("fake_text_detector_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("fake_text_detector_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fake_text_detector_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|883.1 MB|
+
+## References
+
+https://huggingface.co/TVI/fake-text-detector-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-fake_text_detector_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-fake_text_detector_model_pipeline_en.md
new file mode 100644
index 00000000000000..fa16a25453fc62
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-fake_text_detector_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English fake_text_detector_model_pipeline pipeline XlmRoBertaForSequenceClassification from TVI
+author: John Snow Labs
+name: fake_text_detector_model_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fake_text_detector_model_pipeline` is a English model originally trained by TVI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fake_text_detector_model_pipeline_en_5.5.1_3.0_1734596224184.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fake_text_detector_model_pipeline_en_5.5.1_3.0_1734596224184.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fake_text_detector_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fake_text_detector_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fake_text_detector_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|883.1 MB|
+
+## References
+
+https://huggingface.co/TVI/fake-text-detector-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-fine_tuned_bert_financial_sentiment_analysis_en.md b/docs/_posts/ahmedlone127/2024-12-19-fine_tuned_bert_financial_sentiment_analysis_en.md
new file mode 100644
index 00000000000000..2010ad32950eeb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-fine_tuned_bert_financial_sentiment_analysis_en.md
@@ -0,0 +1,98 @@
+---
+layout: model
+title: English fine_tuned_bert_financial_sentiment_analysis BertForSequenceClassification from mstafam
+author: John Snow Labs
+name: fine_tuned_bert_financial_sentiment_analysis
+date: 2024-12-19
+tags: [bert, en, open_source, sequence_classification, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_bert_financial_sentiment_analysis` is a English model originally trained by mstafam.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_bert_financial_sentiment_analysis_en_5.5.1_3.0_1734571627483.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_bert_financial_sentiment_analysis_en_5.5.1_3.0_1734571627483.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = DocumentAssembler()\
+    .setInputCol("text")\
+    .setOutputCol("document")
+
+tokenizer = Tokenizer()\
+    .setInputCols("document")\
+    .setOutputCol("token")  
+    
+sequenceClassifier = BertForSequenceClassification.pretrained("fine_tuned_bert_financial_sentiment_analysis","en")\
+            .setInputCols(["document","token"])\
+            .setOutputCol("class")
+
+pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val document_assembler = new DocumentAssembler()
+    .setInputCol("text")
+    .setOutputCol("document")
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document") 
+    .setOutputCol("token")  
+    
+val sequenceClassifier = BertForSequenceClassification.pretrained("fine_tuned_bert_financial_sentiment_analysis","en")
+            .setInputCols(Array("document","token"))
+            .setOutputCol("class")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_bert_financial_sentiment_analysis|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+References
+
+https://huggingface.co/mstafam/fine-tuned-bert-financial-sentiment-analysis
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-fine_tuned_bert_financial_sentiment_analysis_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-fine_tuned_bert_financial_sentiment_analysis_pipeline_en.md
new file mode 100644
index 00000000000000..c3bbb13acb3952
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-fine_tuned_bert_financial_sentiment_analysis_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English fine_tuned_bert_financial_sentiment_analysis_pipeline pipeline BertForSequenceClassification from stfamod
+author: John Snow Labs
+name: fine_tuned_bert_financial_sentiment_analysis_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_bert_financial_sentiment_analysis_pipeline` is a English model originally trained by stfamod.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_bert_financial_sentiment_analysis_pipeline_en_5.5.1_3.0_1734571648322.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_bert_financial_sentiment_analysis_pipeline_en_5.5.1_3.0_1734571648322.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fine_tuned_bert_financial_sentiment_analysis_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fine_tuned_bert_financial_sentiment_analysis_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_bert_financial_sentiment_analysis_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/stfamod/fine-tuned-bert-financial-sentiment-analysis
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-fine_tuned_marbertv2_en.md b/docs/_posts/ahmedlone127/2024-12-19-fine_tuned_marbertv2_en.md
new file mode 100644
index 00000000000000..70716fcf56e636
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-fine_tuned_marbertv2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English fine_tuned_marbertv2 BertForSequenceClassification from MN-Alrasheedy
+author: John Snow Labs
+name: fine_tuned_marbertv2
+date: 2024-12-19
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_marbertv2` is a English model originally trained by MN-Alrasheedy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_marbertv2_en_5.5.1_3.0_1734571090938.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_marbertv2_en_5.5.1_3.0_1734571090938.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("fine_tuned_marbertv2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("fine_tuned_marbertv2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_marbertv2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|608.8 MB|
+
+## References
+
+https://huggingface.co/MN-Alrasheedy/fine-tuned-MARBERTv2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-fine_tuned_marbertv2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-fine_tuned_marbertv2_pipeline_en.md
new file mode 100644
index 00000000000000..c66fb68be144b5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-fine_tuned_marbertv2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English fine_tuned_marbertv2_pipeline pipeline BertForSequenceClassification from MN-Alrasheedy
+author: John Snow Labs
+name: fine_tuned_marbertv2_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_marbertv2_pipeline` is a English model originally trained by MN-Alrasheedy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_marbertv2_pipeline_en_5.5.1_3.0_1734571121964.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_marbertv2_pipeline_en_5.5.1_3.0_1734571121964.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fine_tuned_marbertv2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fine_tuned_marbertv2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_marbertv2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|608.8 MB|
+
+## References
+
+https://huggingface.co/MN-Alrasheedy/fine-tuned-MARBERTv2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-fine_tuned_t5_small_model_miasetya_en.md b/docs/_posts/ahmedlone127/2024-12-19-fine_tuned_t5_small_model_miasetya_en.md
new file mode 100644
index 00000000000000..260e3dd6d1b067
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-fine_tuned_t5_small_model_miasetya_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English fine_tuned_t5_small_model_miasetya T5Transformer from miasetya
+author: John Snow Labs
+name: fine_tuned_t5_small_model_miasetya
+date: 2024-12-19
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_t5_small_model_miasetya` is a English model originally trained by miasetya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_small_model_miasetya_en_5.5.1_3.0_1734567427818.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_small_model_miasetya_en_5.5.1_3.0_1734567427818.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("fine_tuned_t5_small_model_miasetya","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("fine_tuned_t5_small_model_miasetya", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_t5_small_model_miasetya|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|261.0 MB|
+
+## References
+
+https://huggingface.co/miasetya/fine_tuned_t5_small_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-fine_tuned_t5_small_model_miasetya_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-fine_tuned_t5_small_model_miasetya_pipeline_en.md
new file mode 100644
index 00000000000000..4a782aee93d250
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-fine_tuned_t5_small_model_miasetya_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English fine_tuned_t5_small_model_miasetya_pipeline pipeline T5Transformer from miasetya
+author: John Snow Labs
+name: fine_tuned_t5_small_model_miasetya_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_t5_small_model_miasetya_pipeline` is a English model originally trained by miasetya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_small_model_miasetya_pipeline_en_5.5.1_3.0_1734567448345.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_small_model_miasetya_pipeline_en_5.5.1_3.0_1734567448345.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fine_tuned_t5_small_model_miasetya_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fine_tuned_t5_small_model_miasetya_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_t5_small_model_miasetya_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|261.0 MB|
+
+## References
+
+https://huggingface.co/miasetya/fine_tuned_t5_small_model
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-fine_tuned_t5_small_model_sec_5_v8_en.md b/docs/_posts/ahmedlone127/2024-12-19-fine_tuned_t5_small_model_sec_5_v8_en.md
new file mode 100644
index 00000000000000..a2180a12a382eb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-fine_tuned_t5_small_model_sec_5_v8_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English fine_tuned_t5_small_model_sec_5_v8 T5Transformer from miasetya
+author: John Snow Labs
+name: fine_tuned_t5_small_model_sec_5_v8
+date: 2024-12-19
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_t5_small_model_sec_5_v8` is a English model originally trained by miasetya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_small_model_sec_5_v8_en_5.5.1_3.0_1734568123234.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_small_model_sec_5_v8_en_5.5.1_3.0_1734568123234.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("fine_tuned_t5_small_model_sec_5_v8","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("fine_tuned_t5_small_model_sec_5_v8", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_t5_small_model_sec_5_v8|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|258.2 MB|
+
+## References
+
+https://huggingface.co/miasetya/fine_tuned_t5_small_model_sec_5_v8
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-fine_tuned_t5_small_model_sec_5_v8_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-fine_tuned_t5_small_model_sec_5_v8_pipeline_en.md
new file mode 100644
index 00000000000000..e0d09d02a9f9a5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-fine_tuned_t5_small_model_sec_5_v8_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English fine_tuned_t5_small_model_sec_5_v8_pipeline pipeline T5Transformer from miasetya
+author: John Snow Labs
+name: fine_tuned_t5_small_model_sec_5_v8_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_t5_small_model_sec_5_v8_pipeline` is a English model originally trained by miasetya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_small_model_sec_5_v8_pipeline_en_5.5.1_3.0_1734568143213.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_small_model_sec_5_v8_pipeline_en_5.5.1_3.0_1734568143213.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fine_tuned_t5_small_model_sec_5_v8_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fine_tuned_t5_small_model_sec_5_v8_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_t5_small_model_sec_5_v8_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|258.2 MB|
+
+## References
+
+https://huggingface.co/miasetya/fine_tuned_t5_small_model_sec_5_v8
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-finetuned_gpt2_sst2_negation0_05_en.md b/docs/_posts/ahmedlone127/2024-12-19-finetuned_gpt2_sst2_negation0_05_en.md
new file mode 100644
index 00000000000000..72102ce4af2d49
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-finetuned_gpt2_sst2_negation0_05_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English finetuned_gpt2_sst2_negation0_05 GPT2Transformer from yuhuizhang
+author: John Snow Labs
+name: finetuned_gpt2_sst2_negation0_05
+date: 2024-12-19
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_gpt2_sst2_negation0_05` is a English model originally trained by yuhuizhang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_gpt2_sst2_negation0_05_en_5.5.1_3.0_1734589160130.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_gpt2_sst2_negation0_05_en_5.5.1_3.0_1734589160130.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("finetuned_gpt2_sst2_negation0_05","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("finetuned_gpt2_sst2_negation0_05","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_gpt2_sst2_negation0_05|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/yuhuizhang/finetuned_gpt2_sst2_negation0.05
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-finetuned_gpt2_sst2_negation0_05_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-finetuned_gpt2_sst2_negation0_05_pipeline_en.md
new file mode 100644
index 00000000000000..af7a1f789f191e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-finetuned_gpt2_sst2_negation0_05_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English finetuned_gpt2_sst2_negation0_05_pipeline pipeline GPT2Transformer from yuhuizhang
+author: John Snow Labs
+name: finetuned_gpt2_sst2_negation0_05_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_gpt2_sst2_negation0_05_pipeline` is a English model originally trained by yuhuizhang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_gpt2_sst2_negation0_05_pipeline_en_5.5.1_3.0_1734589183390.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_gpt2_sst2_negation0_05_pipeline_en_5.5.1_3.0_1734589183390.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuned_gpt2_sst2_negation0_05_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuned_gpt2_sst2_negation0_05_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_gpt2_sst2_negation0_05_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/yuhuizhang/finetuned_gpt2_sst2_negation0.05
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-flan_t5_finetune_macmotus3_0_en.md b/docs/_posts/ahmedlone127/2024-12-19-flan_t5_finetune_macmotus3_0_en.md
new file mode 100644
index 00000000000000..781afe566472d4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-flan_t5_finetune_macmotus3_0_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English flan_t5_finetune_macmotus3_0 T5Transformer from sebasqz
+author: John Snow Labs
+name: flan_t5_finetune_macmotus3_0
+date: 2024-12-19
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_finetune_macmotus3_0` is a English model originally trained by sebasqz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_finetune_macmotus3_0_en_5.5.1_3.0_1734568035002.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_finetune_macmotus3_0_en_5.5.1_3.0_1734568035002.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("flan_t5_finetune_macmotus3_0","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("flan_t5_finetune_macmotus3_0", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_finetune_macmotus3_0|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/sebasqz/flan-t5-finetune-macmotus3.0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-flan_t5_finetune_macmotus3_0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-flan_t5_finetune_macmotus3_0_pipeline_en.md
new file mode 100644
index 00000000000000..a8cafdbc08cc11
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-flan_t5_finetune_macmotus3_0_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English flan_t5_finetune_macmotus3_0_pipeline pipeline T5Transformer from sebasqz
+author: John Snow Labs
+name: flan_t5_finetune_macmotus3_0_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_finetune_macmotus3_0_pipeline` is a English model originally trained by sebasqz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_finetune_macmotus3_0_pipeline_en_5.5.1_3.0_1734568086066.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_finetune_macmotus3_0_pipeline_en_5.5.1_3.0_1734568086066.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("flan_t5_finetune_macmotus3_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("flan_t5_finetune_macmotus3_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_finetune_macmotus3_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/sebasqz/flan-t5-finetune-macmotus3.0
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-flan_t5_rouge_durga_3_en.md b/docs/_posts/ahmedlone127/2024-12-19-flan_t5_rouge_durga_3_en.md
new file mode 100644
index 00000000000000..461e569180804b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-flan_t5_rouge_durga_3_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English flan_t5_rouge_durga_3 T5Transformer from devagonal
+author: John Snow Labs
+name: flan_t5_rouge_durga_3
+date: 2024-12-19
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_rouge_durga_3` is a English model originally trained by devagonal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_rouge_durga_3_en_5.5.1_3.0_1734567856312.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_rouge_durga_3_en_5.5.1_3.0_1734567856312.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("flan_t5_rouge_durga_3","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("flan_t5_rouge_durga_3", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_rouge_durga_3|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/devagonal/flan-t5-rouge-durga-3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-flan_t5_rouge_durga_3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-flan_t5_rouge_durga_3_pipeline_en.md
new file mode 100644
index 00000000000000..6ada9f073e6b1e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-flan_t5_rouge_durga_3_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English flan_t5_rouge_durga_3_pipeline pipeline T5Transformer from devagonal
+author: John Snow Labs
+name: flan_t5_rouge_durga_3_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_rouge_durga_3_pipeline` is a English model originally trained by devagonal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_rouge_durga_3_pipeline_en_5.5.1_3.0_1734567908792.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_rouge_durga_3_pipeline_en_5.5.1_3.0_1734567908792.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("flan_t5_rouge_durga_3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("flan_t5_rouge_durga_3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_rouge_durga_3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/devagonal/flan-t5-rouge-durga-3
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-flan_t5_rouge_durga_q5_2_en.md b/docs/_posts/ahmedlone127/2024-12-19-flan_t5_rouge_durga_q5_2_en.md
new file mode 100644
index 00000000000000..e45e18cfb02654
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-flan_t5_rouge_durga_q5_2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English flan_t5_rouge_durga_q5_2 T5Transformer from devagonal
+author: John Snow Labs
+name: flan_t5_rouge_durga_q5_2
+date: 2024-12-19
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_rouge_durga_q5_2` is a English model originally trained by devagonal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_rouge_durga_q5_2_en_5.5.1_3.0_1734567235885.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_rouge_durga_q5_2_en_5.5.1_3.0_1734567235885.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("flan_t5_rouge_durga_q5_2","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("flan_t5_rouge_durga_q5_2", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_rouge_durga_q5_2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/devagonal/flan-t5-rouge-durga-q5-2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-flan_t5_rouge_durga_q5_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-flan_t5_rouge_durga_q5_2_pipeline_en.md
new file mode 100644
index 00000000000000..0fff5e4a32a2b8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-flan_t5_rouge_durga_q5_2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English flan_t5_rouge_durga_q5_2_pipeline pipeline T5Transformer from devagonal
+author: John Snow Labs
+name: flan_t5_rouge_durga_q5_2_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_rouge_durga_q5_2_pipeline` is a English model originally trained by devagonal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_rouge_durga_q5_2_pipeline_en_5.5.1_3.0_1734567286697.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_rouge_durga_q5_2_pipeline_en_5.5.1_3.0_1734567286697.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("flan_t5_rouge_durga_q5_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("flan_t5_rouge_durga_q5_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_rouge_durga_q5_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/devagonal/flan-t5-rouge-durga-q5-2
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-flan_t5_rouge_durga_q5_clean_4b_en.md b/docs/_posts/ahmedlone127/2024-12-19-flan_t5_rouge_durga_q5_clean_4b_en.md
new file mode 100644
index 00000000000000..76a4e691a83231
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-flan_t5_rouge_durga_q5_clean_4b_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English flan_t5_rouge_durga_q5_clean_4b T5Transformer from devagonal
+author: John Snow Labs
+name: flan_t5_rouge_durga_q5_clean_4b
+date: 2024-12-19
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_rouge_durga_q5_clean_4b` is a English model originally trained by devagonal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_rouge_durga_q5_clean_4b_en_5.5.1_3.0_1734568679950.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_rouge_durga_q5_clean_4b_en_5.5.1_3.0_1734568679950.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("flan_t5_rouge_durga_q5_clean_4b","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("flan_t5_rouge_durga_q5_clean_4b", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_rouge_durga_q5_clean_4b|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/devagonal/flan-t5-rouge-durga-q5-clean-4b
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-flan_t5_rouge_durga_q5_clean_4b_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-flan_t5_rouge_durga_q5_clean_4b_pipeline_en.md
new file mode 100644
index 00000000000000..57fd8570e2c97e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-flan_t5_rouge_durga_q5_clean_4b_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English flan_t5_rouge_durga_q5_clean_4b_pipeline pipeline T5Transformer from devagonal
+author: John Snow Labs
+name: flan_t5_rouge_durga_q5_clean_4b_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_rouge_durga_q5_clean_4b_pipeline` is a English model originally trained by devagonal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_rouge_durga_q5_clean_4b_pipeline_en_5.5.1_3.0_1734568734426.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_rouge_durga_q5_clean_4b_pipeline_en_5.5.1_3.0_1734568734426.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("flan_t5_rouge_durga_q5_clean_4b_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("flan_t5_rouge_durga_q5_clean_4b_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_rouge_durga_q5_clean_4b_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/devagonal/flan-t5-rouge-durga-q5-clean-4b
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-flan_t5_small_gigatrue_en.md b/docs/_posts/ahmedlone127/2024-12-19-flan_t5_small_gigatrue_en.md
new file mode 100644
index 00000000000000..89c6f76d037595
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-flan_t5_small_gigatrue_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English flan_t5_small_gigatrue T5Transformer from Plasmoxy
+author: John Snow Labs
+name: flan_t5_small_gigatrue
+date: 2024-12-19
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_small_gigatrue` is a English model originally trained by Plasmoxy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_small_gigatrue_en_5.5.1_3.0_1734567338404.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_small_gigatrue_en_5.5.1_3.0_1734567338404.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("flan_t5_small_gigatrue","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("flan_t5_small_gigatrue", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_small_gigatrue|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|178.0 MB|
+
+## References
+
+https://huggingface.co/Plasmoxy/flan-t5-small-gigatrue
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-flan_t5_small_gigatrue_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-flan_t5_small_gigatrue_pipeline_en.md
new file mode 100644
index 00000000000000..5d88a9e94d867a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-flan_t5_small_gigatrue_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English flan_t5_small_gigatrue_pipeline pipeline T5Transformer from Plasmoxy
+author: John Snow Labs
+name: flan_t5_small_gigatrue_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_small_gigatrue_pipeline` is a English model originally trained by Plasmoxy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_small_gigatrue_pipeline_en_5.5.1_3.0_1734567397095.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_small_gigatrue_pipeline_en_5.5.1_3.0_1734567397095.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("flan_t5_small_gigatrue_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("flan_t5_small_gigatrue_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_small_gigatrue_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|178.0 MB|
+
+## References
+
+https://huggingface.co/Plasmoxy/flan-t5-small-gigatrue
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-flan_t5_small_rafahorn03_en.md b/docs/_posts/ahmedlone127/2024-12-19-flan_t5_small_rafahorn03_en.md
new file mode 100644
index 00000000000000..d24f093bbff622
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-flan_t5_small_rafahorn03_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English flan_t5_small_rafahorn03 T5Transformer from rafahorn03
+author: John Snow Labs
+name: flan_t5_small_rafahorn03
+date: 2024-12-19
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_small_rafahorn03` is a English model originally trained by rafahorn03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_small_rafahorn03_en_5.5.1_3.0_1734569358272.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_small_rafahorn03_en_5.5.1_3.0_1734569358272.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("flan_t5_small_rafahorn03","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("flan_t5_small_rafahorn03", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_small_rafahorn03|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|349.8 MB|
+
+## References
+
+https://huggingface.co/rafahorn03/flan-t5-small
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-flan_t5_small_rafahorn03_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-flan_t5_small_rafahorn03_pipeline_en.md
new file mode 100644
index 00000000000000..c89f57c313a1ed
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-flan_t5_small_rafahorn03_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English flan_t5_small_rafahorn03_pipeline pipeline T5Transformer from rafahorn03
+author: John Snow Labs
+name: flan_t5_small_rafahorn03_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_small_rafahorn03_pipeline` is a English model originally trained by rafahorn03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_small_rafahorn03_pipeline_en_5.5.1_3.0_1734569388062.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_small_rafahorn03_pipeline_en_5.5.1_3.0_1734569388062.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("flan_t5_small_rafahorn03_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("flan_t5_small_rafahorn03_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_small_rafahorn03_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|349.8 MB|
+
+## References
+
+https://huggingface.co/rafahorn03/flan-t5-small
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-ft_t5_small_dutch_2_fol_v1_1_en.md b/docs/_posts/ahmedlone127/2024-12-19-ft_t5_small_dutch_2_fol_v1_1_en.md
new file mode 100644
index 00000000000000..98f362003e8292
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-ft_t5_small_dutch_2_fol_v1_1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English ft_t5_small_dutch_2_fol_v1_1 T5Transformer from tuanbc88
+author: John Snow Labs
+name: ft_t5_small_dutch_2_fol_v1_1
+date: 2024-12-19
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ft_t5_small_dutch_2_fol_v1_1` is a English model originally trained by tuanbc88.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ft_t5_small_dutch_2_fol_v1_1_en_5.5.1_3.0_1734567741952.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ft_t5_small_dutch_2_fol_v1_1_en_5.5.1_3.0_1734567741952.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("ft_t5_small_dutch_2_fol_v1_1","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("ft_t5_small_dutch_2_fol_v1_1", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ft_t5_small_dutch_2_fol_v1_1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|147.3 MB|
+
+## References
+
+https://huggingface.co/tuanbc88/ft-t5-small-nl-2-fol-v1.1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-ft_t5_small_dutch_2_fol_v1_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-ft_t5_small_dutch_2_fol_v1_1_pipeline_en.md
new file mode 100644
index 00000000000000..f15af60df48406
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-ft_t5_small_dutch_2_fol_v1_1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English ft_t5_small_dutch_2_fol_v1_1_pipeline pipeline T5Transformer from tuanbc88
+author: John Snow Labs
+name: ft_t5_small_dutch_2_fol_v1_1_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ft_t5_small_dutch_2_fol_v1_1_pipeline` is a English model originally trained by tuanbc88.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ft_t5_small_dutch_2_fol_v1_1_pipeline_en_5.5.1_3.0_1734567788792.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ft_t5_small_dutch_2_fol_v1_1_pipeline_en_5.5.1_3.0_1734567788792.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ft_t5_small_dutch_2_fol_v1_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ft_t5_small_dutch_2_fol_v1_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ft_t5_small_dutch_2_fol_v1_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|147.3 MB|
+
+## References
+
+https://huggingface.co/tuanbc88/ft-t5-small-nl-2-fol-v1.1
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-gladosystem_en.md b/docs/_posts/ahmedlone127/2024-12-19-gladosystem_en.md
new file mode 100644
index 00000000000000..f5c1b764d72343
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-gladosystem_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English gladosystem GPT2Transformer from huggingtweets
+author: John Snow Labs
+name: gladosystem
+date: 2024-12-19
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gladosystem` is a English model originally trained by huggingtweets.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gladosystem_en_5.5.1_3.0_1734584362627.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gladosystem_en_5.5.1_3.0_1734584362627.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("gladosystem","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("gladosystem","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gladosystem|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/huggingtweets/gladosystem
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-gladosystem_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-gladosystem_pipeline_en.md
new file mode 100644
index 00000000000000..58039369a7a36e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-gladosystem_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English gladosystem_pipeline pipeline GPT2Transformer from huggingtweets
+author: John Snow Labs
+name: gladosystem_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gladosystem_pipeline` is a English model originally trained by huggingtweets.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gladosystem_pipeline_en_5.5.1_3.0_1734584386596.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gladosystem_pipeline_en_5.5.1_3.0_1734584386596.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gladosystem_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gladosystem_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gladosystem_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/huggingtweets/gladosystem
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-google_flan_large_q_own_en.md b/docs/_posts/ahmedlone127/2024-12-19-google_flan_large_q_own_en.md
new file mode 100644
index 00000000000000..c7edfb7a5c8564
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-google_flan_large_q_own_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English google_flan_large_q_own T5Transformer from kartheekkumar65
+author: John Snow Labs
+name: google_flan_large_q_own
+date: 2024-12-19
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`google_flan_large_q_own` is a English model originally trained by kartheekkumar65.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/google_flan_large_q_own_en_5.5.1_3.0_1734569405725.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/google_flan_large_q_own_en_5.5.1_3.0_1734569405725.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("google_flan_large_q_own","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("google_flan_large_q_own", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|google_flan_large_q_own|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|3.0 GB|
+
+## References
+
+https://huggingface.co/kartheekkumar65/google-flan-large-Q-own
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-google_flan_large_q_own_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-google_flan_large_q_own_pipeline_en.md
new file mode 100644
index 00000000000000..de04597ae287da
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-google_flan_large_q_own_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English google_flan_large_q_own_pipeline pipeline T5Transformer from kartheekkumar65
+author: John Snow Labs
+name: google_flan_large_q_own_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`google_flan_large_q_own_pipeline` is a English model originally trained by kartheekkumar65.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/google_flan_large_q_own_pipeline_en_5.5.1_3.0_1734569563087.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/google_flan_large_q_own_pipeline_en_5.5.1_3.0_1734569563087.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("google_flan_large_q_own_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("google_flan_large_q_own_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|google_flan_large_q_own_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|3.0 GB|
+
+## References
+
+https://huggingface.co/kartheekkumar65/google-flan-large-Q-own
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-gpt2_51m_1_31b_pubmedabs_en.md b/docs/_posts/ahmedlone127/2024-12-19-gpt2_51m_1_31b_pubmedabs_en.md
new file mode 100644
index 00000000000000..186f1fc92d6f82
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-gpt2_51m_1_31b_pubmedabs_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English gpt2_51m_1_31b_pubmedabs GPT2Transformer from UDACA
+author: John Snow Labs
+name: gpt2_51m_1_31b_pubmedabs
+date: 2024-12-19
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_51m_1_31b_pubmedabs` is a English model originally trained by UDACA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_51m_1_31b_pubmedabs_en_5.5.1_3.0_1734589737856.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_51m_1_31b_pubmedabs_en_5.5.1_3.0_1734589737856.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("gpt2_51m_1_31b_pubmedabs","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("gpt2_51m_1_31b_pubmedabs","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_51m_1_31b_pubmedabs|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|194.0 MB|
+
+## References
+
+https://huggingface.co/UDACA/gpt2-51M-1.31B-PubMedAbs
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-gpt2_51m_1_31b_pubmedabs_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-gpt2_51m_1_31b_pubmedabs_pipeline_en.md
new file mode 100644
index 00000000000000..96f935c4b34c85
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-gpt2_51m_1_31b_pubmedabs_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English gpt2_51m_1_31b_pubmedabs_pipeline pipeline GPT2Transformer from UDACA
+author: John Snow Labs
+name: gpt2_51m_1_31b_pubmedabs_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_51m_1_31b_pubmedabs_pipeline` is a English model originally trained by UDACA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_51m_1_31b_pubmedabs_pipeline_en_5.5.1_3.0_1734589747746.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_51m_1_31b_pubmedabs_pipeline_en_5.5.1_3.0_1734589747746.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpt2_51m_1_31b_pubmedabs_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpt2_51m_1_31b_pubmedabs_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_51m_1_31b_pubmedabs_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|194.0 MB|
+
+## References
+
+https://huggingface.co/UDACA/gpt2-51M-1.31B-PubMedAbs
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-gpt2_guanaco_dolly_platypus_en.md b/docs/_posts/ahmedlone127/2024-12-19-gpt2_guanaco_dolly_platypus_en.md
new file mode 100644
index 00000000000000..60661c492ced21
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-gpt2_guanaco_dolly_platypus_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English gpt2_guanaco_dolly_platypus GPT2Transformer from lgaalves
+author: John Snow Labs
+name: gpt2_guanaco_dolly_platypus
+date: 2024-12-19
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_guanaco_dolly_platypus` is a English model originally trained by lgaalves.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_guanaco_dolly_platypus_en_5.5.1_3.0_1734585588565.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_guanaco_dolly_platypus_en_5.5.1_3.0_1734585588565.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("gpt2_guanaco_dolly_platypus","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("gpt2_guanaco_dolly_platypus","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_guanaco_dolly_platypus|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|298.5 MB|
+
+## References
+
+https://huggingface.co/lgaalves/gpt2_guanaco-dolly-platypus
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-gpt2_guanaco_dolly_platypus_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-gpt2_guanaco_dolly_platypus_pipeline_en.md
new file mode 100644
index 00000000000000..314ceddc38860f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-gpt2_guanaco_dolly_platypus_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English gpt2_guanaco_dolly_platypus_pipeline pipeline GPT2Transformer from lgaalves
+author: John Snow Labs
+name: gpt2_guanaco_dolly_platypus_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_guanaco_dolly_platypus_pipeline` is a English model originally trained by lgaalves.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_guanaco_dolly_platypus_pipeline_en_5.5.1_3.0_1734585704460.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_guanaco_dolly_platypus_pipeline_en_5.5.1_3.0_1734585704460.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpt2_guanaco_dolly_platypus_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpt2_guanaco_dolly_platypus_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_guanaco_dolly_platypus_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|298.6 MB|
+
+## References
+
+https://huggingface.co/lgaalves/gpt2_guanaco-dolly-platypus
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-gpt2_platypus_dolly_guanaco_en.md b/docs/_posts/ahmedlone127/2024-12-19-gpt2_platypus_dolly_guanaco_en.md
new file mode 100644
index 00000000000000..3e608b3b081106
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-gpt2_platypus_dolly_guanaco_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English gpt2_platypus_dolly_guanaco GPT2Transformer from lgaalves
+author: John Snow Labs
+name: gpt2_platypus_dolly_guanaco
+date: 2024-12-19
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_platypus_dolly_guanaco` is a English model originally trained by lgaalves.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_platypus_dolly_guanaco_en_5.5.1_3.0_1734583928250.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_platypus_dolly_guanaco_en_5.5.1_3.0_1734583928250.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("gpt2_platypus_dolly_guanaco","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("gpt2_platypus_dolly_guanaco","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_platypus_dolly_guanaco|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|298.5 MB|
+
+## References
+
+https://huggingface.co/lgaalves/gpt2_platypus-dolly-guanaco
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-gpt2_platypus_dolly_guanaco_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-gpt2_platypus_dolly_guanaco_pipeline_en.md
new file mode 100644
index 00000000000000..ba71f736a1fc5a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-gpt2_platypus_dolly_guanaco_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English gpt2_platypus_dolly_guanaco_pipeline pipeline GPT2Transformer from lgaalves
+author: John Snow Labs
+name: gpt2_platypus_dolly_guanaco_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_platypus_dolly_guanaco_pipeline` is a English model originally trained by lgaalves.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_platypus_dolly_guanaco_pipeline_en_5.5.1_3.0_1734584011438.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_platypus_dolly_guanaco_pipeline_en_5.5.1_3.0_1734584011438.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpt2_platypus_dolly_guanaco_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpt2_platypus_dolly_guanaco_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_platypus_dolly_guanaco_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|298.6 MB|
+
+## References
+
+https://huggingface.co/lgaalves/gpt2_platypus-dolly-guanaco
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-gpt2_small_arabic_ar.md b/docs/_posts/ahmedlone127/2024-12-19-gpt2_small_arabic_ar.md
new file mode 100644
index 00000000000000..d04862213d0b18
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-gpt2_small_arabic_ar.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Arabic gpt2_small_arabic GPT2Transformer from akhooli
+author: John Snow Labs
+name: gpt2_small_arabic
+date: 2024-12-19
+tags: [ar, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: ar
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_small_arabic` is a Arabic model originally trained by akhooli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_small_arabic_ar_5.5.1_3.0_1734591247782.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_small_arabic_ar_5.5.1_3.0_1734591247782.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("gpt2_small_arabic","ar") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("gpt2_small_arabic","ar") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_small_arabic|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|ar|
+|Size:|299.0 MB|
+
+## References
+
+https://huggingface.co/akhooli/gpt2-small-arabic
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-gpt2_small_arabic_pipeline_ar.md b/docs/_posts/ahmedlone127/2024-12-19-gpt2_small_arabic_pipeline_ar.md
new file mode 100644
index 00000000000000..31f8c3c68b8f55
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-gpt2_small_arabic_pipeline_ar.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Arabic gpt2_small_arabic_pipeline pipeline GPT2Transformer from akhooli
+author: John Snow Labs
+name: gpt2_small_arabic_pipeline
+date: 2024-12-19
+tags: [ar, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: ar
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_small_arabic_pipeline` is a Arabic model originally trained by akhooli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_small_arabic_pipeline_ar_5.5.1_3.0_1734591332527.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_small_arabic_pipeline_ar_5.5.1_3.0_1734591332527.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpt2_small_arabic_pipeline", lang = "ar")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpt2_small_arabic_pipeline", lang = "ar")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_small_arabic_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ar|
+|Size:|299.0 MB|
+
+## References
+
+https://huggingface.co/akhooli/gpt2-small-arabic
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-gpt2_small_indonesian_522m_id.md b/docs/_posts/ahmedlone127/2024-12-19-gpt2_small_indonesian_522m_id.md
new file mode 100644
index 00000000000000..61c4836dcfea87
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-gpt2_small_indonesian_522m_id.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Indonesian gpt2_small_indonesian_522m GPT2Transformer from cahya
+author: John Snow Labs
+name: gpt2_small_indonesian_522m
+date: 2024-12-19
+tags: [id, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: id
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_small_indonesian_522m` is a Indonesian model originally trained by cahya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_small_indonesian_522m_id_5.5.1_3.0_1734582585496.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_small_indonesian_522m_id_5.5.1_3.0_1734582585496.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("gpt2_small_indonesian_522m","id") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("gpt2_small_indonesian_522m","id") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_small_indonesian_522m|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|id|
+|Size:|467.2 MB|
+
+## References
+
+https://huggingface.co/cahya/gpt2-small-indonesian-522M
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-gpt2_small_indonesian_522m_pipeline_id.md b/docs/_posts/ahmedlone127/2024-12-19-gpt2_small_indonesian_522m_pipeline_id.md
new file mode 100644
index 00000000000000..160d0fd42a816b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-gpt2_small_indonesian_522m_pipeline_id.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Indonesian gpt2_small_indonesian_522m_pipeline pipeline GPT2Transformer from cahya
+author: John Snow Labs
+name: gpt2_small_indonesian_522m_pipeline
+date: 2024-12-19
+tags: [id, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: id
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_small_indonesian_522m_pipeline` is a Indonesian model originally trained by cahya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_small_indonesian_522m_pipeline_id_5.5.1_3.0_1734582609023.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_small_indonesian_522m_pipeline_id_5.5.1_3.0_1734582609023.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpt2_small_indonesian_522m_pipeline", lang = "id")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpt2_small_indonesian_522m_pipeline", lang = "id")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_small_indonesian_522m_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|id|
+|Size:|467.3 MB|
+
+## References
+
+https://huggingface.co/cahya/gpt2-small-indonesian-522M
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-gpt2_small_portuguese_pierreguillou_pipeline_pt.md b/docs/_posts/ahmedlone127/2024-12-19-gpt2_small_portuguese_pierreguillou_pipeline_pt.md
new file mode 100644
index 00000000000000..9ce763837d29ac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-gpt2_small_portuguese_pierreguillou_pipeline_pt.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Portuguese gpt2_small_portuguese_pierreguillou_pipeline pipeline GPT2Transformer from pierreguillou
+author: John Snow Labs
+name: gpt2_small_portuguese_pierreguillou_pipeline
+date: 2024-12-19
+tags: [pt, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: pt
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_small_portuguese_pierreguillou_pipeline` is a Portuguese model originally trained by pierreguillou.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_small_portuguese_pierreguillou_pipeline_pt_5.5.1_3.0_1734583317437.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_small_portuguese_pierreguillou_pipeline_pt_5.5.1_3.0_1734583317437.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpt2_small_portuguese_pierreguillou_pipeline", lang = "pt")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpt2_small_portuguese_pierreguillou_pipeline", lang = "pt")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_small_portuguese_pierreguillou_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|pt|
+|Size:|299.3 MB|
+
+## References
+
+https://huggingface.co/pierreguillou/gpt2-small-portuguese
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-gpt2_small_portuguese_pierreguillou_pt.md b/docs/_posts/ahmedlone127/2024-12-19-gpt2_small_portuguese_pierreguillou_pt.md
new file mode 100644
index 00000000000000..b4836bb27e4456
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-gpt2_small_portuguese_pierreguillou_pt.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Portuguese gpt2_small_portuguese_pierreguillou GPT2Transformer from pierreguillou
+author: John Snow Labs
+name: gpt2_small_portuguese_pierreguillou
+date: 2024-12-19
+tags: [pt, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: pt
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_small_portuguese_pierreguillou` is a Portuguese model originally trained by pierreguillou.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_small_portuguese_pierreguillou_pt_5.5.1_3.0_1734583234794.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_small_portuguese_pierreguillou_pt_5.5.1_3.0_1734583234794.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("gpt2_small_portuguese_pierreguillou","pt") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("gpt2_small_portuguese_pierreguillou","pt") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_small_portuguese_pierreguillou|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|pt|
+|Size:|299.3 MB|
+
+## References
+
+https://huggingface.co/pierreguillou/gpt2-small-portuguese
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-gpt2_spanish_es.md b/docs/_posts/ahmedlone127/2024-12-19-gpt2_spanish_es.md
new file mode 100644
index 00000000000000..3cbc4398465f2a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-gpt2_spanish_es.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Castilian, Spanish gpt2_spanish GPT2Transformer from DeepESP
+author: John Snow Labs
+name: gpt2_spanish
+date: 2024-12-19
+tags: [es, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: es
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_spanish` is a Castilian, Spanish model originally trained by DeepESP.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_spanish_es_5.5.1_3.0_1734586463285.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_spanish_es_5.5.1_3.0_1734586463285.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("gpt2_spanish","es") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("gpt2_spanish","es") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_spanish|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|es|
+|Size:|297.5 MB|
+
+## References
+
+https://huggingface.co/DeepESP/gpt2-spanish
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-gpt2_spanish_pipeline_es.md b/docs/_posts/ahmedlone127/2024-12-19-gpt2_spanish_pipeline_es.md
new file mode 100644
index 00000000000000..d814629a5e64a3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-gpt2_spanish_pipeline_es.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Castilian, Spanish gpt2_spanish_pipeline pipeline GPT2Transformer from DeepESP
+author: John Snow Labs
+name: gpt2_spanish_pipeline
+date: 2024-12-19
+tags: [es, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: es
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_spanish_pipeline` is a Castilian, Spanish model originally trained by DeepESP.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_spanish_pipeline_es_5.5.1_3.0_1734586549166.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_spanish_pipeline_es_5.5.1_3.0_1734586549166.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpt2_spanish_pipeline", lang = "es")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpt2_spanish_pipeline", lang = "es")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_spanish_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|es|
+|Size:|297.5 MB|
+
+## References
+
+https://huggingface.co/DeepESP/gpt2-spanish
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-gpt2_turkish_128_token_pipeline_tr.md b/docs/_posts/ahmedlone127/2024-12-19-gpt2_turkish_128_token_pipeline_tr.md
new file mode 100644
index 00000000000000..8ffe34dc5c0116
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-gpt2_turkish_128_token_pipeline_tr.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Turkish gpt2_turkish_128_token_pipeline pipeline GPT2Transformer from cenkersisman
+author: John Snow Labs
+name: gpt2_turkish_128_token_pipeline
+date: 2024-12-19
+tags: [tr, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: tr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_turkish_128_token_pipeline` is a Turkish model originally trained by cenkersisman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_turkish_128_token_pipeline_tr_5.5.1_3.0_1734582831886.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_turkish_128_token_pipeline_tr_5.5.1_3.0_1734582831886.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpt2_turkish_128_token_pipeline", lang = "tr")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpt2_turkish_128_token_pipeline", lang = "tr")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_turkish_128_token_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|tr|
+|Size:|467.1 MB|
+
+## References
+
+https://huggingface.co/cenkersisman/gpt2-turkish-128-token
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-gpt2_turkish_128_token_tr.md b/docs/_posts/ahmedlone127/2024-12-19-gpt2_turkish_128_token_tr.md
new file mode 100644
index 00000000000000..9a584eec70291c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-gpt2_turkish_128_token_tr.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Turkish gpt2_turkish_128_token GPT2Transformer from cenkersisman
+author: John Snow Labs
+name: gpt2_turkish_128_token
+date: 2024-12-19
+tags: [tr, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: tr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_turkish_128_token` is a Turkish model originally trained by cenkersisman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_turkish_128_token_tr_5.5.1_3.0_1734582808579.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_turkish_128_token_tr_5.5.1_3.0_1734582808579.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("gpt2_turkish_128_token","tr") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("gpt2_turkish_128_token","tr") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_turkish_128_token|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|tr|
+|Size:|467.1 MB|
+
+## References
+
+https://huggingface.co/cenkersisman/gpt2-turkish-128-token
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-gpt2_turkish_base_pipeline_tr.md b/docs/_posts/ahmedlone127/2024-12-19-gpt2_turkish_base_pipeline_tr.md
new file mode 100644
index 00000000000000..90d587e7146a79
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-gpt2_turkish_base_pipeline_tr.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Turkish gpt2_turkish_base_pipeline pipeline GPT2Transformer from erythropygia
+author: John Snow Labs
+name: gpt2_turkish_base_pipeline
+date: 2024-12-19
+tags: [tr, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: tr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_turkish_base_pipeline` is a Turkish model originally trained by erythropygia.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_turkish_base_pipeline_tr_5.5.1_3.0_1734588863860.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_turkish_base_pipeline_tr_5.5.1_3.0_1734588863860.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpt2_turkish_base_pipeline", lang = "tr")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpt2_turkish_base_pipeline", lang = "tr")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_turkish_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|tr|
+|Size:|467.2 MB|
+
+## References
+
+https://huggingface.co/erythropygia/gpt2-turkish-base
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-gpt2_turkish_base_tr.md b/docs/_posts/ahmedlone127/2024-12-19-gpt2_turkish_base_tr.md
new file mode 100644
index 00000000000000..e43936f0af610c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-gpt2_turkish_base_tr.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Turkish gpt2_turkish_base GPT2Transformer from erythropygia
+author: John Snow Labs
+name: gpt2_turkish_base
+date: 2024-12-19
+tags: [tr, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: tr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_turkish_base` is a Turkish model originally trained by erythropygia.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_turkish_base_tr_5.5.1_3.0_1734588838239.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_turkish_base_tr_5.5.1_3.0_1734588838239.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("gpt2_turkish_base","tr") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("gpt2_turkish_base","tr") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_turkish_base|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|tr|
+|Size:|467.2 MB|
+
+## References
+
+https://huggingface.co/erythropygia/gpt2-turkish-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-gpt2_turkish_uncased_en.md b/docs/_posts/ahmedlone127/2024-12-19-gpt2_turkish_uncased_en.md
new file mode 100644
index 00000000000000..17b64c9a980f14
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-gpt2_turkish_uncased_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English gpt2_turkish_uncased GPT2Transformer from ByteWave
+author: John Snow Labs
+name: gpt2_turkish_uncased
+date: 2024-12-19
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_turkish_uncased` is a English model originally trained by ByteWave.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_turkish_uncased_en_5.5.1_3.0_1734591782899.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_turkish_uncased_en_5.5.1_3.0_1734591782899.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("gpt2_turkish_uncased","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("gpt2_turkish_uncased","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_turkish_uncased|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.9 MB|
+
+## References
+
+https://huggingface.co/ByteWave/gpt2-turkish-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-gpt2_turkish_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-gpt2_turkish_uncased_pipeline_en.md
new file mode 100644
index 00000000000000..fb6b84ffdada25
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-gpt2_turkish_uncased_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English gpt2_turkish_uncased_pipeline pipeline GPT2Transformer from ByteWave
+author: John Snow Labs
+name: gpt2_turkish_uncased_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_turkish_uncased_pipeline` is a English model originally trained by ByteWave.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_turkish_uncased_pipeline_en_5.5.1_3.0_1734591806760.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_turkish_uncased_pipeline_en_5.5.1_3.0_1734591806760.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpt2_turkish_uncased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpt2_turkish_uncased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_turkish_uncased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.9 MB|
+
+## References
+
+https://huggingface.co/ByteWave/gpt2-turkish-uncased
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-gqa_roberta_en.md b/docs/_posts/ahmedlone127/2024-12-19-gqa_roberta_en.md
new file mode 100644
index 00000000000000..cf3dffdd747bba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-gqa_roberta_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English gqa_roberta RoBertaForQuestionAnswering from farid1088
+author: John Snow Labs
+name: gqa_roberta
+date: 2024-12-19
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gqa_roberta` is a English model originally trained by farid1088.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gqa_roberta_en_5.5.1_3.0_1734601075025.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gqa_roberta_en_5.5.1_3.0_1734601075025.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("gqa_roberta","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("gqa_roberta", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gqa_roberta|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|465.8 MB|
+
+## References
+
+https://huggingface.co/farid1088/GQA_RoBERTa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-gqa_roberta_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-gqa_roberta_pipeline_en.md
new file mode 100644
index 00000000000000..651679ae1b1de5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-gqa_roberta_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English gqa_roberta_pipeline pipeline RoBertaForQuestionAnswering from farid1088
+author: John Snow Labs
+name: gqa_roberta_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gqa_roberta_pipeline` is a English model originally trained by farid1088.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gqa_roberta_pipeline_en_5.5.1_3.0_1734601101844.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gqa_roberta_pipeline_en_5.5.1_3.0_1734601101844.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gqa_roberta_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gqa_roberta_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gqa_roberta_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|465.8 MB|
+
+## References
+
+https://huggingface.co/farid1088/GQA_RoBERTa
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-html_accessibility_fixer_en.md b/docs/_posts/ahmedlone127/2024-12-19-html_accessibility_fixer_en.md
new file mode 100644
index 00000000000000..fafec94ad4babc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-html_accessibility_fixer_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English html_accessibility_fixer T5Transformer from SnehaPriyaaMP
+author: John Snow Labs
+name: html_accessibility_fixer
+date: 2024-12-19
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`html_accessibility_fixer` is a English model originally trained by SnehaPriyaaMP.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/html_accessibility_fixer_en_5.5.1_3.0_1734566882643.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/html_accessibility_fixer_en_5.5.1_3.0_1734566882643.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("html_accessibility_fixer","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("html_accessibility_fixer", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|html_accessibility_fixer|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|232.9 MB|
+
+## References
+
+https://huggingface.co/SnehaPriyaaMP/html-accessibility-fixer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-html_accessibility_fixer_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-html_accessibility_fixer_pipeline_en.md
new file mode 100644
index 00000000000000..1d99018a519d0a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-html_accessibility_fixer_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English html_accessibility_fixer_pipeline pipeline T5Transformer from SnehaPriyaaMP
+author: John Snow Labs
+name: html_accessibility_fixer_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`html_accessibility_fixer_pipeline` is a English model originally trained by SnehaPriyaaMP.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/html_accessibility_fixer_pipeline_en_5.5.1_3.0_1734566910399.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/html_accessibility_fixer_pipeline_en_5.5.1_3.0_1734566910399.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("html_accessibility_fixer_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("html_accessibility_fixer_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|html_accessibility_fixer_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|232.9 MB|
+
+## References
+
+https://huggingface.co/SnehaPriyaaMP/html-accessibility-fixer
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-hubert_common_voice_japanese_demo_kana_only_50epochs_ja.md b/docs/_posts/ahmedlone127/2024-12-19-hubert_common_voice_japanese_demo_kana_only_50epochs_ja.md
new file mode 100644
index 00000000000000..0882d66a188a78
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-hubert_common_voice_japanese_demo_kana_only_50epochs_ja.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Japanese hubert_common_voice_japanese_demo_kana_only_50epochs HubertForCTC from utakumi
+author: John Snow Labs
+name: hubert_common_voice_japanese_demo_kana_only_50epochs
+date: 2024-12-19
+tags: [ja, open_source, onnx, asr, hubert]
+task: Automatic Speech Recognition
+language: ja
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: HubertForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_common_voice_japanese_demo_kana_only_50epochs` is a Japanese model originally trained by utakumi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_common_voice_japanese_demo_kana_only_50epochs_ja_5.5.1_3.0_1734599520307.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_common_voice_japanese_demo_kana_only_50epochs_ja_5.5.1_3.0_1734599520307.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = HubertForCTC.pretrained("hubert_common_voice_japanese_demo_kana_only_50epochs","ja") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = HubertForCTC.pretrained("hubert_common_voice_japanese_demo_kana_only_50epochs", "ja")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hubert_common_voice_japanese_demo_kana_only_50epochs|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|ja|
+|Size:|698.2 MB|
+
+## References
+
+https://huggingface.co/utakumi/Hubert-common_voice-ja-demo-kana-only-50epochs
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-hubert_common_voice_japanese_demo_kana_only_50epochs_pipeline_ja.md b/docs/_posts/ahmedlone127/2024-12-19-hubert_common_voice_japanese_demo_kana_only_50epochs_pipeline_ja.md
new file mode 100644
index 00000000000000..402de6aab5d130
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-hubert_common_voice_japanese_demo_kana_only_50epochs_pipeline_ja.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Japanese hubert_common_voice_japanese_demo_kana_only_50epochs_pipeline pipeline HubertForCTC from utakumi
+author: John Snow Labs
+name: hubert_common_voice_japanese_demo_kana_only_50epochs_pipeline
+date: 2024-12-19
+tags: [ja, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: ja
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_common_voice_japanese_demo_kana_only_50epochs_pipeline` is a Japanese model originally trained by utakumi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_common_voice_japanese_demo_kana_only_50epochs_pipeline_ja_5.5.1_3.0_1734599559510.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_common_voice_japanese_demo_kana_only_50epochs_pipeline_ja_5.5.1_3.0_1734599559510.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("hubert_common_voice_japanese_demo_kana_only_50epochs_pipeline", lang = "ja")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hubert_common_voice_japanese_demo_kana_only_50epochs_pipeline", lang = "ja")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hubert_common_voice_japanese_demo_kana_only_50epochs_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ja|
+|Size:|698.2 MB|
+
+## References
+
+https://huggingface.co/utakumi/Hubert-common_voice-ja-demo-kana-only-50epochs
+
+## Included Models
+
+- AudioAssembler
+- HubertForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-hubert_large_ll60k_librispeech_clean_100h_demo_dist_macabdul9_en.md b/docs/_posts/ahmedlone127/2024-12-19-hubert_large_ll60k_librispeech_clean_100h_demo_dist_macabdul9_en.md
new file mode 100644
index 00000000000000..dc7b56d822d253
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-hubert_large_ll60k_librispeech_clean_100h_demo_dist_macabdul9_en.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: English hubert_large_ll60k_librispeech_clean_100h_demo_dist_macabdul9 HubertForCTC from macabdul9
+author: John Snow Labs
+name: hubert_large_ll60k_librispeech_clean_100h_demo_dist_macabdul9
+date: 2024-12-19
+tags: [en, open_source, onnx, asr, hubert]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: HubertForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_large_ll60k_librispeech_clean_100h_demo_dist_macabdul9` is a English model originally trained by macabdul9.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_large_ll60k_librispeech_clean_100h_demo_dist_macabdul9_en_5.5.1_3.0_1734600049563.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_large_ll60k_librispeech_clean_100h_demo_dist_macabdul9_en_5.5.1_3.0_1734600049563.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = HubertForCTC.pretrained("hubert_large_ll60k_librispeech_clean_100h_demo_dist_macabdul9","en") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = HubertForCTC.pretrained("hubert_large_ll60k_librispeech_clean_100h_demo_dist_macabdul9", "en")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hubert_large_ll60k_librispeech_clean_100h_demo_dist_macabdul9|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|en|
+|Size:|2.4 GB|
+
+## References
+
+https://huggingface.co/macabdul9/hubert-large-ll60k-librispeech-clean-100h-demo-dist
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-hubert_large_ll60k_librispeech_clean_100h_demo_dist_macabdul9_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-hubert_large_ll60k_librispeech_clean_100h_demo_dist_macabdul9_pipeline_en.md
new file mode 100644
index 00000000000000..e48102847ae14b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-hubert_large_ll60k_librispeech_clean_100h_demo_dist_macabdul9_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English hubert_large_ll60k_librispeech_clean_100h_demo_dist_macabdul9_pipeline pipeline HubertForCTC from macabdul9
+author: John Snow Labs
+name: hubert_large_ll60k_librispeech_clean_100h_demo_dist_macabdul9_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_large_ll60k_librispeech_clean_100h_demo_dist_macabdul9_pipeline` is a English model originally trained by macabdul9.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_large_ll60k_librispeech_clean_100h_demo_dist_macabdul9_pipeline_en_5.5.1_3.0_1734600165333.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_large_ll60k_librispeech_clean_100h_demo_dist_macabdul9_pipeline_en_5.5.1_3.0_1734600165333.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("hubert_large_ll60k_librispeech_clean_100h_demo_dist_macabdul9_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hubert_large_ll60k_librispeech_clean_100h_demo_dist_macabdul9_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hubert_large_ll60k_librispeech_clean_100h_demo_dist_macabdul9_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|2.4 GB|
+
+## References
+
+https://huggingface.co/macabdul9/hubert-large-ll60k-librispeech-clean-100h-demo-dist
+
+## Included Models
+
+- AudioAssembler
+- HubertForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-improved_xlm_roberta_base_en.md b/docs/_posts/ahmedlone127/2024-12-19-improved_xlm_roberta_base_en.md
new file mode 100644
index 00000000000000..5c95d9f247a0fe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-improved_xlm_roberta_base_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English improved_xlm_roberta_base XlmRoBertaForSequenceClassification from Anwaarma
+author: John Snow Labs
+name: improved_xlm_roberta_base
+date: 2024-12-19
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`improved_xlm_roberta_base` is a English model originally trained by Anwaarma.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/improved_xlm_roberta_base_en_5.5.1_3.0_1734597681119.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/improved_xlm_roberta_base_en_5.5.1_3.0_1734597681119.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("improved_xlm_roberta_base","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("improved_xlm_roberta_base", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|improved_xlm_roberta_base|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|655.1 MB|
+
+## References
+
+https://huggingface.co/Anwaarma/Improved-xlm-roberta-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-improved_xlm_roberta_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-improved_xlm_roberta_base_pipeline_en.md
new file mode 100644
index 00000000000000..78e27438c83e0b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-improved_xlm_roberta_base_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English improved_xlm_roberta_base_pipeline pipeline XlmRoBertaForSequenceClassification from Anwaarma
+author: John Snow Labs
+name: improved_xlm_roberta_base_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`improved_xlm_roberta_base_pipeline` is a English model originally trained by Anwaarma.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/improved_xlm_roberta_base_pipeline_en_5.5.1_3.0_1734597862705.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/improved_xlm_roberta_base_pipeline_en_5.5.1_3.0_1734597862705.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("improved_xlm_roberta_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("improved_xlm_roberta_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|improved_xlm_roberta_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|655.2 MB|
+
+## References
+
+https://huggingface.co/Anwaarma/Improved-xlm-roberta-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-instruct_gpt_en.md b/docs/_posts/ahmedlone127/2024-12-19-instruct_gpt_en.md
new file mode 100644
index 00000000000000..048a3c0f660a41
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-instruct_gpt_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English instruct_gpt GPT2Transformer from Sharathhebbar24
+author: John Snow Labs
+name: instruct_gpt
+date: 2024-12-19
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`instruct_gpt` is a English model originally trained by Sharathhebbar24.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/instruct_gpt_en_5.5.1_3.0_1734591242510.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/instruct_gpt_en_5.5.1_3.0_1734591242510.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("instruct_gpt","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("instruct_gpt","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|instruct_gpt|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/Sharathhebbar24/Instruct_GPT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-instruct_gpt_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-instruct_gpt_pipeline_en.md
new file mode 100644
index 00000000000000..8b7a89fe63afb5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-instruct_gpt_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English instruct_gpt_pipeline pipeline GPT2Transformer from Sharathhebbar24
+author: John Snow Labs
+name: instruct_gpt_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`instruct_gpt_pipeline` is a English model originally trained by Sharathhebbar24.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/instruct_gpt_pipeline_en_5.5.1_3.0_1734591309058.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/instruct_gpt_pipeline_en_5.5.1_3.0_1734591309058.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("instruct_gpt_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("instruct_gpt_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|instruct_gpt_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/Sharathhebbar24/Instruct_GPT
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-javanese_sentiment_analysis_indobert_id.md b/docs/_posts/ahmedlone127/2024-12-19-javanese_sentiment_analysis_indobert_id.md
new file mode 100644
index 00000000000000..058d033a62db62
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-javanese_sentiment_analysis_indobert_id.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Indonesian javanese_sentiment_analysis_indobert BertForSequenceClassification from azizp128
+author: John Snow Labs
+name: javanese_sentiment_analysis_indobert
+date: 2024-12-19
+tags: [id, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: id
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`javanese_sentiment_analysis_indobert` is a Indonesian model originally trained by azizp128.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/javanese_sentiment_analysis_indobert_id_5.5.1_3.0_1734571203879.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/javanese_sentiment_analysis_indobert_id_5.5.1_3.0_1734571203879.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("javanese_sentiment_analysis_indobert","id") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("javanese_sentiment_analysis_indobert", "id")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|javanese_sentiment_analysis_indobert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|id|
+|Size:|466.4 MB|
+
+## References
+
+https://huggingface.co/azizp128/javanese-sentiment-analysis-indobert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-javanese_sentiment_analysis_indobert_pipeline_id.md b/docs/_posts/ahmedlone127/2024-12-19-javanese_sentiment_analysis_indobert_pipeline_id.md
new file mode 100644
index 00000000000000..753a81e85a540c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-javanese_sentiment_analysis_indobert_pipeline_id.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Indonesian javanese_sentiment_analysis_indobert_pipeline pipeline BertForSequenceClassification from azizp128
+author: John Snow Labs
+name: javanese_sentiment_analysis_indobert_pipeline
+date: 2024-12-19
+tags: [id, open_source, pipeline, onnx]
+task: Text Classification
+language: id
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`javanese_sentiment_analysis_indobert_pipeline` is a Indonesian model originally trained by azizp128.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/javanese_sentiment_analysis_indobert_pipeline_id_5.5.1_3.0_1734571227706.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/javanese_sentiment_analysis_indobert_pipeline_id_5.5.1_3.0_1734571227706.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("javanese_sentiment_analysis_indobert_pipeline", lang = "id")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("javanese_sentiment_analysis_indobert_pipeline", lang = "id")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|javanese_sentiment_analysis_indobert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|id|
+|Size:|466.4 MB|
+
+## References
+
+https://huggingface.co/azizp128/javanese-sentiment-analysis-indobert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-jinyong_gpt2_pipeline_zh.md b/docs/_posts/ahmedlone127/2024-12-19-jinyong_gpt2_pipeline_zh.md
new file mode 100644
index 00000000000000..841ed092ee502f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-jinyong_gpt2_pipeline_zh.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Chinese jinyong_gpt2_pipeline pipeline GPT2Transformer from supermy
+author: John Snow Labs
+name: jinyong_gpt2_pipeline
+date: 2024-12-19
+tags: [zh, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: zh
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`jinyong_gpt2_pipeline` is a Chinese model originally trained by supermy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/jinyong_gpt2_pipeline_zh_5.5.1_3.0_1734584754279.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/jinyong_gpt2_pipeline_zh_5.5.1_3.0_1734584754279.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("jinyong_gpt2_pipeline", lang = "zh")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("jinyong_gpt2_pipeline", lang = "zh")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|jinyong_gpt2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|zh|
+|Size:|467.3 MB|
+
+## References
+
+https://huggingface.co/supermy/jinyong-gpt2
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-jinyong_gpt2_zh.md b/docs/_posts/ahmedlone127/2024-12-19-jinyong_gpt2_zh.md
new file mode 100644
index 00000000000000..41de2531158c1e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-jinyong_gpt2_zh.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Chinese jinyong_gpt2 GPT2Transformer from supermy
+author: John Snow Labs
+name: jinyong_gpt2
+date: 2024-12-19
+tags: [zh, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: zh
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`jinyong_gpt2` is a Chinese model originally trained by supermy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/jinyong_gpt2_zh_5.5.1_3.0_1734584730486.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/jinyong_gpt2_zh_5.5.1_3.0_1734584730486.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("jinyong_gpt2","zh") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("jinyong_gpt2","zh") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|jinyong_gpt2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|zh|
+|Size:|467.3 MB|
+
+## References
+
+https://huggingface.co/supermy/jinyong-gpt2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-keyword_extractor_model_en.md b/docs/_posts/ahmedlone127/2024-12-19-keyword_extractor_model_en.md
new file mode 100644
index 00000000000000..2e48d44d2a0664
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-keyword_extractor_model_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English keyword_extractor_model T5Transformer from SaiSaketh
+author: John Snow Labs
+name: keyword_extractor_model
+date: 2024-12-19
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`keyword_extractor_model` is a English model originally trained by SaiSaketh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/keyword_extractor_model_en_5.5.1_3.0_1734567170767.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/keyword_extractor_model_en_5.5.1_3.0_1734567170767.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("keyword_extractor_model","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("keyword_extractor_model", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|keyword_extractor_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|266.8 MB|
+
+## References
+
+https://huggingface.co/SaiSaketh/keyword-extractor-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-keyword_extractor_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-keyword_extractor_model_pipeline_en.md
new file mode 100644
index 00000000000000..247ffe1ea22a1b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-keyword_extractor_model_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English keyword_extractor_model_pipeline pipeline T5Transformer from SaiSaketh
+author: John Snow Labs
+name: keyword_extractor_model_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`keyword_extractor_model_pipeline` is a English model originally trained by SaiSaketh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/keyword_extractor_model_pipeline_en_5.5.1_3.0_1734567190036.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/keyword_extractor_model_pipeline_en_5.5.1_3.0_1734567190036.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("keyword_extractor_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("keyword_extractor_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|keyword_extractor_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|266.8 MB|
+
+## References
+
+https://huggingface.co/SaiSaketh/keyword-extractor-model
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-latent_gpt2_medium_alpaca_e3_en.md b/docs/_posts/ahmedlone127/2024-12-19-latent_gpt2_medium_alpaca_e3_en.md
new file mode 100644
index 00000000000000..da8731df352433
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-latent_gpt2_medium_alpaca_e3_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English latent_gpt2_medium_alpaca_e3 GPT2Transformer from LordNoah
+author: John Snow Labs
+name: latent_gpt2_medium_alpaca_e3
+date: 2024-12-19
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`latent_gpt2_medium_alpaca_e3` is a English model originally trained by LordNoah.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/latent_gpt2_medium_alpaca_e3_en_5.5.1_3.0_1734590865883.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/latent_gpt2_medium_alpaca_e3_en_5.5.1_3.0_1734590865883.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("latent_gpt2_medium_alpaca_e3","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("latent_gpt2_medium_alpaca_e3","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|latent_gpt2_medium_alpaca_e3|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/LordNoah/latent_gpt2_medium_alpaca_e3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-latent_gpt2_medium_alpaca_e3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-latent_gpt2_medium_alpaca_e3_pipeline_en.md
new file mode 100644
index 00000000000000..5f2fbc3fd64d87
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-latent_gpt2_medium_alpaca_e3_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English latent_gpt2_medium_alpaca_e3_pipeline pipeline GPT2Transformer from LordNoah
+author: John Snow Labs
+name: latent_gpt2_medium_alpaca_e3_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`latent_gpt2_medium_alpaca_e3_pipeline` is a English model originally trained by LordNoah.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/latent_gpt2_medium_alpaca_e3_pipeline_en_5.5.1_3.0_1734590931688.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/latent_gpt2_medium_alpaca_e3_pipeline_en_5.5.1_3.0_1734590931688.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("latent_gpt2_medium_alpaca_e3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("latent_gpt2_medium_alpaca_e3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|latent_gpt2_medium_alpaca_e3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/LordNoah/latent_gpt2_medium_alpaca_e3
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-legal_pashto_prosecution_flan_t5_en.md b/docs/_posts/ahmedlone127/2024-12-19-legal_pashto_prosecution_flan_t5_en.md
new file mode 100644
index 00000000000000..95fff15afafba1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-legal_pashto_prosecution_flan_t5_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English legal_pashto_prosecution_flan_t5 T5Transformer from subha-roy
+author: John Snow Labs
+name: legal_pashto_prosecution_flan_t5
+date: 2024-12-19
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`legal_pashto_prosecution_flan_t5` is a English model originally trained by subha-roy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/legal_pashto_prosecution_flan_t5_en_5.5.1_3.0_1734567686543.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/legal_pashto_prosecution_flan_t5_en_5.5.1_3.0_1734567686543.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("legal_pashto_prosecution_flan_t5","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("legal_pashto_prosecution_flan_t5", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|legal_pashto_prosecution_flan_t5|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/subha-roy/legal-ps-prosecution-FLAN-T5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-legal_pashto_prosecution_flan_t5_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-legal_pashto_prosecution_flan_t5_pipeline_en.md
new file mode 100644
index 00000000000000..5b53c989a45c7a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-legal_pashto_prosecution_flan_t5_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English legal_pashto_prosecution_flan_t5_pipeline pipeline T5Transformer from subha-roy
+author: John Snow Labs
+name: legal_pashto_prosecution_flan_t5_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`legal_pashto_prosecution_flan_t5_pipeline` is a English model originally trained by subha-roy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/legal_pashto_prosecution_flan_t5_pipeline_en_5.5.1_3.0_1734567737037.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/legal_pashto_prosecution_flan_t5_pipeline_en_5.5.1_3.0_1734567737037.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("legal_pashto_prosecution_flan_t5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("legal_pashto_prosecution_flan_t5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|legal_pashto_prosecution_flan_t5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/subha-roy/legal-ps-prosecution-FLAN-T5
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-llama_3_7b_instruct_hf_int4_en.md b/docs/_posts/ahmedlone127/2024-12-19-llama_3_7b_instruct_hf_int4_en.md
new file mode 100644
index 00000000000000..01e3370a935b55
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-llama_3_7b_instruct_hf_int4_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: llama_3_7b_instruct_hf_int4 model from meta-llama
+author: John Snow Labs
+name: llama_3_7b_instruct_hf_int4
+date: 2024-12-19
+tags: [en, open_source, openvino]
+task: Text Generation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: openvino
+annotator: LLAMA3Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained LLAMA3Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`llama_3_7b_instruct_hf_int4` is a english model originally trained by meta-llama.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/llama_3_7b_instruct_hf_int4_en_5.5.1_3.0_1734607923506.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/llama_3_7b_instruct_hf_int4_en_5.5.1_3.0_1734607923506.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+seq2seq = LLAMA3Transformer.pretrained("llama_3_7b_instruct_hf_int4","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = LLAMA3Transformer.pretrained("llama_3_7b_instruct_hf_int4","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|llama_3_7b_instruct_hf_int4|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[documents]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|4.8 GB|
+
+## References
+
+https://huggingface.co/meta-llama/Llama-2-7b-chat-hf
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-maltese_coref_english_arabic_coref_en.md b/docs/_posts/ahmedlone127/2024-12-19-maltese_coref_english_arabic_coref_en.md
new file mode 100644
index 00000000000000..02da58baccbcf6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-maltese_coref_english_arabic_coref_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English maltese_coref_english_arabic_coref MarianTransformer from nlphuji
+author: John Snow Labs
+name: maltese_coref_english_arabic_coref
+date: 2024-12-19
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`maltese_coref_english_arabic_coref` is a English model originally trained by nlphuji.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/maltese_coref_english_arabic_coref_en_5.5.1_3.0_1734588100756.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/maltese_coref_english_arabic_coref_en_5.5.1_3.0_1734588100756.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("maltese_coref_english_arabic_coref","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("maltese_coref_english_arabic_coref","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|maltese_coref_english_arabic_coref|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|409.8 MB|
+
+## References
+
+https://huggingface.co/nlphuji/mt_coref_en_ar_coref
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-maltese_coref_english_arabic_coref_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-maltese_coref_english_arabic_coref_pipeline_en.md
new file mode 100644
index 00000000000000..40c4079a82d262
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-maltese_coref_english_arabic_coref_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English maltese_coref_english_arabic_coref_pipeline pipeline MarianTransformer from nlphuji
+author: John Snow Labs
+name: maltese_coref_english_arabic_coref_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`maltese_coref_english_arabic_coref_pipeline` is a English model originally trained by nlphuji.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/maltese_coref_english_arabic_coref_pipeline_en_5.5.1_3.0_1734588122284.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/maltese_coref_english_arabic_coref_pipeline_en_5.5.1_3.0_1734588122284.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("maltese_coref_english_arabic_coref_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("maltese_coref_english_arabic_coref_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|maltese_coref_english_arabic_coref_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.3 MB|
+
+## References
+
+https://huggingface.co/nlphuji/mt_coref_en_ar_coref
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-maltese_coref_english_french_gender_en.md b/docs/_posts/ahmedlone127/2024-12-19-maltese_coref_english_french_gender_en.md
new file mode 100644
index 00000000000000..4d0a1adc405424
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-maltese_coref_english_french_gender_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English maltese_coref_english_french_gender MarianTransformer from nlphuji
+author: John Snow Labs
+name: maltese_coref_english_french_gender
+date: 2024-12-19
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`maltese_coref_english_french_gender` is a English model originally trained by nlphuji.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/maltese_coref_english_french_gender_en_5.5.1_3.0_1734587848625.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/maltese_coref_english_french_gender_en_5.5.1_3.0_1734587848625.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("maltese_coref_english_french_gender","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("maltese_coref_english_french_gender","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|maltese_coref_english_french_gender|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|397.3 MB|
+
+## References
+
+https://huggingface.co/nlphuji/mt_coref_en_fr_gender
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-maltese_coref_english_french_gender_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-maltese_coref_english_french_gender_pipeline_en.md
new file mode 100644
index 00000000000000..eca7c29d3a822e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-maltese_coref_english_french_gender_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English maltese_coref_english_french_gender_pipeline pipeline MarianTransformer from nlphuji
+author: John Snow Labs
+name: maltese_coref_english_french_gender_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`maltese_coref_english_french_gender_pipeline` is a English model originally trained by nlphuji.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/maltese_coref_english_french_gender_pipeline_en_5.5.1_3.0_1734587871861.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/maltese_coref_english_french_gender_pipeline_en_5.5.1_3.0_1734587871861.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("maltese_coref_english_french_gender_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("maltese_coref_english_french_gender_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|maltese_coref_english_french_gender_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|397.9 MB|
+
+## References
+
+https://huggingface.co/nlphuji/mt_coref_en_fr_gender
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-maltese_coref_english_spanish_coref_en.md b/docs/_posts/ahmedlone127/2024-12-19-maltese_coref_english_spanish_coref_en.md
new file mode 100644
index 00000000000000..3b0bb5b339e469
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-maltese_coref_english_spanish_coref_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English maltese_coref_english_spanish_coref MarianTransformer from nlphuji
+author: John Snow Labs
+name: maltese_coref_english_spanish_coref
+date: 2024-12-19
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`maltese_coref_english_spanish_coref` is a English model originally trained by nlphuji.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/maltese_coref_english_spanish_coref_en_5.5.1_3.0_1734587850753.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/maltese_coref_english_spanish_coref_en_5.5.1_3.0_1734587850753.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("maltese_coref_english_spanish_coref","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("maltese_coref_english_spanish_coref","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|maltese_coref_english_spanish_coref|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|418.5 MB|
+
+## References
+
+https://huggingface.co/nlphuji/mt_coref_en_es_coref
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-maltese_coref_english_spanish_coref_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-maltese_coref_english_spanish_coref_pipeline_en.md
new file mode 100644
index 00000000000000..687a8a86e23ebf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-maltese_coref_english_spanish_coref_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English maltese_coref_english_spanish_coref_pipeline pipeline MarianTransformer from nlphuji
+author: John Snow Labs
+name: maltese_coref_english_spanish_coref_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`maltese_coref_english_spanish_coref_pipeline` is a English model originally trained by nlphuji.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/maltese_coref_english_spanish_coref_pipeline_en_5.5.1_3.0_1734587878174.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/maltese_coref_english_spanish_coref_pipeline_en_5.5.1_3.0_1734587878174.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("maltese_coref_english_spanish_coref_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("maltese_coref_english_spanish_coref_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|maltese_coref_english_spanish_coref_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|419.1 MB|
+
+## References
+
+https://huggingface.co/nlphuji/mt_coref_en_es_coref
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-mt5_base_anaphora_czech_3e_en.md b/docs/_posts/ahmedlone127/2024-12-19-mt5_base_anaphora_czech_3e_en.md
new file mode 100644
index 00000000000000..2df4fa085a2b1f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-mt5_base_anaphora_czech_3e_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mt5_base_anaphora_czech_3e T5Transformer from patrixtano
+author: John Snow Labs
+name: mt5_base_anaphora_czech_3e
+date: 2024-12-19
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_base_anaphora_czech_3e` is a English model originally trained by patrixtano.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_base_anaphora_czech_3e_en_5.5.1_3.0_1734566916249.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_base_anaphora_czech_3e_en_5.5.1_3.0_1734566916249.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("mt5_base_anaphora_czech_3e","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("mt5_base_anaphora_czech_3e", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_base_anaphora_czech_3e|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|2.3 GB|
+
+## References
+
+https://huggingface.co/patrixtano/mt5-base-anaphora_czech_3e
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-mt5_base_anaphora_czech_3e_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-mt5_base_anaphora_czech_3e_pipeline_en.md
new file mode 100644
index 00000000000000..5a121e1d15af05
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-mt5_base_anaphora_czech_3e_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mt5_base_anaphora_czech_3e_pipeline pipeline T5Transformer from patrixtano
+author: John Snow Labs
+name: mt5_base_anaphora_czech_3e_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_base_anaphora_czech_3e_pipeline` is a English model originally trained by patrixtano.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_base_anaphora_czech_3e_pipeline_en_5.5.1_3.0_1734567136819.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_base_anaphora_czech_3e_pipeline_en_5.5.1_3.0_1734567136819.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mt5_base_anaphora_czech_3e_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mt5_base_anaphora_czech_3e_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_base_anaphora_czech_3e_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|2.3 GB|
+
+## References
+
+https://huggingface.co/patrixtano/mt5-base-anaphora_czech_3e
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-mt5_small_bif02_en.md b/docs/_posts/ahmedlone127/2024-12-19-mt5_small_bif02_en.md
new file mode 100644
index 00000000000000..84a63745fca19e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-mt5_small_bif02_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mt5_small_bif02 T5Transformer from bif02
+author: John Snow Labs
+name: mt5_small_bif02
+date: 2024-12-19
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_small_bif02` is a English model originally trained by bif02.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_small_bif02_en_5.5.1_3.0_1734569715571.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_small_bif02_en_5.5.1_3.0_1734569715571.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("mt5_small_bif02","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("mt5_small_bif02", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_small_bif02|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/bif02/mt5_small
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-mt5_small_bif02_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-mt5_small_bif02_pipeline_en.md
new file mode 100644
index 00000000000000..f76b54ddd07586
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-mt5_small_bif02_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mt5_small_bif02_pipeline pipeline T5Transformer from bif02
+author: John Snow Labs
+name: mt5_small_bif02_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_small_bif02_pipeline` is a English model originally trained by bif02.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_small_bif02_pipeline_en_5.5.1_3.0_1734569865550.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_small_bif02_pipeline_en_5.5.1_3.0_1734569865550.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mt5_small_bif02_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mt5_small_bif02_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_small_bif02_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/bif02/mt5_small
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-numerical_en.md b/docs/_posts/ahmedlone127/2024-12-19-numerical_en.md
new file mode 100644
index 00000000000000..0b6e3c6fa2298c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-numerical_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English numerical BertForSequenceClassification from Ejada
+author: John Snow Labs
+name: numerical
+date: 2024-12-19
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`numerical` is a English model originally trained by Ejada.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/numerical_en_5.5.1_3.0_1734572051743.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/numerical_en_5.5.1_3.0_1734572051743.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("numerical","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("numerical", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|numerical|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/Ejada/numerical
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-numerical_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-numerical_pipeline_en.md
new file mode 100644
index 00000000000000..cbb82a7e244e7e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-numerical_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English numerical_pipeline pipeline BertForSequenceClassification from Ejada
+author: John Snow Labs
+name: numerical_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`numerical_pipeline` is a English model originally trained by Ejada.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/numerical_pipeline_en_5.5.1_3.0_1734572072443.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/numerical_pipeline_en_5.5.1_3.0_1734572072443.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("numerical_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("numerical_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|numerical_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/Ejada/numerical
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-opus_wmt_finetuned_enfr_en.md b/docs/_posts/ahmedlone127/2024-12-19-opus_wmt_finetuned_enfr_en.md
new file mode 100644
index 00000000000000..62eba177be9072
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-opus_wmt_finetuned_enfr_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_wmt_finetuned_enfr MarianTransformer from ethansimrm
+author: John Snow Labs
+name: opus_wmt_finetuned_enfr
+date: 2024-12-19
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_wmt_finetuned_enfr` is a English model originally trained by ethansimrm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_wmt_finetuned_enfr_en_5.5.1_3.0_1734587848603.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_wmt_finetuned_enfr_en_5.5.1_3.0_1734587848603.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_wmt_finetuned_enfr","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_wmt_finetuned_enfr","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_wmt_finetuned_enfr|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|397.2 MB|
+
+## References
+
+https://huggingface.co/ethansimrm/opus_wmt_finetuned_enfr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-opus_wmt_finetuned_enfr_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-opus_wmt_finetuned_enfr_pipeline_en.md
new file mode 100644
index 00000000000000..6a8f1fa0c8bdfa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-opus_wmt_finetuned_enfr_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_wmt_finetuned_enfr_pipeline pipeline MarianTransformer from ethansimrm
+author: John Snow Labs
+name: opus_wmt_finetuned_enfr_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_wmt_finetuned_enfr_pipeline` is a English model originally trained by ethansimrm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_wmt_finetuned_enfr_pipeline_en_5.5.1_3.0_1734587877334.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_wmt_finetuned_enfr_pipeline_en_5.5.1_3.0_1734587877334.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("opus_wmt_finetuned_enfr_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_wmt_finetuned_enfr_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_wmt_finetuned_enfr_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|397.7 MB|
+
+## References
+
+https://huggingface.co/ethansimrm/opus_wmt_finetuned_enfr
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-peace_bert_en.md b/docs/_posts/ahmedlone127/2024-12-19-peace_bert_en.md
new file mode 100644
index 00000000000000..d8fe8e22da46f7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-peace_bert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English peace_bert BertForSequenceClassification from BenjaminOcampo
+author: John Snow Labs
+name: peace_bert
+date: 2024-12-19
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`peace_bert` is a English model originally trained by BenjaminOcampo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/peace_bert_en_5.5.1_3.0_1734571898197.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/peace_bert_en_5.5.1_3.0_1734571898197.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("peace_bert","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("peace_bert", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|peace_bert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/BenjaminOcampo/peace_bert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-peace_bert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-peace_bert_pipeline_en.md
new file mode 100644
index 00000000000000..96f78cfff2aec0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-peace_bert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English peace_bert_pipeline pipeline BertForSequenceClassification from BenjaminOcampo
+author: John Snow Labs
+name: peace_bert_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`peace_bert_pipeline` is a English model originally trained by BenjaminOcampo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/peace_bert_pipeline_en_5.5.1_3.0_1734571920905.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/peace_bert_pipeline_en_5.5.1_3.0_1734571920905.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("peace_bert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("peace_bert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|peace_bert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/BenjaminOcampo/peace_bert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-predict_perception_xlmr_blame_assassin_en.md b/docs/_posts/ahmedlone127/2024-12-19-predict_perception_xlmr_blame_assassin_en.md
new file mode 100644
index 00000000000000..8ad21075b59e1f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-predict_perception_xlmr_blame_assassin_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English predict_perception_xlmr_blame_assassin XlmRoBertaForSequenceClassification from responsibility-framing
+author: John Snow Labs
+name: predict_perception_xlmr_blame_assassin
+date: 2024-12-19
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`predict_perception_xlmr_blame_assassin` is a English model originally trained by responsibility-framing.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/predict_perception_xlmr_blame_assassin_en_5.5.1_3.0_1734598643530.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/predict_perception_xlmr_blame_assassin_en_5.5.1_3.0_1734598643530.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("predict_perception_xlmr_blame_assassin","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("predict_perception_xlmr_blame_assassin", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|predict_perception_xlmr_blame_assassin|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|837.6 MB|
+
+## References
+
+https://huggingface.co/responsibility-framing/predict-perception-xlmr-blame-assassin
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-predict_perception_xlmr_blame_assassin_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-predict_perception_xlmr_blame_assassin_pipeline_en.md
new file mode 100644
index 00000000000000..2aaf3399070a05
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-predict_perception_xlmr_blame_assassin_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English predict_perception_xlmr_blame_assassin_pipeline pipeline XlmRoBertaForSequenceClassification from responsibility-framing
+author: John Snow Labs
+name: predict_perception_xlmr_blame_assassin_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`predict_perception_xlmr_blame_assassin_pipeline` is a English model originally trained by responsibility-framing.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/predict_perception_xlmr_blame_assassin_pipeline_en_5.5.1_3.0_1734598709514.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/predict_perception_xlmr_blame_assassin_pipeline_en_5.5.1_3.0_1734598709514.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("predict_perception_xlmr_blame_assassin_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("predict_perception_xlmr_blame_assassin_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|predict_perception_xlmr_blame_assassin_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|837.6 MB|
+
+## References
+
+https://huggingface.co/responsibility-framing/predict-perception-xlmr-blame-assassin
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-product_description_generator_bprateek_en.md b/docs/_posts/ahmedlone127/2024-12-19-product_description_generator_bprateek_en.md
new file mode 100644
index 00000000000000..2b9d60824df606
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-product_description_generator_bprateek_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English product_description_generator_bprateek GPT2Transformer from bprateek
+author: John Snow Labs
+name: product_description_generator_bprateek
+date: 2024-12-19
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`product_description_generator_bprateek` is a English model originally trained by bprateek.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/product_description_generator_bprateek_en_5.5.1_3.0_1734592957460.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/product_description_generator_bprateek_en_5.5.1_3.0_1734592957460.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("product_description_generator_bprateek","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("product_description_generator_bprateek","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|product_description_generator_bprateek|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.9 MB|
+
+## References
+
+https://huggingface.co/bprateek/product-description-generator
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-product_description_generator_bprateek_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-product_description_generator_bprateek_pipeline_en.md
new file mode 100644
index 00000000000000..15a46ec6b9323d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-product_description_generator_bprateek_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English product_description_generator_bprateek_pipeline pipeline GPT2Transformer from bprateek
+author: John Snow Labs
+name: product_description_generator_bprateek_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`product_description_generator_bprateek_pipeline` is a English model originally trained by bprateek.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/product_description_generator_bprateek_pipeline_en_5.5.1_3.0_1734592981172.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/product_description_generator_bprateek_pipeline_en_5.5.1_3.0_1734592981172.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("product_description_generator_bprateek_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("product_description_generator_bprateek_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|product_description_generator_bprateek_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.9 MB|
+
+## References
+
+https://huggingface.co/bprateek/product-description-generator
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-prompt_expansion_en.md b/docs/_posts/ahmedlone127/2024-12-19-prompt_expansion_en.md
new file mode 100644
index 00000000000000..0f64440d2f7dd0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-prompt_expansion_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English prompt_expansion GPT2Transformer from ghunkins
+author: John Snow Labs
+name: prompt_expansion
+date: 2024-12-19
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`prompt_expansion` is a English model originally trained by ghunkins.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/prompt_expansion_en_5.5.1_3.0_1734586269551.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/prompt_expansion_en_5.5.1_3.0_1734586269551.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("prompt_expansion","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("prompt_expansion","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|prompt_expansion|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|298.8 MB|
+
+## References
+
+https://huggingface.co/ghunkins/prompt-expansion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-prompt_expansion_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-prompt_expansion_pipeline_en.md
new file mode 100644
index 00000000000000..c2ec92cbde97c5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-prompt_expansion_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English prompt_expansion_pipeline pipeline GPT2Transformer from ghunkins
+author: John Snow Labs
+name: prompt_expansion_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`prompt_expansion_pipeline` is a English model originally trained by ghunkins.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/prompt_expansion_pipeline_en_5.5.1_3.0_1734586353702.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/prompt_expansion_pipeline_en_5.5.1_3.0_1734586353702.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("prompt_expansion_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("prompt_expansion_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|prompt_expansion_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|298.8 MB|
+
+## References
+
+https://huggingface.co/ghunkins/prompt-expansion
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-protgpt2_distilled_tiny_en.md b/docs/_posts/ahmedlone127/2024-12-19-protgpt2_distilled_tiny_en.md
new file mode 100644
index 00000000000000..bc1f77c1bc4176
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-protgpt2_distilled_tiny_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English protgpt2_distilled_tiny GPT2Transformer from littleworth
+author: John Snow Labs
+name: protgpt2_distilled_tiny
+date: 2024-12-19
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`protgpt2_distilled_tiny` is a English model originally trained by littleworth.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/protgpt2_distilled_tiny_en_5.5.1_3.0_1734588785105.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/protgpt2_distilled_tiny_en_5.5.1_3.0_1734588785105.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("protgpt2_distilled_tiny","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("protgpt2_distilled_tiny","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|protgpt2_distilled_tiny|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|146.4 MB|
+
+## References
+
+https://huggingface.co/littleworth/protgpt2-distilled-tiny
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-protgpt2_distilled_tiny_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-protgpt2_distilled_tiny_pipeline_en.md
new file mode 100644
index 00000000000000..6244955a08deee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-protgpt2_distilled_tiny_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English protgpt2_distilled_tiny_pipeline pipeline GPT2Transformer from littleworth
+author: John Snow Labs
+name: protgpt2_distilled_tiny_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`protgpt2_distilled_tiny_pipeline` is a English model originally trained by littleworth.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/protgpt2_distilled_tiny_pipeline_en_5.5.1_3.0_1734588792232.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/protgpt2_distilled_tiny_pipeline_en_5.5.1_3.0_1734588792232.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("protgpt2_distilled_tiny_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("protgpt2_distilled_tiny_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|protgpt2_distilled_tiny_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|146.4 MB|
+
+## References
+
+https://huggingface.co/littleworth/protgpt2-distilled-tiny
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-pruned_model_en.md b/docs/_posts/ahmedlone127/2024-12-19-pruned_model_en.md
new file mode 100644
index 00000000000000..86951856b0941d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-pruned_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English pruned_model DistilBertForQuestionAnswering from vxbrandon
+author: John Snow Labs
+name: pruned_model
+date: 2024-12-19
+tags: [distilbert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pruned_model` is a English model originally trained by vxbrandon.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pruned_model_en_5.5.1_3.0_1734568643483.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pruned_model_en_5.5.1_3.0_1734568643483.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("pruned_model","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering  
+    .pretrained("pruned_model", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pruned_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|742.6 MB|
+
+## References
+
+References
+
+References
+
+https://huggingface.co/vxbrandon/pruned_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-pruned_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-pruned_model_pipeline_en.md
new file mode 100644
index 00000000000000..bbdec205c809a2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-pruned_model_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English pruned_model_pipeline pipeline T5Transformer from Rakshith0808
+author: John Snow Labs
+name: pruned_model_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pruned_model_pipeline` is a English model originally trained by Rakshith0808.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pruned_model_pipeline_en_5.5.1_3.0_1734568712515.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pruned_model_pipeline_en_5.5.1_3.0_1734568712515.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("pruned_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("pruned_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pruned_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|742.6 MB|
+
+## References
+
+https://huggingface.co/Rakshith0808/pruned_model
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-qa_roberta_model_en.md b/docs/_posts/ahmedlone127/2024-12-19-qa_roberta_model_en.md
new file mode 100644
index 00000000000000..22676da434a02e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-qa_roberta_model_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English qa_roberta_model RoBertaForQuestionAnswering from MattNandavong
+author: John Snow Labs
+name: qa_roberta_model
+date: 2024-12-19
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_roberta_model` is a English model originally trained by MattNandavong.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_roberta_model_en_5.5.1_3.0_1734601075872.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_roberta_model_en_5.5.1_3.0_1734601075872.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("qa_roberta_model","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("qa_roberta_model", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_roberta_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|462.3 MB|
+
+## References
+
+https://huggingface.co/MattNandavong/QA-roberta-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-qa_roberta_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-qa_roberta_model_pipeline_en.md
new file mode 100644
index 00000000000000..f77fc44cf11143
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-qa_roberta_model_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English qa_roberta_model_pipeline pipeline RoBertaForQuestionAnswering from MattNandavong
+author: John Snow Labs
+name: qa_roberta_model_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_roberta_model_pipeline` is a English model originally trained by MattNandavong.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_roberta_model_pipeline_en_5.5.1_3.0_1734601103883.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_roberta_model_pipeline_en_5.5.1_3.0_1734601103883.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("qa_roberta_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("qa_roberta_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_roberta_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|462.4 MB|
+
+## References
+
+https://huggingface.co/MattNandavong/QA-roberta-model
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-rag_model_t5_ai_en.md b/docs/_posts/ahmedlone127/2024-12-19-rag_model_t5_ai_en.md
new file mode 100644
index 00000000000000..0a0cbcd7dabb32
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-rag_model_t5_ai_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English rag_model_t5_ai T5Transformer from ArmaanDhande
+author: John Snow Labs
+name: rag_model_t5_ai
+date: 2024-12-19
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rag_model_t5_ai` is a English model originally trained by ArmaanDhande.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rag_model_t5_ai_en_5.5.1_3.0_1734567992636.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rag_model_t5_ai_en_5.5.1_3.0_1734567992636.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("rag_model_t5_ai","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("rag_model_t5_ai", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rag_model_t5_ai|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|239.7 MB|
+
+## References
+
+https://huggingface.co/ArmaanDhande/rag_model_t5_AI
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-rag_model_t5_ai_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-rag_model_t5_ai_pipeline_en.md
new file mode 100644
index 00000000000000..50ca249b35f130
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-rag_model_t5_ai_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English rag_model_t5_ai_pipeline pipeline T5Transformer from ArmaanDhande
+author: John Snow Labs
+name: rag_model_t5_ai_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rag_model_t5_ai_pipeline` is a English model originally trained by ArmaanDhande.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rag_model_t5_ai_pipeline_en_5.5.1_3.0_1734568018586.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rag_model_t5_ai_pipeline_en_5.5.1_3.0_1734568018586.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("rag_model_t5_ai_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("rag_model_t5_ai_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rag_model_t5_ai_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|239.7 MB|
+
+## References
+
+https://huggingface.co/ArmaanDhande/rag_model_t5_AI
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-reason_nepal_bhasa_en.md b/docs/_posts/ahmedlone127/2024-12-19-reason_nepal_bhasa_en.md
new file mode 100644
index 00000000000000..029cf19a77464c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-reason_nepal_bhasa_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English reason_nepal_bhasa BertForSequenceClassification from Mahmoud3899
+author: John Snow Labs
+name: reason_nepal_bhasa
+date: 2024-12-19
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`reason_nepal_bhasa` is a English model originally trained by Mahmoud3899.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/reason_nepal_bhasa_en_5.5.1_3.0_1734571229110.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/reason_nepal_bhasa_en_5.5.1_3.0_1734571229110.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("reason_nepal_bhasa","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("reason_nepal_bhasa", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|reason_nepal_bhasa|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/Mahmoud3899/reason_new
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-reason_nepal_bhasa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-reason_nepal_bhasa_pipeline_en.md
new file mode 100644
index 00000000000000..84749c576c61c7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-reason_nepal_bhasa_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English reason_nepal_bhasa_pipeline pipeline BertForSequenceClassification from Mahmoud3899
+author: John Snow Labs
+name: reason_nepal_bhasa_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`reason_nepal_bhasa_pipeline` is a English model originally trained by Mahmoud3899.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/reason_nepal_bhasa_pipeline_en_5.5.1_3.0_1734571254963.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/reason_nepal_bhasa_pipeline_en_5.5.1_3.0_1734571254963.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("reason_nepal_bhasa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("reason_nepal_bhasa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|reason_nepal_bhasa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/Mahmoud3899/reason_new
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-results_altan01_en.md b/docs/_posts/ahmedlone127/2024-12-19-results_altan01_en.md
new file mode 100644
index 00000000000000..d64a2574feab46
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-results_altan01_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English results_altan01 BertForSequenceClassification from altan01
+author: John Snow Labs
+name: results_altan01
+date: 2024-12-19
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_altan01` is a English model originally trained by altan01.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_altan01_en_5.5.1_3.0_1734570987610.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_altan01_en_5.5.1_3.0_1734570987610.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("results_altan01","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("results_altan01", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_altan01|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|414.7 MB|
+
+## References
+
+https://huggingface.co/altan01/results
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-results_altan01_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-results_altan01_pipeline_en.md
new file mode 100644
index 00000000000000..6aeb5f5487b56b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-results_altan01_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English results_altan01_pipeline pipeline BertForSequenceClassification from altan01
+author: John Snow Labs
+name: results_altan01_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_altan01_pipeline` is a English model originally trained by altan01.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_altan01_pipeline_en_5.5.1_3.0_1734571011367.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_altan01_pipeline_en_5.5.1_3.0_1734571011367.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("results_altan01_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("results_altan01_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_altan01_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|414.7 MB|
+
+## References
+
+https://huggingface.co/altan01/results
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-results_normankier_en.md b/docs/_posts/ahmedlone127/2024-12-19-results_normankier_en.md
new file mode 100644
index 00000000000000..a2f2aa1bfe57fb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-results_normankier_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English results_normankier T5Transformer from normankier
+author: John Snow Labs
+name: results_normankier
+date: 2024-12-19
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_normankier` is a English model originally trained by normankier.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_normankier_en_5.5.1_3.0_1734566566864.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_normankier_en_5.5.1_3.0_1734566566864.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("results_normankier","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("results_normankier", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_normankier|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/normankier/results
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-results_normankier_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-results_normankier_pipeline_en.md
new file mode 100644
index 00000000000000..38ce0a98f46bf0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-results_normankier_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English results_normankier_pipeline pipeline T5Transformer from normankier
+author: John Snow Labs
+name: results_normankier_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_normankier_pipeline` is a English model originally trained by normankier.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_normankier_pipeline_en_5.5.1_3.0_1734566617921.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_normankier_pipeline_en_5.5.1_3.0_1734566617921.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("results_normankier_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("results_normankier_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_normankier_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/normankier/results
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-results_supkon_en.md b/docs/_posts/ahmedlone127/2024-12-19-results_supkon_en.md
new file mode 100644
index 00000000000000..e5c4f0287b6b82
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-results_supkon_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English results_supkon T5Transformer from supkon
+author: John Snow Labs
+name: results_supkon
+date: 2024-12-19
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_supkon` is a English model originally trained by supkon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_supkon_en_5.5.1_3.0_1734566433938.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_supkon_en_5.5.1_3.0_1734566433938.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("results_supkon","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("results_supkon", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_supkon|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|519.5 MB|
+
+## References
+
+https://huggingface.co/supkon/results
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-results_supkon_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-results_supkon_pipeline_en.md
new file mode 100644
index 00000000000000..c77ed30eac02e7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-results_supkon_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English results_supkon_pipeline pipeline T5Transformer from supkon
+author: John Snow Labs
+name: results_supkon_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_supkon_pipeline` is a English model originally trained by supkon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_supkon_pipeline_en_5.5.1_3.0_1734566601534.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_supkon_pipeline_en_5.5.1_3.0_1734566601534.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("results_supkon_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("results_supkon_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_supkon_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|519.5 MB|
+
+## References
+
+https://huggingface.co/supkon/results
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-roberta_attacker_en.md b/docs/_posts/ahmedlone127/2024-12-19-roberta_attacker_en.md
new file mode 100644
index 00000000000000..7004833b01c64d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-roberta_attacker_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_attacker RoBertaForTokenClassification from Cyber-ThreaD
+author: John Snow Labs
+name: roberta_attacker
+date: 2024-12-19
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_attacker` is a English model originally trained by Cyber-ThreaD.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_attacker_en_5.5.1_3.0_1734594453360.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_attacker_en_5.5.1_3.0_1734594453360.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("roberta_attacker","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_attacker", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_attacker|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|423.0 MB|
+
+## References
+
+https://huggingface.co/Cyber-ThreaD/RoBERTa-AttackER
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-roberta_attacker_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-roberta_attacker_pipeline_en.md
new file mode 100644
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@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_attacker_pipeline pipeline RoBertaForTokenClassification from Cyber-ThreaD
+author: John Snow Labs
+name: roberta_attacker_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_attacker_pipeline` is a English model originally trained by Cyber-ThreaD.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_attacker_pipeline_en_5.5.1_3.0_1734594492410.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_attacker_pipeline_en_5.5.1_3.0_1734594492410.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_attacker_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_attacker_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_attacker_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|423.0 MB|
+
+## References
+
+https://huggingface.co/Cyber-ThreaD/RoBERTa-AttackER
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-roberta_base_en.md b/docs/_posts/ahmedlone127/2024-12-19-roberta_base_en.md
new file mode 100644
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--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-roberta_base_en.md
@@ -0,0 +1,99 @@
+---
+layout: model
+title: RoBERTa base model
+author: John Snow Labs
+name: roberta_base
+date: 2024-12-19
+tags: [en, english, roberta, embeddings, open_source, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in [this paper](https://arxiv.org/abs/1907.11692) and first released in [this repository](https://github.com/pytorch/fairseq/tree/master/examples/roberta). This model is case-sensitive: it makes a difference between english and English.
+
+RoBERTa is a transformers model pretrained on a large corpus of English data in a self-supervised fashion. This means it was pretrained on the raw texts only, with no humans labeling them in any way (which is why it can use lots of publicly available data) with an automatic process to generate inputs and labels from those texts.
+
+More precisely, it was pretrained with the Masked language modeling (MLM) objective. Taking a sentence, the model randomly masks 15% of the words in the input then runs the entire masked sentence through the model and has to predict the masked words. This is different from traditional recurrent neural networks (RNNs) that usually see the words one after the other, or from autoregressive models like GPT which internally mask the future tokens. It allows the model to learn a bidirectional representation of the sentence.
+
+This way, the model learns an inner representation of the English language that can then be used to extract features useful for downstream tasks: if you have a dataset of labeled sentences, for instance, you can train a standard classifier using the features produced by the BERT model as inputs.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_en_5.5.1_3.0_1734573103884.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_en_5.5.1_3.0_1734573103884.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+embeddings = RoBertaEmbeddings.pretrained("roberta_base", "en") \
+.setInputCols("sentence", "token") \
+.setOutputCol("embeddings")
+```
+```scala
+val embeddings = RoBertaEmbeddings.pretrained("roberta_base", "en")
+.setInputCols("sentence", "token")
+.setOutputCol("embeddings")
+val pipeline = new Pipeline().setStages(Array(document_assembler, sentence_detector, tokenizer, embeddings))
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.embed.roberta").predict("""Put your text here.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|447.4 MB|
+
+## References
+
+References
+
+[https://huggingface.co/roberta-base](https://huggingface.co/roberta-base)
+
+## Benchmarking
+
+```bash
+
+Benchmarking
+
+
+When fine-tuned on downstream tasks, this model achieves the following results:
+
+Glue test results:
+
+| Task | MNLI | QQP  | QNLI | SST-2 | CoLA | STS-B | MRPC | RTE  |
+|:----:|:----:|:----:|:----:|:-----:|:----:|:-----:|:----:|:----:|
+|      | 87.6 | 91.9 | 92.8 | 94.8  | 63.6 | 91.2  | 90.2 | 78.7 |
+```
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-roberta_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-roberta_base_pipeline_en.md
new file mode 100644
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--- /dev/null
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@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_base_pipeline pipeline RoBertaForQuestionAnswering from ClemMbote
+author: John Snow Labs
+name: roberta_base_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_pipeline` is a English model originally trained by ClemMbote.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_pipeline_en_5.5.1_3.0_1734573132907.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_pipeline_en_5.5.1_3.0_1734573132907.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|447.4 MB|
+
+## References
+
+https://huggingface.co/ClemMbote/roberta-base
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-roberta_dnrti_en.md b/docs/_posts/ahmedlone127/2024-12-19-roberta_dnrti_en.md
new file mode 100644
index 00000000000000..4ee8f4bd429270
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-roberta_dnrti_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English roberta_dnrti RoBertaForTokenClassification from anonymouspd
+author: John Snow Labs
+name: roberta_dnrti
+date: 2024-12-19
+tags: [roberta, en, open_source, token_classification, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_dnrti` is a English model originally trained by anonymouspd.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_dnrti_en_5.5.1_3.0_1734595031391.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_dnrti_en_5.5.1_3.0_1734595031391.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+    
+tokenizer = Tokenizer() \
+        .setInputCols(["document"]) \
+        .setOutputCol("token")
+        
+    
+tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_dnrti","en") \
+            .setInputCols(["document","token"]) \
+            .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val tokenizer = Tokenizer() \
+        .setInputCols(Array("document")) \
+        .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification  
+    .pretrained("roberta_dnrti", "en")
+    .setInputCols(Array("document","token")) 
+    .setOutputCol("ner") 
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_dnrti|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|426.1 MB|
+
+## References
+
+References
+
+https://huggingface.co/anonymouspd/RoBERTa-DNRTI
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-roberta_dnrti_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-roberta_dnrti_pipeline_en.md
new file mode 100644
index 00000000000000..ed1b9e07460b30
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-roberta_dnrti_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_dnrti_pipeline pipeline RoBertaForTokenClassification from Cyber-ThreaD
+author: John Snow Labs
+name: roberta_dnrti_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_dnrti_pipeline` is a English model originally trained by Cyber-ThreaD.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_dnrti_pipeline_en_5.5.1_3.0_1734595070484.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_dnrti_pipeline_en_5.5.1_3.0_1734595070484.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_dnrti_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_dnrti_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_dnrti_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|426.1 MB|
+
+## References
+
+https://huggingface.co/Cyber-ThreaD/RoBERTa-DNRTI
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-roberta_large_squad_en.md b/docs/_posts/ahmedlone127/2024-12-19-roberta_large_squad_en.md
new file mode 100644
index 00000000000000..55964303b075e2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-roberta_large_squad_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English roberta_large_squad RoBertaForQuestionAnswering from varun-v-rao
+author: John Snow Labs
+name: roberta_large_squad
+date: 2024-12-19
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_squad` is a English model originally trained by varun-v-rao.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_squad_en_5.5.1_3.0_1734601532615.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_squad_en_5.5.1_3.0_1734601532615.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_large_squad","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_large_squad", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_large_squad|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/varun-v-rao/roberta-large-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-roberta_large_squad_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-roberta_large_squad_pipeline_en.md
new file mode 100644
index 00000000000000..33fffd7c403ca3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-roberta_large_squad_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_large_squad_pipeline pipeline RoBertaForQuestionAnswering from varun-v-rao
+author: John Snow Labs
+name: roberta_large_squad_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_squad_pipeline` is a English model originally trained by varun-v-rao.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_squad_pipeline_en_5.5.1_3.0_1734601598791.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_squad_pipeline_en_5.5.1_3.0_1734601598791.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_large_squad_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_large_squad_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_large_squad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/varun-v-rao/roberta-large-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-social_behavior_emotions_en.md b/docs/_posts/ahmedlone127/2024-12-19-social_behavior_emotions_en.md
new file mode 100644
index 00000000000000..13be2bcba94173
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-social_behavior_emotions_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English social_behavior_emotions XlmRoBertaForSequenceClassification from JoseLuis95
+author: John Snow Labs
+name: social_behavior_emotions
+date: 2024-12-19
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`social_behavior_emotions` is a English model originally trained by JoseLuis95.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/social_behavior_emotions_en_5.5.1_3.0_1734598004475.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/social_behavior_emotions_en_5.5.1_3.0_1734598004475.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("social_behavior_emotions","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("social_behavior_emotions", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|social_behavior_emotions|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|831.8 MB|
+
+## References
+
+https://huggingface.co/JoseLuis95/social-behavior-emotions
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-social_behavior_emotions_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-social_behavior_emotions_pipeline_en.md
new file mode 100644
index 00000000000000..ae6b180d6a99e2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-social_behavior_emotions_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English social_behavior_emotions_pipeline pipeline XlmRoBertaForSequenceClassification from JoseLuis95
+author: John Snow Labs
+name: social_behavior_emotions_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`social_behavior_emotions_pipeline` is a English model originally trained by JoseLuis95.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/social_behavior_emotions_pipeline_en_5.5.1_3.0_1734598096115.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/social_behavior_emotions_pipeline_en_5.5.1_3.0_1734598096115.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("social_behavior_emotions_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("social_behavior_emotions_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|social_behavior_emotions_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|831.9 MB|
+
+## References
+
+https://huggingface.co/JoseLuis95/social-behavior-emotions
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-sportsfanghost_en.md b/docs/_posts/ahmedlone127/2024-12-19-sportsfanghost_en.md
new file mode 100644
index 00000000000000..6aa5d6d5a62a60
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-sportsfanghost_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English sportsfanghost GPT2Transformer from SSI
+author: John Snow Labs
+name: sportsfanghost
+date: 2024-12-19
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sportsfanghost` is a English model originally trained by SSI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sportsfanghost_en_5.5.1_3.0_1734589192568.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sportsfanghost_en_5.5.1_3.0_1734589192568.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("sportsfanghost","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("sportsfanghost","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sportsfanghost|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/SSI/SportsFanGhost
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-sportsfanghost_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-sportsfanghost_pipeline_en.md
new file mode 100644
index 00000000000000..972606c72e09fe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-sportsfanghost_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English sportsfanghost_pipeline pipeline GPT2Transformer from SSI
+author: John Snow Labs
+name: sportsfanghost_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sportsfanghost_pipeline` is a English model originally trained by SSI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sportsfanghost_pipeline_en_5.5.1_3.0_1734589260460.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sportsfanghost_pipeline_en_5.5.1_3.0_1734589260460.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sportsfanghost_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sportsfanghost_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sportsfanghost_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/SSI/SportsFanGhost
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-ssh_355m_en.md b/docs/_posts/ahmedlone127/2024-12-19-ssh_355m_en.md
new file mode 100644
index 00000000000000..d1763e990342bd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-ssh_355m_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English ssh_355m GPT2Transformer from Sharathhebbar24
+author: John Snow Labs
+name: ssh_355m
+date: 2024-12-19
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ssh_355m` is a English model originally trained by Sharathhebbar24.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ssh_355m_en_5.5.1_3.0_1734591620004.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ssh_355m_en_5.5.1_3.0_1734591620004.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("ssh_355m","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("ssh_355m","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ssh_355m|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/Sharathhebbar24/SSH_355M
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-ssh_355m_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-ssh_355m_pipeline_en.md
new file mode 100644
index 00000000000000..227fb36c6033b9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-ssh_355m_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English ssh_355m_pipeline pipeline GPT2Transformer from Sharathhebbar24
+author: John Snow Labs
+name: ssh_355m_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ssh_355m_pipeline` is a English model originally trained by Sharathhebbar24.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ssh_355m_pipeline_en_5.5.1_3.0_1734591685978.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ssh_355m_pipeline_en_5.5.1_3.0_1734591685978.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ssh_355m_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ssh_355m_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ssh_355m_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/Sharathhebbar24/SSH_355M
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-subjectiveqa_specific_en.md b/docs/_posts/ahmedlone127/2024-12-19-subjectiveqa_specific_en.md
new file mode 100644
index 00000000000000..3e48a0128214ab
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-subjectiveqa_specific_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English subjectiveqa_specific BertForSequenceClassification from gtfintechlab
+author: John Snow Labs
+name: subjectiveqa_specific
+date: 2024-12-19
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`subjectiveqa_specific` is a English model originally trained by gtfintechlab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/subjectiveqa_specific_en_5.5.1_3.0_1734571385401.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/subjectiveqa_specific_en_5.5.1_3.0_1734571385401.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("subjectiveqa_specific","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("subjectiveqa_specific", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|subjectiveqa_specific|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|411.6 MB|
+
+## References
+
+https://huggingface.co/gtfintechlab/SubjECTiveQA-SPECIFIC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-subjectiveqa_specific_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-subjectiveqa_specific_pipeline_en.md
new file mode 100644
index 00000000000000..d0ce1a543636d2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-subjectiveqa_specific_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English subjectiveqa_specific_pipeline pipeline BertForSequenceClassification from gtfintechlab
+author: John Snow Labs
+name: subjectiveqa_specific_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`subjectiveqa_specific_pipeline` is a English model originally trained by gtfintechlab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/subjectiveqa_specific_pipeline_en_5.5.1_3.0_1734571407092.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/subjectiveqa_specific_pipeline_en_5.5.1_3.0_1734571407092.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("subjectiveqa_specific_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("subjectiveqa_specific_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|subjectiveqa_specific_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|411.7 MB|
+
+## References
+
+https://huggingface.co/gtfintechlab/SubjECTiveQA-SPECIFIC
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-t5_ie_budquo_finetuned_en.md b/docs/_posts/ahmedlone127/2024-12-19-t5_ie_budquo_finetuned_en.md
new file mode 100644
index 00000000000000..dad1e90df430bf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-t5_ie_budquo_finetuned_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_ie_budquo_finetuned T5Transformer from RamsesDIIP
+author: John Snow Labs
+name: t5_ie_budquo_finetuned
+date: 2024-12-19
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_ie_budquo_finetuned` is a English model originally trained by RamsesDIIP.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_ie_budquo_finetuned_en_5.5.1_3.0_1734567257810.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_ie_budquo_finetuned_en_5.5.1_3.0_1734567257810.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_ie_budquo_finetuned","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_ie_budquo_finetuned", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_ie_budquo_finetuned|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|2.2 GB|
+
+## References
+
+https://huggingface.co/RamsesDIIP/t5-ie-budquo-finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-t5_ie_budquo_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-t5_ie_budquo_finetuned_pipeline_en.md
new file mode 100644
index 00000000000000..013dc283fdebda
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-t5_ie_budquo_finetuned_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_ie_budquo_finetuned_pipeline pipeline T5Transformer from RamsesDIIP
+author: John Snow Labs
+name: t5_ie_budquo_finetuned_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_ie_budquo_finetuned_pipeline` is a English model originally trained by RamsesDIIP.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_ie_budquo_finetuned_pipeline_en_5.5.1_3.0_1734567420953.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_ie_budquo_finetuned_pipeline_en_5.5.1_3.0_1734567420953.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_ie_budquo_finetuned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_ie_budquo_finetuned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_ie_budquo_finetuned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|2.2 GB|
+
+## References
+
+https://huggingface.co/RamsesDIIP/t5-ie-budquo-finetuned
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-t5_large_sum_dpo_25k_8_1ep_en.md b/docs/_posts/ahmedlone127/2024-12-19-t5_large_sum_dpo_25k_8_1ep_en.md
new file mode 100644
index 00000000000000..444874b35e6425
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-t5_large_sum_dpo_25k_8_1ep_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_large_sum_dpo_25k_8_1ep T5Transformer from Muadil
+author: John Snow Labs
+name: t5_large_sum_dpo_25k_8_1ep
+date: 2024-12-19
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_large_sum_dpo_25k_8_1ep` is a English model originally trained by Muadil.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_large_sum_dpo_25k_8_1ep_en_5.5.1_3.0_1734569129417.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_large_sum_dpo_25k_8_1ep_en_5.5.1_3.0_1734569129417.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_large_sum_dpo_25k_8_1ep","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_large_sum_dpo_25k_8_1ep", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_large_sum_dpo_25k_8_1ep|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/Muadil/t5-large_sum_DPO_25k_8_1ep
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-t5_large_sum_dpo_25k_8_1ep_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-t5_large_sum_dpo_25k_8_1ep_pipeline_en.md
new file mode 100644
index 00000000000000..17ceb1899d0c3c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-t5_large_sum_dpo_25k_8_1ep_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_large_sum_dpo_25k_8_1ep_pipeline pipeline T5Transformer from Muadil
+author: John Snow Labs
+name: t5_large_sum_dpo_25k_8_1ep_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_large_sum_dpo_25k_8_1ep_pipeline` is a English model originally trained by Muadil.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_large_sum_dpo_25k_8_1ep_pipeline_en_5.5.1_3.0_1734569620390.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_large_sum_dpo_25k_8_1ep_pipeline_en_5.5.1_3.0_1734569620390.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_large_sum_dpo_25k_8_1ep_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_large_sum_dpo_25k_8_1ep_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_large_sum_dpo_25k_8_1ep_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/Muadil/t5-large_sum_DPO_25k_8_1ep
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-t5_large_sum_dpo_50k_4_1ep_en.md b/docs/_posts/ahmedlone127/2024-12-19-t5_large_sum_dpo_50k_4_1ep_en.md
new file mode 100644
index 00000000000000..af67dd4b56acfe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-t5_large_sum_dpo_50k_4_1ep_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_large_sum_dpo_50k_4_1ep T5Transformer from Muadil
+author: John Snow Labs
+name: t5_large_sum_dpo_50k_4_1ep
+date: 2024-12-19
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_large_sum_dpo_50k_4_1ep` is a English model originally trained by Muadil.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_large_sum_dpo_50k_4_1ep_en_5.5.1_3.0_1734569347878.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_large_sum_dpo_50k_4_1ep_en_5.5.1_3.0_1734569347878.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_large_sum_dpo_50k_4_1ep","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_large_sum_dpo_50k_4_1ep", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_large_sum_dpo_50k_4_1ep|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/Muadil/t5-large_sum_DPO_50k_4_1ep
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-t5_large_sum_dpo_50k_4_1ep_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-t5_large_sum_dpo_50k_4_1ep_pipeline_en.md
new file mode 100644
index 00000000000000..73e75a0ca38aa4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-t5_large_sum_dpo_50k_4_1ep_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_large_sum_dpo_50k_4_1ep_pipeline pipeline T5Transformer from Muadil
+author: John Snow Labs
+name: t5_large_sum_dpo_50k_4_1ep_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_large_sum_dpo_50k_4_1ep_pipeline` is a English model originally trained by Muadil.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_large_sum_dpo_50k_4_1ep_pipeline_en_5.5.1_3.0_1734569835512.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_large_sum_dpo_50k_4_1ep_pipeline_en_5.5.1_3.0_1734569835512.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_large_sum_dpo_50k_4_1ep_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_large_sum_dpo_50k_4_1ep_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_large_sum_dpo_50k_4_1ep_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/Muadil/t5-large_sum_DPO_50k_4_1ep
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-text_generation_bangla_model_en.md b/docs/_posts/ahmedlone127/2024-12-19-text_generation_bangla_model_en.md
new file mode 100644
index 00000000000000..d710fb9ebd89dd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-text_generation_bangla_model_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English text_generation_bangla_model GPT2Transformer from shahidul034
+author: John Snow Labs
+name: text_generation_bangla_model
+date: 2024-12-19
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`text_generation_bangla_model` is a English model originally trained by shahidul034.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/text_generation_bangla_model_en_5.5.1_3.0_1734590350129.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/text_generation_bangla_model_en_5.5.1_3.0_1734590350129.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("text_generation_bangla_model","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("text_generation_bangla_model","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|text_generation_bangla_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.7 MB|
+
+## References
+
+https://huggingface.co/shahidul034/text_generation_bangla_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-text_generation_bangla_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-text_generation_bangla_model_pipeline_en.md
new file mode 100644
index 00000000000000..a753ccbada3e41
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-text_generation_bangla_model_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English text_generation_bangla_model_pipeline pipeline GPT2Transformer from shahidul034
+author: John Snow Labs
+name: text_generation_bangla_model_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`text_generation_bangla_model_pipeline` is a English model originally trained by shahidul034.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/text_generation_bangla_model_pipeline_en_5.5.1_3.0_1734590373584.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/text_generation_bangla_model_pipeline_en_5.5.1_3.0_1734590373584.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("text_generation_bangla_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("text_generation_bangla_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|text_generation_bangla_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.7 MB|
+
+## References
+
+https://huggingface.co/shahidul034/text_generation_bangla_model
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-tinier_bart_en.md b/docs/_posts/ahmedlone127/2024-12-19-tinier_bart_en.md
new file mode 100644
index 00000000000000..56a77ac52a1051
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-tinier_bart_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English tinier_bart BartTransformer from sshleifer
+author: John Snow Labs
+name: tinier_bart
+date: 2024-12-19
+tags: [en, open_source, onnx, text_generation, bart]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BartTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tinier_bart` is a English model originally trained by sshleifer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tinier_bart_en_5.5.1_3.0_1734577320641.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tinier_bart_en_5.5.1_3.0_1734577320641.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = BartTransformer.pretrained("tinier_bart","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = BartTransformer.pretrained("tinier_bart","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tinier_bart|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|14.9 MB|
+
+## References
+
+https://huggingface.co/sshleifer/tinier_bart
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-tinier_bart_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-tinier_bart_pipeline_en.md
new file mode 100644
index 00000000000000..e97aaaa425906f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-tinier_bart_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English tinier_bart_pipeline pipeline BartTransformer from sshleifer
+author: John Snow Labs
+name: tinier_bart_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tinier_bart_pipeline` is a English model originally trained by sshleifer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tinier_bart_pipeline_en_5.5.1_3.0_1734577321857.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tinier_bart_pipeline_en_5.5.1_3.0_1734577321857.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("tinier_bart_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("tinier_bart_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tinier_bart_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|14.9 MB|
+
+## References
+
+https://huggingface.co/sshleifer/tinier_bart
+
+## Included Models
+
+- DocumentAssembler
+- BartTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-tiny_t5forconditionalgeneration_qgallouedec_en.md b/docs/_posts/ahmedlone127/2024-12-19-tiny_t5forconditionalgeneration_qgallouedec_en.md
new file mode 100644
index 00000000000000..e21eb68d2cf205
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-tiny_t5forconditionalgeneration_qgallouedec_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English tiny_t5forconditionalgeneration_qgallouedec T5Transformer from qgallouedec
+author: John Snow Labs
+name: tiny_t5forconditionalgeneration_qgallouedec
+date: 2024-12-19
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_t5forconditionalgeneration_qgallouedec` is a English model originally trained by qgallouedec.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_t5forconditionalgeneration_qgallouedec_en_5.5.1_3.0_1734566684526.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_t5forconditionalgeneration_qgallouedec_en_5.5.1_3.0_1734566684526.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("tiny_t5forconditionalgeneration_qgallouedec","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("tiny_t5forconditionalgeneration_qgallouedec", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tiny_t5forconditionalgeneration_qgallouedec|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|4.5 MB|
+
+## References
+
+https://huggingface.co/qgallouedec/tiny-T5ForConditionalGeneration
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-tiny_t5forconditionalgeneration_qgallouedec_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-tiny_t5forconditionalgeneration_qgallouedec_pipeline_en.md
new file mode 100644
index 00000000000000..c9f104309051dc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-tiny_t5forconditionalgeneration_qgallouedec_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English tiny_t5forconditionalgeneration_qgallouedec_pipeline pipeline T5Transformer from qgallouedec
+author: John Snow Labs
+name: tiny_t5forconditionalgeneration_qgallouedec_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_t5forconditionalgeneration_qgallouedec_pipeline` is a English model originally trained by qgallouedec.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_t5forconditionalgeneration_qgallouedec_pipeline_en_5.5.1_3.0_1734566685152.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_t5forconditionalgeneration_qgallouedec_pipeline_en_5.5.1_3.0_1734566685152.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("tiny_t5forconditionalgeneration_qgallouedec_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("tiny_t5forconditionalgeneration_qgallouedec_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tiny_t5forconditionalgeneration_qgallouedec_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|4.5 MB|
+
+## References
+
+https://huggingface.co/qgallouedec/tiny-T5ForConditionalGeneration
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-toxic_sentence_generator_en.md b/docs/_posts/ahmedlone127/2024-12-19-toxic_sentence_generator_en.md
new file mode 100644
index 00000000000000..a48fead6842d3b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-toxic_sentence_generator_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English toxic_sentence_generator GPT2Transformer from theastronuts
+author: John Snow Labs
+name: toxic_sentence_generator
+date: 2024-12-19
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`toxic_sentence_generator` is a English model originally trained by theastronuts.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/toxic_sentence_generator_en_5.5.1_3.0_1734589417163.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/toxic_sentence_generator_en_5.5.1_3.0_1734589417163.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("toxic_sentence_generator","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("toxic_sentence_generator","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|toxic_sentence_generator|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/theastronuts/toxic_sentence_generator
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-toxic_sentence_generator_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-toxic_sentence_generator_pipeline_en.md
new file mode 100644
index 00000000000000..3326baac23b6e5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-toxic_sentence_generator_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English toxic_sentence_generator_pipeline pipeline GPT2Transformer from theastronuts
+author: John Snow Labs
+name: toxic_sentence_generator_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`toxic_sentence_generator_pipeline` is a English model originally trained by theastronuts.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/toxic_sentence_generator_pipeline_en_5.5.1_3.0_1734589440504.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/toxic_sentence_generator_pipeline_en_5.5.1_3.0_1734589440504.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("toxic_sentence_generator_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("toxic_sentence_generator_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|toxic_sentence_generator_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/theastronuts/toxic_sentence_generator
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-trainer_wheel_model_en.md b/docs/_posts/ahmedlone127/2024-12-19-trainer_wheel_model_en.md
new file mode 100644
index 00000000000000..b8fa587cdc6c2a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-trainer_wheel_model_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English trainer_wheel_model T5Transformer from ai1-test
+author: John Snow Labs
+name: trainer_wheel_model
+date: 2024-12-19
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`trainer_wheel_model` is a English model originally trained by ai1-test.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/trainer_wheel_model_en_5.5.1_3.0_1734566975518.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/trainer_wheel_model_en_5.5.1_3.0_1734566975518.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("trainer_wheel_model","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("trainer_wheel_model", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|trainer_wheel_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/ai1-test/trainer_wheel_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-trainer_wheel_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-trainer_wheel_model_pipeline_en.md
new file mode 100644
index 00000000000000..221e88b3c14c09
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-trainer_wheel_model_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English trainer_wheel_model_pipeline pipeline T5Transformer from ai1-test
+author: John Snow Labs
+name: trainer_wheel_model_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`trainer_wheel_model_pipeline` is a English model originally trained by ai1-test.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/trainer_wheel_model_pipeline_en_5.5.1_3.0_1734567027746.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/trainer_wheel_model_pipeline_en_5.5.1_3.0_1734567027746.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("trainer_wheel_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("trainer_wheel_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|trainer_wheel_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/ai1-test/trainer_wheel_model
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-twi_eng_dialect_en.md b/docs/_posts/ahmedlone127/2024-12-19-twi_eng_dialect_en.md
new file mode 100644
index 00000000000000..37d76191e8341a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-twi_eng_dialect_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English twi_eng_dialect XlmRoBertaForSequenceClassification from sgjwong
+author: John Snow Labs
+name: twi_eng_dialect
+date: 2024-12-19
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twi_eng_dialect` is a English model originally trained by sgjwong.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twi_eng_dialect_en_5.5.1_3.0_1734596687093.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twi_eng_dialect_en_5.5.1_3.0_1734596687093.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("twi_eng_dialect","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("twi_eng_dialect", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|twi_eng_dialect|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/sgjwong/tw_eng_dialect
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-twi_eng_dialect_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-twi_eng_dialect_pipeline_en.md
new file mode 100644
index 00000000000000..e6864924b24209
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-twi_eng_dialect_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English twi_eng_dialect_pipeline pipeline XlmRoBertaForSequenceClassification from sgjwong
+author: John Snow Labs
+name: twi_eng_dialect_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twi_eng_dialect_pipeline` is a English model originally trained by sgjwong.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twi_eng_dialect_pipeline_en_5.5.1_3.0_1734596746361.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twi_eng_dialect_pipeline_en_5.5.1_3.0_1734596746361.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("twi_eng_dialect_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("twi_eng_dialect_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|twi_eng_dialect_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/sgjwong/tw_eng_dialect
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-wizzgptv2_en.md b/docs/_posts/ahmedlone127/2024-12-19-wizzgptv2_en.md
new file mode 100644
index 00000000000000..72b2eb8969a69e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-wizzgptv2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English wizzgptv2 GPT2Transformer from Wizz13150
+author: John Snow Labs
+name: wizzgptv2
+date: 2024-12-19
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`wizzgptv2` is a English model originally trained by Wizz13150.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/wizzgptv2_en_5.5.1_3.0_1734592653507.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/wizzgptv2_en_5.5.1_3.0_1734592653507.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("wizzgptv2","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("wizzgptv2","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|wizzgptv2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/Wizz13150/WizzGPTv2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-wizzgptv2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-wizzgptv2_pipeline_en.md
new file mode 100644
index 00000000000000..0b5887fff35328
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-wizzgptv2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English wizzgptv2_pipeline pipeline GPT2Transformer from Wizz13150
+author: John Snow Labs
+name: wizzgptv2_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`wizzgptv2_pipeline` is a English model originally trained by Wizz13150.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/wizzgptv2_pipeline_en_5.5.1_3.0_1734592677767.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/wizzgptv2_pipeline_en_5.5.1_3.0_1734592677767.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("wizzgptv2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("wizzgptv2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|wizzgptv2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/Wizz13150/WizzGPTv2
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_caste_hatespech_xlmr_en.md b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_caste_hatespech_xlmr_en.md
new file mode 100644
index 00000000000000..e0feab4dfee5e8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_caste_hatespech_xlmr_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_caste_hatespech_xlmr XlmRoBertaForSequenceClassification from mdosama39
+author: John Snow Labs
+name: xlm_roberta_base_caste_hatespech_xlmr
+date: 2024-12-19
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_caste_hatespech_xlmr` is a English model originally trained by mdosama39.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_caste_hatespech_xlmr_en_5.5.1_3.0_1734598855584.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_caste_hatespech_xlmr_en_5.5.1_3.0_1734598855584.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_caste_hatespech_xlmr","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_caste_hatespech_xlmr", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_caste_hatespech_xlmr|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|811.6 MB|
+
+## References
+
+https://huggingface.co/mdosama39/xlm-roberta-base-Caste-HateSpech-xlmr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_caste_hatespech_xlmr_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_caste_hatespech_xlmr_pipeline_en.md
new file mode 100644
index 00000000000000..f1f1eeea4f362f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_caste_hatespech_xlmr_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_caste_hatespech_xlmr_pipeline pipeline XlmRoBertaForSequenceClassification from mdosama39
+author: John Snow Labs
+name: xlm_roberta_base_caste_hatespech_xlmr_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_caste_hatespech_xlmr_pipeline` is a English model originally trained by mdosama39.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_caste_hatespech_xlmr_pipeline_en_5.5.1_3.0_1734598971296.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_caste_hatespech_xlmr_pipeline_en_5.5.1_3.0_1734598971296.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_caste_hatespech_xlmr_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_caste_hatespech_xlmr_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_caste_hatespech_xlmr_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|811.6 MB|
+
+## References
+
+https://huggingface.co/mdosama39/xlm-roberta-base-Caste-HateSpech-xlmr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_fakenews_dravidian_en.md b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_fakenews_dravidian_en.md
new file mode 100644
index 00000000000000..087f54d7f786b6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_fakenews_dravidian_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_fakenews_dravidian XlmRoBertaForSequenceClassification from mdosama39
+author: John Snow Labs
+name: xlm_roberta_base_fakenews_dravidian
+date: 2024-12-19
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_fakenews_dravidian` is a English model originally trained by mdosama39.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_fakenews_dravidian_en_5.5.1_3.0_1734598393215.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_fakenews_dravidian_en_5.5.1_3.0_1734598393215.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_fakenews_dravidian","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_fakenews_dravidian", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_fakenews_dravidian|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|785.3 MB|
+
+## References
+
+https://huggingface.co/mdosama39/xlm-roberta-base-FakeNews-Dravidian
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_fakenews_dravidian_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_fakenews_dravidian_pipeline_en.md
new file mode 100644
index 00000000000000..ca018042791650
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_fakenews_dravidian_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_fakenews_dravidian_pipeline pipeline XlmRoBertaForSequenceClassification from mdosama39
+author: John Snow Labs
+name: xlm_roberta_base_fakenews_dravidian_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_fakenews_dravidian_pipeline` is a English model originally trained by mdosama39.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_fakenews_dravidian_pipeline_en_5.5.1_3.0_1734598532121.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_fakenews_dravidian_pipeline_en_5.5.1_3.0_1734598532121.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_fakenews_dravidian_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_fakenews_dravidian_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_fakenews_dravidian_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|785.3 MB|
+
+## References
+
+https://huggingface.co/mdosama39/xlm-roberta-base-FakeNews-Dravidian
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_final_mixed_aug_insert_synonym_2_en.md b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_final_mixed_aug_insert_synonym_2_en.md
new file mode 100644
index 00000000000000..e06ee308c42513
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_final_mixed_aug_insert_synonym_2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_final_mixed_aug_insert_synonym_2 XlmRoBertaForSequenceClassification from ThuyNT03
+author: John Snow Labs
+name: xlm_roberta_base_final_mixed_aug_insert_synonym_2
+date: 2024-12-19
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_final_mixed_aug_insert_synonym_2` is a English model originally trained by ThuyNT03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_final_mixed_aug_insert_synonym_2_en_5.5.1_3.0_1734598563871.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_final_mixed_aug_insert_synonym_2_en_5.5.1_3.0_1734598563871.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_final_mixed_aug_insert_synonym_2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_final_mixed_aug_insert_synonym_2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_final_mixed_aug_insert_synonym_2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|795.2 MB|
+
+## References
+
+https://huggingface.co/ThuyNT03/xlm-roberta-base-Final_Mixed-aug_insert_synonym-2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_final_mixed_aug_insert_synonym_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_final_mixed_aug_insert_synonym_2_pipeline_en.md
new file mode 100644
index 00000000000000..864ebaef577a5f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_final_mixed_aug_insert_synonym_2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_final_mixed_aug_insert_synonym_2_pipeline pipeline XlmRoBertaForSequenceClassification from ThuyNT03
+author: John Snow Labs
+name: xlm_roberta_base_final_mixed_aug_insert_synonym_2_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_final_mixed_aug_insert_synonym_2_pipeline` is a English model originally trained by ThuyNT03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_final_mixed_aug_insert_synonym_2_pipeline_en_5.5.1_3.0_1734598687897.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_final_mixed_aug_insert_synonym_2_pipeline_en_5.5.1_3.0_1734598687897.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_final_mixed_aug_insert_synonym_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_final_mixed_aug_insert_synonym_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_final_mixed_aug_insert_synonym_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|795.3 MB|
+
+## References
+
+https://huggingface.co/ThuyNT03/xlm-roberta-base-Final_Mixed-aug_insert_synonym-2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_finetuned_emo_une_en.md b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_finetuned_emo_une_en.md
new file mode 100644
index 00000000000000..17766d073cfdaf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_finetuned_emo_une_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_emo_une XlmRoBertaForSequenceClassification from Gregorig
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_emo_une
+date: 2024-12-19
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_emo_une` is a English model originally trained by Gregorig.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_emo_une_en_5.5.1_3.0_1734596683786.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_emo_une_en_5.5.1_3.0_1734596683786.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_finetuned_emo_une","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_finetuned_emo_une", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_emo_une|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|796.4 MB|
+
+## References
+
+https://huggingface.co/Gregorig/xlm-roberta-base-finetuned-emo_une
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_finetuned_emo_une_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_finetuned_emo_une_pipeline_en.md
new file mode 100644
index 00000000000000..fbda74a357e99a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_finetuned_emo_une_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_emo_une_pipeline pipeline XlmRoBertaForSequenceClassification from Gregorig
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_emo_une_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_emo_une_pipeline` is a English model originally trained by Gregorig.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_emo_une_pipeline_en_5.5.1_3.0_1734596817899.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_emo_une_pipeline_en_5.5.1_3.0_1734596817899.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_emo_une_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_emo_une_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_emo_une_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|796.4 MB|
+
+## References
+
+https://huggingface.co/Gregorig/xlm-roberta-base-finetuned-emo_une
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_finetuned_language_identification_ninazh_en.md b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_finetuned_language_identification_ninazh_en.md
new file mode 100644
index 00000000000000..2352290d14ea89
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_finetuned_language_identification_ninazh_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_language_identification_ninazh XlmRoBertaForSequenceClassification from ninazh
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_language_identification_ninazh
+date: 2024-12-19
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_language_identification_ninazh` is a English model originally trained by ninazh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_language_identification_ninazh_en_5.5.1_3.0_1734596263915.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_language_identification_ninazh_en_5.5.1_3.0_1734596263915.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_finetuned_language_identification_ninazh","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_finetuned_language_identification_ninazh", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_language_identification_ninazh|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|904.0 MB|
+
+## References
+
+https://huggingface.co/ninazh/xlm-roberta-base-finetuned-language-identification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_finetuned_language_identification_ninazh_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_finetuned_language_identification_ninazh_pipeline_en.md
new file mode 100644
index 00000000000000..25b5ca37994ef9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_finetuned_language_identification_ninazh_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_language_identification_ninazh_pipeline pipeline XlmRoBertaForSequenceClassification from ninazh
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_language_identification_ninazh_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_language_identification_ninazh_pipeline` is a English model originally trained by ninazh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_language_identification_ninazh_pipeline_en_5.5.1_3.0_1734596357700.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_language_identification_ninazh_pipeline_en_5.5.1_3.0_1734596357700.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_language_identification_ninazh_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_language_identification_ninazh_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_language_identification_ninazh_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|904.0 MB|
+
+## References
+
+https://huggingface.co/ninazh/xlm-roberta-base-finetuned-language-identification
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_finetuned_marc_english_daveccampbell_en.md b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_finetuned_marc_english_daveccampbell_en.md
new file mode 100644
index 00000000000000..8e7e482caf1e84
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_finetuned_marc_english_daveccampbell_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_marc_english_daveccampbell XlmRoBertaForSequenceClassification from daveccampbell
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_marc_english_daveccampbell
+date: 2024-12-19
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_marc_english_daveccampbell` is a English model originally trained by daveccampbell.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_marc_english_daveccampbell_en_5.5.1_3.0_1734596176969.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_marc_english_daveccampbell_en_5.5.1_3.0_1734596176969.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_finetuned_marc_english_daveccampbell","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_finetuned_marc_english_daveccampbell", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_marc_english_daveccampbell|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|833.4 MB|
+
+## References
+
+https://huggingface.co/daveccampbell/xlm-roberta-base-finetuned-marc-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_finetuned_marc_english_daveccampbell_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_finetuned_marc_english_daveccampbell_pipeline_en.md
new file mode 100644
index 00000000000000..2241aec2cabcc0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_finetuned_marc_english_daveccampbell_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_marc_english_daveccampbell_pipeline pipeline XlmRoBertaForSequenceClassification from daveccampbell
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_marc_english_daveccampbell_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_marc_english_daveccampbell_pipeline` is a English model originally trained by daveccampbell.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_marc_english_daveccampbell_pipeline_en_5.5.1_3.0_1734596267187.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_marc_english_daveccampbell_pipeline_en_5.5.1_3.0_1734596267187.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_marc_english_daveccampbell_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_marc_english_daveccampbell_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_marc_english_daveccampbell_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|833.5 MB|
+
+## References
+
+https://huggingface.co/daveccampbell/xlm-roberta-base-finetuned-marc-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_finetuned_t_overall_en.md b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_finetuned_t_overall_en.md
new file mode 100644
index 00000000000000..5b5aa3336d071b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_finetuned_t_overall_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_t_overall XlmRoBertaForSequenceClassification from Gregorig
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_t_overall
+date: 2024-12-19
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_t_overall` is a English model originally trained by Gregorig.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_t_overall_en_5.5.1_3.0_1734597074876.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_t_overall_en_5.5.1_3.0_1734597074876.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_finetuned_t_overall","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_finetuned_t_overall", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_t_overall|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|796.4 MB|
+
+## References
+
+https://huggingface.co/Gregorig/xlm-roberta-base-finetuned-t_overall
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_finetuned_t_overall_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_finetuned_t_overall_pipeline_en.md
new file mode 100644
index 00000000000000..e7cfb402334662
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_finetuned_t_overall_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_t_overall_pipeline pipeline XlmRoBertaForSequenceClassification from Gregorig
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_t_overall_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_t_overall_pipeline` is a English model originally trained by Gregorig.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_t_overall_pipeline_en_5.5.1_3.0_1734597199969.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_t_overall_pipeline_en_5.5.1_3.0_1734597199969.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_t_overall_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_t_overall_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_t_overall_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|796.4 MB|
+
+## References
+
+https://huggingface.co/Gregorig/xlm-roberta-base-finetuned-t_overall
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_finetuning_semeval_all_then_wrime_all_first_epoch3_test03_en.md b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_finetuning_semeval_all_then_wrime_all_first_epoch3_test03_en.md
new file mode 100644
index 00000000000000..8db1d283f88aa7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_finetuning_semeval_all_then_wrime_all_first_epoch3_test03_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuning_semeval_all_then_wrime_all_first_epoch3_test03 XlmRoBertaForSequenceClassification from grrfdghebsz
+author: John Snow Labs
+name: xlm_roberta_base_finetuning_semeval_all_then_wrime_all_first_epoch3_test03
+date: 2024-12-19
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuning_semeval_all_then_wrime_all_first_epoch3_test03` is a English model originally trained by grrfdghebsz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuning_semeval_all_then_wrime_all_first_epoch3_test03_en_5.5.1_3.0_1734597404013.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuning_semeval_all_then_wrime_all_first_epoch3_test03_en_5.5.1_3.0_1734597404013.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_finetuning_semeval_all_then_wrime_all_first_epoch3_test03","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_finetuning_semeval_all_then_wrime_all_first_epoch3_test03", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuning_semeval_all_then_wrime_all_first_epoch3_test03|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|812.5 MB|
+
+## References
+
+https://huggingface.co/grrfdghebsz/xlm-roberta-base-finetuning-semeval-all-then-wrime-all-first-epoch3-test03
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_finetuning_semeval_all_then_wrime_all_first_epoch3_test03_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_finetuning_semeval_all_then_wrime_all_first_epoch3_test03_pipeline_en.md
new file mode 100644
index 00000000000000..3b500be30039b1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_finetuning_semeval_all_then_wrime_all_first_epoch3_test03_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuning_semeval_all_then_wrime_all_first_epoch3_test03_pipeline pipeline XlmRoBertaForSequenceClassification from grrfdghebsz
+author: John Snow Labs
+name: xlm_roberta_base_finetuning_semeval_all_then_wrime_all_first_epoch3_test03_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuning_semeval_all_then_wrime_all_first_epoch3_test03_pipeline` is a English model originally trained by grrfdghebsz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuning_semeval_all_then_wrime_all_first_epoch3_test03_pipeline_en_5.5.1_3.0_1734597522149.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuning_semeval_all_then_wrime_all_first_epoch3_test03_pipeline_en_5.5.1_3.0_1734597522149.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuning_semeval_all_then_wrime_all_first_epoch3_test03_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuning_semeval_all_then_wrime_all_first_epoch3_test03_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuning_semeval_all_then_wrime_all_first_epoch3_test03_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|812.6 MB|
+
+## References
+
+https://huggingface.co/grrfdghebsz/xlm-roberta-base-finetuning-semeval-all-then-wrime-all-first-epoch3-test03
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_lr0_0001_seed42_basic_original_kinyarwanda_amh_eng_train_en.md b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_lr0_0001_seed42_basic_original_kinyarwanda_amh_eng_train_en.md
new file mode 100644
index 00000000000000..3e435e3be739f5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_lr0_0001_seed42_basic_original_kinyarwanda_amh_eng_train_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_lr0_0001_seed42_basic_original_kinyarwanda_amh_eng_train XlmRoBertaForSequenceClassification from shanhy
+author: John Snow Labs
+name: xlm_roberta_base_lr0_0001_seed42_basic_original_kinyarwanda_amh_eng_train
+date: 2024-12-19
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_lr0_0001_seed42_basic_original_kinyarwanda_amh_eng_train` is a English model originally trained by shanhy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_lr0_0001_seed42_basic_original_kinyarwanda_amh_eng_train_en_5.5.1_3.0_1734597739657.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_lr0_0001_seed42_basic_original_kinyarwanda_amh_eng_train_en_5.5.1_3.0_1734597739657.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_lr0_0001_seed42_basic_original_kinyarwanda_amh_eng_train","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_lr0_0001_seed42_basic_original_kinyarwanda_amh_eng_train", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_lr0_0001_seed42_basic_original_kinyarwanda_amh_eng_train|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|815.6 MB|
+
+## References
+
+https://huggingface.co/shanhy/xlm-roberta-base_lr0.0001_seed42_basic_original_kin-amh-eng_train
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_lr0_0001_seed42_basic_original_kinyarwanda_amh_eng_train_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_lr0_0001_seed42_basic_original_kinyarwanda_amh_eng_train_pipeline_en.md
new file mode 100644
index 00000000000000..07d4220ad3c54f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_lr0_0001_seed42_basic_original_kinyarwanda_amh_eng_train_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_lr0_0001_seed42_basic_original_kinyarwanda_amh_eng_train_pipeline pipeline XlmRoBertaForSequenceClassification from shanhy
+author: John Snow Labs
+name: xlm_roberta_base_lr0_0001_seed42_basic_original_kinyarwanda_amh_eng_train_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_lr0_0001_seed42_basic_original_kinyarwanda_amh_eng_train_pipeline` is a English model originally trained by shanhy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_lr0_0001_seed42_basic_original_kinyarwanda_amh_eng_train_pipeline_en_5.5.1_3.0_1734597861205.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_lr0_0001_seed42_basic_original_kinyarwanda_amh_eng_train_pipeline_en_5.5.1_3.0_1734597861205.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_lr0_0001_seed42_basic_original_kinyarwanda_amh_eng_train_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_lr0_0001_seed42_basic_original_kinyarwanda_amh_eng_train_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_lr0_0001_seed42_basic_original_kinyarwanda_amh_eng_train_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|815.6 MB|
+
+## References
+
+https://huggingface.co/shanhy/xlm-roberta-base_lr0.0001_seed42_basic_original_kin-amh-eng_train
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_lr0_0001_seed42_esp_kinyarwanda_eng_train_en.md b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_lr0_0001_seed42_esp_kinyarwanda_eng_train_en.md
new file mode 100644
index 00000000000000..51b9ae406b5f90
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_lr0_0001_seed42_esp_kinyarwanda_eng_train_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_lr0_0001_seed42_esp_kinyarwanda_eng_train XlmRoBertaForSequenceClassification from shanhy
+author: John Snow Labs
+name: xlm_roberta_base_lr0_0001_seed42_esp_kinyarwanda_eng_train
+date: 2024-12-19
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_lr0_0001_seed42_esp_kinyarwanda_eng_train` is a English model originally trained by shanhy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_lr0_0001_seed42_esp_kinyarwanda_eng_train_en_5.5.1_3.0_1734598113155.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_lr0_0001_seed42_esp_kinyarwanda_eng_train_en_5.5.1_3.0_1734598113155.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_lr0_0001_seed42_esp_kinyarwanda_eng_train","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_lr0_0001_seed42_esp_kinyarwanda_eng_train", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_lr0_0001_seed42_esp_kinyarwanda_eng_train|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|825.8 MB|
+
+## References
+
+https://huggingface.co/shanhy/xlm-roberta-base_lr0.0001_seed42_esp-kin-eng_train
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_lr0_0001_seed42_esp_kinyarwanda_eng_train_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_lr0_0001_seed42_esp_kinyarwanda_eng_train_pipeline_en.md
new file mode 100644
index 00000000000000..490a6334d82bb7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_lr0_0001_seed42_esp_kinyarwanda_eng_train_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_lr0_0001_seed42_esp_kinyarwanda_eng_train_pipeline pipeline XlmRoBertaForSequenceClassification from shanhy
+author: John Snow Labs
+name: xlm_roberta_base_lr0_0001_seed42_esp_kinyarwanda_eng_train_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_lr0_0001_seed42_esp_kinyarwanda_eng_train_pipeline` is a English model originally trained by shanhy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_lr0_0001_seed42_esp_kinyarwanda_eng_train_pipeline_en_5.5.1_3.0_1734598231567.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_lr0_0001_seed42_esp_kinyarwanda_eng_train_pipeline_en_5.5.1_3.0_1734598231567.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_lr0_0001_seed42_esp_kinyarwanda_eng_train_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_lr0_0001_seed42_esp_kinyarwanda_eng_train_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_lr0_0001_seed42_esp_kinyarwanda_eng_train_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|825.9 MB|
+
+## References
+
+https://huggingface.co/shanhy/xlm-roberta-base_lr0.0001_seed42_esp-kin-eng_train
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_lr2e_05_seed42_amh_esp_eng_train_en.md b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_lr2e_05_seed42_amh_esp_eng_train_en.md
new file mode 100644
index 00000000000000..d09d38d151aacf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_lr2e_05_seed42_amh_esp_eng_train_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_lr2e_05_seed42_amh_esp_eng_train XlmRoBertaForSequenceClassification from shanhy
+author: John Snow Labs
+name: xlm_roberta_base_lr2e_05_seed42_amh_esp_eng_train
+date: 2024-12-19
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_lr2e_05_seed42_amh_esp_eng_train` is a English model originally trained by shanhy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_lr2e_05_seed42_amh_esp_eng_train_en_5.5.1_3.0_1734597390626.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_lr2e_05_seed42_amh_esp_eng_train_en_5.5.1_3.0_1734597390626.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_lr2e_05_seed42_amh_esp_eng_train","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_lr2e_05_seed42_amh_esp_eng_train", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_lr2e_05_seed42_amh_esp_eng_train|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|810.5 MB|
+
+## References
+
+https://huggingface.co/shanhy/xlm-roberta-base_lr2e-05_seed42_amh-esp-eng_train
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_lr2e_05_seed42_amh_esp_eng_train_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_lr2e_05_seed42_amh_esp_eng_train_pipeline_en.md
new file mode 100644
index 00000000000000..b153a2e461e01e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_lr2e_05_seed42_amh_esp_eng_train_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_lr2e_05_seed42_amh_esp_eng_train_pipeline pipeline XlmRoBertaForSequenceClassification from shanhy
+author: John Snow Labs
+name: xlm_roberta_base_lr2e_05_seed42_amh_esp_eng_train_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_lr2e_05_seed42_amh_esp_eng_train_pipeline` is a English model originally trained by shanhy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_lr2e_05_seed42_amh_esp_eng_train_pipeline_en_5.5.1_3.0_1734597517724.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_lr2e_05_seed42_amh_esp_eng_train_pipeline_en_5.5.1_3.0_1734597517724.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_lr2e_05_seed42_amh_esp_eng_train_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_lr2e_05_seed42_amh_esp_eng_train_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_lr2e_05_seed42_amh_esp_eng_train_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|810.5 MB|
+
+## References
+
+https://huggingface.co/shanhy/xlm-roberta-base_lr2e-05_seed42_amh-esp-eng_train
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_lr5e_06_seed42_amh_hau_eng_train_en.md b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_lr5e_06_seed42_amh_hau_eng_train_en.md
new file mode 100644
index 00000000000000..a4d87327bb6f51
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_lr5e_06_seed42_amh_hau_eng_train_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_lr5e_06_seed42_amh_hau_eng_train XlmRoBertaForSequenceClassification from shanhy
+author: John Snow Labs
+name: xlm_roberta_base_lr5e_06_seed42_amh_hau_eng_train
+date: 2024-12-19
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_lr5e_06_seed42_amh_hau_eng_train` is a English model originally trained by shanhy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_lr5e_06_seed42_amh_hau_eng_train_en_5.5.1_3.0_1734597865225.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_lr5e_06_seed42_amh_hau_eng_train_en_5.5.1_3.0_1734597865225.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_lr5e_06_seed42_amh_hau_eng_train","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_lr5e_06_seed42_amh_hau_eng_train", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_lr5e_06_seed42_amh_hau_eng_train|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|801.8 MB|
+
+## References
+
+https://huggingface.co/shanhy/xlm-roberta-base_lr5e-06_seed42_amh-hau-eng_train
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_lr5e_06_seed42_amh_hau_eng_train_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_lr5e_06_seed42_amh_hau_eng_train_pipeline_en.md
new file mode 100644
index 00000000000000..4abdc321a2082b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_lr5e_06_seed42_amh_hau_eng_train_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_lr5e_06_seed42_amh_hau_eng_train_pipeline pipeline XlmRoBertaForSequenceClassification from shanhy
+author: John Snow Labs
+name: xlm_roberta_base_lr5e_06_seed42_amh_hau_eng_train_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_lr5e_06_seed42_amh_hau_eng_train_pipeline` is a English model originally trained by shanhy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_lr5e_06_seed42_amh_hau_eng_train_pipeline_en_5.5.1_3.0_1734598007234.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_lr5e_06_seed42_amh_hau_eng_train_pipeline_en_5.5.1_3.0_1734598007234.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_lr5e_06_seed42_amh_hau_eng_train_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_lr5e_06_seed42_amh_hau_eng_train_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_lr5e_06_seed42_amh_hau_eng_train_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|801.8 MB|
+
+## References
+
+https://huggingface.co/shanhy/xlm-roberta-base_lr5e-06_seed42_amh-hau-eng_train
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_lr5e_06_seed42_basic_original_kinyarwanda_hau_eng_train_en.md b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_lr5e_06_seed42_basic_original_kinyarwanda_hau_eng_train_en.md
new file mode 100644
index 00000000000000..1650c64c60f9f3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_lr5e_06_seed42_basic_original_kinyarwanda_hau_eng_train_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_lr5e_06_seed42_basic_original_kinyarwanda_hau_eng_train XlmRoBertaForSequenceClassification from shanhy
+author: John Snow Labs
+name: xlm_roberta_base_lr5e_06_seed42_basic_original_kinyarwanda_hau_eng_train
+date: 2024-12-19
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_lr5e_06_seed42_basic_original_kinyarwanda_hau_eng_train` is a English model originally trained by shanhy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_lr5e_06_seed42_basic_original_kinyarwanda_hau_eng_train_en_5.5.1_3.0_1734596884224.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_lr5e_06_seed42_basic_original_kinyarwanda_hau_eng_train_en_5.5.1_3.0_1734596884224.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_lr5e_06_seed42_basic_original_kinyarwanda_hau_eng_train","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_lr5e_06_seed42_basic_original_kinyarwanda_hau_eng_train", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_lr5e_06_seed42_basic_original_kinyarwanda_hau_eng_train|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|797.3 MB|
+
+## References
+
+https://huggingface.co/shanhy/xlm-roberta-base_lr5e-06_seed42_basic_original_kin-hau-eng_train
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_lr5e_06_seed42_basic_original_kinyarwanda_hau_eng_train_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_lr5e_06_seed42_basic_original_kinyarwanda_hau_eng_train_pipeline_en.md
new file mode 100644
index 00000000000000..7e039384af3eea
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_lr5e_06_seed42_basic_original_kinyarwanda_hau_eng_train_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_lr5e_06_seed42_basic_original_kinyarwanda_hau_eng_train_pipeline pipeline XlmRoBertaForSequenceClassification from shanhy
+author: John Snow Labs
+name: xlm_roberta_base_lr5e_06_seed42_basic_original_kinyarwanda_hau_eng_train_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_lr5e_06_seed42_basic_original_kinyarwanda_hau_eng_train_pipeline` is a English model originally trained by shanhy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_lr5e_06_seed42_basic_original_kinyarwanda_hau_eng_train_pipeline_en_5.5.1_3.0_1734597017057.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_lr5e_06_seed42_basic_original_kinyarwanda_hau_eng_train_pipeline_en_5.5.1_3.0_1734597017057.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_lr5e_06_seed42_basic_original_kinyarwanda_hau_eng_train_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_lr5e_06_seed42_basic_original_kinyarwanda_hau_eng_train_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_lr5e_06_seed42_basic_original_kinyarwanda_hau_eng_train_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|797.3 MB|
+
+## References
+
+https://huggingface.co/shanhy/xlm-roberta-base_lr5e-06_seed42_basic_original_kin-hau-eng_train
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_rte_100_en.md b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_rte_100_en.md
new file mode 100644
index 00000000000000..dbc84c34f3fc55
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_rte_100_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_rte_100 XlmRoBertaForSequenceClassification from tmnam20
+author: John Snow Labs
+name: xlm_roberta_base_rte_100
+date: 2024-12-19
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_rte_100` is a English model originally trained by tmnam20.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_rte_100_en_5.5.1_3.0_1734597285764.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_rte_100_en_5.5.1_3.0_1734597285764.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_rte_100","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_rte_100", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_rte_100|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|784.1 MB|
+
+## References
+
+https://huggingface.co/tmnam20/xlm-roberta-base-rte-100
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_rte_100_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_rte_100_pipeline_en.md
new file mode 100644
index 00000000000000..ee364e31f5822d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_rte_100_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_rte_100_pipeline pipeline XlmRoBertaForSequenceClassification from tmnam20
+author: John Snow Labs
+name: xlm_roberta_base_rte_100_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_rte_100_pipeline` is a English model originally trained by tmnam20.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_rte_100_pipeline_en_5.5.1_3.0_1734597421949.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_rte_100_pipeline_en_5.5.1_3.0_1734597421949.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_rte_100_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_rte_100_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_rte_100_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|784.2 MB|
+
+## References
+
+https://huggingface.co/tmnam20/xlm-roberta-base-rte-100
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_wordnet_dataset_two_fine_tuned_en.md b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_wordnet_dataset_two_fine_tuned_en.md
new file mode 100644
index 00000000000000..4e6604fca80b96
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_wordnet_dataset_two_fine_tuned_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_wordnet_dataset_two_fine_tuned XlmRoBertaForSequenceClassification from Carick
+author: John Snow Labs
+name: xlm_roberta_base_wordnet_dataset_two_fine_tuned
+date: 2024-12-19
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_wordnet_dataset_two_fine_tuned` is a English model originally trained by Carick.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_wordnet_dataset_two_fine_tuned_en_5.5.1_3.0_1734596445747.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_wordnet_dataset_two_fine_tuned_en_5.5.1_3.0_1734596445747.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_wordnet_dataset_two_fine_tuned","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_wordnet_dataset_two_fine_tuned", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_wordnet_dataset_two_fine_tuned|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|843.8 MB|
+
+## References
+
+https://huggingface.co/Carick/xlm-roberta-base-wordnet_dataset_two-fine-tuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_wordnet_dataset_two_fine_tuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_wordnet_dataset_two_fine_tuned_pipeline_en.md
new file mode 100644
index 00000000000000..fa064c00f14d9b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_wordnet_dataset_two_fine_tuned_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_wordnet_dataset_two_fine_tuned_pipeline pipeline XlmRoBertaForSequenceClassification from Carick
+author: John Snow Labs
+name: xlm_roberta_base_wordnet_dataset_two_fine_tuned_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_wordnet_dataset_two_fine_tuned_pipeline` is a English model originally trained by Carick.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_wordnet_dataset_two_fine_tuned_pipeline_en_5.5.1_3.0_1734596527802.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_wordnet_dataset_two_fine_tuned_pipeline_en_5.5.1_3.0_1734596527802.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_wordnet_dataset_two_fine_tuned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_wordnet_dataset_two_fine_tuned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_wordnet_dataset_two_fine_tuned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|843.8 MB|
+
+## References
+
+https://huggingface.co/Carick/xlm-roberta-base-wordnet_dataset_two-fine-tuned
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_xnli_arabic_trimmed_arabic_en.md b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_xnli_arabic_trimmed_arabic_en.md
new file mode 100644
index 00000000000000..e20b9303004b6c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_xnli_arabic_trimmed_arabic_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_xnli_arabic_trimmed_arabic XlmRoBertaForSequenceClassification from vocabtrimmer
+author: John Snow Labs
+name: xlm_roberta_base_xnli_arabic_trimmed_arabic
+date: 2024-12-19
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_xnli_arabic_trimmed_arabic` is a English model originally trained by vocabtrimmer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_xnli_arabic_trimmed_arabic_en_5.5.1_3.0_1734597980495.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_xnli_arabic_trimmed_arabic_en_5.5.1_3.0_1734597980495.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_xnli_arabic_trimmed_arabic","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_xnli_arabic_trimmed_arabic", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_xnli_arabic_trimmed_arabic|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|437.8 MB|
+
+## References
+
+https://huggingface.co/vocabtrimmer/xlm-roberta-base-xnli-ar-trimmed-ar
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_xnli_arabic_trimmed_arabic_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_xnli_arabic_trimmed_arabic_pipeline_en.md
new file mode 100644
index 00000000000000..8c541f52a02587
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_base_xnli_arabic_trimmed_arabic_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_xnli_arabic_trimmed_arabic_pipeline pipeline XlmRoBertaForSequenceClassification from vocabtrimmer
+author: John Snow Labs
+name: xlm_roberta_base_xnli_arabic_trimmed_arabic_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_xnli_arabic_trimmed_arabic_pipeline` is a English model originally trained by vocabtrimmer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_xnli_arabic_trimmed_arabic_pipeline_en_5.5.1_3.0_1734598014506.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_xnli_arabic_trimmed_arabic_pipeline_en_5.5.1_3.0_1734598014506.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_xnli_arabic_trimmed_arabic_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_xnli_arabic_trimmed_arabic_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_xnli_arabic_trimmed_arabic_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|437.8 MB|
+
+## References
+
+https://huggingface.co/vocabtrimmer/xlm-roberta-base-xnli-ar-trimmed-ar
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_finetune_muserc_en.md b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_finetune_muserc_en.md
new file mode 100644
index 00000000000000..a5714b9abb598b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_finetune_muserc_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_finetune_muserc XlmRoBertaForSequenceClassification from accelotron
+author: John Snow Labs
+name: xlm_roberta_finetune_muserc
+date: 2024-12-19
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_finetune_muserc` is a English model originally trained by accelotron.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_finetune_muserc_en_5.5.1_3.0_1734596987263.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_finetune_muserc_en_5.5.1_3.0_1734596987263.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_finetune_muserc","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_finetune_muserc", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_finetune_muserc|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|853.2 MB|
+
+## References
+
+https://huggingface.co/accelotron/xlm-roberta-finetune-muserc
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_finetune_muserc_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_finetune_muserc_pipeline_en.md
new file mode 100644
index 00000000000000..55cb5640787445
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-xlm_roberta_finetune_muserc_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_finetune_muserc_pipeline pipeline XlmRoBertaForSequenceClassification from accelotron
+author: John Snow Labs
+name: xlm_roberta_finetune_muserc_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_finetune_muserc_pipeline` is a English model originally trained by accelotron.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_finetune_muserc_pipeline_en_5.5.1_3.0_1734597050037.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_finetune_muserc_pipeline_en_5.5.1_3.0_1734597050037.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_finetune_muserc_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_finetune_muserc_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_finetune_muserc_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|853.3 MB|
+
+## References
+
+https://huggingface.co/accelotron/xlm-roberta-finetune-muserc
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-xlmr_english_chinese_all_shuffled_1985_test1000_en.md b/docs/_posts/ahmedlone127/2024-12-19-xlmr_english_chinese_all_shuffled_1985_test1000_en.md
new file mode 100644
index 00000000000000..4f3a9a52d51b15
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-xlmr_english_chinese_all_shuffled_1985_test1000_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlmr_english_chinese_all_shuffled_1985_test1000 XlmRoBertaForSequenceClassification from patpizio
+author: John Snow Labs
+name: xlmr_english_chinese_all_shuffled_1985_test1000
+date: 2024-12-19
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmr_english_chinese_all_shuffled_1985_test1000` is a English model originally trained by patpizio.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmr_english_chinese_all_shuffled_1985_test1000_en_5.5.1_3.0_1734598146217.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmr_english_chinese_all_shuffled_1985_test1000_en_5.5.1_3.0_1734598146217.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlmr_english_chinese_all_shuffled_1985_test1000","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlmr_english_chinese_all_shuffled_1985_test1000", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmr_english_chinese_all_shuffled_1985_test1000|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|826.8 MB|
+
+## References
+
+https://huggingface.co/patpizio/xlmr-en-zh-all_shuffled-1985-test1000
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-xlmr_english_chinese_all_shuffled_1985_test1000_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-xlmr_english_chinese_all_shuffled_1985_test1000_pipeline_en.md
new file mode 100644
index 00000000000000..ec8727ef5947c4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-xlmr_english_chinese_all_shuffled_1985_test1000_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlmr_english_chinese_all_shuffled_1985_test1000_pipeline pipeline XlmRoBertaForSequenceClassification from patpizio
+author: John Snow Labs
+name: xlmr_english_chinese_all_shuffled_1985_test1000_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmr_english_chinese_all_shuffled_1985_test1000_pipeline` is a English model originally trained by patpizio.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmr_english_chinese_all_shuffled_1985_test1000_pipeline_en_5.5.1_3.0_1734598260800.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmr_english_chinese_all_shuffled_1985_test1000_pipeline_en_5.5.1_3.0_1734598260800.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlmr_english_chinese_all_shuffled_1985_test1000_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmr_english_chinese_all_shuffled_1985_test1000_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmr_english_chinese_all_shuffled_1985_test1000_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|826.9 MB|
+
+## References
+
+https://huggingface.co/patpizio/xlmr-en-zh-all_shuffled-1985-test1000
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-xlmr_sinhalese_english_all_shuffled_1985_test1000_en.md b/docs/_posts/ahmedlone127/2024-12-19-xlmr_sinhalese_english_all_shuffled_1985_test1000_en.md
new file mode 100644
index 00000000000000..a090030afd8529
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-xlmr_sinhalese_english_all_shuffled_1985_test1000_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlmr_sinhalese_english_all_shuffled_1985_test1000 XlmRoBertaForSequenceClassification from patpizio
+author: John Snow Labs
+name: xlmr_sinhalese_english_all_shuffled_1985_test1000
+date: 2024-12-19
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmr_sinhalese_english_all_shuffled_1985_test1000` is a English model originally trained by patpizio.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmr_sinhalese_english_all_shuffled_1985_test1000_en_5.5.1_3.0_1734598987310.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmr_sinhalese_english_all_shuffled_1985_test1000_en_5.5.1_3.0_1734598987310.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlmr_sinhalese_english_all_shuffled_1985_test1000","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlmr_sinhalese_english_all_shuffled_1985_test1000", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmr_sinhalese_english_all_shuffled_1985_test1000|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|815.7 MB|
+
+## References
+
+https://huggingface.co/patpizio/xlmr-si-en-all_shuffled-1985-test1000
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-xlmr_sinhalese_english_all_shuffled_1985_test1000_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-xlmr_sinhalese_english_all_shuffled_1985_test1000_pipeline_en.md
new file mode 100644
index 00000000000000..8284a50b9419ee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-xlmr_sinhalese_english_all_shuffled_1985_test1000_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlmr_sinhalese_english_all_shuffled_1985_test1000_pipeline pipeline XlmRoBertaForSequenceClassification from patpizio
+author: John Snow Labs
+name: xlmr_sinhalese_english_all_shuffled_1985_test1000_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmr_sinhalese_english_all_shuffled_1985_test1000_pipeline` is a English model originally trained by patpizio.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmr_sinhalese_english_all_shuffled_1985_test1000_pipeline_en_5.5.1_3.0_1734599101730.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmr_sinhalese_english_all_shuffled_1985_test1000_pipeline_en_5.5.1_3.0_1734599101730.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlmr_sinhalese_english_all_shuffled_1985_test1000_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmr_sinhalese_english_all_shuffled_1985_test1000_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmr_sinhalese_english_all_shuffled_1985_test1000_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|815.8 MB|
+
+## References
+
+https://huggingface.co/patpizio/xlmr-si-en-all_shuffled-1985-test1000
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-zinc10m_gpt2_smiles_bpe_combined_step2_en.md b/docs/_posts/ahmedlone127/2024-12-19-zinc10m_gpt2_smiles_bpe_combined_step2_en.md
new file mode 100644
index 00000000000000..ad1a786d23aad3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-zinc10m_gpt2_smiles_bpe_combined_step2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English zinc10m_gpt2_smiles_bpe_combined_step2 GPT2Transformer from jarod0411
+author: John Snow Labs
+name: zinc10m_gpt2_smiles_bpe_combined_step2
+date: 2024-12-19
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`zinc10m_gpt2_smiles_bpe_combined_step2` is a English model originally trained by jarod0411.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/zinc10m_gpt2_smiles_bpe_combined_step2_en_5.5.1_3.0_1734591485745.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/zinc10m_gpt2_smiles_bpe_combined_step2_en_5.5.1_3.0_1734591485745.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("zinc10m_gpt2_smiles_bpe_combined_step2","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("zinc10m_gpt2_smiles_bpe_combined_step2","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|zinc10m_gpt2_smiles_bpe_combined_step2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|466.8 MB|
+
+## References
+
+https://huggingface.co/jarod0411/zinc10M_gpt2_SMILES_bpe_combined_step2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-19-zinc10m_gpt2_smiles_bpe_combined_step2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-19-zinc10m_gpt2_smiles_bpe_combined_step2_pipeline_en.md
new file mode 100644
index 00000000000000..a43c85bdf0e08c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-19-zinc10m_gpt2_smiles_bpe_combined_step2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English zinc10m_gpt2_smiles_bpe_combined_step2_pipeline pipeline GPT2Transformer from jarod0411
+author: John Snow Labs
+name: zinc10m_gpt2_smiles_bpe_combined_step2_pipeline
+date: 2024-12-19
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`zinc10m_gpt2_smiles_bpe_combined_step2_pipeline` is a English model originally trained by jarod0411.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/zinc10m_gpt2_smiles_bpe_combined_step2_pipeline_en_5.5.1_3.0_1734591509122.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/zinc10m_gpt2_smiles_bpe_combined_step2_pipeline_en_5.5.1_3.0_1734591509122.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("zinc10m_gpt2_smiles_bpe_combined_step2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("zinc10m_gpt2_smiles_bpe_combined_step2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|zinc10m_gpt2_smiles_bpe_combined_step2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.8 MB|
+
+## References
+
+https://huggingface.co/jarod0411/zinc10M_gpt2_SMILES_bpe_combined_step2
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-20-baai_bge_reranker_base_v1___2024_09_11_22_23_59_en.md b/docs/_posts/ahmedlone127/2024-12-20-baai_bge_reranker_base_v1___2024_09_11_22_23_59_en.md
new file mode 100644
index 00000000000000..44f36dff818153
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-20-baai_bge_reranker_base_v1___2024_09_11_22_23_59_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English baai_bge_reranker_base_v1___2024_09_11_22_23_59 XlmRoBertaForSequenceClassification from onzi-suba
+author: John Snow Labs
+name: baai_bge_reranker_base_v1___2024_09_11_22_23_59
+date: 2024-12-20
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`baai_bge_reranker_base_v1___2024_09_11_22_23_59` is a English model originally trained by onzi-suba.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/baai_bge_reranker_base_v1___2024_09_11_22_23_59_en_5.5.1_3.0_1734686856761.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/baai_bge_reranker_base_v1___2024_09_11_22_23_59_en_5.5.1_3.0_1734686856761.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("baai_bge_reranker_base_v1___2024_09_11_22_23_59","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("baai_bge_reranker_base_v1___2024_09_11_22_23_59", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|baai_bge_reranker_base_v1___2024_09_11_22_23_59|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|993.9 MB|
+
+## References
+
+https://huggingface.co/onzi-suba/BAAI_bge-reranker-base_V1___2024-09-11_22-23-59
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-20-baai_bge_reranker_base_v1___2024_09_11_22_23_59_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-20-baai_bge_reranker_base_v1___2024_09_11_22_23_59_pipeline_en.md
new file mode 100644
index 00000000000000..492038bb7db881
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-20-baai_bge_reranker_base_v1___2024_09_11_22_23_59_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English baai_bge_reranker_base_v1___2024_09_11_22_23_59_pipeline pipeline XlmRoBertaForSequenceClassification from onzi-suba
+author: John Snow Labs
+name: baai_bge_reranker_base_v1___2024_09_11_22_23_59_pipeline
+date: 2024-12-20
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`baai_bge_reranker_base_v1___2024_09_11_22_23_59_pipeline` is a English model originally trained by onzi-suba.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/baai_bge_reranker_base_v1___2024_09_11_22_23_59_pipeline_en_5.5.1_3.0_1734686921989.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/baai_bge_reranker_base_v1___2024_09_11_22_23_59_pipeline_en_5.5.1_3.0_1734686921989.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("baai_bge_reranker_base_v1___2024_09_11_22_23_59_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("baai_bge_reranker_base_v1___2024_09_11_22_23_59_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|baai_bge_reranker_base_v1___2024_09_11_22_23_59_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|993.9 MB|
+
+## References
+
+https://huggingface.co/onzi-suba/BAAI_bge-reranker-base_V1___2024-09-11_22-23-59
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-20-burmese_awesome_text_classification_v2_1_2_en.md b/docs/_posts/ahmedlone127/2024-12-20-burmese_awesome_text_classification_v2_1_2_en.md
new file mode 100644
index 00000000000000..cf08a17346a694
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-20-burmese_awesome_text_classification_v2_1_2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_text_classification_v2_1_2 XlmRoBertaForSequenceClassification from lilyyellow
+author: John Snow Labs
+name: burmese_awesome_text_classification_v2_1_2
+date: 2024-12-20
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_text_classification_v2_1_2` is a English model originally trained by lilyyellow.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_text_classification_v2_1_2_en_5.5.1_3.0_1734686960620.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_text_classification_v2_1_2_en_5.5.1_3.0_1734686960620.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("burmese_awesome_text_classification_v2_1_2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("burmese_awesome_text_classification_v2_1_2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_text_classification_v2_1_2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|825.0 MB|
+
+## References
+
+https://huggingface.co/lilyyellow/my_awesome_text_classification_v2.1.2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-20-burmese_awesome_text_classification_v2_1_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-20-burmese_awesome_text_classification_v2_1_2_pipeline_en.md
new file mode 100644
index 00000000000000..594d0059c8c6ed
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-20-burmese_awesome_text_classification_v2_1_2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_text_classification_v2_1_2_pipeline pipeline XlmRoBertaForSequenceClassification from lilyyellow
+author: John Snow Labs
+name: burmese_awesome_text_classification_v2_1_2_pipeline
+date: 2024-12-20
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_text_classification_v2_1_2_pipeline` is a English model originally trained by lilyyellow.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_text_classification_v2_1_2_pipeline_en_5.5.1_3.0_1734687071702.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_text_classification_v2_1_2_pipeline_en_5.5.1_3.0_1734687071702.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_text_classification_v2_1_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_text_classification_v2_1_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_text_classification_v2_1_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|825.0 MB|
+
+## References
+
+https://huggingface.co/lilyyellow/my_awesome_text_classification_v2.1.2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-20-intent_analysis_3label_xml_en.md b/docs/_posts/ahmedlone127/2024-12-20-intent_analysis_3label_xml_en.md
new file mode 100644
index 00000000000000..0c75e92211370d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-20-intent_analysis_3label_xml_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English intent_analysis_3label_xml XlmRoBertaForSequenceClassification from adriansanz
+author: John Snow Labs
+name: intent_analysis_3label_xml
+date: 2024-12-20
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`intent_analysis_3label_xml` is a English model originally trained by adriansanz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/intent_analysis_3label_xml_en_5.5.1_3.0_1734687258699.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/intent_analysis_3label_xml_en_5.5.1_3.0_1734687258699.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("intent_analysis_3label_xml","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("intent_analysis_3label_xml", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|intent_analysis_3label_xml|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|796.3 MB|
+
+## References
+
+https://huggingface.co/adriansanz/intent_analysis-3label-xml
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-20-intent_analysis_3label_xml_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-20-intent_analysis_3label_xml_pipeline_en.md
new file mode 100644
index 00000000000000..8f55de95296559
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-20-intent_analysis_3label_xml_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English intent_analysis_3label_xml_pipeline pipeline XlmRoBertaForSequenceClassification from adriansanz
+author: John Snow Labs
+name: intent_analysis_3label_xml_pipeline
+date: 2024-12-20
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`intent_analysis_3label_xml_pipeline` is a English model originally trained by adriansanz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/intent_analysis_3label_xml_pipeline_en_5.5.1_3.0_1734687384286.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/intent_analysis_3label_xml_pipeline_en_5.5.1_3.0_1734687384286.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("intent_analysis_3label_xml_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("intent_analysis_3label_xml_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|intent_analysis_3label_xml_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|796.3 MB|
+
+## References
+
+https://huggingface.co/adriansanz/intent_analysis-3label-xml
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-20-mmarco_mminilmv2_l4_h384_v1_distilled_en.md b/docs/_posts/ahmedlone127/2024-12-20-mmarco_mminilmv2_l4_h384_v1_distilled_en.md
new file mode 100644
index 00000000000000..dca6144df87e7c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-20-mmarco_mminilmv2_l4_h384_v1_distilled_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mmarco_mminilmv2_l4_h384_v1_distilled XlmRoBertaForSequenceClassification from GeniusVoice
+author: John Snow Labs
+name: mmarco_mminilmv2_l4_h384_v1_distilled
+date: 2024-12-20
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mmarco_mminilmv2_l4_h384_v1_distilled` is a English model originally trained by GeniusVoice.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mmarco_mminilmv2_l4_h384_v1_distilled_en_5.5.1_3.0_1734687064514.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mmarco_mminilmv2_l4_h384_v1_distilled_en_5.5.1_3.0_1734687064514.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("mmarco_mminilmv2_l4_h384_v1_distilled","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("mmarco_mminilmv2_l4_h384_v1_distilled", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mmarco_mminilmv2_l4_h384_v1_distilled|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|339.8 MB|
+
+## References
+
+https://huggingface.co/GeniusVoice/mmarco-mMiniLMv2-L4-H384-v1-distilled
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-20-mmarco_mminilmv2_l4_h384_v1_distilled_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-20-mmarco_mminilmv2_l4_h384_v1_distilled_pipeline_en.md
new file mode 100644
index 00000000000000..ddfb155755d687
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-20-mmarco_mminilmv2_l4_h384_v1_distilled_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mmarco_mminilmv2_l4_h384_v1_distilled_pipeline pipeline XlmRoBertaForSequenceClassification from GeniusVoice
+author: John Snow Labs
+name: mmarco_mminilmv2_l4_h384_v1_distilled_pipeline
+date: 2024-12-20
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mmarco_mminilmv2_l4_h384_v1_distilled_pipeline` is a English model originally trained by GeniusVoice.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mmarco_mminilmv2_l4_h384_v1_distilled_pipeline_en_5.5.1_3.0_1734687094749.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mmarco_mminilmv2_l4_h384_v1_distilled_pipeline_en_5.5.1_3.0_1734687094749.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mmarco_mminilmv2_l4_h384_v1_distilled_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mmarco_mminilmv2_l4_h384_v1_distilled_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mmarco_mminilmv2_l4_h384_v1_distilled_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|339.8 MB|
+
+## References
+
+https://huggingface.co/GeniusVoice/mmarco-mMiniLMv2-L4-H384-v1-distilled
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-20-scenario_non_kd_pr_copy_cdf_cl_d2_data_cl_cardiff_cl_only_delta_en.md b/docs/_posts/ahmedlone127/2024-12-20-scenario_non_kd_pr_copy_cdf_cl_d2_data_cl_cardiff_cl_only_delta_en.md
new file mode 100644
index 00000000000000..2f17f779bc5375
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-20-scenario_non_kd_pr_copy_cdf_cl_d2_data_cl_cardiff_cl_only_delta_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English scenario_non_kd_pr_copy_cdf_cl_d2_data_cl_cardiff_cl_only_delta XlmRoBertaForSequenceClassification from haryoaw
+author: John Snow Labs
+name: scenario_non_kd_pr_copy_cdf_cl_d2_data_cl_cardiff_cl_only_delta
+date: 2024-12-20
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scenario_non_kd_pr_copy_cdf_cl_d2_data_cl_cardiff_cl_only_delta` is a English model originally trained by haryoaw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/scenario_non_kd_pr_copy_cdf_cl_d2_data_cl_cardiff_cl_only_delta_en_5.5.1_3.0_1734686246335.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scenario_non_kd_pr_copy_cdf_cl_d2_data_cl_cardiff_cl_only_delta_en_5.5.1_3.0_1734686246335.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("scenario_non_kd_pr_copy_cdf_cl_d2_data_cl_cardiff_cl_only_delta","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("scenario_non_kd_pr_copy_cdf_cl_d2_data_cl_cardiff_cl_only_delta", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|scenario_non_kd_pr_copy_cdf_cl_d2_data_cl_cardiff_cl_only_delta|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|681.6 MB|
+
+## References
+
+https://huggingface.co/haryoaw/scenario-NON-KD-PR-COPY-CDF-CL-D2_data-cl-cardiff_cl_only_delta
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-20-scenario_non_kd_pr_copy_cdf_cl_d2_data_cl_cardiff_cl_only_delta_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-20-scenario_non_kd_pr_copy_cdf_cl_d2_data_cl_cardiff_cl_only_delta_pipeline_en.md
new file mode 100644
index 00000000000000..0c2b49eccf35f5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-20-scenario_non_kd_pr_copy_cdf_cl_d2_data_cl_cardiff_cl_only_delta_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English scenario_non_kd_pr_copy_cdf_cl_d2_data_cl_cardiff_cl_only_delta_pipeline pipeline XlmRoBertaForSequenceClassification from haryoaw
+author: John Snow Labs
+name: scenario_non_kd_pr_copy_cdf_cl_d2_data_cl_cardiff_cl_only_delta_pipeline
+date: 2024-12-20
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scenario_non_kd_pr_copy_cdf_cl_d2_data_cl_cardiff_cl_only_delta_pipeline` is a English model originally trained by haryoaw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/scenario_non_kd_pr_copy_cdf_cl_d2_data_cl_cardiff_cl_only_delta_pipeline_en_5.5.1_3.0_1734686329143.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scenario_non_kd_pr_copy_cdf_cl_d2_data_cl_cardiff_cl_only_delta_pipeline_en_5.5.1_3.0_1734686329143.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("scenario_non_kd_pr_copy_cdf_cl_d2_data_cl_cardiff_cl_only_delta_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("scenario_non_kd_pr_copy_cdf_cl_d2_data_cl_cardiff_cl_only_delta_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|scenario_non_kd_pr_copy_cdf_cl_d2_data_cl_cardiff_cl_only_delta_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|681.6 MB|
+
+## References
+
+https://huggingface.co/haryoaw/scenario-NON-KD-PR-COPY-CDF-CL-D2_data-cl-cardiff_cl_only_delta
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-20-scenario_non_kd_scr_copy_cdf_english_d2_data_english_cardiff_eng_only_alpha_en.md b/docs/_posts/ahmedlone127/2024-12-20-scenario_non_kd_scr_copy_cdf_english_d2_data_english_cardiff_eng_only_alpha_en.md
new file mode 100644
index 00000000000000..2a67fc276b723b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-20-scenario_non_kd_scr_copy_cdf_english_d2_data_english_cardiff_eng_only_alpha_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English scenario_non_kd_scr_copy_cdf_english_d2_data_english_cardiff_eng_only_alpha XlmRoBertaForSequenceClassification from haryoaw
+author: John Snow Labs
+name: scenario_non_kd_scr_copy_cdf_english_d2_data_english_cardiff_eng_only_alpha
+date: 2024-12-20
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scenario_non_kd_scr_copy_cdf_english_d2_data_english_cardiff_eng_only_alpha` is a English model originally trained by haryoaw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/scenario_non_kd_scr_copy_cdf_english_d2_data_english_cardiff_eng_only_alpha_en_5.5.1_3.0_1734686548410.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scenario_non_kd_scr_copy_cdf_english_d2_data_english_cardiff_eng_only_alpha_en_5.5.1_3.0_1734686548410.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("scenario_non_kd_scr_copy_cdf_english_d2_data_english_cardiff_eng_only_alpha","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("scenario_non_kd_scr_copy_cdf_english_d2_data_english_cardiff_eng_only_alpha", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|scenario_non_kd_scr_copy_cdf_english_d2_data_english_cardiff_eng_only_alpha|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|883.8 MB|
+
+## References
+
+https://huggingface.co/haryoaw/scenario-NON-KD-SCR-COPY-CDF-EN-D2_data-en-cardiff_eng_only_alpha
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-20-scenario_non_kd_scr_copy_cdf_english_d2_data_english_cardiff_eng_only_alpha_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-20-scenario_non_kd_scr_copy_cdf_english_d2_data_english_cardiff_eng_only_alpha_pipeline_en.md
new file mode 100644
index 00000000000000..fe85269e6b1b98
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-20-scenario_non_kd_scr_copy_cdf_english_d2_data_english_cardiff_eng_only_alpha_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English scenario_non_kd_scr_copy_cdf_english_d2_data_english_cardiff_eng_only_alpha_pipeline pipeline XlmRoBertaForSequenceClassification from haryoaw
+author: John Snow Labs
+name: scenario_non_kd_scr_copy_cdf_english_d2_data_english_cardiff_eng_only_alpha_pipeline
+date: 2024-12-20
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scenario_non_kd_scr_copy_cdf_english_d2_data_english_cardiff_eng_only_alpha_pipeline` is a English model originally trained by haryoaw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/scenario_non_kd_scr_copy_cdf_english_d2_data_english_cardiff_eng_only_alpha_pipeline_en_5.5.1_3.0_1734686592660.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scenario_non_kd_scr_copy_cdf_english_d2_data_english_cardiff_eng_only_alpha_pipeline_en_5.5.1_3.0_1734686592660.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("scenario_non_kd_scr_copy_cdf_english_d2_data_english_cardiff_eng_only_alpha_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("scenario_non_kd_scr_copy_cdf_english_d2_data_english_cardiff_eng_only_alpha_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|scenario_non_kd_scr_copy_cdf_english_d2_data_english_cardiff_eng_only_alpha_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|883.8 MB|
+
+## References
+
+https://huggingface.co/haryoaw/scenario-NON-KD-SCR-COPY-CDF-EN-D2_data-en-cardiff_eng_only_alpha
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-20-sentimientos_milei_es.md b/docs/_posts/ahmedlone127/2024-12-20-sentimientos_milei_es.md
new file mode 100644
index 00000000000000..bf75906ad78a31
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-20-sentimientos_milei_es.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Castilian, Spanish sentimientos_milei XlmRoBertaForSequenceClassification from natmarinn
+author: John Snow Labs
+name: sentimientos_milei
+date: 2024-12-20
+tags: [es, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: es
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentimientos_milei` is a Castilian, Spanish model originally trained by natmarinn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentimientos_milei_es_5.5.1_3.0_1734687064979.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentimientos_milei_es_5.5.1_3.0_1734687064979.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("sentimientos_milei","es") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("sentimientos_milei", "es")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sentimientos_milei|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|es|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/natmarinn/sentimientos-milei
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-20-sentimientos_milei_pipeline_es.md b/docs/_posts/ahmedlone127/2024-12-20-sentimientos_milei_pipeline_es.md
new file mode 100644
index 00000000000000..23aa1be9743197
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-20-sentimientos_milei_pipeline_es.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Castilian, Spanish sentimientos_milei_pipeline pipeline XlmRoBertaForSequenceClassification from natmarinn
+author: John Snow Labs
+name: sentimientos_milei_pipeline
+date: 2024-12-20
+tags: [es, open_source, pipeline, onnx]
+task: Text Classification
+language: es
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentimientos_milei_pipeline` is a Castilian, Spanish model originally trained by natmarinn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentimientos_milei_pipeline_es_5.5.1_3.0_1734687124188.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentimientos_milei_pipeline_es_5.5.1_3.0_1734687124188.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sentimientos_milei_pipeline", lang = "es")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sentimientos_milei_pipeline", lang = "es")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sentimientos_milei_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|es|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/natmarinn/sentimientos-milei
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-20-xlm_roberta_base_final_mixed_aug_delete_en.md b/docs/_posts/ahmedlone127/2024-12-20-xlm_roberta_base_final_mixed_aug_delete_en.md
new file mode 100644
index 00000000000000..7064a9b8023914
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-20-xlm_roberta_base_final_mixed_aug_delete_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_final_mixed_aug_delete XlmRoBertaForSequenceClassification from ThuyNT03
+author: John Snow Labs
+name: xlm_roberta_base_final_mixed_aug_delete
+date: 2024-12-20
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_final_mixed_aug_delete` is a English model originally trained by ThuyNT03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_final_mixed_aug_delete_en_5.5.1_3.0_1734686258585.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_final_mixed_aug_delete_en_5.5.1_3.0_1734686258585.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_final_mixed_aug_delete","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_final_mixed_aug_delete", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_final_mixed_aug_delete|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|794.8 MB|
+
+## References
+
+https://huggingface.co/ThuyNT03/xlm-roberta-base-Final_Mixed-aug_delete
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-20-xlm_roberta_base_final_mixed_aug_delete_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-20-xlm_roberta_base_final_mixed_aug_delete_pipeline_en.md
new file mode 100644
index 00000000000000..798e173dd6af6b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-20-xlm_roberta_base_final_mixed_aug_delete_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_final_mixed_aug_delete_pipeline pipeline XlmRoBertaForSequenceClassification from ThuyNT03
+author: John Snow Labs
+name: xlm_roberta_base_final_mixed_aug_delete_pipeline
+date: 2024-12-20
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_final_mixed_aug_delete_pipeline` is a English model originally trained by ThuyNT03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_final_mixed_aug_delete_pipeline_en_5.5.1_3.0_1734686379824.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_final_mixed_aug_delete_pipeline_en_5.5.1_3.0_1734686379824.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_final_mixed_aug_delete_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_final_mixed_aug_delete_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_final_mixed_aug_delete_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|794.8 MB|
+
+## References
+
+https://huggingface.co/ThuyNT03/xlm-roberta-base-Final_Mixed-aug_delete
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-20-xlm_roberta_base_final_vietnam_aug_insert_w2v_en.md b/docs/_posts/ahmedlone127/2024-12-20-xlm_roberta_base_final_vietnam_aug_insert_w2v_en.md
new file mode 100644
index 00000000000000..a4dc41d27f73d2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-20-xlm_roberta_base_final_vietnam_aug_insert_w2v_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_final_vietnam_aug_insert_w2v XlmRoBertaForSequenceClassification from ThuyNT03
+author: John Snow Labs
+name: xlm_roberta_base_final_vietnam_aug_insert_w2v
+date: 2024-12-20
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_final_vietnam_aug_insert_w2v` is a English model originally trained by ThuyNT03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_final_vietnam_aug_insert_w2v_en_5.5.1_3.0_1734686738775.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_final_vietnam_aug_insert_w2v_en_5.5.1_3.0_1734686738775.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_final_vietnam_aug_insert_w2v","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_final_vietnam_aug_insert_w2v", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_final_vietnam_aug_insert_w2v|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|795.9 MB|
+
+## References
+
+https://huggingface.co/ThuyNT03/xlm-roberta-base-Final_VietNam-aug_insert_w2v
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-20-xlm_roberta_base_final_vietnam_aug_insert_w2v_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-20-xlm_roberta_base_final_vietnam_aug_insert_w2v_pipeline_en.md
new file mode 100644
index 00000000000000..d587df9b066d72
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-20-xlm_roberta_base_final_vietnam_aug_insert_w2v_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_final_vietnam_aug_insert_w2v_pipeline pipeline XlmRoBertaForSequenceClassification from ThuyNT03
+author: John Snow Labs
+name: xlm_roberta_base_final_vietnam_aug_insert_w2v_pipeline
+date: 2024-12-20
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_final_vietnam_aug_insert_w2v_pipeline` is a English model originally trained by ThuyNT03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_final_vietnam_aug_insert_w2v_pipeline_en_5.5.1_3.0_1734686861124.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_final_vietnam_aug_insert_w2v_pipeline_en_5.5.1_3.0_1734686861124.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_final_vietnam_aug_insert_w2v_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_final_vietnam_aug_insert_w2v_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_final_vietnam_aug_insert_w2v_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|795.9 MB|
+
+## References
+
+https://huggingface.co/ThuyNT03/xlm-roberta-base-Final_VietNam-aug_insert_w2v
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-20-xlm_roberta_base_lr2e_05_seed42_amh_hau_eng_train_en.md b/docs/_posts/ahmedlone127/2024-12-20-xlm_roberta_base_lr2e_05_seed42_amh_hau_eng_train_en.md
new file mode 100644
index 00000000000000..88321b1f6a0a40
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-20-xlm_roberta_base_lr2e_05_seed42_amh_hau_eng_train_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_lr2e_05_seed42_amh_hau_eng_train XlmRoBertaForSequenceClassification from shanhy
+author: John Snow Labs
+name: xlm_roberta_base_lr2e_05_seed42_amh_hau_eng_train
+date: 2024-12-20
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_lr2e_05_seed42_amh_hau_eng_train` is a English model originally trained by shanhy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_lr2e_05_seed42_amh_hau_eng_train_en_5.5.1_3.0_1734686788070.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_lr2e_05_seed42_amh_hau_eng_train_en_5.5.1_3.0_1734686788070.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_lr2e_05_seed42_amh_hau_eng_train","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_lr2e_05_seed42_amh_hau_eng_train", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_lr2e_05_seed42_amh_hau_eng_train|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|802.0 MB|
+
+## References
+
+https://huggingface.co/shanhy/xlm-roberta-base_lr2e-05_seed42_amh-hau-eng_train
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-20-xlm_roberta_base_lr2e_05_seed42_amh_hau_eng_train_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-20-xlm_roberta_base_lr2e_05_seed42_amh_hau_eng_train_pipeline_en.md
new file mode 100644
index 00000000000000..8cd7913ee934be
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-20-xlm_roberta_base_lr2e_05_seed42_amh_hau_eng_train_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_lr2e_05_seed42_amh_hau_eng_train_pipeline pipeline XlmRoBertaForSequenceClassification from shanhy
+author: John Snow Labs
+name: xlm_roberta_base_lr2e_05_seed42_amh_hau_eng_train_pipeline
+date: 2024-12-20
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_lr2e_05_seed42_amh_hau_eng_train_pipeline` is a English model originally trained by shanhy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_lr2e_05_seed42_amh_hau_eng_train_pipeline_en_5.5.1_3.0_1734686918549.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_lr2e_05_seed42_amh_hau_eng_train_pipeline_en_5.5.1_3.0_1734686918549.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_lr2e_05_seed42_amh_hau_eng_train_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_lr2e_05_seed42_amh_hau_eng_train_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_lr2e_05_seed42_amh_hau_eng_train_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|802.0 MB|
+
+## References
+
+https://huggingface.co/shanhy/xlm-roberta-base_lr2e-05_seed42_amh-hau-eng_train
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-20-xlm_roberta_base_lr5e_06_seed42_basic_original_amh_hau_eng_train_en.md b/docs/_posts/ahmedlone127/2024-12-20-xlm_roberta_base_lr5e_06_seed42_basic_original_amh_hau_eng_train_en.md
new file mode 100644
index 00000000000000..0bf4a999f527a8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-20-xlm_roberta_base_lr5e_06_seed42_basic_original_amh_hau_eng_train_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_lr5e_06_seed42_basic_original_amh_hau_eng_train XlmRoBertaForSequenceClassification from shanhy
+author: John Snow Labs
+name: xlm_roberta_base_lr5e_06_seed42_basic_original_amh_hau_eng_train
+date: 2024-12-20
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_lr5e_06_seed42_basic_original_amh_hau_eng_train` is a English model originally trained by shanhy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_lr5e_06_seed42_basic_original_amh_hau_eng_train_en_5.5.1_3.0_1734687302125.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_lr5e_06_seed42_basic_original_amh_hau_eng_train_en_5.5.1_3.0_1734687302125.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_lr5e_06_seed42_basic_original_amh_hau_eng_train","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_lr5e_06_seed42_basic_original_amh_hau_eng_train", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_lr5e_06_seed42_basic_original_amh_hau_eng_train|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|798.7 MB|
+
+## References
+
+https://huggingface.co/shanhy/xlm-roberta-base_lr5e-06_seed42_basic_original_amh-hau-eng_train
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-20-xlm_roberta_base_lr5e_06_seed42_basic_original_amh_hau_eng_train_pipeline_en.md b/docs/_posts/ahmedlone127/2024-12-20-xlm_roberta_base_lr5e_06_seed42_basic_original_amh_hau_eng_train_pipeline_en.md
new file mode 100644
index 00000000000000..775de612efccd5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-20-xlm_roberta_base_lr5e_06_seed42_basic_original_amh_hau_eng_train_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_lr5e_06_seed42_basic_original_amh_hau_eng_train_pipeline pipeline XlmRoBertaForSequenceClassification from shanhy
+author: John Snow Labs
+name: xlm_roberta_base_lr5e_06_seed42_basic_original_amh_hau_eng_train_pipeline
+date: 2024-12-20
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_lr5e_06_seed42_basic_original_amh_hau_eng_train_pipeline` is a English model originally trained by shanhy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_lr5e_06_seed42_basic_original_amh_hau_eng_train_pipeline_en_5.5.1_3.0_1734687432571.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_lr5e_06_seed42_basic_original_amh_hau_eng_train_pipeline_en_5.5.1_3.0_1734687432571.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_lr5e_06_seed42_basic_original_amh_hau_eng_train_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_lr5e_06_seed42_basic_original_amh_hau_eng_train_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_lr5e_06_seed42_basic_original_amh_hau_eng_train_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|798.7 MB|
+
+## References
+
+https://huggingface.co/shanhy/xlm-roberta-base_lr5e-06_seed42_basic_original_amh-hau-eng_train
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-12-20-xlm_roberta_base_sentiment_multilingual_finetuned_xx.md b/docs/_posts/ahmedlone127/2024-12-20-xlm_roberta_base_sentiment_multilingual_finetuned_xx.md
new file mode 100644
index 00000000000000..fa3b6d1d13b62d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-12-20-xlm_roberta_base_sentiment_multilingual_finetuned_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual xlm_roberta_base_sentiment_multilingual_finetuned XlmRoBertaForSequenceClassification from terrencewee12
+author: John Snow Labs
+name: xlm_roberta_base_sentiment_multilingual_finetuned
+date: 2024-12-20
+tags: [xx, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_sentiment_multilingual_finetuned` is a Multilingual model originally trained by terrencewee12.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_sentiment_multilingual_finetuned_xx_5.5.1_3.0_1734687638782.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_sentiment_multilingual_finetuned_xx_5.5.1_3.0_1734687638782.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_sentiment_multilingual_finetuned","xx") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_sentiment_multilingual_finetuned", "xx")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_sentiment_multilingual_finetuned|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|xx|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/terrencewee12/xlm-roberta-base-sentiment-multilingual-finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-16-bge_small_en_v1.5_en.md b/docs/_posts/ahmedlone127/2025-01-16-bge_small_en_v1.5_en.md
new file mode 100644
index 00000000000000..651cd293538615
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-16-bge_small_en_v1.5_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: bge_small_en_v1.5 model from BAAI
+author: John Snow Labs
+name: bge_small_en_v1.5
+date: 2025-01-16
+tags: [en, open_source, openvino, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.bge_small_en_v1.5 is a English model originally trained by BAAI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_small_en_v1.5_en_5.5.1_3.0_1737033852599.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_small_en_v1.5_en_5.5.1_3.0_1737033852599.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeds = BGEEmbeddings.pretrained("bge_small_en_v1.5","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeds])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeds = BGEEmbeddings.pretrained("bge_small_en_v1.5","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeds))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_small_en_v1.5|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|78.9 MB|
+
+## References
+
+https://huggingface.co/BAAI/bge-small-en-v1.5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-080524_15ep_02_en.md b/docs/_posts/ahmedlone127/2025-01-23-080524_15ep_02_en.md
new file mode 100644
index 00000000000000..54a6f005694bce
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-080524_15ep_02_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English 080524_15ep_02 RoBertaForZeroShotClassification from adriansanz
+author: John Snow Labs
+name: 080524_15ep_02
+date: 2025-01-23
+tags: [en, open_source, onnx, zero_shot, roberta]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`080524_15ep_02` is a English model originally trained by adriansanz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/080524_15ep_02_en_5.5.1_3.0_1737659468448.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/080524_15ep_02_en_5.5.1_3.0_1737659468448.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+zeroShotClassifier  = RoBertaForZeroShotClassification.pretrained("080524_15ep_02","en") \
+     .setInputCols(["document","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, zeroShotClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val zeroShotClassifier  = RoBertaForZeroShotClassification.pretrained("080524_15ep_02", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, zeroShotClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|080524_15ep_02|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|450.1 MB|
+
+## References
+
+https://huggingface.co/adriansanz/080524_15ep_02
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-080524_15ep_02_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-080524_15ep_02_pipeline_en.md
new file mode 100644
index 00000000000000..07fd3df1f2a607
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-080524_15ep_02_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English 080524_15ep_02_pipeline pipeline RoBertaForZeroShotClassification from adriansanz
+author: John Snow Labs
+name: 080524_15ep_02_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`080524_15ep_02_pipeline` is a English model originally trained by adriansanz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/080524_15ep_02_pipeline_en_5.5.1_3.0_1737659496488.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/080524_15ep_02_pipeline_en_5.5.1_3.0_1737659496488.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("080524_15ep_02_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("080524_15ep_02_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|080524_15ep_02_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|450.1 MB|
+
+## References
+
+https://huggingface.co/adriansanz/080524_15ep_02
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-adv_en.md b/docs/_posts/ahmedlone127/2025-01-23-adv_en.md
new file mode 100644
index 00000000000000..ece9727f261d84
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-adv_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English adv XlmRoBertaForSequenceClassification from susnato
+author: John Snow Labs
+name: adv
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`adv` is a English model originally trained by susnato.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/adv_en_5.5.1_3.0_1737652363780.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/adv_en_5.5.1_3.0_1737652363780.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("adv","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("adv", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|adv|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|803.1 MB|
+
+## References
+
+https://huggingface.co/susnato/ADV
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-adv_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-adv_pipeline_en.md
new file mode 100644
index 00000000000000..ebfeb39a5c9655
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-adv_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English adv_pipeline pipeline XlmRoBertaForSequenceClassification from susnato
+author: John Snow Labs
+name: adv_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`adv_pipeline` is a English model originally trained by susnato.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/adv_pipeline_en_5.5.1_3.0_1737652490711.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/adv_pipeline_en_5.5.1_3.0_1737652490711.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("adv_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("adv_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|adv_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|803.1 MB|
+
+## References
+
+https://huggingface.co/susnato/ADV
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-afriberta_v2_base_en.md b/docs/_posts/ahmedlone127/2025-01-23-afriberta_v2_base_en.md
new file mode 100644
index 00000000000000..2d7608934b58b6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-afriberta_v2_base_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English afriberta_v2_base XlmRoBertaEmbeddings from castorini
+author: John Snow Labs
+name: afriberta_v2_base
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`afriberta_v2_base` is a English model originally trained by castorini.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/afriberta_v2_base_en_5.5.1_3.0_1737668497328.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/afriberta_v2_base_en_5.5.1_3.0_1737668497328.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("afriberta_v2_base","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("afriberta_v2_base","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|afriberta_v2_base|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|645.7 MB|
+
+## References
+
+https://huggingface.co/castorini/afriberta_v2_base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-afriberta_v2_base_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-afriberta_v2_base_pipeline_en.md
new file mode 100644
index 00000000000000..8d83ad1e618e6f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-afriberta_v2_base_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English afriberta_v2_base_pipeline pipeline XlmRoBertaEmbeddings from castorini
+author: John Snow Labs
+name: afriberta_v2_base_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`afriberta_v2_base_pipeline` is a English model originally trained by castorini.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/afriberta_v2_base_pipeline_en_5.5.1_3.0_1737668531714.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/afriberta_v2_base_pipeline_en_5.5.1_3.0_1737668531714.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("afriberta_v2_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("afriberta_v2_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|afriberta_v2_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|645.7 MB|
+
+## References
+
+https://huggingface.co/castorini/afriberta_v2_base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-afro_xlmr_base_emakhuwa_en.md b/docs/_posts/ahmedlone127/2025-01-23-afro_xlmr_base_emakhuwa_en.md
new file mode 100644
index 00000000000000..f21394851485e5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-afro_xlmr_base_emakhuwa_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English afro_xlmr_base_emakhuwa XlmRoBertaEmbeddings from felerminoali
+author: John Snow Labs
+name: afro_xlmr_base_emakhuwa
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`afro_xlmr_base_emakhuwa` is a English model originally trained by felerminoali.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/afro_xlmr_base_emakhuwa_en_5.5.1_3.0_1737668690560.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/afro_xlmr_base_emakhuwa_en_5.5.1_3.0_1737668690560.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("afro_xlmr_base_emakhuwa","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("afro_xlmr_base_emakhuwa","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|afro_xlmr_base_emakhuwa|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/felerminoali/afro_xlmr_base_emakhuwa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-afro_xlmr_base_emakhuwa_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-afro_xlmr_base_emakhuwa_pipeline_en.md
new file mode 100644
index 00000000000000..d0ba1092240d9f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-afro_xlmr_base_emakhuwa_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English afro_xlmr_base_emakhuwa_pipeline pipeline XlmRoBertaEmbeddings from felerminoali
+author: John Snow Labs
+name: afro_xlmr_base_emakhuwa_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`afro_xlmr_base_emakhuwa_pipeline` is a English model originally trained by felerminoali.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/afro_xlmr_base_emakhuwa_pipeline_en_5.5.1_3.0_1737668744585.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/afro_xlmr_base_emakhuwa_pipeline_en_5.5.1_3.0_1737668744585.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("afro_xlmr_base_emakhuwa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("afro_xlmr_base_emakhuwa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|afro_xlmr_base_emakhuwa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/felerminoali/afro_xlmr_base_emakhuwa
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-albert_base_v2_grammar_ner_en.md b/docs/_posts/ahmedlone127/2025-01-23-albert_base_v2_grammar_ner_en.md
new file mode 100644
index 00000000000000..6a1287130a462f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-albert_base_v2_grammar_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English albert_base_v2_grammar_ner AlbertForTokenClassification from codymd
+author: John Snow Labs
+name: albert_base_v2_grammar_ner
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, albert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_v2_grammar_ner` is a English model originally trained by codymd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_v2_grammar_ner_en_5.5.1_3.0_1737661447892.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_v2_grammar_ner_en_5.5.1_3.0_1737661447892.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = AlbertForTokenClassification.pretrained("albert_base_v2_grammar_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = AlbertForTokenClassification.pretrained("albert_base_v2_grammar_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_base_v2_grammar_ner|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|42.1 MB|
+
+## References
+
+https://huggingface.co/codymd/albert-base-v2-grammar-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-albert_base_v2_grammar_ner_generic_en.md b/docs/_posts/ahmedlone127/2025-01-23-albert_base_v2_grammar_ner_generic_en.md
new file mode 100644
index 00000000000000..1a521c40c65380
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-albert_base_v2_grammar_ner_generic_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English albert_base_v2_grammar_ner_generic AlbertForTokenClassification from codymd
+author: John Snow Labs
+name: albert_base_v2_grammar_ner_generic
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, albert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_v2_grammar_ner_generic` is a English model originally trained by codymd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_v2_grammar_ner_generic_en_5.5.1_3.0_1737661447789.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_v2_grammar_ner_generic_en_5.5.1_3.0_1737661447789.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = AlbertForTokenClassification.pretrained("albert_base_v2_grammar_ner_generic","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = AlbertForTokenClassification.pretrained("albert_base_v2_grammar_ner_generic", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_base_v2_grammar_ner_generic|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|41.9 MB|
+
+## References
+
+https://huggingface.co/codymd/albert-base-v2-grammar-ner-generic
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-albert_base_v2_grammar_ner_generic_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-albert_base_v2_grammar_ner_generic_pipeline_en.md
new file mode 100644
index 00000000000000..12e43f82ecfb85
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-albert_base_v2_grammar_ner_generic_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English albert_base_v2_grammar_ner_generic_pipeline pipeline AlbertForTokenClassification from codymd
+author: John Snow Labs
+name: albert_base_v2_grammar_ner_generic_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_v2_grammar_ner_generic_pipeline` is a English model originally trained by codymd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_v2_grammar_ner_generic_pipeline_en_5.5.1_3.0_1737661450228.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_v2_grammar_ner_generic_pipeline_en_5.5.1_3.0_1737661450228.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("albert_base_v2_grammar_ner_generic_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("albert_base_v2_grammar_ner_generic_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_base_v2_grammar_ner_generic_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|42.0 MB|
+
+## References
+
+https://huggingface.co/codymd/albert-base-v2-grammar-ner-generic
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-albert_base_v2_grammar_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-albert_base_v2_grammar_ner_pipeline_en.md
new file mode 100644
index 00000000000000..76cbed92c6f9d5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-albert_base_v2_grammar_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English albert_base_v2_grammar_ner_pipeline pipeline AlbertForTokenClassification from codymd
+author: John Snow Labs
+name: albert_base_v2_grammar_ner_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_v2_grammar_ner_pipeline` is a English model originally trained by codymd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_v2_grammar_ner_pipeline_en_5.5.1_3.0_1737661450313.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_v2_grammar_ner_pipeline_en_5.5.1_3.0_1737661450313.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("albert_base_v2_grammar_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("albert_base_v2_grammar_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_base_v2_grammar_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|42.1 MB|
+
+## References
+
+https://huggingface.co/codymd/albert-base-v2-grammar-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-all_minilm_l6_v2_personal_project_finetuned_2024_05_17_en.md b/docs/_posts/ahmedlone127/2025-01-23-all_minilm_l6_v2_personal_project_finetuned_2024_05_17_en.md
new file mode 100644
index 00000000000000..cfca8eb87454f2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-all_minilm_l6_v2_personal_project_finetuned_2024_05_17_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English all_minilm_l6_v2_personal_project_finetuned_2024_05_17 BertEmbeddings from brugmark
+author: John Snow Labs
+name: all_minilm_l6_v2_personal_project_finetuned_2024_05_17
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_minilm_l6_v2_personal_project_finetuned_2024_05_17` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_finetuned_2024_05_17_en_5.5.1_3.0_1737637911042.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_finetuned_2024_05_17_en_5.5.1_3.0_1737637911042.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("all_minilm_l6_v2_personal_project_finetuned_2024_05_17","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("all_minilm_l6_v2_personal_project_finetuned_2024_05_17","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_minilm_l6_v2_personal_project_finetuned_2024_05_17|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|84.4 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-finetuned-2024-05-17
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-all_minilm_l6_v2_personal_project_finetuned_2024_05_17_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-all_minilm_l6_v2_personal_project_finetuned_2024_05_17_pipeline_en.md
new file mode 100644
index 00000000000000..6f5d0b2e9abdd7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-all_minilm_l6_v2_personal_project_finetuned_2024_05_17_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English all_minilm_l6_v2_personal_project_finetuned_2024_05_17_pipeline pipeline BertEmbeddings from brugmark
+author: John Snow Labs
+name: all_minilm_l6_v2_personal_project_finetuned_2024_05_17_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_minilm_l6_v2_personal_project_finetuned_2024_05_17_pipeline` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_finetuned_2024_05_17_pipeline_en_5.5.1_3.0_1737637915772.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_finetuned_2024_05_17_pipeline_en_5.5.1_3.0_1737637915772.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("all_minilm_l6_v2_personal_project_finetuned_2024_05_17_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("all_minilm_l6_v2_personal_project_finetuned_2024_05_17_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_minilm_l6_v2_personal_project_finetuned_2024_05_17_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|84.4 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-finetuned-2024-05-17
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-all_minilm_l6_v2_personal_project_finetuned_2024_06_07_en.md b/docs/_posts/ahmedlone127/2025-01-23-all_minilm_l6_v2_personal_project_finetuned_2024_06_07_en.md
new file mode 100644
index 00000000000000..e9341116a1e74c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-all_minilm_l6_v2_personal_project_finetuned_2024_06_07_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English all_minilm_l6_v2_personal_project_finetuned_2024_06_07 BertEmbeddings from brugmark
+author: John Snow Labs
+name: all_minilm_l6_v2_personal_project_finetuned_2024_06_07
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_minilm_l6_v2_personal_project_finetuned_2024_06_07` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_finetuned_2024_06_07_en_5.5.1_3.0_1737637361944.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_finetuned_2024_06_07_en_5.5.1_3.0_1737637361944.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("all_minilm_l6_v2_personal_project_finetuned_2024_06_07","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("all_minilm_l6_v2_personal_project_finetuned_2024_06_07","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_minilm_l6_v2_personal_project_finetuned_2024_06_07|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|84.8 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-finetuned-2024-06-07
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-all_minilm_l6_v2_personal_project_finetuned_2024_06_07_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-all_minilm_l6_v2_personal_project_finetuned_2024_06_07_pipeline_en.md
new file mode 100644
index 00000000000000..a5fab202f04984
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-all_minilm_l6_v2_personal_project_finetuned_2024_06_07_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English all_minilm_l6_v2_personal_project_finetuned_2024_06_07_pipeline pipeline BertEmbeddings from brugmark
+author: John Snow Labs
+name: all_minilm_l6_v2_personal_project_finetuned_2024_06_07_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_minilm_l6_v2_personal_project_finetuned_2024_06_07_pipeline` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_finetuned_2024_06_07_pipeline_en_5.5.1_3.0_1737637366308.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_finetuned_2024_06_07_pipeline_en_5.5.1_3.0_1737637366308.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("all_minilm_l6_v2_personal_project_finetuned_2024_06_07_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("all_minilm_l6_v2_personal_project_finetuned_2024_06_07_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_minilm_l6_v2_personal_project_finetuned_2024_06_07_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|84.8 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-finetuned-2024-06-07
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-amharicnewsnoncleaned_en.md b/docs/_posts/ahmedlone127/2025-01-23-amharicnewsnoncleaned_en.md
new file mode 100644
index 00000000000000..f0fd0ef28ee9cb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-amharicnewsnoncleaned_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English amharicnewsnoncleaned XlmRoBertaForSequenceClassification from akiseid
+author: John Snow Labs
+name: amharicnewsnoncleaned
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`amharicnewsnoncleaned` is a English model originally trained by akiseid.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/amharicnewsnoncleaned_en_5.5.1_3.0_1737652769296.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/amharicnewsnoncleaned_en_5.5.1_3.0_1737652769296.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("amharicnewsnoncleaned","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("amharicnewsnoncleaned", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|amharicnewsnoncleaned|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|841.0 MB|
+
+## References
+
+https://huggingface.co/akiseid/AmharicNewsNonCleaned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-amharicnewsnoncleaned_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-amharicnewsnoncleaned_pipeline_en.md
new file mode 100644
index 00000000000000..0d96264e89a453
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-amharicnewsnoncleaned_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English amharicnewsnoncleaned_pipeline pipeline XlmRoBertaForSequenceClassification from akiseid
+author: John Snow Labs
+name: amharicnewsnoncleaned_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`amharicnewsnoncleaned_pipeline` is a English model originally trained by akiseid.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/amharicnewsnoncleaned_pipeline_en_5.5.1_3.0_1737652858418.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/amharicnewsnoncleaned_pipeline_en_5.5.1_3.0_1737652858418.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("amharicnewsnoncleaned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("amharicnewsnoncleaned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|amharicnewsnoncleaned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|841.0 MB|
+
+## References
+
+https://huggingface.co/akiseid/AmharicNewsNonCleaned
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-anime_recommendation_model_en.md b/docs/_posts/ahmedlone127/2025-01-23-anime_recommendation_model_en.md
new file mode 100644
index 00000000000000..37a2d28dd92bd4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-anime_recommendation_model_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English anime_recommendation_model MPNetEmbeddings from Prashasst
+author: John Snow Labs
+name: anime_recommendation_model
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`anime_recommendation_model` is a English model originally trained by Prashasst.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/anime_recommendation_model_en_5.5.1_3.0_1737669970293.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/anime_recommendation_model_en_5.5.1_3.0_1737669970293.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("anime_recommendation_model","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("anime_recommendation_model","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|anime_recommendation_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.7 MB|
+
+## References
+
+https://huggingface.co/Prashasst/anime-recommendation-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-anime_recommendation_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-anime_recommendation_model_pipeline_en.md
new file mode 100644
index 00000000000000..2a04e029f5ce52
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-anime_recommendation_model_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English anime_recommendation_model_pipeline pipeline MPNetEmbeddings from Prashasst
+author: John Snow Labs
+name: anime_recommendation_model_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`anime_recommendation_model_pipeline` is a English model originally trained by Prashasst.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/anime_recommendation_model_pipeline_en_5.5.1_3.0_1737669992327.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/anime_recommendation_model_pipeline_en_5.5.1_3.0_1737669992327.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("anime_recommendation_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("anime_recommendation_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|anime_recommendation_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.7 MB|
+
+## References
+
+https://huggingface.co/Prashasst/anime-recommendation-model
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-bania_model_en.md b/docs/_posts/ahmedlone127/2025-01-23-bania_model_en.md
new file mode 100644
index 00000000000000..b635749221867f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-bania_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bania_model DistilBertForTokenClassification from Bania2001
+author: John Snow Labs
+name: bania_model
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bania_model` is a English model originally trained by Bania2001.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bania_model_en_5.5.1_3.0_1737627155561.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bania_model_en_5.5.1_3.0_1737627155561.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("bania_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("bania_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bania_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Bania2001/Bania_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-bania_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-bania_model_pipeline_en.md
new file mode 100644
index 00000000000000..3712311e2ee311
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-bania_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bania_model_pipeline pipeline DistilBertForTokenClassification from Bania2001
+author: John Snow Labs
+name: bania_model_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bania_model_pipeline` is a English model originally trained by Bania2001.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bania_model_pipeline_en_5.5.1_3.0_1737627169171.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bania_model_pipeline_en_5.5.1_3.0_1737627169171.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bania_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bania_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bania_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Bania2001/Bania_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-bart_large_mnli_finetune_cnn_news_en.md b/docs/_posts/ahmedlone127/2025-01-23-bart_large_mnli_finetune_cnn_news_en.md
new file mode 100644
index 00000000000000..b48b848d4759cf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-bart_large_mnli_finetune_cnn_news_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bart_large_mnli_finetune_cnn_news BartForZeroShotClassification from AyoubChLin
+author: John Snow Labs
+name: bart_large_mnli_finetune_cnn_news
+date: 2025-01-23
+tags: [en, open_source, onnx, zero_shot, bart]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BartForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bart_large_mnli_finetune_cnn_news` is a English model originally trained by AyoubChLin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bart_large_mnli_finetune_cnn_news_en_5.5.1_3.0_1737638797313.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bart_large_mnli_finetune_cnn_news_en_5.5.1_3.0_1737638797313.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+zeroShotClassifier  = BartForZeroShotClassification.pretrained("bart_large_mnli_finetune_cnn_news","en") \
+     .setInputCols(["document","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, zeroShotClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val zeroShotClassifier  = BartForZeroShotClassification.pretrained("bart_large_mnli_finetune_cnn_news", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, zeroShotClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bart_large_mnli_finetune_cnn_news|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/AyoubChLin/bart_large_mnli_finetune_cnn_news
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-bart_large_mnli_finetune_cnn_news_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-bart_large_mnli_finetune_cnn_news_pipeline_en.md
new file mode 100644
index 00000000000000..d8fb0e4cc1085f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-bart_large_mnli_finetune_cnn_news_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bart_large_mnli_finetune_cnn_news_pipeline pipeline BartForZeroShotClassification from AyoubChLin
+author: John Snow Labs
+name: bart_large_mnli_finetune_cnn_news_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bart_large_mnli_finetune_cnn_news_pipeline` is a English model originally trained by AyoubChLin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bart_large_mnli_finetune_cnn_news_pipeline_en_5.5.1_3.0_1737638885902.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bart_large_mnli_finetune_cnn_news_pipeline_en_5.5.1_3.0_1737638885902.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bart_large_mnli_finetune_cnn_news_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bart_large_mnli_finetune_cnn_news_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bart_large_mnli_finetune_cnn_news_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/AyoubChLin/bart_large_mnli_finetune_cnn_news
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BartForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-bart_large_mnli_katanemo_en.md b/docs/_posts/ahmedlone127/2025-01-23-bart_large_mnli_katanemo_en.md
new file mode 100644
index 00000000000000..2d813dde5b8ef7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-bart_large_mnli_katanemo_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bart_large_mnli_katanemo BartForZeroShotClassification from katanemo
+author: John Snow Labs
+name: bart_large_mnli_katanemo
+date: 2025-01-23
+tags: [en, open_source, onnx, zero_shot, bart]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BartForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bart_large_mnli_katanemo` is a English model originally trained by katanemo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bart_large_mnli_katanemo_en_5.5.1_3.0_1737639169107.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bart_large_mnli_katanemo_en_5.5.1_3.0_1737639169107.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+zeroShotClassifier  = BartForZeroShotClassification.pretrained("bart_large_mnli_katanemo","en") \
+     .setInputCols(["document","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, zeroShotClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val zeroShotClassifier  = BartForZeroShotClassification.pretrained("bart_large_mnli_katanemo", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, zeroShotClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bart_large_mnli_katanemo|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|975.7 MB|
+
+## References
+
+https://huggingface.co/katanemo/bart-large-mnli
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-bart_large_mnli_katanemo_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-bart_large_mnli_katanemo_pipeline_en.md
new file mode 100644
index 00000000000000..67f7c0dab75892
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-bart_large_mnli_katanemo_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bart_large_mnli_katanemo_pipeline pipeline BartForZeroShotClassification from katanemo
+author: John Snow Labs
+name: bart_large_mnli_katanemo_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bart_large_mnli_katanemo_pipeline` is a English model originally trained by katanemo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bart_large_mnli_katanemo_pipeline_en_5.5.1_3.0_1737639460509.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bart_large_mnli_katanemo_pipeline_en_5.5.1_3.0_1737639460509.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bart_large_mnli_katanemo_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bart_large_mnli_katanemo_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bart_large_mnli_katanemo_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|975.7 MB|
+
+## References
+
+https://huggingface.co/katanemo/bart-large-mnli
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BartForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-bart_large_mnli_navteca_en.md b/docs/_posts/ahmedlone127/2025-01-23-bart_large_mnli_navteca_en.md
new file mode 100644
index 00000000000000..fb4b4fe1f6bd48
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-bart_large_mnli_navteca_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bart_large_mnli_navteca BartForZeroShotClassification from navteca
+author: John Snow Labs
+name: bart_large_mnli_navteca
+date: 2025-01-23
+tags: [en, open_source, onnx, zero_shot, bart]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BartForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bart_large_mnli_navteca` is a English model originally trained by navteca.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bart_large_mnli_navteca_en_5.5.1_3.0_1737639793775.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bart_large_mnli_navteca_en_5.5.1_3.0_1737639793775.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+zeroShotClassifier  = BartForZeroShotClassification.pretrained("bart_large_mnli_navteca","en") \
+     .setInputCols(["document","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, zeroShotClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val zeroShotClassifier  = BartForZeroShotClassification.pretrained("bart_large_mnli_navteca", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, zeroShotClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bart_large_mnli_navteca|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|975.7 MB|
+
+## References
+
+https://huggingface.co/navteca/bart-large-mnli
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-bart_large_mnli_navteca_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-bart_large_mnli_navteca_pipeline_en.md
new file mode 100644
index 00000000000000..d997b176ad18d3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-bart_large_mnli_navteca_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bart_large_mnli_navteca_pipeline pipeline BartForZeroShotClassification from navteca
+author: John Snow Labs
+name: bart_large_mnli_navteca_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bart_large_mnli_navteca_pipeline` is a English model originally trained by navteca.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bart_large_mnli_navteca_pipeline_en_5.5.1_3.0_1737640086284.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bart_large_mnli_navteca_pipeline_en_5.5.1_3.0_1737640086284.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bart_large_mnli_navteca_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bart_large_mnli_navteca_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bart_large_mnli_navteca_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|975.7 MB|
+
+## References
+
+https://huggingface.co/navteca/bart-large-mnli
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BartForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-bart_large_mnli_yahoo_answers_joeddav_en.md b/docs/_posts/ahmedlone127/2025-01-23-bart_large_mnli_yahoo_answers_joeddav_en.md
new file mode 100644
index 00000000000000..30f1c1674d0166
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-bart_large_mnli_yahoo_answers_joeddav_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bart_large_mnli_yahoo_answers_joeddav BartForZeroShotClassification from joeddav
+author: John Snow Labs
+name: bart_large_mnli_yahoo_answers_joeddav
+date: 2025-01-23
+tags: [en, open_source, onnx, zero_shot, bart]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BartForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bart_large_mnli_yahoo_answers_joeddav` is a English model originally trained by joeddav.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bart_large_mnli_yahoo_answers_joeddav_en_5.5.1_3.0_1737638574481.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bart_large_mnli_yahoo_answers_joeddav_en_5.5.1_3.0_1737638574481.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+zeroShotClassifier  = BartForZeroShotClassification.pretrained("bart_large_mnli_yahoo_answers_joeddav","en") \
+     .setInputCols(["document","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, zeroShotClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val zeroShotClassifier  = BartForZeroShotClassification.pretrained("bart_large_mnli_yahoo_answers_joeddav", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, zeroShotClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bart_large_mnli_yahoo_answers_joeddav|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/joeddav/bart-large-mnli-yahoo-answers
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-bart_large_mnli_yahoo_answers_joeddav_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-bart_large_mnli_yahoo_answers_joeddav_pipeline_en.md
new file mode 100644
index 00000000000000..80389612819ece
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-bart_large_mnli_yahoo_answers_joeddav_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bart_large_mnli_yahoo_answers_joeddav_pipeline pipeline BartForZeroShotClassification from joeddav
+author: John Snow Labs
+name: bart_large_mnli_yahoo_answers_joeddav_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bart_large_mnli_yahoo_answers_joeddav_pipeline` is a English model originally trained by joeddav.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bart_large_mnli_yahoo_answers_joeddav_pipeline_en_5.5.1_3.0_1737638655364.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bart_large_mnli_yahoo_answers_joeddav_pipeline_en_5.5.1_3.0_1737638655364.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bart_large_mnli_yahoo_answers_joeddav_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bart_large_mnli_yahoo_answers_joeddav_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bart_large_mnli_yahoo_answers_joeddav_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/joeddav/bart-large-mnli-yahoo-answers
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BartForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-bart_large_mnli_yahoo_answers_weakit_v_en.md b/docs/_posts/ahmedlone127/2025-01-23-bart_large_mnli_yahoo_answers_weakit_v_en.md
new file mode 100644
index 00000000000000..4c72ce01df62ee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-bart_large_mnli_yahoo_answers_weakit_v_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bart_large_mnli_yahoo_answers_weakit_v BartForZeroShotClassification from weakit-v
+author: John Snow Labs
+name: bart_large_mnli_yahoo_answers_weakit_v
+date: 2025-01-23
+tags: [en, open_source, onnx, zero_shot, bart]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BartForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bart_large_mnli_yahoo_answers_weakit_v` is a English model originally trained by weakit-v.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bart_large_mnli_yahoo_answers_weakit_v_en_5.5.1_3.0_1737640122051.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bart_large_mnli_yahoo_answers_weakit_v_en_5.5.1_3.0_1737640122051.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+zeroShotClassifier  = BartForZeroShotClassification.pretrained("bart_large_mnli_yahoo_answers_weakit_v","en") \
+     .setInputCols(["document","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, zeroShotClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val zeroShotClassifier  = BartForZeroShotClassification.pretrained("bart_large_mnli_yahoo_answers_weakit_v", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, zeroShotClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bart_large_mnli_yahoo_answers_weakit_v|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/weakit-v/bart-large-mnli-yahoo-answers
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-bart_large_mnli_yahoo_answers_weakit_v_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-bart_large_mnli_yahoo_answers_weakit_v_pipeline_en.md
new file mode 100644
index 00000000000000..af6029673c3de8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-bart_large_mnli_yahoo_answers_weakit_v_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bart_large_mnli_yahoo_answers_weakit_v_pipeline pipeline BartForZeroShotClassification from weakit-v
+author: John Snow Labs
+name: bart_large_mnli_yahoo_answers_weakit_v_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bart_large_mnli_yahoo_answers_weakit_v_pipeline` is a English model originally trained by weakit-v.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bart_large_mnli_yahoo_answers_weakit_v_pipeline_en_5.5.1_3.0_1737640200032.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bart_large_mnli_yahoo_answers_weakit_v_pipeline_en_5.5.1_3.0_1737640200032.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bart_large_mnli_yahoo_answers_weakit_v_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bart_large_mnli_yahoo_answers_weakit_v_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bart_large_mnli_yahoo_answers_weakit_v_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/weakit-v/bart-large-mnli-yahoo-answers
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BartForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-bart_large_zero_shot_classifier_mnli_en.md b/docs/_posts/ahmedlone127/2025-01-23-bart_large_zero_shot_classifier_mnli_en.md
new file mode 100644
index 00000000000000..277e02fef9410f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-bart_large_zero_shot_classifier_mnli_en.md
@@ -0,0 +1,112 @@
+---
+layout: model
+title: Bart Zero Shot Classifier Large -MNLI (bart_large_zero_shot_classifier_mnli)
+author: John Snow Labs
+name: bart_large_zero_shot_classifier_mnli
+date: 2025-01-23
+tags: [bart, zero_shot, en, open_source, openvino, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BartForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+This model is intended to be used for zero-shot text classification, especially in English. It is fine-tuned on MNLI by using large BART model.
+
+BartForZeroShotClassification using a ModelForSequenceClassification trained on MNLI  tasks. Equivalent of BartForSequenceClassification models, but these models don’t require a hardcoded number of potential classes, they can be chosen at runtime. It usually means it’s slower but it is much more flexible.
+
+We used TFBartForSequenceClassification to train this model and used BartForZeroShotClassification annotator in Spark NLP 🚀 for prediction at scale!
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bart_large_zero_shot_classifier_mnli_en_5.5.1_3.0_1737639252080.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bart_large_zero_shot_classifier_mnli_en_5.5.1_3.0_1737639252080.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = DocumentAssembler() \
+.setInputCol('text') \
+.setOutputCol('document')
+
+tokenizer = Tokenizer() \
+.setInputCols(['document']) \
+.setOutputCol('token')
+
+zeroShotClassifier = BartForZeroShotClassification \
+.pretrained('bart_large_zero_shot_classifier_mnli', 'en') \
+.setInputCols(['token', 'document']) \
+.setOutputCol('class') \
+.setCaseSensitive(True) \
+.setMaxSentenceLength(512) \
+.setCandidateLabels(["urgent", "mobile", "travel", "movie", "music", "sport", "weather", "technology"])
+
+pipeline = Pipeline(stages=[
+document_assembler,
+tokenizer,
+zeroShotClassifier
+])
+
+example = spark.createDataFrame([['I have a problem with my iphone that needs to be resolved asap!!']]).toDF("text")
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document_assembler = DocumentAssembler()
+.setInputCol("text")
+.setOutputCol("document")
+
+val tokenizer = Tokenizer()
+.setInputCols("document")
+.setOutputCol("token")
+
+val zeroShotClassifier = BartForSequenceClassification.pretrained("bart_large_zero_shot_classifier_mnli", "en")
+.setInputCols("document", "token")
+.setOutputCol("class")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+.setCandidateLabels(Array("urgent", "mobile", "travel", "movie", "music", "sport", "weather", "technology"))
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, tokenizer, zeroShotClassifier))
+
+val example = Seq("I have a problem with my iphone that needs to be resolved asap!!").toDS.toDF("text")
+
+val result = pipeline.fit(example).transform(example)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bart_large_zero_shot_classifier_mnli|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|975.7 MB|
+
+## References
+
+References
+
+https://huggingface.co/facebook/bart-large-mnli
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-bart_large_zero_shot_classifier_mnli_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-bart_large_zero_shot_classifier_mnli_pipeline_en.md
new file mode 100644
index 00000000000000..425a8738edec82
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-bart_large_zero_shot_classifier_mnli_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bart_large_zero_shot_classifier_mnli_pipeline pipeline BartForZeroShotClassification from facebook
+author: John Snow Labs
+name: bart_large_zero_shot_classifier_mnli_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bart_large_zero_shot_classifier_mnli_pipeline` is a English model originally trained by facebook.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bart_large_zero_shot_classifier_mnli_pipeline_en_5.5.1_3.0_1737639544199.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bart_large_zero_shot_classifier_mnli_pipeline_en_5.5.1_3.0_1737639544199.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bart_large_zero_shot_classifier_mnli_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bart_large_zero_shot_classifier_mnli_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bart_large_zero_shot_classifier_mnli_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|975.7 MB|
+
+## References
+
+https://huggingface.co/facebook/bart-large-mnli
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BartForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-bart_mnli_cnn_256_en.md b/docs/_posts/ahmedlone127/2025-01-23-bart_mnli_cnn_256_en.md
new file mode 100644
index 00000000000000..c569e5e4119d3e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-bart_mnli_cnn_256_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bart_mnli_cnn_256 BartForZeroShotClassification from AyoubChLin
+author: John Snow Labs
+name: bart_mnli_cnn_256
+date: 2025-01-23
+tags: [en, open_source, onnx, zero_shot, bart]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BartForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bart_mnli_cnn_256` is a English model originally trained by AyoubChLin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bart_mnli_cnn_256_en_5.5.1_3.0_1737638777779.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bart_mnli_cnn_256_en_5.5.1_3.0_1737638777779.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+zeroShotClassifier  = BartForZeroShotClassification.pretrained("bart_mnli_cnn_256","en") \
+     .setInputCols(["document","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, zeroShotClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val zeroShotClassifier  = BartForZeroShotClassification.pretrained("bart_mnli_cnn_256", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, zeroShotClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bart_mnli_cnn_256|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/AyoubChLin/BART-mnli_cnn_256
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-bart_mnli_cnn_256_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-bart_mnli_cnn_256_pipeline_en.md
new file mode 100644
index 00000000000000..687bbdc740e42b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-bart_mnli_cnn_256_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bart_mnli_cnn_256_pipeline pipeline BartForZeroShotClassification from AyoubChLin
+author: John Snow Labs
+name: bart_mnli_cnn_256_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bart_mnli_cnn_256_pipeline` is a English model originally trained by AyoubChLin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bart_mnli_cnn_256_pipeline_en_5.5.1_3.0_1737638863511.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bart_mnli_cnn_256_pipeline_en_5.5.1_3.0_1737638863511.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bart_mnli_cnn_256_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bart_mnli_cnn_256_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bart_mnli_cnn_256_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/AyoubChLin/BART-mnli_cnn_256
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BartForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-bart_mnli_cnn_news_en.md b/docs/_posts/ahmedlone127/2025-01-23-bart_mnli_cnn_news_en.md
new file mode 100644
index 00000000000000..bd6fc19660091e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-bart_mnli_cnn_news_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bart_mnli_cnn_news BartForZeroShotClassification from AyoubChLin
+author: John Snow Labs
+name: bart_mnli_cnn_news
+date: 2025-01-23
+tags: [en, open_source, onnx, zero_shot, bart]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BartForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bart_mnli_cnn_news` is a English model originally trained by AyoubChLin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bart_mnli_cnn_news_en_5.5.1_3.0_1737639890422.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bart_mnli_cnn_news_en_5.5.1_3.0_1737639890422.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+zeroShotClassifier  = BartForZeroShotClassification.pretrained("bart_mnli_cnn_news","en") \
+     .setInputCols(["document","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, zeroShotClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val zeroShotClassifier  = BartForZeroShotClassification.pretrained("bart_mnli_cnn_news", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, zeroShotClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bart_mnli_cnn_news|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/AyoubChLin/Bart-MNLI-CNN_news
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-bart_mnli_cnn_news_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-bart_mnli_cnn_news_pipeline_en.md
new file mode 100644
index 00000000000000..70a1e41722b292
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-bart_mnli_cnn_news_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bart_mnli_cnn_news_pipeline pipeline BartForZeroShotClassification from AyoubChLin
+author: John Snow Labs
+name: bart_mnli_cnn_news_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bart_mnli_cnn_news_pipeline` is a English model originally trained by AyoubChLin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bart_mnli_cnn_news_pipeline_en_5.5.1_3.0_1737639976411.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bart_mnli_cnn_news_pipeline_en_5.5.1_3.0_1737639976411.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bart_mnli_cnn_news_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bart_mnli_cnn_news_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bart_mnli_cnn_news_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/AyoubChLin/Bart-MNLI-CNN_news
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BartForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-base_full_v0_100_en.md b/docs/_posts/ahmedlone127/2025-01-23-base_full_v0_100_en.md
new file mode 100644
index 00000000000000..612eadd6ec1601
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-base_full_v0_100_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English base_full_v0_100 XlmRoBertaForSequenceClassification from sreddy109
+author: John Snow Labs
+name: base_full_v0_100
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`base_full_v0_100` is a English model originally trained by sreddy109.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/base_full_v0_100_en_5.5.1_3.0_1737653299952.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/base_full_v0_100_en_5.5.1_3.0_1737653299952.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("base_full_v0_100","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("base_full_v0_100", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|base_full_v0_100|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|993.9 MB|
+
+## References
+
+https://huggingface.co/sreddy109/base-full-v0-100
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-base_full_v0_100_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-base_full_v0_100_pipeline_en.md
new file mode 100644
index 00000000000000..a00c47ae178080
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-base_full_v0_100_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English base_full_v0_100_pipeline pipeline XlmRoBertaForSequenceClassification from sreddy109
+author: John Snow Labs
+name: base_full_v0_100_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`base_full_v0_100_pipeline` is a English model originally trained by sreddy109.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/base_full_v0_100_pipeline_en_5.5.1_3.0_1737653357407.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/base_full_v0_100_pipeline_en_5.5.1_3.0_1737653357407.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("base_full_v0_100_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("base_full_v0_100_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|base_full_v0_100_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|993.9 MB|
+
+## References
+
+https://huggingface.co/sreddy109/base-full-v0-100
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-base_full_v0_1200_en.md b/docs/_posts/ahmedlone127/2025-01-23-base_full_v0_1200_en.md
new file mode 100644
index 00000000000000..987624e3f7df4f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-base_full_v0_1200_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English base_full_v0_1200 XlmRoBertaForSequenceClassification from sreddy109
+author: John Snow Labs
+name: base_full_v0_1200
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`base_full_v0_1200` is a English model originally trained by sreddy109.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/base_full_v0_1200_en_5.5.1_3.0_1737653114632.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/base_full_v0_1200_en_5.5.1_3.0_1737653114632.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("base_full_v0_1200","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("base_full_v0_1200", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|base_full_v0_1200|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|993.9 MB|
+
+## References
+
+https://huggingface.co/sreddy109/base-full-v0-1200
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-base_full_v0_1200_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-base_full_v0_1200_pipeline_en.md
new file mode 100644
index 00000000000000..0a3b161de89a9f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-base_full_v0_1200_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English base_full_v0_1200_pipeline pipeline XlmRoBertaForSequenceClassification from sreddy109
+author: John Snow Labs
+name: base_full_v0_1200_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`base_full_v0_1200_pipeline` is a English model originally trained by sreddy109.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/base_full_v0_1200_pipeline_en_5.5.1_3.0_1737653174415.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/base_full_v0_1200_pipeline_en_5.5.1_3.0_1737653174415.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("base_full_v0_1200_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("base_full_v0_1200_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|base_full_v0_1200_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|993.9 MB|
+
+## References
+
+https://huggingface.co/sreddy109/base-full-v0-1200
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-base_full_v0_1600_en.md b/docs/_posts/ahmedlone127/2025-01-23-base_full_v0_1600_en.md
new file mode 100644
index 00000000000000..d2a0d03ae11af8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-base_full_v0_1600_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English base_full_v0_1600 XlmRoBertaForSequenceClassification from sreddy109
+author: John Snow Labs
+name: base_full_v0_1600
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`base_full_v0_1600` is a English model originally trained by sreddy109.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/base_full_v0_1600_en_5.5.1_3.0_1737653385222.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/base_full_v0_1600_en_5.5.1_3.0_1737653385222.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("base_full_v0_1600","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("base_full_v0_1600", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|base_full_v0_1600|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|993.9 MB|
+
+## References
+
+https://huggingface.co/sreddy109/base-full-v0-1600
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-base_full_v0_1600_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-base_full_v0_1600_pipeline_en.md
new file mode 100644
index 00000000000000..1cda0c90c99c8e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-base_full_v0_1600_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English base_full_v0_1600_pipeline pipeline XlmRoBertaForSequenceClassification from sreddy109
+author: John Snow Labs
+name: base_full_v0_1600_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`base_full_v0_1600_pipeline` is a English model originally trained by sreddy109.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/base_full_v0_1600_pipeline_en_5.5.1_3.0_1737653441066.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/base_full_v0_1600_pipeline_en_5.5.1_3.0_1737653441066.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("base_full_v0_1600_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("base_full_v0_1600_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|base_full_v0_1600_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|993.9 MB|
+
+## References
+
+https://huggingface.co/sreddy109/base-full-v0-1600
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-beds_step4_en.md b/docs/_posts/ahmedlone127/2025-01-23-beds_step4_en.md
new file mode 100644
index 00000000000000..bed3c1389e4089
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-beds_step4_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English beds_step4 MPNetEmbeddings from andreyunic23
+author: John Snow Labs
+name: beds_step4
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`beds_step4` is a English model originally trained by andreyunic23.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/beds_step4_en_5.5.1_3.0_1737669900531.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/beds_step4_en_5.5.1_3.0_1737669900531.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("beds_step4","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("beds_step4","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|beds_step4|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.7 MB|
+
+## References
+
+https://huggingface.co/andreyunic23/beds_step4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-beds_step4_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-beds_step4_pipeline_en.md
new file mode 100644
index 00000000000000..a3d24777a182de
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-beds_step4_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English beds_step4_pipeline pipeline MPNetEmbeddings from andreyunic23
+author: John Snow Labs
+name: beds_step4_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`beds_step4_pipeline` is a English model originally trained by andreyunic23.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/beds_step4_pipeline_en_5.5.1_3.0_1737669923135.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/beds_step4_pipeline_en_5.5.1_3.0_1737669923135.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("beds_step4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("beds_step4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|beds_step4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.7 MB|
+
+## References
+
+https://huggingface.co/andreyunic23/beds_step4
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-bert_base_cased_finetuned_bible_en.md b/docs/_posts/ahmedlone127/2025-01-23-bert_base_cased_finetuned_bible_en.md
new file mode 100644
index 00000000000000..23d6442d22aa0f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-bert_base_cased_finetuned_bible_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_cased_finetuned_bible BertEmbeddings from Pragash-Mohanarajah
+author: John Snow Labs
+name: bert_base_cased_finetuned_bible
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_finetuned_bible` is a English model originally trained by Pragash-Mohanarajah.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_finetuned_bible_en_5.5.1_3.0_1737637137526.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_finetuned_bible_en_5.5.1_3.0_1737637137526.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_base_cased_finetuned_bible","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_base_cased_finetuned_bible","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_cased_finetuned_bible|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/Pragash-Mohanarajah/bert-base-cased-finetuned-bible
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-bert_base_cased_finetuned_bible_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-bert_base_cased_finetuned_bible_pipeline_en.md
new file mode 100644
index 00000000000000..d6c3cc027ea7f2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-bert_base_cased_finetuned_bible_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_cased_finetuned_bible_pipeline pipeline BertEmbeddings from Pragash-Mohanarajah
+author: John Snow Labs
+name: bert_base_cased_finetuned_bible_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_finetuned_bible_pipeline` is a English model originally trained by Pragash-Mohanarajah.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_finetuned_bible_pipeline_en_5.5.1_3.0_1737637162470.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_finetuned_bible_pipeline_en_5.5.1_3.0_1737637162470.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_cased_finetuned_bible_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_cased_finetuned_bible_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_cased_finetuned_bible_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/Pragash-Mohanarajah/bert-base-cased-finetuned-bible
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-bert_base_cased_wikitext2_davyalan1_en.md b/docs/_posts/ahmedlone127/2025-01-23-bert_base_cased_wikitext2_davyalan1_en.md
new file mode 100644
index 00000000000000..f0465bc7c86743
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-bert_base_cased_wikitext2_davyalan1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_cased_wikitext2_davyalan1 BertEmbeddings from davyalan1
+author: John Snow Labs
+name: bert_base_cased_wikitext2_davyalan1
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_wikitext2_davyalan1` is a English model originally trained by davyalan1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_wikitext2_davyalan1_en_5.5.1_3.0_1737637844592.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_wikitext2_davyalan1_en_5.5.1_3.0_1737637844592.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_base_cased_wikitext2_davyalan1","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_base_cased_wikitext2_davyalan1","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_cased_wikitext2_davyalan1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|403.4 MB|
+
+## References
+
+https://huggingface.co/davyalan1/bert-base-cased-wikitext2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-bert_base_cased_wikitext2_davyalan1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-bert_base_cased_wikitext2_davyalan1_pipeline_en.md
new file mode 100644
index 00000000000000..a0b39d02f5e1f2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-bert_base_cased_wikitext2_davyalan1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_cased_wikitext2_davyalan1_pipeline pipeline BertEmbeddings from davyalan1
+author: John Snow Labs
+name: bert_base_cased_wikitext2_davyalan1_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_wikitext2_davyalan1_pipeline` is a English model originally trained by davyalan1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_wikitext2_davyalan1_pipeline_en_5.5.1_3.0_1737637866198.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_wikitext2_davyalan1_pipeline_en_5.5.1_3.0_1737637866198.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_cased_wikitext2_davyalan1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_cased_wikitext2_davyalan1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_cased_wikitext2_davyalan1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.5 MB|
+
+## References
+
+https://huggingface.co/davyalan1/bert-base-cased-wikitext2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-bert_base_multilingual_sakha_cased_2_pipeline_xx.md b/docs/_posts/ahmedlone127/2025-01-23-bert_base_multilingual_sakha_cased_2_pipeline_xx.md
new file mode 100644
index 00000000000000..9112d35ea9da26
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-bert_base_multilingual_sakha_cased_2_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual bert_base_multilingual_sakha_cased_2_pipeline pipeline BertEmbeddings from bamaxi
+author: John Snow Labs
+name: bert_base_multilingual_sakha_cased_2_pipeline
+date: 2025-01-23
+tags: [xx, open_source, pipeline, onnx]
+task: Embeddings
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_sakha_cased_2_pipeline` is a Multilingual model originally trained by bamaxi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_sakha_cased_2_pipeline_xx_5.5.1_3.0_1737637704620.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_sakha_cased_2_pipeline_xx_5.5.1_3.0_1737637704620.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_multilingual_sakha_cased_2_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_multilingual_sakha_cased_2_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_multilingual_sakha_cased_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|743.1 MB|
+
+## References
+
+https://huggingface.co/bamaxi/bert-base-multilingual-sakha-cased_2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-bert_base_multilingual_sakha_cased_2_xx.md b/docs/_posts/ahmedlone127/2025-01-23-bert_base_multilingual_sakha_cased_2_xx.md
new file mode 100644
index 00000000000000..d9a1ec45864d26
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-bert_base_multilingual_sakha_cased_2_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual bert_base_multilingual_sakha_cased_2 BertEmbeddings from bamaxi
+author: John Snow Labs
+name: bert_base_multilingual_sakha_cased_2
+date: 2025-01-23
+tags: [xx, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_sakha_cased_2` is a Multilingual model originally trained by bamaxi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_sakha_cased_2_xx_5.5.1_3.0_1737637665602.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_sakha_cased_2_xx_5.5.1_3.0_1737637665602.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_base_multilingual_sakha_cased_2","xx") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_base_multilingual_sakha_cased_2","xx") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_multilingual_sakha_cased_2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|xx|
+|Size:|743.1 MB|
+
+## References
+
+https://huggingface.co/bamaxi/bert-base-multilingual-sakha-cased_2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-bert_base_uncased_finetuned_imdb_en.md b/docs/_posts/ahmedlone127/2025-01-23-bert_base_uncased_finetuned_imdb_en.md
new file mode 100644
index 00000000000000..cc00b2ae7f06db
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-bert_base_uncased_finetuned_imdb_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_uncased_finetuned_imdb DistilBertEmbeddings from Savoxism
+author: John Snow Labs
+name: bert_base_uncased_finetuned_imdb
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_imdb` is a English model originally trained by Savoxism.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_imdb_en_5.5.1_3.0_1737663009551.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_imdb_en_5.5.1_3.0_1737663009551.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("bert_base_uncased_finetuned_imdb","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("bert_base_uncased_finetuned_imdb","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetuned_imdb|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Savoxism/bert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-bert_base_uncased_finetuned_imdb_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-bert_base_uncased_finetuned_imdb_pipeline_en.md
new file mode 100644
index 00000000000000..bc86af828194f1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-bert_base_uncased_finetuned_imdb_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_uncased_finetuned_imdb_pipeline pipeline DistilBertEmbeddings from Savoxism
+author: John Snow Labs
+name: bert_base_uncased_finetuned_imdb_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_imdb_pipeline` is a English model originally trained by Savoxism.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_imdb_pipeline_en_5.5.1_3.0_1737663023255.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_imdb_pipeline_en_5.5.1_3.0_1737663023255.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetuned_imdb_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_imdb_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetuned_imdb_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Savoxism/bert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-bert_base_uncased_rxnorm_babbage_en.md b/docs/_posts/ahmedlone127/2025-01-23-bert_base_uncased_rxnorm_babbage_en.md
new file mode 100644
index 00000000000000..47dcff2ffec9a0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-bert_base_uncased_rxnorm_babbage_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_uncased_rxnorm_babbage BertEmbeddings from Su-informatics-lab
+author: John Snow Labs
+name: bert_base_uncased_rxnorm_babbage
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_rxnorm_babbage` is a English model originally trained by Su-informatics-lab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_rxnorm_babbage_en_5.5.1_3.0_1737637136025.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_rxnorm_babbage_en_5.5.1_3.0_1737637136025.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_base_uncased_rxnorm_babbage","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_base_uncased_rxnorm_babbage","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_rxnorm_babbage|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/Su-informatics-lab/bert_base_uncased_rxnorm_babbage
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-bert_base_uncased_rxnorm_babbage_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-bert_base_uncased_rxnorm_babbage_pipeline_en.md
new file mode 100644
index 00000000000000..1d1871938c7691
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-bert_base_uncased_rxnorm_babbage_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_uncased_rxnorm_babbage_pipeline pipeline BertEmbeddings from Su-informatics-lab
+author: John Snow Labs
+name: bert_base_uncased_rxnorm_babbage_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_rxnorm_babbage_pipeline` is a English model originally trained by Su-informatics-lab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_rxnorm_babbage_pipeline_en_5.5.1_3.0_1737637162600.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_rxnorm_babbage_pipeline_en_5.5.1_3.0_1737637162600.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_rxnorm_babbage_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_rxnorm_babbage_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_rxnorm_babbage_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/Su-informatics-lab/bert_base_uncased_rxnorm_babbage
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-bert_combined_top_en.md b/docs/_posts/ahmedlone127/2025-01-23-bert_combined_top_en.md
new file mode 100644
index 00000000000000..96e79ff081a231
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-bert_combined_top_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_combined_top DistilBertForSequenceClassification from eskayML
+author: John Snow Labs
+name: bert_combined_top
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_combined_top` is a English model originally trained by eskayML.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_combined_top_en_5.5.1_3.0_1737650593658.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_combined_top_en_5.5.1_3.0_1737650593658.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("bert_combined_top","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("bert_combined_top", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_combined_top|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/eskayML/bert_combined_top
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-bert_combined_top_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-bert_combined_top_pipeline_en.md
new file mode 100644
index 00000000000000..094c0bef45e857
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-bert_combined_top_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_combined_top_pipeline pipeline DistilBertForSequenceClassification from eskayML
+author: John Snow Labs
+name: bert_combined_top_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_combined_top_pipeline` is a English model originally trained by eskayML.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_combined_top_pipeline_en_5.5.1_3.0_1737650611756.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_combined_top_pipeline_en_5.5.1_3.0_1737650611756.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_combined_top_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_combined_top_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_combined_top_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/eskayML/bert_combined_top
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-bert_electrical_ner_en.md b/docs/_posts/ahmedlone127/2025-01-23-bert_electrical_ner_en.md
new file mode 100644
index 00000000000000..0dca982674dd3e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-bert_electrical_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_electrical_ner DistilBertForTokenClassification from yasserrmd
+author: John Snow Labs
+name: bert_electrical_ner
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_electrical_ner` is a English model originally trained by yasserrmd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_electrical_ner_en_5.5.1_3.0_1737627777484.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_electrical_ner_en_5.5.1_3.0_1737627777484.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("bert_electrical_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("bert_electrical_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_electrical_ner|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/yasserrmd/bert-electrical-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-bert_electrical_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-bert_electrical_ner_pipeline_en.md
new file mode 100644
index 00000000000000..060d9fc38e6603
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-bert_electrical_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_electrical_ner_pipeline pipeline DistilBertForTokenClassification from yasserrmd
+author: John Snow Labs
+name: bert_electrical_ner_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_electrical_ner_pipeline` is a English model originally trained by yasserrmd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_electrical_ner_pipeline_en_5.5.1_3.0_1737627790986.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_electrical_ner_pipeline_en_5.5.1_3.0_1737627790986.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_electrical_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_electrical_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_electrical_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/yasserrmd/bert-electrical-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-bert_empathy_en.md b/docs/_posts/ahmedlone127/2025-01-23-bert_empathy_en.md
new file mode 100644
index 00000000000000..addf9b98c032e1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-bert_empathy_en.md
@@ -0,0 +1,98 @@
+---
+layout: model
+title: English bert_empathy RoBertaForSequenceClassification from paragon-analytics
+author: John Snow Labs
+name: bert_empathy
+date: 2025-01-23
+tags: [roberta, en, open_source, sequence_classification, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_empathy` is a English model originally trained by paragon-analytics.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_empathy_en_5.5.1_3.0_1737650002479.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_empathy_en_5.5.1_3.0_1737650002479.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = DocumentAssembler()\
+    .setInputCol("text")\
+    .setOutputCol("document")
+
+tokenizer = Tokenizer()\
+    .setInputCols("document")\
+    .setOutputCol("token")  
+    
+sequenceClassifier = RoBertaForSequenceClassification.pretrained("bert_empathy","en")\
+            .setInputCols(["document","token"])\
+            .setOutputCol("class")
+
+pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val document_assembler = new DocumentAssembler()
+    .setInputCol("text")
+    .setOutputCol("document")
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document") 
+    .setOutputCol("token")  
+    
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("bert_empathy","en")
+            .setInputCols(Array("document","token"))
+            .setOutputCol("class")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_empathy|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+References
+
+https://huggingface.co/paragon-analytics/bert_empathy
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-bert_empathy_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-bert_empathy_pipeline_en.md
new file mode 100644
index 00000000000000..c185a8446a821b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-bert_empathy_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_empathy_pipeline pipeline DistilBertForSequenceClassification from MoaazZaki
+author: John Snow Labs
+name: bert_empathy_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_empathy_pipeline` is a English model originally trained by MoaazZaki.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_empathy_pipeline_en_5.5.1_3.0_1737650023670.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_empathy_pipeline_en_5.5.1_3.0_1737650023670.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_empathy_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_empathy_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_empathy_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/MoaazZaki/bert-empathy
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-bert_large_uncased_en.md b/docs/_posts/ahmedlone127/2025-01-23-bert_large_uncased_en.md
new file mode 100644
index 00000000000000..1cc42ab2acb1b7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-bert_large_uncased_en.md
@@ -0,0 +1,93 @@
+---
+layout: model
+title: BERT Embeddings (Large Uncased)
+author: John Snow Labs
+name: bert_large_uncased
+date: 2025-01-23
+tags: [open_source, embeddings, en, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+This model contains a deep bidirectional transformer trained on Wikipedia and the BookCorpus. The details are described in the paper "[BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://arxiv.org/abs/1810.04805)".
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_en_5.5.1_3.0_1737637412137.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_en_5.5.1_3.0_1737637412137.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+...
+embeddings = BertEmbeddings.pretrained("bert_large_uncased", "en") \
+.setInputCols("sentence", "token") \
+.setOutputCol("embeddings")
+nlp_pipeline = Pipeline(stages=[document_assembler, sentence_detector, tokenizer, embeddings])
+pipeline_model = nlp_pipeline.fit(spark.createDataFrame([[""]]).toDF("text"))
+result = pipeline_model.transform(spark.createDataFrame([['I love NLP']], ["text"]))
+```
+```scala
+...
+val embeddings = BertEmbeddings.pretrained("bert_large_uncased", "en")
+.setInputCols("sentence", "token")
+.setOutputCol("embeddings")
+val pipeline = new Pipeline().setStages(Array(document_assembler, sentence_detector, tokenizer, embeddings))
+val data = Seq("I love NLP").toDF("text")
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+
+text = ["I love NLP"]
+embeddings_df = nlu.load('en.embed.bert.large_uncased').predict(text, output_level='token')
+embeddings_df
+```
+</div>
+
+## Results
+
+```bash
+
+
+	en_embed_bert_large_uncased_embeddings	token
+	
+	[-0.07447264343500137, -0.337308406829834, -0....	I
+	[-0.5735481977462769, -0.3580206632614136, -0....	love
+	[-0.3929762840270996, -0.4147087037563324, 0.2...	NLP
+```
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_large_uncased|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|1.3 GB|
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-bert_large_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-bert_large_uncased_pipeline_en.md
new file mode 100644
index 00000000000000..6a05d1569ca149
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-bert_large_uncased_pipeline_en.md
@@ -0,0 +1,72 @@
+---
+layout: model
+title: English bert_large_uncased_pipeline pipeline BertEmbeddings from google-bert
+author: John Snow Labs
+name: bert_large_uncased_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_pipeline` is a English model originally trained by google-bert.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_pipeline_en_5.5.1_3.0_1737637481801.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_pipeline_en_5.5.1_3.0_1737637481801.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("bert_large_uncased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("bert_large_uncased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_large_uncased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+References
+
+https://huggingface.co/google-bert/bert-large-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-bert_qa_en.md b/docs/_posts/ahmedlone127/2025-01-23-bert_qa_en.md
new file mode 100644
index 00000000000000..7da764e9f2c7ed
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-bert_qa_en.md
@@ -0,0 +1,92 @@
+---
+layout: model
+title: English BertForQuestionAnswering Cased model (from srcocotero)
+author: John Snow Labs
+name: bert_qa
+date: 2025-01-23
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-qa-en` is a English model originally trained by `srcocotero`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_en_5.5.1_3.0_1737660552896.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_en_5.5.1_3.0_1737660552896.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = BertForQuestionAnswering.pretrained("bert_qa","en")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa","en")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|505.4 MB|
+
+## References
+
+References
+
+- https://huggingface.co/srcocotero/bert-qa-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-bert_qa_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-bert_qa_pipeline_en.md
new file mode 100644
index 00000000000000..dad3cd2868e8e7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-bert_qa_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_qa_pipeline pipeline DistilBertForQuestionAnswering from AIForge
+author: John Snow Labs
+name: bert_qa_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_qa_pipeline` is a English model originally trained by AIForge.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_pipeline_en_5.5.1_3.0_1737660583886.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_pipeline_en_5.5.1_3.0_1737660583886.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_qa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_qa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|505.4 MB|
+
+## References
+
+https://huggingface.co/AIForge/bert-qa
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-bert_small_uncased_en.md b/docs/_posts/ahmedlone127/2025-01-23-bert_small_uncased_en.md
new file mode 100644
index 00000000000000..7c40cba580bf1e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-bert_small_uncased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_small_uncased BertEmbeddings from gaunernst
+author: John Snow Labs
+name: bert_small_uncased
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_small_uncased` is a English model originally trained by gaunernst.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_small_uncased_en_5.5.1_3.0_1737637002138.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_small_uncased_en_5.5.1_3.0_1737637002138.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_small_uncased","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_small_uncased","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_small_uncased|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|107.0 MB|
+
+## References
+
+https://huggingface.co/gaunernst/bert-small-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-bert_small_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-bert_small_uncased_pipeline_en.md
new file mode 100644
index 00000000000000..09e08f175af12c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-bert_small_uncased_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_small_uncased_pipeline pipeline BertEmbeddings from gaunernst
+author: John Snow Labs
+name: bert_small_uncased_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_small_uncased_pipeline` is a English model originally trained by gaunernst.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_small_uncased_pipeline_en_5.5.1_3.0_1737637007509.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_small_uncased_pipeline_en_5.5.1_3.0_1737637007509.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_small_uncased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_small_uncased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_small_uncased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|107.0 MB|
+
+## References
+
+https://huggingface.co/gaunernst/bert-small-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-bert_swahili_x_small_end_en.md b/docs/_posts/ahmedlone127/2025-01-23-bert_swahili_x_small_end_en.md
new file mode 100644
index 00000000000000..aea87761df7570
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-bert_swahili_x_small_end_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_swahili_x_small_end DistilBertForQuestionAnswering from Whalejay
+author: John Snow Labs
+name: bert_swahili_x_small_end
+date: 2025-01-23
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_swahili_x_small_end` is a English model originally trained by Whalejay.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_swahili_x_small_end_en_5.5.1_3.0_1737660695156.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_swahili_x_small_end_en_5.5.1_3.0_1737660695156.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("bert_swahili_x_small_end","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("bert_swahili_x_small_end", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_swahili_x_small_end|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/Whalejay/bert-sw_x_small_end
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-bert_swahili_x_small_end_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-bert_swahili_x_small_end_pipeline_en.md
new file mode 100644
index 00000000000000..4fa743df59d33d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-bert_swahili_x_small_end_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_swahili_x_small_end_pipeline pipeline DistilBertForQuestionAnswering from Whalejay
+author: John Snow Labs
+name: bert_swahili_x_small_end_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_swahili_x_small_end_pipeline` is a English model originally trained by Whalejay.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_swahili_x_small_end_pipeline_en_5.5.1_3.0_1737660709301.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_swahili_x_small_end_pipeline_en_5.5.1_3.0_1737660709301.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_swahili_x_small_end_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_swahili_x_small_end_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_swahili_x_small_end_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/Whalejay/bert-sw_x_small_end
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-bertin_base_gaussian_es.md b/docs/_posts/ahmedlone127/2025-01-23-bertin_base_gaussian_es.md
new file mode 100644
index 00000000000000..a464061a2bcd90
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-bertin_base_gaussian_es.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Castilian, Spanish bertin_base_gaussian RoBertaEmbeddings from bertin-project
+author: John Snow Labs
+name: bertin_base_gaussian
+date: 2025-01-23
+tags: [es, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: es
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bertin_base_gaussian` is a Castilian, Spanish model originally trained by bertin-project.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bertin_base_gaussian_es_5.5.1_3.0_1737643848028.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bertin_base_gaussian_es_5.5.1_3.0_1737643848028.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("bertin_base_gaussian","es") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("bertin_base_gaussian","es") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bertin_base_gaussian|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|es|
+|Size:|231.8 MB|
+
+## References
+
+https://huggingface.co/bertin-project/bertin-base-gaussian
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-bertin_base_gaussian_pipeline_es.md b/docs/_posts/ahmedlone127/2025-01-23-bertin_base_gaussian_pipeline_es.md
new file mode 100644
index 00000000000000..2f322c871b6142
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-bertin_base_gaussian_pipeline_es.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Castilian, Spanish bertin_base_gaussian_pipeline pipeline RoBertaEmbeddings from bertin-project
+author: John Snow Labs
+name: bertin_base_gaussian_pipeline
+date: 2025-01-23
+tags: [es, open_source, pipeline, onnx]
+task: Embeddings
+language: es
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bertin_base_gaussian_pipeline` is a Castilian, Spanish model originally trained by bertin-project.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bertin_base_gaussian_pipeline_es_5.5.1_3.0_1737643926774.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bertin_base_gaussian_pipeline_es_5.5.1_3.0_1737643926774.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bertin_base_gaussian_pipeline", lang = "es")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bertin_base_gaussian_pipeline", lang = "es")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bertin_base_gaussian_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|es|
+|Size:|231.8 MB|
+
+## References
+
+https://huggingface.co/bertin-project/bertin-base-gaussian
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-bias_classifier_albertv2_en.md b/docs/_posts/ahmedlone127/2025-01-23-bias_classifier_albertv2_en.md
new file mode 100644
index 00000000000000..f2fae79eef7827
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-bias_classifier_albertv2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bias_classifier_albertv2 AlbertForSequenceClassification from holistic-ai
+author: John Snow Labs
+name: bias_classifier_albertv2
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, albert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bias_classifier_albertv2` is a English model originally trained by holistic-ai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bias_classifier_albertv2_en_5.5.1_3.0_1737624514208.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bias_classifier_albertv2_en_5.5.1_3.0_1737624514208.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = AlbertForSequenceClassification.pretrained("bias_classifier_albertv2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = AlbertForSequenceClassification.pretrained("bias_classifier_albertv2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bias_classifier_albertv2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/holistic-ai/bias_classifier_albertv2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-bias_classifier_albertv2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-bias_classifier_albertv2_pipeline_en.md
new file mode 100644
index 00000000000000..59c0e89c408be0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-bias_classifier_albertv2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bias_classifier_albertv2_pipeline pipeline AlbertForSequenceClassification from holistic-ai
+author: John Snow Labs
+name: bias_classifier_albertv2_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bias_classifier_albertv2_pipeline` is a English model originally trained by holistic-ai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bias_classifier_albertv2_pipeline_en_5.5.1_3.0_1737624516589.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bias_classifier_albertv2_pipeline_en_5.5.1_3.0_1737624516589.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bias_classifier_albertv2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bias_classifier_albertv2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bias_classifier_albertv2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/holistic-ai/bias_classifier_albertv2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-bowdpr_wiki_en.md b/docs/_posts/ahmedlone127/2025-01-23-bowdpr_wiki_en.md
new file mode 100644
index 00000000000000..b289a3d008ffc5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-bowdpr_wiki_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bowdpr_wiki BertEmbeddings from bowdpr
+author: John Snow Labs
+name: bowdpr_wiki
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bowdpr_wiki` is a English model originally trained by bowdpr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bowdpr_wiki_en_5.5.1_3.0_1737638012765.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bowdpr_wiki_en_5.5.1_3.0_1737638012765.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bowdpr_wiki","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bowdpr_wiki","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bowdpr_wiki|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.9 MB|
+
+## References
+
+https://huggingface.co/bowdpr/bowdpr_wiki
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-bowdpr_wiki_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-bowdpr_wiki_pipeline_en.md
new file mode 100644
index 00000000000000..604337d6e92e40
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-bowdpr_wiki_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bowdpr_wiki_pipeline pipeline BertEmbeddings from bowdpr
+author: John Snow Labs
+name: bowdpr_wiki_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bowdpr_wiki_pipeline` is a English model originally trained by bowdpr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bowdpr_wiki_pipeline_en_5.5.1_3.0_1737638034621.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bowdpr_wiki_pipeline_en_5.5.1_3.0_1737638034621.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bowdpr_wiki_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bowdpr_wiki_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bowdpr_wiki_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|408.0 MB|
+
+## References
+
+https://huggingface.co/bowdpr/bowdpr_wiki
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-brwac_v1_4__checkpoint_last_en.md b/docs/_posts/ahmedlone127/2025-01-23-brwac_v1_4__checkpoint_last_en.md
new file mode 100644
index 00000000000000..dfc57a2cb5cf19
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-brwac_v1_4__checkpoint_last_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English brwac_v1_4__checkpoint_last RoBertaEmbeddings from eduagarcia-temp
+author: John Snow Labs
+name: brwac_v1_4__checkpoint_last
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`brwac_v1_4__checkpoint_last` is a English model originally trained by eduagarcia-temp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/brwac_v1_4__checkpoint_last_en_5.5.1_3.0_1737644089341.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/brwac_v1_4__checkpoint_last_en_5.5.1_3.0_1737644089341.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("brwac_v1_4__checkpoint_last","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("brwac_v1_4__checkpoint_last","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|brwac_v1_4__checkpoint_last|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|298.0 MB|
+
+## References
+
+https://huggingface.co/eduagarcia-temp/brwac_v1_4__checkpoint_last
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-brwac_v1_4__checkpoint_last_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-brwac_v1_4__checkpoint_last_pipeline_en.md
new file mode 100644
index 00000000000000..e6283e30f38a89
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-brwac_v1_4__checkpoint_last_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English brwac_v1_4__checkpoint_last_pipeline pipeline RoBertaEmbeddings from eduagarcia-temp
+author: John Snow Labs
+name: brwac_v1_4__checkpoint_last_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`brwac_v1_4__checkpoint_last_pipeline` is a English model originally trained by eduagarcia-temp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/brwac_v1_4__checkpoint_last_pipeline_en_5.5.1_3.0_1737644177341.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/brwac_v1_4__checkpoint_last_pipeline_en_5.5.1_3.0_1737644177341.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("brwac_v1_4__checkpoint_last_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("brwac_v1_4__checkpoint_last_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|brwac_v1_4__checkpoint_last_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|298.0 MB|
+
+## References
+
+https://huggingface.co/eduagarcia-temp/brwac_v1_4__checkpoint_last
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_model_huzalisandra_en.md b/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_model_huzalisandra_en.md
new file mode 100644
index 00000000000000..9a2bdce46347e8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_model_huzalisandra_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_huzalisandra DistilBertForSequenceClassification from huzalisandra
+author: John Snow Labs
+name: burmese_awesome_model_huzalisandra
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_huzalisandra` is a English model originally trained by huzalisandra.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_huzalisandra_en_5.5.1_3.0_1737650255129.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_huzalisandra_en_5.5.1_3.0_1737650255129.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_huzalisandra","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_huzalisandra", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_huzalisandra|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/huzalisandra/my_awesome_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_model_huzalisandra_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_model_huzalisandra_pipeline_en.md
new file mode 100644
index 00000000000000..c7e7d15c81ad3d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_model_huzalisandra_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_huzalisandra_pipeline pipeline DistilBertForSequenceClassification from huzalisandra
+author: John Snow Labs
+name: burmese_awesome_model_huzalisandra_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_huzalisandra_pipeline` is a English model originally trained by huzalisandra.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_huzalisandra_pipeline_en_5.5.1_3.0_1737650269579.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_huzalisandra_pipeline_en_5.5.1_3.0_1737650269579.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_huzalisandra_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_huzalisandra_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_huzalisandra_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/huzalisandra/my_awesome_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_opus_books_model_gwendolyn122_en.md b/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_opus_books_model_gwendolyn122_en.md
new file mode 100644
index 00000000000000..91d5b728a31587
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_opus_books_model_gwendolyn122_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_opus_books_model_gwendolyn122 T5Transformer from gwendolyn122
+author: John Snow Labs
+name: burmese_awesome_opus_books_model_gwendolyn122
+date: 2025-01-23
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_opus_books_model_gwendolyn122` is a English model originally trained by gwendolyn122.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_gwendolyn122_en_5.5.1_3.0_1737633683121.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_gwendolyn122_en_5.5.1_3.0_1737633683121.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("burmese_awesome_opus_books_model_gwendolyn122","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("burmese_awesome_opus_books_model_gwendolyn122", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_opus_books_model_gwendolyn122|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|279.5 MB|
+
+## References
+
+https://huggingface.co/gwendolyn122/my_awesome_opus_books_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_opus_books_model_gwendolyn122_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_opus_books_model_gwendolyn122_pipeline_en.md
new file mode 100644
index 00000000000000..770976c9c17be3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_opus_books_model_gwendolyn122_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_opus_books_model_gwendolyn122_pipeline pipeline T5Transformer from gwendolyn122
+author: John Snow Labs
+name: burmese_awesome_opus_books_model_gwendolyn122_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_opus_books_model_gwendolyn122_pipeline` is a English model originally trained by gwendolyn122.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_gwendolyn122_pipeline_en_5.5.1_3.0_1737633700128.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_gwendolyn122_pipeline_en_5.5.1_3.0_1737633700128.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_opus_books_model_gwendolyn122_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_opus_books_model_gwendolyn122_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_opus_books_model_gwendolyn122_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|279.5 MB|
+
+## References
+
+https://huggingface.co/gwendolyn122/my_awesome_opus_books_model
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_qa_model_cheeseleeeeena_en.md b/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_qa_model_cheeseleeeeena_en.md
new file mode 100644
index 00000000000000..1000aa13001de9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_qa_model_cheeseleeeeena_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_cheeseleeeeena DistilBertForQuestionAnswering from cheeseleeeeena
+author: John Snow Labs
+name: burmese_awesome_qa_model_cheeseleeeeena
+date: 2025-01-23
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_cheeseleeeeena` is a English model originally trained by cheeseleeeeena.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_cheeseleeeeena_en_5.5.1_3.0_1737660539864.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_cheeseleeeeena_en_5.5.1_3.0_1737660539864.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_cheeseleeeeena","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_cheeseleeeeena", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_cheeseleeeeena|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/cheeseleeeeena/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_qa_model_cheeseleeeeena_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_qa_model_cheeseleeeeena_pipeline_en.md
new file mode 100644
index 00000000000000..31ed37dc1ed968
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_qa_model_cheeseleeeeena_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_cheeseleeeeena_pipeline pipeline DistilBertForQuestionAnswering from cheeseleeeeena
+author: John Snow Labs
+name: burmese_awesome_qa_model_cheeseleeeeena_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_cheeseleeeeena_pipeline` is a English model originally trained by cheeseleeeeena.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_cheeseleeeeena_pipeline_en_5.5.1_3.0_1737660553819.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_cheeseleeeeena_pipeline_en_5.5.1_3.0_1737660553819.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_cheeseleeeeena_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_cheeseleeeeena_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_cheeseleeeeena_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/cheeseleeeeena/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_qa_model_ippobox_en.md b/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_qa_model_ippobox_en.md
new file mode 100644
index 00000000000000..7c5ff7b9f436c7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_qa_model_ippobox_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_ippobox DistilBertForQuestionAnswering from ippoBox
+author: John Snow Labs
+name: burmese_awesome_qa_model_ippobox
+date: 2025-01-23
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_ippobox` is a English model originally trained by ippoBox.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_ippobox_en_5.5.1_3.0_1737660333405.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_ippobox_en_5.5.1_3.0_1737660333405.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_ippobox","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_ippobox", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_ippobox|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/ippoBox/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_qa_model_ippobox_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_qa_model_ippobox_pipeline_en.md
new file mode 100644
index 00000000000000..e7b8868785f5dd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_qa_model_ippobox_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_ippobox_pipeline pipeline DistilBertForQuestionAnswering from ippoBox
+author: John Snow Labs
+name: burmese_awesome_qa_model_ippobox_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_ippobox_pipeline` is a English model originally trained by ippoBox.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_ippobox_pipeline_en_5.5.1_3.0_1737660347503.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_ippobox_pipeline_en_5.5.1_3.0_1737660347503.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_ippobox_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_ippobox_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_ippobox_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/ippoBox/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_qa_model_jajacola_en.md b/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_qa_model_jajacola_en.md
new file mode 100644
index 00000000000000..b5d97614e72f84
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_qa_model_jajacola_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_jajacola DistilBertForQuestionAnswering from jajacola
+author: John Snow Labs
+name: burmese_awesome_qa_model_jajacola
+date: 2025-01-23
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_jajacola` is a English model originally trained by jajacola.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_jajacola_en_5.5.1_3.0_1737660149936.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_jajacola_en_5.5.1_3.0_1737660149936.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_jajacola","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_jajacola", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_jajacola|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/jajacola/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_qa_model_jajacola_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_qa_model_jajacola_pipeline_en.md
new file mode 100644
index 00000000000000..5eb8903ad343ba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_qa_model_jajacola_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_jajacola_pipeline pipeline DistilBertForQuestionAnswering from jajacola
+author: John Snow Labs
+name: burmese_awesome_qa_model_jajacola_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_jajacola_pipeline` is a English model originally trained by jajacola.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_jajacola_pipeline_en_5.5.1_3.0_1737660163241.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_jajacola_pipeline_en_5.5.1_3.0_1737660163241.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_jajacola_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_jajacola_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_jajacola_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/jajacola/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_qa_model_louwill_en.md b/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_qa_model_louwill_en.md
new file mode 100644
index 00000000000000..94def496a66a5c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_qa_model_louwill_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_louwill DistilBertForQuestionAnswering from louwill
+author: John Snow Labs
+name: burmese_awesome_qa_model_louwill
+date: 2025-01-23
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_louwill` is a English model originally trained by louwill.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_louwill_en_5.5.1_3.0_1737660789556.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_louwill_en_5.5.1_3.0_1737660789556.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_louwill","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_louwill", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_louwill|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/louwill/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_qa_model_louwill_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_qa_model_louwill_pipeline_en.md
new file mode 100644
index 00000000000000..825fff21ea882c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_qa_model_louwill_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_louwill_pipeline pipeline DistilBertForQuestionAnswering from louwill
+author: John Snow Labs
+name: burmese_awesome_qa_model_louwill_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_louwill_pipeline` is a English model originally trained by louwill.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_louwill_pipeline_en_5.5.1_3.0_1737660804403.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_louwill_pipeline_en_5.5.1_3.0_1737660804403.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_louwill_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_louwill_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_louwill_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/louwill/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_qa_model_optifox_en.md b/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_qa_model_optifox_en.md
new file mode 100644
index 00000000000000..c3a40c26f95a97
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_qa_model_optifox_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_optifox DistilBertForQuestionAnswering from optifox
+author: John Snow Labs
+name: burmese_awesome_qa_model_optifox
+date: 2025-01-23
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_optifox` is a English model originally trained by optifox.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_optifox_en_5.5.1_3.0_1737660859005.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_optifox_en_5.5.1_3.0_1737660859005.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_optifox","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_optifox", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_optifox|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/optifox/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_qa_model_optifox_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_qa_model_optifox_pipeline_en.md
new file mode 100644
index 00000000000000..6eee179b116636
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_qa_model_optifox_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_optifox_pipeline pipeline DistilBertForQuestionAnswering from optifox
+author: John Snow Labs
+name: burmese_awesome_qa_model_optifox_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_optifox_pipeline` is a English model originally trained by optifox.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_optifox_pipeline_en_5.5.1_3.0_1737660873276.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_optifox_pipeline_en_5.5.1_3.0_1737660873276.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_optifox_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_optifox_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_optifox_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/optifox/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_qa_model_you_g_en.md b/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_qa_model_you_g_en.md
new file mode 100644
index 00000000000000..119d03b30339a1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_qa_model_you_g_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_you_g DistilBertForQuestionAnswering from YOU-G
+author: John Snow Labs
+name: burmese_awesome_qa_model_you_g
+date: 2025-01-23
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_you_g` is a English model originally trained by YOU-G.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_you_g_en_5.5.1_3.0_1737660948295.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_you_g_en_5.5.1_3.0_1737660948295.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_you_g","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_you_g", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_you_g|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/YOU-G/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_qa_model_you_g_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_qa_model_you_g_pipeline_en.md
new file mode 100644
index 00000000000000..61b7f49ea9c1ef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_qa_model_you_g_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_you_g_pipeline pipeline DistilBertForQuestionAnswering from YOU-G
+author: John Snow Labs
+name: burmese_awesome_qa_model_you_g_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_you_g_pipeline` is a English model originally trained by YOU-G.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_you_g_pipeline_en_5.5.1_3.0_1737660962592.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_you_g_pipeline_en_5.5.1_3.0_1737660962592.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_you_g_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_you_g_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_you_g_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/YOU-G/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_qa_model_zhunan915_en.md b/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_qa_model_zhunan915_en.md
new file mode 100644
index 00000000000000..10510c9a953555
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_qa_model_zhunan915_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_zhunan915 DistilBertForQuestionAnswering from zhunan915
+author: John Snow Labs
+name: burmese_awesome_qa_model_zhunan915
+date: 2025-01-23
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_zhunan915` is a English model originally trained by zhunan915.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_zhunan915_en_5.5.1_3.0_1737660499578.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_zhunan915_en_5.5.1_3.0_1737660499578.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_zhunan915","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_zhunan915", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_zhunan915|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/zhunan915/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_qa_model_zhunan915_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_qa_model_zhunan915_pipeline_en.md
new file mode 100644
index 00000000000000..3fd590712aa179
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_qa_model_zhunan915_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_zhunan915_pipeline pipeline DistilBertForQuestionAnswering from zhunan915
+author: John Snow Labs
+name: burmese_awesome_qa_model_zhunan915_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_zhunan915_pipeline` is a English model originally trained by zhunan915.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_zhunan915_pipeline_en_5.5.1_3.0_1737660512959.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_zhunan915_pipeline_en_5.5.1_3.0_1737660512959.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_zhunan915_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_zhunan915_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_zhunan915_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/zhunan915/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_token_classification_v3_en.md b/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_token_classification_v3_en.md
new file mode 100644
index 00000000000000..88baa84a67249e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_token_classification_v3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_token_classification_v3 XlmRoBertaForTokenClassification from lilyyellow
+author: John Snow Labs
+name: burmese_awesome_token_classification_v3
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_token_classification_v3` is a English model originally trained by lilyyellow.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_token_classification_v3_en_5.5.1_3.0_1737674626436.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_token_classification_v3_en_5.5.1_3.0_1737674626436.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("burmese_awesome_token_classification_v3","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("burmese_awesome_token_classification_v3", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_token_classification_v3|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|830.4 MB|
+
+## References
+
+https://huggingface.co/lilyyellow/my_awesome_token_classification_v3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_token_classification_v3_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_token_classification_v3_pipeline_en.md
new file mode 100644
index 00000000000000..daa841a594b7e6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_token_classification_v3_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_token_classification_v3_pipeline pipeline XlmRoBertaForTokenClassification from lilyyellow
+author: John Snow Labs
+name: burmese_awesome_token_classification_v3_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_token_classification_v3_pipeline` is a English model originally trained by lilyyellow.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_token_classification_v3_pipeline_en_5.5.1_3.0_1737674739777.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_token_classification_v3_pipeline_en_5.5.1_3.0_1737674739777.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_token_classification_v3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_token_classification_v3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_token_classification_v3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|830.4 MB|
+
+## References
+
+https://huggingface.co/lilyyellow/my_awesome_token_classification_v3
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_wnut_model_livtro_en.md b/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_wnut_model_livtro_en.md
new file mode 100644
index 00000000000000..d22ac05732d606
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_wnut_model_livtro_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_livtro DistilBertForTokenClassification from Livtro
+author: John Snow Labs
+name: burmese_awesome_wnut_model_livtro
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_livtro` is a English model originally trained by Livtro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_livtro_en_5.5.1_3.0_1737627772180.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_livtro_en_5.5.1_3.0_1737627772180.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_livtro","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_livtro", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_livtro|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Livtro/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_wnut_model_livtro_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_wnut_model_livtro_pipeline_en.md
new file mode 100644
index 00000000000000..ae426a08aa51fa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_wnut_model_livtro_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_livtro_pipeline pipeline DistilBertForTokenClassification from Livtro
+author: John Snow Labs
+name: burmese_awesome_wnut_model_livtro_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_livtro_pipeline` is a English model originally trained by Livtro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_livtro_pipeline_en_5.5.1_3.0_1737627786289.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_livtro_pipeline_en_5.5.1_3.0_1737627786289.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_wnut_model_livtro_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_wnut_model_livtro_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_livtro_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Livtro/my_awesome_wnut_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_wnut_model_louwill_en.md b/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_wnut_model_louwill_en.md
new file mode 100644
index 00000000000000..48d24b4566acf2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_wnut_model_louwill_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_louwill DistilBertForTokenClassification from louwill
+author: John Snow Labs
+name: burmese_awesome_wnut_model_louwill
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_louwill` is a English model originally trained by louwill.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_louwill_en_5.5.1_3.0_1737627791656.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_louwill_en_5.5.1_3.0_1737627791656.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_louwill","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_louwill", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_louwill|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/louwill/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_wnut_model_louwill_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_wnut_model_louwill_pipeline_en.md
new file mode 100644
index 00000000000000..3b68ca54886465
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-burmese_awesome_wnut_model_louwill_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_louwill_pipeline pipeline DistilBertForTokenClassification from louwill
+author: John Snow Labs
+name: burmese_awesome_wnut_model_louwill_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_louwill_pipeline` is a English model originally trained by louwill.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_louwill_pipeline_en_5.5.1_3.0_1737627807084.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_louwill_pipeline_en_5.5.1_3.0_1737627807084.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_wnut_model_louwill_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_wnut_model_louwill_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_louwill_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/louwill/my_awesome_wnut_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-burmese_fine_tuned_model_en.md b/docs/_posts/ahmedlone127/2025-01-23-burmese_fine_tuned_model_en.md
new file mode 100644
index 00000000000000..8cc648839184ef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-burmese_fine_tuned_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_fine_tuned_model DistilBertForSequenceClassification from shivamratti
+author: John Snow Labs
+name: burmese_fine_tuned_model
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_fine_tuned_model` is a English model originally trained by shivamratti.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_fine_tuned_model_en_5.5.1_3.0_1737650487799.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_fine_tuned_model_en_5.5.1_3.0_1737650487799.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_fine_tuned_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_fine_tuned_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_fine_tuned_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/shivamratti/my_fine_tuned_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-burmese_fine_tuned_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-burmese_fine_tuned_model_pipeline_en.md
new file mode 100644
index 00000000000000..30675351fdad45
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-burmese_fine_tuned_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_fine_tuned_model_pipeline pipeline DistilBertForSequenceClassification from shivamratti
+author: John Snow Labs
+name: burmese_fine_tuned_model_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_fine_tuned_model_pipeline` is a English model originally trained by shivamratti.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_fine_tuned_model_pipeline_en_5.5.1_3.0_1737650501840.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_fine_tuned_model_pipeline_en_5.5.1_3.0_1737650501840.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_fine_tuned_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_fine_tuned_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_fine_tuned_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/shivamratti/my_fine_tuned_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-burmese_finetuned_distilbert_ner_en.md b/docs/_posts/ahmedlone127/2025-01-23-burmese_finetuned_distilbert_ner_en.md
new file mode 100644
index 00000000000000..e23f9ec8bbc8f7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-burmese_finetuned_distilbert_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_finetuned_distilbert_ner DistilBertForTokenClassification from emohammadi97
+author: John Snow Labs
+name: burmese_finetuned_distilbert_ner
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_finetuned_distilbert_ner` is a English model originally trained by emohammadi97.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_finetuned_distilbert_ner_en_5.5.1_3.0_1737627262847.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_finetuned_distilbert_ner_en_5.5.1_3.0_1737627262847.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_finetuned_distilbert_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_finetuned_distilbert_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_finetuned_distilbert_ner|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/emohammadi97/my-finetuned-distilbert-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-burmese_finetuned_distilbert_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-burmese_finetuned_distilbert_ner_pipeline_en.md
new file mode 100644
index 00000000000000..02b1f22b6a40e2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-burmese_finetuned_distilbert_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_finetuned_distilbert_ner_pipeline pipeline DistilBertForTokenClassification from emohammadi97
+author: John Snow Labs
+name: burmese_finetuned_distilbert_ner_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_finetuned_distilbert_ner_pipeline` is a English model originally trained by emohammadi97.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_finetuned_distilbert_ner_pipeline_en_5.5.1_3.0_1737627297229.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_finetuned_distilbert_ner_pipeline_en_5.5.1_3.0_1737627297229.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_finetuned_distilbert_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_finetuned_distilbert_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_finetuned_distilbert_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/emohammadi97/my-finetuned-distilbert-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-burmese_first_maskedlm_en.md b/docs/_posts/ahmedlone127/2025-01-23-burmese_first_maskedlm_en.md
new file mode 100644
index 00000000000000..4f2cd464e03680
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-burmese_first_maskedlm_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_first_maskedlm RoBertaEmbeddings from hoganpham
+author: John Snow Labs
+name: burmese_first_maskedlm
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_first_maskedlm` is a English model originally trained by hoganpham.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_first_maskedlm_en_5.5.1_3.0_1737644351976.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_first_maskedlm_en_5.5.1_3.0_1737644351976.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("burmese_first_maskedlm","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("burmese_first_maskedlm","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_first_maskedlm|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/hoganpham/my_first_maskedlm
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-burmese_first_maskedlm_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-burmese_first_maskedlm_pipeline_en.md
new file mode 100644
index 00000000000000..7ff2309944a5db
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-burmese_first_maskedlm_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_first_maskedlm_pipeline pipeline RoBertaEmbeddings from hoganpham
+author: John Snow Labs
+name: burmese_first_maskedlm_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_first_maskedlm_pipeline` is a English model originally trained by hoganpham.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_first_maskedlm_pipeline_en_5.5.1_3.0_1737644372107.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_first_maskedlm_pipeline_en_5.5.1_3.0_1737644372107.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_first_maskedlm_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_first_maskedlm_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_first_maskedlm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/hoganpham/my_first_maskedlm
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-burmese_first_model_en.md b/docs/_posts/ahmedlone127/2025-01-23-burmese_first_model_en.md
new file mode 100644
index 00000000000000..9bc66ae9315d8b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-burmese_first_model_en.md
@@ -0,0 +1,96 @@
+---
+layout: model
+title: English burmese_first_model DistilBertForQuestionAnswering from DarrenLo
+author: John Snow Labs
+name: burmese_first_model
+date: 2025-01-23
+tags: [distilbert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_first_model` is a English model originally trained by DarrenLo.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_first_model_en_5.5.1_3.0_1737660781091.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_first_model_en_5.5.1_3.0_1737660781091.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_first_model","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering  
+    .pretrained("burmese_first_model", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_first_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+References
+
+References
+
+References
+
+https://huggingface.co/DarrenLo/my_first_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-burmese_first_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-burmese_first_model_pipeline_en.md
new file mode 100644
index 00000000000000..1a4915fd11d8ef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-burmese_first_model_pipeline_en.md
@@ -0,0 +1,73 @@
+---
+layout: model
+title: English burmese_first_model_pipeline pipeline CamemBertEmbeddings from hippoleveque
+author: John Snow Labs
+name: burmese_first_model_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_first_model_pipeline` is a English model originally trained by hippoleveque.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_first_model_pipeline_en_5.5.1_3.0_1737660795750.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_first_model_pipeline_en_5.5.1_3.0_1737660795750.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("burmese_first_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("burmese_first_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_first_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+References
+
+References
+
+https://huggingface.co/hippoleveque/my-first-model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-burmese_first_ner_en.md b/docs/_posts/ahmedlone127/2025-01-23-burmese_first_ner_en.md
new file mode 100644
index 00000000000000..934774858e2b30
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-burmese_first_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_first_ner DistilBertForTokenClassification from hoganpham
+author: John Snow Labs
+name: burmese_first_ner
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_first_ner` is a English model originally trained by hoganpham.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_first_ner_en_5.5.1_3.0_1737626899844.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_first_ner_en_5.5.1_3.0_1737626899844.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_first_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_first_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_first_ner|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/hoganpham/my_first_ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-burmese_first_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-burmese_first_ner_pipeline_en.md
new file mode 100644
index 00000000000000..d3a0c0893dc796
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-burmese_first_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_first_ner_pipeline pipeline DistilBertForTokenClassification from hoganpham
+author: John Snow Labs
+name: burmese_first_ner_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_first_ner_pipeline` is a English model originally trained by hoganpham.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_first_ner_pipeline_en_5.5.1_3.0_1737626913561.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_first_ner_pipeline_en_5.5.1_3.0_1737626913561.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_first_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_first_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_first_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/hoganpham/my_first_ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-burmese_first_qa_model_en.md b/docs/_posts/ahmedlone127/2025-01-23-burmese_first_qa_model_en.md
new file mode 100644
index 00000000000000..9d83edb02e68e7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-burmese_first_qa_model_en.md
@@ -0,0 +1,88 @@
+---
+layout: model
+title: English burmese_first_qa_model DistilBertForQuestionAnswering from idah4
+author: John Snow Labs
+name: burmese_first_qa_model
+date: 2025-01-23
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_first_qa_model` is a English model originally trained by idah4.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_first_qa_model_en_5.5.1_3.0_1737661008331.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_first_qa_model_en_5.5.1_3.0_1737661008331.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_first_qa_model","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_first_qa_model", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_first_qa_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+References
+
+https://huggingface.co/idah4/my_first_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-burmese_first_qa_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-burmese_first_qa_model_pipeline_en.md
new file mode 100644
index 00000000000000..475351f354b715
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-burmese_first_qa_model_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English burmese_first_qa_model_pipeline pipeline DistilBertForQuestionAnswering from idah4
+author: John Snow Labs
+name: burmese_first_qa_model_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_first_qa_model_pipeline` is a English model originally trained by idah4.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_first_qa_model_pipeline_en_5.5.1_3.0_1737661023368.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_first_qa_model_pipeline_en_5.5.1_3.0_1737661023368.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("burmese_first_qa_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("burmese_first_qa_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_first_qa_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+References
+
+https://huggingface.co/idah4/my_first_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-burmese_first_summarization_model_en.md b/docs/_posts/ahmedlone127/2025-01-23-burmese_first_summarization_model_en.md
new file mode 100644
index 00000000000000..00a1fbc1a4a19e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-burmese_first_summarization_model_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_first_summarization_model T5Transformer from hoganpham
+author: John Snow Labs
+name: burmese_first_summarization_model
+date: 2025-01-23
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_first_summarization_model` is a English model originally trained by hoganpham.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_first_summarization_model_en_5.5.1_3.0_1737635094526.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_first_summarization_model_en_5.5.1_3.0_1737635094526.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("burmese_first_summarization_model","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("burmese_first_summarization_model", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_first_summarization_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|266.0 MB|
+
+## References
+
+https://huggingface.co/hoganpham/my_first_summarization_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-burmese_first_summarization_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-burmese_first_summarization_model_pipeline_en.md
new file mode 100644
index 00000000000000..0f0ce1f322468b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-burmese_first_summarization_model_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_first_summarization_model_pipeline pipeline T5Transformer from hoganpham
+author: John Snow Labs
+name: burmese_first_summarization_model_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_first_summarization_model_pipeline` is a English model originally trained by hoganpham.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_first_summarization_model_pipeline_en_5.5.1_3.0_1737635113358.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_first_summarization_model_pipeline_en_5.5.1_3.0_1737635113358.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_first_summarization_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_first_summarization_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_first_summarization_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|266.0 MB|
+
+## References
+
+https://huggingface.co/hoganpham/my_first_summarization_model
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-cf_albert_finetuned1_en.md b/docs/_posts/ahmedlone127/2025-01-23-cf_albert_finetuned1_en.md
new file mode 100644
index 00000000000000..4a9eda429bc1eb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-cf_albert_finetuned1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English cf_albert_finetuned1 AlbertForSequenceClassification from mrfire15
+author: John Snow Labs
+name: cf_albert_finetuned1
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, albert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cf_albert_finetuned1` is a English model originally trained by mrfire15.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cf_albert_finetuned1_en_5.5.1_3.0_1737624431541.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cf_albert_finetuned1_en_5.5.1_3.0_1737624431541.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = AlbertForSequenceClassification.pretrained("cf_albert_finetuned1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = AlbertForSequenceClassification.pretrained("cf_albert_finetuned1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cf_albert_finetuned1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/mrfire15/cf-albert-finetuned1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-cf_albert_finetuned1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-cf_albert_finetuned1_pipeline_en.md
new file mode 100644
index 00000000000000..18c7234b693141
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-cf_albert_finetuned1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English cf_albert_finetuned1_pipeline pipeline AlbertForSequenceClassification from mrfire15
+author: John Snow Labs
+name: cf_albert_finetuned1_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cf_albert_finetuned1_pipeline` is a English model originally trained by mrfire15.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cf_albert_finetuned1_pipeline_en_5.5.1_3.0_1737624434013.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cf_albert_finetuned1_pipeline_en_5.5.1_3.0_1737624434013.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("cf_albert_finetuned1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cf_albert_finetuned1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cf_albert_finetuned1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|44.3 MB|
+
+## References
+
+https://huggingface.co/mrfire15/cf-albert-finetuned1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-chatbot_huggingface_python_en.md b/docs/_posts/ahmedlone127/2025-01-23-chatbot_huggingface_python_en.md
new file mode 100644
index 00000000000000..112e6ca2ec2c4e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-chatbot_huggingface_python_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English chatbot_huggingface_python DistilBertForQuestionAnswering from srinuvasan
+author: John Snow Labs
+name: chatbot_huggingface_python
+date: 2025-01-23
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`chatbot_huggingface_python` is a English model originally trained by srinuvasan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/chatbot_huggingface_python_en_5.5.1_3.0_1737660792588.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/chatbot_huggingface_python_en_5.5.1_3.0_1737660792588.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("chatbot_huggingface_python","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("chatbot_huggingface_python", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|chatbot_huggingface_python|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/srinuvasan/chatbot-huggingface-python
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-chatbot_huggingface_python_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-chatbot_huggingface_python_pipeline_en.md
new file mode 100644
index 00000000000000..9b16711dccbef4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-chatbot_huggingface_python_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English chatbot_huggingface_python_pipeline pipeline DistilBertForQuestionAnswering from srinuvasan
+author: John Snow Labs
+name: chatbot_huggingface_python_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`chatbot_huggingface_python_pipeline` is a English model originally trained by srinuvasan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/chatbot_huggingface_python_pipeline_en_5.5.1_3.0_1737660816181.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/chatbot_huggingface_python_pipeline_en_5.5.1_3.0_1737660816181.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("chatbot_huggingface_python_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("chatbot_huggingface_python_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|chatbot_huggingface_python_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/srinuvasan/chatbot-huggingface-python
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-chkpt_en.md b/docs/_posts/ahmedlone127/2025-01-23-chkpt_en.md
new file mode 100644
index 00000000000000..e01405c0819c67
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-chkpt_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English chkpt T5Transformer from khji06
+author: John Snow Labs
+name: chkpt
+date: 2025-01-23
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`chkpt` is a English model originally trained by khji06.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/chkpt_en_5.5.1_3.0_1737634495232.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/chkpt_en_5.5.1_3.0_1737634495232.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("chkpt","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("chkpt", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|chkpt|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/khji06/chkpt
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-chkpt_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-chkpt_pipeline_en.md
new file mode 100644
index 00000000000000..8eedc1e0bba1ad
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-chkpt_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English chkpt_pipeline pipeline T5Transformer from khji06
+author: John Snow Labs
+name: chkpt_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`chkpt_pipeline` is a English model originally trained by khji06.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/chkpt_pipeline_en_5.5.1_3.0_1737634557193.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/chkpt_pipeline_en_5.5.1_3.0_1737634557193.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("chkpt_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("chkpt_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|chkpt_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/khji06/chkpt
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-clasificador_tweets_adicional_en.md b/docs/_posts/ahmedlone127/2025-01-23-clasificador_tweets_adicional_en.md
new file mode 100644
index 00000000000000..ff1eabf0b58d93
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-clasificador_tweets_adicional_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English clasificador_tweets_adicional XlmRoBertaForSequenceClassification from manapole
+author: John Snow Labs
+name: clasificador_tweets_adicional
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clasificador_tweets_adicional` is a English model originally trained by manapole.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clasificador_tweets_adicional_en_5.5.1_3.0_1737654007529.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clasificador_tweets_adicional_en_5.5.1_3.0_1737654007529.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("clasificador_tweets_adicional","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("clasificador_tweets_adicional", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clasificador_tweets_adicional|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/manapole/clasificador-tweets-adicional
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-clasificador_tweets_adicional_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-clasificador_tweets_adicional_pipeline_en.md
new file mode 100644
index 00000000000000..9f62785f354f49
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-clasificador_tweets_adicional_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English clasificador_tweets_adicional_pipeline pipeline XlmRoBertaForSequenceClassification from manapole
+author: John Snow Labs
+name: clasificador_tweets_adicional_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clasificador_tweets_adicional_pipeline` is a English model originally trained by manapole.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clasificador_tweets_adicional_pipeline_en_5.5.1_3.0_1737654060298.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clasificador_tweets_adicional_pipeline_en_5.5.1_3.0_1737654060298.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("clasificador_tweets_adicional_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("clasificador_tweets_adicional_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clasificador_tweets_adicional_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/manapole/clasificador-tweets-adicional
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-clickbaitdetectionmodel_en.md b/docs/_posts/ahmedlone127/2025-01-23-clickbaitdetectionmodel_en.md
new file mode 100644
index 00000000000000..d0469249e739c7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-clickbaitdetectionmodel_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English clickbaitdetectionmodel MPNetForSequenceClassification from Milan97
+author: John Snow Labs
+name: clickbaitdetectionmodel
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, mpnet]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clickbaitdetectionmodel` is a English model originally trained by Milan97.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clickbaitdetectionmodel_en_5.5.1_3.0_1737642115289.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clickbaitdetectionmodel_en_5.5.1_3.0_1737642115289.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = MPNetForSequenceClassification.pretrained("clickbaitdetectionmodel","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = MPNetForSequenceClassification.pretrained("clickbaitdetectionmodel", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clickbaitdetectionmodel|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|408.9 MB|
+
+## References
+
+https://huggingface.co/Milan97/ClickbaitDetectionModel
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-clickbaitdetectionmodel_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-clickbaitdetectionmodel_pipeline_en.md
new file mode 100644
index 00000000000000..13a0fd2fa96476
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-clickbaitdetectionmodel_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English clickbaitdetectionmodel_pipeline pipeline MPNetForSequenceClassification from Milan97
+author: John Snow Labs
+name: clickbaitdetectionmodel_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clickbaitdetectionmodel_pipeline` is a English model originally trained by Milan97.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clickbaitdetectionmodel_pipeline_en_5.5.1_3.0_1737642141203.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clickbaitdetectionmodel_pipeline_en_5.5.1_3.0_1737642141203.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("clickbaitdetectionmodel_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("clickbaitdetectionmodel_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clickbaitdetectionmodel_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|408.9 MB|
+
+## References
+
+https://huggingface.co/Milan97/ClickbaitDetectionModel
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- MPNetForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-clinicalbert_finetune_en.md b/docs/_posts/ahmedlone127/2025-01-23-clinicalbert_finetune_en.md
new file mode 100644
index 00000000000000..8470666e9aef8e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-clinicalbert_finetune_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English clinicalbert_finetune DistilBertEmbeddings from Peter99
+author: John Snow Labs
+name: clinicalbert_finetune
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clinicalbert_finetune` is a English model originally trained by Peter99.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clinicalbert_finetune_en_5.5.1_3.0_1737663240436.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clinicalbert_finetune_en_5.5.1_3.0_1737663240436.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("clinicalbert_finetune","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("clinicalbert_finetune","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clinicalbert_finetune|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|505.3 MB|
+
+## References
+
+https://huggingface.co/Peter99/clinicalbert_finetune
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-clinicalbert_finetune_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-clinicalbert_finetune_pipeline_en.md
new file mode 100644
index 00000000000000..547548376fbe18
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-clinicalbert_finetune_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English clinicalbert_finetune_pipeline pipeline DistilBertEmbeddings from Peter99
+author: John Snow Labs
+name: clinicalbert_finetune_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clinicalbert_finetune_pipeline` is a English model originally trained by Peter99.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clinicalbert_finetune_pipeline_en_5.5.1_3.0_1737663268519.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clinicalbert_finetune_pipeline_en_5.5.1_3.0_1737663268519.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("clinicalbert_finetune_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("clinicalbert_finetune_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clinicalbert_finetune_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|505.3 MB|
+
+## References
+
+https://huggingface.co/Peter99/clinicalbert_finetune
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-clip_vit_b_32_laion2b_s34b_b79k_en.md b/docs/_posts/ahmedlone127/2025-01-23-clip_vit_b_32_laion2b_s34b_b79k_en.md
new file mode 100644
index 00000000000000..58b5905a3d0e88
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-clip_vit_b_32_laion2b_s34b_b79k_en.md
@@ -0,0 +1,120 @@
+---
+layout: model
+title: English clip_vit_b_32_laion2b_s34b_b79k CLIPForZeroShotClassification from timsek
+author: John Snow Labs
+name: clip_vit_b_32_laion2b_s34b_b79k
+date: 2025-01-23
+tags: [en, open_source, onnx, zero_shot, clip, image]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CLIPForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_b_32_laion2b_s34b_b79k` is a English model originally trained by timsek.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_b_32_laion2b_s34b_b79k_en_5.5.1_3.0_1737629417079.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_b_32_laion2b_s34b_b79k_en_5.5.1_3.0_1737629417079.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+imageDF = spark.read \
+    .format("image") \
+    .option("dropInvalid", value = True) \
+    .load("src/test/resources/image/")
+    
+candidateLabels = [
+    "a photo of a bird",
+    "a photo of a cat",
+    "a photo of a dog",
+    "a photo of a hen",
+    "a photo of a hippo",
+    "a photo of a room",
+    "a photo of a tractor",
+    "a photo of an ostrich",
+    "a photo of an ox"]
+
+ImageAssembler = ImageAssembler() \
+	.setInputCol("image") \
+	.setOutputCol("image_assembler")
+
+imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_b_32_laion2b_s34b_b79k","en") \
+     .setInputCols(["image_assembler"]) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+
+pipeline = Pipeline().setStages([ImageAssembler, imageClassifier])
+pipelineModel = pipeline.fit(imageDF)
+pipelineDF = pipelineModel.transform(imageDF)
+
+
+```
+```scala
+
+		
+val imageDF = ResourceHelper.spark.read
+  .format("image")
+  .option("dropInvalid", value = true)
+  .load("src/test/resources/image/")
+
+val candidateLabels = Array(
+  "a photo of a bird",
+  "a photo of a cat",
+  "a photo of a dog",
+  "a photo of a hen",
+  "a photo of a hippo",
+  "a photo of a room",
+  "a photo of a tractor",
+  "a photo of an ostrich",
+  "a photo of an ox")
+
+val imageAssembler = new ImageAssembler()
+  .setInputCol("image")
+  .setOutputCol("image_assembler")
+  
+val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_b_32_laion2b_s34b_b79k","en") \
+     .setInputCols(Array("image_assembler")) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+  
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+val pipelineModel = pipeline.fit(imageDF)
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_vit_b_32_laion2b_s34b_b79k|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|567.6 MB|
+
+## References
+
+https://huggingface.co/timsek/CLIP-ViT-B-32-laion2B-s34B-b79K
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-clip_vit_b_32_laion2b_s34b_b79k_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-clip_vit_b_32_laion2b_s34b_b79k_pipeline_en.md
new file mode 100644
index 00000000000000..fde24936f77857
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-clip_vit_b_32_laion2b_s34b_b79k_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English clip_vit_b_32_laion2b_s34b_b79k_pipeline pipeline CLIPForZeroShotClassification from timsek
+author: John Snow Labs
+name: clip_vit_b_32_laion2b_s34b_b79k_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_b_32_laion2b_s34b_b79k_pipeline` is a English model originally trained by timsek.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_b_32_laion2b_s34b_b79k_pipeline_en_5.5.1_3.0_1737629447482.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_b_32_laion2b_s34b_b79k_pipeline_en_5.5.1_3.0_1737629447482.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("clip_vit_b_32_laion2b_s34b_b79k_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("clip_vit_b_32_laion2b_s34b_b79k_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_vit_b_32_laion2b_s34b_b79k_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|567.6 MB|
+
+## References
+
+https://huggingface.co/timsek/CLIP-ViT-B-32-laion2B-s34B-b79K
+
+## Included Models
+
+- ImageAssembler
+- CLIPForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-clipnet_en.md b/docs/_posts/ahmedlone127/2025-01-23-clipnet_en.md
new file mode 100644
index 00000000000000..418abf8da7c97b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-clipnet_en.md
@@ -0,0 +1,120 @@
+---
+layout: model
+title: English clipnet CLIPForZeroShotClassification from swapnillo
+author: John Snow Labs
+name: clipnet
+date: 2025-01-23
+tags: [en, open_source, onnx, zero_shot, clip, image]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CLIPForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clipnet` is a English model originally trained by swapnillo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clipnet_en_5.5.1_3.0_1737630828092.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clipnet_en_5.5.1_3.0_1737630828092.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+imageDF = spark.read \
+    .format("image") \
+    .option("dropInvalid", value = True) \
+    .load("src/test/resources/image/")
+    
+candidateLabels = [
+    "a photo of a bird",
+    "a photo of a cat",
+    "a photo of a dog",
+    "a photo of a hen",
+    "a photo of a hippo",
+    "a photo of a room",
+    "a photo of a tractor",
+    "a photo of an ostrich",
+    "a photo of an ox"]
+
+ImageAssembler = ImageAssembler() \
+	.setInputCol("image") \
+	.setOutputCol("image_assembler")
+
+imageClassifier = CLIPForZeroShotClassification.pretrained("clipnet","en") \
+     .setInputCols(["image_assembler"]) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+
+pipeline = Pipeline().setStages([ImageAssembler, imageClassifier])
+pipelineModel = pipeline.fit(imageDF)
+pipelineDF = pipelineModel.transform(imageDF)
+
+
+```
+```scala
+
+		
+val imageDF = ResourceHelper.spark.read
+  .format("image")
+  .option("dropInvalid", value = true)
+  .load("src/test/resources/image/")
+
+val candidateLabels = Array(
+  "a photo of a bird",
+  "a photo of a cat",
+  "a photo of a dog",
+  "a photo of a hen",
+  "a photo of a hippo",
+  "a photo of a room",
+  "a photo of a tractor",
+  "a photo of an ostrich",
+  "a photo of an ox")
+
+val imageAssembler = new ImageAssembler()
+  .setInputCol("image")
+  .setOutputCol("image_assembler")
+  
+val imageClassifier = CLIPForZeroShotClassification.pretrained("clipnet","en") \
+     .setInputCols(Array("image_assembler")) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+  
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+val pipelineModel = pipeline.fit(imageDF)
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clipnet|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/swapnillo/clipnet
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-clipnet_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-clipnet_pipeline_en.md
new file mode 100644
index 00000000000000..d448293e41e637
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-clipnet_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English clipnet_pipeline pipeline CLIPForZeroShotClassification from swapnillo
+author: John Snow Labs
+name: clipnet_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clipnet_pipeline` is a English model originally trained by swapnillo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clipnet_pipeline_en_5.5.1_3.0_1737630908810.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clipnet_pipeline_en_5.5.1_3.0_1737630908810.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("clipnet_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("clipnet_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clipnet_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/swapnillo/clipnet
+
+## Included Models
+
+- ImageAssembler
+- CLIPForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-context_skill_extraction_base_en.md b/docs/_posts/ahmedlone127/2025-01-23-context_skill_extraction_base_en.md
new file mode 100644
index 00000000000000..5a25e19ef305cb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-context_skill_extraction_base_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English context_skill_extraction_base MPNetEmbeddings from jensjorisdecorte
+author: John Snow Labs
+name: context_skill_extraction_base
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`context_skill_extraction_base` is a English model originally trained by jensjorisdecorte.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/context_skill_extraction_base_en_5.5.1_3.0_1737670250022.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/context_skill_extraction_base_en_5.5.1_3.0_1737670250022.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("context_skill_extraction_base","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("context_skill_extraction_base","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|context_skill_extraction_base|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.7 MB|
+
+## References
+
+https://huggingface.co/jensjorisdecorte/ConTeXT-Skill-Extraction-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-context_skill_extraction_base_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-context_skill_extraction_base_pipeline_en.md
new file mode 100644
index 00000000000000..216b36693f0e77
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-context_skill_extraction_base_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English context_skill_extraction_base_pipeline pipeline MPNetEmbeddings from jensjorisdecorte
+author: John Snow Labs
+name: context_skill_extraction_base_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`context_skill_extraction_base_pipeline` is a English model originally trained by jensjorisdecorte.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/context_skill_extraction_base_pipeline_en_5.5.1_3.0_1737670272079.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/context_skill_extraction_base_pipeline_en_5.5.1_3.0_1737670272079.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("context_skill_extraction_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("context_skill_extraction_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|context_skill_extraction_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.7 MB|
+
+## References
+
+https://huggingface.co/jensjorisdecorte/ConTeXT-Skill-Extraction-base
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-crime_model_en.md b/docs/_posts/ahmedlone127/2025-01-23-crime_model_en.md
new file mode 100644
index 00000000000000..1974d4182eccd6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-crime_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English crime_model RoBertaEmbeddings from pavi156
+author: John Snow Labs
+name: crime_model
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`crime_model` is a English model originally trained by pavi156.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/crime_model_en_5.5.1_3.0_1737644336663.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/crime_model_en_5.5.1_3.0_1737644336663.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("crime_model","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("crime_model","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|crime_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/pavi156/crime_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-crime_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-crime_model_pipeline_en.md
new file mode 100644
index 00000000000000..076c348d670d68
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-crime_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English crime_model_pipeline pipeline RoBertaEmbeddings from pavi156
+author: John Snow Labs
+name: crime_model_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`crime_model_pipeline` is a English model originally trained by pavi156.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/crime_model_pipeline_en_5.5.1_3.0_1737644353483.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/crime_model_pipeline_en_5.5.1_3.0_1737644353483.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("crime_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("crime_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|crime_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/pavi156/crime_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-cs221_cs221_deberta_v3_base_finetuned_finetuned_finetuned_en.md b/docs/_posts/ahmedlone127/2025-01-23-cs221_cs221_deberta_v3_base_finetuned_finetuned_finetuned_en.md
new file mode 100644
index 00000000000000..4695906bb4ebd2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-cs221_cs221_deberta_v3_base_finetuned_finetuned_finetuned_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English cs221_cs221_deberta_v3_base_finetuned_finetuned_finetuned DeBertaForSequenceClassification from sercetexam9
+author: John Snow Labs
+name: cs221_cs221_deberta_v3_base_finetuned_finetuned_finetuned
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cs221_cs221_deberta_v3_base_finetuned_finetuned_finetuned` is a English model originally trained by sercetexam9.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cs221_cs221_deberta_v3_base_finetuned_finetuned_finetuned_en_5.5.1_3.0_1737648215357.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cs221_cs221_deberta_v3_base_finetuned_finetuned_finetuned_en_5.5.1_3.0_1737648215357.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("cs221_cs221_deberta_v3_base_finetuned_finetuned_finetuned","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("cs221_cs221_deberta_v3_base_finetuned_finetuned_finetuned", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cs221_cs221_deberta_v3_base_finetuned_finetuned_finetuned|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|574.2 MB|
+
+## References
+
+https://huggingface.co/sercetexam9/cs221-cs221-deberta-v3-base-finetuned-finetuned-finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-cs221_cs221_deberta_v3_base_finetuned_finetuned_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-cs221_cs221_deberta_v3_base_finetuned_finetuned_finetuned_pipeline_en.md
new file mode 100644
index 00000000000000..99c84a7464e33a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-cs221_cs221_deberta_v3_base_finetuned_finetuned_finetuned_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English cs221_cs221_deberta_v3_base_finetuned_finetuned_finetuned_pipeline pipeline DeBertaForSequenceClassification from sercetexam9
+author: John Snow Labs
+name: cs221_cs221_deberta_v3_base_finetuned_finetuned_finetuned_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cs221_cs221_deberta_v3_base_finetuned_finetuned_finetuned_pipeline` is a English model originally trained by sercetexam9.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cs221_cs221_deberta_v3_base_finetuned_finetuned_finetuned_pipeline_en_5.5.1_3.0_1737648292611.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cs221_cs221_deberta_v3_base_finetuned_finetuned_finetuned_pipeline_en_5.5.1_3.0_1737648292611.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("cs221_cs221_deberta_v3_base_finetuned_finetuned_finetuned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cs221_cs221_deberta_v3_base_finetuned_finetuned_finetuned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cs221_cs221_deberta_v3_base_finetuned_finetuned_finetuned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|574.2 MB|
+
+## References
+
+https://huggingface.co/sercetexam9/cs221-cs221-deberta-v3-base-finetuned-finetuned-finetuned
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-cs221_deberta_base_multi_label_classifier_eng_finetuned_30_epochs_tapt_en.md b/docs/_posts/ahmedlone127/2025-01-23-cs221_deberta_base_multi_label_classifier_eng_finetuned_30_epochs_tapt_en.md
new file mode 100644
index 00000000000000..99b38f601fb72a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-cs221_deberta_base_multi_label_classifier_eng_finetuned_30_epochs_tapt_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English cs221_deberta_base_multi_label_classifier_eng_finetuned_30_epochs_tapt DeBertaForSequenceClassification from sercetexam9
+author: John Snow Labs
+name: cs221_deberta_base_multi_label_classifier_eng_finetuned_30_epochs_tapt
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cs221_deberta_base_multi_label_classifier_eng_finetuned_30_epochs_tapt` is a English model originally trained by sercetexam9.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cs221_deberta_base_multi_label_classifier_eng_finetuned_30_epochs_tapt_en_5.5.1_3.0_1737646990240.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cs221_deberta_base_multi_label_classifier_eng_finetuned_30_epochs_tapt_en_5.5.1_3.0_1737646990240.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("cs221_deberta_base_multi_label_classifier_eng_finetuned_30_epochs_tapt","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("cs221_deberta_base_multi_label_classifier_eng_finetuned_30_epochs_tapt", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cs221_deberta_base_multi_label_classifier_eng_finetuned_30_epochs_tapt|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|689.3 MB|
+
+## References
+
+https://huggingface.co/sercetexam9/cs221-deberta-base-multi-label-classifier-eng-finetuned-30-epochs-tapt
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-cs221_deberta_base_multi_label_classifier_eng_finetuned_30_epochs_tapt_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-cs221_deberta_base_multi_label_classifier_eng_finetuned_30_epochs_tapt_pipeline_en.md
new file mode 100644
index 00000000000000..b14e5fad3166da
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-cs221_deberta_base_multi_label_classifier_eng_finetuned_30_epochs_tapt_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English cs221_deberta_base_multi_label_classifier_eng_finetuned_30_epochs_tapt_pipeline pipeline DeBertaForSequenceClassification from sercetexam9
+author: John Snow Labs
+name: cs221_deberta_base_multi_label_classifier_eng_finetuned_30_epochs_tapt_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cs221_deberta_base_multi_label_classifier_eng_finetuned_30_epochs_tapt_pipeline` is a English model originally trained by sercetexam9.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cs221_deberta_base_multi_label_classifier_eng_finetuned_30_epochs_tapt_pipeline_en_5.5.1_3.0_1737647027583.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cs221_deberta_base_multi_label_classifier_eng_finetuned_30_epochs_tapt_pipeline_en_5.5.1_3.0_1737647027583.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("cs221_deberta_base_multi_label_classifier_eng_finetuned_30_epochs_tapt_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cs221_deberta_base_multi_label_classifier_eng_finetuned_30_epochs_tapt_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cs221_deberta_base_multi_label_classifier_eng_finetuned_30_epochs_tapt_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|689.3 MB|
+
+## References
+
+https://huggingface.co/sercetexam9/cs221-deberta-base-multi-label-classifier-eng-finetuned-30-epochs-tapt
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-cs221_deberta_base_multi_label_classifier_finetuned_30_epochs_en.md b/docs/_posts/ahmedlone127/2025-01-23-cs221_deberta_base_multi_label_classifier_finetuned_30_epochs_en.md
new file mode 100644
index 00000000000000..510fa876ccef2f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-cs221_deberta_base_multi_label_classifier_finetuned_30_epochs_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English cs221_deberta_base_multi_label_classifier_finetuned_30_epochs DeBertaForSequenceClassification from sercetexam9
+author: John Snow Labs
+name: cs221_deberta_base_multi_label_classifier_finetuned_30_epochs
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cs221_deberta_base_multi_label_classifier_finetuned_30_epochs` is a English model originally trained by sercetexam9.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cs221_deberta_base_multi_label_classifier_finetuned_30_epochs_en_5.5.1_3.0_1737647424498.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cs221_deberta_base_multi_label_classifier_finetuned_30_epochs_en_5.5.1_3.0_1737647424498.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("cs221_deberta_base_multi_label_classifier_finetuned_30_epochs","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("cs221_deberta_base_multi_label_classifier_finetuned_30_epochs", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cs221_deberta_base_multi_label_classifier_finetuned_30_epochs|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|689.3 MB|
+
+## References
+
+https://huggingface.co/sercetexam9/cs221-deberta-base-multi-label-classifier-finetuned-30-epochs
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-cs221_deberta_base_multi_label_classifier_finetuned_30_epochs_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-cs221_deberta_base_multi_label_classifier_finetuned_30_epochs_pipeline_en.md
new file mode 100644
index 00000000000000..c3bba179256492
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-cs221_deberta_base_multi_label_classifier_finetuned_30_epochs_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English cs221_deberta_base_multi_label_classifier_finetuned_30_epochs_pipeline pipeline DeBertaForSequenceClassification from sercetexam9
+author: John Snow Labs
+name: cs221_deberta_base_multi_label_classifier_finetuned_30_epochs_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cs221_deberta_base_multi_label_classifier_finetuned_30_epochs_pipeline` is a English model originally trained by sercetexam9.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cs221_deberta_base_multi_label_classifier_finetuned_30_epochs_pipeline_en_5.5.1_3.0_1737647463564.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cs221_deberta_base_multi_label_classifier_finetuned_30_epochs_pipeline_en_5.5.1_3.0_1737647463564.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("cs221_deberta_base_multi_label_classifier_finetuned_30_epochs_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cs221_deberta_base_multi_label_classifier_finetuned_30_epochs_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cs221_deberta_base_multi_label_classifier_finetuned_30_epochs_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|689.4 MB|
+
+## References
+
+https://huggingface.co/sercetexam9/cs221-deberta-base-multi-label-classifier-finetuned-30-epochs
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-cs221_deberta_base_multi_label_classifier_finetuned_en.md b/docs/_posts/ahmedlone127/2025-01-23-cs221_deberta_base_multi_label_classifier_finetuned_en.md
new file mode 100644
index 00000000000000..ce07cce14e3df9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-cs221_deberta_base_multi_label_classifier_finetuned_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English cs221_deberta_base_multi_label_classifier_finetuned DeBertaForSequenceClassification from sercetexam9
+author: John Snow Labs
+name: cs221_deberta_base_multi_label_classifier_finetuned
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cs221_deberta_base_multi_label_classifier_finetuned` is a English model originally trained by sercetexam9.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cs221_deberta_base_multi_label_classifier_finetuned_en_5.5.1_3.0_1737647383357.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cs221_deberta_base_multi_label_classifier_finetuned_en_5.5.1_3.0_1737647383357.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("cs221_deberta_base_multi_label_classifier_finetuned","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("cs221_deberta_base_multi_label_classifier_finetuned", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cs221_deberta_base_multi_label_classifier_finetuned|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|689.3 MB|
+
+## References
+
+https://huggingface.co/sercetexam9/cs221-deberta-base-multi-label-classifier-finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-cs221_deberta_base_multi_label_classifier_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-cs221_deberta_base_multi_label_classifier_finetuned_pipeline_en.md
new file mode 100644
index 00000000000000..55b0d591bf4178
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-cs221_deberta_base_multi_label_classifier_finetuned_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English cs221_deberta_base_multi_label_classifier_finetuned_pipeline pipeline DeBertaForSequenceClassification from sercetexam9
+author: John Snow Labs
+name: cs221_deberta_base_multi_label_classifier_finetuned_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cs221_deberta_base_multi_label_classifier_finetuned_pipeline` is a English model originally trained by sercetexam9.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cs221_deberta_base_multi_label_classifier_finetuned_pipeline_en_5.5.1_3.0_1737647419885.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cs221_deberta_base_multi_label_classifier_finetuned_pipeline_en_5.5.1_3.0_1737647419885.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("cs221_deberta_base_multi_label_classifier_finetuned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cs221_deberta_base_multi_label_classifier_finetuned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cs221_deberta_base_multi_label_classifier_finetuned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|689.4 MB|
+
+## References
+
+https://huggingface.co/sercetexam9/cs221-deberta-base-multi-label-classifier-finetuned
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-cs221_deberta_v3_base_en.md b/docs/_posts/ahmedlone127/2025-01-23-cs221_deberta_v3_base_en.md
new file mode 100644
index 00000000000000..79e5aeb6615b64
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-cs221_deberta_v3_base_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English cs221_deberta_v3_base DeBertaForSequenceClassification from Kuongan
+author: John Snow Labs
+name: cs221_deberta_v3_base
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cs221_deberta_v3_base` is a English model originally trained by Kuongan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cs221_deberta_v3_base_en_5.5.1_3.0_1737658203724.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cs221_deberta_v3_base_en_5.5.1_3.0_1737658203724.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("cs221_deberta_v3_base","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("cs221_deberta_v3_base", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cs221_deberta_v3_base|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|573.5 MB|
+
+## References
+
+https://huggingface.co/Kuongan/CS221-deberta-v3-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-cs221_deberta_v3_base_finetuned_en.md b/docs/_posts/ahmedlone127/2025-01-23-cs221_deberta_v3_base_finetuned_en.md
new file mode 100644
index 00000000000000..6b05778292c034
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-cs221_deberta_v3_base_finetuned_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English cs221_deberta_v3_base_finetuned DeBertaForSequenceClassification from sercetexam9
+author: John Snow Labs
+name: cs221_deberta_v3_base_finetuned
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cs221_deberta_v3_base_finetuned` is a English model originally trained by sercetexam9.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cs221_deberta_v3_base_finetuned_en_5.5.1_3.0_1737648145328.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cs221_deberta_v3_base_finetuned_en_5.5.1_3.0_1737648145328.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("cs221_deberta_v3_base_finetuned","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("cs221_deberta_v3_base_finetuned", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cs221_deberta_v3_base_finetuned|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|572.9 MB|
+
+## References
+
+https://huggingface.co/sercetexam9/cs221-deberta-v3-base-finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-cs221_deberta_v3_base_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-cs221_deberta_v3_base_finetuned_pipeline_en.md
new file mode 100644
index 00000000000000..e9d79189b1f56a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-cs221_deberta_v3_base_finetuned_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English cs221_deberta_v3_base_finetuned_pipeline pipeline DeBertaForSequenceClassification from sercetexam9
+author: John Snow Labs
+name: cs221_deberta_v3_base_finetuned_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cs221_deberta_v3_base_finetuned_pipeline` is a English model originally trained by sercetexam9.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cs221_deberta_v3_base_finetuned_pipeline_en_5.5.1_3.0_1737648214210.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cs221_deberta_v3_base_finetuned_pipeline_en_5.5.1_3.0_1737648214210.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("cs221_deberta_v3_base_finetuned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cs221_deberta_v3_base_finetuned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cs221_deberta_v3_base_finetuned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|572.9 MB|
+
+## References
+
+https://huggingface.co/sercetexam9/cs221-deberta-v3-base-finetuned
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-cs221_deberta_v3_base_finetuned_semeval_aug_en.md b/docs/_posts/ahmedlone127/2025-01-23-cs221_deberta_v3_base_finetuned_semeval_aug_en.md
new file mode 100644
index 00000000000000..6a5ca82a4fde9d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-cs221_deberta_v3_base_finetuned_semeval_aug_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English cs221_deberta_v3_base_finetuned_semeval_aug DeBertaForSequenceClassification from Kuongan
+author: John Snow Labs
+name: cs221_deberta_v3_base_finetuned_semeval_aug
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cs221_deberta_v3_base_finetuned_semeval_aug` is a English model originally trained by Kuongan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cs221_deberta_v3_base_finetuned_semeval_aug_en_5.5.1_3.0_1737656861887.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cs221_deberta_v3_base_finetuned_semeval_aug_en_5.5.1_3.0_1737656861887.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("cs221_deberta_v3_base_finetuned_semeval_aug","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("cs221_deberta_v3_base_finetuned_semeval_aug", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cs221_deberta_v3_base_finetuned_semeval_aug|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|578.0 MB|
+
+## References
+
+https://huggingface.co/Kuongan/CS221-deberta-v3-base-finetuned-semeval-aug
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-cs221_deberta_v3_base_finetuned_semeval_aug_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-cs221_deberta_v3_base_finetuned_semeval_aug_pipeline_en.md
new file mode 100644
index 00000000000000..e08395ea913e26
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-cs221_deberta_v3_base_finetuned_semeval_aug_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English cs221_deberta_v3_base_finetuned_semeval_aug_pipeline pipeline DeBertaForSequenceClassification from Kuongan
+author: John Snow Labs
+name: cs221_deberta_v3_base_finetuned_semeval_aug_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cs221_deberta_v3_base_finetuned_semeval_aug_pipeline` is a English model originally trained by Kuongan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cs221_deberta_v3_base_finetuned_semeval_aug_pipeline_en_5.5.1_3.0_1737656929388.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cs221_deberta_v3_base_finetuned_semeval_aug_pipeline_en_5.5.1_3.0_1737656929388.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("cs221_deberta_v3_base_finetuned_semeval_aug_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cs221_deberta_v3_base_finetuned_semeval_aug_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cs221_deberta_v3_base_finetuned_semeval_aug_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|578.0 MB|
+
+## References
+
+https://huggingface.co/Kuongan/CS221-deberta-v3-base-finetuned-semeval-aug
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-cs221_deberta_v3_base_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-cs221_deberta_v3_base_pipeline_en.md
new file mode 100644
index 00000000000000..2c38e526ee407a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-cs221_deberta_v3_base_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English cs221_deberta_v3_base_pipeline pipeline DeBertaForSequenceClassification from Kuongan
+author: John Snow Labs
+name: cs221_deberta_v3_base_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cs221_deberta_v3_base_pipeline` is a English model originally trained by Kuongan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cs221_deberta_v3_base_pipeline_en_5.5.1_3.0_1737658271787.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cs221_deberta_v3_base_pipeline_en_5.5.1_3.0_1737658271787.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("cs221_deberta_v3_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cs221_deberta_v3_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cs221_deberta_v3_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|573.5 MB|
+
+## References
+
+https://huggingface.co/Kuongan/CS221-deberta-v3-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-cs221_deberta_v3_large_finetuned_semeval_en.md b/docs/_posts/ahmedlone127/2025-01-23-cs221_deberta_v3_large_finetuned_semeval_en.md
new file mode 100644
index 00000000000000..62665155b1af0f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-cs221_deberta_v3_large_finetuned_semeval_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English cs221_deberta_v3_large_finetuned_semeval DeBertaForSequenceClassification from Kuongan
+author: John Snow Labs
+name: cs221_deberta_v3_large_finetuned_semeval
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cs221_deberta_v3_large_finetuned_semeval` is a English model originally trained by Kuongan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cs221_deberta_v3_large_finetuned_semeval_en_5.5.1_3.0_1737658653398.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cs221_deberta_v3_large_finetuned_semeval_en_5.5.1_3.0_1737658653398.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("cs221_deberta_v3_large_finetuned_semeval","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("cs221_deberta_v3_large_finetuned_semeval", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cs221_deberta_v3_large_finetuned_semeval|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/Kuongan/CS221-deberta-v3-large-finetuned-semeval
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-cs221_deberta_v3_large_finetuned_semeval_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-cs221_deberta_v3_large_finetuned_semeval_pipeline_en.md
new file mode 100644
index 00000000000000..f38035c0898d70
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-cs221_deberta_v3_large_finetuned_semeval_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English cs221_deberta_v3_large_finetuned_semeval_pipeline pipeline DeBertaForSequenceClassification from Kuongan
+author: John Snow Labs
+name: cs221_deberta_v3_large_finetuned_semeval_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cs221_deberta_v3_large_finetuned_semeval_pipeline` is a English model originally trained by Kuongan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cs221_deberta_v3_large_finetuned_semeval_pipeline_en_5.5.1_3.0_1737658778126.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cs221_deberta_v3_large_finetuned_semeval_pipeline_en_5.5.1_3.0_1737658778126.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("cs221_deberta_v3_large_finetuned_semeval_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cs221_deberta_v3_large_finetuned_semeval_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cs221_deberta_v3_large_finetuned_semeval_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/Kuongan/CS221-deberta-v3-large-finetuned-semeval
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-cs221_mdeberta_v3_base_finetuned_semeval_aug_en.md b/docs/_posts/ahmedlone127/2025-01-23-cs221_mdeberta_v3_base_finetuned_semeval_aug_en.md
new file mode 100644
index 00000000000000..eb2a01467d4f88
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-cs221_mdeberta_v3_base_finetuned_semeval_aug_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English cs221_mdeberta_v3_base_finetuned_semeval_aug DeBertaForSequenceClassification from Kuongan
+author: John Snow Labs
+name: cs221_mdeberta_v3_base_finetuned_semeval_aug
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cs221_mdeberta_v3_base_finetuned_semeval_aug` is a English model originally trained by Kuongan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cs221_mdeberta_v3_base_finetuned_semeval_aug_en_5.5.1_3.0_1737648460250.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cs221_mdeberta_v3_base_finetuned_semeval_aug_en_5.5.1_3.0_1737648460250.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("cs221_mdeberta_v3_base_finetuned_semeval_aug","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("cs221_mdeberta_v3_base_finetuned_semeval_aug", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cs221_mdeberta_v3_base_finetuned_semeval_aug|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|837.4 MB|
+
+## References
+
+https://huggingface.co/Kuongan/CS221-mdeberta-v3-base-finetuned-semeval-aug
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-cs221_mdeberta_v3_base_finetuned_semeval_aug_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-cs221_mdeberta_v3_base_finetuned_semeval_aug_pipeline_en.md
new file mode 100644
index 00000000000000..83ac0426c77e2f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-cs221_mdeberta_v3_base_finetuned_semeval_aug_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English cs221_mdeberta_v3_base_finetuned_semeval_aug_pipeline pipeline DeBertaForSequenceClassification from Kuongan
+author: John Snow Labs
+name: cs221_mdeberta_v3_base_finetuned_semeval_aug_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cs221_mdeberta_v3_base_finetuned_semeval_aug_pipeline` is a English model originally trained by Kuongan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cs221_mdeberta_v3_base_finetuned_semeval_aug_pipeline_en_5.5.1_3.0_1737648526247.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cs221_mdeberta_v3_base_finetuned_semeval_aug_pipeline_en_5.5.1_3.0_1737648526247.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("cs221_mdeberta_v3_base_finetuned_semeval_aug_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cs221_mdeberta_v3_base_finetuned_semeval_aug_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cs221_mdeberta_v3_base_finetuned_semeval_aug_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|837.4 MB|
+
+## References
+
+https://huggingface.co/Kuongan/CS221-mdeberta-v3-base-finetuned-semeval-aug
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-cs350_qa_model_en.md b/docs/_posts/ahmedlone127/2025-01-23-cs350_qa_model_en.md
new file mode 100644
index 00000000000000..9018ac51e0cb3c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-cs350_qa_model_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English cs350_qa_model DistilBertForQuestionAnswering from joeeyw
+author: John Snow Labs
+name: cs350_qa_model
+date: 2025-01-23
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cs350_qa_model` is a English model originally trained by joeeyw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cs350_qa_model_en_5.5.1_3.0_1737660007282.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cs350_qa_model_en_5.5.1_3.0_1737660007282.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("cs350_qa_model","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("cs350_qa_model", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cs350_qa_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/joeeyw/cs350_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-cs350_qa_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-cs350_qa_model_pipeline_en.md
new file mode 100644
index 00000000000000..7b8b25e6234ade
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-cs350_qa_model_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English cs350_qa_model_pipeline pipeline DistilBertForQuestionAnswering from joeeyw
+author: John Snow Labs
+name: cs350_qa_model_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cs350_qa_model_pipeline` is a English model originally trained by joeeyw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cs350_qa_model_pipeline_en_5.5.1_3.0_1737660020278.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cs350_qa_model_pipeline_en_5.5.1_3.0_1737660020278.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("cs350_qa_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cs350_qa_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cs350_qa_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/joeeyw/cs350_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-cs350_qamodel_en.md b/docs/_posts/ahmedlone127/2025-01-23-cs350_qamodel_en.md
new file mode 100644
index 00000000000000..9d1c0f8e59095d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-cs350_qamodel_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English cs350_qamodel DistilBertForQuestionAnswering from roopa35
+author: John Snow Labs
+name: cs350_qamodel
+date: 2025-01-23
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cs350_qamodel` is a English model originally trained by roopa35.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cs350_qamodel_en_5.5.1_3.0_1737660454599.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cs350_qamodel_en_5.5.1_3.0_1737660454599.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("cs350_qamodel","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("cs350_qamodel", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cs350_qamodel|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/roopa35/cs350_QAmodel
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-cs350_qamodel_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-cs350_qamodel_pipeline_en.md
new file mode 100644
index 00000000000000..8e55e0af0c97ca
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-cs350_qamodel_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English cs350_qamodel_pipeline pipeline DistilBertForQuestionAnswering from roopa35
+author: John Snow Labs
+name: cs350_qamodel_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cs350_qamodel_pipeline` is a English model originally trained by roopa35.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cs350_qamodel_pipeline_en_5.5.1_3.0_1737660470574.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cs350_qamodel_pipeline_en_5.5.1_3.0_1737660470574.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("cs350_qamodel_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cs350_qamodel_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cs350_qamodel_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/roopa35/cs350_QAmodel
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-custom_dataset_deberta_xsmall_en.md b/docs/_posts/ahmedlone127/2025-01-23-custom_dataset_deberta_xsmall_en.md
new file mode 100644
index 00000000000000..9e82f9a67b7e1d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-custom_dataset_deberta_xsmall_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English custom_dataset_deberta_xsmall DeBertaEmbeddings from Sandy1857
+author: John Snow Labs
+name: custom_dataset_deberta_xsmall
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, deberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`custom_dataset_deberta_xsmall` is a English model originally trained by Sandy1857.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/custom_dataset_deberta_xsmall_en_5.5.1_3.0_1737643164295.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/custom_dataset_deberta_xsmall_en_5.5.1_3.0_1737643164295.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DeBertaEmbeddings.pretrained("custom_dataset_deberta_xsmall","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DeBertaEmbeddings.pretrained("custom_dataset_deberta_xsmall","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|custom_dataset_deberta_xsmall|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence, token]|
+|Output Labels:|[deberta]|
+|Language:|en|
+|Size:|265.5 MB|
+
+## References
+
+https://huggingface.co/Sandy1857/custom-dataset-deberta-xsmall
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-custom_dataset_deberta_xsmall_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-custom_dataset_deberta_xsmall_pipeline_en.md
new file mode 100644
index 00000000000000..7b7aa436923d68
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-custom_dataset_deberta_xsmall_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English custom_dataset_deberta_xsmall_pipeline pipeline DeBertaEmbeddings from Sandy1857
+author: John Snow Labs
+name: custom_dataset_deberta_xsmall_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`custom_dataset_deberta_xsmall_pipeline` is a English model originally trained by Sandy1857.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/custom_dataset_deberta_xsmall_pipeline_en_5.5.1_3.0_1737643178470.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/custom_dataset_deberta_xsmall_pipeline_en_5.5.1_3.0_1737643178470.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("custom_dataset_deberta_xsmall_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("custom_dataset_deberta_xsmall_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|custom_dataset_deberta_xsmall_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|265.5 MB|
+
+## References
+
+https://huggingface.co/Sandy1857/custom-dataset-deberta-xsmall
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-cybert_aptner_en.md b/docs/_posts/ahmedlone127/2025-01-23-cybert_aptner_en.md
new file mode 100644
index 00000000000000..82e0d454ceef70
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-cybert_aptner_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English cybert_aptner RoBertaForTokenClassification from anonymouspd
+author: John Snow Labs
+name: cybert_aptner
+date: 2025-01-23
+tags: [roberta, en, open_source, token_classification, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cybert_aptner` is a English model originally trained by anonymouspd.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cybert_aptner_en_5.5.1_3.0_1737665281839.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cybert_aptner_en_5.5.1_3.0_1737665281839.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+    
+tokenizer = Tokenizer() \
+        .setInputCols(["document"]) \
+        .setOutputCol("token")
+        
+    
+tokenClassifier = RoBertaForTokenClassification.pretrained("cybert_aptner","en") \
+            .setInputCols(["document","token"]) \
+            .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val tokenizer = Tokenizer() \
+        .setInputCols(Array("document")) \
+        .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification  
+    .pretrained("cybert_aptner", "en")
+    .setInputCols(Array("document","token")) 
+    .setOutputCol("ner") 
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cybert_aptner|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|311.5 MB|
+
+## References
+
+References
+
+https://huggingface.co/anonymouspd/CyBERT-APTNER
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-cybert_aptner_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-cybert_aptner_pipeline_en.md
new file mode 100644
index 00000000000000..51e905e8d91060
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-cybert_aptner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English cybert_aptner_pipeline pipeline RoBertaForTokenClassification from Cyber-ThreaD
+author: John Snow Labs
+name: cybert_aptner_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cybert_aptner_pipeline` is a English model originally trained by Cyber-ThreaD.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cybert_aptner_pipeline_en_5.5.1_3.0_1737665300131.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cybert_aptner_pipeline_en_5.5.1_3.0_1737665300131.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("cybert_aptner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cybert_aptner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cybert_aptner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|311.5 MB|
+
+## References
+
+https://huggingface.co/Cyber-ThreaD/CyBERT-APTNER
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-danish_ft_distilbert_base_uncased_en.md b/docs/_posts/ahmedlone127/2025-01-23-danish_ft_distilbert_base_uncased_en.md
new file mode 100644
index 00000000000000..9b192296fbb2ae
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-danish_ft_distilbert_base_uncased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English danish_ft_distilbert_base_uncased DistilBertForSequenceClassification from NLP-FEUP
+author: John Snow Labs
+name: danish_ft_distilbert_base_uncased
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`danish_ft_distilbert_base_uncased` is a English model originally trained by NLP-FEUP.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/danish_ft_distilbert_base_uncased_en_5.5.1_3.0_1737650595262.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/danish_ft_distilbert_base_uncased_en_5.5.1_3.0_1737650595262.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("danish_ft_distilbert_base_uncased","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("danish_ft_distilbert_base_uncased", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|danish_ft_distilbert_base_uncased|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/NLP-FEUP/DA-FT-distilbert-base-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-danish_ft_distilbert_base_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-danish_ft_distilbert_base_uncased_pipeline_en.md
new file mode 100644
index 00000000000000..099ae9ceede011
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-danish_ft_distilbert_base_uncased_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English danish_ft_distilbert_base_uncased_pipeline pipeline DistilBertForSequenceClassification from NLP-FEUP
+author: John Snow Labs
+name: danish_ft_distilbert_base_uncased_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`danish_ft_distilbert_base_uncased_pipeline` is a English model originally trained by NLP-FEUP.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/danish_ft_distilbert_base_uncased_pipeline_en_5.5.1_3.0_1737650611041.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/danish_ft_distilbert_base_uncased_pipeline_en_5.5.1_3.0_1737650611041.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("danish_ft_distilbert_base_uncased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("danish_ft_distilbert_base_uncased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|danish_ft_distilbert_base_uncased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/NLP-FEUP/DA-FT-distilbert-base-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-db_fe2_6_2_1_en.md b/docs/_posts/ahmedlone127/2025-01-23-db_fe2_6_2_1_en.md
new file mode 100644
index 00000000000000..6140b8fe46c5c3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-db_fe2_6_2_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English db_fe2_6_2_1 DistilBertForSequenceClassification from exala
+author: John Snow Labs
+name: db_fe2_6_2_1
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`db_fe2_6_2_1` is a English model originally trained by exala.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/db_fe2_6_2_1_en_5.5.1_3.0_1737650362559.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/db_fe2_6_2_1_en_5.5.1_3.0_1737650362559.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("db_fe2_6_2_1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("db_fe2_6_2_1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|db_fe2_6_2_1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.7 MB|
+
+## References
+
+https://huggingface.co/exala/db_fe2_6.2.1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-db_fe2_6_2_1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-db_fe2_6_2_1_pipeline_en.md
new file mode 100644
index 00000000000000..e0ad388739a35f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-db_fe2_6_2_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English db_fe2_6_2_1_pipeline pipeline DistilBertForSequenceClassification from exala
+author: John Snow Labs
+name: db_fe2_6_2_1_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`db_fe2_6_2_1_pipeline` is a English model originally trained by exala.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/db_fe2_6_2_1_pipeline_en_5.5.1_3.0_1737650377364.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/db_fe2_6_2_1_pipeline_en_5.5.1_3.0_1737650377364.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("db_fe2_6_2_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("db_fe2_6_2_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|db_fe2_6_2_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.7 MB|
+
+## References
+
+https://huggingface.co/exala/db_fe2_6.2.1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-deberta_13th_dec_en.md b/docs/_posts/ahmedlone127/2025-01-23-deberta_13th_dec_en.md
new file mode 100644
index 00000000000000..23b2fb0f2cc81d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-deberta_13th_dec_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_13th_dec DeBertaForSequenceClassification from siddharudhh
+author: John Snow Labs
+name: deberta_13th_dec
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_13th_dec` is a English model originally trained by siddharudhh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_13th_dec_en_5.5.1_3.0_1737655521761.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_13th_dec_en_5.5.1_3.0_1737655521761.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_13th_dec","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_13th_dec", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_13th_dec|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/siddharudhh/deberta_13th_dec
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-deberta_13th_dec_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-deberta_13th_dec_pipeline_en.md
new file mode 100644
index 00000000000000..62718588bae4fc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-deberta_13th_dec_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_13th_dec_pipeline pipeline DeBertaForSequenceClassification from siddharudhh
+author: John Snow Labs
+name: deberta_13th_dec_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_13th_dec_pipeline` is a English model originally trained by siddharudhh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_13th_dec_pipeline_en_5.5.1_3.0_1737655662029.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_13th_dec_pipeline_en_5.5.1_3.0_1737655662029.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_13th_dec_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_13th_dec_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_13th_dec_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/siddharudhh/deberta_13th_dec
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-deberta_14th_nov_en.md b/docs/_posts/ahmedlone127/2025-01-23-deberta_14th_nov_en.md
new file mode 100644
index 00000000000000..4fef18710686e3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-deberta_14th_nov_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_14th_nov DeBertaForSequenceClassification from ajinkya-ftpl
+author: John Snow Labs
+name: deberta_14th_nov
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_14th_nov` is a English model originally trained by ajinkya-ftpl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_14th_nov_en_5.5.1_3.0_1737656112321.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_14th_nov_en_5.5.1_3.0_1737656112321.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_14th_nov","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_14th_nov", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_14th_nov|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/ajinkya-ftpl/deberta_14th_nov
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-deberta_14th_nov_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-deberta_14th_nov_pipeline_en.md
new file mode 100644
index 00000000000000..9dce0eac0388e9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-deberta_14th_nov_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_14th_nov_pipeline pipeline DeBertaForSequenceClassification from ajinkya-ftpl
+author: John Snow Labs
+name: deberta_14th_nov_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_14th_nov_pipeline` is a English model originally trained by ajinkya-ftpl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_14th_nov_pipeline_en_5.5.1_3.0_1737656197018.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_14th_nov_pipeline_en_5.5.1_3.0_1737656197018.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_14th_nov_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_14th_nov_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_14th_nov_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/ajinkya-ftpl/deberta_14th_nov
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-deberta_attr_score_90fr_en.md b/docs/_posts/ahmedlone127/2025-01-23-deberta_attr_score_90fr_en.md
new file mode 100644
index 00000000000000..4f3e093d85da83
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-deberta_attr_score_90fr_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_attr_score_90fr DeBertaForSequenceClassification from Josef0801
+author: John Snow Labs
+name: deberta_attr_score_90fr
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_attr_score_90fr` is a English model originally trained by Josef0801.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_attr_score_90fr_en_5.5.1_3.0_1737657940204.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_attr_score_90fr_en_5.5.1_3.0_1737657940204.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_attr_score_90fr","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_attr_score_90fr", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_attr_score_90fr|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|668.8 MB|
+
+## References
+
+https://huggingface.co/Josef0801/deberta_attr_score_90fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-deberta_attr_score_90fr_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-deberta_attr_score_90fr_pipeline_en.md
new file mode 100644
index 00000000000000..62cb5e4585e6bc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-deberta_attr_score_90fr_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_attr_score_90fr_pipeline pipeline DeBertaForSequenceClassification from Josef0801
+author: John Snow Labs
+name: deberta_attr_score_90fr_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_attr_score_90fr_pipeline` is a English model originally trained by Josef0801.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_attr_score_90fr_pipeline_en_5.5.1_3.0_1737657979126.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_attr_score_90fr_pipeline_en_5.5.1_3.0_1737657979126.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_attr_score_90fr_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_attr_score_90fr_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_attr_score_90fr_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|668.9 MB|
+
+## References
+
+https://huggingface.co/Josef0801/deberta_attr_score_90fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-deberta_attr_score_en.md b/docs/_posts/ahmedlone127/2025-01-23-deberta_attr_score_en.md
new file mode 100644
index 00000000000000..0142a67b215b24
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-deberta_attr_score_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_attr_score DeBertaForSequenceClassification from Josef0801
+author: John Snow Labs
+name: deberta_attr_score
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_attr_score` is a English model originally trained by Josef0801.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_attr_score_en_5.5.1_3.0_1737647402974.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_attr_score_en_5.5.1_3.0_1737647402974.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_attr_score","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_attr_score", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_attr_score|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|642.5 MB|
+
+## References
+
+https://huggingface.co/Josef0801/deberta_attr_score
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-deberta_attr_score_filter_en.md b/docs/_posts/ahmedlone127/2025-01-23-deberta_attr_score_filter_en.md
new file mode 100644
index 00000000000000..2a1c63714087b0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-deberta_attr_score_filter_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_attr_score_filter DeBertaForSequenceClassification from Josef0801
+author: John Snow Labs
+name: deberta_attr_score_filter
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_attr_score_filter` is a English model originally trained by Josef0801.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_attr_score_filter_en_5.5.1_3.0_1737656155657.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_attr_score_filter_en_5.5.1_3.0_1737656155657.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_attr_score_filter","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_attr_score_filter", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_attr_score_filter|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|667.8 MB|
+
+## References
+
+https://huggingface.co/Josef0801/deberta_attr_score_filter
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-deberta_attr_score_filter_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-deberta_attr_score_filter_pipeline_en.md
new file mode 100644
index 00000000000000..704a23fed27de0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-deberta_attr_score_filter_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_attr_score_filter_pipeline pipeline DeBertaForSequenceClassification from Josef0801
+author: John Snow Labs
+name: deberta_attr_score_filter_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_attr_score_filter_pipeline` is a English model originally trained by Josef0801.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_attr_score_filter_pipeline_en_5.5.1_3.0_1737656194851.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_attr_score_filter_pipeline_en_5.5.1_3.0_1737656194851.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_attr_score_filter_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_attr_score_filter_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_attr_score_filter_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|667.8 MB|
+
+## References
+
+https://huggingface.co/Josef0801/deberta_attr_score_filter
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-deberta_attr_score_filter_raw_en.md b/docs/_posts/ahmedlone127/2025-01-23-deberta_attr_score_filter_raw_en.md
new file mode 100644
index 00000000000000..a2534d07c515cc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-deberta_attr_score_filter_raw_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_attr_score_filter_raw DeBertaForSequenceClassification from Josef0801
+author: John Snow Labs
+name: deberta_attr_score_filter_raw
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_attr_score_filter_raw` is a English model originally trained by Josef0801.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_attr_score_filter_raw_en_5.5.1_3.0_1737647191221.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_attr_score_filter_raw_en_5.5.1_3.0_1737647191221.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_attr_score_filter_raw","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_attr_score_filter_raw", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_attr_score_filter_raw|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|667.3 MB|
+
+## References
+
+https://huggingface.co/Josef0801/deberta_attr_score_filter_raw
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-deberta_attr_score_filter_raw_final_en.md b/docs/_posts/ahmedlone127/2025-01-23-deberta_attr_score_filter_raw_final_en.md
new file mode 100644
index 00000000000000..0373e43359e61a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-deberta_attr_score_filter_raw_final_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_attr_score_filter_raw_final DeBertaForSequenceClassification from Josef0801
+author: John Snow Labs
+name: deberta_attr_score_filter_raw_final
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_attr_score_filter_raw_final` is a English model originally trained by Josef0801.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_attr_score_filter_raw_final_en_5.5.1_3.0_1737646995058.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_attr_score_filter_raw_final_en_5.5.1_3.0_1737646995058.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_attr_score_filter_raw_final","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_attr_score_filter_raw_final", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_attr_score_filter_raw_final|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|667.7 MB|
+
+## References
+
+https://huggingface.co/Josef0801/deberta_attr_score_filter_raw_final
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-deberta_attr_score_filter_raw_final_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-deberta_attr_score_filter_raw_final_pipeline_en.md
new file mode 100644
index 00000000000000..d76e162021628f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-deberta_attr_score_filter_raw_final_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_attr_score_filter_raw_final_pipeline pipeline DeBertaForSequenceClassification from Josef0801
+author: John Snow Labs
+name: deberta_attr_score_filter_raw_final_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_attr_score_filter_raw_final_pipeline` is a English model originally trained by Josef0801.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_attr_score_filter_raw_final_pipeline_en_5.5.1_3.0_1737647040884.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_attr_score_filter_raw_final_pipeline_en_5.5.1_3.0_1737647040884.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_attr_score_filter_raw_final_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_attr_score_filter_raw_final_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_attr_score_filter_raw_final_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|667.8 MB|
+
+## References
+
+https://huggingface.co/Josef0801/deberta_attr_score_filter_raw_final
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-deberta_attr_score_filter_raw_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-deberta_attr_score_filter_raw_pipeline_en.md
new file mode 100644
index 00000000000000..cedfa7c405d5f8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-deberta_attr_score_filter_raw_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_attr_score_filter_raw_pipeline pipeline DeBertaForSequenceClassification from Josef0801
+author: John Snow Labs
+name: deberta_attr_score_filter_raw_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_attr_score_filter_raw_pipeline` is a English model originally trained by Josef0801.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_attr_score_filter_raw_pipeline_en_5.5.1_3.0_1737647232932.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_attr_score_filter_raw_pipeline_en_5.5.1_3.0_1737647232932.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_attr_score_filter_raw_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_attr_score_filter_raw_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_attr_score_filter_raw_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|667.3 MB|
+
+## References
+
+https://huggingface.co/Josef0801/deberta_attr_score_filter_raw
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-deberta_attr_score_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-deberta_attr_score_pipeline_en.md
new file mode 100644
index 00000000000000..ef2035faac4f2f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-deberta_attr_score_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_attr_score_pipeline pipeline DeBertaForSequenceClassification from Josef0801
+author: John Snow Labs
+name: deberta_attr_score_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_attr_score_pipeline` is a English model originally trained by Josef0801.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_attr_score_pipeline_en_5.5.1_3.0_1737647445058.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_attr_score_pipeline_en_5.5.1_3.0_1737647445058.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_attr_score_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_attr_score_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_attr_score_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|642.5 MB|
+
+## References
+
+https://huggingface.co/Josef0801/deberta_attr_score
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-deberta_eoc_convo_classifierv2_en.md b/docs/_posts/ahmedlone127/2025-01-23-deberta_eoc_convo_classifierv2_en.md
new file mode 100644
index 00000000000000..da775d7be2a586
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-deberta_eoc_convo_classifierv2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_eoc_convo_classifierv2 DeBertaForSequenceClassification from MathewManoj
+author: John Snow Labs
+name: deberta_eoc_convo_classifierv2
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_eoc_convo_classifierv2` is a English model originally trained by MathewManoj.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_eoc_convo_classifierv2_en_5.5.1_3.0_1737647206650.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_eoc_convo_classifierv2_en_5.5.1_3.0_1737647206650.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_eoc_convo_classifierv2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_eoc_convo_classifierv2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_eoc_convo_classifierv2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|582.1 MB|
+
+## References
+
+https://huggingface.co/MathewManoj/deberta-EOC-convo-classifierV2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-deberta_eoc_convo_classifierv2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-deberta_eoc_convo_classifierv2_pipeline_en.md
new file mode 100644
index 00000000000000..2f24cd89a6a089
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-deberta_eoc_convo_classifierv2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_eoc_convo_classifierv2_pipeline pipeline DeBertaForSequenceClassification from MathewManoj
+author: John Snow Labs
+name: deberta_eoc_convo_classifierv2_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_eoc_convo_classifierv2_pipeline` is a English model originally trained by MathewManoj.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_eoc_convo_classifierv2_pipeline_en_5.5.1_3.0_1737647279567.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_eoc_convo_classifierv2_pipeline_en_5.5.1_3.0_1737647279567.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_eoc_convo_classifierv2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_eoc_convo_classifierv2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_eoc_convo_classifierv2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|582.1 MB|
+
+## References
+
+https://huggingface.co/MathewManoj/deberta-EOC-convo-classifierV2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-deberta_fake_reviews_modell_en.md b/docs/_posts/ahmedlone127/2025-01-23-deberta_fake_reviews_modell_en.md
new file mode 100644
index 00000000000000..74dd4b9b3efa8e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-deberta_fake_reviews_modell_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_fake_reviews_modell DeBertaForSequenceClassification from zh-h
+author: John Snow Labs
+name: deberta_fake_reviews_modell
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_fake_reviews_modell` is a English model originally trained by zh-h.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_fake_reviews_modell_en_5.5.1_3.0_1737656966015.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_fake_reviews_modell_en_5.5.1_3.0_1737656966015.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_fake_reviews_modell","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_fake_reviews_modell", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_fake_reviews_modell|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|623.3 MB|
+
+## References
+
+https://huggingface.co/zh-h/deberta-fake-reviews-modell
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-deberta_fake_reviews_modell_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-deberta_fake_reviews_modell_pipeline_en.md
new file mode 100644
index 00000000000000..314d59c301cb03
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-deberta_fake_reviews_modell_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_fake_reviews_modell_pipeline pipeline DeBertaForSequenceClassification from zh-h
+author: John Snow Labs
+name: deberta_fake_reviews_modell_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_fake_reviews_modell_pipeline` is a English model originally trained by zh-h.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_fake_reviews_modell_pipeline_en_5.5.1_3.0_1737657015420.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_fake_reviews_modell_pipeline_en_5.5.1_3.0_1737657015420.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_fake_reviews_modell_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_fake_reviews_modell_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_fake_reviews_modell_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|623.3 MB|
+
+## References
+
+https://huggingface.co/zh-h/deberta-fake-reviews-modell
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-deberta_ft_ze_zeggen_dat_testmodel_en.md b/docs/_posts/ahmedlone127/2025-01-23-deberta_ft_ze_zeggen_dat_testmodel_en.md
new file mode 100644
index 00000000000000..f57f6e8b86cadf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-deberta_ft_ze_zeggen_dat_testmodel_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_ft_ze_zeggen_dat_testmodel DeBertaForSequenceClassification from SeppeV
+author: John Snow Labs
+name: deberta_ft_ze_zeggen_dat_testmodel
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_ft_ze_zeggen_dat_testmodel` is a English model originally trained by SeppeV.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_ft_ze_zeggen_dat_testmodel_en_5.5.1_3.0_1737657680630.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_ft_ze_zeggen_dat_testmodel_en_5.5.1_3.0_1737657680630.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_ft_ze_zeggen_dat_testmodel","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_ft_ze_zeggen_dat_testmodel", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_ft_ze_zeggen_dat_testmodel|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|553.4 MB|
+
+## References
+
+https://huggingface.co/SeppeV/deberta-ft-ze-zeggen-dat-testmodel
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-deberta_ft_ze_zeggen_dat_testmodel_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-deberta_ft_ze_zeggen_dat_testmodel_pipeline_en.md
new file mode 100644
index 00000000000000..1ae36270370a7e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-deberta_ft_ze_zeggen_dat_testmodel_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_ft_ze_zeggen_dat_testmodel_pipeline pipeline DeBertaForSequenceClassification from SeppeV
+author: John Snow Labs
+name: deberta_ft_ze_zeggen_dat_testmodel_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_ft_ze_zeggen_dat_testmodel_pipeline` is a English model originally trained by SeppeV.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_ft_ze_zeggen_dat_testmodel_pipeline_en_5.5.1_3.0_1737657771375.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_ft_ze_zeggen_dat_testmodel_pipeline_en_5.5.1_3.0_1737657771375.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_ft_ze_zeggen_dat_testmodel_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_ft_ze_zeggen_dat_testmodel_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_ft_ze_zeggen_dat_testmodel_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|553.4 MB|
+
+## References
+
+https://huggingface.co/SeppeV/deberta-ft-ze-zeggen-dat-testmodel
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-deberta_multitask_v0_en.md b/docs/_posts/ahmedlone127/2025-01-23-deberta_multitask_v0_en.md
new file mode 100644
index 00000000000000..60cbfa64132a28
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-deberta_multitask_v0_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_multitask_v0 DeBertaForSequenceClassification from Quintu
+author: John Snow Labs
+name: deberta_multitask_v0
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_multitask_v0` is a English model originally trained by Quintu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_multitask_v0_en_5.5.1_3.0_1737656566535.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_multitask_v0_en_5.5.1_3.0_1737656566535.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_multitask_v0","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_multitask_v0", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_multitask_v0|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/Quintu/deberta-multitask-v0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-deberta_multitask_v0_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-deberta_multitask_v0_pipeline_en.md
new file mode 100644
index 00000000000000..18c8bb20c058bb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-deberta_multitask_v0_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_multitask_v0_pipeline pipeline DeBertaForSequenceClassification from Quintu
+author: John Snow Labs
+name: deberta_multitask_v0_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_multitask_v0_pipeline` is a English model originally trained by Quintu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_multitask_v0_pipeline_en_5.5.1_3.0_1737656649601.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_multitask_v0_pipeline_en_5.5.1_3.0_1737656649601.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_multitask_v0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_multitask_v0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_multitask_v0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/Quintu/deberta-multitask-v0
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-deberta_v3_aac_classifier_en.md b/docs/_posts/ahmedlone127/2025-01-23-deberta_v3_aac_classifier_en.md
new file mode 100644
index 00000000000000..08c7d867f3f06c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-deberta_v3_aac_classifier_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_aac_classifier DeBertaForSequenceClassification from figmtu
+author: John Snow Labs
+name: deberta_v3_aac_classifier
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_aac_classifier` is a English model originally trained by figmtu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_aac_classifier_en_5.5.1_3.0_1737648310957.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_aac_classifier_en_5.5.1_3.0_1737648310957.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_aac_classifier","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_aac_classifier", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_aac_classifier|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|438.9 MB|
+
+## References
+
+https://huggingface.co/figmtu/deberta-v3-aac-classifier
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-deberta_v3_aac_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-deberta_v3_aac_classifier_pipeline_en.md
new file mode 100644
index 00000000000000..0dfc1a7ed56f57
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-deberta_v3_aac_classifier_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_aac_classifier_pipeline pipeline DeBertaForSequenceClassification from figmtu
+author: John Snow Labs
+name: deberta_v3_aac_classifier_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_aac_classifier_pipeline` is a English model originally trained by figmtu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_aac_classifier_pipeline_en_5.5.1_3.0_1737648444200.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_aac_classifier_pipeline_en_5.5.1_3.0_1737648444200.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_aac_classifier_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_aac_classifier_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_aac_classifier_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|438.9 MB|
+
+## References
+
+https://huggingface.co/figmtu/deberta-v3-aac-classifier
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-deberta_v3_base_daigenc_mgt1a_en.md b/docs/_posts/ahmedlone127/2025-01-23-deberta_v3_base_daigenc_mgt1a_en.md
new file mode 100644
index 00000000000000..6efb40702e9c0c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-deberta_v3_base_daigenc_mgt1a_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_base_daigenc_mgt1a DeBertaForSequenceClassification from OU-Advacheck
+author: John Snow Labs
+name: deberta_v3_base_daigenc_mgt1a
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_daigenc_mgt1a` is a English model originally trained by OU-Advacheck.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_daigenc_mgt1a_en_5.5.1_3.0_1737648378420.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_daigenc_mgt1a_en_5.5.1_3.0_1737648378420.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_base_daigenc_mgt1a","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_daigenc_mgt1a", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_daigenc_mgt1a|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|685.3 MB|
+
+## References
+
+https://huggingface.co/OU-Advacheck/deberta-v3-base-daigenc-mgt1a
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-deberta_v3_base_daigenc_mgt1a_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-deberta_v3_base_daigenc_mgt1a_pipeline_en.md
new file mode 100644
index 00000000000000..002cb909e09554
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-deberta_v3_base_daigenc_mgt1a_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_base_daigenc_mgt1a_pipeline pipeline DeBertaForSequenceClassification from OU-Advacheck
+author: John Snow Labs
+name: deberta_v3_base_daigenc_mgt1a_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_daigenc_mgt1a_pipeline` is a English model originally trained by OU-Advacheck.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_daigenc_mgt1a_pipeline_en_5.5.1_3.0_1737648416948.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_daigenc_mgt1a_pipeline_en_5.5.1_3.0_1737648416948.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_base_daigenc_mgt1a_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_base_daigenc_mgt1a_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_daigenc_mgt1a_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|685.4 MB|
+
+## References
+
+https://huggingface.co/OU-Advacheck/deberta-v3-base-daigenc-mgt1a
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-deberta_v3_base_finetuned_with_classification_head_2024_12_01_09_06_en.md b/docs/_posts/ahmedlone127/2025-01-23-deberta_v3_base_finetuned_with_classification_head_2024_12_01_09_06_en.md
new file mode 100644
index 00000000000000..99e97effdf7420
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-deberta_v3_base_finetuned_with_classification_head_2024_12_01_09_06_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_base_finetuned_with_classification_head_2024_12_01_09_06 DeBertaForSequenceClassification from bhujith10
+author: John Snow Labs
+name: deberta_v3_base_finetuned_with_classification_head_2024_12_01_09_06
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_finetuned_with_classification_head_2024_12_01_09_06` is a English model originally trained by bhujith10.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_finetuned_with_classification_head_2024_12_01_09_06_en_5.5.1_3.0_1737646895785.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_finetuned_with_classification_head_2024_12_01_09_06_en_5.5.1_3.0_1737646895785.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_base_finetuned_with_classification_head_2024_12_01_09_06","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_finetuned_with_classification_head_2024_12_01_09_06", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_finetuned_with_classification_head_2024_12_01_09_06|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|352.3 MB|
+
+## References
+
+https://huggingface.co/bhujith10/deberta-v3-base_finetuned_with_classification_head_2024_12_01_09_06
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-deberta_v3_base_finetuned_with_classification_head_2024_12_01_09_06_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-deberta_v3_base_finetuned_with_classification_head_2024_12_01_09_06_pipeline_en.md
new file mode 100644
index 00000000000000..3968aa7f9f8708
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-deberta_v3_base_finetuned_with_classification_head_2024_12_01_09_06_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_base_finetuned_with_classification_head_2024_12_01_09_06_pipeline pipeline DeBertaForSequenceClassification from bhujith10
+author: John Snow Labs
+name: deberta_v3_base_finetuned_with_classification_head_2024_12_01_09_06_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_finetuned_with_classification_head_2024_12_01_09_06_pipeline` is a English model originally trained by bhujith10.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_finetuned_with_classification_head_2024_12_01_09_06_pipeline_en_5.5.1_3.0_1737647018380.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_finetuned_with_classification_head_2024_12_01_09_06_pipeline_en_5.5.1_3.0_1737647018380.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_base_finetuned_with_classification_head_2024_12_01_09_06_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_base_finetuned_with_classification_head_2024_12_01_09_06_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_finetuned_with_classification_head_2024_12_01_09_06_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|352.4 MB|
+
+## References
+
+https://huggingface.co/bhujith10/deberta-v3-base_finetuned_with_classification_head_2024_12_01_09_06
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-deberta_v3_ft_predtrade_0_685_en.md b/docs/_posts/ahmedlone127/2025-01-23-deberta_v3_ft_predtrade_0_685_en.md
new file mode 100644
index 00000000000000..0aa52b20e6a960
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-deberta_v3_ft_predtrade_0_685_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_ft_predtrade_0_685 DeBertaForSequenceClassification from akseljoonas
+author: John Snow Labs
+name: deberta_v3_ft_predtrade_0_685
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_ft_predtrade_0_685` is a English model originally trained by akseljoonas.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_ft_predtrade_0_685_en_5.5.1_3.0_1737657677944.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_ft_predtrade_0_685_en_5.5.1_3.0_1737657677944.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_ft_predtrade_0_685","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_ft_predtrade_0_685", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_ft_predtrade_0_685|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|437.1 MB|
+
+## References
+
+https://huggingface.co/akseljoonas/deberta-v3-ft-predtrade_0.685
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-deberta_v3_ft_predtrade_0_685_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-deberta_v3_ft_predtrade_0_685_pipeline_en.md
new file mode 100644
index 00000000000000..469fc1f092254c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-deberta_v3_ft_predtrade_0_685_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_ft_predtrade_0_685_pipeline pipeline DeBertaForSequenceClassification from akseljoonas
+author: John Snow Labs
+name: deberta_v3_ft_predtrade_0_685_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_ft_predtrade_0_685_pipeline` is a English model originally trained by akseljoonas.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_ft_predtrade_0_685_pipeline_en_5.5.1_3.0_1737657745749.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_ft_predtrade_0_685_pipeline_en_5.5.1_3.0_1737657745749.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_ft_predtrade_0_685_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_ft_predtrade_0_685_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_ft_predtrade_0_685_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|437.1 MB|
+
+## References
+
+https://huggingface.co/akseljoonas/deberta-v3-ft-predtrade_0.685
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-deberta_v3_large_faster_learning_en.md b/docs/_posts/ahmedlone127/2025-01-23-deberta_v3_large_faster_learning_en.md
new file mode 100644
index 00000000000000..a470c04335e918
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-deberta_v3_large_faster_learning_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_large_faster_learning DeBertaForSequenceClassification from bobbyw
+author: John Snow Labs
+name: deberta_v3_large_faster_learning
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_faster_learning` is a English model originally trained by bobbyw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_faster_learning_en_5.5.1_3.0_1737656504293.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_faster_learning_en_5.5.1_3.0_1737656504293.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_large_faster_learning","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large_faster_learning", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large_faster_learning|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/bobbyw/deberta-v3-large_faster_learning
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-deberta_v3_large_faster_learning_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-deberta_v3_large_faster_learning_pipeline_en.md
new file mode 100644
index 00000000000000..603f3e2b5763cf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-deberta_v3_large_faster_learning_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_large_faster_learning_pipeline pipeline DeBertaForSequenceClassification from bobbyw
+author: John Snow Labs
+name: deberta_v3_large_faster_learning_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_faster_learning_pipeline` is a English model originally trained by bobbyw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_faster_learning_pipeline_en_5.5.1_3.0_1737656652069.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_faster_learning_pipeline_en_5.5.1_3.0_1737656652069.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_large_faster_learning_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_large_faster_learning_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large_faster_learning_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/bobbyw/deberta-v3-large_faster_learning
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-deberta_v3_small_mbib_2048_en.md b/docs/_posts/ahmedlone127/2025-01-23-deberta_v3_small_mbib_2048_en.md
new file mode 100644
index 00000000000000..5633ddb1cc190c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-deberta_v3_small_mbib_2048_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_small_mbib_2048 DeBertaForSequenceClassification from ANGKJ1995
+author: John Snow Labs
+name: deberta_v3_small_mbib_2048
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_small_mbib_2048` is a English model originally trained by ANGKJ1995.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_small_mbib_2048_en_5.5.1_3.0_1737656380656.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_small_mbib_2048_en_5.5.1_3.0_1737656380656.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_small_mbib_2048","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_small_mbib_2048", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_small_mbib_2048|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|457.2 MB|
+
+## References
+
+https://huggingface.co/ANGKJ1995/deberta-v3-small-mbib-2048
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-deberta_v3_small_mbib_2048_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-deberta_v3_small_mbib_2048_pipeline_en.md
new file mode 100644
index 00000000000000..f86819014fd0af
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-deberta_v3_small_mbib_2048_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_small_mbib_2048_pipeline pipeline DeBertaForSequenceClassification from ANGKJ1995
+author: John Snow Labs
+name: deberta_v3_small_mbib_2048_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_small_mbib_2048_pipeline` is a English model originally trained by ANGKJ1995.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_small_mbib_2048_pipeline_en_5.5.1_3.0_1737656423639.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_small_mbib_2048_pipeline_en_5.5.1_3.0_1737656423639.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_small_mbib_2048_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_small_mbib_2048_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_small_mbib_2048_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|457.2 MB|
+
+## References
+
+https://huggingface.co/ANGKJ1995/deberta-v3-small-mbib-2048
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-deberta_v3_xsmall_zyda_2_sentiment_en.md b/docs/_posts/ahmedlone127/2025-01-23-deberta_v3_xsmall_zyda_2_sentiment_en.md
new file mode 100644
index 00000000000000..ff85cdd084da6c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-deberta_v3_xsmall_zyda_2_sentiment_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_xsmall_zyda_2_sentiment DeBertaForSequenceClassification from agentlans
+author: John Snow Labs
+name: deberta_v3_xsmall_zyda_2_sentiment
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_xsmall_zyda_2_sentiment` is a English model originally trained by agentlans.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_zyda_2_sentiment_en_5.5.1_3.0_1737646779172.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_zyda_2_sentiment_en_5.5.1_3.0_1737646779172.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_xsmall_zyda_2_sentiment","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_xsmall_zyda_2_sentiment", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_xsmall_zyda_2_sentiment|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|266.2 MB|
+
+## References
+
+https://huggingface.co/agentlans/deberta-v3-xsmall-zyda-2-sentiment
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-deberta_v3_xsmall_zyda_2_sentiment_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-deberta_v3_xsmall_zyda_2_sentiment_pipeline_en.md
new file mode 100644
index 00000000000000..a4485ec3dfc4ac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-deberta_v3_xsmall_zyda_2_sentiment_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_xsmall_zyda_2_sentiment_pipeline pipeline DeBertaForSequenceClassification from agentlans
+author: John Snow Labs
+name: deberta_v3_xsmall_zyda_2_sentiment_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_xsmall_zyda_2_sentiment_pipeline` is a English model originally trained by agentlans.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_zyda_2_sentiment_pipeline_en_5.5.1_3.0_1737646793839.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_zyda_2_sentiment_pipeline_en_5.5.1_3.0_1737646793839.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_xsmall_zyda_2_sentiment_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_xsmall_zyda_2_sentiment_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_xsmall_zyda_2_sentiment_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|266.2 MB|
+
+## References
+
+https://huggingface.co/agentlans/deberta-v3-xsmall-zyda-2-sentiment
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-debertav3_finetuned_banking_transaction_classification_text_only_en.md b/docs/_posts/ahmedlone127/2025-01-23-debertav3_finetuned_banking_transaction_classification_text_only_en.md
new file mode 100644
index 00000000000000..fccf986b559d55
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-debertav3_finetuned_banking_transaction_classification_text_only_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English debertav3_finetuned_banking_transaction_classification_text_only DeBertaForSequenceClassification from wanadzhar913
+author: John Snow Labs
+name: debertav3_finetuned_banking_transaction_classification_text_only
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`debertav3_finetuned_banking_transaction_classification_text_only` is a English model originally trained by wanadzhar913.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/debertav3_finetuned_banking_transaction_classification_text_only_en_5.5.1_3.0_1737656354027.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/debertav3_finetuned_banking_transaction_classification_text_only_en_5.5.1_3.0_1737656354027.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("debertav3_finetuned_banking_transaction_classification_text_only","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("debertav3_finetuned_banking_transaction_classification_text_only", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|debertav3_finetuned_banking_transaction_classification_text_only|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|589.6 MB|
+
+## References
+
+https://huggingface.co/wanadzhar913/debertav3-finetuned-banking-transaction-classification-text-only
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-debertav3_finetuned_banking_transaction_classification_text_only_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-debertav3_finetuned_banking_transaction_classification_text_only_pipeline_en.md
new file mode 100644
index 00000000000000..ccb034d2951839
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-debertav3_finetuned_banking_transaction_classification_text_only_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English debertav3_finetuned_banking_transaction_classification_text_only_pipeline pipeline DeBertaForSequenceClassification from wanadzhar913
+author: John Snow Labs
+name: debertav3_finetuned_banking_transaction_classification_text_only_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`debertav3_finetuned_banking_transaction_classification_text_only_pipeline` is a English model originally trained by wanadzhar913.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/debertav3_finetuned_banking_transaction_classification_text_only_pipeline_en_5.5.1_3.0_1737656420920.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/debertav3_finetuned_banking_transaction_classification_text_only_pipeline_en_5.5.1_3.0_1737656420920.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("debertav3_finetuned_banking_transaction_classification_text_only_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("debertav3_finetuned_banking_transaction_classification_text_only_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|debertav3_finetuned_banking_transaction_classification_text_only_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|589.6 MB|
+
+## References
+
+https://huggingface.co/wanadzhar913/debertav3-finetuned-banking-transaction-classification-text-only
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-desired_model_name_en.md b/docs/_posts/ahmedlone127/2025-01-23-desired_model_name_en.md
new file mode 100644
index 00000000000000..9548f1a6fb6c2c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-desired_model_name_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English desired_model_name DistilBertForSequenceClassification from YuChern
+author: John Snow Labs
+name: desired_model_name
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`desired_model_name` is a English model originally trained by YuChern.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/desired_model_name_en_5.5.1_3.0_1737650567747.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/desired_model_name_en_5.5.1_3.0_1737650567747.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("desired_model_name","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("desired_model_name", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|desired_model_name|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/YuChern/desired-model-name
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-desired_model_name_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-desired_model_name_pipeline_en.md
new file mode 100644
index 00000000000000..ffb186bf45a198
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-desired_model_name_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English desired_model_name_pipeline pipeline DistilBertForSequenceClassification from YuChern
+author: John Snow Labs
+name: desired_model_name_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`desired_model_name_pipeline` is a English model originally trained by YuChern.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/desired_model_name_pipeline_en_5.5.1_3.0_1737650582755.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/desired_model_name_pipeline_en_5.5.1_3.0_1737650582755.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("desired_model_name_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("desired_model_name_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|desired_model_name_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/YuChern/desired-model-name
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-disease_ner_cat_v0_ca.md b/docs/_posts/ahmedlone127/2025-01-23-disease_ner_cat_v0_ca.md
new file mode 100644
index 00000000000000..6084f187c2dafa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-disease_ner_cat_v0_ca.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Catalan, Valencian disease_ner_cat_v0 RoBertaForTokenClassification from BSC-NLP4BIA
+author: John Snow Labs
+name: disease_ner_cat_v0
+date: 2025-01-23
+tags: [ca, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: ca
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`disease_ner_cat_v0` is a Catalan, Valencian model originally trained by BSC-NLP4BIA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/disease_ner_cat_v0_ca_5.5.1_3.0_1737666507934.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/disease_ner_cat_v0_ca_5.5.1_3.0_1737666507934.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("disease_ner_cat_v0","ca") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("disease_ner_cat_v0", "ca")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|disease_ner_cat_v0|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|ca|
+|Size:|436.1 MB|
+
+## References
+
+https://huggingface.co/BSC-NLP4BIA/disease-ner-cat-v0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-disease_ner_cat_v0_pipeline_ca.md b/docs/_posts/ahmedlone127/2025-01-23-disease_ner_cat_v0_pipeline_ca.md
new file mode 100644
index 00000000000000..15f934608ac691
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-disease_ner_cat_v0_pipeline_ca.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Catalan, Valencian disease_ner_cat_v0_pipeline pipeline RoBertaForTokenClassification from BSC-NLP4BIA
+author: John Snow Labs
+name: disease_ner_cat_v0_pipeline
+date: 2025-01-23
+tags: [ca, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: ca
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`disease_ner_cat_v0_pipeline` is a Catalan, Valencian model originally trained by BSC-NLP4BIA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/disease_ner_cat_v0_pipeline_ca_5.5.1_3.0_1737666532337.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/disease_ner_cat_v0_pipeline_ca_5.5.1_3.0_1737666532337.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("disease_ner_cat_v0_pipeline", lang = "ca")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("disease_ner_cat_v0_pipeline", lang = "ca")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|disease_ner_cat_v0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ca|
+|Size:|436.1 MB|
+
+## References
+
+https://huggingface.co/BSC-NLP4BIA/disease-ner-cat-v0
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbart_mnli_12_1_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbart_mnli_12_1_en.md
new file mode 100644
index 00000000000000..f5546b23e3eeb1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbart_mnli_12_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbart_mnli_12_1 BartForZeroShotClassification from valhalla
+author: John Snow Labs
+name: distilbart_mnli_12_1
+date: 2025-01-23
+tags: [en, open_source, onnx, zero_shot, bart]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BartForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbart_mnli_12_1` is a English model originally trained by valhalla.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbart_mnli_12_1_en_5.5.1_3.0_1737640049860.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbart_mnli_12_1_en_5.5.1_3.0_1737640049860.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+zeroShotClassifier  = BartForZeroShotClassification.pretrained("distilbart_mnli_12_1","en") \
+     .setInputCols(["document","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, zeroShotClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val zeroShotClassifier  = BartForZeroShotClassification.pretrained("distilbart_mnli_12_1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, zeroShotClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbart_mnli_12_1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|558.4 MB|
+
+## References
+
+https://huggingface.co/valhalla/distilbart-mnli-12-1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbart_mnli_12_1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbart_mnli_12_1_pipeline_en.md
new file mode 100644
index 00000000000000..66f2302d53c438
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbart_mnli_12_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbart_mnli_12_1_pipeline pipeline BartForZeroShotClassification from valhalla
+author: John Snow Labs
+name: distilbart_mnli_12_1_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbart_mnli_12_1_pipeline` is a English model originally trained by valhalla.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbart_mnli_12_1_pipeline_en_5.5.1_3.0_1737640203885.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbart_mnli_12_1_pipeline_en_5.5.1_3.0_1737640203885.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbart_mnli_12_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbart_mnli_12_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbart_mnli_12_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|558.4 MB|
+
+## References
+
+https://huggingface.co/valhalla/distilbart-mnli-12-1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BartForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbart_mnli_12_3_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbart_mnli_12_3_en.md
new file mode 100644
index 00000000000000..c5c79557372545
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbart_mnli_12_3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbart_mnli_12_3 BartForZeroShotClassification from valhalla
+author: John Snow Labs
+name: distilbart_mnli_12_3
+date: 2025-01-23
+tags: [en, open_source, onnx, zero_shot, bart]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BartForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbart_mnli_12_3` is a English model originally trained by valhalla.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbart_mnli_12_3_en_5.5.1_3.0_1737639238108.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbart_mnli_12_3_en_5.5.1_3.0_1737639238108.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+zeroShotClassifier  = BartForZeroShotClassification.pretrained("distilbart_mnli_12_3","en") \
+     .setInputCols(["document","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, zeroShotClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val zeroShotClassifier  = BartForZeroShotClassification.pretrained("distilbart_mnli_12_3", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, zeroShotClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbart_mnli_12_3|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|684.2 MB|
+
+## References
+
+https://huggingface.co/valhalla/distilbart-mnli-12-3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbart_mnli_12_3_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbart_mnli_12_3_pipeline_en.md
new file mode 100644
index 00000000000000..0880a08c143191
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbart_mnli_12_3_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbart_mnli_12_3_pipeline pipeline BartForZeroShotClassification from valhalla
+author: John Snow Labs
+name: distilbart_mnli_12_3_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbart_mnli_12_3_pipeline` is a English model originally trained by valhalla.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbart_mnli_12_3_pipeline_en_5.5.1_3.0_1737639395012.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbart_mnli_12_3_pipeline_en_5.5.1_3.0_1737639395012.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbart_mnli_12_3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbart_mnli_12_3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbart_mnli_12_3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|684.3 MB|
+
+## References
+
+https://huggingface.co/valhalla/distilbart-mnli-12-3
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BartForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbart_mnli_12_6_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbart_mnli_12_6_en.md
new file mode 100644
index 00000000000000..ea2d0a118f17c0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbart_mnli_12_6_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbart_mnli_12_6 BartForZeroShotClassification from valhalla
+author: John Snow Labs
+name: distilbart_mnli_12_6
+date: 2025-01-23
+tags: [en, open_source, onnx, zero_shot, bart]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BartForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbart_mnli_12_6` is a English model originally trained by valhalla.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbart_mnli_12_6_en_5.5.1_3.0_1737640265067.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbart_mnli_12_6_en_5.5.1_3.0_1737640265067.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+zeroShotClassifier  = BartForZeroShotClassification.pretrained("distilbart_mnli_12_6","en") \
+     .setInputCols(["document","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, zeroShotClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val zeroShotClassifier  = BartForZeroShotClassification.pretrained("distilbart_mnli_12_6", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, zeroShotClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbart_mnli_12_6|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|873.0 MB|
+
+## References
+
+https://huggingface.co/valhalla/distilbart-mnli-12-6
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbart_mnli_12_6_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbart_mnli_12_6_pipeline_en.md
new file mode 100644
index 00000000000000..9ae09cedee4839
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbart_mnli_12_6_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbart_mnli_12_6_pipeline pipeline BartForZeroShotClassification from valhalla
+author: John Snow Labs
+name: distilbart_mnli_12_6_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbart_mnli_12_6_pipeline` is a English model originally trained by valhalla.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbart_mnli_12_6_pipeline_en_5.5.1_3.0_1737640427427.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbart_mnli_12_6_pipeline_en_5.5.1_3.0_1737640427427.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbart_mnli_12_6_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbart_mnli_12_6_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbart_mnli_12_6_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|873.0 MB|
+
+## References
+
+https://huggingface.co/valhalla/distilbart-mnli-12-6
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BartForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbart_mnli_12_9_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbart_mnli_12_9_en.md
new file mode 100644
index 00000000000000..d8042f377db131
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbart_mnli_12_9_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbart_mnli_12_9 BartForZeroShotClassification from valhalla
+author: John Snow Labs
+name: distilbart_mnli_12_9
+date: 2025-01-23
+tags: [en, open_source, onnx, zero_shot, bart]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BartForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbart_mnli_12_9` is a English model originally trained by valhalla.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbart_mnli_12_9_en_5.5.1_3.0_1737639304808.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbart_mnli_12_9_en_5.5.1_3.0_1737639304808.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+zeroShotClassifier  = BartForZeroShotClassification.pretrained("distilbart_mnli_12_9","en") \
+     .setInputCols(["document","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, zeroShotClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val zeroShotClassifier  = BartForZeroShotClassification.pretrained("distilbart_mnli_12_9", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, zeroShotClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbart_mnli_12_9|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/valhalla/distilbart-mnli-12-9
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbart_mnli_12_9_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbart_mnli_12_9_pipeline_en.md
new file mode 100644
index 00000000000000..877ef5505789d5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbart_mnli_12_9_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbart_mnli_12_9_pipeline pipeline BartForZeroShotClassification from valhalla
+author: John Snow Labs
+name: distilbart_mnli_12_9_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbart_mnli_12_9_pipeline` is a English model originally trained by valhalla.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbart_mnli_12_9_pipeline_en_5.5.1_3.0_1737639482798.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbart_mnli_12_9_pipeline_en_5.5.1_3.0_1737639482798.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbart_mnli_12_9_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbart_mnli_12_9_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbart_mnli_12_9_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/valhalla/distilbart-mnli-12-9
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BartForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbart_mnli_cnn_news_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbart_mnli_cnn_news_en.md
new file mode 100644
index 00000000000000..994cad724e7862
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbart_mnli_cnn_news_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbart_mnli_cnn_news BartForZeroShotClassification from AyoubChLin
+author: John Snow Labs
+name: distilbart_mnli_cnn_news
+date: 2025-01-23
+tags: [en, open_source, onnx, zero_shot, bart]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BartForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbart_mnli_cnn_news` is a English model originally trained by AyoubChLin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbart_mnli_cnn_news_en_5.5.1_3.0_1737639658842.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbart_mnli_cnn_news_en_5.5.1_3.0_1737639658842.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+zeroShotClassifier  = BartForZeroShotClassification.pretrained("distilbart_mnli_cnn_news","en") \
+     .setInputCols(["document","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, zeroShotClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val zeroShotClassifier  = BartForZeroShotClassification.pretrained("distilbart_mnli_cnn_news", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, zeroShotClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbart_mnli_cnn_news|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/AyoubChLin/distilBART-mnli-cnn_news
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbart_mnli_cnn_news_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbart_mnli_cnn_news_pipeline_en.md
new file mode 100644
index 00000000000000..3db610d4e8dca0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbart_mnli_cnn_news_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbart_mnli_cnn_news_pipeline pipeline BartForZeroShotClassification from AyoubChLin
+author: John Snow Labs
+name: distilbart_mnli_cnn_news_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbart_mnli_cnn_news_pipeline` is a English model originally trained by AyoubChLin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbart_mnli_cnn_news_pipeline_en_5.5.1_3.0_1737639726413.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbart_mnli_cnn_news_pipeline_en_5.5.1_3.0_1737639726413.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbart_mnli_cnn_news_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbart_mnli_cnn_news_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbart_mnli_cnn_news_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/AyoubChLin/distilBART-mnli-cnn_news
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BartForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_multilingual_cased_finetuned_imdb_v1_pipeline_xx.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_multilingual_cased_finetuned_imdb_v1_pipeline_xx.md
new file mode 100644
index 00000000000000..ba12c5d5c6d29b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_multilingual_cased_finetuned_imdb_v1_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual distilbert_base_multilingual_cased_finetuned_imdb_v1_pipeline pipeline DistilBertEmbeddings from marcelovidigal
+author: John Snow Labs
+name: distilbert_base_multilingual_cased_finetuned_imdb_v1_pipeline
+date: 2025-01-23
+tags: [xx, open_source, pipeline, onnx]
+task: Embeddings
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_multilingual_cased_finetuned_imdb_v1_pipeline` is a Multilingual model originally trained by marcelovidigal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_multilingual_cased_finetuned_imdb_v1_pipeline_xx_5.5.1_3.0_1737662788250.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_multilingual_cased_finetuned_imdb_v1_pipeline_xx_5.5.1_3.0_1737662788250.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_multilingual_cased_finetuned_imdb_v1_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_multilingual_cased_finetuned_imdb_v1_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_multilingual_cased_finetuned_imdb_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|505.4 MB|
+
+## References
+
+https://huggingface.co/marcelovidigal/distilbert-base-multilingual-cased-finetuned-imdb-v1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_multilingual_cased_finetuned_imdb_v1_xx.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_multilingual_cased_finetuned_imdb_v1_xx.md
new file mode 100644
index 00000000000000..b66e22da24ec0e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_multilingual_cased_finetuned_imdb_v1_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual distilbert_base_multilingual_cased_finetuned_imdb_v1 DistilBertEmbeddings from marcelovidigal
+author: John Snow Labs
+name: distilbert_base_multilingual_cased_finetuned_imdb_v1
+date: 2025-01-23
+tags: [xx, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_multilingual_cased_finetuned_imdb_v1` is a Multilingual model originally trained by marcelovidigal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_multilingual_cased_finetuned_imdb_v1_xx_5.5.1_3.0_1737662759658.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_multilingual_cased_finetuned_imdb_v1_xx_5.5.1_3.0_1737662759658.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_multilingual_cased_finetuned_imdb_v1","xx") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_multilingual_cased_finetuned_imdb_v1","xx") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_multilingual_cased_finetuned_imdb_v1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|xx|
+|Size:|505.4 MB|
+
+## References
+
+https://huggingface.co/marcelovidigal/distilbert-base-multilingual-cased-finetuned-imdb-v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_multilingual_cased_finetuned_imdb_v2_pipeline_xx.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_multilingual_cased_finetuned_imdb_v2_pipeline_xx.md
new file mode 100644
index 00000000000000..347af5e346ed60
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_multilingual_cased_finetuned_imdb_v2_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual distilbert_base_multilingual_cased_finetuned_imdb_v2_pipeline pipeline DistilBertEmbeddings from marcelovidigal
+author: John Snow Labs
+name: distilbert_base_multilingual_cased_finetuned_imdb_v2_pipeline
+date: 2025-01-23
+tags: [xx, open_source, pipeline, onnx]
+task: Embeddings
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_multilingual_cased_finetuned_imdb_v2_pipeline` is a Multilingual model originally trained by marcelovidigal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_multilingual_cased_finetuned_imdb_v2_pipeline_xx_5.5.1_3.0_1737663453068.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_multilingual_cased_finetuned_imdb_v2_pipeline_xx_5.5.1_3.0_1737663453068.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_multilingual_cased_finetuned_imdb_v2_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_multilingual_cased_finetuned_imdb_v2_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_multilingual_cased_finetuned_imdb_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|505.4 MB|
+
+## References
+
+https://huggingface.co/marcelovidigal/distilbert-base-multilingual-cased-finetuned-imdb-v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_multilingual_cased_finetuned_imdb_v2_xx.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_multilingual_cased_finetuned_imdb_v2_xx.md
new file mode 100644
index 00000000000000..f901b487f632f8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_multilingual_cased_finetuned_imdb_v2_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual distilbert_base_multilingual_cased_finetuned_imdb_v2 DistilBertEmbeddings from marcelovidigal
+author: John Snow Labs
+name: distilbert_base_multilingual_cased_finetuned_imdb_v2
+date: 2025-01-23
+tags: [xx, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_multilingual_cased_finetuned_imdb_v2` is a Multilingual model originally trained by marcelovidigal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_multilingual_cased_finetuned_imdb_v2_xx_5.5.1_3.0_1737663419340.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_multilingual_cased_finetuned_imdb_v2_xx_5.5.1_3.0_1737663419340.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_multilingual_cased_finetuned_imdb_v2","xx") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_multilingual_cased_finetuned_imdb_v2","xx") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_multilingual_cased_finetuned_imdb_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|xx|
+|Size:|505.4 MB|
+
+## References
+
+https://huggingface.co/marcelovidigal/distilbert-base-multilingual-cased-finetuned-imdb-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_3epoch6_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_3epoch6_en.md
new file mode 100644
index 00000000000000..9ea43bc2af170a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_3epoch6_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_3epoch6 DistilBertForSequenceClassification from dianamihalache27
+author: John Snow Labs
+name: distilbert_base_uncased_3epoch6
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_3epoch6` is a English model originally trained by dianamihalache27.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_3epoch6_en_5.5.1_3.0_1737650916343.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_3epoch6_en_5.5.1_3.0_1737650916343.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_3epoch6","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_3epoch6", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_3epoch6|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/dianamihalache27/distilbert-base-uncased_3epoch6
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_3epoch6_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_3epoch6_pipeline_en.md
new file mode 100644
index 00000000000000..41334bb414cff9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_3epoch6_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_3epoch6_pipeline pipeline DistilBertForSequenceClassification from dianamihalache27
+author: John Snow Labs
+name: distilbert_base_uncased_3epoch6_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_3epoch6_pipeline` is a English model originally trained by dianamihalache27.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_3epoch6_pipeline_en_5.5.1_3.0_1737650930540.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_3epoch6_pipeline_en_5.5.1_3.0_1737650930540.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_3epoch6_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_3epoch6_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_3epoch6_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/dianamihalache27/distilbert-base-uncased_3epoch6
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_distilled_clinc_feng_2052_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_distilled_clinc_feng_2052_en.md
new file mode 100644
index 00000000000000..acbdf325c49ae7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_distilled_clinc_feng_2052_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_distilled_clinc_feng_2052 DistilBertForSequenceClassification from feng-2052
+author: John Snow Labs
+name: distilbert_base_uncased_distilled_clinc_feng_2052
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_distilled_clinc_feng_2052` is a English model originally trained by feng-2052.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_distilled_clinc_feng_2052_en_5.5.1_3.0_1737650790571.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_distilled_clinc_feng_2052_en_5.5.1_3.0_1737650790571.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_distilled_clinc_feng_2052","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_distilled_clinc_feng_2052", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_distilled_clinc_feng_2052|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.9 MB|
+
+## References
+
+https://huggingface.co/feng-2052/distilbert-base-uncased-distilled-clinc
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_distilled_clinc_feng_2052_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_distilled_clinc_feng_2052_pipeline_en.md
new file mode 100644
index 00000000000000..f23bafb70766a5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_distilled_clinc_feng_2052_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_distilled_clinc_feng_2052_pipeline pipeline DistilBertForSequenceClassification from feng-2052
+author: John Snow Labs
+name: distilbert_base_uncased_distilled_clinc_feng_2052_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_distilled_clinc_feng_2052_pipeline` is a English model originally trained by feng-2052.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_distilled_clinc_feng_2052_pipeline_en_5.5.1_3.0_1737650804309.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_distilled_clinc_feng_2052_pipeline_en_5.5.1_3.0_1737650804309.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_distilled_clinc_feng_2052_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_distilled_clinc_feng_2052_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_distilled_clinc_feng_2052_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.9 MB|
+
+## References
+
+https://huggingface.co/feng-2052/distilbert-base-uncased-distilled-clinc
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_ag_news_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_ag_news_en.md
new file mode 100644
index 00000000000000..2d5b185f6fe773
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_ag_news_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ag_news DistilBertEmbeddings from miggwp
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ag_news
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ag_news` is a English model originally trained by miggwp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ag_news_en_5.5.1_3.0_1737662859354.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ag_news_en_5.5.1_3.0_1737662859354.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_ag_news","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_ag_news","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ag_news|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/miggwp/distilbert-base-uncased-finetuned-ag-news
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_ag_news_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_ag_news_pipeline_en.md
new file mode 100644
index 00000000000000..199b48516a7a70
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_ag_news_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ag_news_pipeline pipeline DistilBertEmbeddings from miggwp
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ag_news_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ag_news_pipeline` is a English model originally trained by miggwp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ag_news_pipeline_en_5.5.1_3.0_1737662874816.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ag_news_pipeline_en_5.5.1_3.0_1737662874816.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_ag_news_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_ag_news_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ag_news_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/miggwp/distilbert-base-uncased-finetuned-ag-news
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_bible_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_bible_en.md
new file mode 100644
index 00000000000000..50e3598b9a3bff
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_bible_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_bible DistilBertEmbeddings from Pragash-Mohanarajah
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_bible
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_bible` is a English model originally trained by Pragash-Mohanarajah.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_bible_en_5.5.1_3.0_1737663014282.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_bible_en_5.5.1_3.0_1737663014282.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_bible","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_bible","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_bible|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Pragash-Mohanarajah/distilbert-base-uncased-finetuned-bible
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_bible_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_bible_pipeline_en.md
new file mode 100644
index 00000000000000..a8819c5ff02599
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_bible_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_bible_pipeline pipeline DistilBertEmbeddings from Pragash-Mohanarajah
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_bible_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_bible_pipeline` is a English model originally trained by Pragash-Mohanarajah.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_bible_pipeline_en_5.5.1_3.0_1737663028132.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_bible_pipeline_en_5.5.1_3.0_1737663028132.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_bible_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_bible_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_bible_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Pragash-Mohanarajah/distilbert-base-uncased-finetuned-bible
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_cola_fatekn_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_cola_fatekn_en.md
new file mode 100644
index 00000000000000..90f38ce9225519
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_cola_fatekn_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_cola_fatekn DistilBertForSequenceClassification from fatekn
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_cola_fatekn
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_cola_fatekn` is a English model originally trained by fatekn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_cola_fatekn_en_5.5.1_3.0_1737650416146.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_cola_fatekn_en_5.5.1_3.0_1737650416146.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_cola_fatekn","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_cola_fatekn", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_cola_fatekn|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/fatekn/distilbert-base-uncased-finetuned-cola
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_cola_fatekn_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_cola_fatekn_pipeline_en.md
new file mode 100644
index 00000000000000..eb308e088143da
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_cola_fatekn_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_cola_fatekn_pipeline pipeline DistilBertForSequenceClassification from fatekn
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_cola_fatekn_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_cola_fatekn_pipeline` is a English model originally trained by fatekn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_cola_fatekn_pipeline_en_5.5.1_3.0_1737650433624.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_cola_fatekn_pipeline_en_5.5.1_3.0_1737650433624.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_cola_fatekn_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_cola_fatekn_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_cola_fatekn_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/fatekn/distilbert-base-uncased-finetuned-cola
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_emotion_ankesaccount_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_emotion_ankesaccount_en.md
new file mode 100644
index 00000000000000..38f279a6b0ce34
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_emotion_ankesaccount_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_ankesaccount DistilBertForSequenceClassification from AnkesAccount
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_ankesaccount
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_ankesaccount` is a English model originally trained by AnkesAccount.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_ankesaccount_en_5.5.1_3.0_1737650275673.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_ankesaccount_en_5.5.1_3.0_1737650275673.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_ankesaccount","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_ankesaccount", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_ankesaccount|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/AnkesAccount/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_emotion_ankesaccount_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_emotion_ankesaccount_pipeline_en.md
new file mode 100644
index 00000000000000..70cca6efa1c1e5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_emotion_ankesaccount_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_ankesaccount_pipeline pipeline DistilBertForSequenceClassification from AnkesAccount
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_ankesaccount_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_ankesaccount_pipeline` is a English model originally trained by AnkesAccount.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_ankesaccount_pipeline_en_5.5.1_3.0_1737650291066.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_ankesaccount_pipeline_en_5.5.1_3.0_1737650291066.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_ankesaccount_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_ankesaccount_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_ankesaccount_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/AnkesAccount/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_akari000_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_akari000_en.md
new file mode 100644
index 00000000000000..806a0c46d9f380
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_akari000_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_akari000 DistilBertEmbeddings from akari000
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_akari000
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_akari000` is a English model originally trained by akari000.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_akari000_en_5.5.1_3.0_1737662986039.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_akari000_en_5.5.1_3.0_1737662986039.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_akari000","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_akari000","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_akari000|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/akari000/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_akari000_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_akari000_pipeline_en.md
new file mode 100644
index 00000000000000..5d9f95165fff51
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_akari000_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_akari000_pipeline pipeline DistilBertEmbeddings from akari000
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_akari000_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_akari000_pipeline` is a English model originally trained by akari000.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_akari000_pipeline_en_5.5.1_3.0_1737663004096.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_akari000_pipeline_en_5.5.1_3.0_1737663004096.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_akari000_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_akari000_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_akari000_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/akari000/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_aniruddh10124_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_aniruddh10124_en.md
new file mode 100644
index 00000000000000..b834e57c1e133e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_aniruddh10124_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_aniruddh10124 DistilBertEmbeddings from aniruddh10124
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_aniruddh10124
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_aniruddh10124` is a English model originally trained by aniruddh10124.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_aniruddh10124_en_5.5.1_3.0_1737663391934.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_aniruddh10124_en_5.5.1_3.0_1737663391934.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_aniruddh10124","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_aniruddh10124","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_aniruddh10124|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/aniruddh10124/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_aniruddh10124_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_aniruddh10124_pipeline_en.md
new file mode 100644
index 00000000000000..df64277e6aa541
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_aniruddh10124_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_aniruddh10124_pipeline pipeline DistilBertEmbeddings from aniruddh10124
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_aniruddh10124_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_aniruddh10124_pipeline` is a English model originally trained by aniruddh10124.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_aniruddh10124_pipeline_en_5.5.1_3.0_1737663406483.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_aniruddh10124_pipeline_en_5.5.1_3.0_1737663406483.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_aniruddh10124_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_aniruddh10124_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_aniruddh10124_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/aniruddh10124/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_dimichw_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_dimichw_en.md
new file mode 100644
index 00000000000000..99af9f455ab26b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_dimichw_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_dimichw DistilBertEmbeddings from DimichW
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_dimichw
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_dimichw` is a English model originally trained by DimichW.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_dimichw_en_5.5.1_3.0_1737662969575.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_dimichw_en_5.5.1_3.0_1737662969575.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_dimichw","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_dimichw","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_dimichw|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/DimichW/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_dimichw_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_dimichw_pipeline_en.md
new file mode 100644
index 00000000000000..ca4b0834e27926
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_dimichw_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_dimichw_pipeline pipeline DistilBertEmbeddings from DimichW
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_dimichw_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_dimichw_pipeline` is a English model originally trained by DimichW.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_dimichw_pipeline_en_5.5.1_3.0_1737662983880.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_dimichw_pipeline_en_5.5.1_3.0_1737662983880.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_dimichw_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_dimichw_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_dimichw_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/DimichW/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_dxy127_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_dxy127_en.md
new file mode 100644
index 00000000000000..2003895fdcbcf4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_dxy127_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_dxy127 DistilBertEmbeddings from dxy127
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_dxy127
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_dxy127` is a English model originally trained by dxy127.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_dxy127_en_5.5.1_3.0_1737663405405.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_dxy127_en_5.5.1_3.0_1737663405405.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_dxy127","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_dxy127","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_dxy127|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/dxy127/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_dxy127_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_dxy127_pipeline_en.md
new file mode 100644
index 00000000000000..39b142b564c98f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_dxy127_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_dxy127_pipeline pipeline DistilBertEmbeddings from dxy127
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_dxy127_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_dxy127_pipeline` is a English model originally trained by dxy127.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_dxy127_pipeline_en_5.5.1_3.0_1737663420453.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_dxy127_pipeline_en_5.5.1_3.0_1737663420453.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_dxy127_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_dxy127_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_dxy127_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/dxy127/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_fhzh123_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_fhzh123_en.md
new file mode 100644
index 00000000000000..52f2cc79f161d3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_fhzh123_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_fhzh123 DistilBertEmbeddings from fhzh123
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_fhzh123
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_fhzh123` is a English model originally trained by fhzh123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_fhzh123_en_5.5.1_3.0_1737662718453.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_fhzh123_en_5.5.1_3.0_1737662718453.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_fhzh123","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_fhzh123","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_fhzh123|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/fhzh123/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_fhzh123_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_fhzh123_pipeline_en.md
new file mode 100644
index 00000000000000..778e99e025eec6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_fhzh123_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_fhzh123_pipeline pipeline DistilBertEmbeddings from fhzh123
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_fhzh123_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_fhzh123_pipeline` is a English model originally trained by fhzh123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_fhzh123_pipeline_en_5.5.1_3.0_1737662739035.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_fhzh123_pipeline_en_5.5.1_3.0_1737662739035.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_fhzh123_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_fhzh123_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_fhzh123_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/fhzh123/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_kclee111_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_kclee111_en.md
new file mode 100644
index 00000000000000..5a394efa8c2c63
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_kclee111_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_kclee111 DistilBertEmbeddings from kclee111
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_kclee111
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_kclee111` is a English model originally trained by kclee111.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_kclee111_en_5.5.1_3.0_1737663517165.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_kclee111_en_5.5.1_3.0_1737663517165.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_kclee111","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_kclee111","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_kclee111|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/kclee111/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_kclee111_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_kclee111_pipeline_en.md
new file mode 100644
index 00000000000000..5fe4119dddc6ef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_kclee111_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_kclee111_pipeline pipeline DistilBertEmbeddings from kclee111
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_kclee111_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_kclee111_pipeline` is a English model originally trained by kclee111.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_kclee111_pipeline_en_5.5.1_3.0_1737663531079.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_kclee111_pipeline_en_5.5.1_3.0_1737663531079.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_kclee111_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_kclee111_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_kclee111_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/kclee111/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_knoam_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_knoam_en.md
new file mode 100644
index 00000000000000..c97f68403aed8e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_knoam_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_knoam DistilBertEmbeddings from knoam
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_knoam
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_knoam` is a English model originally trained by knoam.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_knoam_en_5.5.1_3.0_1737663364477.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_knoam_en_5.5.1_3.0_1737663364477.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_knoam","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_knoam","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_knoam|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/knoam/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_knoam_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_knoam_pipeline_en.md
new file mode 100644
index 00000000000000..679a833fb6296d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_knoam_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_knoam_pipeline pipeline DistilBertEmbeddings from knoam
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_knoam_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_knoam_pipeline` is a English model originally trained by knoam.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_knoam_pipeline_en_5.5.1_3.0_1737663378851.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_knoam_pipeline_en_5.5.1_3.0_1737663378851.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_knoam_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_knoam_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_knoam_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/knoam/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_kunleo_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_kunleo_en.md
new file mode 100644
index 00000000000000..81248ab3a1d872
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_kunleo_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_kunleo DistilBertEmbeddings from KunleO
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_kunleo
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_kunleo` is a English model originally trained by KunleO.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_kunleo_en_5.5.1_3.0_1737662852031.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_kunleo_en_5.5.1_3.0_1737662852031.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_kunleo","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_kunleo","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_kunleo|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/KunleO/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_kunleo_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_kunleo_pipeline_en.md
new file mode 100644
index 00000000000000..7fecf2f3e71fe1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_kunleo_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_kunleo_pipeline pipeline DistilBertEmbeddings from KunleO
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_kunleo_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_kunleo_pipeline` is a English model originally trained by KunleO.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_kunleo_pipeline_en_5.5.1_3.0_1737662866501.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_kunleo_pipeline_en_5.5.1_3.0_1737662866501.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_kunleo_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_kunleo_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_kunleo_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/KunleO/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_lcccluck_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_lcccluck_en.md
new file mode 100644
index 00000000000000..8c3c920d797aa5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_lcccluck_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_lcccluck DistilBertEmbeddings from lcccluck
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_lcccluck
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_lcccluck` is a English model originally trained by lcccluck.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_lcccluck_en_5.5.1_3.0_1737663115807.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_lcccluck_en_5.5.1_3.0_1737663115807.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_lcccluck","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_lcccluck","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_lcccluck|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/lcccluck/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_lcccluck_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_lcccluck_pipeline_en.md
new file mode 100644
index 00000000000000..0b6c23702764f6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_lcccluck_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_lcccluck_pipeline pipeline DistilBertEmbeddings from lcccluck
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_lcccluck_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_lcccluck_pipeline` is a English model originally trained by lcccluck.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_lcccluck_pipeline_en_5.5.1_3.0_1737663130253.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_lcccluck_pipeline_en_5.5.1_3.0_1737663130253.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_lcccluck_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_lcccluck_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_lcccluck_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/lcccluck/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_linmatrix_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_linmatrix_en.md
new file mode 100644
index 00000000000000..5a1867aea4e079
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_linmatrix_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_linmatrix DistilBertEmbeddings from linmatrix
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_linmatrix
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_linmatrix` is a English model originally trained by linmatrix.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_linmatrix_en_5.5.1_3.0_1737663251736.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_linmatrix_en_5.5.1_3.0_1737663251736.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_linmatrix","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_linmatrix","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_linmatrix|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/linmatrix/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_linmatrix_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_linmatrix_pipeline_en.md
new file mode 100644
index 00000000000000..a743d4fe34827b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_linmatrix_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_linmatrix_pipeline pipeline DistilBertEmbeddings from linmatrix
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_linmatrix_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_linmatrix_pipeline` is a English model originally trained by linmatrix.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_linmatrix_pipeline_en_5.5.1_3.0_1737663268401.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_linmatrix_pipeline_en_5.5.1_3.0_1737663268401.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_linmatrix_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_linmatrix_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_linmatrix_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/linmatrix/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_maxugoodboy_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_maxugoodboy_en.md
new file mode 100644
index 00000000000000..019c5e04cda76c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_maxugoodboy_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_maxugoodboy DistilBertEmbeddings from Maxugoodboy
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_maxugoodboy
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_maxugoodboy` is a English model originally trained by Maxugoodboy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_maxugoodboy_en_5.5.1_3.0_1737663092807.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_maxugoodboy_en_5.5.1_3.0_1737663092807.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_maxugoodboy","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_maxugoodboy","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_maxugoodboy|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Maxugoodboy/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_maxugoodboy_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_maxugoodboy_pipeline_en.md
new file mode 100644
index 00000000000000..c064fa4fe9a3fb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_maxugoodboy_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_maxugoodboy_pipeline pipeline DistilBertEmbeddings from Maxugoodboy
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_maxugoodboy_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_maxugoodboy_pipeline` is a English model originally trained by Maxugoodboy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_maxugoodboy_pipeline_en_5.5.1_3.0_1737663107000.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_maxugoodboy_pipeline_en_5.5.1_3.0_1737663107000.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_maxugoodboy_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_maxugoodboy_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_maxugoodboy_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Maxugoodboy/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_mehwishalam_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_mehwishalam_en.md
new file mode 100644
index 00000000000000..cf7b19ea9eeac9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_mehwishalam_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_mehwishalam DistilBertEmbeddings from mehwishalam
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_mehwishalam
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_mehwishalam` is a English model originally trained by mehwishalam.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_mehwishalam_en_5.5.1_3.0_1737663161507.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_mehwishalam_en_5.5.1_3.0_1737663161507.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_mehwishalam","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_mehwishalam","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_mehwishalam|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/mehwishalam/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_mehwishalam_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_mehwishalam_pipeline_en.md
new file mode 100644
index 00000000000000..d5b45f56eec547
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_mehwishalam_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_mehwishalam_pipeline pipeline DistilBertEmbeddings from mehwishalam
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_mehwishalam_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_mehwishalam_pipeline` is a English model originally trained by mehwishalam.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_mehwishalam_pipeline_en_5.5.1_3.0_1737663175752.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_mehwishalam_pipeline_en_5.5.1_3.0_1737663175752.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_mehwishalam_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_mehwishalam_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_mehwishalam_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/mehwishalam/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_mrcolley_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_mrcolley_en.md
new file mode 100644
index 00000000000000..df5e2fe337c08f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_mrcolley_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_mrcolley DistilBertEmbeddings from mrcolley
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_mrcolley
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_mrcolley` is a English model originally trained by mrcolley.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_mrcolley_en_5.5.1_3.0_1737662888787.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_mrcolley_en_5.5.1_3.0_1737662888787.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_mrcolley","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_mrcolley","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_mrcolley|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/mrcolley/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_mrcolley_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_mrcolley_pipeline_en.md
new file mode 100644
index 00000000000000..4fea85555be1ea
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_mrcolley_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_mrcolley_pipeline pipeline DistilBertEmbeddings from mrcolley
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_mrcolley_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_mrcolley_pipeline` is a English model originally trained by mrcolley.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_mrcolley_pipeline_en_5.5.1_3.0_1737662906703.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_mrcolley_pipeline_en_5.5.1_3.0_1737662906703.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_mrcolley_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_mrcolley_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_mrcolley_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/mrcolley/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_rajabilalnazir_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_rajabilalnazir_en.md
new file mode 100644
index 00000000000000..093cbe63d7c584
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_rajabilalnazir_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_rajabilalnazir DistilBertEmbeddings from rajabilalnazir
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_rajabilalnazir
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_rajabilalnazir` is a English model originally trained by rajabilalnazir.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_rajabilalnazir_en_5.5.1_3.0_1737663532122.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_rajabilalnazir_en_5.5.1_3.0_1737663532122.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_rajabilalnazir","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_rajabilalnazir","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_rajabilalnazir|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/rajabilalnazir/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_rajabilalnazir_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_rajabilalnazir_pipeline_en.md
new file mode 100644
index 00000000000000..db4c3ab9bb5133
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_rajabilalnazir_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_rajabilalnazir_pipeline pipeline DistilBertEmbeddings from rajabilalnazir
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_rajabilalnazir_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_rajabilalnazir_pipeline` is a English model originally trained by rajabilalnazir.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_rajabilalnazir_pipeline_en_5.5.1_3.0_1737663548278.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_rajabilalnazir_pipeline_en_5.5.1_3.0_1737663548278.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_rajabilalnazir_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_rajabilalnazir_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_rajabilalnazir_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/rajabilalnazir/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_real_jiakai_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_real_jiakai_en.md
new file mode 100644
index 00000000000000..714ae6e9f28cdb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_real_jiakai_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_real_jiakai DistilBertEmbeddings from real-jiakai
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_real_jiakai
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_real_jiakai` is a English model originally trained by real-jiakai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_real_jiakai_en_5.5.1_3.0_1737662885913.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_real_jiakai_en_5.5.1_3.0_1737662885913.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_real_jiakai","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_real_jiakai","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_real_jiakai|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/real-jiakai/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_real_jiakai_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_real_jiakai_pipeline_en.md
new file mode 100644
index 00000000000000..33f6d220f36657
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_real_jiakai_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_real_jiakai_pipeline pipeline DistilBertEmbeddings from real-jiakai
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_real_jiakai_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_real_jiakai_pipeline` is a English model originally trained by real-jiakai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_real_jiakai_pipeline_en_5.5.1_3.0_1737662901898.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_real_jiakai_pipeline_en_5.5.1_3.0_1737662901898.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_real_jiakai_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_real_jiakai_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_real_jiakai_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/real-jiakai/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_rizstwn_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_rizstwn_en.md
new file mode 100644
index 00000000000000..b45ba5142c3592
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_rizstwn_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_rizstwn DistilBertEmbeddings from rizstwn
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_rizstwn
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_rizstwn` is a English model originally trained by rizstwn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_rizstwn_en_5.5.1_3.0_1737663575324.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_rizstwn_en_5.5.1_3.0_1737663575324.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_rizstwn","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_rizstwn","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_rizstwn|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/rizstwn/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_rizstwn_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_rizstwn_pipeline_en.md
new file mode 100644
index 00000000000000..88efa39329b9c2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_rizstwn_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_rizstwn_pipeline pipeline DistilBertEmbeddings from rizstwn
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_rizstwn_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_rizstwn_pipeline` is a English model originally trained by rizstwn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_rizstwn_pipeline_en_5.5.1_3.0_1737663590999.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_rizstwn_pipeline_en_5.5.1_3.0_1737663590999.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_rizstwn_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_rizstwn_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_rizstwn_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/rizstwn/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_ryo_hsgw_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_ryo_hsgw_en.md
new file mode 100644
index 00000000000000..828c44fbaafe11
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_ryo_hsgw_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_ryo_hsgw DistilBertEmbeddings from ryo-hsgw
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_ryo_hsgw
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_ryo_hsgw` is a English model originally trained by ryo-hsgw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_ryo_hsgw_en_5.5.1_3.0_1737663722940.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_ryo_hsgw_en_5.5.1_3.0_1737663722940.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_ryo_hsgw","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_ryo_hsgw","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_ryo_hsgw|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/ryo-hsgw/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_ryo_hsgw_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_ryo_hsgw_pipeline_en.md
new file mode 100644
index 00000000000000..67adc21072dff0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_ryo_hsgw_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_ryo_hsgw_pipeline pipeline DistilBertEmbeddings from ryo-hsgw
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_ryo_hsgw_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_ryo_hsgw_pipeline` is a English model originally trained by ryo-hsgw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_ryo_hsgw_pipeline_en_5.5.1_3.0_1737663736452.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_ryo_hsgw_pipeline_en_5.5.1_3.0_1737663736452.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_ryo_hsgw_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_ryo_hsgw_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_ryo_hsgw_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/ryo-hsgw/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_vaibhavtalekar87_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_vaibhavtalekar87_en.md
new file mode 100644
index 00000000000000..f7a24f9b86b322
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_vaibhavtalekar87_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_vaibhavtalekar87 DistilBertEmbeddings from vaibhavtalekar87
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_vaibhavtalekar87
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_vaibhavtalekar87` is a English model originally trained by vaibhavtalekar87.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_vaibhavtalekar87_en_5.5.1_3.0_1737663200733.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_vaibhavtalekar87_en_5.5.1_3.0_1737663200733.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_vaibhavtalekar87","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_vaibhavtalekar87","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_vaibhavtalekar87|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/vaibhavtalekar87/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_vaibhavtalekar87_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_vaibhavtalekar87_pipeline_en.md
new file mode 100644
index 00000000000000..de1b1af73bf138
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_vaibhavtalekar87_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_vaibhavtalekar87_pipeline pipeline DistilBertEmbeddings from vaibhavtalekar87
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_vaibhavtalekar87_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_vaibhavtalekar87_pipeline` is a English model originally trained by vaibhavtalekar87.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_vaibhavtalekar87_pipeline_en_5.5.1_3.0_1737663214599.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_vaibhavtalekar87_pipeline_en_5.5.1_3.0_1737663214599.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_vaibhavtalekar87_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_vaibhavtalekar87_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_vaibhavtalekar87_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/vaibhavtalekar87/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_wuzhongyanqiu_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_wuzhongyanqiu_en.md
new file mode 100644
index 00000000000000..e0af8e853bd4b1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_wuzhongyanqiu_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_wuzhongyanqiu DistilBertEmbeddings from wuzhongyanqiu
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_wuzhongyanqiu
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_wuzhongyanqiu` is a English model originally trained by wuzhongyanqiu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_wuzhongyanqiu_en_5.5.1_3.0_1737662883665.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_wuzhongyanqiu_en_5.5.1_3.0_1737662883665.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_wuzhongyanqiu","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_wuzhongyanqiu","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_wuzhongyanqiu|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/wuzhongyanqiu/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_wuzhongyanqiu_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_wuzhongyanqiu_pipeline_en.md
new file mode 100644
index 00000000000000..c6c618974ba043
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_wuzhongyanqiu_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_wuzhongyanqiu_pipeline pipeline DistilBertEmbeddings from wuzhongyanqiu
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_wuzhongyanqiu_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_wuzhongyanqiu_pipeline` is a English model originally trained by wuzhongyanqiu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_wuzhongyanqiu_pipeline_en_5.5.1_3.0_1737662897957.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_wuzhongyanqiu_pipeline_en_5.5.1_3.0_1737662897957.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_wuzhongyanqiu_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_wuzhongyanqiu_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_wuzhongyanqiu_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/wuzhongyanqiu/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_yanmife_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_yanmife_en.md
new file mode 100644
index 00000000000000..30e25b8b3883b2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_yanmife_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_yanmife DistilBertEmbeddings from Yanmife
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_yanmife
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_yanmife` is a English model originally trained by Yanmife.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_yanmife_en_5.5.1_3.0_1737663427334.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_yanmife_en_5.5.1_3.0_1737663427334.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_yanmife","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_yanmife","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_yanmife|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Yanmife/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_yanmife_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_yanmife_pipeline_en.md
new file mode 100644
index 00000000000000..c58a0d69eaaabf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_yanmife_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_yanmife_pipeline pipeline DistilBertEmbeddings from Yanmife
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_yanmife_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_yanmife_pipeline` is a English model originally trained by Yanmife.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_yanmife_pipeline_en_5.5.1_3.0_1737663444372.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_yanmife_pipeline_en_5.5.1_3.0_1737663444372.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_yanmife_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_yanmife_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_yanmife_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Yanmife/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_zmeeks_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_zmeeks_en.md
new file mode 100644
index 00000000000000..7d22e89fd0d86a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_zmeeks_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_zmeeks DistilBertEmbeddings from zmeeks
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_zmeeks
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_zmeeks` is a English model originally trained by zmeeks.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_zmeeks_en_5.5.1_3.0_1737663232400.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_zmeeks_en_5.5.1_3.0_1737663232400.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_zmeeks","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_zmeeks","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_zmeeks|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/zmeeks/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_zmeeks_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_zmeeks_pipeline_en.md
new file mode 100644
index 00000000000000..0b0eddab5629c0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_imdb_zmeeks_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_zmeeks_pipeline pipeline DistilBertEmbeddings from zmeeks
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_zmeeks_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_zmeeks_pipeline` is a English model originally trained by zmeeks.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_zmeeks_pipeline_en_5.5.1_3.0_1737663246745.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_zmeeks_pipeline_en_5.5.1_3.0_1737663246745.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_zmeeks_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_zmeeks_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_zmeeks_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/zmeeks/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_ner_arielb30_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_ner_arielb30_en.md
new file mode 100644
index 00000000000000..1119de843a0386
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_ner_arielb30_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_arielb30 DistilBertForTokenClassification from arielb30
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_arielb30
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_arielb30` is a English model originally trained by arielb30.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_arielb30_en_5.5.1_3.0_1737627738984.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_arielb30_en_5.5.1_3.0_1737627738984.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_arielb30","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_arielb30", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_arielb30|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/arielb30/distilbert-base-uncased-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_ner_arielb30_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_ner_arielb30_pipeline_en.md
new file mode 100644
index 00000000000000..f7e26e8a9ad7bb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_ner_arielb30_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_arielb30_pipeline pipeline DistilBertForTokenClassification from arielb30
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_arielb30_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_arielb30_pipeline` is a English model originally trained by arielb30.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_arielb30_pipeline_en_5.5.1_3.0_1737627752228.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_arielb30_pipeline_en_5.5.1_3.0_1737627752228.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_ner_arielb30_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_ner_arielb30_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_arielb30_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/arielb30/distilbert-base-uncased-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_ner_hitmanreborn_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_ner_hitmanreborn_en.md
new file mode 100644
index 00000000000000..939ece51666f3b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_ner_hitmanreborn_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_hitmanreborn DistilBertForTokenClassification from HitmanReborn
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_hitmanreborn
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_hitmanreborn` is a English model originally trained by HitmanReborn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_hitmanreborn_en_5.5.1_3.0_1737627382779.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_hitmanreborn_en_5.5.1_3.0_1737627382779.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_hitmanreborn","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_hitmanreborn", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_hitmanreborn|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/HitmanReborn/distilbert-base-uncased-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_ner_hitmanreborn_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_ner_hitmanreborn_pipeline_en.md
new file mode 100644
index 00000000000000..1640b3dd24c7d3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_ner_hitmanreborn_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_hitmanreborn_pipeline pipeline DistilBertForTokenClassification from HitmanReborn
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_hitmanreborn_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_hitmanreborn_pipeline` is a English model originally trained by HitmanReborn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_hitmanreborn_pipeline_en_5.5.1_3.0_1737627397638.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_hitmanreborn_pipeline_en_5.5.1_3.0_1737627397638.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_ner_hitmanreborn_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_ner_hitmanreborn_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_hitmanreborn_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/HitmanReborn/distilbert-base-uncased-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_ner_nstrn_mo_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_ner_nstrn_mo_en.md
new file mode 100644
index 00000000000000..eae87ee13d50f8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_ner_nstrn_mo_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_nstrn_mo DistilBertForTokenClassification from nstrn-mo
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_nstrn_mo
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_nstrn_mo` is a English model originally trained by nstrn-mo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_nstrn_mo_en_5.5.1_3.0_1737627045519.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_nstrn_mo_en_5.5.1_3.0_1737627045519.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_nstrn_mo","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_nstrn_mo", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_nstrn_mo|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/nstrn-mo/distilbert-base-uncased-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_ner_nstrn_mo_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_ner_nstrn_mo_pipeline_en.md
new file mode 100644
index 00000000000000..99d4cbe1bbe2ee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_ner_nstrn_mo_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_nstrn_mo_pipeline pipeline DistilBertForTokenClassification from nstrn-mo
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_nstrn_mo_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_nstrn_mo_pipeline` is a English model originally trained by nstrn-mo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_nstrn_mo_pipeline_en_5.5.1_3.0_1737627060093.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_nstrn_mo_pipeline_en_5.5.1_3.0_1737627060093.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_ner_nstrn_mo_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_ner_nstrn_mo_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_nstrn_mo_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/nstrn-mo/distilbert-base-uncased-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_ner_uppaluru_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_ner_uppaluru_en.md
new file mode 100644
index 00000000000000..eff44a614b9019
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_ner_uppaluru_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_uppaluru DistilBertForTokenClassification from uppaluru
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_uppaluru
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_uppaluru` is a English model originally trained by uppaluru.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_uppaluru_en_5.5.1_3.0_1737627211828.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_uppaluru_en_5.5.1_3.0_1737627211828.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_uppaluru","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_uppaluru", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_uppaluru|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/uppaluru/distilbert-base-uncased-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_ner_uppaluru_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_ner_uppaluru_pipeline_en.md
new file mode 100644
index 00000000000000..275bfb9e2b53a4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_ner_uppaluru_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_uppaluru_pipeline pipeline DistilBertForTokenClassification from uppaluru
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_uppaluru_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_uppaluru_pipeline` is a English model originally trained by uppaluru.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_uppaluru_pipeline_en_5.5.1_3.0_1737627225546.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_uppaluru_pipeline_en_5.5.1_3.0_1737627225546.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_ner_uppaluru_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_ner_uppaluru_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_uppaluru_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/uppaluru/distilbert-base-uncased-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_ner_yanyaner_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_ner_yanyaner_en.md
new file mode 100644
index 00000000000000..0ac757f7667d05
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_ner_yanyaner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_yanyaner DistilBertForTokenClassification from YanYaner
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_yanyaner
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_yanyaner` is a English model originally trained by YanYaner.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_yanyaner_en_5.5.1_3.0_1737627902992.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_yanyaner_en_5.5.1_3.0_1737627902992.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_yanyaner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_yanyaner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_yanyaner|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/YanYaner/distilbert-base-uncased-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_ner_yanyaner_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_ner_yanyaner_pipeline_en.md
new file mode 100644
index 00000000000000..8326912f22919d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_ner_yanyaner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_yanyaner_pipeline pipeline DistilBertForTokenClassification from YanYaner
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_yanyaner_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_yanyaner_pipeline` is a English model originally trained by YanYaner.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_yanyaner_pipeline_en_5.5.1_3.0_1737627916033.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_yanyaner_pipeline_en_5.5.1_3.0_1737627916033.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_ner_yanyaner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_ner_yanyaner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_yanyaner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/YanYaner/distilbert-base-uncased-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_react_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_react_en.md
new file mode 100644
index 00000000000000..799cbea6b9a8ae
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_react_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_react DistilBertEmbeddings from mjalg
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_react
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_react` is a English model originally trained by mjalg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_react_en_5.5.1_3.0_1737663138490.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_react_en_5.5.1_3.0_1737663138490.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_react","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_react","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_react|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/mjalg/distilbert-base-uncased-finetuned-react
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_react_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_react_pipeline_en.md
new file mode 100644
index 00000000000000..d43097d5c80c9a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_react_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_react_pipeline pipeline DistilBertEmbeddings from mjalg
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_react_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_react_pipeline` is a English model originally trained by mjalg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_react_pipeline_en_5.5.1_3.0_1737663152975.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_react_pipeline_en_5.5.1_3.0_1737663152975.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_react_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_react_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_react_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/mjalg/distilbert-base-uncased-finetuned-react
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_squad_agrecounisa_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_squad_agrecounisa_en.md
new file mode 100644
index 00000000000000..2ca35a272f8ed5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_squad_agrecounisa_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_agrecounisa DistilBertForQuestionAnswering from agrecounisa
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_agrecounisa
+date: 2025-01-23
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_agrecounisa` is a English model originally trained by agrecounisa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_agrecounisa_en_5.5.1_3.0_1737660669982.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_agrecounisa_en_5.5.1_3.0_1737660669982.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_agrecounisa","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_agrecounisa", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_agrecounisa|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/agrecounisa/distilbert-base-uncased-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_squad_agrecounisa_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_squad_agrecounisa_pipeline_en.md
new file mode 100644
index 00000000000000..23aa0a650de43f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_squad_agrecounisa_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_agrecounisa_pipeline pipeline DistilBertForQuestionAnswering from agrecounisa
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_agrecounisa_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_agrecounisa_pipeline` is a English model originally trained by agrecounisa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_agrecounisa_pipeline_en_5.5.1_3.0_1737660688504.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_agrecounisa_pipeline_en_5.5.1_3.0_1737660688504.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_squad_agrecounisa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_squad_agrecounisa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_agrecounisa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/agrecounisa/distilbert-base-uncased-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_squad_alsg00_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_squad_alsg00_en.md
new file mode 100644
index 00000000000000..a68c88439196d2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_squad_alsg00_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_alsg00 DistilBertForQuestionAnswering from AlSG00
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_alsg00
+date: 2025-01-23
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_alsg00` is a English model originally trained by AlSG00.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_alsg00_en_5.5.1_3.0_1737660684861.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_alsg00_en_5.5.1_3.0_1737660684861.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_alsg00","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_alsg00", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_alsg00|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/AlSG00/distilbert-base-uncased-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_squad_alsg00_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_squad_alsg00_pipeline_en.md
new file mode 100644
index 00000000000000..79914423776ea6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_squad_alsg00_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_alsg00_pipeline pipeline DistilBertForQuestionAnswering from AlSG00
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_alsg00_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_alsg00_pipeline` is a English model originally trained by AlSG00.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_alsg00_pipeline_en_5.5.1_3.0_1737660699129.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_alsg00_pipeline_en_5.5.1_3.0_1737660699129.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_squad_alsg00_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_squad_alsg00_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_alsg00_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/AlSG00/distilbert-base-uncased-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_squad_chandan345923_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_squad_chandan345923_en.md
new file mode 100644
index 00000000000000..992b91d00da50b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_squad_chandan345923_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_chandan345923 DistilBertForQuestionAnswering from Chandan345923
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_chandan345923
+date: 2025-01-23
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_chandan345923` is a English model originally trained by Chandan345923.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_chandan345923_en_5.5.1_3.0_1737660441712.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_chandan345923_en_5.5.1_3.0_1737660441712.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_chandan345923","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_chandan345923", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_chandan345923|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Chandan345923/distilbert-base-uncased-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_squad_chandan345923_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_squad_chandan345923_pipeline_en.md
new file mode 100644
index 00000000000000..8b8fd3c4e614a6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_squad_chandan345923_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_chandan345923_pipeline pipeline DistilBertForQuestionAnswering from Chandan345923
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_chandan345923_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_chandan345923_pipeline` is a English model originally trained by Chandan345923.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_chandan345923_pipeline_en_5.5.1_3.0_1737660455513.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_chandan345923_pipeline_en_5.5.1_3.0_1737660455513.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_squad_chandan345923_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_squad_chandan345923_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_chandan345923_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Chandan345923/distilbert-base-uncased-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_squad_jjateen_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_squad_jjateen_en.md
new file mode 100644
index 00000000000000..25b8c48f1bf918
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_squad_jjateen_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_jjateen DistilBertForQuestionAnswering from Jjateen
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_jjateen
+date: 2025-01-23
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_jjateen` is a English model originally trained by Jjateen.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_jjateen_en_5.5.1_3.0_1737660542732.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_jjateen_en_5.5.1_3.0_1737660542732.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_jjateen","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_jjateen", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_jjateen|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Jjateen/distilbert-base-uncased-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_squad_jjateen_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_squad_jjateen_pipeline_en.md
new file mode 100644
index 00000000000000..e5b018ba7db526
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_squad_jjateen_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_jjateen_pipeline pipeline DistilBertForQuestionAnswering from Jjateen
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_jjateen_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_jjateen_pipeline` is a English model originally trained by Jjateen.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_jjateen_pipeline_en_5.5.1_3.0_1737660557572.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_jjateen_pipeline_en_5.5.1_3.0_1737660557572.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_squad_jjateen_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_squad_jjateen_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_jjateen_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Jjateen/distilbert-base-uncased-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_squad_luc401_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_squad_luc401_en.md
new file mode 100644
index 00000000000000..6802be34cedf6c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_squad_luc401_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_luc401 DistilBertForQuestionAnswering from Luc401
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_luc401
+date: 2025-01-23
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_luc401` is a English model originally trained by Luc401.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_luc401_en_5.5.1_3.0_1737661116568.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_luc401_en_5.5.1_3.0_1737661116568.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_luc401","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_luc401", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_luc401|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Luc401/distilbert-base-uncased-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_squad_luc401_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_squad_luc401_pipeline_en.md
new file mode 100644
index 00000000000000..53879d4ad540b3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_squad_luc401_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_luc401_pipeline pipeline DistilBertForQuestionAnswering from Luc401
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_luc401_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_luc401_pipeline` is a English model originally trained by Luc401.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_luc401_pipeline_en_5.5.1_3.0_1737661130677.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_luc401_pipeline_en_5.5.1_3.0_1737661130677.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_squad_luc401_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_squad_luc401_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_luc401_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Luc401/distilbert-base-uncased-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_squad_monjila_moni_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_squad_monjila_moni_en.md
new file mode 100644
index 00000000000000..704d4bcc5bf7d9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_squad_monjila_moni_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_monjila_moni DistilBertForQuestionAnswering from Monjila-Moni
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_monjila_moni
+date: 2025-01-23
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_monjila_moni` is a English model originally trained by Monjila-Moni.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_monjila_moni_en_5.5.1_3.0_1737660963407.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_monjila_moni_en_5.5.1_3.0_1737660963407.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_monjila_moni","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_monjila_moni", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_monjila_moni|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Monjila-Moni/distilbert-base-uncased-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_squad_monjila_moni_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_squad_monjila_moni_pipeline_en.md
new file mode 100644
index 00000000000000..095f78d0ba64d0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_squad_monjila_moni_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_monjila_moni_pipeline pipeline DistilBertForQuestionAnswering from Monjila-Moni
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_monjila_moni_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_monjila_moni_pipeline` is a English model originally trained by Monjila-Moni.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_monjila_moni_pipeline_en_5.5.1_3.0_1737660979635.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_monjila_moni_pipeline_en_5.5.1_3.0_1737660979635.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_squad_monjila_moni_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_squad_monjila_moni_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_monjila_moni_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Monjila-Moni/distilbert-base-uncased-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_squad_wwwzwbz_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_squad_wwwzwbz_en.md
new file mode 100644
index 00000000000000..131c25cde7b9fa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_squad_wwwzwbz_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_wwwzwbz DistilBertForQuestionAnswering from wwwzwbz
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_wwwzwbz
+date: 2025-01-23
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_wwwzwbz` is a English model originally trained by wwwzwbz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_wwwzwbz_en_5.5.1_3.0_1737660671089.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_wwwzwbz_en_5.5.1_3.0_1737660671089.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_wwwzwbz","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_wwwzwbz", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_wwwzwbz|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/wwwzwbz/distilbert-base-uncased-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_squad_wwwzwbz_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_squad_wwwzwbz_pipeline_en.md
new file mode 100644
index 00000000000000..9908687cada720
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_squad_wwwzwbz_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_wwwzwbz_pipeline pipeline DistilBertForQuestionAnswering from wwwzwbz
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_wwwzwbz_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_wwwzwbz_pipeline` is a English model originally trained by wwwzwbz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_wwwzwbz_pipeline_en_5.5.1_3.0_1737660688607.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_wwwzwbz_pipeline_en_5.5.1_3.0_1737660688607.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_squad_wwwzwbz_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_squad_wwwzwbz_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_wwwzwbz_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/wwwzwbz/distilbert-base-uncased-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_sst_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_sst_en.md
new file mode 100644
index 00000000000000..25434ac52dee42
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_sst_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_sst DistilBertEmbeddings from rajabilalnazir
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_sst
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_sst` is a English model originally trained by rajabilalnazir.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_sst_en_5.5.1_3.0_1737663577258.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_sst_en_5.5.1_3.0_1737663577258.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_sst","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_sst","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_sst|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/rajabilalnazir/distilbert-base-uncased-finetuned-sst
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_sst_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_sst_pipeline_en.md
new file mode 100644
index 00000000000000..a8b2eb5319bbfa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_sst_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_sst_pipeline pipeline DistilBertEmbeddings from rajabilalnazir
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_sst_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_sst_pipeline` is a English model originally trained by rajabilalnazir.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_sst_pipeline_en_5.5.1_3.0_1737663593195.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_sst_pipeline_en_5.5.1_3.0_1737663593195.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_sst_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_sst_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_sst_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/rajabilalnazir/distilbert-base-uncased-finetuned-sst
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_t_payment_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_t_payment_en.md
new file mode 100644
index 00000000000000..8910f1b8c492e7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_t_payment_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_t_payment DistilBertForSequenceClassification from Gregorig
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_t_payment
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_t_payment` is a English model originally trained by Gregorig.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_t_payment_en_5.5.1_3.0_1737650945058.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_t_payment_en_5.5.1_3.0_1737650945058.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_t_payment","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_t_payment", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_t_payment|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Gregorig/distilbert-base-uncased-finetuned-t_payment
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_t_payment_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_t_payment_pipeline_en.md
new file mode 100644
index 00000000000000..735ae3f3fb4ff1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_t_payment_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_t_payment_pipeline pipeline DistilBertForSequenceClassification from Gregorig
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_t_payment_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_t_payment_pipeline` is a English model originally trained by Gregorig.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_t_payment_pipeline_en_5.5.1_3.0_1737650958913.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_t_payment_pipeline_en_5.5.1_3.0_1737650958913.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_t_payment_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_t_payment_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_t_payment_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Gregorig/distilbert-base-uncased-finetuned-t_payment
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_t_price_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_t_price_en.md
new file mode 100644
index 00000000000000..acc06667b0a312
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_t_price_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_t_price DistilBertForSequenceClassification from Gregorig
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_t_price
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_t_price` is a English model originally trained by Gregorig.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_t_price_en_5.5.1_3.0_1737650129658.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_t_price_en_5.5.1_3.0_1737650129658.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_t_price","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_t_price", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_t_price|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Gregorig/distilbert-base-uncased-finetuned-t_price
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_t_price_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_t_price_pipeline_en.md
new file mode 100644
index 00000000000000..c58f1333aa9480
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_t_price_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_t_price_pipeline pipeline DistilBertForSequenceClassification from Gregorig
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_t_price_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_t_price_pipeline` is a English model originally trained by Gregorig.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_t_price_pipeline_en_5.5.1_3.0_1737650144101.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_t_price_pipeline_en_5.5.1_3.0_1737650144101.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_t_price_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_t_price_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_t_price_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Gregorig/distilbert-base-uncased-finetuned-t_price
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_tydi_qa_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_tydi_qa_en.md
new file mode 100644
index 00000000000000..9595a621fb912f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_tydi_qa_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_tydi_qa DistilBertForQuestionAnswering from flochner94
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_tydi_qa
+date: 2025-01-23
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_tydi_qa` is a English model originally trained by flochner94.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_tydi_qa_en_5.5.1_3.0_1737661017916.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_tydi_qa_en_5.5.1_3.0_1737661017916.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_tydi_qa","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_tydi_qa", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_tydi_qa|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/flochner94/distilbert-base-uncased-finetuned-tydi-qa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_tydi_qa_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_tydi_qa_pipeline_en.md
new file mode 100644
index 00000000000000..1f960d1835bd6d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_base_uncased_finetuned_tydi_qa_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_tydi_qa_pipeline pipeline DistilBertForQuestionAnswering from flochner94
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_tydi_qa_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_tydi_qa_pipeline` is a English model originally trained by flochner94.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_tydi_qa_pipeline_en_5.5.1_3.0_1737661031542.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_tydi_qa_pipeline_en_5.5.1_3.0_1737661031542.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_tydi_qa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_tydi_qa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_tydi_qa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/flochner94/distilbert-base-uncased-finetuned-tydi-qa
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_emotion_c4n11_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_emotion_c4n11_en.md
new file mode 100644
index 00000000000000..ef40d9f1509fdd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_emotion_c4n11_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_emotion_c4n11 DistilBertForSequenceClassification from c4n11
+author: John Snow Labs
+name: distilbert_emotion_c4n11
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_emotion_c4n11` is a English model originally trained by c4n11.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_emotion_c4n11_en_5.5.1_3.0_1737650002155.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_emotion_c4n11_en_5.5.1_3.0_1737650002155.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_emotion_c4n11","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_emotion_c4n11", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_emotion_c4n11|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/c4n11/distilbert-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_emotion_c4n11_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_emotion_c4n11_pipeline_en.md
new file mode 100644
index 00000000000000..5038aed892c9dc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_emotion_c4n11_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_emotion_c4n11_pipeline pipeline DistilBertForSequenceClassification from c4n11
+author: John Snow Labs
+name: distilbert_emotion_c4n11_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_emotion_c4n11_pipeline` is a English model originally trained by c4n11.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_emotion_c4n11_pipeline_en_5.5.1_3.0_1737650021978.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_emotion_c4n11_pipeline_en_5.5.1_3.0_1737650021978.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_emotion_c4n11_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_emotion_c4n11_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_emotion_c4n11_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/c4n11/distilbert-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_emotion_lekkala_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_emotion_lekkala_en.md
new file mode 100644
index 00000000000000..6667e0cd02169b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_emotion_lekkala_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_emotion_lekkala DistilBertForSequenceClassification from Lekkala
+author: John Snow Labs
+name: distilbert_emotion_lekkala
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_emotion_lekkala` is a English model originally trained by Lekkala.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_emotion_lekkala_en_5.5.1_3.0_1737650449624.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_emotion_lekkala_en_5.5.1_3.0_1737650449624.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_emotion_lekkala","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_emotion_lekkala", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_emotion_lekkala|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Lekkala/distilbert-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_emotion_lekkala_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_emotion_lekkala_pipeline_en.md
new file mode 100644
index 00000000000000..5dc4e3cf6bab10
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_emotion_lekkala_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_emotion_lekkala_pipeline pipeline DistilBertForSequenceClassification from Lekkala
+author: John Snow Labs
+name: distilbert_emotion_lekkala_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_emotion_lekkala_pipeline` is a English model originally trained by Lekkala.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_emotion_lekkala_pipeline_en_5.5.1_3.0_1737650463949.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_emotion_lekkala_pipeline_en_5.5.1_3.0_1737650463949.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_emotion_lekkala_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_emotion_lekkala_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_emotion_lekkala_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Lekkala/distilbert-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_emotion_mini_amazon_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_emotion_mini_amazon_en.md
new file mode 100644
index 00000000000000..f61ace07064add
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_emotion_mini_amazon_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_emotion_mini_amazon DistilBertForSequenceClassification from ncoskun
+author: John Snow Labs
+name: distilbert_emotion_mini_amazon
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_emotion_mini_amazon` is a English model originally trained by ncoskun.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_emotion_mini_amazon_en_5.5.1_3.0_1737650146059.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_emotion_mini_amazon_en_5.5.1_3.0_1737650146059.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_emotion_mini_amazon","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_emotion_mini_amazon", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_emotion_mini_amazon|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/ncoskun/distilbert-emotion-mini-amazon
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_emotion_mini_amazon_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_emotion_mini_amazon_pipeline_en.md
new file mode 100644
index 00000000000000..8d1e1211bce004
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_emotion_mini_amazon_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_emotion_mini_amazon_pipeline pipeline DistilBertForSequenceClassification from ncoskun
+author: John Snow Labs
+name: distilbert_emotion_mini_amazon_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_emotion_mini_amazon_pipeline` is a English model originally trained by ncoskun.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_emotion_mini_amazon_pipeline_en_5.5.1_3.0_1737650161275.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_emotion_mini_amazon_pipeline_en_5.5.1_3.0_1737650161275.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_emotion_mini_amazon_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_emotion_mini_amazon_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_emotion_mini_amazon_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/ncoskun/distilbert-emotion-mini-amazon
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_en.md
new file mode 100644
index 00000000000000..e2c9e680598365
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert DistilBertEmbeddings from Abirami1213
+author: John Snow Labs
+name: distilbert
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert` is a English model originally trained by Abirami1213.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_en_5.5.1_3.0_1737662718365.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_en_5.5.1_3.0_1737662718365.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Abirami1213/distilbert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_finetuned_adcm_v6data_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_finetuned_adcm_v6data_en.md
new file mode 100644
index 00000000000000..e5dfb5c4963c35
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_finetuned_adcm_v6data_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilbert_finetuned_adcm_v6data DistilBertForQuestionAnswering from DenBond2002
+author: John Snow Labs
+name: distilbert_finetuned_adcm_v6data
+date: 2025-01-23
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetuned_adcm_v6data` is a English model originally trained by DenBond2002.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_adcm_v6data_en_5.5.1_3.0_1737660352952.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_adcm_v6data_en_5.5.1_3.0_1737660352952.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_finetuned_adcm_v6data","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_finetuned_adcm_v6data", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_finetuned_adcm_v6data|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/DenBond2002/distilbert-finetuned-adcm-v6data
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_finetuned_adcm_v6data_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_finetuned_adcm_v6data_pipeline_en.md
new file mode 100644
index 00000000000000..beade91ae48595
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_finetuned_adcm_v6data_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbert_finetuned_adcm_v6data_pipeline pipeline DistilBertForQuestionAnswering from DenBond2002
+author: John Snow Labs
+name: distilbert_finetuned_adcm_v6data_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetuned_adcm_v6data_pipeline` is a English model originally trained by DenBond2002.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_adcm_v6data_pipeline_en_5.5.1_3.0_1737660366217.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_adcm_v6data_pipeline_en_5.5.1_3.0_1737660366217.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_finetuned_adcm_v6data_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_finetuned_adcm_v6data_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_finetuned_adcm_v6data_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/DenBond2002/distilbert-finetuned-adcm-v6data
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_finetuned_imdb_ex_course_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_finetuned_imdb_ex_course_en.md
new file mode 100644
index 00000000000000..de67ed08abf772
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_finetuned_imdb_ex_course_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_finetuned_imdb_ex_course DistilBertEmbeddings from LuisMBA
+author: John Snow Labs
+name: distilbert_finetuned_imdb_ex_course
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetuned_imdb_ex_course` is a English model originally trained by LuisMBA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_imdb_ex_course_en_5.5.1_3.0_1737662718448.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_imdb_ex_course_en_5.5.1_3.0_1737662718448.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_finetuned_imdb_ex_course","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_finetuned_imdb_ex_course","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_finetuned_imdb_ex_course|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/LuisMBA/distilbert-finetuned-imdb-ex-course
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_finetuned_imdb_ex_course_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_finetuned_imdb_ex_course_pipeline_en.md
new file mode 100644
index 00000000000000..5549bbd34d3320
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_finetuned_imdb_ex_course_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_finetuned_imdb_ex_course_pipeline pipeline DistilBertEmbeddings from LuisMBA
+author: John Snow Labs
+name: distilbert_finetuned_imdb_ex_course_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetuned_imdb_ex_course_pipeline` is a English model originally trained by LuisMBA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_imdb_ex_course_pipeline_en_5.5.1_3.0_1737662734203.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_imdb_ex_course_pipeline_en_5.5.1_3.0_1737662734203.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_finetuned_imdb_ex_course_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_finetuned_imdb_ex_course_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_finetuned_imdb_ex_course_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/LuisMBA/distilbert-finetuned-imdb-ex-course
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_finetuned_imdb_mlm_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_finetuned_imdb_mlm_en.md
new file mode 100644
index 00000000000000..a320afd0394bf0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_finetuned_imdb_mlm_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_finetuned_imdb_mlm DistilBertEmbeddings from Prikshit7766
+author: John Snow Labs
+name: distilbert_finetuned_imdb_mlm
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetuned_imdb_mlm` is a English model originally trained by Prikshit7766.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_imdb_mlm_en_5.5.1_3.0_1737663581812.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_imdb_mlm_en_5.5.1_3.0_1737663581812.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_finetuned_imdb_mlm","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_finetuned_imdb_mlm","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_finetuned_imdb_mlm|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Prikshit7766/distilbert-finetuned-imdb-mlm
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_finetuned_imdb_mlm_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_finetuned_imdb_mlm_pipeline_en.md
new file mode 100644
index 00000000000000..14f567b2f6248d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_finetuned_imdb_mlm_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_finetuned_imdb_mlm_pipeline pipeline DistilBertEmbeddings from Prikshit7766
+author: John Snow Labs
+name: distilbert_finetuned_imdb_mlm_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetuned_imdb_mlm_pipeline` is a English model originally trained by Prikshit7766.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_imdb_mlm_pipeline_en_5.5.1_3.0_1737663596667.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_imdb_mlm_pipeline_en_5.5.1_3.0_1737663596667.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_finetuned_imdb_mlm_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_finetuned_imdb_mlm_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_finetuned_imdb_mlm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Prikshit7766/distilbert-finetuned-imdb-mlm
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_finetuned_ner1_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_finetuned_ner1_en.md
new file mode 100644
index 00000000000000..0d91bf9b838ad1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_finetuned_ner1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_finetuned_ner1 DistilBertForTokenClassification from leo1234messi
+author: John Snow Labs
+name: distilbert_finetuned_ner1
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetuned_ner1` is a English model originally trained by leo1234messi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_ner1_en_5.5.1_3.0_1737627647768.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_ner1_en_5.5.1_3.0_1737627647768.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_finetuned_ner1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_finetuned_ner1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_finetuned_ner1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/leo1234messi/distilbert-finetuned-ner1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_finetuned_ner1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_finetuned_ner1_pipeline_en.md
new file mode 100644
index 00000000000000..526800e4715fa6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_finetuned_ner1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_finetuned_ner1_pipeline pipeline DistilBertForTokenClassification from leo1234messi
+author: John Snow Labs
+name: distilbert_finetuned_ner1_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetuned_ner1_pipeline` is a English model originally trained by leo1234messi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_ner1_pipeline_en_5.5.1_3.0_1737627671903.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_ner1_pipeline_en_5.5.1_3.0_1737627671903.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_finetuned_ner1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_finetuned_ner1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_finetuned_ner1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/leo1234messi/distilbert-finetuned-ner1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_finetuned_ner_ep_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_finetuned_ner_ep_en.md
new file mode 100644
index 00000000000000..de8acde27345b7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_finetuned_ner_ep_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_finetuned_ner_ep DistilBertForTokenClassification from leo1234messi
+author: John Snow Labs
+name: distilbert_finetuned_ner_ep
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetuned_ner_ep` is a English model originally trained by leo1234messi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_ner_ep_en_5.5.1_3.0_1737627404318.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_ner_ep_en_5.5.1_3.0_1737627404318.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_finetuned_ner_ep","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_finetuned_ner_ep", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_finetuned_ner_ep|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/leo1234messi/distilbert-finetuned-ner_ep
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_finetuned_ner_ep_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_finetuned_ner_ep_pipeline_en.md
new file mode 100644
index 00000000000000..b08224a5120ed3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_finetuned_ner_ep_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_finetuned_ner_ep_pipeline pipeline DistilBertForTokenClassification from leo1234messi
+author: John Snow Labs
+name: distilbert_finetuned_ner_ep_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetuned_ner_ep_pipeline` is a English model originally trained by leo1234messi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_ner_ep_pipeline_en_5.5.1_3.0_1737627417643.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_ner_ep_pipeline_en_5.5.1_3.0_1737627417643.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_finetuned_ner_ep_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_finetuned_ner_ep_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_finetuned_ner_ep_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/leo1234messi/distilbert-finetuned-ner_ep
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_finetuned_ner_leo1234messi_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_finetuned_ner_leo1234messi_en.md
new file mode 100644
index 00000000000000..04a26427ab4b89
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_finetuned_ner_leo1234messi_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_finetuned_ner_leo1234messi DistilBertForTokenClassification from leo1234messi
+author: John Snow Labs
+name: distilbert_finetuned_ner_leo1234messi
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetuned_ner_leo1234messi` is a English model originally trained by leo1234messi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_ner_leo1234messi_en_5.5.1_3.0_1737627533726.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_ner_leo1234messi_en_5.5.1_3.0_1737627533726.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_finetuned_ner_leo1234messi","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_finetuned_ner_leo1234messi", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_finetuned_ner_leo1234messi|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/leo1234messi/distilbert-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_finetuned_ner_leo1234messi_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_finetuned_ner_leo1234messi_pipeline_en.md
new file mode 100644
index 00000000000000..1e63f330622eb9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_finetuned_ner_leo1234messi_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_finetuned_ner_leo1234messi_pipeline pipeline DistilBertForTokenClassification from leo1234messi
+author: John Snow Labs
+name: distilbert_finetuned_ner_leo1234messi_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetuned_ner_leo1234messi_pipeline` is a English model originally trained by leo1234messi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_ner_leo1234messi_pipeline_en_5.5.1_3.0_1737627547629.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_ner_leo1234messi_pipeline_en_5.5.1_3.0_1737627547629.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_finetuned_ner_leo1234messi_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_finetuned_ner_leo1234messi_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_finetuned_ner_leo1234messi_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/leo1234messi/distilbert-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_finetuned_ner_procit009_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_finetuned_ner_procit009_en.md
new file mode 100644
index 00000000000000..51e8f8b7d27cc9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_finetuned_ner_procit009_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_finetuned_ner_procit009 DistilBertForTokenClassification from procit009
+author: John Snow Labs
+name: distilbert_finetuned_ner_procit009
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetuned_ner_procit009` is a English model originally trained by procit009.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_ner_procit009_en_5.5.1_3.0_1737627380056.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_ner_procit009_en_5.5.1_3.0_1737627380056.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_finetuned_ner_procit009","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_finetuned_ner_procit009", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_finetuned_ner_procit009|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/procit009/distilbert-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_finetuned_ner_procit009_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_finetuned_ner_procit009_pipeline_en.md
new file mode 100644
index 00000000000000..2facd16487adad
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_finetuned_ner_procit009_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_finetuned_ner_procit009_pipeline pipeline DistilBertForTokenClassification from procit009
+author: John Snow Labs
+name: distilbert_finetuned_ner_procit009_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetuned_ner_procit009_pipeline` is a English model originally trained by procit009.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_ner_procit009_pipeline_en_5.5.1_3.0_1737627393977.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_ner_procit009_pipeline_en_5.5.1_3.0_1737627393977.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_finetuned_ner_procit009_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_finetuned_ner_procit009_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_finetuned_ner_procit009_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/procit009/distilbert-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_for_intent_prediction_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_for_intent_prediction_en.md
new file mode 100644
index 00000000000000..8c530f00c135b9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_for_intent_prediction_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_for_intent_prediction DistilBertForSequenceClassification from MeanBean-05
+author: John Snow Labs
+name: distilbert_for_intent_prediction
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_for_intent_prediction` is a English model originally trained by MeanBean-05.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_for_intent_prediction_en_5.5.1_3.0_1737650470401.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_for_intent_prediction_en_5.5.1_3.0_1737650470401.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_for_intent_prediction","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_for_intent_prediction", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_for_intent_prediction|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/MeanBean-05/distilbert-for-intent-prediction
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_for_intent_prediction_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_for_intent_prediction_pipeline_en.md
new file mode 100644
index 00000000000000..bae1925ce92c35
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_for_intent_prediction_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_for_intent_prediction_pipeline pipeline DistilBertForSequenceClassification from MeanBean-05
+author: John Snow Labs
+name: distilbert_for_intent_prediction_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_for_intent_prediction_pipeline` is a English model originally trained by MeanBean-05.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_for_intent_prediction_pipeline_en_5.5.1_3.0_1737650484243.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_for_intent_prediction_pipeline_en_5.5.1_3.0_1737650484243.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_for_intent_prediction_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_for_intent_prediction_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_for_intent_prediction_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/MeanBean-05/distilbert-for-intent-prediction
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_kazakh_ner_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_kazakh_ner_en.md
new file mode 100644
index 00000000000000..d4a1b58c5d94e7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_kazakh_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_kazakh_ner DistilBertForTokenClassification from yasminsur
+author: John Snow Labs
+name: distilbert_kazakh_ner
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_kazakh_ner` is a English model originally trained by yasminsur.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_kazakh_ner_en_5.5.1_3.0_1737628157807.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_kazakh_ner_en_5.5.1_3.0_1737628157807.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_kazakh_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_kazakh_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_kazakh_ner|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|505.5 MB|
+
+## References
+
+https://huggingface.co/yasminsur/distilbert-kazakh-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_kazakh_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_kazakh_ner_pipeline_en.md
new file mode 100644
index 00000000000000..846e781454200d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_kazakh_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_kazakh_ner_pipeline pipeline DistilBertForTokenClassification from yasminsur
+author: John Snow Labs
+name: distilbert_kazakh_ner_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_kazakh_ner_pipeline` is a English model originally trained by yasminsur.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_kazakh_ner_pipeline_en_5.5.1_3.0_1737628183566.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_kazakh_ner_pipeline_en_5.5.1_3.0_1737628183566.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_kazakh_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_kazakh_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_kazakh_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|505.6 MB|
+
+## References
+
+https://huggingface.co/yasminsur/distilbert-kazakh-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_ner_conll2003_drippypale_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_ner_conll2003_drippypale_en.md
new file mode 100644
index 00000000000000..b2eddd6bfd9452
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_ner_conll2003_drippypale_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_ner_conll2003_drippypale DistilBertForTokenClassification from drippypale
+author: John Snow Labs
+name: distilbert_ner_conll2003_drippypale
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_ner_conll2003_drippypale` is a English model originally trained by drippypale.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_ner_conll2003_drippypale_en_5.5.1_3.0_1737626900787.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_ner_conll2003_drippypale_en_5.5.1_3.0_1737626900787.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_ner_conll2003_drippypale","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_ner_conll2003_drippypale", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_ner_conll2003_drippypale|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/drippypale/distilbert-ner-conll2003
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_ner_conll2003_drippypale_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_ner_conll2003_drippypale_pipeline_en.md
new file mode 100644
index 00000000000000..af9a53379a4efb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_ner_conll2003_drippypale_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_ner_conll2003_drippypale_pipeline pipeline DistilBertForTokenClassification from drippypale
+author: John Snow Labs
+name: distilbert_ner_conll2003_drippypale_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_ner_conll2003_drippypale_pipeline` is a English model originally trained by drippypale.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_ner_conll2003_drippypale_pipeline_en_5.5.1_3.0_1737626921157.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_ner_conll2003_drippypale_pipeline_en_5.5.1_3.0_1737626921157.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_ner_conll2003_drippypale_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_ner_conll2003_drippypale_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_ner_conll2003_drippypale_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/drippypale/distilbert-ner-conll2003
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_ner_conll2003_drjm13_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_ner_conll2003_drjm13_en.md
new file mode 100644
index 00000000000000..5ec3aa062a88c4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_ner_conll2003_drjm13_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_ner_conll2003_drjm13 DistilBertForTokenClassification from drjm13
+author: John Snow Labs
+name: distilbert_ner_conll2003_drjm13
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_ner_conll2003_drjm13` is a English model originally trained by drjm13.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_ner_conll2003_drjm13_en_5.5.1_3.0_1737627848071.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_ner_conll2003_drjm13_en_5.5.1_3.0_1737627848071.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_ner_conll2003_drjm13","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_ner_conll2003_drjm13", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_ner_conll2003_drjm13|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/drjm13/distilbert-ner-conll2003
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_ner_conll2003_drjm13_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_ner_conll2003_drjm13_pipeline_en.md
new file mode 100644
index 00000000000000..ce96fb28e414bb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_ner_conll2003_drjm13_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_ner_conll2003_drjm13_pipeline pipeline DistilBertForTokenClassification from drjm13
+author: John Snow Labs
+name: distilbert_ner_conll2003_drjm13_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_ner_conll2003_drjm13_pipeline` is a English model originally trained by drjm13.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_ner_conll2003_drjm13_pipeline_en_5.5.1_3.0_1737627861235.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_ner_conll2003_drjm13_pipeline_en_5.5.1_3.0_1737627861235.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_ner_conll2003_drjm13_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_ner_conll2003_drjm13_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_ner_conll2003_drjm13_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/drjm13/distilbert-ner-conll2003
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_ner_conll2003_salehkiani_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_ner_conll2003_salehkiani_en.md
new file mode 100644
index 00000000000000..de1975c57bf19b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_ner_conll2003_salehkiani_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_ner_conll2003_salehkiani DistilBertForTokenClassification from salehkiani
+author: John Snow Labs
+name: distilbert_ner_conll2003_salehkiani
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_ner_conll2003_salehkiani` is a English model originally trained by salehkiani.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_ner_conll2003_salehkiani_en_5.5.1_3.0_1737627637976.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_ner_conll2003_salehkiani_en_5.5.1_3.0_1737627637976.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_ner_conll2003_salehkiani","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_ner_conll2003_salehkiani", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_ner_conll2003_salehkiani|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/salehkiani/distilbert-ner-conll2003
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_ner_conll2003_salehkiani_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_ner_conll2003_salehkiani_pipeline_en.md
new file mode 100644
index 00000000000000..0920ffa29350ed
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_ner_conll2003_salehkiani_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_ner_conll2003_salehkiani_pipeline pipeline DistilBertForTokenClassification from salehkiani
+author: John Snow Labs
+name: distilbert_ner_conll2003_salehkiani_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_ner_conll2003_salehkiani_pipeline` is a English model originally trained by salehkiani.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_ner_conll2003_salehkiani_pipeline_en_5.5.1_3.0_1737627651352.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_ner_conll2003_salehkiani_pipeline_en_5.5.1_3.0_1737627651352.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_ner_conll2003_salehkiani_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_ner_conll2003_salehkiani_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_ner_conll2003_salehkiani_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/salehkiani/distilbert-ner-conll2003
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_ner_conll2003_zahra_fmma_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_ner_conll2003_zahra_fmma_en.md
new file mode 100644
index 00000000000000..a9f570ff6fabcf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_ner_conll2003_zahra_fmma_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_ner_conll2003_zahra_fmma DistilBertForTokenClassification from Zahra-FMMA
+author: John Snow Labs
+name: distilbert_ner_conll2003_zahra_fmma
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_ner_conll2003_zahra_fmma` is a English model originally trained by Zahra-FMMA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_ner_conll2003_zahra_fmma_en_5.5.1_3.0_1737627781434.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_ner_conll2003_zahra_fmma_en_5.5.1_3.0_1737627781434.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_ner_conll2003_zahra_fmma","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_ner_conll2003_zahra_fmma", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_ner_conll2003_zahra_fmma|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Zahra-FMMA/distilbert-ner-conll2003
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_ner_conll2003_zahra_fmma_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_ner_conll2003_zahra_fmma_pipeline_en.md
new file mode 100644
index 00000000000000..8ea039feb1a85a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_ner_conll2003_zahra_fmma_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_ner_conll2003_zahra_fmma_pipeline pipeline DistilBertForTokenClassification from Zahra-FMMA
+author: John Snow Labs
+name: distilbert_ner_conll2003_zahra_fmma_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_ner_conll2003_zahra_fmma_pipeline` is a English model originally trained by Zahra-FMMA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_ner_conll2003_zahra_fmma_pipeline_en_5.5.1_3.0_1737627794927.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_ner_conll2003_zahra_fmma_pipeline_en_5.5.1_3.0_1737627794927.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_ner_conll2003_zahra_fmma_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_ner_conll2003_zahra_fmma_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_ner_conll2003_zahra_fmma_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Zahra-FMMA/distilbert-ner-conll2003
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_ner_math_finetuned_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_ner_math_finetuned_en.md
new file mode 100644
index 00000000000000..3948b2f39a9635
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_ner_math_finetuned_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_ner_math_finetuned DistilBertForTokenClassification from Heather-Driver
+author: John Snow Labs
+name: distilbert_ner_math_finetuned
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_ner_math_finetuned` is a English model originally trained by Heather-Driver.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_ner_math_finetuned_en_5.5.1_3.0_1737627159651.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_ner_math_finetuned_en_5.5.1_3.0_1737627159651.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_ner_math_finetuned","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_ner_math_finetuned", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_ner_math_finetuned|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|244.0 MB|
+
+## References
+
+https://huggingface.co/Heather-Driver/distilbert-NER-Math-finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_ner_math_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_ner_math_finetuned_pipeline_en.md
new file mode 100644
index 00000000000000..1e273f019a76cc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_ner_math_finetuned_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_ner_math_finetuned_pipeline pipeline DistilBertForTokenClassification from Heather-Driver
+author: John Snow Labs
+name: distilbert_ner_math_finetuned_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_ner_math_finetuned_pipeline` is a English model originally trained by Heather-Driver.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_ner_math_finetuned_pipeline_en_5.5.1_3.0_1737627172444.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_ner_math_finetuned_pipeline_en_5.5.1_3.0_1737627172444.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_ner_math_finetuned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_ner_math_finetuned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_ner_math_finetuned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|244.0 MB|
+
+## References
+
+https://huggingface.co/Heather-Driver/distilbert-NER-Math-finetuned
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_pipeline_en.md
new file mode 100644
index 00000000000000..7e9eaece92adcd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_pipeline pipeline DistilBertEmbeddings from Abirami1213
+author: John Snow Labs
+name: distilbert_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_pipeline` is a English model originally trained by Abirami1213.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_pipeline_en_5.5.1_3.0_1737662739061.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_pipeline_en_5.5.1_3.0_1737662739061.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Abirami1213/distilbert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_token_classification_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_token_classification_en.md
new file mode 100644
index 00000000000000..aad80baa66796f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_token_classification_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_token_classification DistilBertForTokenClassification from vactoTodeath
+author: John Snow Labs
+name: distilbert_token_classification
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_token_classification` is a English model originally trained by vactoTodeath.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_token_classification_en_5.5.1_3.0_1737628064284.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_token_classification_en_5.5.1_3.0_1737628064284.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_token_classification","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_token_classification", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_token_classification|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/vactoTodeath/distilbert-token-classification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_token_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_token_classification_pipeline_en.md
new file mode 100644
index 00000000000000..a0748a85565b28
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_token_classification_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_token_classification_pipeline pipeline DistilBertForTokenClassification from vactoTodeath
+author: John Snow Labs
+name: distilbert_token_classification_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_token_classification_pipeline` is a English model originally trained by vactoTodeath.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_token_classification_pipeline_en_5.5.1_3.0_1737628077607.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_token_classification_pipeline_en_5.5.1_3.0_1737628077607.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_token_classification_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_token_classification_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_token_classification_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/vactoTodeath/distilbert-token-classification
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_token_classification_v2_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_token_classification_v2_en.md
new file mode 100644
index 00000000000000..3b07a2d633bcc8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_token_classification_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_token_classification_v2 DistilBertForTokenClassification from Useer923
+author: John Snow Labs
+name: distilbert_token_classification_v2
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_token_classification_v2` is a English model originally trained by Useer923.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_token_classification_v2_en_5.5.1_3.0_1737627267495.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_token_classification_v2_en_5.5.1_3.0_1737627267495.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_token_classification_v2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_token_classification_v2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_token_classification_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Useer923/distilbert-token-classification-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilbert_token_classification_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilbert_token_classification_v2_pipeline_en.md
new file mode 100644
index 00000000000000..26c6a9b77db34c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilbert_token_classification_v2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_token_classification_v2_pipeline pipeline DistilBertForTokenClassification from Useer923
+author: John Snow Labs
+name: distilbert_token_classification_v2_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_token_classification_v2_pipeline` is a English model originally trained by Useer923.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_token_classification_v2_pipeline_en_5.5.1_3.0_1737627297421.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_token_classification_v2_pipeline_en_5.5.1_3.0_1737627297421.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_token_classification_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_token_classification_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_token_classification_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Useer923/distilbert-token-classification-v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilledbert_finetuned_ner_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilledbert_finetuned_ner_en.md
new file mode 100644
index 00000000000000..bfee4e121b90ea
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilledbert_finetuned_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilledbert_finetuned_ner DistilBertForTokenClassification from Wencho
+author: John Snow Labs
+name: distilledbert_finetuned_ner
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilledbert_finetuned_ner` is a English model originally trained by Wencho.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilledbert_finetuned_ner_en_5.5.1_3.0_1737627956897.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilledbert_finetuned_ner_en_5.5.1_3.0_1737627956897.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilledbert_finetuned_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilledbert_finetuned_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilledbert_finetuned_ner|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Wencho/distilledbert-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilledbert_finetuned_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilledbert_finetuned_ner_pipeline_en.md
new file mode 100644
index 00000000000000..4a42537c6ad8fd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilledbert_finetuned_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilledbert_finetuned_ner_pipeline pipeline DistilBertForTokenClassification from Wencho
+author: John Snow Labs
+name: distilledbert_finetuned_ner_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilledbert_finetuned_ner_pipeline` is a English model originally trained by Wencho.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilledbert_finetuned_ner_pipeline_en_5.5.1_3.0_1737627970244.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilledbert_finetuned_ner_pipeline_en_5.5.1_3.0_1737627970244.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilledbert_finetuned_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilledbert_finetuned_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilledbert_finetuned_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Wencho/distilledbert-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilroberta_base_ft_changemyview_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilroberta_base_ft_changemyview_en.md
new file mode 100644
index 00000000000000..5e7ed8ea81959a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilroberta_base_ft_changemyview_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilroberta_base_ft_changemyview RoBertaEmbeddings from jkruk
+author: John Snow Labs
+name: distilroberta_base_ft_changemyview
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_ft_changemyview` is a English model originally trained by jkruk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_base_ft_changemyview_en_5.5.1_3.0_1737643986088.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_ft_changemyview_en_5.5.1_3.0_1737643986088.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("distilroberta_base_ft_changemyview","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("distilroberta_base_ft_changemyview","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_base_ft_changemyview|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/jkruk/distilroberta-base-ft-changemyview
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilroberta_base_ft_changemyview_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilroberta_base_ft_changemyview_pipeline_en.md
new file mode 100644
index 00000000000000..8d944b14c8b8eb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilroberta_base_ft_changemyview_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilroberta_base_ft_changemyview_pipeline pipeline RoBertaEmbeddings from jkruk
+author: John Snow Labs
+name: distilroberta_base_ft_changemyview_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_ft_changemyview_pipeline` is a English model originally trained by jkruk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_base_ft_changemyview_pipeline_en_5.5.1_3.0_1737644003108.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_ft_changemyview_pipeline_en_5.5.1_3.0_1737644003108.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilroberta_base_ft_changemyview_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilroberta_base_ft_changemyview_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_base_ft_changemyview_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/jkruk/distilroberta-base-ft-changemyview
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilroberta_base_ft_relationship_advice_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilroberta_base_ft_relationship_advice_en.md
new file mode 100644
index 00000000000000..235714f103294f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilroberta_base_ft_relationship_advice_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilroberta_base_ft_relationship_advice RoBertaEmbeddings from jkruk
+author: John Snow Labs
+name: distilroberta_base_ft_relationship_advice
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_ft_relationship_advice` is a English model originally trained by jkruk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_base_ft_relationship_advice_en_5.5.1_3.0_1737644216282.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_ft_relationship_advice_en_5.5.1_3.0_1737644216282.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("distilroberta_base_ft_relationship_advice","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("distilroberta_base_ft_relationship_advice","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_base_ft_relationship_advice|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|306.4 MB|
+
+## References
+
+https://huggingface.co/jkruk/distilroberta-base-ft-relationship_advice
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-distilroberta_base_ft_relationship_advice_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-distilroberta_base_ft_relationship_advice_pipeline_en.md
new file mode 100644
index 00000000000000..ae23d2e9a105d5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-distilroberta_base_ft_relationship_advice_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilroberta_base_ft_relationship_advice_pipeline pipeline RoBertaEmbeddings from jkruk
+author: John Snow Labs
+name: distilroberta_base_ft_relationship_advice_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_ft_relationship_advice_pipeline` is a English model originally trained by jkruk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_base_ft_relationship_advice_pipeline_en_5.5.1_3.0_1737644233076.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_ft_relationship_advice_pipeline_en_5.5.1_3.0_1737644233076.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilroberta_base_ft_relationship_advice_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilroberta_base_ft_relationship_advice_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_base_ft_relationship_advice_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/jkruk/distilroberta-base-ft-relationship_advice
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-dmodels_en.md b/docs/_posts/ahmedlone127/2025-01-23-dmodels_en.md
new file mode 100644
index 00000000000000..e4e413f86e69f5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-dmodels_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dmodels CamemBertForSequenceClassification from spidersouris
+author: John Snow Labs
+name: dmodels
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, camembert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dmodels` is a English model originally trained by spidersouris.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dmodels_en_5.5.1_3.0_1737628607847.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dmodels_en_5.5.1_3.0_1737628607847.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = CamemBertForSequenceClassification.pretrained("dmodels","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = CamemBertForSequenceClassification.pretrained("dmodels", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dmodels|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|394.9 MB|
+
+## References
+
+https://huggingface.co/spidersouris/dmodels
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-dmodels_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-dmodels_pipeline_en.md
new file mode 100644
index 00000000000000..aa76deaf7fbce7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-dmodels_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dmodels_pipeline pipeline CamemBertForSequenceClassification from spidersouris
+author: John Snow Labs
+name: dmodels_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dmodels_pipeline` is a English model originally trained by spidersouris.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dmodels_pipeline_en_5.5.1_3.0_1737628641982.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dmodels_pipeline_en_5.5.1_3.0_1737628641982.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dmodels_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dmodels_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dmodels_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|394.9 MB|
+
+## References
+
+https://huggingface.co/spidersouris/dmodels
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-donaldistilbertsunderland6epoch_en.md b/docs/_posts/ahmedlone127/2025-01-23-donaldistilbertsunderland6epoch_en.md
new file mode 100644
index 00000000000000..06646a9fd49efb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-donaldistilbertsunderland6epoch_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English donaldistilbertsunderland6epoch DistilBertEmbeddings from dcrowleymunster
+author: John Snow Labs
+name: donaldistilbertsunderland6epoch
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`donaldistilbertsunderland6epoch` is a English model originally trained by dcrowleymunster.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/donaldistilbertsunderland6epoch_en_5.5.1_3.0_1737663016122.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/donaldistilbertsunderland6epoch_en_5.5.1_3.0_1737663016122.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("donaldistilbertsunderland6epoch","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("donaldistilbertsunderland6epoch","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|donaldistilbertsunderland6epoch|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/dcrowleymunster/donalDistiLBERTSunderland6Epoch
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-donaldistilbertsunderland6epoch_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-donaldistilbertsunderland6epoch_pipeline_en.md
new file mode 100644
index 00000000000000..85b261b2d1af83
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-donaldistilbertsunderland6epoch_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English donaldistilbertsunderland6epoch_pipeline pipeline DistilBertEmbeddings from dcrowleymunster
+author: John Snow Labs
+name: donaldistilbertsunderland6epoch_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`donaldistilbertsunderland6epoch_pipeline` is a English model originally trained by dcrowleymunster.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/donaldistilbertsunderland6epoch_pipeline_en_5.5.1_3.0_1737663031769.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/donaldistilbertsunderland6epoch_pipeline_en_5.5.1_3.0_1737663031769.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("donaldistilbertsunderland6epoch_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("donaldistilbertsunderland6epoch_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|donaldistilbertsunderland6epoch_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/dcrowleymunster/donalDistiLBERTSunderland6Epoch
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-dummy_model_appohfaiths_en.md b/docs/_posts/ahmedlone127/2025-01-23-dummy_model_appohfaiths_en.md
new file mode 100644
index 00000000000000..6715987415be81
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-dummy_model_appohfaiths_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_appohfaiths DistilBertForSequenceClassification from appohfaiths
+author: John Snow Labs
+name: dummy_model_appohfaiths
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_appohfaiths` is a English model originally trained by appohfaiths.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_appohfaiths_en_5.5.1_3.0_1737650307589.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_appohfaiths_en_5.5.1_3.0_1737650307589.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("dummy_model_appohfaiths","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("dummy_model_appohfaiths", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_appohfaiths|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|408.1 MB|
+
+## References
+
+https://huggingface.co/appohfaiths/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-dummy_model_appohfaiths_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-dummy_model_appohfaiths_pipeline_en.md
new file mode 100644
index 00000000000000..d61a347a600396
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-dummy_model_appohfaiths_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_appohfaiths_pipeline pipeline DistilBertForSequenceClassification from appohfaiths
+author: John Snow Labs
+name: dummy_model_appohfaiths_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_appohfaiths_pipeline` is a English model originally trained by appohfaiths.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_appohfaiths_pipeline_en_5.5.1_3.0_1737650329586.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_appohfaiths_pipeline_en_5.5.1_3.0_1737650329586.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_appohfaiths_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_appohfaiths_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_appohfaiths_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|408.1 MB|
+
+## References
+
+https://huggingface.co/appohfaiths/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-electrical_ner_distilbert_base_en.md b/docs/_posts/ahmedlone127/2025-01-23-electrical_ner_distilbert_base_en.md
new file mode 100644
index 00000000000000..273e3808ba8801
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-electrical_ner_distilbert_base_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English electrical_ner_distilbert_base DistilBertForTokenClassification from disham993
+author: John Snow Labs
+name: electrical_ner_distilbert_base
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`electrical_ner_distilbert_base` is a English model originally trained by disham993.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electrical_ner_distilbert_base_en_5.5.1_3.0_1737628017046.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electrical_ner_distilbert_base_en_5.5.1_3.0_1737628017046.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("electrical_ner_distilbert_base","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("electrical_ner_distilbert_base", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electrical_ner_distilbert_base|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/disham993/electrical-ner-distilbert-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-electrical_ner_distilbert_base_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-electrical_ner_distilbert_base_pipeline_en.md
new file mode 100644
index 00000000000000..af50167b629964
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-electrical_ner_distilbert_base_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English electrical_ner_distilbert_base_pipeline pipeline DistilBertForTokenClassification from disham993
+author: John Snow Labs
+name: electrical_ner_distilbert_base_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`electrical_ner_distilbert_base_pipeline` is a English model originally trained by disham993.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electrical_ner_distilbert_base_pipeline_en_5.5.1_3.0_1737628030180.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electrical_ner_distilbert_base_pipeline_en_5.5.1_3.0_1737628030180.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("electrical_ner_distilbert_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("electrical_ner_distilbert_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electrical_ner_distilbert_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/disham993/electrical-ner-distilbert-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-english_bert_squad_en.md b/docs/_posts/ahmedlone127/2025-01-23-english_bert_squad_en.md
new file mode 100644
index 00000000000000..9b5f68b1d6c695
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-english_bert_squad_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English english_bert_squad DistilBertForQuestionAnswering from muratsimsek003
+author: John Snow Labs
+name: english_bert_squad
+date: 2025-01-23
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_bert_squad` is a English model originally trained by muratsimsek003.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/english_bert_squad_en_5.5.1_3.0_1737660379233.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_bert_squad_en_5.5.1_3.0_1737660379233.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("english_bert_squad","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("english_bert_squad", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|english_bert_squad|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/muratsimsek003/english-bert-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-english_bert_squad_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-english_bert_squad_pipeline_en.md
new file mode 100644
index 00000000000000..8ee2de9c510ea1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-english_bert_squad_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English english_bert_squad_pipeline pipeline DistilBertForQuestionAnswering from muratsimsek003
+author: John Snow Labs
+name: english_bert_squad_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_bert_squad_pipeline` is a English model originally trained by muratsimsek003.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/english_bert_squad_pipeline_en_5.5.1_3.0_1737660395696.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_bert_squad_pipeline_en_5.5.1_3.0_1737660395696.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("english_bert_squad_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("english_bert_squad_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|english_bert_squad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/muratsimsek003/english-bert-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-esgi_5iabd2_gbo_afo_td7_en.md b/docs/_posts/ahmedlone127/2025-01-23-esgi_5iabd2_gbo_afo_td7_en.md
new file mode 100644
index 00000000000000..dc2100c59bc732
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-esgi_5iabd2_gbo_afo_td7_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English esgi_5iabd2_gbo_afo_td7 DistilBertForTokenClassification from Elbub
+author: John Snow Labs
+name: esgi_5iabd2_gbo_afo_td7
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`esgi_5iabd2_gbo_afo_td7` is a English model originally trained by Elbub.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/esgi_5iabd2_gbo_afo_td7_en_5.5.1_3.0_1737627521946.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/esgi_5iabd2_gbo_afo_td7_en_5.5.1_3.0_1737627521946.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("esgi_5iabd2_gbo_afo_td7","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("esgi_5iabd2_gbo_afo_td7", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|esgi_5iabd2_gbo_afo_td7|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/Elbub/ESGI_5IABD2_GBO_AFO_TD7
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-esgi_5iabd2_gbo_afo_td7_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-esgi_5iabd2_gbo_afo_td7_pipeline_en.md
new file mode 100644
index 00000000000000..b892e4b65c92eb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-esgi_5iabd2_gbo_afo_td7_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English esgi_5iabd2_gbo_afo_td7_pipeline pipeline DistilBertForTokenClassification from Elbub
+author: John Snow Labs
+name: esgi_5iabd2_gbo_afo_td7_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`esgi_5iabd2_gbo_afo_td7_pipeline` is a English model originally trained by Elbub.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/esgi_5iabd2_gbo_afo_td7_pipeline_en_5.5.1_3.0_1737627535607.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/esgi_5iabd2_gbo_afo_td7_pipeline_en_5.5.1_3.0_1737627535607.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("esgi_5iabd2_gbo_afo_td7_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("esgi_5iabd2_gbo_afo_td7_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|esgi_5iabd2_gbo_afo_td7_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/Elbub/ESGI_5IABD2_GBO_AFO_TD7
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-esperberto_en.md b/docs/_posts/ahmedlone127/2025-01-23-esperberto_en.md
new file mode 100644
index 00000000000000..470f6ca4263a71
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-esperberto_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English esperberto RoBertaEmbeddings from SamJoshua
+author: John Snow Labs
+name: esperberto
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`esperberto` is a English model originally trained by SamJoshua.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/esperberto_en_5.5.1_3.0_1737643813372.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/esperberto_en_5.5.1_3.0_1737643813372.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("esperberto","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("esperberto","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|esperberto|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|311.4 MB|
+
+## References
+
+https://huggingface.co/SamJoshua/EsperBERTo
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-esperberto_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-esperberto_pipeline_en.md
new file mode 100644
index 00000000000000..b7ee094bf6796f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-esperberto_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English esperberto_pipeline pipeline RoBertaEmbeddings from SamJoshua
+author: John Snow Labs
+name: esperberto_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`esperberto_pipeline` is a English model originally trained by SamJoshua.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/esperberto_pipeline_en_5.5.1_3.0_1737643830342.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/esperberto_pipeline_en_5.5.1_3.0_1737643830342.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("esperberto_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("esperberto_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|esperberto_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|311.5 MB|
+
+## References
+
+https://huggingface.co/SamJoshua/EsperBERTo
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-ethix4context12_en.md b/docs/_posts/ahmedlone127/2025-01-23-ethix4context12_en.md
new file mode 100644
index 00000000000000..10cf8951350c7e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-ethix4context12_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ethix4context12 DistilBertForTokenClassification from Somisetty2347
+author: John Snow Labs
+name: ethix4context12
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ethix4context12` is a English model originally trained by Somisetty2347.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ethix4context12_en_5.5.1_3.0_1737626900081.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ethix4context12_en_5.5.1_3.0_1737626900081.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("ethix4context12","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("ethix4context12", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ethix4context12|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|244.0 MB|
+
+## References
+
+https://huggingface.co/Somisetty2347/Ethix4context12
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-ethix4context12_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-ethix4context12_pipeline_en.md
new file mode 100644
index 00000000000000..2ffe67eaeffedb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-ethix4context12_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ethix4context12_pipeline pipeline DistilBertForTokenClassification from Somisetty2347
+author: John Snow Labs
+name: ethix4context12_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ethix4context12_pipeline` is a English model originally trained by Somisetty2347.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ethix4context12_pipeline_en_5.5.1_3.0_1737626920786.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ethix4context12_pipeline_en_5.5.1_3.0_1737626920786.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ethix4context12_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ethix4context12_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ethix4context12_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|244.0 MB|
+
+## References
+
+https://huggingface.co/Somisetty2347/Ethix4context12
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-ethix4context_en.md b/docs/_posts/ahmedlone127/2025-01-23-ethix4context_en.md
new file mode 100644
index 00000000000000..913e50cf7e232b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-ethix4context_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ethix4context DistilBertForTokenClassification from Somisetty2347
+author: John Snow Labs
+name: ethix4context
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ethix4context` is a English model originally trained by Somisetty2347.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ethix4context_en_5.5.1_3.0_1737627649811.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ethix4context_en_5.5.1_3.0_1737627649811.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("ethix4context","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("ethix4context", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ethix4context|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|244.0 MB|
+
+## References
+
+https://huggingface.co/Somisetty2347/Ethix4context
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-ethix4context_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-ethix4context_pipeline_en.md
new file mode 100644
index 00000000000000..ff7ea9c1888f4f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-ethix4context_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ethix4context_pipeline pipeline DistilBertForTokenClassification from Somisetty2347
+author: John Snow Labs
+name: ethix4context_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ethix4context_pipeline` is a English model originally trained by Somisetty2347.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ethix4context_pipeline_en_5.5.1_3.0_1737627674389.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ethix4context_pipeline_en_5.5.1_3.0_1737627674389.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ethix4context_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ethix4context_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ethix4context_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|244.0 MB|
+
+## References
+
+https://huggingface.co/Somisetty2347/Ethix4context
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-farabi_en.md b/docs/_posts/ahmedlone127/2025-01-23-farabi_en.md
new file mode 100644
index 00000000000000..2ffa31f81358f8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-farabi_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English farabi XlmRoBertaEmbeddings from blaze187
+author: John Snow Labs
+name: farabi
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`farabi` is a English model originally trained by blaze187.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/farabi_en_5.5.1_3.0_1737668810689.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/farabi_en_5.5.1_3.0_1737668810689.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("farabi","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("farabi","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|farabi|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|981.3 MB|
+
+## References
+
+https://huggingface.co/blaze187/farabi
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-farabi_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-farabi_pipeline_en.md
new file mode 100644
index 00000000000000..c924aaba7110d5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-farabi_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English farabi_pipeline pipeline XlmRoBertaEmbeddings from blaze187
+author: John Snow Labs
+name: farabi_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`farabi_pipeline` is a English model originally trained by blaze187.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/farabi_pipeline_en_5.5.1_3.0_1737668886673.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/farabi_pipeline_en_5.5.1_3.0_1737668886673.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("farabi_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("farabi_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|farabi_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|981.3 MB|
+
+## References
+
+https://huggingface.co/blaze187/farabi
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-fb_improved_zeroshot_en.md b/docs/_posts/ahmedlone127/2025-01-23-fb_improved_zeroshot_en.md
new file mode 100644
index 00000000000000..d92750466f5e05
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-fb_improved_zeroshot_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English fb_improved_zeroshot BartForZeroShotClassification from oigele
+author: John Snow Labs
+name: fb_improved_zeroshot
+date: 2025-01-23
+tags: [en, open_source, onnx, zero_shot, bart]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BartForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fb_improved_zeroshot` is a English model originally trained by oigele.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fb_improved_zeroshot_en_5.5.1_3.0_1737638967141.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fb_improved_zeroshot_en_5.5.1_3.0_1737638967141.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+zeroShotClassifier  = BartForZeroShotClassification.pretrained("fb_improved_zeroshot","en") \
+     .setInputCols(["document","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, zeroShotClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val zeroShotClassifier  = BartForZeroShotClassification.pretrained("fb_improved_zeroshot", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, zeroShotClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fb_improved_zeroshot|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/oigele/Fb_improved_zeroshot
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-fb_improved_zeroshot_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-fb_improved_zeroshot_pipeline_en.md
new file mode 100644
index 00000000000000..71537b58a3f527
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-fb_improved_zeroshot_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English fb_improved_zeroshot_pipeline pipeline BartForZeroShotClassification from oigele
+author: John Snow Labs
+name: fb_improved_zeroshot_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fb_improved_zeroshot_pipeline` is a English model originally trained by oigele.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fb_improved_zeroshot_pipeline_en_5.5.1_3.0_1737639062566.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fb_improved_zeroshot_pipeline_en_5.5.1_3.0_1737639062566.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fb_improved_zeroshot_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fb_improved_zeroshot_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fb_improved_zeroshot_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/oigele/Fb_improved_zeroshot
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BartForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-feel_italian_finetuned_pro_emit_correlations_en.md b/docs/_posts/ahmedlone127/2025-01-23-feel_italian_finetuned_pro_emit_correlations_en.md
new file mode 100644
index 00000000000000..2861b726baaa71
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-feel_italian_finetuned_pro_emit_correlations_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English feel_italian_finetuned_pro_emit_correlations CamemBertForSequenceClassification from lupobricco
+author: John Snow Labs
+name: feel_italian_finetuned_pro_emit_correlations
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, camembert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`feel_italian_finetuned_pro_emit_correlations` is a English model originally trained by lupobricco.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/feel_italian_finetuned_pro_emit_correlations_en_5.5.1_3.0_1737628603285.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/feel_italian_finetuned_pro_emit_correlations_en_5.5.1_3.0_1737628603285.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = CamemBertForSequenceClassification.pretrained("feel_italian_finetuned_pro_emit_correlations","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = CamemBertForSequenceClassification.pretrained("feel_italian_finetuned_pro_emit_correlations", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|feel_italian_finetuned_pro_emit_correlations|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|402.7 MB|
+
+## References
+
+https://huggingface.co/lupobricco/feel_it_finetuned_pro_emit_correlations
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-feel_italian_finetuned_pro_emit_correlations_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-feel_italian_finetuned_pro_emit_correlations_pipeline_en.md
new file mode 100644
index 00000000000000..2fab190f808bb3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-feel_italian_finetuned_pro_emit_correlations_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English feel_italian_finetuned_pro_emit_correlations_pipeline pipeline CamemBertForSequenceClassification from lupobricco
+author: John Snow Labs
+name: feel_italian_finetuned_pro_emit_correlations_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`feel_italian_finetuned_pro_emit_correlations_pipeline` is a English model originally trained by lupobricco.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/feel_italian_finetuned_pro_emit_correlations_pipeline_en_5.5.1_3.0_1737628630999.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/feel_italian_finetuned_pro_emit_correlations_pipeline_en_5.5.1_3.0_1737628630999.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("feel_italian_finetuned_pro_emit_correlations_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("feel_italian_finetuned_pro_emit_correlations_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|feel_italian_finetuned_pro_emit_correlations_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|402.8 MB|
+
+## References
+
+https://huggingface.co/lupobricco/feel_it_finetuned_pro_emit_correlations
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-fierro_5_en.md b/docs/_posts/ahmedlone127/2025-01-23-fierro_5_en.md
new file mode 100644
index 00000000000000..e2f34656126334
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-fierro_5_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English fierro_5 DistilBertForQuestionAnswering from Kinga1BK
+author: John Snow Labs
+name: fierro_5
+date: 2025-01-23
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fierro_5` is a English model originally trained by Kinga1BK.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fierro_5_en_5.5.1_3.0_1737660365563.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fierro_5_en_5.5.1_3.0_1737660365563.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("fierro_5","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("fierro_5", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fierro_5|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Kinga1BK/FIERRO_5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-fierro_5_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-fierro_5_pipeline_en.md
new file mode 100644
index 00000000000000..050e716546154a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-fierro_5_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English fierro_5_pipeline pipeline DistilBertForQuestionAnswering from Kinga1BK
+author: John Snow Labs
+name: fierro_5_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fierro_5_pipeline` is a English model originally trained by Kinga1BK.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fierro_5_pipeline_en_5.5.1_3.0_1737660380593.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fierro_5_pipeline_en_5.5.1_3.0_1737660380593.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fierro_5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fierro_5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fierro_5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Kinga1BK/FIERRO_5
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-finbert_basevocab_cased_en.md b/docs/_posts/ahmedlone127/2025-01-23-finbert_basevocab_cased_en.md
new file mode 100644
index 00000000000000..4fc67ac4a2904f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-finbert_basevocab_cased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finbert_basevocab_cased BertEmbeddings from radmada
+author: John Snow Labs
+name: finbert_basevocab_cased
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finbert_basevocab_cased` is a English model originally trained by radmada.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finbert_basevocab_cased_en_5.5.1_3.0_1737637147681.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finbert_basevocab_cased_en_5.5.1_3.0_1737637147681.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("finbert_basevocab_cased","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("finbert_basevocab_cased","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finbert_basevocab_cased|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/radmada/FinBERT-BaseVocab-Cased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-finbert_basevocab_cased_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-finbert_basevocab_cased_pipeline_en.md
new file mode 100644
index 00000000000000..b245c13f5d82ba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-finbert_basevocab_cased_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finbert_basevocab_cased_pipeline pipeline BertEmbeddings from radmada
+author: John Snow Labs
+name: finbert_basevocab_cased_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finbert_basevocab_cased_pipeline` is a English model originally trained by radmada.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finbert_basevocab_cased_pipeline_en_5.5.1_3.0_1737637170114.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finbert_basevocab_cased_pipeline_en_5.5.1_3.0_1737637170114.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finbert_basevocab_cased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finbert_basevocab_cased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finbert_basevocab_cased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/radmada/FinBERT-BaseVocab-Cased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-fine_tuned_distilbert_hf_chunks_en.md b/docs/_posts/ahmedlone127/2025-01-23-fine_tuned_distilbert_hf_chunks_en.md
new file mode 100644
index 00000000000000..79fc51b35cfdde
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-fine_tuned_distilbert_hf_chunks_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English fine_tuned_distilbert_hf_chunks DistilBertForSequenceClassification from vcolella
+author: John Snow Labs
+name: fine_tuned_distilbert_hf_chunks
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_distilbert_hf_chunks` is a English model originally trained by vcolella.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_distilbert_hf_chunks_en_5.5.1_3.0_1737650001957.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_distilbert_hf_chunks_en_5.5.1_3.0_1737650001957.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("fine_tuned_distilbert_hf_chunks","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("fine_tuned_distilbert_hf_chunks", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_distilbert_hf_chunks|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|252.4 MB|
+
+## References
+
+https://huggingface.co/vcolella/fine-tuned-distilbert-hf_chunks
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-fine_tuned_distilbert_hf_chunks_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-fine_tuned_distilbert_hf_chunks_pipeline_en.md
new file mode 100644
index 00000000000000..65b2b7cb6756f0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-fine_tuned_distilbert_hf_chunks_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English fine_tuned_distilbert_hf_chunks_pipeline pipeline DistilBertForSequenceClassification from vcolella
+author: John Snow Labs
+name: fine_tuned_distilbert_hf_chunks_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_distilbert_hf_chunks_pipeline` is a English model originally trained by vcolella.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_distilbert_hf_chunks_pipeline_en_5.5.1_3.0_1737650021885.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_distilbert_hf_chunks_pipeline_en_5.5.1_3.0_1737650021885.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fine_tuned_distilbert_hf_chunks_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fine_tuned_distilbert_hf_chunks_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_distilbert_hf_chunks_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|252.5 MB|
+
+## References
+
+https://huggingface.co/vcolella/fine-tuned-distilbert-hf_chunks
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-fine_tuned_t5_sales_report_en.md b/docs/_posts/ahmedlone127/2025-01-23-fine_tuned_t5_sales_report_en.md
new file mode 100644
index 00000000000000..defa60fa19b7ff
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-fine_tuned_t5_sales_report_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English fine_tuned_t5_sales_report T5Transformer from SubhaL
+author: John Snow Labs
+name: fine_tuned_t5_sales_report
+date: 2025-01-23
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_t5_sales_report` is a English model originally trained by SubhaL.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_sales_report_en_5.5.1_3.0_1737633833803.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_sales_report_en_5.5.1_3.0_1737633833803.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("fine_tuned_t5_sales_report","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("fine_tuned_t5_sales_report", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_t5_sales_report|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|269.2 MB|
+
+## References
+
+https://huggingface.co/SubhaL/fine-tuned-t5-sales-report
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-fine_tuned_t5_sales_report_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-fine_tuned_t5_sales_report_pipeline_en.md
new file mode 100644
index 00000000000000..dc918e69a19d1d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-fine_tuned_t5_sales_report_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English fine_tuned_t5_sales_report_pipeline pipeline T5Transformer from SubhaL
+author: John Snow Labs
+name: fine_tuned_t5_sales_report_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_t5_sales_report_pipeline` is a English model originally trained by SubhaL.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_sales_report_pipeline_en_5.5.1_3.0_1737633852073.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_sales_report_pipeline_en_5.5.1_3.0_1737633852073.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fine_tuned_t5_sales_report_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fine_tuned_t5_sales_report_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_t5_sales_report_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|269.2 MB|
+
+## References
+
+https://huggingface.co/SubhaL/fine-tuned-t5-sales-report
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-finetuned_distilbert_yelp_en.md b/docs/_posts/ahmedlone127/2025-01-23-finetuned_distilbert_yelp_en.md
new file mode 100644
index 00000000000000..fbf517ee87d363
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-finetuned_distilbert_yelp_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuned_distilbert_yelp DistilBertForSequenceClassification from superchillbasedpogger
+author: John Snow Labs
+name: finetuned_distilbert_yelp
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_distilbert_yelp` is a English model originally trained by superchillbasedpogger.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_distilbert_yelp_en_5.5.1_3.0_1737650267582.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_distilbert_yelp_en_5.5.1_3.0_1737650267582.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuned_distilbert_yelp","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuned_distilbert_yelp", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_distilbert_yelp|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/superchillbasedpogger/finetuned-distilbert-yelp
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-finetuned_distilbert_yelp_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-finetuned_distilbert_yelp_pipeline_en.md
new file mode 100644
index 00000000000000..335597b7a19b0e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-finetuned_distilbert_yelp_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuned_distilbert_yelp_pipeline pipeline DistilBertForSequenceClassification from superchillbasedpogger
+author: John Snow Labs
+name: finetuned_distilbert_yelp_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_distilbert_yelp_pipeline` is a English model originally trained by superchillbasedpogger.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_distilbert_yelp_pipeline_en_5.5.1_3.0_1737650281461.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_distilbert_yelp_pipeline_en_5.5.1_3.0_1737650281461.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuned_distilbert_yelp_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuned_distilbert_yelp_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_distilbert_yelp_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/superchillbasedpogger/finetuned-distilbert-yelp
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-finetuned_roberta_bias_classification_en.md b/docs/_posts/ahmedlone127/2025-01-23-finetuned_roberta_bias_classification_en.md
new file mode 100644
index 00000000000000..a115a739e4c5e1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-finetuned_roberta_bias_classification_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuned_roberta_bias_classification RoBertaForSequenceClassification from charisgao
+author: John Snow Labs
+name: finetuned_roberta_bias_classification
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_roberta_bias_classification` is a English model originally trained by charisgao.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_roberta_bias_classification_en_5.5.1_3.0_1737671962846.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_roberta_bias_classification_en_5.5.1_3.0_1737671962846.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("finetuned_roberta_bias_classification","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("finetuned_roberta_bias_classification", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_roberta_bias_classification|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|426.5 MB|
+
+## References
+
+https://huggingface.co/charisgao/finetuned-roberta-bias-classification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-finetuned_roberta_bias_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-finetuned_roberta_bias_classification_pipeline_en.md
new file mode 100644
index 00000000000000..2cdfcb7748e014
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-finetuned_roberta_bias_classification_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuned_roberta_bias_classification_pipeline pipeline RoBertaForSequenceClassification from charisgao
+author: John Snow Labs
+name: finetuned_roberta_bias_classification_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_roberta_bias_classification_pipeline` is a English model originally trained by charisgao.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_roberta_bias_classification_pipeline_en_5.5.1_3.0_1737672003259.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_roberta_bias_classification_pipeline_en_5.5.1_3.0_1737672003259.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuned_roberta_bias_classification_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuned_roberta_bias_classification_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_roberta_bias_classification_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|426.6 MB|
+
+## References
+
+https://huggingface.co/charisgao/finetuned-roberta-bias-classification
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-finetuning_sentiment_model_3000_samples_jmdrst_en.md b/docs/_posts/ahmedlone127/2025-01-23-finetuning_sentiment_model_3000_samples_jmdrst_en.md
new file mode 100644
index 00000000000000..539e985168134f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-finetuning_sentiment_model_3000_samples_jmdrst_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_jmdrst DistilBertForSequenceClassification from jmdrst
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_jmdrst
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_jmdrst` is a English model originally trained by jmdrst.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_jmdrst_en_5.5.1_3.0_1737650382548.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_jmdrst_en_5.5.1_3.0_1737650382548.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_jmdrst","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_jmdrst", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_jmdrst|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/jmdrst/finetuning-sentiment-model-3000-samples
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-finetuning_sentiment_model_3000_samples_jmdrst_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-finetuning_sentiment_model_3000_samples_jmdrst_pipeline_en.md
new file mode 100644
index 00000000000000..830ec00278c4a7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-finetuning_sentiment_model_3000_samples_jmdrst_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_jmdrst_pipeline pipeline DistilBertForSequenceClassification from jmdrst
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_jmdrst_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_jmdrst_pipeline` is a English model originally trained by jmdrst.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_jmdrst_pipeline_en_5.5.1_3.0_1737650397037.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_jmdrst_pipeline_en_5.5.1_3.0_1737650397037.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuning_sentiment_model_3000_samples_jmdrst_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuning_sentiment_model_3000_samples_jmdrst_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_jmdrst_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/jmdrst/finetuning-sentiment-model-3000-samples
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-finetuning_sentiment_model_3000_samples_ricardopoleo_en.md b/docs/_posts/ahmedlone127/2025-01-23-finetuning_sentiment_model_3000_samples_ricardopoleo_en.md
new file mode 100644
index 00000000000000..f4db3e50177139
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-finetuning_sentiment_model_3000_samples_ricardopoleo_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_ricardopoleo DistilBertForSequenceClassification from RicardoPoleo
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_ricardopoleo
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_ricardopoleo` is a English model originally trained by RicardoPoleo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_ricardopoleo_en_5.5.1_3.0_1737650578711.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_ricardopoleo_en_5.5.1_3.0_1737650578711.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_ricardopoleo","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_ricardopoleo", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_ricardopoleo|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/RicardoPoleo/finetuning-sentiment-model-3000-samples
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-finetuning_sentiment_model_3000_samples_ricardopoleo_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-finetuning_sentiment_model_3000_samples_ricardopoleo_pipeline_en.md
new file mode 100644
index 00000000000000..b32a77954ed1ba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-finetuning_sentiment_model_3000_samples_ricardopoleo_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_ricardopoleo_pipeline pipeline DistilBertForSequenceClassification from RicardoPoleo
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_ricardopoleo_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_ricardopoleo_pipeline` is a English model originally trained by RicardoPoleo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_ricardopoleo_pipeline_en_5.5.1_3.0_1737650592332.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_ricardopoleo_pipeline_en_5.5.1_3.0_1737650592332.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuning_sentiment_model_3000_samples_ricardopoleo_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuning_sentiment_model_3000_samples_ricardopoleo_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_ricardopoleo_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/RicardoPoleo/finetuning-sentiment-model-3000-samples
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-finetuning_sentiment_model_3000_samples_salwa2026_en.md b/docs/_posts/ahmedlone127/2025-01-23-finetuning_sentiment_model_3000_samples_salwa2026_en.md
new file mode 100644
index 00000000000000..382bebffabb842
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-finetuning_sentiment_model_3000_samples_salwa2026_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_salwa2026 DistilBertForSequenceClassification from Salwa2026
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_salwa2026
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_salwa2026` is a English model originally trained by Salwa2026.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_salwa2026_en_5.5.1_3.0_1737650087287.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_salwa2026_en_5.5.1_3.0_1737650087287.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_salwa2026","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_salwa2026", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_salwa2026|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Salwa2026/finetuning-sentiment-model-3000-samples
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-finetuning_sentiment_model_3000_samples_salwa2026_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-finetuning_sentiment_model_3000_samples_salwa2026_pipeline_en.md
new file mode 100644
index 00000000000000..5f16713745afef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-finetuning_sentiment_model_3000_samples_salwa2026_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_salwa2026_pipeline pipeline DistilBertForSequenceClassification from Salwa2026
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_salwa2026_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_salwa2026_pipeline` is a English model originally trained by Salwa2026.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_salwa2026_pipeline_en_5.5.1_3.0_1737650100583.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_salwa2026_pipeline_en_5.5.1_3.0_1737650100583.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuning_sentiment_model_3000_samples_salwa2026_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuning_sentiment_model_3000_samples_salwa2026_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_salwa2026_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Salwa2026/finetuning-sentiment-model-3000-samples
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-flan_t5_base_samsum_jetmaxx_en.md b/docs/_posts/ahmedlone127/2025-01-23-flan_t5_base_samsum_jetmaxx_en.md
new file mode 100644
index 00000000000000..9b81a5daf3583c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-flan_t5_base_samsum_jetmaxx_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English flan_t5_base_samsum_jetmaxx T5Transformer from Jetmaxx
+author: John Snow Labs
+name: flan_t5_base_samsum_jetmaxx
+date: 2025-01-23
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_base_samsum_jetmaxx` is a English model originally trained by Jetmaxx.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_base_samsum_jetmaxx_en_5.5.1_3.0_1737635394237.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_base_samsum_jetmaxx_en_5.5.1_3.0_1737635394237.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("flan_t5_base_samsum_jetmaxx","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("flan_t5_base_samsum_jetmaxx", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_base_samsum_jetmaxx|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Jetmaxx/flan-t5-base-samsum
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-flan_t5_base_samsum_jetmaxx_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-flan_t5_base_samsum_jetmaxx_pipeline_en.md
new file mode 100644
index 00000000000000..394545cee0fef2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-flan_t5_base_samsum_jetmaxx_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English flan_t5_base_samsum_jetmaxx_pipeline pipeline T5Transformer from Jetmaxx
+author: John Snow Labs
+name: flan_t5_base_samsum_jetmaxx_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_base_samsum_jetmaxx_pipeline` is a English model originally trained by Jetmaxx.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_base_samsum_jetmaxx_pipeline_en_5.5.1_3.0_1737635448092.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_base_samsum_jetmaxx_pipeline_en_5.5.1_3.0_1737635448092.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("flan_t5_base_samsum_jetmaxx_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("flan_t5_base_samsum_jetmaxx_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_base_samsum_jetmaxx_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Jetmaxx/flan-t5-base-samsum
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-flan_t5_rouge_squad_qg_testf_en.md b/docs/_posts/ahmedlone127/2025-01-23-flan_t5_rouge_squad_qg_testf_en.md
new file mode 100644
index 00000000000000..191d16615290a2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-flan_t5_rouge_squad_qg_testf_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English flan_t5_rouge_squad_qg_testf T5Transformer from devagonal
+author: John Snow Labs
+name: flan_t5_rouge_squad_qg_testf
+date: 2025-01-23
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_rouge_squad_qg_testf` is a English model originally trained by devagonal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_rouge_squad_qg_testf_en_5.5.1_3.0_1737633558307.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_rouge_squad_qg_testf_en_5.5.1_3.0_1737633558307.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("flan_t5_rouge_squad_qg_testf","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("flan_t5_rouge_squad_qg_testf", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_rouge_squad_qg_testf|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|349.8 MB|
+
+## References
+
+https://huggingface.co/devagonal/flan-t5-rouge-squad-qg-testf
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-flan_t5_rouge_squad_qg_testf_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-flan_t5_rouge_squad_qg_testf_pipeline_en.md
new file mode 100644
index 00000000000000..5f9efb9d6a9c48
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-flan_t5_rouge_squad_qg_testf_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English flan_t5_rouge_squad_qg_testf_pipeline pipeline T5Transformer from devagonal
+author: John Snow Labs
+name: flan_t5_rouge_squad_qg_testf_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_rouge_squad_qg_testf_pipeline` is a English model originally trained by devagonal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_rouge_squad_qg_testf_pipeline_en_5.5.1_3.0_1737633576596.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_rouge_squad_qg_testf_pipeline_en_5.5.1_3.0_1737633576596.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("flan_t5_rouge_squad_qg_testf_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("flan_t5_rouge_squad_qg_testf_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_rouge_squad_qg_testf_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|349.8 MB|
+
+## References
+
+https://huggingface.co/devagonal/flan-t5-rouge-squad-qg-testf
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-flan_t5_small_tuned_tech_docs_en.md b/docs/_posts/ahmedlone127/2025-01-23-flan_t5_small_tuned_tech_docs_en.md
new file mode 100644
index 00000000000000..7087f1befab0e8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-flan_t5_small_tuned_tech_docs_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English flan_t5_small_tuned_tech_docs T5Transformer from saidsef
+author: John Snow Labs
+name: flan_t5_small_tuned_tech_docs
+date: 2025-01-23
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_small_tuned_tech_docs` is a English model originally trained by saidsef.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_small_tuned_tech_docs_en_5.5.1_3.0_1737635596284.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_small_tuned_tech_docs_en_5.5.1_3.0_1737635596284.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("flan_t5_small_tuned_tech_docs","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("flan_t5_small_tuned_tech_docs", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_small_tuned_tech_docs|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|349.8 MB|
+
+## References
+
+https://huggingface.co/saidsef/flan-t5-small-tuned-tech-docs
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-flan_t5_small_tuned_tech_docs_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-flan_t5_small_tuned_tech_docs_pipeline_en.md
new file mode 100644
index 00000000000000..0e8dbc37168c8a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-flan_t5_small_tuned_tech_docs_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English flan_t5_small_tuned_tech_docs_pipeline pipeline T5Transformer from saidsef
+author: John Snow Labs
+name: flan_t5_small_tuned_tech_docs_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_small_tuned_tech_docs_pipeline` is a English model originally trained by saidsef.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_small_tuned_tech_docs_pipeline_en_5.5.1_3.0_1737635615181.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_small_tuned_tech_docs_pipeline_en_5.5.1_3.0_1737635615181.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("flan_t5_small_tuned_tech_docs_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("flan_t5_small_tuned_tech_docs_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_small_tuned_tech_docs_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|349.8 MB|
+
+## References
+
+https://huggingface.co/saidsef/flan-t5-small-tuned-tech-docs
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-focal_loss_distillbert_en.md b/docs/_posts/ahmedlone127/2025-01-23-focal_loss_distillbert_en.md
new file mode 100644
index 00000000000000..6000cc4ef4a6d4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-focal_loss_distillbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English focal_loss_distillbert DistilBertForTokenClassification from pmpmp74832
+author: John Snow Labs
+name: focal_loss_distillbert
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`focal_loss_distillbert` is a English model originally trained by pmpmp74832.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/focal_loss_distillbert_en_5.5.1_3.0_1737627232209.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/focal_loss_distillbert_en_5.5.1_3.0_1737627232209.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("focal_loss_distillbert","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("focal_loss_distillbert", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|focal_loss_distillbert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|329.3 MB|
+
+## References
+
+https://huggingface.co/pmpmp74832/focal-loss-distillbert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-focal_loss_distillbert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-focal_loss_distillbert_pipeline_en.md
new file mode 100644
index 00000000000000..d0e816857bea03
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-focal_loss_distillbert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English focal_loss_distillbert_pipeline pipeline DistilBertForTokenClassification from pmpmp74832
+author: John Snow Labs
+name: focal_loss_distillbert_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`focal_loss_distillbert_pipeline` is a English model originally trained by pmpmp74832.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/focal_loss_distillbert_pipeline_en_5.5.1_3.0_1737627250466.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/focal_loss_distillbert_pipeline_en_5.5.1_3.0_1737627250466.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("focal_loss_distillbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("focal_loss_distillbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|focal_loss_distillbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|329.4 MB|
+
+## References
+
+https://huggingface.co/pmpmp74832/focal-loss-distillbert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-fold_4_model_deberta_en.md b/docs/_posts/ahmedlone127/2025-01-23-fold_4_model_deberta_en.md
new file mode 100644
index 00000000000000..e33dce87a1498e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-fold_4_model_deberta_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English fold_4_model_deberta DeBertaForSequenceClassification from Kuongan
+author: John Snow Labs
+name: fold_4_model_deberta
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fold_4_model_deberta` is a English model originally trained by Kuongan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fold_4_model_deberta_en_5.5.1_3.0_1737647745444.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fold_4_model_deberta_en_5.5.1_3.0_1737647745444.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("fold_4_model_deberta","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("fold_4_model_deberta", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fold_4_model_deberta|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|574.7 MB|
+
+## References
+
+https://huggingface.co/Kuongan/fold_4_model_deberta
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-fold_4_model_deberta_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-fold_4_model_deberta_pipeline_en.md
new file mode 100644
index 00000000000000..b58c0437771cf4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-fold_4_model_deberta_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English fold_4_model_deberta_pipeline pipeline DeBertaForSequenceClassification from Kuongan
+author: John Snow Labs
+name: fold_4_model_deberta_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fold_4_model_deberta_pipeline` is a English model originally trained by Kuongan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fold_4_model_deberta_pipeline_en_5.5.1_3.0_1737647815847.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fold_4_model_deberta_pipeline_en_5.5.1_3.0_1737647815847.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fold_4_model_deberta_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fold_4_model_deberta_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fold_4_model_deberta_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|574.7 MB|
+
+## References
+
+https://huggingface.co/Kuongan/fold_4_model_deberta
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-food_embeddings_en.md b/docs/_posts/ahmedlone127/2025-01-23-food_embeddings_en.md
new file mode 100644
index 00000000000000..9bf52e260f00c1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-food_embeddings_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English food_embeddings MPNetEmbeddings from jonny9f
+author: John Snow Labs
+name: food_embeddings
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`food_embeddings` is a English model originally trained by jonny9f.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/food_embeddings_en_5.5.1_3.0_1737670346338.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/food_embeddings_en_5.5.1_3.0_1737670346338.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("food_embeddings","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("food_embeddings","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|food_embeddings|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/jonny9f/food_embeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-food_embeddings_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-food_embeddings_pipeline_en.md
new file mode 100644
index 00000000000000..ad02763ebc363c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-food_embeddings_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English food_embeddings_pipeline pipeline MPNetEmbeddings from jonny9f
+author: John Snow Labs
+name: food_embeddings_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`food_embeddings_pipeline` is a English model originally trained by jonny9f.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/food_embeddings_pipeline_en_5.5.1_3.0_1737670368257.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/food_embeddings_pipeline_en_5.5.1_3.0_1737670368257.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("food_embeddings_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("food_embeddings_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|food_embeddings_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/jonny9f/food_embeddings
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-ft_thai_products_groupclassify_en.md b/docs/_posts/ahmedlone127/2025-01-23-ft_thai_products_groupclassify_en.md
new file mode 100644
index 00000000000000..38f193265f61f9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-ft_thai_products_groupclassify_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ft_thai_products_groupclassify CamemBertForSequenceClassification from StrangeSX
+author: John Snow Labs
+name: ft_thai_products_groupclassify
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, camembert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ft_thai_products_groupclassify` is a English model originally trained by StrangeSX.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ft_thai_products_groupclassify_en_5.5.1_3.0_1737628791834.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ft_thai_products_groupclassify_en_5.5.1_3.0_1737628791834.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = CamemBertForSequenceClassification.pretrained("ft_thai_products_groupclassify","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = CamemBertForSequenceClassification.pretrained("ft_thai_products_groupclassify", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ft_thai_products_groupclassify|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|394.4 MB|
+
+## References
+
+https://huggingface.co/StrangeSX/FT-Thai-Products-GroupClassify
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-ft_thai_products_groupclassify_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-ft_thai_products_groupclassify_pipeline_en.md
new file mode 100644
index 00000000000000..f7153be73f06f1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-ft_thai_products_groupclassify_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ft_thai_products_groupclassify_pipeline pipeline CamemBertForSequenceClassification from StrangeSX
+author: John Snow Labs
+name: ft_thai_products_groupclassify_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ft_thai_products_groupclassify_pipeline` is a English model originally trained by StrangeSX.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ft_thai_products_groupclassify_pipeline_en_5.5.1_3.0_1737628813023.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ft_thai_products_groupclassify_pipeline_en_5.5.1_3.0_1737628813023.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ft_thai_products_groupclassify_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ft_thai_products_groupclassify_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ft_thai_products_groupclassify_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|394.4 MB|
+
+## References
+
+https://huggingface.co/StrangeSX/FT-Thai-Products-GroupClassify
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-german_zeroshot_de.md b/docs/_posts/ahmedlone127/2025-01-23-german_zeroshot_de.md
new file mode 100644
index 00000000000000..23bf52733035ce
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-german_zeroshot_de.md
@@ -0,0 +1,96 @@
+---
+layout: model
+title: German german_zeroshot BertForZeroShotClassification from Sahajtomar
+author: John Snow Labs
+name: german_zeroshot
+date: 2025-01-23
+tags: [de, open_source, onnx, zero_shot, bert]
+task: Zero-Shot Classification
+language: de
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`german_zeroshot` is a German model originally trained by Sahajtomar.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/german_zeroshot_de_5.5.1_3.0_1737640916576.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/german_zeroshot_de_5.5.1_3.0_1737640916576.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+zeroShotClassifier  = BertForZeroShotClassification.pretrained("german_zeroshot","de") \
+     .setInputCols(["document","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, zeroShotClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val zeroShotClassifier  = BertForZeroShotClassification.pretrained("german_zeroshot", "de")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, zeroShotClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|german_zeroshot|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|de|
+|Size:|1.3 GB|
+
+## References
+
+References
+
+https://huggingface.co/Sahajtomar/German_Zeroshot
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-german_zeroshot_pipeline_de.md b/docs/_posts/ahmedlone127/2025-01-23-german_zeroshot_pipeline_de.md
new file mode 100644
index 00000000000000..9536dc45e1eed0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-german_zeroshot_pipeline_de.md
@@ -0,0 +1,72 @@
+---
+layout: model
+title: German german_zeroshot_pipeline pipeline BertForZeroShotClassification from Sahajtomar
+author: John Snow Labs
+name: german_zeroshot_pipeline
+date: 2025-01-23
+tags: [de, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: de
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`german_zeroshot_pipeline` is a German model originally trained by Sahajtomar.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/german_zeroshot_pipeline_de_5.5.1_3.0_1737640979587.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/german_zeroshot_pipeline_de_5.5.1_3.0_1737640979587.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("german_zeroshot_pipeline", lang = "de")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("german_zeroshot_pipeline", lang = "de")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|german_zeroshot_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|de|
+|Size:|1.3 GB|
+
+## References
+
+References
+
+https://huggingface.co/Sahajtomar/German_Zeroshot
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-gottbert_base_last_de.md b/docs/_posts/ahmedlone127/2025-01-23-gottbert_base_last_de.md
new file mode 100644
index 00000000000000..8681002465d6e2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-gottbert_base_last_de.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: German gottbert_base_last RoBertaEmbeddings from TUM
+author: John Snow Labs
+name: gottbert_base_last
+date: 2025-01-23
+tags: [de, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: de
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gottbert_base_last` is a German model originally trained by TUM.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gottbert_base_last_de_5.5.1_3.0_1737644016812.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gottbert_base_last_de_5.5.1_3.0_1737644016812.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("gottbert_base_last","de") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("gottbert_base_last","de") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gottbert_base_last|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|de|
+|Size:|470.6 MB|
+
+## References
+
+https://huggingface.co/TUM/GottBERT_base_last
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-gottbert_base_last_pipeline_de.md b/docs/_posts/ahmedlone127/2025-01-23-gottbert_base_last_pipeline_de.md
new file mode 100644
index 00000000000000..1b25d67183dfa9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-gottbert_base_last_pipeline_de.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: German gottbert_base_last_pipeline pipeline RoBertaEmbeddings from TUM
+author: John Snow Labs
+name: gottbert_base_last_pipeline
+date: 2025-01-23
+tags: [de, open_source, pipeline, onnx]
+task: Embeddings
+language: de
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gottbert_base_last_pipeline` is a German model originally trained by TUM.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gottbert_base_last_pipeline_de_5.5.1_3.0_1737644041653.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gottbert_base_last_pipeline_de_5.5.1_3.0_1737644041653.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gottbert_base_last_pipeline", lang = "de")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gottbert_base_last_pipeline", lang = "de")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gottbert_base_last_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|de|
+|Size:|470.7 MB|
+
+## References
+
+https://huggingface.co/TUM/GottBERT_base_last
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-harmaug_guard_en.md b/docs/_posts/ahmedlone127/2025-01-23-harmaug_guard_en.md
new file mode 100644
index 00000000000000..4f55071c81c2c1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-harmaug_guard_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English harmaug_guard DeBertaForSequenceClassification from hbseong
+author: John Snow Labs
+name: harmaug_guard
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`harmaug_guard` is a English model originally trained by hbseong.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/harmaug_guard_en_5.5.1_3.0_1737656880030.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/harmaug_guard_en_5.5.1_3.0_1737656880030.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("harmaug_guard","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("harmaug_guard", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|harmaug_guard|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/hbseong/HarmAug-Guard
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-harmaug_guard_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-harmaug_guard_pipeline_en.md
new file mode 100644
index 00000000000000..a6d1a2900c00fb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-harmaug_guard_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English harmaug_guard_pipeline pipeline DeBertaForSequenceClassification from hbseong
+author: John Snow Labs
+name: harmaug_guard_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`harmaug_guard_pipeline` is a English model originally trained by hbseong.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/harmaug_guard_pipeline_en_5.5.1_3.0_1737656966490.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/harmaug_guard_pipeline_en_5.5.1_3.0_1737656966490.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("harmaug_guard_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("harmaug_guard_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|harmaug_guard_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/hbseong/HarmAug-Guard
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-hf_token_classification_en.md b/docs/_posts/ahmedlone127/2025-01-23-hf_token_classification_en.md
new file mode 100644
index 00000000000000..075127e7dd5f2d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-hf_token_classification_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English hf_token_classification DistilBertForTokenClassification from ngchuchi
+author: John Snow Labs
+name: hf_token_classification
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hf_token_classification` is a English model originally trained by ngchuchi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hf_token_classification_en_5.5.1_3.0_1737627045885.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hf_token_classification_en_5.5.1_3.0_1737627045885.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("hf_token_classification","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("hf_token_classification", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hf_token_classification|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/ngchuchi/hf_token_classification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-hf_token_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-hf_token_classification_pipeline_en.md
new file mode 100644
index 00000000000000..fd6436cf064df3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-hf_token_classification_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English hf_token_classification_pipeline pipeline DistilBertForTokenClassification from ngchuchi
+author: John Snow Labs
+name: hf_token_classification_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hf_token_classification_pipeline` is a English model originally trained by ngchuchi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hf_token_classification_pipeline_en_5.5.1_3.0_1737627061556.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hf_token_classification_pipeline_en_5.5.1_3.0_1737627061556.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("hf_token_classification_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hf_token_classification_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hf_token_classification_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/ngchuchi/hf_token_classification
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-hscore_balanced_en.md b/docs/_posts/ahmedlone127/2025-01-23-hscore_balanced_en.md
new file mode 100644
index 00000000000000..3bb5e010828b28
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-hscore_balanced_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English hscore_balanced CamemBertForSequenceClassification from spidersouris
+author: John Snow Labs
+name: hscore_balanced
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, camembert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hscore_balanced` is a English model originally trained by spidersouris.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hscore_balanced_en_5.5.1_3.0_1737628601890.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hscore_balanced_en_5.5.1_3.0_1737628601890.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = CamemBertForSequenceClassification.pretrained("hscore_balanced","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = CamemBertForSequenceClassification.pretrained("hscore_balanced", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hscore_balanced|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|400.7 MB|
+
+## References
+
+https://huggingface.co/spidersouris/hscore-balanced
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-hscore_balanced_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-hscore_balanced_pipeline_en.md
new file mode 100644
index 00000000000000..5d6e695f41e2b4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-hscore_balanced_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English hscore_balanced_pipeline pipeline CamemBertForSequenceClassification from spidersouris
+author: John Snow Labs
+name: hscore_balanced_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hscore_balanced_pipeline` is a English model originally trained by spidersouris.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hscore_balanced_pipeline_en_5.5.1_3.0_1737628629766.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hscore_balanced_pipeline_en_5.5.1_3.0_1737628629766.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("hscore_balanced_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hscore_balanced_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hscore_balanced_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|400.7 MB|
+
+## References
+
+https://huggingface.co/spidersouris/hscore-balanced
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-hscorer_full_en.md b/docs/_posts/ahmedlone127/2025-01-23-hscorer_full_en.md
new file mode 100644
index 00000000000000..541fbd145aed4c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-hscorer_full_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English hscorer_full CamemBertForSequenceClassification from spidersouris
+author: John Snow Labs
+name: hscorer_full
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, camembert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hscorer_full` is a English model originally trained by spidersouris.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hscorer_full_en_5.5.1_3.0_1737628897185.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hscorer_full_en_5.5.1_3.0_1737628897185.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = CamemBertForSequenceClassification.pretrained("hscorer_full","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = CamemBertForSequenceClassification.pretrained("hscorer_full", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hscorer_full|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|414.3 MB|
+
+## References
+
+https://huggingface.co/spidersouris/hscorer-full
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-hscorer_full_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-hscorer_full_pipeline_en.md
new file mode 100644
index 00000000000000..4a898d2c6ca5fc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-hscorer_full_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English hscorer_full_pipeline pipeline CamemBertForSequenceClassification from spidersouris
+author: John Snow Labs
+name: hscorer_full_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hscorer_full_pipeline` is a English model originally trained by spidersouris.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hscorer_full_pipeline_en_5.5.1_3.0_1737628918532.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hscorer_full_pipeline_en_5.5.1_3.0_1737628918532.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("hscorer_full_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hscorer_full_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hscorer_full_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|414.4 MB|
+
+## References
+
+https://huggingface.co/spidersouris/hscorer-full
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-hub_report_20241202125641_en.md b/docs/_posts/ahmedlone127/2025-01-23-hub_report_20241202125641_en.md
new file mode 100644
index 00000000000000..0adc74a0fe2c21
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-hub_report_20241202125641_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English hub_report_20241202125641 MPNetForSequenceClassification from Kevinger
+author: John Snow Labs
+name: hub_report_20241202125641
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, mpnet]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hub_report_20241202125641` is a English model originally trained by Kevinger.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hub_report_20241202125641_en_5.5.1_3.0_1737642173443.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hub_report_20241202125641_en_5.5.1_3.0_1737642173443.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = MPNetForSequenceClassification.pretrained("hub_report_20241202125641","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = MPNetForSequenceClassification.pretrained("hub_report_20241202125641", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hub_report_20241202125641|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.2 MB|
+
+## References
+
+https://huggingface.co/Kevinger/Hub-Report-20241202125641
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-hub_report_20241202125641_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-hub_report_20241202125641_pipeline_en.md
new file mode 100644
index 00000000000000..dc8358d0299809
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-hub_report_20241202125641_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English hub_report_20241202125641_pipeline pipeline MPNetForSequenceClassification from Kevinger
+author: John Snow Labs
+name: hub_report_20241202125641_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hub_report_20241202125641_pipeline` is a English model originally trained by Kevinger.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hub_report_20241202125641_pipeline_en_5.5.1_3.0_1737642196186.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hub_report_20241202125641_pipeline_en_5.5.1_3.0_1737642196186.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("hub_report_20241202125641_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hub_report_20241202125641_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hub_report_20241202125641_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.2 MB|
+
+## References
+
+https://huggingface.co/Kevinger/Hub-Report-20241202125641
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- MPNetForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-hubert_common_voice_japanese_demo_kana_debug_50epochs_cosine_ja.md b/docs/_posts/ahmedlone127/2025-01-23-hubert_common_voice_japanese_demo_kana_debug_50epochs_cosine_ja.md
new file mode 100644
index 00000000000000..265222e411a2f0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-hubert_common_voice_japanese_demo_kana_debug_50epochs_cosine_ja.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Japanese hubert_common_voice_japanese_demo_kana_debug_50epochs_cosine HubertForCTC from utakumi
+author: John Snow Labs
+name: hubert_common_voice_japanese_demo_kana_debug_50epochs_cosine
+date: 2025-01-23
+tags: [ja, open_source, onnx, asr, hubert]
+task: Automatic Speech Recognition
+language: ja
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: HubertForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_common_voice_japanese_demo_kana_debug_50epochs_cosine` is a Japanese model originally trained by utakumi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_common_voice_japanese_demo_kana_debug_50epochs_cosine_ja_5.5.1_3.0_1737625774210.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_common_voice_japanese_demo_kana_debug_50epochs_cosine_ja_5.5.1_3.0_1737625774210.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = HubertForCTC.pretrained("hubert_common_voice_japanese_demo_kana_debug_50epochs_cosine","ja") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = HubertForCTC.pretrained("hubert_common_voice_japanese_demo_kana_debug_50epochs_cosine", "ja")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hubert_common_voice_japanese_demo_kana_debug_50epochs_cosine|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|ja|
+|Size:|698.2 MB|
+
+## References
+
+https://huggingface.co/utakumi/Hubert-common_voice-ja-demo-kana-debug-50epochs-cosine
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-hubert_common_voice_japanese_demo_kana_debug_50epochs_cosine_pipeline_ja.md b/docs/_posts/ahmedlone127/2025-01-23-hubert_common_voice_japanese_demo_kana_debug_50epochs_cosine_pipeline_ja.md
new file mode 100644
index 00000000000000..3eb9ec20754e65
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-hubert_common_voice_japanese_demo_kana_debug_50epochs_cosine_pipeline_ja.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Japanese hubert_common_voice_japanese_demo_kana_debug_50epochs_cosine_pipeline pipeline HubertForCTC from utakumi
+author: John Snow Labs
+name: hubert_common_voice_japanese_demo_kana_debug_50epochs_cosine_pipeline
+date: 2025-01-23
+tags: [ja, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: ja
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_common_voice_japanese_demo_kana_debug_50epochs_cosine_pipeline` is a Japanese model originally trained by utakumi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_common_voice_japanese_demo_kana_debug_50epochs_cosine_pipeline_ja_5.5.1_3.0_1737625820658.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_common_voice_japanese_demo_kana_debug_50epochs_cosine_pipeline_ja_5.5.1_3.0_1737625820658.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("hubert_common_voice_japanese_demo_kana_debug_50epochs_cosine_pipeline", lang = "ja")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hubert_common_voice_japanese_demo_kana_debug_50epochs_cosine_pipeline", lang = "ja")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hubert_common_voice_japanese_demo_kana_debug_50epochs_cosine_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ja|
+|Size:|698.2 MB|
+
+## References
+
+https://huggingface.co/utakumi/Hubert-common_voice-ja-demo-kana-debug-50epochs-cosine
+
+## Included Models
+
+- AudioAssembler
+- HubertForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-hubert_common_voice_japanese_demo_phonemes_cosine_3e_5_ja.md b/docs/_posts/ahmedlone127/2025-01-23-hubert_common_voice_japanese_demo_phonemes_cosine_3e_5_ja.md
new file mode 100644
index 00000000000000..b3d666f63265d4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-hubert_common_voice_japanese_demo_phonemes_cosine_3e_5_ja.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Japanese hubert_common_voice_japanese_demo_phonemes_cosine_3e_5 HubertForCTC from utakumi
+author: John Snow Labs
+name: hubert_common_voice_japanese_demo_phonemes_cosine_3e_5
+date: 2025-01-23
+tags: [ja, open_source, onnx, asr, hubert]
+task: Automatic Speech Recognition
+language: ja
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: HubertForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_common_voice_japanese_demo_phonemes_cosine_3e_5` is a Japanese model originally trained by utakumi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_common_voice_japanese_demo_phonemes_cosine_3e_5_ja_5.5.1_3.0_1737625836765.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_common_voice_japanese_demo_phonemes_cosine_3e_5_ja_5.5.1_3.0_1737625836765.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = HubertForCTC.pretrained("hubert_common_voice_japanese_demo_phonemes_cosine_3e_5","ja") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = HubertForCTC.pretrained("hubert_common_voice_japanese_demo_phonemes_cosine_3e_5", "ja")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hubert_common_voice_japanese_demo_phonemes_cosine_3e_5|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|ja|
+|Size:|698.0 MB|
+
+## References
+
+https://huggingface.co/utakumi/Hubert-common_voice-ja-demo-phonemes-cosine-3e-5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-hubert_common_voice_japanese_demo_phonemes_cosine_3e_5_pipeline_ja.md b/docs/_posts/ahmedlone127/2025-01-23-hubert_common_voice_japanese_demo_phonemes_cosine_3e_5_pipeline_ja.md
new file mode 100644
index 00000000000000..d260fb24c6167a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-hubert_common_voice_japanese_demo_phonemes_cosine_3e_5_pipeline_ja.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Japanese hubert_common_voice_japanese_demo_phonemes_cosine_3e_5_pipeline pipeline HubertForCTC from utakumi
+author: John Snow Labs
+name: hubert_common_voice_japanese_demo_phonemes_cosine_3e_5_pipeline
+date: 2025-01-23
+tags: [ja, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: ja
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_common_voice_japanese_demo_phonemes_cosine_3e_5_pipeline` is a Japanese model originally trained by utakumi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_common_voice_japanese_demo_phonemes_cosine_3e_5_pipeline_ja_5.5.1_3.0_1737625877844.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_common_voice_japanese_demo_phonemes_cosine_3e_5_pipeline_ja_5.5.1_3.0_1737625877844.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("hubert_common_voice_japanese_demo_phonemes_cosine_3e_5_pipeline", lang = "ja")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hubert_common_voice_japanese_demo_phonemes_cosine_3e_5_pipeline", lang = "ja")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hubert_common_voice_japanese_demo_phonemes_cosine_3e_5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ja|
+|Size:|698.0 MB|
+
+## References
+
+https://huggingface.co/utakumi/Hubert-common_voice-ja-demo-phonemes-cosine-3e-5
+
+## Included Models
+
+- AudioAssembler
+- HubertForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-hubert_common_voice_japanese_demo_roma_debug_40epochs_cosine_ja.md b/docs/_posts/ahmedlone127/2025-01-23-hubert_common_voice_japanese_demo_roma_debug_40epochs_cosine_ja.md
new file mode 100644
index 00000000000000..91931e0c6ba018
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-hubert_common_voice_japanese_demo_roma_debug_40epochs_cosine_ja.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Japanese hubert_common_voice_japanese_demo_roma_debug_40epochs_cosine HubertForCTC from utakumi
+author: John Snow Labs
+name: hubert_common_voice_japanese_demo_roma_debug_40epochs_cosine
+date: 2025-01-23
+tags: [ja, open_source, onnx, asr, hubert]
+task: Automatic Speech Recognition
+language: ja
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: HubertForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_common_voice_japanese_demo_roma_debug_40epochs_cosine` is a Japanese model originally trained by utakumi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_common_voice_japanese_demo_roma_debug_40epochs_cosine_ja_5.5.1_3.0_1737625382604.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_common_voice_japanese_demo_roma_debug_40epochs_cosine_ja_5.5.1_3.0_1737625382604.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = HubertForCTC.pretrained("hubert_common_voice_japanese_demo_roma_debug_40epochs_cosine","ja") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = HubertForCTC.pretrained("hubert_common_voice_japanese_demo_roma_debug_40epochs_cosine", "ja")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hubert_common_voice_japanese_demo_roma_debug_40epochs_cosine|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|ja|
+|Size:|697.9 MB|
+
+## References
+
+https://huggingface.co/utakumi/Hubert-common_voice-ja-demo-roma-debug-40epochs-cosine
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-hubert_common_voice_japanese_demo_roma_debug_40epochs_cosine_pipeline_ja.md b/docs/_posts/ahmedlone127/2025-01-23-hubert_common_voice_japanese_demo_roma_debug_40epochs_cosine_pipeline_ja.md
new file mode 100644
index 00000000000000..b52cfa73f93712
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-hubert_common_voice_japanese_demo_roma_debug_40epochs_cosine_pipeline_ja.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Japanese hubert_common_voice_japanese_demo_roma_debug_40epochs_cosine_pipeline pipeline HubertForCTC from utakumi
+author: John Snow Labs
+name: hubert_common_voice_japanese_demo_roma_debug_40epochs_cosine_pipeline
+date: 2025-01-23
+tags: [ja, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: ja
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_common_voice_japanese_demo_roma_debug_40epochs_cosine_pipeline` is a Japanese model originally trained by utakumi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_common_voice_japanese_demo_roma_debug_40epochs_cosine_pipeline_ja_5.5.1_3.0_1737625423313.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_common_voice_japanese_demo_roma_debug_40epochs_cosine_pipeline_ja_5.5.1_3.0_1737625423313.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("hubert_common_voice_japanese_demo_roma_debug_40epochs_cosine_pipeline", lang = "ja")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hubert_common_voice_japanese_demo_roma_debug_40epochs_cosine_pipeline", lang = "ja")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hubert_common_voice_japanese_demo_roma_debug_40epochs_cosine_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ja|
+|Size:|697.9 MB|
+
+## References
+
+https://huggingface.co/utakumi/Hubert-common_voice-ja-demo-roma-debug-40epochs-cosine
+
+## Included Models
+
+- AudioAssembler
+- HubertForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-hubert_common_voice_phoneme_ctc_zero_infinity_ja.md b/docs/_posts/ahmedlone127/2025-01-23-hubert_common_voice_phoneme_ctc_zero_infinity_ja.md
new file mode 100644
index 00000000000000..b6925e70daa679
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-hubert_common_voice_phoneme_ctc_zero_infinity_ja.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Japanese hubert_common_voice_phoneme_ctc_zero_infinity HubertForCTC from utakumi
+author: John Snow Labs
+name: hubert_common_voice_phoneme_ctc_zero_infinity
+date: 2025-01-23
+tags: [ja, open_source, onnx, asr, hubert]
+task: Automatic Speech Recognition
+language: ja
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: HubertForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_common_voice_phoneme_ctc_zero_infinity` is a Japanese model originally trained by utakumi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_common_voice_phoneme_ctc_zero_infinity_ja_5.5.1_3.0_1737625544100.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_common_voice_phoneme_ctc_zero_infinity_ja_5.5.1_3.0_1737625544100.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = HubertForCTC.pretrained("hubert_common_voice_phoneme_ctc_zero_infinity","ja") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = HubertForCTC.pretrained("hubert_common_voice_phoneme_ctc_zero_infinity", "ja")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hubert_common_voice_phoneme_ctc_zero_infinity|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|ja|
+|Size:|697.9 MB|
+
+## References
+
+https://huggingface.co/utakumi/Hubert-common_voice-phoneme-ctc_zero_infinity
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-hubert_common_voice_phoneme_ctc_zero_infinity_pipeline_ja.md b/docs/_posts/ahmedlone127/2025-01-23-hubert_common_voice_phoneme_ctc_zero_infinity_pipeline_ja.md
new file mode 100644
index 00000000000000..c40490d7fc7fbe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-hubert_common_voice_phoneme_ctc_zero_infinity_pipeline_ja.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Japanese hubert_common_voice_phoneme_ctc_zero_infinity_pipeline pipeline HubertForCTC from utakumi
+author: John Snow Labs
+name: hubert_common_voice_phoneme_ctc_zero_infinity_pipeline
+date: 2025-01-23
+tags: [ja, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: ja
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_common_voice_phoneme_ctc_zero_infinity_pipeline` is a Japanese model originally trained by utakumi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_common_voice_phoneme_ctc_zero_infinity_pipeline_ja_5.5.1_3.0_1737625584810.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_common_voice_phoneme_ctc_zero_infinity_pipeline_ja_5.5.1_3.0_1737625584810.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("hubert_common_voice_phoneme_ctc_zero_infinity_pipeline", lang = "ja")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hubert_common_voice_phoneme_ctc_zero_infinity_pipeline", lang = "ja")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hubert_common_voice_phoneme_ctc_zero_infinity_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ja|
+|Size:|697.9 MB|
+
+## References
+
+https://huggingface.co/utakumi/Hubert-common_voice-phoneme-ctc_zero_infinity
+
+## Included Models
+
+- AudioAssembler
+- HubertForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-hubert_common_voice_phoneme_debug_warmup500_ja.md b/docs/_posts/ahmedlone127/2025-01-23-hubert_common_voice_phoneme_debug_warmup500_ja.md
new file mode 100644
index 00000000000000..19085ca139f3f9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-hubert_common_voice_phoneme_debug_warmup500_ja.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Japanese hubert_common_voice_phoneme_debug_warmup500 HubertForCTC from utakumi
+author: John Snow Labs
+name: hubert_common_voice_phoneme_debug_warmup500
+date: 2025-01-23
+tags: [ja, open_source, onnx, asr, hubert]
+task: Automatic Speech Recognition
+language: ja
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: HubertForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_common_voice_phoneme_debug_warmup500` is a Japanese model originally trained by utakumi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_common_voice_phoneme_debug_warmup500_ja_5.5.1_3.0_1737625565418.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_common_voice_phoneme_debug_warmup500_ja_5.5.1_3.0_1737625565418.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = HubertForCTC.pretrained("hubert_common_voice_phoneme_debug_warmup500","ja") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = HubertForCTC.pretrained("hubert_common_voice_phoneme_debug_warmup500", "ja")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hubert_common_voice_phoneme_debug_warmup500|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|ja|
+|Size:|698.0 MB|
+
+## References
+
+https://huggingface.co/utakumi/Hubert-common_voice-phoneme-debug-warmup500
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-hubert_common_voice_phoneme_debug_warmup500_pipeline_ja.md b/docs/_posts/ahmedlone127/2025-01-23-hubert_common_voice_phoneme_debug_warmup500_pipeline_ja.md
new file mode 100644
index 00000000000000..162307a327eb6e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-hubert_common_voice_phoneme_debug_warmup500_pipeline_ja.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Japanese hubert_common_voice_phoneme_debug_warmup500_pipeline pipeline HubertForCTC from utakumi
+author: John Snow Labs
+name: hubert_common_voice_phoneme_debug_warmup500_pipeline
+date: 2025-01-23
+tags: [ja, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: ja
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_common_voice_phoneme_debug_warmup500_pipeline` is a Japanese model originally trained by utakumi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_common_voice_phoneme_debug_warmup500_pipeline_ja_5.5.1_3.0_1737625609016.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_common_voice_phoneme_debug_warmup500_pipeline_ja_5.5.1_3.0_1737625609016.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("hubert_common_voice_phoneme_debug_warmup500_pipeline", lang = "ja")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hubert_common_voice_phoneme_debug_warmup500_pipeline", lang = "ja")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hubert_common_voice_phoneme_debug_warmup500_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ja|
+|Size:|698.0 MB|
+
+## References
+
+https://huggingface.co/utakumi/Hubert-common_voice-phoneme-debug-warmup500
+
+## Included Models
+
+- AudioAssembler
+- HubertForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-hubert_common_voice_phoneme_onlyjsut_ja.md b/docs/_posts/ahmedlone127/2025-01-23-hubert_common_voice_phoneme_onlyjsut_ja.md
new file mode 100644
index 00000000000000..6f7ad2352542d5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-hubert_common_voice_phoneme_onlyjsut_ja.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Japanese hubert_common_voice_phoneme_onlyjsut HubertForCTC from utakumi
+author: John Snow Labs
+name: hubert_common_voice_phoneme_onlyjsut
+date: 2025-01-23
+tags: [ja, open_source, onnx, asr, hubert]
+task: Automatic Speech Recognition
+language: ja
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: HubertForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_common_voice_phoneme_onlyjsut` is a Japanese model originally trained by utakumi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_common_voice_phoneme_onlyjsut_ja_5.5.1_3.0_1737625723545.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_common_voice_phoneme_onlyjsut_ja_5.5.1_3.0_1737625723545.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = HubertForCTC.pretrained("hubert_common_voice_phoneme_onlyjsut","ja") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = HubertForCTC.pretrained("hubert_common_voice_phoneme_onlyjsut", "ja")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hubert_common_voice_phoneme_onlyjsut|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|ja|
+|Size:|698.0 MB|
+
+## References
+
+https://huggingface.co/utakumi/Hubert-common_voice-phoneme-onlyJSUT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-hubert_common_voice_phoneme_onlyjsut_pipeline_ja.md b/docs/_posts/ahmedlone127/2025-01-23-hubert_common_voice_phoneme_onlyjsut_pipeline_ja.md
new file mode 100644
index 00000000000000..e13147ade65633
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-hubert_common_voice_phoneme_onlyjsut_pipeline_ja.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Japanese hubert_common_voice_phoneme_onlyjsut_pipeline pipeline HubertForCTC from utakumi
+author: John Snow Labs
+name: hubert_common_voice_phoneme_onlyjsut_pipeline
+date: 2025-01-23
+tags: [ja, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: ja
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_common_voice_phoneme_onlyjsut_pipeline` is a Japanese model originally trained by utakumi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_common_voice_phoneme_onlyjsut_pipeline_ja_5.5.1_3.0_1737625770604.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_common_voice_phoneme_onlyjsut_pipeline_ja_5.5.1_3.0_1737625770604.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("hubert_common_voice_phoneme_onlyjsut_pipeline", lang = "ja")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hubert_common_voice_phoneme_onlyjsut_pipeline", lang = "ja")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hubert_common_voice_phoneme_onlyjsut_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ja|
+|Size:|698.0 MB|
+
+## References
+
+https://huggingface.co/utakumi/Hubert-common_voice-phoneme-onlyJSUT
+
+## Included Models
+
+- AudioAssembler
+- HubertForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-hubert_common_voice_phonemes_debug_ja.md b/docs/_posts/ahmedlone127/2025-01-23-hubert_common_voice_phonemes_debug_ja.md
new file mode 100644
index 00000000000000..058761626e7d6c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-hubert_common_voice_phonemes_debug_ja.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Japanese hubert_common_voice_phonemes_debug HubertForCTC from utakumi
+author: John Snow Labs
+name: hubert_common_voice_phonemes_debug
+date: 2025-01-23
+tags: [ja, open_source, onnx, asr, hubert]
+task: Automatic Speech Recognition
+language: ja
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: HubertForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_common_voice_phonemes_debug` is a Japanese model originally trained by utakumi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_common_voice_phonemes_debug_ja_5.5.1_3.0_1737625164063.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_common_voice_phonemes_debug_ja_5.5.1_3.0_1737625164063.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = HubertForCTC.pretrained("hubert_common_voice_phonemes_debug","ja") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = HubertForCTC.pretrained("hubert_common_voice_phonemes_debug", "ja")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hubert_common_voice_phonemes_debug|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|ja|
+|Size:|697.7 MB|
+
+## References
+
+https://huggingface.co/utakumi/Hubert-common_voice-phonemes-debug
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-hubert_common_voice_phonemes_debug_pipeline_ja.md b/docs/_posts/ahmedlone127/2025-01-23-hubert_common_voice_phonemes_debug_pipeline_ja.md
new file mode 100644
index 00000000000000..27c01f13382b71
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-hubert_common_voice_phonemes_debug_pipeline_ja.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Japanese hubert_common_voice_phonemes_debug_pipeline pipeline HubertForCTC from utakumi
+author: John Snow Labs
+name: hubert_common_voice_phonemes_debug_pipeline
+date: 2025-01-23
+tags: [ja, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: ja
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_common_voice_phonemes_debug_pipeline` is a Japanese model originally trained by utakumi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_common_voice_phonemes_debug_pipeline_ja_5.5.1_3.0_1737625218732.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_common_voice_phonemes_debug_pipeline_ja_5.5.1_3.0_1737625218732.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("hubert_common_voice_phonemes_debug_pipeline", lang = "ja")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hubert_common_voice_phonemes_debug_pipeline", lang = "ja")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hubert_common_voice_phonemes_debug_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ja|
+|Size:|697.7 MB|
+
+## References
+
+https://huggingface.co/utakumi/Hubert-common_voice-phonemes-debug
+
+## Included Models
+
+- AudioAssembler
+- HubertForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-hubert_ft_eval_ja.md b/docs/_posts/ahmedlone127/2025-01-23-hubert_ft_eval_ja.md
new file mode 100644
index 00000000000000..364c618718bc78
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-hubert_ft_eval_ja.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Japanese hubert_ft_eval HubertForCTC from utakumi
+author: John Snow Labs
+name: hubert_ft_eval
+date: 2025-01-23
+tags: [ja, open_source, onnx, asr, hubert]
+task: Automatic Speech Recognition
+language: ja
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: HubertForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_ft_eval` is a Japanese model originally trained by utakumi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_ft_eval_ja_5.5.1_3.0_1737625163872.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_ft_eval_ja_5.5.1_3.0_1737625163872.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = HubertForCTC.pretrained("hubert_ft_eval","ja") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = HubertForCTC.pretrained("hubert_ft_eval", "ja")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hubert_ft_eval|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|ja|
+|Size:|697.9 MB|
+
+## References
+
+https://huggingface.co/utakumi/Hubert-ft-eval
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-hubert_ft_eval_pipeline_ja.md b/docs/_posts/ahmedlone127/2025-01-23-hubert_ft_eval_pipeline_ja.md
new file mode 100644
index 00000000000000..afdf5370438ae4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-hubert_ft_eval_pipeline_ja.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Japanese hubert_ft_eval_pipeline pipeline HubertForCTC from utakumi
+author: John Snow Labs
+name: hubert_ft_eval_pipeline
+date: 2025-01-23
+tags: [ja, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: ja
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_ft_eval_pipeline` is a Japanese model originally trained by utakumi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_ft_eval_pipeline_ja_5.5.1_3.0_1737625218764.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_ft_eval_pipeline_ja_5.5.1_3.0_1737625218764.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("hubert_ft_eval_pipeline", lang = "ja")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hubert_ft_eval_pipeline", lang = "ja")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hubert_ft_eval_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ja|
+|Size:|697.9 MB|
+
+## References
+
+https://huggingface.co/utakumi/Hubert-ft-eval
+
+## Included Models
+
+- AudioAssembler
+- HubertForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-hubert_kakeiken_w_elevator_hall_en.md b/docs/_posts/ahmedlone127/2025-01-23-hubert_kakeiken_w_elevator_hall_en.md
new file mode 100644
index 00000000000000..109c928740ac31
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-hubert_kakeiken_w_elevator_hall_en.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: English hubert_kakeiken_w_elevator_hall HubertForCTC from utakumi
+author: John Snow Labs
+name: hubert_kakeiken_w_elevator_hall
+date: 2025-01-23
+tags: [en, open_source, onnx, asr, hubert]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: HubertForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_kakeiken_w_elevator_hall` is a English model originally trained by utakumi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_kakeiken_w_elevator_hall_en_5.5.1_3.0_1737625991197.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_kakeiken_w_elevator_hall_en_5.5.1_3.0_1737625991197.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = HubertForCTC.pretrained("hubert_kakeiken_w_elevator_hall","en") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = HubertForCTC.pretrained("hubert_kakeiken_w_elevator_hall", "en")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hubert_kakeiken_w_elevator_hall|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|en|
+|Size:|697.9 MB|
+
+## References
+
+https://huggingface.co/utakumi/Hubert-kakeiken-W-elevator_hall
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-hubert_kakeiken_w_elevator_hall_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-hubert_kakeiken_w_elevator_hall_pipeline_en.md
new file mode 100644
index 00000000000000..61ed5d28d8f818
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-hubert_kakeiken_w_elevator_hall_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English hubert_kakeiken_w_elevator_hall_pipeline pipeline HubertForCTC from utakumi
+author: John Snow Labs
+name: hubert_kakeiken_w_elevator_hall_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_kakeiken_w_elevator_hall_pipeline` is a English model originally trained by utakumi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_kakeiken_w_elevator_hall_pipeline_en_5.5.1_3.0_1737626032239.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_kakeiken_w_elevator_hall_pipeline_en_5.5.1_3.0_1737626032239.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("hubert_kakeiken_w_elevator_hall_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hubert_kakeiken_w_elevator_hall_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hubert_kakeiken_w_elevator_hall_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|697.9 MB|
+
+## References
+
+https://huggingface.co/utakumi/Hubert-kakeiken-W-elevator_hall
+
+## Included Models
+
+- AudioAssembler
+- HubertForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_chuvash_kakeiken_d_en.md b/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_chuvash_kakeiken_d_en.md
new file mode 100644
index 00000000000000..c5e977b01afc14
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_chuvash_kakeiken_d_en.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: English hubert_noisy_chuvash_kakeiken_d HubertForCTC from utakumi
+author: John Snow Labs
+name: hubert_noisy_chuvash_kakeiken_d
+date: 2025-01-23
+tags: [en, open_source, onnx, asr, hubert]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: HubertForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_noisy_chuvash_kakeiken_d` is a English model originally trained by utakumi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_noisy_chuvash_kakeiken_d_en_5.5.1_3.0_1737625603712.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_noisy_chuvash_kakeiken_d_en_5.5.1_3.0_1737625603712.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = HubertForCTC.pretrained("hubert_noisy_chuvash_kakeiken_d","en") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = HubertForCTC.pretrained("hubert_noisy_chuvash_kakeiken_d", "en")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hubert_noisy_chuvash_kakeiken_d|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|en|
+|Size:|697.3 MB|
+
+## References
+
+https://huggingface.co/utakumi/Hubert-noisy-cv-kakeiken-D
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_chuvash_kakeiken_d_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_chuvash_kakeiken_d_pipeline_en.md
new file mode 100644
index 00000000000000..578c87ddf313b9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_chuvash_kakeiken_d_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English hubert_noisy_chuvash_kakeiken_d_pipeline pipeline HubertForCTC from utakumi
+author: John Snow Labs
+name: hubert_noisy_chuvash_kakeiken_d_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_noisy_chuvash_kakeiken_d_pipeline` is a English model originally trained by utakumi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_noisy_chuvash_kakeiken_d_pipeline_en_5.5.1_3.0_1737625647223.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_noisy_chuvash_kakeiken_d_pipeline_en_5.5.1_3.0_1737625647223.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("hubert_noisy_chuvash_kakeiken_d_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hubert_noisy_chuvash_kakeiken_d_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hubert_noisy_chuvash_kakeiken_d_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|697.3 MB|
+
+## References
+
+https://huggingface.co/utakumi/Hubert-noisy-cv-kakeiken-D
+
+## Included Models
+
+- AudioAssembler
+- HubertForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_chuvash_kakeiken_e_en.md b/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_chuvash_kakeiken_e_en.md
new file mode 100644
index 00000000000000..486ea8afaca1ed
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_chuvash_kakeiken_e_en.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: English hubert_noisy_chuvash_kakeiken_e HubertForCTC from utakumi
+author: John Snow Labs
+name: hubert_noisy_chuvash_kakeiken_e
+date: 2025-01-23
+tags: [en, open_source, onnx, asr, hubert]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: HubertForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_noisy_chuvash_kakeiken_e` is a English model originally trained by utakumi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_noisy_chuvash_kakeiken_e_en_5.5.1_3.0_1737625765456.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_noisy_chuvash_kakeiken_e_en_5.5.1_3.0_1737625765456.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = HubertForCTC.pretrained("hubert_noisy_chuvash_kakeiken_e","en") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = HubertForCTC.pretrained("hubert_noisy_chuvash_kakeiken_e", "en")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hubert_noisy_chuvash_kakeiken_e|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|en|
+|Size:|697.3 MB|
+
+## References
+
+https://huggingface.co/utakumi/Hubert-noisy-cv-kakeiken-E
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_chuvash_kakeiken_e_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_chuvash_kakeiken_e_pipeline_en.md
new file mode 100644
index 00000000000000..6f0ffb1153b64e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_chuvash_kakeiken_e_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English hubert_noisy_chuvash_kakeiken_e_pipeline pipeline HubertForCTC from utakumi
+author: John Snow Labs
+name: hubert_noisy_chuvash_kakeiken_e_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_noisy_chuvash_kakeiken_e_pipeline` is a English model originally trained by utakumi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_noisy_chuvash_kakeiken_e_pipeline_en_5.5.1_3.0_1737625810177.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_noisy_chuvash_kakeiken_e_pipeline_en_5.5.1_3.0_1737625810177.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("hubert_noisy_chuvash_kakeiken_e_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hubert_noisy_chuvash_kakeiken_e_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hubert_noisy_chuvash_kakeiken_e_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|697.3 MB|
+
+## References
+
+https://huggingface.co/utakumi/Hubert-noisy-cv-kakeiken-E
+
+## Included Models
+
+- AudioAssembler
+- HubertForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_chuvash_kakeiken_j_en.md b/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_chuvash_kakeiken_j_en.md
new file mode 100644
index 00000000000000..d7bc03d38b7bb5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_chuvash_kakeiken_j_en.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: English hubert_noisy_chuvash_kakeiken_j HubertForCTC from utakumi
+author: John Snow Labs
+name: hubert_noisy_chuvash_kakeiken_j
+date: 2025-01-23
+tags: [en, open_source, onnx, asr, hubert]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: HubertForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_noisy_chuvash_kakeiken_j` is a English model originally trained by utakumi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_noisy_chuvash_kakeiken_j_en_5.5.1_3.0_1737625353562.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_noisy_chuvash_kakeiken_j_en_5.5.1_3.0_1737625353562.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = HubertForCTC.pretrained("hubert_noisy_chuvash_kakeiken_j","en") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = HubertForCTC.pretrained("hubert_noisy_chuvash_kakeiken_j", "en")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hubert_noisy_chuvash_kakeiken_j|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|en|
+|Size:|697.8 MB|
+
+## References
+
+https://huggingface.co/utakumi/Hubert-noisy-cv-kakeiken-J
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_chuvash_kakeiken_j_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_chuvash_kakeiken_j_pipeline_en.md
new file mode 100644
index 00000000000000..37871d196f5b9e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_chuvash_kakeiken_j_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English hubert_noisy_chuvash_kakeiken_j_pipeline pipeline HubertForCTC from utakumi
+author: John Snow Labs
+name: hubert_noisy_chuvash_kakeiken_j_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_noisy_chuvash_kakeiken_j_pipeline` is a English model originally trained by utakumi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_noisy_chuvash_kakeiken_j_pipeline_en_5.5.1_3.0_1737625400850.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_noisy_chuvash_kakeiken_j_pipeline_en_5.5.1_3.0_1737625400850.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("hubert_noisy_chuvash_kakeiken_j_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hubert_noisy_chuvash_kakeiken_j_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hubert_noisy_chuvash_kakeiken_j_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|697.8 MB|
+
+## References
+
+https://huggingface.co/utakumi/Hubert-noisy-cv-kakeiken-J
+
+## Included Models
+
+- AudioAssembler
+- HubertForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_chuvash_kakeiken_j_ver4_en.md b/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_chuvash_kakeiken_j_ver4_en.md
new file mode 100644
index 00000000000000..0de8e6662c8684
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_chuvash_kakeiken_j_ver4_en.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: English hubert_noisy_chuvash_kakeiken_j_ver4 HubertForCTC from utakumi
+author: John Snow Labs
+name: hubert_noisy_chuvash_kakeiken_j_ver4
+date: 2025-01-23
+tags: [en, open_source, onnx, asr, hubert]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: HubertForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_noisy_chuvash_kakeiken_j_ver4` is a English model originally trained by utakumi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_noisy_chuvash_kakeiken_j_ver4_en_5.5.1_3.0_1737626056422.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_noisy_chuvash_kakeiken_j_ver4_en_5.5.1_3.0_1737626056422.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = HubertForCTC.pretrained("hubert_noisy_chuvash_kakeiken_j_ver4","en") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = HubertForCTC.pretrained("hubert_noisy_chuvash_kakeiken_j_ver4", "en")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hubert_noisy_chuvash_kakeiken_j_ver4|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|en|
+|Size:|697.9 MB|
+
+## References
+
+https://huggingface.co/utakumi/Hubert-noisy-cv-kakeiken-J_ver4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_chuvash_kakeiken_j_ver4_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_chuvash_kakeiken_j_ver4_pipeline_en.md
new file mode 100644
index 00000000000000..6e3ca8300b4d3f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_chuvash_kakeiken_j_ver4_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English hubert_noisy_chuvash_kakeiken_j_ver4_pipeline pipeline HubertForCTC from utakumi
+author: John Snow Labs
+name: hubert_noisy_chuvash_kakeiken_j_ver4_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_noisy_chuvash_kakeiken_j_ver4_pipeline` is a English model originally trained by utakumi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_noisy_chuvash_kakeiken_j_ver4_pipeline_en_5.5.1_3.0_1737626096419.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_noisy_chuvash_kakeiken_j_ver4_pipeline_en_5.5.1_3.0_1737626096419.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("hubert_noisy_chuvash_kakeiken_j_ver4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hubert_noisy_chuvash_kakeiken_j_ver4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hubert_noisy_chuvash_kakeiken_j_ver4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|697.9 MB|
+
+## References
+
+https://huggingface.co/utakumi/Hubert-noisy-cv-kakeiken-J_ver4
+
+## Included Models
+
+- AudioAssembler
+- HubertForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_chuvash_kakeiken_j_ver5_en.md b/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_chuvash_kakeiken_j_ver5_en.md
new file mode 100644
index 00000000000000..0cbff123162145
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_chuvash_kakeiken_j_ver5_en.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: English hubert_noisy_chuvash_kakeiken_j_ver5 HubertForCTC from utakumi
+author: John Snow Labs
+name: hubert_noisy_chuvash_kakeiken_j_ver5
+date: 2025-01-23
+tags: [en, open_source, onnx, asr, hubert]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: HubertForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_noisy_chuvash_kakeiken_j_ver5` is a English model originally trained by utakumi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_noisy_chuvash_kakeiken_j_ver5_en_5.5.1_3.0_1737625164115.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_noisy_chuvash_kakeiken_j_ver5_en_5.5.1_3.0_1737625164115.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = HubertForCTC.pretrained("hubert_noisy_chuvash_kakeiken_j_ver5","en") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = HubertForCTC.pretrained("hubert_noisy_chuvash_kakeiken_j_ver5", "en")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hubert_noisy_chuvash_kakeiken_j_ver5|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|en|
+|Size:|697.9 MB|
+
+## References
+
+https://huggingface.co/utakumi/Hubert-noisy-cv-kakeiken-J_ver5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_chuvash_kakeiken_j_ver5_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_chuvash_kakeiken_j_ver5_pipeline_en.md
new file mode 100644
index 00000000000000..85144054a50371
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_chuvash_kakeiken_j_ver5_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English hubert_noisy_chuvash_kakeiken_j_ver5_pipeline pipeline HubertForCTC from utakumi
+author: John Snow Labs
+name: hubert_noisy_chuvash_kakeiken_j_ver5_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_noisy_chuvash_kakeiken_j_ver5_pipeline` is a English model originally trained by utakumi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_noisy_chuvash_kakeiken_j_ver5_pipeline_en_5.5.1_3.0_1737625210230.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_noisy_chuvash_kakeiken_j_ver5_pipeline_en_5.5.1_3.0_1737625210230.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("hubert_noisy_chuvash_kakeiken_j_ver5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hubert_noisy_chuvash_kakeiken_j_ver5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hubert_noisy_chuvash_kakeiken_j_ver5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|697.9 MB|
+
+## References
+
+https://huggingface.co/utakumi/Hubert-noisy-cv-kakeiken-J_ver5
+
+## Included Models
+
+- AudioAssembler
+- HubertForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_chuvash_kakeiken_ja.md b/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_chuvash_kakeiken_ja.md
new file mode 100644
index 00000000000000..bc8aef242bd7c6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_chuvash_kakeiken_ja.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Japanese hubert_noisy_chuvash_kakeiken HubertForCTC from utakumi
+author: John Snow Labs
+name: hubert_noisy_chuvash_kakeiken
+date: 2025-01-23
+tags: [ja, open_source, onnx, asr, hubert]
+task: Automatic Speech Recognition
+language: ja
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: HubertForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_noisy_chuvash_kakeiken` is a Japanese model originally trained by utakumi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_noisy_chuvash_kakeiken_ja_5.5.1_3.0_1737625519615.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_noisy_chuvash_kakeiken_ja_5.5.1_3.0_1737625519615.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = HubertForCTC.pretrained("hubert_noisy_chuvash_kakeiken","ja") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = HubertForCTC.pretrained("hubert_noisy_chuvash_kakeiken", "ja")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hubert_noisy_chuvash_kakeiken|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|ja|
+|Size:|698.0 MB|
+
+## References
+
+https://huggingface.co/utakumi/Hubert-noisy-cv-kakeiken
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_chuvash_kakeiken_pipeline_ja.md b/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_chuvash_kakeiken_pipeline_ja.md
new file mode 100644
index 00000000000000..b8d3b4148c2f80
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_chuvash_kakeiken_pipeline_ja.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Japanese hubert_noisy_chuvash_kakeiken_pipeline pipeline HubertForCTC from utakumi
+author: John Snow Labs
+name: hubert_noisy_chuvash_kakeiken_pipeline
+date: 2025-01-23
+tags: [ja, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: ja
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_noisy_chuvash_kakeiken_pipeline` is a Japanese model originally trained by utakumi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_noisy_chuvash_kakeiken_pipeline_ja_5.5.1_3.0_1737625560576.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_noisy_chuvash_kakeiken_pipeline_ja_5.5.1_3.0_1737625560576.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("hubert_noisy_chuvash_kakeiken_pipeline", lang = "ja")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hubert_noisy_chuvash_kakeiken_pipeline", lang = "ja")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hubert_noisy_chuvash_kakeiken_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ja|
+|Size:|698.0 MB|
+
+## References
+
+https://huggingface.co/utakumi/Hubert-noisy-cv-kakeiken
+
+## Included Models
+
+- AudioAssembler
+- HubertForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_common_voice_debug_ja.md b/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_common_voice_debug_ja.md
new file mode 100644
index 00000000000000..017883242a30f9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_common_voice_debug_ja.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Japanese hubert_noisy_common_voice_debug HubertForCTC from utakumi
+author: John Snow Labs
+name: hubert_noisy_common_voice_debug
+date: 2025-01-23
+tags: [ja, open_source, onnx, asr, hubert]
+task: Automatic Speech Recognition
+language: ja
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: HubertForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_noisy_common_voice_debug` is a Japanese model originally trained by utakumi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_noisy_common_voice_debug_ja_5.5.1_3.0_1737625310612.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_noisy_common_voice_debug_ja_5.5.1_3.0_1737625310612.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = HubertForCTC.pretrained("hubert_noisy_common_voice_debug","ja") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = HubertForCTC.pretrained("hubert_noisy_common_voice_debug", "ja")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hubert_noisy_common_voice_debug|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|ja|
+|Size:|697.7 MB|
+
+## References
+
+https://huggingface.co/utakumi/Hubert-noisy_common_voice_debug
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_common_voice_debug_pipeline_ja.md b/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_common_voice_debug_pipeline_ja.md
new file mode 100644
index 00000000000000..f47b116fcaad2c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_common_voice_debug_pipeline_ja.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Japanese hubert_noisy_common_voice_debug_pipeline pipeline HubertForCTC from utakumi
+author: John Snow Labs
+name: hubert_noisy_common_voice_debug_pipeline
+date: 2025-01-23
+tags: [ja, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: ja
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_noisy_common_voice_debug_pipeline` is a Japanese model originally trained by utakumi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_noisy_common_voice_debug_pipeline_ja_5.5.1_3.0_1737625353222.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_noisy_common_voice_debug_pipeline_ja_5.5.1_3.0_1737625353222.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("hubert_noisy_common_voice_debug_pipeline", lang = "ja")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hubert_noisy_common_voice_debug_pipeline", lang = "ja")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hubert_noisy_common_voice_debug_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ja|
+|Size:|697.7 MB|
+
+## References
+
+https://huggingface.co/utakumi/Hubert-noisy_common_voice_debug
+
+## Included Models
+
+- AudioAssembler
+- HubertForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_common_voice_phonemes_debug_ja.md b/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_common_voice_phonemes_debug_ja.md
new file mode 100644
index 00000000000000..c8469e7960d112
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_common_voice_phonemes_debug_ja.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Japanese hubert_noisy_common_voice_phonemes_debug HubertForCTC from utakumi
+author: John Snow Labs
+name: hubert_noisy_common_voice_phonemes_debug
+date: 2025-01-23
+tags: [ja, open_source, onnx, asr, hubert]
+task: Automatic Speech Recognition
+language: ja
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: HubertForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_noisy_common_voice_phonemes_debug` is a Japanese model originally trained by utakumi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_noisy_common_voice_phonemes_debug_ja_5.5.1_3.0_1737625933339.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_noisy_common_voice_phonemes_debug_ja_5.5.1_3.0_1737625933339.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = HubertForCTC.pretrained("hubert_noisy_common_voice_phonemes_debug","ja") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = HubertForCTC.pretrained("hubert_noisy_common_voice_phonemes_debug", "ja")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hubert_noisy_common_voice_phonemes_debug|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|ja|
+|Size:|697.7 MB|
+
+## References
+
+https://huggingface.co/utakumi/Hubert_noisy_common_voice_phonemes_debug
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_common_voice_phonemes_debug_pipeline_ja.md b/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_common_voice_phonemes_debug_pipeline_ja.md
new file mode 100644
index 00000000000000..d9b8e1025ac21a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_common_voice_phonemes_debug_pipeline_ja.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Japanese hubert_noisy_common_voice_phonemes_debug_pipeline pipeline HubertForCTC from utakumi
+author: John Snow Labs
+name: hubert_noisy_common_voice_phonemes_debug_pipeline
+date: 2025-01-23
+tags: [ja, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: ja
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_noisy_common_voice_phonemes_debug_pipeline` is a Japanese model originally trained by utakumi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_noisy_common_voice_phonemes_debug_pipeline_ja_5.5.1_3.0_1737625974712.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_noisy_common_voice_phonemes_debug_pipeline_ja_5.5.1_3.0_1737625974712.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("hubert_noisy_common_voice_phonemes_debug_pipeline", lang = "ja")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hubert_noisy_common_voice_phonemes_debug_pipeline", lang = "ja")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hubert_noisy_common_voice_phonemes_debug_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ja|
+|Size:|697.7 MB|
+
+## References
+
+https://huggingface.co/utakumi/Hubert_noisy_common_voice_phonemes_debug
+
+## Included Models
+
+- AudioAssembler
+- HubertForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_ft_eval_ja.md b/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_ft_eval_ja.md
new file mode 100644
index 00000000000000..9651ca1ada9765
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_ft_eval_ja.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Japanese hubert_noisy_ft_eval HubertForCTC from utakumi
+author: John Snow Labs
+name: hubert_noisy_ft_eval
+date: 2025-01-23
+tags: [ja, open_source, onnx, asr, hubert]
+task: Automatic Speech Recognition
+language: ja
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: HubertForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_noisy_ft_eval` is a Japanese model originally trained by utakumi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_noisy_ft_eval_ja_5.5.1_3.0_1737625373594.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_noisy_ft_eval_ja_5.5.1_3.0_1737625373594.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = HubertForCTC.pretrained("hubert_noisy_ft_eval","ja") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = HubertForCTC.pretrained("hubert_noisy_ft_eval", "ja")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hubert_noisy_ft_eval|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|ja|
+|Size:|697.7 MB|
+
+## References
+
+https://huggingface.co/utakumi/Hubert-noisy-ft-eval
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_ft_eval_pipeline_ja.md b/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_ft_eval_pipeline_ja.md
new file mode 100644
index 00000000000000..f9ee2d8c67f666
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-hubert_noisy_ft_eval_pipeline_ja.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Japanese hubert_noisy_ft_eval_pipeline pipeline HubertForCTC from utakumi
+author: John Snow Labs
+name: hubert_noisy_ft_eval_pipeline
+date: 2025-01-23
+tags: [ja, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: ja
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_noisy_ft_eval_pipeline` is a Japanese model originally trained by utakumi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_noisy_ft_eval_pipeline_ja_5.5.1_3.0_1737625414623.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_noisy_ft_eval_pipeline_ja_5.5.1_3.0_1737625414623.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("hubert_noisy_ft_eval_pipeline", lang = "ja")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hubert_noisy_ft_eval_pipeline", lang = "ja")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hubert_noisy_ft_eval_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ja|
+|Size:|697.7 MB|
+
+## References
+
+https://huggingface.co/utakumi/Hubert-noisy-ft-eval
+
+## Included Models
+
+- AudioAssembler
+- HubertForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-idt5_base_qaqg_v2_en.md b/docs/_posts/ahmedlone127/2025-01-23-idt5_base_qaqg_v2_en.md
new file mode 100644
index 00000000000000..0ef95b539db689
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-idt5_base_qaqg_v2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English idt5_base_qaqg_v2 T5Transformer from hawalurahman
+author: John Snow Labs
+name: idt5_base_qaqg_v2
+date: 2025-01-23
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`idt5_base_qaqg_v2` is a English model originally trained by hawalurahman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/idt5_base_qaqg_v2_en_5.5.1_3.0_1737633756763.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/idt5_base_qaqg_v2_en_5.5.1_3.0_1737633756763.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("idt5_base_qaqg_v2","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("idt5_base_qaqg_v2", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|idt5_base_qaqg_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|983.5 MB|
+
+## References
+
+https://huggingface.co/hawalurahman/idt5-base-qaqg_v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-idt5_base_qaqg_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-idt5_base_qaqg_v2_pipeline_en.md
new file mode 100644
index 00000000000000..15cff49ceb8d92
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-idt5_base_qaqg_v2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English idt5_base_qaqg_v2_pipeline pipeline T5Transformer from hawalurahman
+author: John Snow Labs
+name: idt5_base_qaqg_v2_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`idt5_base_qaqg_v2_pipeline` is a English model originally trained by hawalurahman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/idt5_base_qaqg_v2_pipeline_en_5.5.1_3.0_1737633808332.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/idt5_base_qaqg_v2_pipeline_en_5.5.1_3.0_1737633808332.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("idt5_base_qaqg_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("idt5_base_qaqg_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|idt5_base_qaqg_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|983.5 MB|
+
+## References
+
+https://huggingface.co/hawalurahman/idt5-base-qaqg_v2
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-indic_bert_profanity_marathi_marh_en.md b/docs/_posts/ahmedlone127/2025-01-23-indic_bert_profanity_marathi_marh_en.md
new file mode 100644
index 00000000000000..7cf5b623243b89
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-indic_bert_profanity_marathi_marh_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English indic_bert_profanity_marathi_marh AlbertForSequenceClassification from callmesan
+author: John Snow Labs
+name: indic_bert_profanity_marathi_marh
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, albert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indic_bert_profanity_marathi_marh` is a English model originally trained by callmesan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indic_bert_profanity_marathi_marh_en_5.5.1_3.0_1737624137996.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indic_bert_profanity_marathi_marh_en_5.5.1_3.0_1737624137996.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = AlbertForSequenceClassification.pretrained("indic_bert_profanity_marathi_marh","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = AlbertForSequenceClassification.pretrained("indic_bert_profanity_marathi_marh", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|indic_bert_profanity_marathi_marh|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|127.7 MB|
+
+## References
+
+https://huggingface.co/callmesan/indic-bert-profanity-mr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-indic_bert_profanity_marathi_marh_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-indic_bert_profanity_marathi_marh_pipeline_en.md
new file mode 100644
index 00000000000000..f1b4f1f646d862
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-indic_bert_profanity_marathi_marh_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English indic_bert_profanity_marathi_marh_pipeline pipeline AlbertForSequenceClassification from callmesan
+author: John Snow Labs
+name: indic_bert_profanity_marathi_marh_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indic_bert_profanity_marathi_marh_pipeline` is a English model originally trained by callmesan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indic_bert_profanity_marathi_marh_pipeline_en_5.5.1_3.0_1737624144517.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indic_bert_profanity_marathi_marh_pipeline_en_5.5.1_3.0_1737624144517.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("indic_bert_profanity_marathi_marh_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("indic_bert_profanity_marathi_marh_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|indic_bert_profanity_marathi_marh_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|127.8 MB|
+
+## References
+
+https://huggingface.co/callmesan/indic-bert-profanity-mr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-indic_bert_roman_urdu_binary_en.md b/docs/_posts/ahmedlone127/2025-01-23-indic_bert_roman_urdu_binary_en.md
new file mode 100644
index 00000000000000..136a9ec46b5a5b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-indic_bert_roman_urdu_binary_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English indic_bert_roman_urdu_binary AlbertForSequenceClassification from callmesan
+author: John Snow Labs
+name: indic_bert_roman_urdu_binary
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, albert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indic_bert_roman_urdu_binary` is a English model originally trained by callmesan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indic_bert_roman_urdu_binary_en_5.5.1_3.0_1737624483569.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indic_bert_roman_urdu_binary_en_5.5.1_3.0_1737624483569.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = AlbertForSequenceClassification.pretrained("indic_bert_roman_urdu_binary","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = AlbertForSequenceClassification.pretrained("indic_bert_roman_urdu_binary", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|indic_bert_roman_urdu_binary|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|127.7 MB|
+
+## References
+
+https://huggingface.co/callmesan/indic-bert-roman-urdu-binary
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-indic_bert_roman_urdu_binary_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-indic_bert_roman_urdu_binary_pipeline_en.md
new file mode 100644
index 00000000000000..f4d1084dcf985a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-indic_bert_roman_urdu_binary_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English indic_bert_roman_urdu_binary_pipeline pipeline AlbertForSequenceClassification from callmesan
+author: John Snow Labs
+name: indic_bert_roman_urdu_binary_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indic_bert_roman_urdu_binary_pipeline` is a English model originally trained by callmesan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indic_bert_roman_urdu_binary_pipeline_en_5.5.1_3.0_1737624489989.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indic_bert_roman_urdu_binary_pipeline_en_5.5.1_3.0_1737624489989.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("indic_bert_roman_urdu_binary_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("indic_bert_roman_urdu_binary_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|indic_bert_roman_urdu_binary_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|127.8 MB|
+
+## References
+
+https://huggingface.co/callmesan/indic-bert-roman-urdu-binary
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-jobbert_v2_en.md b/docs/_posts/ahmedlone127/2025-01-23-jobbert_v2_en.md
new file mode 100644
index 00000000000000..26df01027960e8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-jobbert_v2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English jobbert_v2 MPNetEmbeddings from jensjorisdecorte
+author: John Snow Labs
+name: jobbert_v2
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`jobbert_v2` is a English model originally trained by jensjorisdecorte.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/jobbert_v2_en_5.5.1_3.0_1737669551649.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/jobbert_v2_en_5.5.1_3.0_1737669551649.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("jobbert_v2","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("jobbert_v2","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|jobbert_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.6 MB|
+
+## References
+
+https://huggingface.co/jensjorisdecorte/JobBERT-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-jobbert_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-jobbert_v2_pipeline_en.md
new file mode 100644
index 00000000000000..fdc7ce7fcd3ab8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-jobbert_v2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English jobbert_v2_pipeline pipeline MPNetEmbeddings from jensjorisdecorte
+author: John Snow Labs
+name: jobbert_v2_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`jobbert_v2_pipeline` is a English model originally trained by jensjorisdecorte.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/jobbert_v2_pipeline_en_5.5.1_3.0_1737669577341.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/jobbert_v2_pipeline_en_5.5.1_3.0_1737669577341.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("jobbert_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("jobbert_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|jobbert_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.7 MB|
+
+## References
+
+https://huggingface.co/jensjorisdecorte/JobBERT-v2
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-jpmodel_remote_work_distilbert_base_uncased_0517_en.md b/docs/_posts/ahmedlone127/2025-01-23-jpmodel_remote_work_distilbert_base_uncased_0517_en.md
new file mode 100644
index 00000000000000..41509d9c4d1601
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-jpmodel_remote_work_distilbert_base_uncased_0517_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English jpmodel_remote_work_distilbert_base_uncased_0517 DistilBertForSequenceClassification from Miamiahong
+author: John Snow Labs
+name: jpmodel_remote_work_distilbert_base_uncased_0517
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`jpmodel_remote_work_distilbert_base_uncased_0517` is a English model originally trained by Miamiahong.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/jpmodel_remote_work_distilbert_base_uncased_0517_en_5.5.1_3.0_1737650702442.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/jpmodel_remote_work_distilbert_base_uncased_0517_en_5.5.1_3.0_1737650702442.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("jpmodel_remote_work_distilbert_base_uncased_0517","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("jpmodel_remote_work_distilbert_base_uncased_0517", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|jpmodel_remote_work_distilbert_base_uncased_0517|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Miamiahong/jpmodel_remote-work_distilbert-base-uncased_0517
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-jpmodel_remote_work_distilbert_base_uncased_0517_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-jpmodel_remote_work_distilbert_base_uncased_0517_pipeline_en.md
new file mode 100644
index 00000000000000..e3356debe1273f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-jpmodel_remote_work_distilbert_base_uncased_0517_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English jpmodel_remote_work_distilbert_base_uncased_0517_pipeline pipeline DistilBertForSequenceClassification from Miamiahong
+author: John Snow Labs
+name: jpmodel_remote_work_distilbert_base_uncased_0517_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`jpmodel_remote_work_distilbert_base_uncased_0517_pipeline` is a English model originally trained by Miamiahong.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/jpmodel_remote_work_distilbert_base_uncased_0517_pipeline_en_5.5.1_3.0_1737650716233.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/jpmodel_remote_work_distilbert_base_uncased_0517_pipeline_en_5.5.1_3.0_1737650716233.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("jpmodel_remote_work_distilbert_base_uncased_0517_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("jpmodel_remote_work_distilbert_base_uncased_0517_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|jpmodel_remote_work_distilbert_base_uncased_0517_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Miamiahong/jpmodel_remote-work_distilbert-base-uncased_0517
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-judge_answer__27_deberta_v3_large_frozen_en.md b/docs/_posts/ahmedlone127/2025-01-23-judge_answer__27_deberta_v3_large_frozen_en.md
new file mode 100644
index 00000000000000..a48a748fd6929a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-judge_answer__27_deberta_v3_large_frozen_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English judge_answer__27_deberta_v3_large_frozen DeBertaForSequenceClassification from tom-010
+author: John Snow Labs
+name: judge_answer__27_deberta_v3_large_frozen
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`judge_answer__27_deberta_v3_large_frozen` is a English model originally trained by tom-010.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/judge_answer__27_deberta_v3_large_frozen_en_5.5.1_3.0_1737657664807.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/judge_answer__27_deberta_v3_large_frozen_en_5.5.1_3.0_1737657664807.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("judge_answer__27_deberta_v3_large_frozen","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("judge_answer__27_deberta_v3_large_frozen", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|judge_answer__27_deberta_v3_large_frozen|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/tom-010/judge_answer__27_deberta_v3_large_frozen
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-judge_answer__27_deberta_v3_large_frozen_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-judge_answer__27_deberta_v3_large_frozen_pipeline_en.md
new file mode 100644
index 00000000000000..bbe7072b03a1d8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-judge_answer__27_deberta_v3_large_frozen_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English judge_answer__27_deberta_v3_large_frozen_pipeline pipeline DeBertaForSequenceClassification from tom-010
+author: John Snow Labs
+name: judge_answer__27_deberta_v3_large_frozen_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`judge_answer__27_deberta_v3_large_frozen_pipeline` is a English model originally trained by tom-010.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/judge_answer__27_deberta_v3_large_frozen_pipeline_en_5.5.1_3.0_1737657757241.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/judge_answer__27_deberta_v3_large_frozen_pipeline_en_5.5.1_3.0_1737657757241.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("judge_answer__27_deberta_v3_large_frozen_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("judge_answer__27_deberta_v3_large_frozen_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|judge_answer__27_deberta_v3_large_frozen_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/tom-010/judge_answer__27_deberta_v3_large_frozen
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-labse_english_russian_finetuned_nlu_en.md b/docs/_posts/ahmedlone127/2025-01-23-labse_english_russian_finetuned_nlu_en.md
new file mode 100644
index 00000000000000..5247a57706a17c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-labse_english_russian_finetuned_nlu_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English labse_english_russian_finetuned_nlu BertEmbeddings from Maldopast
+author: John Snow Labs
+name: labse_english_russian_finetuned_nlu
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`labse_english_russian_finetuned_nlu` is a English model originally trained by Maldopast.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/labse_english_russian_finetuned_nlu_en_5.5.1_3.0_1737637393222.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/labse_english_russian_finetuned_nlu_en_5.5.1_3.0_1737637393222.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("labse_english_russian_finetuned_nlu","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("labse_english_russian_finetuned_nlu","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|labse_english_russian_finetuned_nlu|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|480.3 MB|
+
+## References
+
+https://huggingface.co/Maldopast/LaBSE-en-ru-finetuned-nlu
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-labse_english_russian_finetuned_nlu_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-labse_english_russian_finetuned_nlu_pipeline_en.md
new file mode 100644
index 00000000000000..87d6f032bb66fb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-labse_english_russian_finetuned_nlu_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English labse_english_russian_finetuned_nlu_pipeline pipeline BertEmbeddings from Maldopast
+author: John Snow Labs
+name: labse_english_russian_finetuned_nlu_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`labse_english_russian_finetuned_nlu_pipeline` is a English model originally trained by Maldopast.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/labse_english_russian_finetuned_nlu_pipeline_en_5.5.1_3.0_1737637418670.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/labse_english_russian_finetuned_nlu_pipeline_en_5.5.1_3.0_1737637418670.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("labse_english_russian_finetuned_nlu_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("labse_english_russian_finetuned_nlu_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|labse_english_russian_finetuned_nlu_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|480.4 MB|
+
+## References
+
+https://huggingface.co/Maldopast/LaBSE-en-ru-finetuned-nlu
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-language_detection_tuesdaylatenight_en.md b/docs/_posts/ahmedlone127/2025-01-23-language_detection_tuesdaylatenight_en.md
new file mode 100644
index 00000000000000..3d4f3d1300b1d8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-language_detection_tuesdaylatenight_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English language_detection_tuesdaylatenight XlmRoBertaForSequenceClassification from sirgecko
+author: John Snow Labs
+name: language_detection_tuesdaylatenight
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`language_detection_tuesdaylatenight` is a English model originally trained by sirgecko.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/language_detection_tuesdaylatenight_en_5.5.1_3.0_1737653647777.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/language_detection_tuesdaylatenight_en_5.5.1_3.0_1737653647777.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("language_detection_tuesdaylatenight","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("language_detection_tuesdaylatenight", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|language_detection_tuesdaylatenight|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|870.4 MB|
+
+## References
+
+https://huggingface.co/sirgecko/language_detection_tuesdaylatenight
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-language_detection_tuesdaylatenight_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-language_detection_tuesdaylatenight_pipeline_en.md
new file mode 100644
index 00000000000000..047ca174ecd107
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-language_detection_tuesdaylatenight_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English language_detection_tuesdaylatenight_pipeline pipeline XlmRoBertaForSequenceClassification from sirgecko
+author: John Snow Labs
+name: language_detection_tuesdaylatenight_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`language_detection_tuesdaylatenight_pipeline` is a English model originally trained by sirgecko.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/language_detection_tuesdaylatenight_pipeline_en_5.5.1_3.0_1737653757087.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/language_detection_tuesdaylatenight_pipeline_en_5.5.1_3.0_1737653757087.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("language_detection_tuesdaylatenight_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("language_detection_tuesdaylatenight_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|language_detection_tuesdaylatenight_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|870.4 MB|
+
+## References
+
+https://huggingface.co/sirgecko/language_detection_tuesdaylatenight
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-longclip_saban_vit_l_14_en.md b/docs/_posts/ahmedlone127/2025-01-23-longclip_saban_vit_l_14_en.md
new file mode 100644
index 00000000000000..8bba3c47b68962
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-longclip_saban_vit_l_14_en.md
@@ -0,0 +1,120 @@
+---
+layout: model
+title: English longclip_saban_vit_l_14 CLIPForZeroShotClassification from zer0int
+author: John Snow Labs
+name: longclip_saban_vit_l_14
+date: 2025-01-23
+tags: [en, open_source, onnx, zero_shot, clip, image]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CLIPForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`longclip_saban_vit_l_14` is a English model originally trained by zer0int.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/longclip_saban_vit_l_14_en_5.5.1_3.0_1737631436372.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/longclip_saban_vit_l_14_en_5.5.1_3.0_1737631436372.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+imageDF = spark.read \
+    .format("image") \
+    .option("dropInvalid", value = True) \
+    .load("src/test/resources/image/")
+    
+candidateLabels = [
+    "a photo of a bird",
+    "a photo of a cat",
+    "a photo of a dog",
+    "a photo of a hen",
+    "a photo of a hippo",
+    "a photo of a room",
+    "a photo of a tractor",
+    "a photo of an ostrich",
+    "a photo of an ox"]
+
+ImageAssembler = ImageAssembler() \
+	.setInputCol("image") \
+	.setOutputCol("image_assembler")
+
+imageClassifier = CLIPForZeroShotClassification.pretrained("longclip_saban_vit_l_14","en") \
+     .setInputCols(["image_assembler"]) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+
+pipeline = Pipeline().setStages([ImageAssembler, imageClassifier])
+pipelineModel = pipeline.fit(imageDF)
+pipelineDF = pipelineModel.transform(imageDF)
+
+
+```
+```scala
+
+		
+val imageDF = ResourceHelper.spark.read
+  .format("image")
+  .option("dropInvalid", value = true)
+  .load("src/test/resources/image/")
+
+val candidateLabels = Array(
+  "a photo of a bird",
+  "a photo of a cat",
+  "a photo of a dog",
+  "a photo of a hen",
+  "a photo of a hippo",
+  "a photo of a room",
+  "a photo of a tractor",
+  "a photo of an ostrich",
+  "a photo of an ox")
+
+val imageAssembler = new ImageAssembler()
+  .setInputCol("image")
+  .setOutputCol("image_assembler")
+  
+val imageClassifier = CLIPForZeroShotClassification.pretrained("longclip_saban_vit_l_14","en") \
+     .setInputCols(Array("image_assembler")) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+  
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+val pipelineModel = pipeline.fit(imageDF)
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|longclip_saban_vit_l_14|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/zer0int/LongCLIP-SAE-ViT-L-14
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-longclip_saban_vit_l_14_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-longclip_saban_vit_l_14_pipeline_en.md
new file mode 100644
index 00000000000000..432cafd4698693
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-longclip_saban_vit_l_14_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English longclip_saban_vit_l_14_pipeline pipeline CLIPForZeroShotClassification from zer0int
+author: John Snow Labs
+name: longclip_saban_vit_l_14_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`longclip_saban_vit_l_14_pipeline` is a English model originally trained by zer0int.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/longclip_saban_vit_l_14_pipeline_en_5.5.1_3.0_1737631718789.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/longclip_saban_vit_l_14_pipeline_en_5.5.1_3.0_1737631718789.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("longclip_saban_vit_l_14_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("longclip_saban_vit_l_14_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|longclip_saban_vit_l_14_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/zer0int/LongCLIP-SAE-ViT-L-14
+
+## Included Models
+
+- ImageAssembler
+- CLIPForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-m2_bert_2k_retrieval_encoder_v1_en.md b/docs/_posts/ahmedlone127/2025-01-23-m2_bert_2k_retrieval_encoder_v1_en.md
new file mode 100644
index 00000000000000..b599ada5e1eb58
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-m2_bert_2k_retrieval_encoder_v1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English m2_bert_2k_retrieval_encoder_v1 BertEmbeddings from hazyresearch
+author: John Snow Labs
+name: m2_bert_2k_retrieval_encoder_v1
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`m2_bert_2k_retrieval_encoder_v1` is a English model originally trained by hazyresearch.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/m2_bert_2k_retrieval_encoder_v1_en_5.5.1_3.0_1737637932595.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/m2_bert_2k_retrieval_encoder_v1_en_5.5.1_3.0_1737637932595.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("m2_bert_2k_retrieval_encoder_v1","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("m2_bert_2k_retrieval_encoder_v1","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|m2_bert_2k_retrieval_encoder_v1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|410.4 MB|
+
+## References
+
+https://huggingface.co/hazyresearch/M2-BERT-2k-Retrieval-Encoder-V1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-m2_bert_2k_retrieval_encoder_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-m2_bert_2k_retrieval_encoder_v1_pipeline_en.md
new file mode 100644
index 00000000000000..9fa5532b84458e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-m2_bert_2k_retrieval_encoder_v1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English m2_bert_2k_retrieval_encoder_v1_pipeline pipeline BertEmbeddings from hazyresearch
+author: John Snow Labs
+name: m2_bert_2k_retrieval_encoder_v1_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`m2_bert_2k_retrieval_encoder_v1_pipeline` is a English model originally trained by hazyresearch.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/m2_bert_2k_retrieval_encoder_v1_pipeline_en_5.5.1_3.0_1737637954659.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/m2_bert_2k_retrieval_encoder_v1_pipeline_en_5.5.1_3.0_1737637954659.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("m2_bert_2k_retrieval_encoder_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("m2_bert_2k_retrieval_encoder_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|m2_bert_2k_retrieval_encoder_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.4 MB|
+
+## References
+
+https://huggingface.co/hazyresearch/M2-BERT-2k-Retrieval-Encoder-V1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-manojbagul_qna1_en.md b/docs/_posts/ahmedlone127/2025-01-23-manojbagul_qna1_en.md
new file mode 100644
index 00000000000000..d08fdd9dca5612
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-manojbagul_qna1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English manojbagul_qna1 DistilBertForQuestionAnswering from manojbagul
+author: John Snow Labs
+name: manojbagul_qna1
+date: 2025-01-23
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`manojbagul_qna1` is a English model originally trained by manojbagul.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/manojbagul_qna1_en_5.5.1_3.0_1737660556395.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/manojbagul_qna1_en_5.5.1_3.0_1737660556395.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("manojbagul_qna1","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("manojbagul_qna1", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|manojbagul_qna1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/manojbagul/ManojBagul_QnA1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-manojbagul_qna1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-manojbagul_qna1_pipeline_en.md
new file mode 100644
index 00000000000000..e4e3a76c803cf9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-manojbagul_qna1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English manojbagul_qna1_pipeline pipeline DistilBertForQuestionAnswering from manojbagul
+author: John Snow Labs
+name: manojbagul_qna1_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`manojbagul_qna1_pipeline` is a English model originally trained by manojbagul.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/manojbagul_qna1_pipeline_en_5.5.1_3.0_1737660573526.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/manojbagul_qna1_pipeline_en_5.5.1_3.0_1737660573526.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("manojbagul_qna1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("manojbagul_qna1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|manojbagul_qna1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/manojbagul/ManojBagul_QnA1
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-manojbagul_qna_en.md b/docs/_posts/ahmedlone127/2025-01-23-manojbagul_qna_en.md
new file mode 100644
index 00000000000000..b97b1c83dbe1cb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-manojbagul_qna_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English manojbagul_qna DistilBertForQuestionAnswering from manojbagul
+author: John Snow Labs
+name: manojbagul_qna
+date: 2025-01-23
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`manojbagul_qna` is a English model originally trained by manojbagul.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/manojbagul_qna_en_5.5.1_3.0_1737660189160.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/manojbagul_qna_en_5.5.1_3.0_1737660189160.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("manojbagul_qna","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("manojbagul_qna", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|manojbagul_qna|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/manojbagul/ManojBagul_QnA
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-manojbagul_qna_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-manojbagul_qna_pipeline_en.md
new file mode 100644
index 00000000000000..f0076672d8d652
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-manojbagul_qna_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English manojbagul_qna_pipeline pipeline DistilBertForQuestionAnswering from manojbagul
+author: John Snow Labs
+name: manojbagul_qna_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`manojbagul_qna_pipeline` is a English model originally trained by manojbagul.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/manojbagul_qna_pipeline_en_5.5.1_3.0_1737660202485.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/manojbagul_qna_pipeline_en_5.5.1_3.0_1737660202485.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("manojbagul_qna_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("manojbagul_qna_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|manojbagul_qna_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/manojbagul/ManojBagul_QnA
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-mask_langauge_modeling_en.md b/docs/_posts/ahmedlone127/2025-01-23-mask_langauge_modeling_en.md
new file mode 100644
index 00000000000000..6fbff85a89fa41
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-mask_langauge_modeling_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mask_langauge_modeling RoBertaEmbeddings from Hemg
+author: John Snow Labs
+name: mask_langauge_modeling
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mask_langauge_modeling` is a English model originally trained by Hemg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mask_langauge_modeling_en_5.5.1_3.0_1737644124882.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mask_langauge_modeling_en_5.5.1_3.0_1737644124882.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("mask_langauge_modeling","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("mask_langauge_modeling","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mask_langauge_modeling|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|306.3 MB|
+
+## References
+
+https://huggingface.co/Hemg/mask-langauge-modeling
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-mask_langauge_modeling_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-mask_langauge_modeling_pipeline_en.md
new file mode 100644
index 00000000000000..e519345d4c47dc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-mask_langauge_modeling_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mask_langauge_modeling_pipeline pipeline RoBertaEmbeddings from Hemg
+author: John Snow Labs
+name: mask_langauge_modeling_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mask_langauge_modeling_pipeline` is a English model originally trained by Hemg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mask_langauge_modeling_pipeline_en_5.5.1_3.0_1737644141459.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mask_langauge_modeling_pipeline_en_5.5.1_3.0_1737644141459.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mask_langauge_modeling_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mask_langauge_modeling_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mask_langauge_modeling_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|306.3 MB|
+
+## References
+
+https://huggingface.co/Hemg/mask-langauge-modeling
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-mdeberta_v3_base_autext2024_04_12_2024_detection_en.md b/docs/_posts/ahmedlone127/2025-01-23-mdeberta_v3_base_autext2024_04_12_2024_detection_en.md
new file mode 100644
index 00000000000000..442a07c717990f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-mdeberta_v3_base_autext2024_04_12_2024_detection_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mdeberta_v3_base_autext2024_04_12_2024_detection DeBertaForSequenceClassification from ISEGURA
+author: John Snow Labs
+name: mdeberta_v3_base_autext2024_04_12_2024_detection
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_autext2024_04_12_2024_detection` is a English model originally trained by ISEGURA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_autext2024_04_12_2024_detection_en_5.5.1_3.0_1737647105660.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_autext2024_04_12_2024_detection_en_5.5.1_3.0_1737647105660.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_autext2024_04_12_2024_detection","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_autext2024_04_12_2024_detection", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_autext2024_04_12_2024_detection|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|898.0 MB|
+
+## References
+
+https://huggingface.co/ISEGURA/mdeberta-v3-base-autext2024_04-12-2024_detection
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-mdeberta_v3_base_autext2024_04_12_2024_detection_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-mdeberta_v3_base_autext2024_04_12_2024_detection_pipeline_en.md
new file mode 100644
index 00000000000000..8378c748ea88b7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-mdeberta_v3_base_autext2024_04_12_2024_detection_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mdeberta_v3_base_autext2024_04_12_2024_detection_pipeline pipeline DeBertaForSequenceClassification from ISEGURA
+author: John Snow Labs
+name: mdeberta_v3_base_autext2024_04_12_2024_detection_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_autext2024_04_12_2024_detection_pipeline` is a English model originally trained by ISEGURA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_autext2024_04_12_2024_detection_pipeline_en_5.5.1_3.0_1737647199992.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_autext2024_04_12_2024_detection_pipeline_en_5.5.1_3.0_1737647199992.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mdeberta_v3_base_autext2024_04_12_2024_detection_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mdeberta_v3_base_autext2024_04_12_2024_detection_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_autext2024_04_12_2024_detection_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|898.0 MB|
+
+## References
+
+https://huggingface.co/ISEGURA/mdeberta-v3-base-autext2024_04-12-2024_detection
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-mdeberta_v3_base_autext2024_05_12_2024_attribution_en.md b/docs/_posts/ahmedlone127/2025-01-23-mdeberta_v3_base_autext2024_05_12_2024_attribution_en.md
new file mode 100644
index 00000000000000..f3ca048f1a82cc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-mdeberta_v3_base_autext2024_05_12_2024_attribution_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mdeberta_v3_base_autext2024_05_12_2024_attribution DeBertaForSequenceClassification from ISEGURA
+author: John Snow Labs
+name: mdeberta_v3_base_autext2024_05_12_2024_attribution
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_autext2024_05_12_2024_attribution` is a English model originally trained by ISEGURA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_autext2024_05_12_2024_attribution_en_5.5.1_3.0_1737657236040.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_autext2024_05_12_2024_attribution_en_5.5.1_3.0_1737657236040.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_autext2024_05_12_2024_attribution","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_autext2024_05_12_2024_attribution", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_autext2024_05_12_2024_attribution|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|880.4 MB|
+
+## References
+
+https://huggingface.co/ISEGURA/mdeberta-v3-base-autext2024_05-12-2024_attribution
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-mdeberta_v3_base_autext2024_05_12_2024_attribution_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-mdeberta_v3_base_autext2024_05_12_2024_attribution_pipeline_en.md
new file mode 100644
index 00000000000000..54aff8ed007130
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-mdeberta_v3_base_autext2024_05_12_2024_attribution_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mdeberta_v3_base_autext2024_05_12_2024_attribution_pipeline pipeline DeBertaForSequenceClassification from ISEGURA
+author: John Snow Labs
+name: mdeberta_v3_base_autext2024_05_12_2024_attribution_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_autext2024_05_12_2024_attribution_pipeline` is a English model originally trained by ISEGURA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_autext2024_05_12_2024_attribution_pipeline_en_5.5.1_3.0_1737657333077.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_autext2024_05_12_2024_attribution_pipeline_en_5.5.1_3.0_1737657333077.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mdeberta_v3_base_autext2024_05_12_2024_attribution_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mdeberta_v3_base_autext2024_05_12_2024_attribution_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_autext2024_05_12_2024_attribution_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|880.4 MB|
+
+## References
+
+https://huggingface.co/ISEGURA/mdeberta-v3-base-autext2024_05-12-2024_attribution
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-mdeberta_v3_base_autext2024_80train_attribution_en.md b/docs/_posts/ahmedlone127/2025-01-23-mdeberta_v3_base_autext2024_80train_attribution_en.md
new file mode 100644
index 00000000000000..5f8aa4aad8d293
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-mdeberta_v3_base_autext2024_80train_attribution_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mdeberta_v3_base_autext2024_80train_attribution DeBertaForSequenceClassification from ISEGURA
+author: John Snow Labs
+name: mdeberta_v3_base_autext2024_80train_attribution
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_autext2024_80train_attribution` is a English model originally trained by ISEGURA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_autext2024_80train_attribution_en_5.5.1_3.0_1737655847794.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_autext2024_80train_attribution_en_5.5.1_3.0_1737655847794.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_autext2024_80train_attribution","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_autext2024_80train_attribution", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_autext2024_80train_attribution|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|850.1 MB|
+
+## References
+
+https://huggingface.co/ISEGURA/mdeberta-v3-base-autext2024_80train_attribution
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-mdeberta_v3_base_autext2024_80train_attribution_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-mdeberta_v3_base_autext2024_80train_attribution_pipeline_en.md
new file mode 100644
index 00000000000000..fd76fb2d75165d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-mdeberta_v3_base_autext2024_80train_attribution_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mdeberta_v3_base_autext2024_80train_attribution_pipeline pipeline DeBertaForSequenceClassification from ISEGURA
+author: John Snow Labs
+name: mdeberta_v3_base_autext2024_80train_attribution_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_autext2024_80train_attribution_pipeline` is a English model originally trained by ISEGURA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_autext2024_80train_attribution_pipeline_en_5.5.1_3.0_1737655970090.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_autext2024_80train_attribution_pipeline_en_5.5.1_3.0_1737655970090.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mdeberta_v3_base_autext2024_80train_attribution_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mdeberta_v3_base_autext2024_80train_attribution_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_autext2024_80train_attribution_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|850.1 MB|
+
+## References
+
+https://huggingface.co/ISEGURA/mdeberta-v3-base-autext2024_80train_attribution
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-mdeberta_v3_base_autext2024_80train_detection_en.md b/docs/_posts/ahmedlone127/2025-01-23-mdeberta_v3_base_autext2024_80train_detection_en.md
new file mode 100644
index 00000000000000..807346a3fa5f30
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-mdeberta_v3_base_autext2024_80train_detection_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mdeberta_v3_base_autext2024_80train_detection DeBertaForSequenceClassification from ISEGURA
+author: John Snow Labs
+name: mdeberta_v3_base_autext2024_80train_detection
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_autext2024_80train_detection` is a English model originally trained by ISEGURA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_autext2024_80train_detection_en_5.5.1_3.0_1737657311437.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_autext2024_80train_detection_en_5.5.1_3.0_1737657311437.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_autext2024_80train_detection","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_autext2024_80train_detection", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_autext2024_80train_detection|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|861.3 MB|
+
+## References
+
+https://huggingface.co/ISEGURA/mdeberta-v3-base-autext2024_80train_detection
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-mdeberta_v3_base_autext2024_80train_detection_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-mdeberta_v3_base_autext2024_80train_detection_pipeline_en.md
new file mode 100644
index 00000000000000..884cddb6d18e8b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-mdeberta_v3_base_autext2024_80train_detection_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mdeberta_v3_base_autext2024_80train_detection_pipeline pipeline DeBertaForSequenceClassification from ISEGURA
+author: John Snow Labs
+name: mdeberta_v3_base_autext2024_80train_detection_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_autext2024_80train_detection_pipeline` is a English model originally trained by ISEGURA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_autext2024_80train_detection_pipeline_en_5.5.1_3.0_1737657430439.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_autext2024_80train_detection_pipeline_en_5.5.1_3.0_1737657430439.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mdeberta_v3_base_autext2024_80train_detection_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mdeberta_v3_base_autext2024_80train_detection_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_autext2024_80train_detection_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|861.3 MB|
+
+## References
+
+https://huggingface.co/ISEGURA/mdeberta-v3-base-autext2024_80train_detection
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-mdeberta_v3_base_autext2024_attribution_en.md b/docs/_posts/ahmedlone127/2025-01-23-mdeberta_v3_base_autext2024_attribution_en.md
new file mode 100644
index 00000000000000..bcf499ce15a12f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-mdeberta_v3_base_autext2024_attribution_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mdeberta_v3_base_autext2024_attribution DeBertaForSequenceClassification from ISEGURA
+author: John Snow Labs
+name: mdeberta_v3_base_autext2024_attribution
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_autext2024_attribution` is a English model originally trained by ISEGURA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_autext2024_attribution_en_5.5.1_3.0_1737647754677.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_autext2024_attribution_en_5.5.1_3.0_1737647754677.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_autext2024_attribution","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_autext2024_attribution", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_autext2024_attribution|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|854.9 MB|
+
+## References
+
+https://huggingface.co/ISEGURA/mdeberta-v3-base-autext2024_attribution
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-mdeberta_v3_base_autext2024_attribution_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-mdeberta_v3_base_autext2024_attribution_pipeline_en.md
new file mode 100644
index 00000000000000..2d6287091590af
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-mdeberta_v3_base_autext2024_attribution_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mdeberta_v3_base_autext2024_attribution_pipeline pipeline DeBertaForSequenceClassification from ISEGURA
+author: John Snow Labs
+name: mdeberta_v3_base_autext2024_attribution_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_autext2024_attribution_pipeline` is a English model originally trained by ISEGURA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_autext2024_attribution_pipeline_en_5.5.1_3.0_1737647880661.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_autext2024_attribution_pipeline_en_5.5.1_3.0_1737647880661.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mdeberta_v3_base_autext2024_attribution_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mdeberta_v3_base_autext2024_attribution_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_autext2024_attribution_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|855.0 MB|
+
+## References
+
+https://huggingface.co/ISEGURA/mdeberta-v3-base-autext2024_attribution
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-mdeberta_v3_base_autext_en.md b/docs/_posts/ahmedlone127/2025-01-23-mdeberta_v3_base_autext_en.md
new file mode 100644
index 00000000000000..169fc11c69e8cf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-mdeberta_v3_base_autext_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mdeberta_v3_base_autext DeBertaForSequenceClassification from jorgefg03
+author: John Snow Labs
+name: mdeberta_v3_base_autext
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_autext` is a English model originally trained by jorgefg03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_autext_en_5.5.1_3.0_1737647681351.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_autext_en_5.5.1_3.0_1737647681351.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_autext","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_autext", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_autext|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|819.2 MB|
+
+## References
+
+https://huggingface.co/jorgefg03/mdeberta-v3-base-autext
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-mdeberta_v3_base_autext_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-mdeberta_v3_base_autext_pipeline_en.md
new file mode 100644
index 00000000000000..5c3fdc7269852c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-mdeberta_v3_base_autext_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mdeberta_v3_base_autext_pipeline pipeline DeBertaForSequenceClassification from jorgefg03
+author: John Snow Labs
+name: mdeberta_v3_base_autext_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_autext_pipeline` is a English model originally trained by jorgefg03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_autext_pipeline_en_5.5.1_3.0_1737647821934.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_autext_pipeline_en_5.5.1_3.0_1737647821934.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mdeberta_v3_base_autext_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mdeberta_v3_base_autext_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_autext_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|819.3 MB|
+
+## References
+
+https://huggingface.co/jorgefg03/mdeberta-v3-base-autext
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-mdeberta_v3_base_qa_en.md b/docs/_posts/ahmedlone127/2025-01-23-mdeberta_v3_base_qa_en.md
new file mode 100644
index 00000000000000..8be7922edf5f03
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-mdeberta_v3_base_qa_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mdeberta_v3_base_qa DeBertaForQuestionAnswering from alynakbaba
+author: John Snow Labs
+name: mdeberta_v3_base_qa
+date: 2025-01-23
+tags: [en, open_source, onnx, question_answering, deberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_qa` is a English model originally trained by alynakbaba.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_qa_en_5.5.1_3.0_1737664273146.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_qa_en_5.5.1_3.0_1737664273146.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DeBertaForQuestionAnswering.pretrained("mdeberta_v3_base_qa","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DeBertaForQuestionAnswering.pretrained("mdeberta_v3_base_qa", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_qa|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|808.7 MB|
+
+## References
+
+https://huggingface.co/alynakbaba/mdeberta-v3-base-QA
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-mdeberta_v3_base_qa_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-mdeberta_v3_base_qa_pipeline_en.md
new file mode 100644
index 00000000000000..659dba77f24434
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-mdeberta_v3_base_qa_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mdeberta_v3_base_qa_pipeline pipeline DeBertaForQuestionAnswering from alynakbaba
+author: John Snow Labs
+name: mdeberta_v3_base_qa_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_qa_pipeline` is a English model originally trained by alynakbaba.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_qa_pipeline_en_5.5.1_3.0_1737664393909.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_qa_pipeline_en_5.5.1_3.0_1737664393909.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mdeberta_v3_base_qa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mdeberta_v3_base_qa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_qa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|808.7 MB|
+
+## References
+
+https://huggingface.co/alynakbaba/mdeberta-v3-base-QA
+
+## Included Models
+
+- MultiDocumentAssembler
+- DeBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-merged_albert_sst2_lora_en.md b/docs/_posts/ahmedlone127/2025-01-23-merged_albert_sst2_lora_en.md
new file mode 100644
index 00000000000000..26994e8d62dabb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-merged_albert_sst2_lora_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English merged_albert_sst2_lora AlbertForSequenceClassification from asm3515
+author: John Snow Labs
+name: merged_albert_sst2_lora
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, albert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`merged_albert_sst2_lora` is a English model originally trained by asm3515.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/merged_albert_sst2_lora_en_5.5.1_3.0_1737624320884.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/merged_albert_sst2_lora_en_5.5.1_3.0_1737624320884.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = AlbertForSequenceClassification.pretrained("merged_albert_sst2_lora","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = AlbertForSequenceClassification.pretrained("merged_albert_sst2_lora", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|merged_albert_sst2_lora|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/asm3515/merged-albert-sst2-lora
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-merged_albert_sst2_lora_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-merged_albert_sst2_lora_pipeline_en.md
new file mode 100644
index 00000000000000..1808252854668f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-merged_albert_sst2_lora_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English merged_albert_sst2_lora_pipeline pipeline AlbertForSequenceClassification from asm3515
+author: John Snow Labs
+name: merged_albert_sst2_lora_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`merged_albert_sst2_lora_pipeline` is a English model originally trained by asm3515.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/merged_albert_sst2_lora_pipeline_en_5.5.1_3.0_1737624323216.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/merged_albert_sst2_lora_pipeline_en_5.5.1_3.0_1737624323216.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("merged_albert_sst2_lora_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("merged_albert_sst2_lora_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|merged_albert_sst2_lora_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/asm3515/merged-albert-sst2-lora
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-merged_distillbert_agnews_lora_en.md b/docs/_posts/ahmedlone127/2025-01-23-merged_distillbert_agnews_lora_en.md
new file mode 100644
index 00000000000000..3b90897672a3b5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-merged_distillbert_agnews_lora_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English merged_distillbert_agnews_lora DistilBertForSequenceClassification from asm3515
+author: John Snow Labs
+name: merged_distillbert_agnews_lora
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`merged_distillbert_agnews_lora` is a English model originally trained by asm3515.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/merged_distillbert_agnews_lora_en_5.5.1_3.0_1737650708291.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/merged_distillbert_agnews_lora_en_5.5.1_3.0_1737650708291.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("merged_distillbert_agnews_lora","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("merged_distillbert_agnews_lora", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|merged_distillbert_agnews_lora|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/asm3515/merged-distillbert-agnews-lora
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-merged_distillbert_agnews_lora_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-merged_distillbert_agnews_lora_pipeline_en.md
new file mode 100644
index 00000000000000..fe04bea0a74a72
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-merged_distillbert_agnews_lora_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English merged_distillbert_agnews_lora_pipeline pipeline DistilBertForSequenceClassification from asm3515
+author: John Snow Labs
+name: merged_distillbert_agnews_lora_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`merged_distillbert_agnews_lora_pipeline` is a English model originally trained by asm3515.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/merged_distillbert_agnews_lora_pipeline_en_5.5.1_3.0_1737650722363.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/merged_distillbert_agnews_lora_pipeline_en_5.5.1_3.0_1737650722363.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("merged_distillbert_agnews_lora_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("merged_distillbert_agnews_lora_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|merged_distillbert_agnews_lora_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/asm3515/merged-distillbert-agnews-lora
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-mfds_all_mpnet_base_v2_en.md b/docs/_posts/ahmedlone127/2025-01-23-mfds_all_mpnet_base_v2_en.md
new file mode 100644
index 00000000000000..681c0255b4be71
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-mfds_all_mpnet_base_v2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mfds_all_mpnet_base_v2 MPNetEmbeddings from pedutronix
+author: John Snow Labs
+name: mfds_all_mpnet_base_v2
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mfds_all_mpnet_base_v2` is a English model originally trained by pedutronix.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mfds_all_mpnet_base_v2_en_5.5.1_3.0_1737669551632.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mfds_all_mpnet_base_v2_en_5.5.1_3.0_1737669551632.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("mfds_all_mpnet_base_v2","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("mfds_all_mpnet_base_v2","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mfds_all_mpnet_base_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.7 MB|
+
+## References
+
+https://huggingface.co/pedutronix/mfds-all-mpnet-base-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-mfds_all_mpnet_base_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-mfds_all_mpnet_base_v2_pipeline_en.md
new file mode 100644
index 00000000000000..b7ffebed114d02
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-mfds_all_mpnet_base_v2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mfds_all_mpnet_base_v2_pipeline pipeline MPNetEmbeddings from pedutronix
+author: John Snow Labs
+name: mfds_all_mpnet_base_v2_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mfds_all_mpnet_base_v2_pipeline` is a English model originally trained by pedutronix.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mfds_all_mpnet_base_v2_pipeline_en_5.5.1_3.0_1737669577896.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mfds_all_mpnet_base_v2_pipeline_en_5.5.1_3.0_1737669577896.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mfds_all_mpnet_base_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mfds_all_mpnet_base_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mfds_all_mpnet_base_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.7 MB|
+
+## References
+
+https://huggingface.co/pedutronix/mfds-all-mpnet-base-v2
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-model_albert_en.md b/docs/_posts/ahmedlone127/2025-01-23-model_albert_en.md
new file mode 100644
index 00000000000000..297ba0065e5431
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-model_albert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English model_albert AlbertForSequenceClassification from KalaiselvanD
+author: John Snow Labs
+name: model_albert
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, albert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_albert` is a English model originally trained by KalaiselvanD.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_albert_en_5.5.1_3.0_1737624534352.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_albert_en_5.5.1_3.0_1737624534352.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = AlbertForSequenceClassification.pretrained("model_albert","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = AlbertForSequenceClassification.pretrained("model_albert", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|model_albert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/KalaiselvanD/model_albert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-model_albert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-model_albert_pipeline_en.md
new file mode 100644
index 00000000000000..f1d09103418a7d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-model_albert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English model_albert_pipeline pipeline AlbertForSequenceClassification from KalaiselvanD
+author: John Snow Labs
+name: model_albert_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_albert_pipeline` is a English model originally trained by KalaiselvanD.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_albert_pipeline_en_5.5.1_3.0_1737624536991.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_albert_pipeline_en_5.5.1_3.0_1737624536991.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("model_albert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("model_albert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|model_albert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/KalaiselvanD/model_albert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-model_ner_en.md b/docs/_posts/ahmedlone127/2025-01-23-model_ner_en.md
new file mode 100644
index 00000000000000..4d7f19bc10e61d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-model_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English model_ner CamemBertForTokenClassification from rdetch22
+author: John Snow Labs
+name: model_ner
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, camembert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_ner` is a English model originally trained by rdetch22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_ner_en_5.5.1_3.0_1737641576080.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_ner_en_5.5.1_3.0_1737641576080.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = CamemBertForTokenClassification.pretrained("model_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = CamemBertForTokenClassification.pretrained("model_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|model_ner|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|411.9 MB|
+
+## References
+
+https://huggingface.co/rdetch22/model_ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-model_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-model_ner_pipeline_en.md
new file mode 100644
index 00000000000000..739611182764f6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-model_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English model_ner_pipeline pipeline CamemBertForTokenClassification from rdetch22
+author: John Snow Labs
+name: model_ner_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_ner_pipeline` is a English model originally trained by rdetch22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_ner_pipeline_en_5.5.1_3.0_1737641598273.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_ner_pipeline_en_5.5.1_3.0_1737641598273.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("model_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("model_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|model_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|411.9 MB|
+
+## References
+
+https://huggingface.co/rdetch22/model_ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-mpnet_base_finetune_triplet_en.md b/docs/_posts/ahmedlone127/2025-01-23-mpnet_base_finetune_triplet_en.md
new file mode 100644
index 00000000000000..b2f6184404b491
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-mpnet_base_finetune_triplet_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mpnet_base_finetune_triplet MPNetEmbeddings from mircoboettcher
+author: John Snow Labs
+name: mpnet_base_finetune_triplet
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mpnet_base_finetune_triplet` is a English model originally trained by mircoboettcher.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mpnet_base_finetune_triplet_en_5.5.1_3.0_1737670277540.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_base_finetune_triplet_en_5.5.1_3.0_1737670277540.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("mpnet_base_finetune_triplet","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("mpnet_base_finetune_triplet","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mpnet_base_finetune_triplet|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|379.9 MB|
+
+## References
+
+https://huggingface.co/mircoboettcher/mpnet-base-finetune-triplet
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-mpnet_base_finetune_triplet_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-mpnet_base_finetune_triplet_pipeline_en.md
new file mode 100644
index 00000000000000..ebf1ce12992691
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-mpnet_base_finetune_triplet_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mpnet_base_finetune_triplet_pipeline pipeline MPNetEmbeddings from mircoboettcher
+author: John Snow Labs
+name: mpnet_base_finetune_triplet_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mpnet_base_finetune_triplet_pipeline` is a English model originally trained by mircoboettcher.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mpnet_base_finetune_triplet_pipeline_en_5.5.1_3.0_1737670309416.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_base_finetune_triplet_pipeline_en_5.5.1_3.0_1737670309416.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mpnet_base_finetune_triplet_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mpnet_base_finetune_triplet_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mpnet_base_finetune_triplet_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|379.9 MB|
+
+## References
+
+https://huggingface.co/mircoboettcher/mpnet-base-finetune-triplet
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-mpnet_jacket4k_en.md b/docs/_posts/ahmedlone127/2025-01-23-mpnet_jacket4k_en.md
new file mode 100644
index 00000000000000..6788575779c8f3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-mpnet_jacket4k_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mpnet_jacket4k MPNetEmbeddings from knguyennguyen
+author: John Snow Labs
+name: mpnet_jacket4k
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mpnet_jacket4k` is a English model originally trained by knguyennguyen.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mpnet_jacket4k_en_5.5.1_3.0_1737669750148.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_jacket4k_en_5.5.1_3.0_1737669750148.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("mpnet_jacket4k","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("mpnet_jacket4k","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mpnet_jacket4k|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.7 MB|
+
+## References
+
+https://huggingface.co/knguyennguyen/mpnet_jacket4k
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-mpnet_jacket4k_enhanced_en.md b/docs/_posts/ahmedlone127/2025-01-23-mpnet_jacket4k_enhanced_en.md
new file mode 100644
index 00000000000000..357ad6d6815cb1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-mpnet_jacket4k_enhanced_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mpnet_jacket4k_enhanced MPNetEmbeddings from knguyennguyen
+author: John Snow Labs
+name: mpnet_jacket4k_enhanced
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mpnet_jacket4k_enhanced` is a English model originally trained by knguyennguyen.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mpnet_jacket4k_enhanced_en_5.5.1_3.0_1737670039443.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_jacket4k_enhanced_en_5.5.1_3.0_1737670039443.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("mpnet_jacket4k_enhanced","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("mpnet_jacket4k_enhanced","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mpnet_jacket4k_enhanced|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.7 MB|
+
+## References
+
+https://huggingface.co/knguyennguyen/mpnet_jacket4k_enhanced
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-mpnet_jacket4k_enhanced_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-mpnet_jacket4k_enhanced_pipeline_en.md
new file mode 100644
index 00000000000000..167b28ccad8314
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-mpnet_jacket4k_enhanced_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mpnet_jacket4k_enhanced_pipeline pipeline MPNetEmbeddings from knguyennguyen
+author: John Snow Labs
+name: mpnet_jacket4k_enhanced_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mpnet_jacket4k_enhanced_pipeline` is a English model originally trained by knguyennguyen.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mpnet_jacket4k_enhanced_pipeline_en_5.5.1_3.0_1737670062091.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_jacket4k_enhanced_pipeline_en_5.5.1_3.0_1737670062091.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mpnet_jacket4k_enhanced_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mpnet_jacket4k_enhanced_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mpnet_jacket4k_enhanced_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.7 MB|
+
+## References
+
+https://huggingface.co/knguyennguyen/mpnet_jacket4k_enhanced
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-mpnet_jacket4k_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-mpnet_jacket4k_pipeline_en.md
new file mode 100644
index 00000000000000..1934225e4e6bc3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-mpnet_jacket4k_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mpnet_jacket4k_pipeline pipeline MPNetEmbeddings from knguyennguyen
+author: John Snow Labs
+name: mpnet_jacket4k_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mpnet_jacket4k_pipeline` is a English model originally trained by knguyennguyen.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mpnet_jacket4k_pipeline_en_5.5.1_3.0_1737669773053.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_jacket4k_pipeline_en_5.5.1_3.0_1737669773053.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mpnet_jacket4k_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mpnet_jacket4k_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mpnet_jacket4k_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.7 MB|
+
+## References
+
+https://huggingface.co/knguyennguyen/mpnet_jacket4k
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-mt5_small_gigatrue_en.md b/docs/_posts/ahmedlone127/2025-01-23-mt5_small_gigatrue_en.md
new file mode 100644
index 00000000000000..6b0d25ffd00980
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-mt5_small_gigatrue_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mt5_small_gigatrue T5Transformer from Plasmoxy
+author: John Snow Labs
+name: mt5_small_gigatrue
+date: 2025-01-23
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_small_gigatrue` is a English model originally trained by Plasmoxy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_small_gigatrue_en_5.5.1_3.0_1737635950862.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_small_gigatrue_en_5.5.1_3.0_1737635950862.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("mt5_small_gigatrue","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("mt5_small_gigatrue", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_small_gigatrue|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|816.7 MB|
+
+## References
+
+https://huggingface.co/Plasmoxy/mt5-small-gigatrue
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-mt5_small_gigatrue_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-mt5_small_gigatrue_pipeline_en.md
new file mode 100644
index 00000000000000..e214065afaef54
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-mt5_small_gigatrue_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mt5_small_gigatrue_pipeline pipeline T5Transformer from Plasmoxy
+author: John Snow Labs
+name: mt5_small_gigatrue_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_small_gigatrue_pipeline` is a English model originally trained by Plasmoxy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_small_gigatrue_pipeline_en_5.5.1_3.0_1737636231630.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_small_gigatrue_pipeline_en_5.5.1_3.0_1737636231630.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mt5_small_gigatrue_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mt5_small_gigatrue_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_small_gigatrue_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|816.7 MB|
+
+## References
+
+https://huggingface.co/Plasmoxy/mt5-small-gigatrue
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-nbmed_en.md b/docs/_posts/ahmedlone127/2025-01-23-nbmed_en.md
new file mode 100644
index 00000000000000..eaa43902698a2a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-nbmed_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English nbmed T5Transformer from NamishKhurshid
+author: John Snow Labs
+name: nbmed
+date: 2025-01-23
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nbmed` is a English model originally trained by NamishKhurshid.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nbmed_en_5.5.1_3.0_1737635088406.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nbmed_en_5.5.1_3.0_1737635088406.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("nbmed","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("nbmed", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nbmed|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|349.8 MB|
+
+## References
+
+https://huggingface.co/NamishKhurshid/NBMED
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-nbmed_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-nbmed_pipeline_en.md
new file mode 100644
index 00000000000000..e9cd122215599c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-nbmed_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English nbmed_pipeline pipeline T5Transformer from NamishKhurshid
+author: John Snow Labs
+name: nbmed_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nbmed_pipeline` is a English model originally trained by NamishKhurshid.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nbmed_pipeline_en_5.5.1_3.0_1737635106794.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nbmed_pipeline_en_5.5.1_3.0_1737635106794.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("nbmed_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("nbmed_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nbmed_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|349.8 MB|
+
+## References
+
+https://huggingface.co/NamishKhurshid/NBMED
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-nepal_bhasa_accountant_en.md b/docs/_posts/ahmedlone127/2025-01-23-nepal_bhasa_accountant_en.md
new file mode 100644
index 00000000000000..4b0a0650291b47
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-nepal_bhasa_accountant_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English nepal_bhasa_accountant DistilBertForQuestionAnswering from Qusaiiii
+author: John Snow Labs
+name: nepal_bhasa_accountant
+date: 2025-01-23
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nepal_bhasa_accountant` is a English model originally trained by Qusaiiii.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nepal_bhasa_accountant_en_5.5.1_3.0_1737660386994.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nepal_bhasa_accountant_en_5.5.1_3.0_1737660386994.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("nepal_bhasa_accountant","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("nepal_bhasa_accountant", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nepal_bhasa_accountant|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Qusaiiii/New_Accountant
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-nepal_bhasa_accountant_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-nepal_bhasa_accountant_pipeline_en.md
new file mode 100644
index 00000000000000..fee30cc7802ad3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-nepal_bhasa_accountant_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English nepal_bhasa_accountant_pipeline pipeline DistilBertForQuestionAnswering from Qusaiiii
+author: John Snow Labs
+name: nepal_bhasa_accountant_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nepal_bhasa_accountant_pipeline` is a English model originally trained by Qusaiiii.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nepal_bhasa_accountant_pipeline_en_5.5.1_3.0_1737660400373.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nepal_bhasa_accountant_pipeline_en_5.5.1_3.0_1737660400373.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("nepal_bhasa_accountant_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("nepal_bhasa_accountant_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nepal_bhasa_accountant_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Qusaiiii/New_Accountant
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-nepal_bhasa_hungarian_myvoice_english_en.md b/docs/_posts/ahmedlone127/2025-01-23-nepal_bhasa_hungarian_myvoice_english_en.md
new file mode 100644
index 00000000000000..b126bc165a3e58
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-nepal_bhasa_hungarian_myvoice_english_en.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: English nepal_bhasa_hungarian_myvoice_english HubertForCTC from asago
+author: John Snow Labs
+name: nepal_bhasa_hungarian_myvoice_english
+date: 2025-01-23
+tags: [en, open_source, onnx, asr, hubert]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: HubertForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nepal_bhasa_hungarian_myvoice_english` is a English model originally trained by asago.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nepal_bhasa_hungarian_myvoice_english_en_5.5.1_3.0_1737625721176.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nepal_bhasa_hungarian_myvoice_english_en_5.5.1_3.0_1737625721176.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = HubertForCTC.pretrained("nepal_bhasa_hungarian_myvoice_english","en") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = HubertForCTC.pretrained("nepal_bhasa_hungarian_myvoice_english", "en")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nepal_bhasa_hungarian_myvoice_english|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|en|
+|Size:|2.4 GB|
+
+## References
+
+https://huggingface.co/asago/NEW_Hu_myvoice_en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-nepal_bhasa_hungarian_myvoice_english_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-nepal_bhasa_hungarian_myvoice_english_pipeline_en.md
new file mode 100644
index 00000000000000..a6710fc4ecbb17
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-nepal_bhasa_hungarian_myvoice_english_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English nepal_bhasa_hungarian_myvoice_english_pipeline pipeline HubertForCTC from asago
+author: John Snow Labs
+name: nepal_bhasa_hungarian_myvoice_english_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nepal_bhasa_hungarian_myvoice_english_pipeline` is a English model originally trained by asago.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nepal_bhasa_hungarian_myvoice_english_pipeline_en_5.5.1_3.0_1737625842709.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nepal_bhasa_hungarian_myvoice_english_pipeline_en_5.5.1_3.0_1737625842709.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("nepal_bhasa_hungarian_myvoice_english_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("nepal_bhasa_hungarian_myvoice_english_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nepal_bhasa_hungarian_myvoice_english_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|2.4 GB|
+
+## References
+
+https://huggingface.co/asago/NEW_Hu_myvoice_en
+
+## Included Models
+
+- AudioAssembler
+- HubertForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-nepali_text_correction_and_punctuation_restoration_mt5_en.md b/docs/_posts/ahmedlone127/2025-01-23-nepali_text_correction_and_punctuation_restoration_mt5_en.md
new file mode 100644
index 00000000000000..a2187ef466de5c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-nepali_text_correction_and_punctuation_restoration_mt5_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English nepali_text_correction_and_punctuation_restoration_mt5 T5Transformer from praneshp1org
+author: John Snow Labs
+name: nepali_text_correction_and_punctuation_restoration_mt5
+date: 2025-01-23
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nepali_text_correction_and_punctuation_restoration_mt5` is a English model originally trained by praneshp1org.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nepali_text_correction_and_punctuation_restoration_mt5_en_5.5.1_3.0_1737634382999.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nepali_text_correction_and_punctuation_restoration_mt5_en_5.5.1_3.0_1737634382999.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("nepali_text_correction_and_punctuation_restoration_mt5","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("nepali_text_correction_and_punctuation_restoration_mt5", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nepali_text_correction_and_punctuation_restoration_mt5|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/praneshp1org/nepali-text-correction-and-punctuation-restoration-mt5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-nepali_text_correction_and_punctuation_restoration_mt5_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-nepali_text_correction_and_punctuation_restoration_mt5_pipeline_en.md
new file mode 100644
index 00000000000000..9dd246ae5d6c92
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-nepali_text_correction_and_punctuation_restoration_mt5_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English nepali_text_correction_and_punctuation_restoration_mt5_pipeline pipeline T5Transformer from praneshp1org
+author: John Snow Labs
+name: nepali_text_correction_and_punctuation_restoration_mt5_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nepali_text_correction_and_punctuation_restoration_mt5_pipeline` is a English model originally trained by praneshp1org.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nepali_text_correction_and_punctuation_restoration_mt5_pipeline_en_5.5.1_3.0_1737634557173.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nepali_text_correction_and_punctuation_restoration_mt5_pipeline_en_5.5.1_3.0_1737634557173.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("nepali_text_correction_and_punctuation_restoration_mt5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("nepali_text_correction_and_punctuation_restoration_mt5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nepali_text_correction_and_punctuation_restoration_mt5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/praneshp1org/nepali-text-correction-and-punctuation-restoration-mt5
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-ner_conll2003_en.md b/docs/_posts/ahmedlone127/2025-01-23-ner_conll2003_en.md
new file mode 100644
index 00000000000000..4bde1f1988c13b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-ner_conll2003_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ner_conll2003 DistilBertForTokenClassification from master-mahdi
+author: John Snow Labs
+name: ner_conll2003
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_conll2003` is a English model originally trained by master-mahdi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_conll2003_en_5.5.1_3.0_1737627617543.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_conll2003_en_5.5.1_3.0_1737627617543.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("ner_conll2003","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("ner_conll2003", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_conll2003|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/master-mahdi/NER-CONLL2003
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-ner_conll2003_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-ner_conll2003_pipeline_en.md
new file mode 100644
index 00000000000000..78ca32ba205c9f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-ner_conll2003_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ner_conll2003_pipeline pipeline DistilBertForTokenClassification from master-mahdi
+author: John Snow Labs
+name: ner_conll2003_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_conll2003_pipeline` is a English model originally trained by master-mahdi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_conll2003_pipeline_en_5.5.1_3.0_1737627632452.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_conll2003_pipeline_en_5.5.1_3.0_1737627632452.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ner_conll2003_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ner_conll2003_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_conll2003_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/master-mahdi/NER-CONLL2003
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-ner_en.md b/docs/_posts/ahmedlone127/2025-01-23-ner_en.md
new file mode 100644
index 00000000000000..c8b8116a7af9bc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-ner_en.md
@@ -0,0 +1,96 @@
+---
+layout: model
+title: English ner XlmRoBertaForTokenClassification from Somesh140
+author: John Snow Labs
+name: ner
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner` is a English model originally trained by Somesh140.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_en_5.5.1_3.0_1737627505995.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_en_5.5.1_3.0_1737627505995.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+References
+
+https://huggingface.co/Somesh140/NER
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-ner_ft_thai_products_oi_en.md b/docs/_posts/ahmedlone127/2025-01-23-ner_ft_thai_products_oi_en.md
new file mode 100644
index 00000000000000..a617e4c23a5d1f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-ner_ft_thai_products_oi_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ner_ft_thai_products_oi CamemBertForTokenClassification from StrangeSX
+author: John Snow Labs
+name: ner_ft_thai_products_oi
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, camembert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_ft_thai_products_oi` is a English model originally trained by StrangeSX.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_ft_thai_products_oi_en_5.5.1_3.0_1737641717453.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_ft_thai_products_oi_en_5.5.1_3.0_1737641717453.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = CamemBertForTokenClassification.pretrained("ner_ft_thai_products_oi","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = CamemBertForTokenClassification.pretrained("ner_ft_thai_products_oi", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_ft_thai_products_oi|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|392.2 MB|
+
+## References
+
+https://huggingface.co/StrangeSX/NER-FT-Thai-Products-OI
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-ner_ft_thai_products_oi_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-ner_ft_thai_products_oi_pipeline_en.md
new file mode 100644
index 00000000000000..1f566b881c5f3e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-ner_ft_thai_products_oi_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ner_ft_thai_products_oi_pipeline pipeline CamemBertForTokenClassification from StrangeSX
+author: John Snow Labs
+name: ner_ft_thai_products_oi_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_ft_thai_products_oi_pipeline` is a English model originally trained by StrangeSX.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_ft_thai_products_oi_pipeline_en_5.5.1_3.0_1737641738286.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_ft_thai_products_oi_pipeline_en_5.5.1_3.0_1737641738286.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ner_ft_thai_products_oi_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ner_ft_thai_products_oi_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_ft_thai_products_oi_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|392.2 MB|
+
+## References
+
+https://huggingface.co/StrangeSX/NER-FT-Thai-Products-OI
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-ner_ft_thai_products_rev1_1_en.md b/docs/_posts/ahmedlone127/2025-01-23-ner_ft_thai_products_rev1_1_en.md
new file mode 100644
index 00000000000000..533457419e7934
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-ner_ft_thai_products_rev1_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ner_ft_thai_products_rev1_1 CamemBertForTokenClassification from StrangeSX
+author: John Snow Labs
+name: ner_ft_thai_products_rev1_1
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, camembert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_ft_thai_products_rev1_1` is a English model originally trained by StrangeSX.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_ft_thai_products_rev1_1_en_5.5.1_3.0_1737641374749.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_ft_thai_products_rev1_1_en_5.5.1_3.0_1737641374749.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = CamemBertForTokenClassification.pretrained("ner_ft_thai_products_rev1_1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = CamemBertForTokenClassification.pretrained("ner_ft_thai_products_rev1_1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_ft_thai_products_rev1_1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|392.2 MB|
+
+## References
+
+https://huggingface.co/StrangeSX/NER-FT-Thai-Products-ReV1.1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-ner_ft_thai_products_rev1_1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-ner_ft_thai_products_rev1_1_pipeline_en.md
new file mode 100644
index 00000000000000..c8f3e057dd8499
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-ner_ft_thai_products_rev1_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ner_ft_thai_products_rev1_1_pipeline pipeline CamemBertForTokenClassification from StrangeSX
+author: John Snow Labs
+name: ner_ft_thai_products_rev1_1_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_ft_thai_products_rev1_1_pipeline` is a English model originally trained by StrangeSX.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_ft_thai_products_rev1_1_pipeline_en_5.5.1_3.0_1737641395066.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_ft_thai_products_rev1_1_pipeline_en_5.5.1_3.0_1737641395066.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ner_ft_thai_products_rev1_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ner_ft_thai_products_rev1_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_ft_thai_products_rev1_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|392.2 MB|
+
+## References
+
+https://huggingface.co/StrangeSX/NER-FT-Thai-Products-ReV1.1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-ner_ft_thai_products_rev1_2_5_en.md b/docs/_posts/ahmedlone127/2025-01-23-ner_ft_thai_products_rev1_2_5_en.md
new file mode 100644
index 00000000000000..4a7aa4f6d2acb5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-ner_ft_thai_products_rev1_2_5_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ner_ft_thai_products_rev1_2_5 CamemBertForTokenClassification from StrangeSX
+author: John Snow Labs
+name: ner_ft_thai_products_rev1_2_5
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, camembert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_ft_thai_products_rev1_2_5` is a English model originally trained by StrangeSX.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_ft_thai_products_rev1_2_5_en_5.5.1_3.0_1737641459385.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_ft_thai_products_rev1_2_5_en_5.5.1_3.0_1737641459385.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = CamemBertForTokenClassification.pretrained("ner_ft_thai_products_rev1_2_5","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = CamemBertForTokenClassification.pretrained("ner_ft_thai_products_rev1_2_5", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_ft_thai_products_rev1_2_5|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|392.2 MB|
+
+## References
+
+https://huggingface.co/StrangeSX/NER-FT-Thai-Products-ReV1.2.5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-ner_ft_thai_products_rev1_2_5_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-ner_ft_thai_products_rev1_2_5_pipeline_en.md
new file mode 100644
index 00000000000000..dab7904c05c4b2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-ner_ft_thai_products_rev1_2_5_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ner_ft_thai_products_rev1_2_5_pipeline pipeline CamemBertForTokenClassification from StrangeSX
+author: John Snow Labs
+name: ner_ft_thai_products_rev1_2_5_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_ft_thai_products_rev1_2_5_pipeline` is a English model originally trained by StrangeSX.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_ft_thai_products_rev1_2_5_pipeline_en_5.5.1_3.0_1737641482106.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_ft_thai_products_rev1_2_5_pipeline_en_5.5.1_3.0_1737641482106.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ner_ft_thai_products_rev1_2_5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ner_ft_thai_products_rev1_2_5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_ft_thai_products_rev1_2_5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|392.2 MB|
+
+## References
+
+https://huggingface.co/StrangeSX/NER-FT-Thai-Products-ReV1.2.5
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-ner_ft_thai_products_rev1_2_6_en.md b/docs/_posts/ahmedlone127/2025-01-23-ner_ft_thai_products_rev1_2_6_en.md
new file mode 100644
index 00000000000000..5eb81e057eee03
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-ner_ft_thai_products_rev1_2_6_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ner_ft_thai_products_rev1_2_6 CamemBertForTokenClassification from StrangeSX
+author: John Snow Labs
+name: ner_ft_thai_products_rev1_2_6
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, camembert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_ft_thai_products_rev1_2_6` is a English model originally trained by StrangeSX.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_ft_thai_products_rev1_2_6_en_5.5.1_3.0_1737641308059.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_ft_thai_products_rev1_2_6_en_5.5.1_3.0_1737641308059.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = CamemBertForTokenClassification.pretrained("ner_ft_thai_products_rev1_2_6","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = CamemBertForTokenClassification.pretrained("ner_ft_thai_products_rev1_2_6", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_ft_thai_products_rev1_2_6|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|392.2 MB|
+
+## References
+
+https://huggingface.co/StrangeSX/NER-FT-Thai-Products-ReV1.2.6
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-ner_ft_thai_products_rev1_2_6_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-ner_ft_thai_products_rev1_2_6_pipeline_en.md
new file mode 100644
index 00000000000000..244675765e2d57
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-ner_ft_thai_products_rev1_2_6_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ner_ft_thai_products_rev1_2_6_pipeline pipeline CamemBertForTokenClassification from StrangeSX
+author: John Snow Labs
+name: ner_ft_thai_products_rev1_2_6_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_ft_thai_products_rev1_2_6_pipeline` is a English model originally trained by StrangeSX.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_ft_thai_products_rev1_2_6_pipeline_en_5.5.1_3.0_1737641332115.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_ft_thai_products_rev1_2_6_pipeline_en_5.5.1_3.0_1737641332115.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ner_ft_thai_products_rev1_2_6_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ner_ft_thai_products_rev1_2_6_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_ft_thai_products_rev1_2_6_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|392.2 MB|
+
+## References
+
+https://huggingface.co/StrangeSX/NER-FT-Thai-Products-ReV1.2.6
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-ner_ft_thai_products_rev1_2_7_5_en.md b/docs/_posts/ahmedlone127/2025-01-23-ner_ft_thai_products_rev1_2_7_5_en.md
new file mode 100644
index 00000000000000..0cad532b6a2dc3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-ner_ft_thai_products_rev1_2_7_5_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ner_ft_thai_products_rev1_2_7_5 CamemBertForTokenClassification from StrangeSX
+author: John Snow Labs
+name: ner_ft_thai_products_rev1_2_7_5
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, camembert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_ft_thai_products_rev1_2_7_5` is a English model originally trained by StrangeSX.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_ft_thai_products_rev1_2_7_5_en_5.5.1_3.0_1737641669584.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_ft_thai_products_rev1_2_7_5_en_5.5.1_3.0_1737641669584.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = CamemBertForTokenClassification.pretrained("ner_ft_thai_products_rev1_2_7_5","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = CamemBertForTokenClassification.pretrained("ner_ft_thai_products_rev1_2_7_5", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_ft_thai_products_rev1_2_7_5|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|392.2 MB|
+
+## References
+
+https://huggingface.co/StrangeSX/NER-FT-Thai-Products-ReV1.2.7.5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-ner_ft_thai_products_rev1_2_7_5_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-ner_ft_thai_products_rev1_2_7_5_pipeline_en.md
new file mode 100644
index 00000000000000..38d35ee995aef6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-ner_ft_thai_products_rev1_2_7_5_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ner_ft_thai_products_rev1_2_7_5_pipeline pipeline CamemBertForTokenClassification from StrangeSX
+author: John Snow Labs
+name: ner_ft_thai_products_rev1_2_7_5_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_ft_thai_products_rev1_2_7_5_pipeline` is a English model originally trained by StrangeSX.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_ft_thai_products_rev1_2_7_5_pipeline_en_5.5.1_3.0_1737641690081.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_ft_thai_products_rev1_2_7_5_pipeline_en_5.5.1_3.0_1737641690081.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ner_ft_thai_products_rev1_2_7_5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ner_ft_thai_products_rev1_2_7_5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_ft_thai_products_rev1_2_7_5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|392.2 MB|
+
+## References
+
+https://huggingface.co/StrangeSX/NER-FT-Thai-Products-ReV1.2.7.5
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-ner_ft_thai_products_rev1_2_7_en.md b/docs/_posts/ahmedlone127/2025-01-23-ner_ft_thai_products_rev1_2_7_en.md
new file mode 100644
index 00000000000000..3a88cbf2a4218f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-ner_ft_thai_products_rev1_2_7_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ner_ft_thai_products_rev1_2_7 CamemBertForTokenClassification from StrangeSX
+author: John Snow Labs
+name: ner_ft_thai_products_rev1_2_7
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, camembert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_ft_thai_products_rev1_2_7` is a English model originally trained by StrangeSX.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_ft_thai_products_rev1_2_7_en_5.5.1_3.0_1737641488558.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_ft_thai_products_rev1_2_7_en_5.5.1_3.0_1737641488558.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = CamemBertForTokenClassification.pretrained("ner_ft_thai_products_rev1_2_7","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = CamemBertForTokenClassification.pretrained("ner_ft_thai_products_rev1_2_7", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_ft_thai_products_rev1_2_7|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|392.2 MB|
+
+## References
+
+https://huggingface.co/StrangeSX/NER-FT-Thai-Products-ReV1.2.7
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-ner_ft_thai_products_rev1_2_7_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-ner_ft_thai_products_rev1_2_7_pipeline_en.md
new file mode 100644
index 00000000000000..e7d87956de2317
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-ner_ft_thai_products_rev1_2_7_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ner_ft_thai_products_rev1_2_7_pipeline pipeline CamemBertForTokenClassification from StrangeSX
+author: John Snow Labs
+name: ner_ft_thai_products_rev1_2_7_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_ft_thai_products_rev1_2_7_pipeline` is a English model originally trained by StrangeSX.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_ft_thai_products_rev1_2_7_pipeline_en_5.5.1_3.0_1737641509647.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_ft_thai_products_rev1_2_7_pipeline_en_5.5.1_3.0_1737641509647.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ner_ft_thai_products_rev1_2_7_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ner_ft_thai_products_rev1_2_7_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_ft_thai_products_rev1_2_7_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|392.2 MB|
+
+## References
+
+https://huggingface.co/StrangeSX/NER-FT-Thai-Products-ReV1.2.7
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-ner_ft_thai_products_rev1_2_en.md b/docs/_posts/ahmedlone127/2025-01-23-ner_ft_thai_products_rev1_2_en.md
new file mode 100644
index 00000000000000..83e985e562eea4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-ner_ft_thai_products_rev1_2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ner_ft_thai_products_rev1_2 CamemBertForTokenClassification from StrangeSX
+author: John Snow Labs
+name: ner_ft_thai_products_rev1_2
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, camembert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_ft_thai_products_rev1_2` is a English model originally trained by StrangeSX.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_ft_thai_products_rev1_2_en_5.5.1_3.0_1737641308626.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_ft_thai_products_rev1_2_en_5.5.1_3.0_1737641308626.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = CamemBertForTokenClassification.pretrained("ner_ft_thai_products_rev1_2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = CamemBertForTokenClassification.pretrained("ner_ft_thai_products_rev1_2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_ft_thai_products_rev1_2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|392.2 MB|
+
+## References
+
+https://huggingface.co/StrangeSX/NER-FT-Thai-Products-ReV1.2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-ner_ft_thai_products_rev1_2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-ner_ft_thai_products_rev1_2_pipeline_en.md
new file mode 100644
index 00000000000000..da68341fd29311
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-ner_ft_thai_products_rev1_2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ner_ft_thai_products_rev1_2_pipeline pipeline CamemBertForTokenClassification from StrangeSX
+author: John Snow Labs
+name: ner_ft_thai_products_rev1_2_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_ft_thai_products_rev1_2_pipeline` is a English model originally trained by StrangeSX.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_ft_thai_products_rev1_2_pipeline_en_5.5.1_3.0_1737641337535.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_ft_thai_products_rev1_2_pipeline_en_5.5.1_3.0_1737641337535.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ner_ft_thai_products_rev1_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ner_ft_thai_products_rev1_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_ft_thai_products_rev1_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|392.2 MB|
+
+## References
+
+https://huggingface.co/StrangeSX/NER-FT-Thai-Products-ReV1.2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-ner_ft_thai_products_rev1_en.md b/docs/_posts/ahmedlone127/2025-01-23-ner_ft_thai_products_rev1_en.md
new file mode 100644
index 00000000000000..fb3c3751b82544
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-ner_ft_thai_products_rev1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ner_ft_thai_products_rev1 CamemBertForTokenClassification from StrangeSX
+author: John Snow Labs
+name: ner_ft_thai_products_rev1
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, camembert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_ft_thai_products_rev1` is a English model originally trained by StrangeSX.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_ft_thai_products_rev1_en_5.5.1_3.0_1737641519128.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_ft_thai_products_rev1_en_5.5.1_3.0_1737641519128.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = CamemBertForTokenClassification.pretrained("ner_ft_thai_products_rev1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = CamemBertForTokenClassification.pretrained("ner_ft_thai_products_rev1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_ft_thai_products_rev1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|392.2 MB|
+
+## References
+
+https://huggingface.co/StrangeSX/NER-FT-Thai-Products-ReV1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-ner_ft_thai_products_rev1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-ner_ft_thai_products_rev1_pipeline_en.md
new file mode 100644
index 00000000000000..82214e9e80df06
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-ner_ft_thai_products_rev1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ner_ft_thai_products_rev1_pipeline pipeline CamemBertForTokenClassification from StrangeSX
+author: John Snow Labs
+name: ner_ft_thai_products_rev1_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_ft_thai_products_rev1_pipeline` is a English model originally trained by StrangeSX.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_ft_thai_products_rev1_pipeline_en_5.5.1_3.0_1737641541374.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_ft_thai_products_rev1_pipeline_en_5.5.1_3.0_1737641541374.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ner_ft_thai_products_rev1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ner_ft_thai_products_rev1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_ft_thai_products_rev1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|392.2 MB|
+
+## References
+
+https://huggingface.co/StrangeSX/NER-FT-Thai-Products-ReV1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-ner_model_en.md b/docs/_posts/ahmedlone127/2025-01-23-ner_model_en.md
new file mode 100644
index 00000000000000..9100dbde937b75
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-ner_model_en.md
@@ -0,0 +1,98 @@
+---
+layout: model
+title: English ner_model BertForTokenClassification from MichaelSargious
+author: John Snow Labs
+name: ner_model
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_model` is a English model originally trained by MichaelSargious.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_model_en_5.5.1_3.0_1737626901504.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_model_en_5.5.1_3.0_1737626901504.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("ner_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("ner_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+References
+
+References
+
+https://huggingface.co/MichaelSargious/ner_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-ner_model_only_en.md b/docs/_posts/ahmedlone127/2025-01-23-ner_model_only_en.md
new file mode 100644
index 00000000000000..d0c3ed2955eef1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-ner_model_only_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ner_model_only DistilBertForTokenClassification from ArshiaKarimian
+author: John Snow Labs
+name: ner_model_only
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_model_only` is a English model originally trained by ArshiaKarimian.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_model_only_en_5.5.1_3.0_1737628059918.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_model_only_en_5.5.1_3.0_1737628059918.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("ner_model_only","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("ner_model_only", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_model_only|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/ArshiaKarimian/ner_model_only
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-ner_model_only_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-ner_model_only_pipeline_en.md
new file mode 100644
index 00000000000000..869e91809606f1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-ner_model_only_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ner_model_only_pipeline pipeline DistilBertForTokenClassification from ArshiaKarimian
+author: John Snow Labs
+name: ner_model_only_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_model_only_pipeline` is a English model originally trained by ArshiaKarimian.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_model_only_pipeline_en_5.5.1_3.0_1737628073158.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_model_only_pipeline_en_5.5.1_3.0_1737628073158.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ner_model_only_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ner_model_only_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_model_only_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/ArshiaKarimian/ner_model_only
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-ner_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-ner_model_pipeline_en.md
new file mode 100644
index 00000000000000..440f6e4baab813
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-ner_model_pipeline_en.md
@@ -0,0 +1,74 @@
+---
+layout: model
+title: English ner_model_pipeline pipeline BertForTokenClassification from MichaelSargious
+author: John Snow Labs
+name: ner_model_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_model_pipeline` is a English model originally trained by MichaelSargious.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_model_pipeline_en_5.5.1_3.0_1737626921478.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_model_pipeline_en_5.5.1_3.0_1737626921478.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("ner_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("ner_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+References
+
+References
+
+https://huggingface.co/MichaelSargious/ner_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-ner_mots_interdits_sante_militaire_distilcamembert_en.md b/docs/_posts/ahmedlone127/2025-01-23-ner_mots_interdits_sante_militaire_distilcamembert_en.md
new file mode 100644
index 00000000000000..d06a1e65b6400b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-ner_mots_interdits_sante_militaire_distilcamembert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ner_mots_interdits_sante_militaire_distilcamembert CamemBertForTokenClassification from Steve77
+author: John Snow Labs
+name: ner_mots_interdits_sante_militaire_distilcamembert
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, camembert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_mots_interdits_sante_militaire_distilcamembert` is a English model originally trained by Steve77.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_mots_interdits_sante_militaire_distilcamembert_en_5.5.1_3.0_1737641612723.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_mots_interdits_sante_militaire_distilcamembert_en_5.5.1_3.0_1737641612723.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = CamemBertForTokenClassification.pretrained("ner_mots_interdits_sante_militaire_distilcamembert","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = CamemBertForTokenClassification.pretrained("ner_mots_interdits_sante_militaire_distilcamembert", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_mots_interdits_sante_militaire_distilcamembert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|253.5 MB|
+
+## References
+
+https://huggingface.co/Steve77/ner-mots_interdits-sante_militaire-distilcamembert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-ner_mots_interdits_sante_militaire_distilcamembert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-ner_mots_interdits_sante_militaire_distilcamembert_pipeline_en.md
new file mode 100644
index 00000000000000..9f7becf58ac7eb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-ner_mots_interdits_sante_militaire_distilcamembert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ner_mots_interdits_sante_militaire_distilcamembert_pipeline pipeline CamemBertForTokenClassification from Steve77
+author: John Snow Labs
+name: ner_mots_interdits_sante_militaire_distilcamembert_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_mots_interdits_sante_militaire_distilcamembert_pipeline` is a English model originally trained by Steve77.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_mots_interdits_sante_militaire_distilcamembert_pipeline_en_5.5.1_3.0_1737641626994.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_mots_interdits_sante_militaire_distilcamembert_pipeline_en_5.5.1_3.0_1737641626994.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ner_mots_interdits_sante_militaire_distilcamembert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ner_mots_interdits_sante_militaire_distilcamembert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_mots_interdits_sante_militaire_distilcamembert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|253.6 MB|
+
+## References
+
+https://huggingface.co/Steve77/ner-mots_interdits-sante_militaire-distilcamembert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-ner_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-ner_pipeline_en.md
new file mode 100644
index 00000000000000..b2c9cf1027ce73
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-ner_pipeline_en.md
@@ -0,0 +1,72 @@
+---
+layout: model
+title: English ner_pipeline pipeline XlmRoBertaForTokenClassification from Somesh140
+author: John Snow Labs
+name: ner_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_pipeline` is a English model originally trained by Somesh140.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_pipeline_en_5.5.1_3.0_1737627522323.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_pipeline_en_5.5.1_3.0_1737627522323.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+References
+
+https://huggingface.co/Somesh140/NER
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-nlp_tp_4_ner_cinese_en.md b/docs/_posts/ahmedlone127/2025-01-23-nlp_tp_4_ner_cinese_en.md
new file mode 100644
index 00000000000000..9515f5c2df45c3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-nlp_tp_4_ner_cinese_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English nlp_tp_4_ner_cinese DistilBertForTokenClassification from marcocarotta
+author: John Snow Labs
+name: nlp_tp_4_ner_cinese
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nlp_tp_4_ner_cinese` is a English model originally trained by marcocarotta.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nlp_tp_4_ner_cinese_en_5.5.1_3.0_1737627336426.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nlp_tp_4_ner_cinese_en_5.5.1_3.0_1737627336426.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("nlp_tp_4_ner_cinese","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("nlp_tp_4_ner_cinese", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nlp_tp_4_ner_cinese|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/marcocarotta/NLP-tp-4-ner-cinese
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-nlp_tp_4_ner_cinese_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-nlp_tp_4_ner_cinese_pipeline_en.md
new file mode 100644
index 00000000000000..50e1887e55737b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-nlp_tp_4_ner_cinese_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English nlp_tp_4_ner_cinese_pipeline pipeline DistilBertForTokenClassification from marcocarotta
+author: John Snow Labs
+name: nlp_tp_4_ner_cinese_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nlp_tp_4_ner_cinese_pipeline` is a English model originally trained by marcocarotta.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nlp_tp_4_ner_cinese_pipeline_en_5.5.1_3.0_1737627349827.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nlp_tp_4_ner_cinese_pipeline_en_5.5.1_3.0_1737627349827.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("nlp_tp_4_ner_cinese_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("nlp_tp_4_ner_cinese_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nlp_tp_4_ner_cinese_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/marcocarotta/NLP-tp-4-ner-cinese
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-nlp_tp_4_ner_danese_en.md b/docs/_posts/ahmedlone127/2025-01-23-nlp_tp_4_ner_danese_en.md
new file mode 100644
index 00000000000000..8e94ded861d367
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-nlp_tp_4_ner_danese_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English nlp_tp_4_ner_danese DistilBertForTokenClassification from marcocarotta
+author: John Snow Labs
+name: nlp_tp_4_ner_danese
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nlp_tp_4_ner_danese` is a English model originally trained by marcocarotta.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nlp_tp_4_ner_danese_en_5.5.1_3.0_1737627512941.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nlp_tp_4_ner_danese_en_5.5.1_3.0_1737627512941.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("nlp_tp_4_ner_danese","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("nlp_tp_4_ner_danese", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nlp_tp_4_ner_danese|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/marcocarotta/NLP-tp-4-ner-danese
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-nlp_tp_4_ner_danese_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-nlp_tp_4_ner_danese_pipeline_en.md
new file mode 100644
index 00000000000000..a7109d2b3d3845
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-nlp_tp_4_ner_danese_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English nlp_tp_4_ner_danese_pipeline pipeline DistilBertForTokenClassification from marcocarotta
+author: John Snow Labs
+name: nlp_tp_4_ner_danese_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nlp_tp_4_ner_danese_pipeline` is a English model originally trained by marcocarotta.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nlp_tp_4_ner_danese_pipeline_en_5.5.1_3.0_1737627527289.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nlp_tp_4_ner_danese_pipeline_en_5.5.1_3.0_1737627527289.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("nlp_tp_4_ner_danese_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("nlp_tp_4_ner_danese_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nlp_tp_4_ner_danese_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/marcocarotta/NLP-tp-4-ner-danese
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-nlp_tp_4_ner_portoghese_en.md b/docs/_posts/ahmedlone127/2025-01-23-nlp_tp_4_ner_portoghese_en.md
new file mode 100644
index 00000000000000..3cf1ae8a2b799b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-nlp_tp_4_ner_portoghese_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English nlp_tp_4_ner_portoghese DistilBertForTokenClassification from marcocarotta
+author: John Snow Labs
+name: nlp_tp_4_ner_portoghese
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nlp_tp_4_ner_portoghese` is a English model originally trained by marcocarotta.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nlp_tp_4_ner_portoghese_en_5.5.1_3.0_1737626896925.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nlp_tp_4_ner_portoghese_en_5.5.1_3.0_1737626896925.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("nlp_tp_4_ner_portoghese","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("nlp_tp_4_ner_portoghese", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nlp_tp_4_ner_portoghese|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/marcocarotta/NLP-tp-4-ner-portoghese
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-nlp_tp_4_ner_portoghese_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-nlp_tp_4_ner_portoghese_pipeline_en.md
new file mode 100644
index 00000000000000..c4885080086f8f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-nlp_tp_4_ner_portoghese_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English nlp_tp_4_ner_portoghese_pipeline pipeline DistilBertForTokenClassification from marcocarotta
+author: John Snow Labs
+name: nlp_tp_4_ner_portoghese_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nlp_tp_4_ner_portoghese_pipeline` is a English model originally trained by marcocarotta.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nlp_tp_4_ner_portoghese_pipeline_en_5.5.1_3.0_1737626910233.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nlp_tp_4_ner_portoghese_pipeline_en_5.5.1_3.0_1737626910233.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("nlp_tp_4_ner_portoghese_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("nlp_tp_4_ner_portoghese_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nlp_tp_4_ner_portoghese_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/marcocarotta/NLP-tp-4-ner-portoghese
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-nlp_tp_4_ner_serbo_en.md b/docs/_posts/ahmedlone127/2025-01-23-nlp_tp_4_ner_serbo_en.md
new file mode 100644
index 00000000000000..ce7f5cf70d804f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-nlp_tp_4_ner_serbo_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English nlp_tp_4_ner_serbo DistilBertForTokenClassification from marcocarotta
+author: John Snow Labs
+name: nlp_tp_4_ner_serbo
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nlp_tp_4_ner_serbo` is a English model originally trained by marcocarotta.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nlp_tp_4_ner_serbo_en_5.5.1_3.0_1737627492042.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nlp_tp_4_ner_serbo_en_5.5.1_3.0_1737627492042.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("nlp_tp_4_ner_serbo","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("nlp_tp_4_ner_serbo", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nlp_tp_4_ner_serbo|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/marcocarotta/NLP-tp-4-ner-serbo
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-nlp_tp_4_ner_serbo_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-nlp_tp_4_ner_serbo_pipeline_en.md
new file mode 100644
index 00000000000000..4c77c91894f5fb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-nlp_tp_4_ner_serbo_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English nlp_tp_4_ner_serbo_pipeline pipeline DistilBertForTokenClassification from marcocarotta
+author: John Snow Labs
+name: nlp_tp_4_ner_serbo_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nlp_tp_4_ner_serbo_pipeline` is a English model originally trained by marcocarotta.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nlp_tp_4_ner_serbo_pipeline_en_5.5.1_3.0_1737627505785.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nlp_tp_4_ner_serbo_pipeline_en_5.5.1_3.0_1737627505785.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("nlp_tp_4_ner_serbo_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("nlp_tp_4_ner_serbo_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nlp_tp_4_ner_serbo_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/marcocarotta/NLP-tp-4-ner-serbo
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-nlp_tp_4_ner_slovacco_en.md b/docs/_posts/ahmedlone127/2025-01-23-nlp_tp_4_ner_slovacco_en.md
new file mode 100644
index 00000000000000..eaedf2d40f57cd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-nlp_tp_4_ner_slovacco_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English nlp_tp_4_ner_slovacco DistilBertForTokenClassification from marcocarotta
+author: John Snow Labs
+name: nlp_tp_4_ner_slovacco
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nlp_tp_4_ner_slovacco` is a English model originally trained by marcocarotta.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nlp_tp_4_ner_slovacco_en_5.5.1_3.0_1737627643747.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nlp_tp_4_ner_slovacco_en_5.5.1_3.0_1737627643747.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("nlp_tp_4_ner_slovacco","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("nlp_tp_4_ner_slovacco", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nlp_tp_4_ner_slovacco|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/marcocarotta/NLP-tp-4-ner-slovacco
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-nlp_tp_4_ner_slovacco_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-nlp_tp_4_ner_slovacco_pipeline_en.md
new file mode 100644
index 00000000000000..b70215a8c40304
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-nlp_tp_4_ner_slovacco_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English nlp_tp_4_ner_slovacco_pipeline pipeline DistilBertForTokenClassification from marcocarotta
+author: John Snow Labs
+name: nlp_tp_4_ner_slovacco_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nlp_tp_4_ner_slovacco_pipeline` is a English model originally trained by marcocarotta.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nlp_tp_4_ner_slovacco_pipeline_en_5.5.1_3.0_1737627663857.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nlp_tp_4_ner_slovacco_pipeline_en_5.5.1_3.0_1737627663857.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("nlp_tp_4_ner_slovacco_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("nlp_tp_4_ner_slovacco_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nlp_tp_4_ner_slovacco_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/marcocarotta/NLP-tp-4-ner-slovacco
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-nlp_tp_4_ner_sloveno_en.md b/docs/_posts/ahmedlone127/2025-01-23-nlp_tp_4_ner_sloveno_en.md
new file mode 100644
index 00000000000000..c31249569ca6bc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-nlp_tp_4_ner_sloveno_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English nlp_tp_4_ner_sloveno DistilBertForTokenClassification from marcocarotta
+author: John Snow Labs
+name: nlp_tp_4_ner_sloveno
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nlp_tp_4_ner_sloveno` is a English model originally trained by marcocarotta.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nlp_tp_4_ner_sloveno_en_5.5.1_3.0_1737627910254.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nlp_tp_4_ner_sloveno_en_5.5.1_3.0_1737627910254.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("nlp_tp_4_ner_sloveno","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("nlp_tp_4_ner_sloveno", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nlp_tp_4_ner_sloveno|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/marcocarotta/NLP-tp-4-ner-sloveno
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-nlp_tp_4_ner_sloveno_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-nlp_tp_4_ner_sloveno_pipeline_en.md
new file mode 100644
index 00000000000000..566b8eeda8733b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-nlp_tp_4_ner_sloveno_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English nlp_tp_4_ner_sloveno_pipeline pipeline DistilBertForTokenClassification from marcocarotta
+author: John Snow Labs
+name: nlp_tp_4_ner_sloveno_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nlp_tp_4_ner_sloveno_pipeline` is a English model originally trained by marcocarotta.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nlp_tp_4_ner_sloveno_pipeline_en_5.5.1_3.0_1737627923751.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nlp_tp_4_ner_sloveno_pipeline_en_5.5.1_3.0_1737627923751.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("nlp_tp_4_ner_sloveno_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("nlp_tp_4_ner_sloveno_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nlp_tp_4_ner_sloveno_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/marcocarotta/NLP-tp-4-ner-sloveno
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-persian_farsi_qa_nlp_model_en.md b/docs/_posts/ahmedlone127/2025-01-23-persian_farsi_qa_nlp_model_en.md
new file mode 100644
index 00000000000000..3b1cee696c49b4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-persian_farsi_qa_nlp_model_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English persian_farsi_qa_nlp_model DistilBertForQuestionAnswering from OmidSakaki
+author: John Snow Labs
+name: persian_farsi_qa_nlp_model
+date: 2025-01-23
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`persian_farsi_qa_nlp_model` is a English model originally trained by OmidSakaki.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/persian_farsi_qa_nlp_model_en_5.5.1_3.0_1737660599267.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/persian_farsi_qa_nlp_model_en_5.5.1_3.0_1737660599267.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("persian_farsi_qa_nlp_model","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("persian_farsi_qa_nlp_model", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|persian_farsi_qa_nlp_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/OmidSakaki/fa_qa_nlp_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-persian_farsi_qa_nlp_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-persian_farsi_qa_nlp_model_pipeline_en.md
new file mode 100644
index 00000000000000..e6c62c3b62a0de
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-persian_farsi_qa_nlp_model_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English persian_farsi_qa_nlp_model_pipeline pipeline DistilBertForQuestionAnswering from OmidSakaki
+author: John Snow Labs
+name: persian_farsi_qa_nlp_model_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`persian_farsi_qa_nlp_model_pipeline` is a English model originally trained by OmidSakaki.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/persian_farsi_qa_nlp_model_pipeline_en_5.5.1_3.0_1737660613010.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/persian_farsi_qa_nlp_model_pipeline_en_5.5.1_3.0_1737660613010.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("persian_farsi_qa_nlp_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("persian_farsi_qa_nlp_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|persian_farsi_qa_nlp_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/OmidSakaki/fa_qa_nlp_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-personality_en.md b/docs/_posts/ahmedlone127/2025-01-23-personality_en.md
new file mode 100644
index 00000000000000..a50105cca59508
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-personality_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English personality BartForZeroShotClassification from Fralet
+author: John Snow Labs
+name: personality
+date: 2025-01-23
+tags: [en, open_source, onnx, zero_shot, bart]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BartForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`personality` is a English model originally trained by Fralet.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/personality_en_5.5.1_3.0_1737639625571.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/personality_en_5.5.1_3.0_1737639625571.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+zeroShotClassifier  = BartForZeroShotClassification.pretrained("personality","en") \
+     .setInputCols(["document","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, zeroShotClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val zeroShotClassifier  = BartForZeroShotClassification.pretrained("personality", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, zeroShotClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|personality|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|975.7 MB|
+
+## References
+
+https://huggingface.co/Fralet/personality
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-personality_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-personality_pipeline_en.md
new file mode 100644
index 00000000000000..4ec835f1a123c4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-personality_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English personality_pipeline pipeline BartForZeroShotClassification from Fralet
+author: John Snow Labs
+name: personality_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`personality_pipeline` is a English model originally trained by Fralet.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/personality_pipeline_en_5.5.1_3.0_1737639917484.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/personality_pipeline_en_5.5.1_3.0_1737639917484.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("personality_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("personality_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|personality_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|975.7 MB|
+
+## References
+
+https://huggingface.co/Fralet/personality
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BartForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-phishing_email_detection_distilbert_v2_4_1_en.md b/docs/_posts/ahmedlone127/2025-01-23-phishing_email_detection_distilbert_v2_4_1_en.md
new file mode 100644
index 00000000000000..abb13280cfb384
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-phishing_email_detection_distilbert_v2_4_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English phishing_email_detection_distilbert_v2_4_1 DistilBertForSequenceClassification from cybersectony
+author: John Snow Labs
+name: phishing_email_detection_distilbert_v2_4_1
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`phishing_email_detection_distilbert_v2_4_1` is a English model originally trained by cybersectony.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/phishing_email_detection_distilbert_v2_4_1_en_5.5.1_3.0_1737650402178.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/phishing_email_detection_distilbert_v2_4_1_en_5.5.1_3.0_1737650402178.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("phishing_email_detection_distilbert_v2_4_1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("phishing_email_detection_distilbert_v2_4_1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|phishing_email_detection_distilbert_v2_4_1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/cybersectony/phishing-email-detection-distilbert_v2.4.1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-phishing_email_detection_distilbert_v2_4_1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-phishing_email_detection_distilbert_v2_4_1_pipeline_en.md
new file mode 100644
index 00000000000000..28032645fa1c1e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-phishing_email_detection_distilbert_v2_4_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English phishing_email_detection_distilbert_v2_4_1_pipeline pipeline DistilBertForSequenceClassification from cybersectony
+author: John Snow Labs
+name: phishing_email_detection_distilbert_v2_4_1_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`phishing_email_detection_distilbert_v2_4_1_pipeline` is a English model originally trained by cybersectony.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/phishing_email_detection_distilbert_v2_4_1_pipeline_en_5.5.1_3.0_1737650417316.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/phishing_email_detection_distilbert_v2_4_1_pipeline_en_5.5.1_3.0_1737650417316.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("phishing_email_detection_distilbert_v2_4_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("phishing_email_detection_distilbert_v2_4_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|phishing_email_detection_distilbert_v2_4_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/cybersectony/phishing-email-detection-distilbert_v2.4.1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-pii_two_stage_deberta_seed42_en.md b/docs/_posts/ahmedlone127/2025-01-23-pii_two_stage_deberta_seed42_en.md
new file mode 100644
index 00000000000000..347f790edea362
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-pii_two_stage_deberta_seed42_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English pii_two_stage_deberta_seed42 DeBertaForTokenClassification from bogoconic1
+author: John Snow Labs
+name: pii_two_stage_deberta_seed42
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, deberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pii_two_stage_deberta_seed42` is a English model originally trained by bogoconic1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pii_two_stage_deberta_seed42_en_5.5.1_3.0_1737642765890.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pii_two_stage_deberta_seed42_en_5.5.1_3.0_1737642765890.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DeBertaForTokenClassification.pretrained("pii_two_stage_deberta_seed42","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DeBertaForTokenClassification.pretrained("pii_two_stage_deberta_seed42", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pii_two_stage_deberta_seed42|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/bogoconic1/pii-two-stage-deberta-seed42
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-pii_two_stage_deberta_seed42_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-pii_two_stage_deberta_seed42_pipeline_en.md
new file mode 100644
index 00000000000000..3ab4700a21845c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-pii_two_stage_deberta_seed42_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English pii_two_stage_deberta_seed42_pipeline pipeline DeBertaForTokenClassification from bogoconic1
+author: John Snow Labs
+name: pii_two_stage_deberta_seed42_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pii_two_stage_deberta_seed42_pipeline` is a English model originally trained by bogoconic1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pii_two_stage_deberta_seed42_pipeline_en_5.5.1_3.0_1737642872374.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pii_two_stage_deberta_seed42_pipeline_en_5.5.1_3.0_1737642872374.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("pii_two_stage_deberta_seed42_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("pii_two_stage_deberta_seed42_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pii_two_stage_deberta_seed42_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/bogoconic1/pii-two-stage-deberta-seed42
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-podcast_summarizer_wick2025_en.md b/docs/_posts/ahmedlone127/2025-01-23-podcast_summarizer_wick2025_en.md
new file mode 100644
index 00000000000000..10622cad79083e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-podcast_summarizer_wick2025_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English podcast_summarizer_wick2025 T5Transformer from Wick2025
+author: John Snow Labs
+name: podcast_summarizer_wick2025
+date: 2025-01-23
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`podcast_summarizer_wick2025` is a English model originally trained by Wick2025.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/podcast_summarizer_wick2025_en_5.5.1_3.0_1737634830441.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/podcast_summarizer_wick2025_en_5.5.1_3.0_1737634830441.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("podcast_summarizer_wick2025","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("podcast_summarizer_wick2025", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|podcast_summarizer_wick2025|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|272.6 MB|
+
+## References
+
+https://huggingface.co/Wick2025/podcast_summarizer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-podcast_summarizer_wick2025_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-podcast_summarizer_wick2025_pipeline_en.md
new file mode 100644
index 00000000000000..e7d687914520e1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-podcast_summarizer_wick2025_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English podcast_summarizer_wick2025_pipeline pipeline T5Transformer from Wick2025
+author: John Snow Labs
+name: podcast_summarizer_wick2025_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`podcast_summarizer_wick2025_pipeline` is a English model originally trained by Wick2025.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/podcast_summarizer_wick2025_pipeline_en_5.5.1_3.0_1737634853456.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/podcast_summarizer_wick2025_pipeline_en_5.5.1_3.0_1737634853456.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("podcast_summarizer_wick2025_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("podcast_summarizer_wick2025_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|podcast_summarizer_wick2025_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|272.6 MB|
+
+## References
+
+https://huggingface.co/Wick2025/podcast_summarizer
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-pretrain_squad_en.md b/docs/_posts/ahmedlone127/2025-01-23-pretrain_squad_en.md
new file mode 100644
index 00000000000000..c5aa82a23d0310
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-pretrain_squad_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English pretrain_squad DistilBertForQuestionAnswering from chuthienlong
+author: John Snow Labs
+name: pretrain_squad
+date: 2025-01-23
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pretrain_squad` is a English model originally trained by chuthienlong.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pretrain_squad_en_5.5.1_3.0_1737660251912.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pretrain_squad_en_5.5.1_3.0_1737660251912.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("pretrain_squad","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("pretrain_squad", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pretrain_squad|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/chuthienlong/pretrain_squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-pretrain_squad_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-pretrain_squad_pipeline_en.md
new file mode 100644
index 00000000000000..86d02d864aeed1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-pretrain_squad_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English pretrain_squad_pipeline pipeline DistilBertForQuestionAnswering from chuthienlong
+author: John Snow Labs
+name: pretrain_squad_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pretrain_squad_pipeline` is a English model originally trained by chuthienlong.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pretrain_squad_pipeline_en_5.5.1_3.0_1737660265724.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pretrain_squad_pipeline_en_5.5.1_3.0_1737660265724.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("pretrain_squad_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("pretrain_squad_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pretrain_squad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/chuthienlong/pretrain_squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-proof_reading_test_en.md b/docs/_posts/ahmedlone127/2025-01-23-proof_reading_test_en.md
new file mode 100644
index 00000000000000..bc9faa9bd47cc8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-proof_reading_test_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English proof_reading_test CamemBertForTokenClassification from Tippawan
+author: John Snow Labs
+name: proof_reading_test
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, camembert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`proof_reading_test` is a English model originally trained by Tippawan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/proof_reading_test_en_5.5.1_3.0_1737641308416.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/proof_reading_test_en_5.5.1_3.0_1737641308416.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = CamemBertForTokenClassification.pretrained("proof_reading_test","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = CamemBertForTokenClassification.pretrained("proof_reading_test", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|proof_reading_test|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|392.1 MB|
+
+## References
+
+https://huggingface.co/Tippawan/Proof-reading-test
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-proof_reading_test_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-proof_reading_test_pipeline_en.md
new file mode 100644
index 00000000000000..8ffea1d02daf9c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-proof_reading_test_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English proof_reading_test_pipeline pipeline CamemBertForTokenClassification from Tippawan
+author: John Snow Labs
+name: proof_reading_test_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`proof_reading_test_pipeline` is a English model originally trained by Tippawan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/proof_reading_test_pipeline_en_5.5.1_3.0_1737641337629.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/proof_reading_test_pipeline_en_5.5.1_3.0_1737641337629.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("proof_reading_test_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("proof_reading_test_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|proof_reading_test_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|392.2 MB|
+
+## References
+
+https://huggingface.co/Tippawan/Proof-reading-test
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-pruned_70_model_en.md b/docs/_posts/ahmedlone127/2025-01-23-pruned_70_model_en.md
new file mode 100644
index 00000000000000..4c6e99247d1567
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-pruned_70_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English pruned_70_model DistilBertForSequenceClassification from andygoh5
+author: John Snow Labs
+name: pruned_70_model
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pruned_70_model` is a English model originally trained by andygoh5.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pruned_70_model_en_5.5.1_3.0_1737650979152.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pruned_70_model_en_5.5.1_3.0_1737650979152.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("pruned_70_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("pruned_70_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pruned_70_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/andygoh5/pruned-70-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-pruned_70_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-pruned_70_model_pipeline_en.md
new file mode 100644
index 00000000000000..2c6cea315712c8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-pruned_70_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English pruned_70_model_pipeline pipeline DistilBertForSequenceClassification from andygoh5
+author: John Snow Labs
+name: pruned_70_model_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pruned_70_model_pipeline` is a English model originally trained by andygoh5.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pruned_70_model_pipeline_en_5.5.1_3.0_1737650993125.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pruned_70_model_pipeline_en_5.5.1_3.0_1737650993125.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("pruned_70_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("pruned_70_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pruned_70_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/andygoh5/pruned-70-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-ptcrawl_plus_legal_base_v3_5__checkpoint_1_20000_en.md b/docs/_posts/ahmedlone127/2025-01-23-ptcrawl_plus_legal_base_v3_5__checkpoint_1_20000_en.md
new file mode 100644
index 00000000000000..2dc5ccb58c930d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-ptcrawl_plus_legal_base_v3_5__checkpoint_1_20000_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ptcrawl_plus_legal_base_v3_5__checkpoint_1_20000 RoBertaEmbeddings from eduagarcia-temp
+author: John Snow Labs
+name: ptcrawl_plus_legal_base_v3_5__checkpoint_1_20000
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ptcrawl_plus_legal_base_v3_5__checkpoint_1_20000` is a English model originally trained by eduagarcia-temp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ptcrawl_plus_legal_base_v3_5__checkpoint_1_20000_en_5.5.1_3.0_1737644101395.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ptcrawl_plus_legal_base_v3_5__checkpoint_1_20000_en_5.5.1_3.0_1737644101395.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("ptcrawl_plus_legal_base_v3_5__checkpoint_1_20000","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("ptcrawl_plus_legal_base_v3_5__checkpoint_1_20000","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ptcrawl_plus_legal_base_v3_5__checkpoint_1_20000|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|296.8 MB|
+
+## References
+
+https://huggingface.co/eduagarcia-temp/ptcrawl_plus_legal_base_v3_5__checkpoint_1_20000
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-ptcrawl_plus_legal_base_v3_5__checkpoint_1_20000_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-ptcrawl_plus_legal_base_v3_5__checkpoint_1_20000_pipeline_en.md
new file mode 100644
index 00000000000000..77d37079e144ea
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-ptcrawl_plus_legal_base_v3_5__checkpoint_1_20000_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ptcrawl_plus_legal_base_v3_5__checkpoint_1_20000_pipeline pipeline RoBertaEmbeddings from eduagarcia-temp
+author: John Snow Labs
+name: ptcrawl_plus_legal_base_v3_5__checkpoint_1_20000_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ptcrawl_plus_legal_base_v3_5__checkpoint_1_20000_pipeline` is a English model originally trained by eduagarcia-temp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ptcrawl_plus_legal_base_v3_5__checkpoint_1_20000_pipeline_en_5.5.1_3.0_1737644191403.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ptcrawl_plus_legal_base_v3_5__checkpoint_1_20000_pipeline_en_5.5.1_3.0_1737644191403.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ptcrawl_plus_legal_base_v3_5__checkpoint_1_20000_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ptcrawl_plus_legal_base_v3_5__checkpoint_1_20000_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ptcrawl_plus_legal_base_v3_5__checkpoint_1_20000_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|296.8 MB|
+
+## References
+
+https://huggingface.co/eduagarcia-temp/ptcrawl_plus_legal_base_v3_5__checkpoint_1_20000
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-randomly_pruned_50_model_en.md b/docs/_posts/ahmedlone127/2025-01-23-randomly_pruned_50_model_en.md
new file mode 100644
index 00000000000000..79b7d6182c42de
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-randomly_pruned_50_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English randomly_pruned_50_model DistilBertForSequenceClassification from andygoh5
+author: John Snow Labs
+name: randomly_pruned_50_model
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`randomly_pruned_50_model` is a English model originally trained by andygoh5.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/randomly_pruned_50_model_en_5.5.1_3.0_1737650002019.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/randomly_pruned_50_model_en_5.5.1_3.0_1737650002019.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("randomly_pruned_50_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("randomly_pruned_50_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|randomly_pruned_50_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/andygoh5/randomly-pruned-50-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-randomly_pruned_50_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-randomly_pruned_50_model_pipeline_en.md
new file mode 100644
index 00000000000000..c0e272a18b73e6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-randomly_pruned_50_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English randomly_pruned_50_model_pipeline pipeline DistilBertForSequenceClassification from andygoh5
+author: John Snow Labs
+name: randomly_pruned_50_model_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`randomly_pruned_50_model_pipeline` is a English model originally trained by andygoh5.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/randomly_pruned_50_model_pipeline_en_5.5.1_3.0_1737650023546.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/randomly_pruned_50_model_pipeline_en_5.5.1_3.0_1737650023546.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("randomly_pruned_50_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("randomly_pruned_50_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|randomly_pruned_50_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/andygoh5/randomly-pruned-50-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-recipe_generator_en.md b/docs/_posts/ahmedlone127/2025-01-23-recipe_generator_en.md
new file mode 100644
index 00000000000000..a69f2b41b72af9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-recipe_generator_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English recipe_generator T5Transformer from Izza-shahzad-13
+author: John Snow Labs
+name: recipe_generator
+date: 2025-01-23
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`recipe_generator` is a English model originally trained by Izza-shahzad-13.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/recipe_generator_en_5.5.1_3.0_1737634481353.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/recipe_generator_en_5.5.1_3.0_1737634481353.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("recipe_generator","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("recipe_generator", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|recipe_generator|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|286.8 MB|
+
+## References
+
+https://huggingface.co/Izza-shahzad-13/recipe-generator
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-recipe_generator_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-recipe_generator_pipeline_en.md
new file mode 100644
index 00000000000000..85b25cc1994687
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-recipe_generator_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English recipe_generator_pipeline pipeline T5Transformer from Izza-shahzad-13
+author: John Snow Labs
+name: recipe_generator_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`recipe_generator_pipeline` is a English model originally trained by Izza-shahzad-13.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/recipe_generator_pipeline_en_5.5.1_3.0_1737634496877.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/recipe_generator_pipeline_en_5.5.1_3.0_1737634496877.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("recipe_generator_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("recipe_generator_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|recipe_generator_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|286.8 MB|
+
+## References
+
+https://huggingface.co/Izza-shahzad-13/recipe-generator
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-regression_xlm_roberta_divemt_ara_en.md b/docs/_posts/ahmedlone127/2025-01-23-regression_xlm_roberta_divemt_ara_en.md
new file mode 100644
index 00000000000000..f628a313df8e86
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-regression_xlm_roberta_divemt_ara_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English regression_xlm_roberta_divemt_ara XlmRoBertaForSequenceClassification from iknlpt3
+author: John Snow Labs
+name: regression_xlm_roberta_divemt_ara
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`regression_xlm_roberta_divemt_ara` is a English model originally trained by iknlpt3.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/regression_xlm_roberta_divemt_ara_en_5.5.1_3.0_1737651753455.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/regression_xlm_roberta_divemt_ara_en_5.5.1_3.0_1737651753455.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("regression_xlm_roberta_divemt_ara","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("regression_xlm_roberta_divemt_ara", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|regression_xlm_roberta_divemt_ara|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|776.9 MB|
+
+## References
+
+https://huggingface.co/iknlpt3/regression_xlm_roberta_divemt_ara
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-regression_xlm_roberta_divemt_ara_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-regression_xlm_roberta_divemt_ara_pipeline_en.md
new file mode 100644
index 00000000000000..e34c287653746b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-regression_xlm_roberta_divemt_ara_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English regression_xlm_roberta_divemt_ara_pipeline pipeline XlmRoBertaForSequenceClassification from iknlpt3
+author: John Snow Labs
+name: regression_xlm_roberta_divemt_ara_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`regression_xlm_roberta_divemt_ara_pipeline` is a English model originally trained by iknlpt3.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/regression_xlm_roberta_divemt_ara_pipeline_en_5.5.1_3.0_1737651901620.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/regression_xlm_roberta_divemt_ara_pipeline_en_5.5.1_3.0_1737651901620.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("regression_xlm_roberta_divemt_ara_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("regression_xlm_roberta_divemt_ara_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|regression_xlm_roberta_divemt_ara_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|776.9 MB|
+
+## References
+
+https://huggingface.co/iknlpt3/regression_xlm_roberta_divemt_ara
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-results_en.md b/docs/_posts/ahmedlone127/2025-01-23-results_en.md
new file mode 100644
index 00000000000000..89b706b729587e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-results_en.md
@@ -0,0 +1,98 @@
+---
+layout: model
+title: English results DistilBertForQuestionAnswering from Souvik123
+author: John Snow Labs
+name: results
+date: 2025-01-23
+tags: [distilbert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results` is a English model originally trained by Souvik123.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_en_5.5.1_3.0_1737642196106.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_en_5.5.1_3.0_1737642196106.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("results","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering  
+    .pretrained("results", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.2 MB|
+
+## References
+
+References
+
+References
+
+References
+
+References
+
+https://huggingface.co/Souvik123/results
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-results_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-results_pipeline_en.md
new file mode 100644
index 00000000000000..0cdb2b5917352e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-results_pipeline_en.md
@@ -0,0 +1,74 @@
+---
+layout: model
+title: English results_pipeline pipeline RoBertaForTokenClassification from danielyoo
+author: John Snow Labs
+name: results_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_pipeline` is a English model originally trained by danielyoo.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_pipeline_en_5.5.1_3.0_1737642221299.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_pipeline_en_5.5.1_3.0_1737642221299.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("results_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("results_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.2 MB|
+
+## References
+
+References
+
+References
+
+https://huggingface.co/danielyoo/results
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- MPNetForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-results_t5base_en.md b/docs/_posts/ahmedlone127/2025-01-23-results_t5base_en.md
new file mode 100644
index 00000000000000..721c1e40c48259
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-results_t5base_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English results_t5base T5Transformer from AbdullahKnn
+author: John Snow Labs
+name: results_t5base
+date: 2025-01-23
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_t5base` is a English model originally trained by AbdullahKnn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_t5base_en_5.5.1_3.0_1737634112082.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_t5base_en_5.5.1_3.0_1737634112082.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("results_t5base","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("results_t5base", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_t5base|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|922.2 MB|
+
+## References
+
+https://huggingface.co/AbdullahKnn/results_t5base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-results_t5base_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-results_t5base_pipeline_en.md
new file mode 100644
index 00000000000000..805e93bb774367
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-results_t5base_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English results_t5base_pipeline pipeline T5Transformer from AbdullahKnn
+author: John Snow Labs
+name: results_t5base_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_t5base_pipeline` is a English model originally trained by AbdullahKnn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_t5base_pipeline_en_5.5.1_3.0_1737634159616.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_t5base_pipeline_en_5.5.1_3.0_1737634159616.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("results_t5base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("results_t5base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_t5base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|922.2 MB|
+
+## References
+
+https://huggingface.co/AbdullahKnn/results_t5base
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-rinna_hubert_eval_ja.md b/docs/_posts/ahmedlone127/2025-01-23-rinna_hubert_eval_ja.md
new file mode 100644
index 00000000000000..76341ae1a8b261
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-rinna_hubert_eval_ja.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Japanese rinna_hubert_eval HubertForCTC from utakumi
+author: John Snow Labs
+name: rinna_hubert_eval
+date: 2025-01-23
+tags: [ja, open_source, onnx, asr, hubert]
+task: Automatic Speech Recognition
+language: ja
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: HubertForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rinna_hubert_eval` is a Japanese model originally trained by utakumi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rinna_hubert_eval_ja_5.5.1_3.0_1737626074433.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rinna_hubert_eval_ja_5.5.1_3.0_1737626074433.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = HubertForCTC.pretrained("rinna_hubert_eval","ja") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = HubertForCTC.pretrained("rinna_hubert_eval", "ja")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rinna_hubert_eval|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|ja|
+|Size:|468.3 MB|
+
+## References
+
+https://huggingface.co/utakumi/rinna-Hubert-eval
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-rinna_hubert_eval_pipeline_ja.md b/docs/_posts/ahmedlone127/2025-01-23-rinna_hubert_eval_pipeline_ja.md
new file mode 100644
index 00000000000000..e690e12fd2986c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-rinna_hubert_eval_pipeline_ja.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Japanese rinna_hubert_eval_pipeline pipeline HubertForCTC from utakumi
+author: John Snow Labs
+name: rinna_hubert_eval_pipeline
+date: 2025-01-23
+tags: [ja, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: ja
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rinna_hubert_eval_pipeline` is a Japanese model originally trained by utakumi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rinna_hubert_eval_pipeline_ja_5.5.1_3.0_1737626198962.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rinna_hubert_eval_pipeline_ja_5.5.1_3.0_1737626198962.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("rinna_hubert_eval_pipeline", lang = "ja")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("rinna_hubert_eval_pipeline", lang = "ja")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rinna_hubert_eval_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ja|
+|Size:|468.3 MB|
+
+## References
+
+https://huggingface.co/utakumi/rinna-Hubert-eval
+
+## Included Models
+
+- AudioAssembler
+- HubertForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-roberta_base_ner_test_2_mn.md b/docs/_posts/ahmedlone127/2025-01-23-roberta_base_ner_test_2_mn.md
new file mode 100644
index 00000000000000..62ab37e9f0f52e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-roberta_base_ner_test_2_mn.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Mongolian roberta_base_ner_test_2 RoBertaForTokenClassification from Dondog
+author: John Snow Labs
+name: roberta_base_ner_test_2
+date: 2025-01-23
+tags: [mn, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: mn
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_ner_test_2` is a Mongolian model originally trained by Dondog.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_ner_test_2_mn_5.5.1_3.0_1737667141830.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_ner_test_2_mn_5.5.1_3.0_1737667141830.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("roberta_base_ner_test_2","mn") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_base_ner_test_2", "mn")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_ner_test_2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|mn|
+|Size:|465.7 MB|
+
+## References
+
+https://huggingface.co/Dondog/roberta-base-ner-test-2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-roberta_base_ner_test_2_pipeline_mn.md b/docs/_posts/ahmedlone127/2025-01-23-roberta_base_ner_test_2_pipeline_mn.md
new file mode 100644
index 00000000000000..d17fa63f8156ee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-roberta_base_ner_test_2_pipeline_mn.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Mongolian roberta_base_ner_test_2_pipeline pipeline RoBertaForTokenClassification from Dondog
+author: John Snow Labs
+name: roberta_base_ner_test_2_pipeline
+date: 2025-01-23
+tags: [mn, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: mn
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_ner_test_2_pipeline` is a Mongolian model originally trained by Dondog.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_ner_test_2_pipeline_mn_5.5.1_3.0_1737667166079.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_ner_test_2_pipeline_mn_5.5.1_3.0_1737667166079.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_base_ner_test_2_pipeline", lang = "mn")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_ner_test_2_pipeline", lang = "mn")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_ner_test_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|mn|
+|Size:|465.7 MB|
+
+## References
+
+https://huggingface.co/Dondog/roberta-base-ner-test-2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-roberta_finetuned_ner_en.md b/docs/_posts/ahmedlone127/2025-01-23-roberta_finetuned_ner_en.md
new file mode 100644
index 00000000000000..916c986a2f1668
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-roberta_finetuned_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_finetuned_ner RoBertaForTokenClassification from george6
+author: John Snow Labs
+name: roberta_finetuned_ner
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_finetuned_ner` is a English model originally trained by george6.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_finetuned_ner_en_5.5.1_3.0_1737666890973.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_finetuned_ner_en_5.5.1_3.0_1737666890973.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("roberta_finetuned_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_finetuned_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_finetuned_ner|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|425.7 MB|
+
+## References
+
+https://huggingface.co/george6/roberta-finetuned-NER
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-roberta_finetuned_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-roberta_finetuned_ner_pipeline_en.md
new file mode 100644
index 00000000000000..84edc3d5024537
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-roberta_finetuned_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_finetuned_ner_pipeline pipeline RoBertaForTokenClassification from george6
+author: John Snow Labs
+name: roberta_finetuned_ner_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_finetuned_ner_pipeline` is a English model originally trained by george6.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_finetuned_ner_pipeline_en_5.5.1_3.0_1737666930844.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_finetuned_ner_pipeline_en_5.5.1_3.0_1737666930844.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_finetuned_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_finetuned_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_finetuned_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|425.8 MB|
+
+## References
+
+https://huggingface.co/george6/roberta-finetuned-NER
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-roberta_large_amazon_fine_tuned_en.md b/docs/_posts/ahmedlone127/2025-01-23-roberta_large_amazon_fine_tuned_en.md
new file mode 100644
index 00000000000000..677c142381a6ab
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-roberta_large_amazon_fine_tuned_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_large_amazon_fine_tuned RoBertaEmbeddings from afcarzero1
+author: John Snow Labs
+name: roberta_large_amazon_fine_tuned
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_amazon_fine_tuned` is a English model originally trained by afcarzero1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_amazon_fine_tuned_en_5.5.1_3.0_1737644381061.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_amazon_fine_tuned_en_5.5.1_3.0_1737644381061.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("roberta_large_amazon_fine_tuned","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("roberta_large_amazon_fine_tuned","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_large_amazon_fine_tuned|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/afcarzero1/roberta-large-amazon-fine-tuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-roberta_large_amazon_fine_tuned_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-roberta_large_amazon_fine_tuned_pipeline_en.md
new file mode 100644
index 00000000000000..e7fa7f24b91197
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-roberta_large_amazon_fine_tuned_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_large_amazon_fine_tuned_pipeline pipeline RoBertaEmbeddings from afcarzero1
+author: John Snow Labs
+name: roberta_large_amazon_fine_tuned_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_amazon_fine_tuned_pipeline` is a English model originally trained by afcarzero1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_amazon_fine_tuned_pipeline_en_5.5.1_3.0_1737644456315.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_amazon_fine_tuned_pipeline_en_5.5.1_3.0_1737644456315.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_large_amazon_fine_tuned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_large_amazon_fine_tuned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_large_amazon_fine_tuned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/afcarzero1/roberta-large-amazon-fine-tuned
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-roberta_large_finetuned_ades_sonatafyai_en.md b/docs/_posts/ahmedlone127/2025-01-23-roberta_large_finetuned_ades_sonatafyai_en.md
new file mode 100644
index 00000000000000..5ef9449c5908ac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-roberta_large_finetuned_ades_sonatafyai_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_large_finetuned_ades_sonatafyai RoBertaForTokenClassification from Sonatafyai
+author: John Snow Labs
+name: roberta_large_finetuned_ades_sonatafyai
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_finetuned_ades_sonatafyai` is a English model originally trained by Sonatafyai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_finetuned_ades_sonatafyai_en_5.5.1_3.0_1737665583095.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_finetuned_ades_sonatafyai_en_5.5.1_3.0_1737665583095.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("roberta_large_finetuned_ades_sonatafyai","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_large_finetuned_ades_sonatafyai", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_large_finetuned_ades_sonatafyai|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/Sonatafyai/roberta-large-finetuned_ADEs_SonatafyAI
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-roberta_large_finetuned_ades_sonatafyai_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-roberta_large_finetuned_ades_sonatafyai_pipeline_en.md
new file mode 100644
index 00000000000000..d1ea268d99f248
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-roberta_large_finetuned_ades_sonatafyai_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_large_finetuned_ades_sonatafyai_pipeline pipeline RoBertaForTokenClassification from Sonatafyai
+author: John Snow Labs
+name: roberta_large_finetuned_ades_sonatafyai_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_finetuned_ades_sonatafyai_pipeline` is a English model originally trained by Sonatafyai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_finetuned_ades_sonatafyai_pipeline_en_5.5.1_3.0_1737665675528.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_finetuned_ades_sonatafyai_pipeline_en_5.5.1_3.0_1737665675528.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_large_finetuned_ades_sonatafyai_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_large_finetuned_ades_sonatafyai_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_large_finetuned_ades_sonatafyai_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/Sonatafyai/roberta-large-finetuned_ADEs_SonatafyAI
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-roberta_large_lm_en.md b/docs/_posts/ahmedlone127/2025-01-23-roberta_large_lm_en.md
new file mode 100644
index 00000000000000..1fb5c28b62ddec
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-roberta_large_lm_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_large_lm RoBertaEmbeddings from ACCORD-NLP
+author: John Snow Labs
+name: roberta_large_lm
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_lm` is a English model originally trained by ACCORD-NLP.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_lm_en_5.5.1_3.0_1737644749503.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_lm_en_5.5.1_3.0_1737644749503.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("roberta_large_lm","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("roberta_large_lm","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_large_lm|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/ACCORD-NLP/roberta-large-lm
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-roberta_large_lm_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-roberta_large_lm_pipeline_en.md
new file mode 100644
index 00000000000000..da26dfaf160062
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-roberta_large_lm_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_large_lm_pipeline pipeline RoBertaEmbeddings from ACCORD-NLP
+author: John Snow Labs
+name: roberta_large_lm_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_lm_pipeline` is a English model originally trained by ACCORD-NLP.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_lm_pipeline_en_5.5.1_3.0_1737644816425.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_lm_pipeline_en_5.5.1_3.0_1737644816425.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_large_lm_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_large_lm_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_large_lm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/ACCORD-NLP/roberta-large-lm
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-scenario_tcr_data_cl_cardiff_cl_only466_en.md b/docs/_posts/ahmedlone127/2025-01-23-scenario_tcr_data_cl_cardiff_cl_only466_en.md
new file mode 100644
index 00000000000000..fb09d149301e01
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-scenario_tcr_data_cl_cardiff_cl_only466_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English scenario_tcr_data_cl_cardiff_cl_only466 XlmRoBertaForSequenceClassification from haryoaw
+author: John Snow Labs
+name: scenario_tcr_data_cl_cardiff_cl_only466
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scenario_tcr_data_cl_cardiff_cl_only466` is a English model originally trained by haryoaw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/scenario_tcr_data_cl_cardiff_cl_only466_en_5.5.1_3.0_1737652898058.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scenario_tcr_data_cl_cardiff_cl_only466_en_5.5.1_3.0_1737652898058.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("scenario_tcr_data_cl_cardiff_cl_only466","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("scenario_tcr_data_cl_cardiff_cl_only466", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|scenario_tcr_data_cl_cardiff_cl_only466|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|849.6 MB|
+
+## References
+
+https://huggingface.co/haryoaw/scenario-TCR_data-cl-cardiff_cl_only466
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-scenario_tcr_data_cl_cardiff_cl_only466_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-scenario_tcr_data_cl_cardiff_cl_only466_pipeline_en.md
new file mode 100644
index 00000000000000..e8552aa3454df9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-scenario_tcr_data_cl_cardiff_cl_only466_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English scenario_tcr_data_cl_cardiff_cl_only466_pipeline pipeline XlmRoBertaForSequenceClassification from haryoaw
+author: John Snow Labs
+name: scenario_tcr_data_cl_cardiff_cl_only466_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scenario_tcr_data_cl_cardiff_cl_only466_pipeline` is a English model originally trained by haryoaw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/scenario_tcr_data_cl_cardiff_cl_only466_pipeline_en_5.5.1_3.0_1737652982739.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scenario_tcr_data_cl_cardiff_cl_only466_pipeline_en_5.5.1_3.0_1737652982739.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("scenario_tcr_data_cl_cardiff_cl_only466_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("scenario_tcr_data_cl_cardiff_cl_only466_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|scenario_tcr_data_cl_cardiff_cl_only466_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|849.6 MB|
+
+## References
+
+https://huggingface.co/haryoaw/scenario-TCR_data-cl-cardiff_cl_only466
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-securebert_dnrti_en.md b/docs/_posts/ahmedlone127/2025-01-23-securebert_dnrti_en.md
new file mode 100644
index 00000000000000..ea62cf431bfa01
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-securebert_dnrti_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English securebert_dnrti RoBertaForTokenClassification from anonymouspd
+author: John Snow Labs
+name: securebert_dnrti
+date: 2025-01-23
+tags: [roberta, en, open_source, token_classification, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`securebert_dnrti` is a English model originally trained by anonymouspd.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/securebert_dnrti_en_5.5.1_3.0_1737665672851.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/securebert_dnrti_en_5.5.1_3.0_1737665672851.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+    
+tokenizer = Tokenizer() \
+        .setInputCols(["document"]) \
+        .setOutputCol("token")
+        
+    
+tokenClassifier = RoBertaForTokenClassification.pretrained("securebert_dnrti","en") \
+            .setInputCols(["document","token"]) \
+            .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val tokenizer = Tokenizer() \
+        .setInputCols(Array("document")) \
+        .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification  
+    .pretrained("securebert_dnrti", "en")
+    .setInputCols(Array("document","token")) 
+    .setOutputCol("ner") 
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|securebert_dnrti|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|466.2 MB|
+
+## References
+
+References
+
+https://huggingface.co/anonymouspd/SecureBERT-DNRTI
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-securebert_dnrti_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-securebert_dnrti_pipeline_en.md
new file mode 100644
index 00000000000000..0fad5993c96ac2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-securebert_dnrti_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English securebert_dnrti_pipeline pipeline RoBertaForTokenClassification from Cyber-ThreaD
+author: John Snow Labs
+name: securebert_dnrti_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`securebert_dnrti_pipeline` is a English model originally trained by Cyber-ThreaD.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/securebert_dnrti_pipeline_en_5.5.1_3.0_1737665699952.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/securebert_dnrti_pipeline_en_5.5.1_3.0_1737665699952.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("securebert_dnrti_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("securebert_dnrti_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|securebert_dnrti_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.2 MB|
+
+## References
+
+https://huggingface.co/Cyber-ThreaD/SecureBERT-DNRTI
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-sent_afriberta_v2_base_en.md b/docs/_posts/ahmedlone127/2025-01-23-sent_afriberta_v2_base_en.md
new file mode 100644
index 00000000000000..2c025587a086f1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-sent_afriberta_v2_base_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_afriberta_v2_base XlmRoBertaSentenceEmbeddings from castorini
+author: John Snow Labs
+name: sent_afriberta_v2_base
+date: 2025-01-23
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_afriberta_v2_base` is a English model originally trained by castorini.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_afriberta_v2_base_en_5.5.1_3.0_1737661760142.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_afriberta_v2_base_en_5.5.1_3.0_1737661760142.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_afriberta_v2_base","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_afriberta_v2_base","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_afriberta_v2_base|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|645.7 MB|
+
+## References
+
+https://huggingface.co/castorini/afriberta_v2_base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-sent_afriberta_v2_base_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-sent_afriberta_v2_base_pipeline_en.md
new file mode 100644
index 00000000000000..0194964ef579c5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-sent_afriberta_v2_base_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_afriberta_v2_base_pipeline pipeline XlmRoBertaSentenceEmbeddings from castorini
+author: John Snow Labs
+name: sent_afriberta_v2_base_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_afriberta_v2_base_pipeline` is a English model originally trained by castorini.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_afriberta_v2_base_pipeline_en_5.5.1_3.0_1737661797296.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_afriberta_v2_base_pipeline_en_5.5.1_3.0_1737661797296.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_afriberta_v2_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_afriberta_v2_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_afriberta_v2_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|646.2 MB|
+
+## References
+
+https://huggingface.co/castorini/afriberta_v2_base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-sent_afro_xlmr_base_emakhuwa_en.md b/docs/_posts/ahmedlone127/2025-01-23-sent_afro_xlmr_base_emakhuwa_en.md
new file mode 100644
index 00000000000000..4ac7187c4415cd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-sent_afro_xlmr_base_emakhuwa_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_afro_xlmr_base_emakhuwa XlmRoBertaSentenceEmbeddings from felerminoali
+author: John Snow Labs
+name: sent_afro_xlmr_base_emakhuwa
+date: 2025-01-23
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_afro_xlmr_base_emakhuwa` is a English model originally trained by felerminoali.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_afro_xlmr_base_emakhuwa_en_5.5.1_3.0_1737662077106.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_afro_xlmr_base_emakhuwa_en_5.5.1_3.0_1737662077106.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_afro_xlmr_base_emakhuwa","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_afro_xlmr_base_emakhuwa","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_afro_xlmr_base_emakhuwa|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/felerminoali/afro_xlmr_base_emakhuwa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-sent_afro_xlmr_base_emakhuwa_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-sent_afro_xlmr_base_emakhuwa_pipeline_en.md
new file mode 100644
index 00000000000000..f83b99037f9020
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-sent_afro_xlmr_base_emakhuwa_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_afro_xlmr_base_emakhuwa_pipeline pipeline XlmRoBertaSentenceEmbeddings from felerminoali
+author: John Snow Labs
+name: sent_afro_xlmr_base_emakhuwa_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_afro_xlmr_base_emakhuwa_pipeline` is a English model originally trained by felerminoali.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_afro_xlmr_base_emakhuwa_pipeline_en_5.5.1_3.0_1737662137565.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_afro_xlmr_base_emakhuwa_pipeline_en_5.5.1_3.0_1737662137565.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_afro_xlmr_base_emakhuwa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_afro_xlmr_base_emakhuwa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_afro_xlmr_base_emakhuwa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/felerminoali/afro_xlmr_base_emakhuwa
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_03_en.md b/docs/_posts/ahmedlone127/2025-01-23-sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_03_en.md
new file mode 100644
index 00000000000000..f9ad918337504d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_03_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_03 BertSentenceEmbeddings from brugmark
+author: John Snow Labs
+name: sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_03
+date: 2025-01-23
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_03` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_03_en_5.5.1_3.0_1737645776902.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_03_en_5.5.1_3.0_1737645776902.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_03","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_03","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_03|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|79.6 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-finetuned-2024-06-03
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_03_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_03_pipeline_en.md
new file mode 100644
index 00000000000000..745f28da952ac5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_03_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_03_pipeline pipeline BertSentenceEmbeddings from brugmark
+author: John Snow Labs
+name: sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_03_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_03_pipeline` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_03_pipeline_en_5.5.1_3.0_1737645782392.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_03_pipeline_en_5.5.1_3.0_1737645782392.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_03_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_03_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_03_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|80.1 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-finetuned-2024-06-03
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_05_en.md b/docs/_posts/ahmedlone127/2025-01-23-sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_05_en.md
new file mode 100644
index 00000000000000..bbf82a05d2008c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_05_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_05 BertSentenceEmbeddings from brugmark
+author: John Snow Labs
+name: sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_05
+date: 2025-01-23
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_05` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_05_en_5.5.1_3.0_1737645538948.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_05_en_5.5.1_3.0_1737645538948.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_05","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_05","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_05|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|80.2 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-finetuned-2024-06-05
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_05_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_05_pipeline_en.md
new file mode 100644
index 00000000000000..01f59e36d1488e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_05_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_05_pipeline pipeline BertSentenceEmbeddings from brugmark
+author: John Snow Labs
+name: sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_05_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_05_pipeline` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_05_pipeline_en_5.5.1_3.0_1737645544108.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_05_pipeline_en_5.5.1_3.0_1737645544108.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_05_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_05_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_05_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|80.7 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-finetuned-2024-06-05
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_12_en.md b/docs/_posts/ahmedlone127/2025-01-23-sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_12_en.md
new file mode 100644
index 00000000000000..fa696fc9d2d755
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_12_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_12 BertSentenceEmbeddings from brugmark
+author: John Snow Labs
+name: sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_12
+date: 2025-01-23
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_12` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_12_en_5.5.1_3.0_1737645749535.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_12_en_5.5.1_3.0_1737645749535.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_12","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_12","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_12|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|84.8 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-finetuned-2024-06-12
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_12_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_12_pipeline_en.md
new file mode 100644
index 00000000000000..6617fecc9dc7a6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_12_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_12_pipeline pipeline BertSentenceEmbeddings from brugmark
+author: John Snow Labs
+name: sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_12_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_12_pipeline` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_12_pipeline_en_5.5.1_3.0_1737645753756.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_12_pipeline_en_5.5.1_3.0_1737645753756.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_12_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_12_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_12_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|85.4 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-finetuned-2024-06-12
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-sent_banglabert_generator_finetuned_fill_in_the_blanks_kaggle_en.md b/docs/_posts/ahmedlone127/2025-01-23-sent_banglabert_generator_finetuned_fill_in_the_blanks_kaggle_en.md
new file mode 100644
index 00000000000000..8f060f53370b5c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-sent_banglabert_generator_finetuned_fill_in_the_blanks_kaggle_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_banglabert_generator_finetuned_fill_in_the_blanks_kaggle BertSentenceEmbeddings from mahsharyahan
+author: John Snow Labs
+name: sent_banglabert_generator_finetuned_fill_in_the_blanks_kaggle
+date: 2025-01-23
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_banglabert_generator_finetuned_fill_in_the_blanks_kaggle` is a English model originally trained by mahsharyahan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_banglabert_generator_finetuned_fill_in_the_blanks_kaggle_en_5.5.1_3.0_1737645697144.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_banglabert_generator_finetuned_fill_in_the_blanks_kaggle_en_5.5.1_3.0_1737645697144.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_banglabert_generator_finetuned_fill_in_the_blanks_kaggle","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_banglabert_generator_finetuned_fill_in_the_blanks_kaggle","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_banglabert_generator_finetuned_fill_in_the_blanks_kaggle|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|130.0 MB|
+
+## References
+
+https://huggingface.co/mahsharyahan/banglabert_generator-finetuned-fill-in-the-blanks-kaggle
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-sent_banglabert_generator_finetuned_fill_in_the_blanks_kaggle_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-sent_banglabert_generator_finetuned_fill_in_the_blanks_kaggle_pipeline_en.md
new file mode 100644
index 00000000000000..b4342c902ce3d1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-sent_banglabert_generator_finetuned_fill_in_the_blanks_kaggle_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_banglabert_generator_finetuned_fill_in_the_blanks_kaggle_pipeline pipeline BertSentenceEmbeddings from mahsharyahan
+author: John Snow Labs
+name: sent_banglabert_generator_finetuned_fill_in_the_blanks_kaggle_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_banglabert_generator_finetuned_fill_in_the_blanks_kaggle_pipeline` is a English model originally trained by mahsharyahan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_banglabert_generator_finetuned_fill_in_the_blanks_kaggle_pipeline_en_5.5.1_3.0_1737645703935.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_banglabert_generator_finetuned_fill_in_the_blanks_kaggle_pipeline_en_5.5.1_3.0_1737645703935.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_banglabert_generator_finetuned_fill_in_the_blanks_kaggle_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_banglabert_generator_finetuned_fill_in_the_blanks_kaggle_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_banglabert_generator_finetuned_fill_in_the_blanks_kaggle_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|130.5 MB|
+
+## References
+
+https://huggingface.co/mahsharyahan/banglabert_generator-finetuned-fill-in-the-blanks-kaggle
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-sent_berel_base_en.md b/docs/_posts/ahmedlone127/2025-01-23-sent_berel_base_en.md
new file mode 100644
index 00000000000000..404f12657448b2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-sent_berel_base_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_berel_base BertSentenceEmbeddings from t4-project
+author: John Snow Labs
+name: sent_berel_base
+date: 2025-01-23
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_berel_base` is a English model originally trained by t4-project.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_berel_base_en_5.5.1_3.0_1737645931386.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_berel_base_en_5.5.1_3.0_1737645931386.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_berel_base","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_berel_base","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_berel_base|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|690.1 MB|
+
+## References
+
+https://huggingface.co/t4-project/BEREL-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-sent_berel_base_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-sent_berel_base_pipeline_en.md
new file mode 100644
index 00000000000000..8a9251ce7095f6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-sent_berel_base_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_berel_base_pipeline pipeline BertSentenceEmbeddings from t4-project
+author: John Snow Labs
+name: sent_berel_base_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_berel_base_pipeline` is a English model originally trained by t4-project.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_berel_base_pipeline_en_5.5.1_3.0_1737645968819.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_berel_base_pipeline_en_5.5.1_3.0_1737645968819.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_berel_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_berel_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_berel_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|690.7 MB|
+
+## References
+
+https://huggingface.co/t4-project/BEREL-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-sent_bert_base_cased_wikitext2_davyalan1_en.md b/docs/_posts/ahmedlone127/2025-01-23-sent_bert_base_cased_wikitext2_davyalan1_en.md
new file mode 100644
index 00000000000000..58d43d64409e7f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-sent_bert_base_cased_wikitext2_davyalan1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_base_cased_wikitext2_davyalan1 BertSentenceEmbeddings from davyalan1
+author: John Snow Labs
+name: sent_bert_base_cased_wikitext2_davyalan1
+date: 2025-01-23
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_cased_wikitext2_davyalan1` is a English model originally trained by davyalan1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_cased_wikitext2_davyalan1_en_5.5.1_3.0_1737645428875.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_cased_wikitext2_davyalan1_en_5.5.1_3.0_1737645428875.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_cased_wikitext2_davyalan1","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_cased_wikitext2_davyalan1","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_cased_wikitext2_davyalan1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|403.4 MB|
+
+## References
+
+https://huggingface.co/davyalan1/bert-base-cased-wikitext2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-sent_bert_base_cased_wikitext2_davyalan1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-sent_bert_base_cased_wikitext2_davyalan1_pipeline_en.md
new file mode 100644
index 00000000000000..258f463299e5f8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-sent_bert_base_cased_wikitext2_davyalan1_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_base_cased_wikitext2_davyalan1_pipeline pipeline BertSentenceEmbeddings from davyalan1
+author: John Snow Labs
+name: sent_bert_base_cased_wikitext2_davyalan1_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_cased_wikitext2_davyalan1_pipeline` is a English model originally trained by davyalan1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_cased_wikitext2_davyalan1_pipeline_en_5.5.1_3.0_1737645451154.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_cased_wikitext2_davyalan1_pipeline_en_5.5.1_3.0_1737645451154.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_base_cased_wikitext2_davyalan1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_cased_wikitext2_davyalan1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_cased_wikitext2_davyalan1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|404.0 MB|
+
+## References
+
+https://huggingface.co/davyalan1/bert-base-cased-wikitext2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-sent_bert_base_cased_wikitext2_lucasday17_en.md b/docs/_posts/ahmedlone127/2025-01-23-sent_bert_base_cased_wikitext2_lucasday17_en.md
new file mode 100644
index 00000000000000..2f4b05efb671e1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-sent_bert_base_cased_wikitext2_lucasday17_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_base_cased_wikitext2_lucasday17 BertSentenceEmbeddings from LucasDay17
+author: John Snow Labs
+name: sent_bert_base_cased_wikitext2_lucasday17
+date: 2025-01-23
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_cased_wikitext2_lucasday17` is a English model originally trained by LucasDay17.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_cased_wikitext2_lucasday17_en_5.5.1_3.0_1737646230973.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_cased_wikitext2_lucasday17_en_5.5.1_3.0_1737646230973.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_cased_wikitext2_lucasday17","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_cased_wikitext2_lucasday17","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_cased_wikitext2_lucasday17|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|403.4 MB|
+
+## References
+
+https://huggingface.co/LucasDay17/bert-base-cased-wikitext2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-sent_bert_base_cased_wikitext2_lucasday17_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-sent_bert_base_cased_wikitext2_lucasday17_pipeline_en.md
new file mode 100644
index 00000000000000..e49be62e4d143a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-sent_bert_base_cased_wikitext2_lucasday17_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_base_cased_wikitext2_lucasday17_pipeline pipeline BertSentenceEmbeddings from LucasDay17
+author: John Snow Labs
+name: sent_bert_base_cased_wikitext2_lucasday17_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_cased_wikitext2_lucasday17_pipeline` is a English model originally trained by LucasDay17.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_cased_wikitext2_lucasday17_pipeline_en_5.5.1_3.0_1737646252882.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_cased_wikitext2_lucasday17_pipeline_en_5.5.1_3.0_1737646252882.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_base_cased_wikitext2_lucasday17_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_cased_wikitext2_lucasday17_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_cased_wikitext2_lucasday17_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|404.0 MB|
+
+## References
+
+https://huggingface.co/LucasDay17/bert-base-cased-wikitext2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-sent_bert_base_multilingual_sakha_cased_2_pipeline_xx.md b/docs/_posts/ahmedlone127/2025-01-23-sent_bert_base_multilingual_sakha_cased_2_pipeline_xx.md
new file mode 100644
index 00000000000000..b818fd10257beb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-sent_bert_base_multilingual_sakha_cased_2_pipeline_xx.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Multilingual sent_bert_base_multilingual_sakha_cased_2_pipeline pipeline BertSentenceEmbeddings from bamaxi
+author: John Snow Labs
+name: sent_bert_base_multilingual_sakha_cased_2_pipeline
+date: 2025-01-23
+tags: [xx, open_source, pipeline, onnx]
+task: Embeddings
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_multilingual_sakha_cased_2_pipeline` is a Multilingual model originally trained by bamaxi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_multilingual_sakha_cased_2_pipeline_xx_5.5.1_3.0_1737645800734.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_multilingual_sakha_cased_2_pipeline_xx_5.5.1_3.0_1737645800734.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_base_multilingual_sakha_cased_2_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_multilingual_sakha_cased_2_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_multilingual_sakha_cased_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|743.6 MB|
+
+## References
+
+https://huggingface.co/bamaxi/bert-base-multilingual-sakha-cased_2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-sent_bert_base_multilingual_sakha_cased_2_xx.md b/docs/_posts/ahmedlone127/2025-01-23-sent_bert_base_multilingual_sakha_cased_2_xx.md
new file mode 100644
index 00000000000000..e104003143fb72
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-sent_bert_base_multilingual_sakha_cased_2_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual sent_bert_base_multilingual_sakha_cased_2 BertSentenceEmbeddings from bamaxi
+author: John Snow Labs
+name: sent_bert_base_multilingual_sakha_cased_2
+date: 2025-01-23
+tags: [xx, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_multilingual_sakha_cased_2` is a Multilingual model originally trained by bamaxi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_multilingual_sakha_cased_2_xx_5.5.1_3.0_1737645762147.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_multilingual_sakha_cased_2_xx_5.5.1_3.0_1737645762147.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_multilingual_sakha_cased_2","xx") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_multilingual_sakha_cased_2","xx") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_multilingual_sakha_cased_2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|xx|
+|Size:|743.1 MB|
+
+## References
+
+https://huggingface.co/bamaxi/bert-base-multilingual-sakha-cased_2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-sent_bert_l2_h768_uncased_en.md b/docs/_posts/ahmedlone127/2025-01-23-sent_bert_l2_h768_uncased_en.md
new file mode 100644
index 00000000000000..381effb4f3e666
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-sent_bert_l2_h768_uncased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_l2_h768_uncased BertSentenceEmbeddings from gaunernst
+author: John Snow Labs
+name: sent_bert_l2_h768_uncased
+date: 2025-01-23
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_l2_h768_uncased` is a English model originally trained by gaunernst.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_l2_h768_uncased_en_5.5.1_3.0_1737645322151.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_l2_h768_uncased_en_5.5.1_3.0_1737645322151.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_l2_h768_uncased","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_l2_h768_uncased","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_l2_h768_uncased|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|141.9 MB|
+
+## References
+
+https://huggingface.co/gaunernst/bert-L2-H768-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-sent_bert_l2_h768_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-sent_bert_l2_h768_uncased_pipeline_en.md
new file mode 100644
index 00000000000000..ae9d84c86dab41
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-sent_bert_l2_h768_uncased_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_l2_h768_uncased_pipeline pipeline BertSentenceEmbeddings from gaunernst
+author: John Snow Labs
+name: sent_bert_l2_h768_uncased_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_l2_h768_uncased_pipeline` is a English model originally trained by gaunernst.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_l2_h768_uncased_pipeline_en_5.5.1_3.0_1737645329390.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_l2_h768_uncased_pipeline_en_5.5.1_3.0_1737645329390.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_l2_h768_uncased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_l2_h768_uncased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_l2_h768_uncased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|142.4 MB|
+
+## References
+
+https://huggingface.co/gaunernst/bert-L2-H768-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-sent_bert_maskedlm_ppt_en.md b/docs/_posts/ahmedlone127/2025-01-23-sent_bert_maskedlm_ppt_en.md
new file mode 100644
index 00000000000000..5ca83d7430fc6e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-sent_bert_maskedlm_ppt_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_maskedlm_ppt BertSentenceEmbeddings from trnthsn
+author: John Snow Labs
+name: sent_bert_maskedlm_ppt
+date: 2025-01-23
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_maskedlm_ppt` is a English model originally trained by trnthsn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_maskedlm_ppt_en_5.5.1_3.0_1737645473940.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_maskedlm_ppt_en_5.5.1_3.0_1737645473940.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_maskedlm_ppt","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_maskedlm_ppt","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_maskedlm_ppt|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|433.7 MB|
+
+## References
+
+https://huggingface.co/trnthsn/bert-maskedlm-ppt
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-sent_bert_maskedlm_ppt_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-sent_bert_maskedlm_ppt_pipeline_en.md
new file mode 100644
index 00000000000000..eed9cfa8c28ff9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-sent_bert_maskedlm_ppt_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_maskedlm_ppt_pipeline pipeline BertSentenceEmbeddings from trnthsn
+author: John Snow Labs
+name: sent_bert_maskedlm_ppt_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_maskedlm_ppt_pipeline` is a English model originally trained by trnthsn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_maskedlm_ppt_pipeline_en_5.5.1_3.0_1737645497013.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_maskedlm_ppt_pipeline_en_5.5.1_3.0_1737645497013.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_maskedlm_ppt_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_maskedlm_ppt_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_maskedlm_ppt_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|434.3 MB|
+
+## References
+
+https://huggingface.co/trnthsn/bert-maskedlm-ppt
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-sent_clip_softmax_bert_base_en.md b/docs/_posts/ahmedlone127/2025-01-23-sent_clip_softmax_bert_base_en.md
new file mode 100644
index 00000000000000..86e45fdf32a517
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-sent_clip_softmax_bert_base_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_clip_softmax_bert_base BertSentenceEmbeddings from magicslabnu
+author: John Snow Labs
+name: sent_clip_softmax_bert_base
+date: 2025-01-23
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_clip_softmax_bert_base` is a English model originally trained by magicslabnu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_clip_softmax_bert_base_en_5.5.1_3.0_1737646179804.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_clip_softmax_bert_base_en_5.5.1_3.0_1737646179804.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_clip_softmax_bert_base","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_clip_softmax_bert_base","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_clip_softmax_bert_base|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|408.4 MB|
+
+## References
+
+https://huggingface.co/magicslabnu/clip_softmax_bert_base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-sent_clip_softmax_bert_base_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-sent_clip_softmax_bert_base_pipeline_en.md
new file mode 100644
index 00000000000000..6d22e57984f9b5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-sent_clip_softmax_bert_base_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_clip_softmax_bert_base_pipeline pipeline BertSentenceEmbeddings from magicslabnu
+author: John Snow Labs
+name: sent_clip_softmax_bert_base_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_clip_softmax_bert_base_pipeline` is a English model originally trained by magicslabnu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_clip_softmax_bert_base_pipeline_en_5.5.1_3.0_1737646201931.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_clip_softmax_bert_base_pipeline_en_5.5.1_3.0_1737646201931.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_clip_softmax_bert_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_clip_softmax_bert_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_clip_softmax_bert_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.0 MB|
+
+## References
+
+https://huggingface.co/magicslabnu/clip_softmax_bert_base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-sent_farabi_en.md b/docs/_posts/ahmedlone127/2025-01-23-sent_farabi_en.md
new file mode 100644
index 00000000000000..9b6503c86f49c2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-sent_farabi_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_farabi XlmRoBertaSentenceEmbeddings from blaze187
+author: John Snow Labs
+name: sent_farabi
+date: 2025-01-23
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_farabi` is a English model originally trained by blaze187.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_farabi_en_5.5.1_3.0_1737662172611.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_farabi_en_5.5.1_3.0_1737662172611.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_farabi","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_farabi","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_farabi|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|981.3 MB|
+
+## References
+
+https://huggingface.co/blaze187/farabi
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-sent_farabi_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-sent_farabi_pipeline_en.md
new file mode 100644
index 00000000000000..d51f76fbe17c94
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-sent_farabi_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_farabi_pipeline pipeline XlmRoBertaSentenceEmbeddings from blaze187
+author: John Snow Labs
+name: sent_farabi_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_farabi_pipeline` is a English model originally trained by blaze187.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_farabi_pipeline_en_5.5.1_3.0_1737662250606.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_farabi_pipeline_en_5.5.1_3.0_1737662250606.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_farabi_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_farabi_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_farabi_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|981.8 MB|
+
+## References
+
+https://huggingface.co/blaze187/farabi
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-sent_gujibert_jian_en.md b/docs/_posts/ahmedlone127/2025-01-23-sent_gujibert_jian_en.md
new file mode 100644
index 00000000000000..b82158701eace6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-sent_gujibert_jian_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_gujibert_jian BertSentenceEmbeddings from hsc748NLP
+author: John Snow Labs
+name: sent_gujibert_jian
+date: 2025-01-23
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_gujibert_jian` is a English model originally trained by hsc748NLP.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_gujibert_jian_en_5.5.1_3.0_1737646385589.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_gujibert_jian_en_5.5.1_3.0_1737646385589.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_gujibert_jian","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_gujibert_jian","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_gujibert_jian|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|420.3 MB|
+
+## References
+
+https://huggingface.co/hsc748NLP/GujiBERT_jian
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-sent_gujibert_jian_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-sent_gujibert_jian_pipeline_en.md
new file mode 100644
index 00000000000000..8ec63f37b16be8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-sent_gujibert_jian_pipeline_en.md
@@ -0,0 +1,73 @@
+---
+layout: model
+title: English sent_gujibert_jian_pipeline pipeline BertSentenceEmbeddings from hsc748NLP
+author: John Snow Labs
+name: sent_gujibert_jian_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_gujibert_jian_pipeline` is a English model originally trained by hsc748NLP.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_gujibert_jian_pipeline_en_5.5.1_3.0_1737646407817.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_gujibert_jian_pipeline_en_5.5.1_3.0_1737646407817.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("sent_gujibert_jian_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("sent_gujibert_jian_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_gujibert_jian_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|420.8 MB|
+
+## References
+
+References
+
+https://huggingface.co/hsc748NLP/GujiBERT_jian
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-sent_mbert_swedish_distilled_cased_pipeline_sv.md b/docs/_posts/ahmedlone127/2025-01-23-sent_mbert_swedish_distilled_cased_pipeline_sv.md
new file mode 100644
index 00000000000000..75ebf888e2eec1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-sent_mbert_swedish_distilled_cased_pipeline_sv.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Swedish sent_mbert_swedish_distilled_cased_pipeline pipeline BertSentenceEmbeddings from Addedk
+author: John Snow Labs
+name: sent_mbert_swedish_distilled_cased_pipeline
+date: 2025-01-23
+tags: [sv, open_source, pipeline, onnx]
+task: Embeddings
+language: sv
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_mbert_swedish_distilled_cased_pipeline` is a Swedish model originally trained by Addedk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_mbert_swedish_distilled_cased_pipeline_sv_5.5.1_3.0_1737645440815.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_mbert_swedish_distilled_cased_pipeline_sv_5.5.1_3.0_1737645440815.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_mbert_swedish_distilled_cased_pipeline", lang = "sv")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_mbert_swedish_distilled_cased_pipeline", lang = "sv")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_mbert_swedish_distilled_cased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|sv|
+|Size:|506.2 MB|
+
+## References
+
+https://huggingface.co/Addedk/mbert-swedish-distilled-cased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-sent_mbert_swedish_distilled_cased_sv.md b/docs/_posts/ahmedlone127/2025-01-23-sent_mbert_swedish_distilled_cased_sv.md
new file mode 100644
index 00000000000000..88ba6b46ee1c6e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-sent_mbert_swedish_distilled_cased_sv.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Swedish sent_mbert_swedish_distilled_cased BertSentenceEmbeddings from Addedk
+author: John Snow Labs
+name: sent_mbert_swedish_distilled_cased
+date: 2025-01-23
+tags: [sv, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: sv
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_mbert_swedish_distilled_cased` is a Swedish model originally trained by Addedk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_mbert_swedish_distilled_cased_sv_5.5.1_3.0_1737645413393.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_mbert_swedish_distilled_cased_sv_5.5.1_3.0_1737645413393.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_mbert_swedish_distilled_cased","sv") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_mbert_swedish_distilled_cased","sv") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_mbert_swedish_distilled_cased|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|sv|
+|Size:|505.7 MB|
+
+## References
+
+https://huggingface.co/Addedk/mbert-swedish-distilled-cased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-sent_spam_bert_uncased_en.md b/docs/_posts/ahmedlone127/2025-01-23-sent_spam_bert_uncased_en.md
new file mode 100644
index 00000000000000..b2a708214adf0b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-sent_spam_bert_uncased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_spam_bert_uncased BertSentenceEmbeddings from prithivMLmods
+author: John Snow Labs
+name: sent_spam_bert_uncased
+date: 2025-01-23
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_spam_bert_uncased` is a English model originally trained by prithivMLmods.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_spam_bert_uncased_en_5.5.1_3.0_1737645637524.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_spam_bert_uncased_en_5.5.1_3.0_1737645637524.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_spam_bert_uncased","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_spam_bert_uncased","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_spam_bert_uncased|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/prithivMLmods/Spam-Bert-Uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-sent_spam_bert_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-sent_spam_bert_uncased_pipeline_en.md
new file mode 100644
index 00000000000000..2485721303194b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-sent_spam_bert_uncased_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_spam_bert_uncased_pipeline pipeline BertSentenceEmbeddings from prithivMLmods
+author: John Snow Labs
+name: sent_spam_bert_uncased_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_spam_bert_uncased_pipeline` is a English model originally trained by prithivMLmods.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_spam_bert_uncased_pipeline_en_5.5.1_3.0_1737645658972.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_spam_bert_uncased_pipeline_en_5.5.1_3.0_1737645658972.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_spam_bert_uncased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_spam_bert_uncased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_spam_bert_uncased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.7 MB|
+
+## References
+
+https://huggingface.co/prithivMLmods/Spam-Bert-Uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-sent_xlm_roberta_base_latin_uncased_la.md b/docs/_posts/ahmedlone127/2025-01-23-sent_xlm_roberta_base_latin_uncased_la.md
new file mode 100644
index 00000000000000..6ec722558d0147
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-sent_xlm_roberta_base_latin_uncased_la.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Latin sent_xlm_roberta_base_latin_uncased XlmRoBertaSentenceEmbeddings from Cicciokr
+author: John Snow Labs
+name: sent_xlm_roberta_base_latin_uncased
+date: 2025-01-23
+tags: [la, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: la
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_roberta_base_latin_uncased` is a Latin model originally trained by Cicciokr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_latin_uncased_la_5.5.1_3.0_1737661798140.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_latin_uncased_la_5.5.1_3.0_1737661798140.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_base_latin_uncased","la") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_base_latin_uncased","la") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_roberta_base_latin_uncased|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|la|
+|Size:|916.1 MB|
+
+## References
+
+https://huggingface.co/Cicciokr/XLM-Roberta-Base-Latin-Uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-sent_xlm_roberta_base_latin_uncased_pipeline_la.md b/docs/_posts/ahmedlone127/2025-01-23-sent_xlm_roberta_base_latin_uncased_pipeline_la.md
new file mode 100644
index 00000000000000..03ddbc31a3de5b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-sent_xlm_roberta_base_latin_uncased_pipeline_la.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Latin sent_xlm_roberta_base_latin_uncased_pipeline pipeline XlmRoBertaSentenceEmbeddings from Cicciokr
+author: John Snow Labs
+name: sent_xlm_roberta_base_latin_uncased_pipeline
+date: 2025-01-23
+tags: [la, open_source, pipeline, onnx]
+task: Embeddings
+language: la
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_roberta_base_latin_uncased_pipeline` is a Latin model originally trained by Cicciokr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_latin_uncased_pipeline_la_5.5.1_3.0_1737661880094.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_latin_uncased_pipeline_la_5.5.1_3.0_1737661880094.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_xlm_roberta_base_latin_uncased_pipeline", lang = "la")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_xlm_roberta_base_latin_uncased_pipeline", lang = "la")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_roberta_base_latin_uncased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|la|
+|Size:|916.7 MB|
+
+## References
+
+https://huggingface.co/Cicciokr/XLM-Roberta-Base-Latin-Uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-sent_xlm_roberta_base_tycholina_en.md b/docs/_posts/ahmedlone127/2025-01-23-sent_xlm_roberta_base_tycholina_en.md
new file mode 100644
index 00000000000000..9f664ff29bc171
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-sent_xlm_roberta_base_tycholina_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_xlm_roberta_base_tycholina XlmRoBertaSentenceEmbeddings from lailamt
+author: John Snow Labs
+name: sent_xlm_roberta_base_tycholina
+date: 2025-01-23
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_roberta_base_tycholina` is a English model originally trained by lailamt.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_tycholina_en_5.5.1_3.0_1737661864504.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_tycholina_en_5.5.1_3.0_1737661864504.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_base_tycholina","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_base_tycholina","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_roberta_base_tycholina|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/lailamt/xlm-roberta-base-tycholina
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-sent_xlm_roberta_base_tycholina_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-sent_xlm_roberta_base_tycholina_pipeline_en.md
new file mode 100644
index 00000000000000..7a107d4cb38e3f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-sent_xlm_roberta_base_tycholina_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_xlm_roberta_base_tycholina_pipeline pipeline XlmRoBertaSentenceEmbeddings from lailamt
+author: John Snow Labs
+name: sent_xlm_roberta_base_tycholina_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_roberta_base_tycholina_pipeline` is a English model originally trained by lailamt.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_tycholina_pipeline_en_5.5.1_3.0_1737661926086.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_tycholina_pipeline_en_5.5.1_3.0_1737661926086.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_xlm_roberta_base_tycholina_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_xlm_roberta_base_tycholina_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_roberta_base_tycholina_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/lailamt/xlm-roberta-base-tycholina
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-sent_xlmr_base_emakhuwa_en.md b/docs/_posts/ahmedlone127/2025-01-23-sent_xlmr_base_emakhuwa_en.md
new file mode 100644
index 00000000000000..fff487a643fa04
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-sent_xlmr_base_emakhuwa_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_xlmr_base_emakhuwa XlmRoBertaSentenceEmbeddings from felerminoali
+author: John Snow Labs
+name: sent_xlmr_base_emakhuwa
+date: 2025-01-23
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlmr_base_emakhuwa` is a English model originally trained by felerminoali.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlmr_base_emakhuwa_en_5.5.1_3.0_1737661984907.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlmr_base_emakhuwa_en_5.5.1_3.0_1737661984907.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlmr_base_emakhuwa","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlmr_base_emakhuwa","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlmr_base_emakhuwa|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/felerminoali/xlmr_base_emakhuwa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-sent_xlmr_base_emakhuwa_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-sent_xlmr_base_emakhuwa_pipeline_en.md
new file mode 100644
index 00000000000000..ab0946e4f65090
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-sent_xlmr_base_emakhuwa_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_xlmr_base_emakhuwa_pipeline pipeline XlmRoBertaSentenceEmbeddings from felerminoali
+author: John Snow Labs
+name: sent_xlmr_base_emakhuwa_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlmr_base_emakhuwa_pipeline` is a English model originally trained by felerminoali.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlmr_base_emakhuwa_pipeline_en_5.5.1_3.0_1737662045488.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlmr_base_emakhuwa_pipeline_en_5.5.1_3.0_1737662045488.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_xlmr_base_emakhuwa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_xlmr_base_emakhuwa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlmr_base_emakhuwa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/felerminoali/xlmr_base_emakhuwa
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-sentiment_analysis_model_v2_en.md b/docs/_posts/ahmedlone127/2025-01-23-sentiment_analysis_model_v2_en.md
new file mode 100644
index 00000000000000..a984a6d0c03044
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-sentiment_analysis_model_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sentiment_analysis_model_v2 DistilBertForSequenceClassification from tashrifmahmud
+author: John Snow Labs
+name: sentiment_analysis_model_v2
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentiment_analysis_model_v2` is a English model originally trained by tashrifmahmud.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentiment_analysis_model_v2_en_5.5.1_3.0_1737650920506.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentiment_analysis_model_v2_en_5.5.1_3.0_1737650920506.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("sentiment_analysis_model_v2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("sentiment_analysis_model_v2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sentiment_analysis_model_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/tashrifmahmud/sentiment_analysis_model_v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-sentiment_analysis_model_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-sentiment_analysis_model_v2_pipeline_en.md
new file mode 100644
index 00000000000000..a3a7272bb8a918
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-sentiment_analysis_model_v2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English sentiment_analysis_model_v2_pipeline pipeline DistilBertForSequenceClassification from tashrifmahmud
+author: John Snow Labs
+name: sentiment_analysis_model_v2_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentiment_analysis_model_v2_pipeline` is a English model originally trained by tashrifmahmud.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentiment_analysis_model_v2_pipeline_en_5.5.1_3.0_1737650935236.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentiment_analysis_model_v2_pipeline_en_5.5.1_3.0_1737650935236.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sentiment_analysis_model_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sentiment_analysis_model_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sentiment_analysis_model_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/tashrifmahmud/sentiment_analysis_model_v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-sinhala_bert_medium_v2_pipeline_si.md b/docs/_posts/ahmedlone127/2025-01-23-sinhala_bert_medium_v2_pipeline_si.md
new file mode 100644
index 00000000000000..a9ac6dd53d5410
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-sinhala_bert_medium_v2_pipeline_si.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Sinhala, Sinhalese sinhala_bert_medium_v2_pipeline pipeline BertEmbeddings from Ransaka
+author: John Snow Labs
+name: sinhala_bert_medium_v2_pipeline
+date: 2025-01-23
+tags: [si, open_source, pipeline, onnx]
+task: Embeddings
+language: si
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sinhala_bert_medium_v2_pipeline` is a Sinhala, Sinhalese model originally trained by Ransaka.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sinhala_bert_medium_v2_pipeline_si_5.5.1_3.0_1737637257242.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sinhala_bert_medium_v2_pipeline_si_5.5.1_3.0_1737637257242.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sinhala_bert_medium_v2_pipeline", lang = "si")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sinhala_bert_medium_v2_pipeline", lang = "si")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sinhala_bert_medium_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|si|
+|Size:|187.4 MB|
+
+## References
+
+https://huggingface.co/Ransaka/sinhala-bert-medium-v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-sinhala_bert_medium_v2_si.md b/docs/_posts/ahmedlone127/2025-01-23-sinhala_bert_medium_v2_si.md
new file mode 100644
index 00000000000000..1b534c55351c10
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-sinhala_bert_medium_v2_si.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Sinhala, Sinhalese sinhala_bert_medium_v2 BertEmbeddings from Ransaka
+author: John Snow Labs
+name: sinhala_bert_medium_v2
+date: 2025-01-23
+tags: [si, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: si
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sinhala_bert_medium_v2` is a Sinhala, Sinhalese model originally trained by Ransaka.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sinhala_bert_medium_v2_si_5.5.1_3.0_1737637247218.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sinhala_bert_medium_v2_si_5.5.1_3.0_1737637247218.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("sinhala_bert_medium_v2","si") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("sinhala_bert_medium_v2","si") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sinhala_bert_medium_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|si|
+|Size:|187.4 MB|
+
+## References
+
+https://huggingface.co/Ransaka/sinhala-bert-medium-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-slm_custom_model_6k_en.md b/docs/_posts/ahmedlone127/2025-01-23-slm_custom_model_6k_en.md
new file mode 100644
index 00000000000000..1ff68b18d008ff
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-slm_custom_model_6k_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English slm_custom_model_6k T5Transformer from karthikeyan-r
+author: John Snow Labs
+name: slm_custom_model_6k
+date: 2025-01-23
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`slm_custom_model_6k` is a English model originally trained by karthikeyan-r.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/slm_custom_model_6k_en_5.5.1_3.0_1737633550241.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/slm_custom_model_6k_en_5.5.1_3.0_1737633550241.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("slm_custom_model_6k","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("slm_custom_model_6k", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|slm_custom_model_6k|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|277.2 MB|
+
+## References
+
+https://huggingface.co/karthikeyan-r/slm-custom-model_6k
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-slm_custom_model_6k_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-slm_custom_model_6k_pipeline_en.md
new file mode 100644
index 00000000000000..f6e1af4b683f82
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-slm_custom_model_6k_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English slm_custom_model_6k_pipeline pipeline T5Transformer from karthikeyan-r
+author: John Snow Labs
+name: slm_custom_model_6k_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`slm_custom_model_6k_pipeline` is a English model originally trained by karthikeyan-r.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/slm_custom_model_6k_pipeline_en_5.5.1_3.0_1737633566571.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/slm_custom_model_6k_pipeline_en_5.5.1_3.0_1737633566571.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("slm_custom_model_6k_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("slm_custom_model_6k_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|slm_custom_model_6k_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|277.2 MB|
+
+## References
+
+https://huggingface.co/karthikeyan-r/slm-custom-model_6k
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-smartbert_v2_en.md b/docs/_posts/ahmedlone127/2025-01-23-smartbert_v2_en.md
new file mode 100644
index 00000000000000..2faf3ef6b26b9e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-smartbert_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English smartbert_v2 RoBertaEmbeddings from web3se
+author: John Snow Labs
+name: smartbert_v2
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`smartbert_v2` is a English model originally trained by web3se.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/smartbert_v2_en_5.5.1_3.0_1737644364240.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/smartbert_v2_en_5.5.1_3.0_1737644364240.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("smartbert_v2","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("smartbert_v2","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|smartbert_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|466.1 MB|
+
+## References
+
+https://huggingface.co/web3se/SmartBERT-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-smartbert_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-smartbert_v2_pipeline_en.md
new file mode 100644
index 00000000000000..b43ce53e3dec70
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-smartbert_v2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English smartbert_v2_pipeline pipeline RoBertaEmbeddings from web3se
+author: John Snow Labs
+name: smartbert_v2_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`smartbert_v2_pipeline` is a English model originally trained by web3se.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/smartbert_v2_pipeline_en_5.5.1_3.0_1737644388705.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/smartbert_v2_pipeline_en_5.5.1_3.0_1737644388705.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("smartbert_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("smartbert_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|smartbert_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.1 MB|
+
+## References
+
+https://huggingface.co/web3se/SmartBERT-v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-soluciona_fm_tcv_1_en.md b/docs/_posts/ahmedlone127/2025-01-23-soluciona_fm_tcv_1_en.md
new file mode 100644
index 00000000000000..b0054d548266ca
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-soluciona_fm_tcv_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English soluciona_fm_tcv_1 XlmRoBertaForSequenceClassification from adriansanz
+author: John Snow Labs
+name: soluciona_fm_tcv_1
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`soluciona_fm_tcv_1` is a English model originally trained by adriansanz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/soluciona_fm_tcv_1_en_5.5.1_3.0_1737651645832.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/soluciona_fm_tcv_1_en_5.5.1_3.0_1737651645832.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("soluciona_fm_tcv_1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("soluciona_fm_tcv_1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|soluciona_fm_tcv_1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|778.8 MB|
+
+## References
+
+https://huggingface.co/adriansanz/soluciona_fm_tcv_1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-soluciona_fm_tcv_1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-soluciona_fm_tcv_1_pipeline_en.md
new file mode 100644
index 00000000000000..9284b00a73a3ba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-soluciona_fm_tcv_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English soluciona_fm_tcv_1_pipeline pipeline XlmRoBertaForSequenceClassification from adriansanz
+author: John Snow Labs
+name: soluciona_fm_tcv_1_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`soluciona_fm_tcv_1_pipeline` is a English model originally trained by adriansanz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/soluciona_fm_tcv_1_pipeline_en_5.5.1_3.0_1737651793534.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/soluciona_fm_tcv_1_pipeline_en_5.5.1_3.0_1737651793534.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("soluciona_fm_tcv_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("soluciona_fm_tcv_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|soluciona_fm_tcv_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|778.8 MB|
+
+## References
+
+https://huggingface.co/adriansanz/soluciona_fm_tcv_1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-spam_bert_uncased_en.md b/docs/_posts/ahmedlone127/2025-01-23-spam_bert_uncased_en.md
new file mode 100644
index 00000000000000..e585871e5e6904
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-spam_bert_uncased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English spam_bert_uncased BertEmbeddings from prithivMLmods
+author: John Snow Labs
+name: spam_bert_uncased
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`spam_bert_uncased` is a English model originally trained by prithivMLmods.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/spam_bert_uncased_en_5.5.1_3.0_1737637445067.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/spam_bert_uncased_en_5.5.1_3.0_1737637445067.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("spam_bert_uncased","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("spam_bert_uncased","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|spam_bert_uncased|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/prithivMLmods/Spam-Bert-Uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-spam_bert_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-spam_bert_uncased_pipeline_en.md
new file mode 100644
index 00000000000000..7ea2d6e7a23679
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-spam_bert_uncased_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English spam_bert_uncased_pipeline pipeline BertEmbeddings from prithivMLmods
+author: John Snow Labs
+name: spam_bert_uncased_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`spam_bert_uncased_pipeline` is a English model originally trained by prithivMLmods.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/spam_bert_uncased_pipeline_en_5.5.1_3.0_1737637466465.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/spam_bert_uncased_pipeline_en_5.5.1_3.0_1737637466465.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("spam_bert_uncased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("spam_bert_uncased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|spam_bert_uncased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/prithivMLmods/Spam-Bert-Uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-squad10json_en.md b/docs/_posts/ahmedlone127/2025-01-23-squad10json_en.md
new file mode 100644
index 00000000000000..d384e6d5190352
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-squad10json_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English squad10json DistilBertForQuestionAnswering from 2023mt03024
+author: John Snow Labs
+name: squad10json
+date: 2025-01-23
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`squad10json` is a English model originally trained by 2023mt03024.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/squad10json_en_5.5.1_3.0_1737660293243.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/squad10json_en_5.5.1_3.0_1737660293243.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("squad10json","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("squad10json", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|squad10json|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/2023mt03024/squad10json
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-squad10json_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-squad10json_pipeline_en.md
new file mode 100644
index 00000000000000..e3485b8eeca5a2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-squad10json_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English squad10json_pipeline pipeline DistilBertForQuestionAnswering from 2023mt03024
+author: John Snow Labs
+name: squad10json_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`squad10json_pipeline` is a English model originally trained by 2023mt03024.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/squad10json_pipeline_en_5.5.1_3.0_1737660307314.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/squad10json_pipeline_en_5.5.1_3.0_1737660307314.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("squad10json_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("squad10json_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|squad10json_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/2023mt03024/squad10json
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-squeezebert_finetuned_better_daily_dialog_en.md b/docs/_posts/ahmedlone127/2025-01-23-squeezebert_finetuned_better_daily_dialog_en.md
new file mode 100644
index 00000000000000..52e894f1eb2454
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-squeezebert_finetuned_better_daily_dialog_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English squeezebert_finetuned_better_daily_dialog BertEmbeddings from BaioSbubens
+author: John Snow Labs
+name: squeezebert_finetuned_better_daily_dialog
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`squeezebert_finetuned_better_daily_dialog` is a English model originally trained by BaioSbubens.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/squeezebert_finetuned_better_daily_dialog_en_5.5.1_3.0_1737638009814.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/squeezebert_finetuned_better_daily_dialog_en_5.5.1_3.0_1737638009814.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("squeezebert_finetuned_better_daily_dialog","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("squeezebert_finetuned_better_daily_dialog","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|squeezebert_finetuned_better_daily_dialog|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|189.0 MB|
+
+## References
+
+https://huggingface.co/BaioSbubens/squeezebert-finetuned-better_daily_dialog
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-squeezebert_finetuned_better_daily_dialog_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-squeezebert_finetuned_better_daily_dialog_pipeline_en.md
new file mode 100644
index 00000000000000..3491272d7f9369
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-squeezebert_finetuned_better_daily_dialog_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English squeezebert_finetuned_better_daily_dialog_pipeline pipeline BertEmbeddings from BaioSbubens
+author: John Snow Labs
+name: squeezebert_finetuned_better_daily_dialog_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`squeezebert_finetuned_better_daily_dialog_pipeline` is a English model originally trained by BaioSbubens.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/squeezebert_finetuned_better_daily_dialog_pipeline_en_5.5.1_3.0_1737638019662.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/squeezebert_finetuned_better_daily_dialog_pipeline_en_5.5.1_3.0_1737638019662.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("squeezebert_finetuned_better_daily_dialog_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("squeezebert_finetuned_better_daily_dialog_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|squeezebert_finetuned_better_daily_dialog_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|189.0 MB|
+
+## References
+
+https://huggingface.co/BaioSbubens/squeezebert-finetuned-better_daily_dialog
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-summarization_model_ddexterr_en.md b/docs/_posts/ahmedlone127/2025-01-23-summarization_model_ddexterr_en.md
new file mode 100644
index 00000000000000..f0bd16f1d96e35
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-summarization_model_ddexterr_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English summarization_model_ddexterr T5Transformer from ddexterr
+author: John Snow Labs
+name: summarization_model_ddexterr
+date: 2025-01-23
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`summarization_model_ddexterr` is a English model originally trained by ddexterr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/summarization_model_ddexterr_en_5.5.1_3.0_1737633858975.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/summarization_model_ddexterr_en_5.5.1_3.0_1737633858975.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("summarization_model_ddexterr","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("summarization_model_ddexterr", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|summarization_model_ddexterr|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|270.4 MB|
+
+## References
+
+https://huggingface.co/ddexterr/Summarization_Model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-summarization_model_ddexterr_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-summarization_model_ddexterr_pipeline_en.md
new file mode 100644
index 00000000000000..d027973fa01bf9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-summarization_model_ddexterr_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English summarization_model_ddexterr_pipeline pipeline T5Transformer from ddexterr
+author: John Snow Labs
+name: summarization_model_ddexterr_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`summarization_model_ddexterr_pipeline` is a English model originally trained by ddexterr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/summarization_model_ddexterr_pipeline_en_5.5.1_3.0_1737633877581.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/summarization_model_ddexterr_pipeline_en_5.5.1_3.0_1737633877581.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("summarization_model_ddexterr_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("summarization_model_ddexterr_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|summarization_model_ddexterr_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|270.4 MB|
+
+## References
+
+https://huggingface.co/ddexterr/Summarization_Model
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-synthetic_text_classification_news_autotrain_model_en.md b/docs/_posts/ahmedlone127/2025-01-23-synthetic_text_classification_news_autotrain_model_en.md
new file mode 100644
index 00000000000000..254be5b38fc771
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-synthetic_text_classification_news_autotrain_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English synthetic_text_classification_news_autotrain_model MPNetForSequenceClassification from argilla
+author: John Snow Labs
+name: synthetic_text_classification_news_autotrain_model
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, mpnet]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`synthetic_text_classification_news_autotrain_model` is a English model originally trained by argilla.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/synthetic_text_classification_news_autotrain_model_en_5.5.1_3.0_1737642115400.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/synthetic_text_classification_news_autotrain_model_en_5.5.1_3.0_1737642115400.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = MPNetForSequenceClassification.pretrained("synthetic_text_classification_news_autotrain_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = MPNetForSequenceClassification.pretrained("synthetic_text_classification_news_autotrain_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|synthetic_text_classification_news_autotrain_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|408.9 MB|
+
+## References
+
+https://huggingface.co/argilla/synthetic-text-classification-news-autotrain-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-synthetic_text_classification_news_autotrain_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-synthetic_text_classification_news_autotrain_model_pipeline_en.md
new file mode 100644
index 00000000000000..e726e217daa5c4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-synthetic_text_classification_news_autotrain_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English synthetic_text_classification_news_autotrain_model_pipeline pipeline MPNetForSequenceClassification from argilla
+author: John Snow Labs
+name: synthetic_text_classification_news_autotrain_model_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`synthetic_text_classification_news_autotrain_model_pipeline` is a English model originally trained by argilla.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/synthetic_text_classification_news_autotrain_model_pipeline_en_5.5.1_3.0_1737642140578.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/synthetic_text_classification_news_autotrain_model_pipeline_en_5.5.1_3.0_1737642140578.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("synthetic_text_classification_news_autotrain_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("synthetic_text_classification_news_autotrain_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|synthetic_text_classification_news_autotrain_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|408.9 MB|
+
+## References
+
+https://huggingface.co/argilla/synthetic-text-classification-news-autotrain-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- MPNetForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-t5_base_neg2pos_en.md b/docs/_posts/ahmedlone127/2025-01-23-t5_base_neg2pos_en.md
new file mode 100644
index 00000000000000..7ff76e4a07cbc3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-t5_base_neg2pos_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_base_neg2pos T5Transformer from ggallipoli
+author: John Snow Labs
+name: t5_base_neg2pos
+date: 2025-01-23
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_base_neg2pos` is a English model originally trained by ggallipoli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_base_neg2pos_en_5.5.1_3.0_1737634820976.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_base_neg2pos_en_5.5.1_3.0_1737634820976.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_base_neg2pos","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_base_neg2pos", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_base_neg2pos|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|927.0 MB|
+
+## References
+
+https://huggingface.co/ggallipoli/t5-base_neg2pos
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-t5_base_neg2pos_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-t5_base_neg2pos_pipeline_en.md
new file mode 100644
index 00000000000000..f7034d3d573d9e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-t5_base_neg2pos_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_base_neg2pos_pipeline pipeline T5Transformer from ggallipoli
+author: John Snow Labs
+name: t5_base_neg2pos_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_base_neg2pos_pipeline` is a English model originally trained by ggallipoli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_base_neg2pos_pipeline_en_5.5.1_3.0_1737634869170.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_base_neg2pos_pipeline_en_5.5.1_3.0_1737634869170.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_base_neg2pos_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_base_neg2pos_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_base_neg2pos_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|927.0 MB|
+
+## References
+
+https://huggingface.co/ggallipoli/t5-base_neg2pos
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-t5_data_reasoning_en.md b/docs/_posts/ahmedlone127/2025-01-23-t5_data_reasoning_en.md
new file mode 100644
index 00000000000000..c27da73deae9cd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-t5_data_reasoning_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_data_reasoning T5Transformer from Mr-Vicky-01
+author: John Snow Labs
+name: t5_data_reasoning
+date: 2025-01-23
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_data_reasoning` is a English model originally trained by Mr-Vicky-01.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_data_reasoning_en_5.5.1_3.0_1737634321454.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_data_reasoning_en_5.5.1_3.0_1737634321454.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_data_reasoning","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_data_reasoning", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_data_reasoning|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|349.7 MB|
+
+## References
+
+https://huggingface.co/Mr-Vicky-01/T5-data-reasoning
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-t5_data_reasoning_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-t5_data_reasoning_pipeline_en.md
new file mode 100644
index 00000000000000..e91ad12bde80d5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-t5_data_reasoning_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_data_reasoning_pipeline pipeline T5Transformer from Mr-Vicky-01
+author: John Snow Labs
+name: t5_data_reasoning_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_data_reasoning_pipeline` is a English model originally trained by Mr-Vicky-01.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_data_reasoning_pipeline_en_5.5.1_3.0_1737634340231.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_data_reasoning_pipeline_en_5.5.1_3.0_1737634340231.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_data_reasoning_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_data_reasoning_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_data_reasoning_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|349.7 MB|
+
+## References
+
+https://huggingface.co/Mr-Vicky-01/T5-data-reasoning
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-t5_large_search_query_generation_en.md b/docs/_posts/ahmedlone127/2025-01-23-t5_large_search_query_generation_en.md
new file mode 100644
index 00000000000000..a2b2425b340c44
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-t5_large_search_query_generation_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_large_search_query_generation T5Transformer from 1rsh
+author: John Snow Labs
+name: t5_large_search_query_generation
+date: 2025-01-23
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_large_search_query_generation` is a English model originally trained by 1rsh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_large_search_query_generation_en_5.5.1_3.0_1737635209987.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_large_search_query_generation_en_5.5.1_3.0_1737635209987.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_large_search_query_generation","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_large_search_query_generation", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_large_search_query_generation|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|2.9 GB|
+
+## References
+
+https://huggingface.co/1rsh/t5-large-search-query-generation
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-t5_large_search_query_generation_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-t5_large_search_query_generation_pipeline_en.md
new file mode 100644
index 00000000000000..cf8f2e62efba8b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-t5_large_search_query_generation_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_large_search_query_generation_pipeline pipeline T5Transformer from 1rsh
+author: John Snow Labs
+name: t5_large_search_query_generation_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_large_search_query_generation_pipeline` is a English model originally trained by 1rsh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_large_search_query_generation_pipeline_en_5.5.1_3.0_1737635351088.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_large_search_query_generation_pipeline_en_5.5.1_3.0_1737635351088.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_large_search_query_generation_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_large_search_query_generation_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_large_search_query_generation_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|2.9 GB|
+
+## References
+
+https://huggingface.co/1rsh/t5-large-search-query-generation
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-t5_ryusangwon_en.md b/docs/_posts/ahmedlone127/2025-01-23-t5_ryusangwon_en.md
new file mode 100644
index 00000000000000..487994ec41c8f0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-t5_ryusangwon_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_ryusangwon T5Transformer from ryusangwon
+author: John Snow Labs
+name: t5_ryusangwon
+date: 2025-01-23
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_ryusangwon` is a English model originally trained by ryusangwon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_ryusangwon_en_5.5.1_3.0_1737636212552.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_ryusangwon_en_5.5.1_3.0_1737636212552.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_ryusangwon","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_ryusangwon", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_ryusangwon|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|2.9 GB|
+
+## References
+
+https://huggingface.co/ryusangwon/t5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-t5_ryusangwon_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-t5_ryusangwon_pipeline_en.md
new file mode 100644
index 00000000000000..c673659440f9ef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-t5_ryusangwon_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_ryusangwon_pipeline pipeline T5Transformer from ryusangwon
+author: John Snow Labs
+name: t5_ryusangwon_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_ryusangwon_pipeline` is a English model originally trained by ryusangwon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_ryusangwon_pipeline_en_5.5.1_3.0_1737636349443.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_ryusangwon_pipeline_en_5.5.1_3.0_1737636349443.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_ryusangwon_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_ryusangwon_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_ryusangwon_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|2.9 GB|
+
+## References
+
+https://huggingface.co/ryusangwon/t5
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-t5_small_fine_tuned_gigaword_en.md b/docs/_posts/ahmedlone127/2025-01-23-t5_small_fine_tuned_gigaword_en.md
new file mode 100644
index 00000000000000..10de00126921df
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-t5_small_fine_tuned_gigaword_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_small_fine_tuned_gigaword T5Transformer from BRUNOKRISTI
+author: John Snow Labs
+name: t5_small_fine_tuned_gigaword
+date: 2025-01-23
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_fine_tuned_gigaword` is a English model originally trained by BRUNOKRISTI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_fine_tuned_gigaword_en_5.5.1_3.0_1737634696902.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_fine_tuned_gigaword_en_5.5.1_3.0_1737634696902.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_small_fine_tuned_gigaword","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_small_fine_tuned_gigaword", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_fine_tuned_gigaword|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|287.6 MB|
+
+## References
+
+https://huggingface.co/BRUNOKRISTI/t5-small-fine-tuned-gigaword
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-t5_small_fine_tuned_gigaword_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-t5_small_fine_tuned_gigaword_pipeline_en.md
new file mode 100644
index 00000000000000..7b1d5488c1e221
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-t5_small_fine_tuned_gigaword_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_small_fine_tuned_gigaword_pipeline pipeline T5Transformer from BRUNOKRISTI
+author: John Snow Labs
+name: t5_small_fine_tuned_gigaword_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_fine_tuned_gigaword_pipeline` is a English model originally trained by BRUNOKRISTI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_fine_tuned_gigaword_pipeline_en_5.5.1_3.0_1737634712267.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_fine_tuned_gigaword_pipeline_en_5.5.1_3.0_1737634712267.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_small_fine_tuned_gigaword_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_small_fine_tuned_gigaword_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_fine_tuned_gigaword_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|287.6 MB|
+
+## References
+
+https://huggingface.co/BRUNOKRISTI/t5-small-fine-tuned-gigaword
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-t5_small_finetuned_ant3wan95_en.md b/docs/_posts/ahmedlone127/2025-01-23-t5_small_finetuned_ant3wan95_en.md
new file mode 100644
index 00000000000000..245736faa6bf2d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-t5_small_finetuned_ant3wan95_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_small_finetuned_ant3wan95 T5Transformer from Ant3wan95
+author: John Snow Labs
+name: t5_small_finetuned_ant3wan95
+date: 2025-01-23
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_finetuned_ant3wan95` is a English model originally trained by Ant3wan95.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_finetuned_ant3wan95_en_5.5.1_3.0_1737634909106.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_finetuned_ant3wan95_en_5.5.1_3.0_1737634909106.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_small_finetuned_ant3wan95","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_small_finetuned_ant3wan95", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_finetuned_ant3wan95|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|268.4 MB|
+
+## References
+
+https://huggingface.co/Ant3wan95/t5_small_finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-t5_small_finetuned_ant3wan95_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-t5_small_finetuned_ant3wan95_pipeline_en.md
new file mode 100644
index 00000000000000..f2eb0b497615c7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-t5_small_finetuned_ant3wan95_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_small_finetuned_ant3wan95_pipeline pipeline T5Transformer from Ant3wan95
+author: John Snow Labs
+name: t5_small_finetuned_ant3wan95_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_finetuned_ant3wan95_pipeline` is a English model originally trained by Ant3wan95.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_finetuned_ant3wan95_pipeline_en_5.5.1_3.0_1737634927903.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_finetuned_ant3wan95_pipeline_en_5.5.1_3.0_1737634927903.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_small_finetuned_ant3wan95_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_small_finetuned_ant3wan95_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_finetuned_ant3wan95_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|268.4 MB|
+
+## References
+
+https://huggingface.co/Ant3wan95/t5_small_finetuned
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-t5_small_finetuned_xsum_ccarvajal_reyes_en.md b/docs/_posts/ahmedlone127/2025-01-23-t5_small_finetuned_xsum_ccarvajal_reyes_en.md
new file mode 100644
index 00000000000000..a39e512589a356
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-t5_small_finetuned_xsum_ccarvajal_reyes_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_small_finetuned_xsum_ccarvajal_reyes T5Transformer from ccarvajal-reyes
+author: John Snow Labs
+name: t5_small_finetuned_xsum_ccarvajal_reyes
+date: 2025-01-23
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_finetuned_xsum_ccarvajal_reyes` is a English model originally trained by ccarvajal-reyes.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_finetuned_xsum_ccarvajal_reyes_en_5.5.1_3.0_1737633671866.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_finetuned_xsum_ccarvajal_reyes_en_5.5.1_3.0_1737633671866.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_small_finetuned_xsum_ccarvajal_reyes","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_small_finetuned_xsum_ccarvajal_reyes", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_finetuned_xsum_ccarvajal_reyes|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|284.9 MB|
+
+## References
+
+https://huggingface.co/ccarvajal-reyes/t5-small-finetuned-xsum
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-t5_small_finetuned_xsum_ccarvajal_reyes_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-t5_small_finetuned_xsum_ccarvajal_reyes_pipeline_en.md
new file mode 100644
index 00000000000000..8720e418e34ce0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-t5_small_finetuned_xsum_ccarvajal_reyes_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_small_finetuned_xsum_ccarvajal_reyes_pipeline pipeline T5Transformer from ccarvajal-reyes
+author: John Snow Labs
+name: t5_small_finetuned_xsum_ccarvajal_reyes_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_finetuned_xsum_ccarvajal_reyes_pipeline` is a English model originally trained by ccarvajal-reyes.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_finetuned_xsum_ccarvajal_reyes_pipeline_en_5.5.1_3.0_1737633687189.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_finetuned_xsum_ccarvajal_reyes_pipeline_en_5.5.1_3.0_1737633687189.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_small_finetuned_xsum_ccarvajal_reyes_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_small_finetuned_xsum_ccarvajal_reyes_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_finetuned_xsum_ccarvajal_reyes_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|284.9 MB|
+
+## References
+
+https://huggingface.co/ccarvajal-reyes/t5-small-finetuned-xsum
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-t5_small_squad_qg_v2_en.md b/docs/_posts/ahmedlone127/2025-01-23-t5_small_squad_qg_v2_en.md
new file mode 100644
index 00000000000000..3674af2385b686
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-t5_small_squad_qg_v2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_small_squad_qg_v2 T5Transformer from EaindraKyaw
+author: John Snow Labs
+name: t5_small_squad_qg_v2
+date: 2025-01-23
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_squad_qg_v2` is a English model originally trained by EaindraKyaw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_squad_qg_v2_en_5.5.1_3.0_1737633689251.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_squad_qg_v2_en_5.5.1_3.0_1737633689251.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_small_squad_qg_v2","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_small_squad_qg_v2", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_squad_qg_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|148.0 MB|
+
+## References
+
+https://huggingface.co/EaindraKyaw/t5-small-squad-qg-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-t5_small_squad_qg_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-t5_small_squad_qg_v2_pipeline_en.md
new file mode 100644
index 00000000000000..606fbebb7a7fdd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-t5_small_squad_qg_v2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_small_squad_qg_v2_pipeline pipeline T5Transformer from EaindraKyaw
+author: John Snow Labs
+name: t5_small_squad_qg_v2_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_squad_qg_v2_pipeline` is a English model originally trained by EaindraKyaw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_squad_qg_v2_pipeline_en_5.5.1_3.0_1737633742187.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_squad_qg_v2_pipeline_en_5.5.1_3.0_1737633742187.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_small_squad_qg_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_small_squad_qg_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_squad_qg_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|148.0 MB|
+
+## References
+
+https://huggingface.co/EaindraKyaw/t5-small-squad-qg-v2
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-tags_gen_t5_v1_en.md b/docs/_posts/ahmedlone127/2025-01-23-tags_gen_t5_v1_en.md
new file mode 100644
index 00000000000000..594c950e30415a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-tags_gen_t5_v1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English tags_gen_t5_v1 T5Transformer from Spyphy
+author: John Snow Labs
+name: tags_gen_t5_v1
+date: 2025-01-23
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tags_gen_t5_v1` is a English model originally trained by Spyphy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tags_gen_t5_v1_en_5.5.1_3.0_1737635303061.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tags_gen_t5_v1_en_5.5.1_3.0_1737635303061.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("tags_gen_t5_v1","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("tags_gen_t5_v1", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tags_gen_t5_v1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|923.8 MB|
+
+## References
+
+https://huggingface.co/Spyphy/tags-gen-t5-v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-tags_gen_t5_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-tags_gen_t5_v1_pipeline_en.md
new file mode 100644
index 00000000000000..51cabb8dc2a80a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-tags_gen_t5_v1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English tags_gen_t5_v1_pipeline pipeline T5Transformer from Spyphy
+author: John Snow Labs
+name: tags_gen_t5_v1_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tags_gen_t5_v1_pipeline` is a English model originally trained by Spyphy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tags_gen_t5_v1_pipeline_en_5.5.1_3.0_1737635351557.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tags_gen_t5_v1_pipeline_en_5.5.1_3.0_1737635351557.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("tags_gen_t5_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("tags_gen_t5_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tags_gen_t5_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|923.8 MB|
+
+## References
+
+https://huggingface.co/Spyphy/tags-gen-t5-v1
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-td7_virtual_assist_en.md b/docs/_posts/ahmedlone127/2025-01-23-td7_virtual_assist_en.md
new file mode 100644
index 00000000000000..70529aa1f5c2d0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-td7_virtual_assist_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English td7_virtual_assist DistilBertForTokenClassification from yahiafhl
+author: John Snow Labs
+name: td7_virtual_assist
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`td7_virtual_assist` is a English model originally trained by yahiafhl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/td7_virtual_assist_en_5.5.1_3.0_1737627952599.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/td7_virtual_assist_en_5.5.1_3.0_1737627952599.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("td7_virtual_assist","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("td7_virtual_assist", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|td7_virtual_assist|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/yahiafhl/td7_virtual_assist
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-td7_virtual_assist_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-td7_virtual_assist_pipeline_en.md
new file mode 100644
index 00000000000000..d9feb15b7afb09
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-td7_virtual_assist_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English td7_virtual_assist_pipeline pipeline DistilBertForTokenClassification from yahiafhl
+author: John Snow Labs
+name: td7_virtual_assist_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`td7_virtual_assist_pipeline` is a English model originally trained by yahiafhl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/td7_virtual_assist_pipeline_en_5.5.1_3.0_1737627965731.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/td7_virtual_assist_pipeline_en_5.5.1_3.0_1737627965731.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("td7_virtual_assist_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("td7_virtual_assist_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|td7_virtual_assist_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/yahiafhl/td7_virtual_assist
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-techdistillbert_en.md b/docs/_posts/ahmedlone127/2025-01-23-techdistillbert_en.md
new file mode 100644
index 00000000000000..b09c15f75dc944
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-techdistillbert_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English techdistillbert DistilBertForQuestionAnswering from sahithya20
+author: John Snow Labs
+name: techdistillbert
+date: 2025-01-23
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`techdistillbert` is a English model originally trained by sahithya20.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/techdistillbert_en_5.5.1_3.0_1737661119871.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/techdistillbert_en_5.5.1_3.0_1737661119871.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("techdistillbert","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("techdistillbert", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|techdistillbert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/sahithya20/techdistillbert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-techdistillbert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-techdistillbert_pipeline_en.md
new file mode 100644
index 00000000000000..96d91c8d3c6ad9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-techdistillbert_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English techdistillbert_pipeline pipeline DistilBertForQuestionAnswering from sahithya20
+author: John Snow Labs
+name: techdistillbert_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`techdistillbert_pipeline` is a English model originally trained by sahithya20.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/techdistillbert_pipeline_en_5.5.1_3.0_1737661133833.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/techdistillbert_pipeline_en_5.5.1_3.0_1737661133833.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("techdistillbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("techdistillbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|techdistillbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/sahithya20/techdistillbert
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-test123test123_en.md b/docs/_posts/ahmedlone127/2025-01-23-test123test123_en.md
new file mode 100644
index 00000000000000..b9152f6d3e979f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-test123test123_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English test123test123 DistilBertEmbeddings from fhzh123
+author: John Snow Labs
+name: test123test123
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test123test123` is a English model originally trained by fhzh123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test123test123_en_5.5.1_3.0_1737663302092.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test123test123_en_5.5.1_3.0_1737663302092.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("test123test123","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("test123test123","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test123test123|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/fhzh123/test123test123
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-test123test123_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-test123test123_pipeline_en.md
new file mode 100644
index 00000000000000..a9ac6a0ea77e00
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-test123test123_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English test123test123_pipeline pipeline DistilBertEmbeddings from fhzh123
+author: John Snow Labs
+name: test123test123_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test123test123_pipeline` is a English model originally trained by fhzh123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test123test123_pipeline_en_5.5.1_3.0_1737663317271.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test123test123_pipeline_en_5.5.1_3.0_1737663317271.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("test123test123_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("test123test123_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test123test123_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/fhzh123/test123test123
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-test_bert_hosting_en.md b/docs/_posts/ahmedlone127/2025-01-23-test_bert_hosting_en.md
new file mode 100644
index 00000000000000..7fa4b3c89f1c58
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-test_bert_hosting_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English test_bert_hosting CamemBertForSequenceClassification from PetchP
+author: John Snow Labs
+name: test_bert_hosting
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, camembert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_bert_hosting` is a English model originally trained by PetchP.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_bert_hosting_en_5.5.1_3.0_1737628710308.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_bert_hosting_en_5.5.1_3.0_1737628710308.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = CamemBertForSequenceClassification.pretrained("test_bert_hosting","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = CamemBertForSequenceClassification.pretrained("test_bert_hosting", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_bert_hosting|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/PetchP/test_bert_hosting
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-test_bert_hosting_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-test_bert_hosting_pipeline_en.md
new file mode 100644
index 00000000000000..34408dc734e9da
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-test_bert_hosting_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English test_bert_hosting_pipeline pipeline CamemBertForSequenceClassification from PetchP
+author: John Snow Labs
+name: test_bert_hosting_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_bert_hosting_pipeline` is a English model originally trained by PetchP.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_bert_hosting_pipeline_en_5.5.1_3.0_1737628762849.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_bert_hosting_pipeline_en_5.5.1_3.0_1737628762849.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("test_bert_hosting_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("test_bert_hosting_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_bert_hosting_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/PetchP/test_bert_hosting
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-testing22_mt5_ha2zh_translation_en.md b/docs/_posts/ahmedlone127/2025-01-23-testing22_mt5_ha2zh_translation_en.md
new file mode 100644
index 00000000000000..f34bc3bc6dd01f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-testing22_mt5_ha2zh_translation_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English testing22_mt5_ha2zh_translation T5Transformer from Kumshe
+author: John Snow Labs
+name: testing22_mt5_ha2zh_translation
+date: 2025-01-23
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`testing22_mt5_ha2zh_translation` is a English model originally trained by Kumshe.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/testing22_mt5_ha2zh_translation_en_5.5.1_3.0_1737634485308.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/testing22_mt5_ha2zh_translation_en_5.5.1_3.0_1737634485308.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("testing22_mt5_ha2zh_translation","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("testing22_mt5_ha2zh_translation", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|testing22_mt5_ha2zh_translation|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/Kumshe/testing22_mt5-ha2zh-translation
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-testing22_mt5_ha2zh_translation_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-testing22_mt5_ha2zh_translation_pipeline_en.md
new file mode 100644
index 00000000000000..772ae63024860b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-testing22_mt5_ha2zh_translation_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English testing22_mt5_ha2zh_translation_pipeline pipeline T5Transformer from Kumshe
+author: John Snow Labs
+name: testing22_mt5_ha2zh_translation_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`testing22_mt5_ha2zh_translation_pipeline` is a English model originally trained by Kumshe.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/testing22_mt5_ha2zh_translation_pipeline_en_5.5.1_3.0_1737634659465.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/testing22_mt5_ha2zh_translation_pipeline_en_5.5.1_3.0_1737634659465.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("testing22_mt5_ha2zh_translation_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("testing22_mt5_ha2zh_translation_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|testing22_mt5_ha2zh_translation_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/Kumshe/testing22_mt5-ha2zh-translation
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-text_classification_uzummarket_pipeline_uz.md b/docs/_posts/ahmedlone127/2025-01-23-text_classification_uzummarket_pipeline_uz.md
new file mode 100644
index 00000000000000..045444c2a8e62d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-text_classification_uzummarket_pipeline_uz.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Uzbek text_classification_uzummarket_pipeline pipeline XlmRoBertaForSequenceClassification from fanaf91318
+author: John Snow Labs
+name: text_classification_uzummarket_pipeline
+date: 2025-01-23
+tags: [uz, open_source, pipeline, onnx]
+task: Text Classification
+language: uz
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`text_classification_uzummarket_pipeline` is a Uzbek model originally trained by fanaf91318.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/text_classification_uzummarket_pipeline_uz_5.5.1_3.0_1737653954503.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/text_classification_uzummarket_pipeline_uz_5.5.1_3.0_1737653954503.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("text_classification_uzummarket_pipeline", lang = "uz")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("text_classification_uzummarket_pipeline", lang = "uz")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|text_classification_uzummarket_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|uz|
+|Size:|825.5 MB|
+
+## References
+
+https://huggingface.co/fanaf91318/text-classification-uzummarket
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-text_classification_uzummarket_uz.md b/docs/_posts/ahmedlone127/2025-01-23-text_classification_uzummarket_uz.md
new file mode 100644
index 00000000000000..bc2f1979b7053c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-text_classification_uzummarket_uz.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Uzbek text_classification_uzummarket XlmRoBertaForSequenceClassification from fanaf91318
+author: John Snow Labs
+name: text_classification_uzummarket
+date: 2025-01-23
+tags: [uz, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: uz
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`text_classification_uzummarket` is a Uzbek model originally trained by fanaf91318.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/text_classification_uzummarket_uz_5.5.1_3.0_1737653829995.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/text_classification_uzummarket_uz_5.5.1_3.0_1737653829995.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("text_classification_uzummarket","uz") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("text_classification_uzummarket", "uz")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|text_classification_uzummarket|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|uz|
+|Size:|825.4 MB|
+
+## References
+
+https://huggingface.co/fanaf91318/text-classification-uzummarket
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-text_summarization_vishnun0027_en.md b/docs/_posts/ahmedlone127/2025-01-23-text_summarization_vishnun0027_en.md
new file mode 100644
index 00000000000000..879dd24d7f9d79
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-text_summarization_vishnun0027_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English text_summarization_vishnun0027 T5Transformer from vishnun0027
+author: John Snow Labs
+name: text_summarization_vishnun0027
+date: 2025-01-23
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`text_summarization_vishnun0027` is a English model originally trained by vishnun0027.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/text_summarization_vishnun0027_en_5.5.1_3.0_1737634912856.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/text_summarization_vishnun0027_en_5.5.1_3.0_1737634912856.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("text_summarization_vishnun0027","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("text_summarization_vishnun0027", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|text_summarization_vishnun0027|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|282.4 MB|
+
+## References
+
+https://huggingface.co/vishnun0027/Text_Summarization
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-text_summarization_vishnun0027_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-text_summarization_vishnun0027_pipeline_en.md
new file mode 100644
index 00000000000000..d0ca860263e439
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-text_summarization_vishnun0027_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English text_summarization_vishnun0027_pipeline pipeline T5Transformer from vishnun0027
+author: John Snow Labs
+name: text_summarization_vishnun0027_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`text_summarization_vishnun0027_pipeline` is a English model originally trained by vishnun0027.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/text_summarization_vishnun0027_pipeline_en_5.5.1_3.0_1737634929202.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/text_summarization_vishnun0027_pipeline_en_5.5.1_3.0_1737634929202.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("text_summarization_vishnun0027_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("text_summarization_vishnun0027_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|text_summarization_vishnun0027_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|282.4 MB|
+
+## References
+
+https://huggingface.co/vishnun0027/Text_Summarization
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-theme_classification_en.md b/docs/_posts/ahmedlone127/2025-01-23-theme_classification_en.md
new file mode 100644
index 00000000000000..58a100998a6e3b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-theme_classification_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English theme_classification BartForZeroShotClassification from eleldar
+author: John Snow Labs
+name: theme_classification
+date: 2025-01-23
+tags: [en, open_source, onnx, zero_shot, bart]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BartForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`theme_classification` is a English model originally trained by eleldar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/theme_classification_en_5.5.1_3.0_1737640041696.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/theme_classification_en_5.5.1_3.0_1737640041696.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+zeroShotClassifier  = BartForZeroShotClassification.pretrained("theme_classification","en") \
+     .setInputCols(["document","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, zeroShotClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val zeroShotClassifier  = BartForZeroShotClassification.pretrained("theme_classification", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, zeroShotClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|theme_classification|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|975.7 MB|
+
+## References
+
+https://huggingface.co/eleldar/theme-classification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-theme_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-theme_classification_pipeline_en.md
new file mode 100644
index 00000000000000..0f4620c714ef1c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-theme_classification_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English theme_classification_pipeline pipeline BartForZeroShotClassification from eleldar
+author: John Snow Labs
+name: theme_classification_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`theme_classification_pipeline` is a English model originally trained by eleldar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/theme_classification_pipeline_en_5.5.1_3.0_1737640332050.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/theme_classification_pipeline_en_5.5.1_3.0_1737640332050.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("theme_classification_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("theme_classification_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|theme_classification_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|975.7 MB|
+
+## References
+
+https://huggingface.co/eleldar/theme-classification
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BartForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-trase_prm_en.md b/docs/_posts/ahmedlone127/2025-01-23-trase_prm_en.md
new file mode 100644
index 00000000000000..696dc9db8b3cf3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-trase_prm_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English trase_prm DistilBertForTokenClassification from MikeMpapa
+author: John Snow Labs
+name: trase_prm
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`trase_prm` is a English model originally trained by MikeMpapa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/trase_prm_en_5.5.1_3.0_1737627099255.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/trase_prm_en_5.5.1_3.0_1737627099255.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("trase_prm","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("trase_prm", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|trase_prm|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/MikeMpapa/trase-prm
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-trase_prm_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-trase_prm_pipeline_en.md
new file mode 100644
index 00000000000000..2ea45b3410b79d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-trase_prm_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English trase_prm_pipeline pipeline DistilBertForTokenClassification from MikeMpapa
+author: John Snow Labs
+name: trase_prm_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`trase_prm_pipeline` is a English model originally trained by MikeMpapa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/trase_prm_pipeline_en_5.5.1_3.0_1737627112637.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/trase_prm_pipeline_en_5.5.1_3.0_1737627112637.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("trase_prm_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("trase_prm_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|trase_prm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/MikeMpapa/trase-prm
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-turkish_bert_xquad_en.md b/docs/_posts/ahmedlone127/2025-01-23-turkish_bert_xquad_en.md
new file mode 100644
index 00000000000000..0f22ba116f08b2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-turkish_bert_xquad_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English turkish_bert_xquad DistilBertForQuestionAnswering from muratsimsek003
+author: John Snow Labs
+name: turkish_bert_xquad
+date: 2025-01-23
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`turkish_bert_xquad` is a English model originally trained by muratsimsek003.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/turkish_bert_xquad_en_5.5.1_3.0_1737660977633.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/turkish_bert_xquad_en_5.5.1_3.0_1737660977633.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("turkish_bert_xquad","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("turkish_bert_xquad", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|turkish_bert_xquad|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/muratsimsek003/turkish-bert-xquad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-turkish_bert_xquad_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-turkish_bert_xquad_pipeline_en.md
new file mode 100644
index 00000000000000..e65e9cf90c862f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-turkish_bert_xquad_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English turkish_bert_xquad_pipeline pipeline DistilBertForQuestionAnswering from muratsimsek003
+author: John Snow Labs
+name: turkish_bert_xquad_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`turkish_bert_xquad_pipeline` is a English model originally trained by muratsimsek003.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/turkish_bert_xquad_pipeline_en_5.5.1_3.0_1737660995181.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/turkish_bert_xquad_pipeline_en_5.5.1_3.0_1737660995181.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("turkish_bert_xquad_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("turkish_bert_xquad_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|turkish_bert_xquad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/muratsimsek003/turkish-bert-xquad
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-turkish_zeroshot_large_pipeline_tr.md b/docs/_posts/ahmedlone127/2025-01-23-turkish_zeroshot_large_pipeline_tr.md
new file mode 100644
index 00000000000000..8081f9aae30fc0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-turkish_zeroshot_large_pipeline_tr.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Turkish turkish_zeroshot_large_pipeline pipeline BertForZeroShotClassification from kaixkhazaki
+author: John Snow Labs
+name: turkish_zeroshot_large_pipeline
+date: 2025-01-23
+tags: [tr, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: tr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`turkish_zeroshot_large_pipeline` is a Turkish model originally trained by kaixkhazaki.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/turkish_zeroshot_large_pipeline_tr_5.5.1_3.0_1737640862080.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/turkish_zeroshot_large_pipeline_tr_5.5.1_3.0_1737640862080.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("turkish_zeroshot_large_pipeline", lang = "tr")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("turkish_zeroshot_large_pipeline", lang = "tr")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|turkish_zeroshot_large_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|tr|
+|Size:|689.4 MB|
+
+## References
+
+https://huggingface.co/kaixkhazaki/turkish-zeroshot-large
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-turkish_zeroshot_large_tr.md b/docs/_posts/ahmedlone127/2025-01-23-turkish_zeroshot_large_tr.md
new file mode 100644
index 00000000000000..1d6583f4174de9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-turkish_zeroshot_large_tr.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Turkish turkish_zeroshot_large BertForZeroShotClassification from kaixkhazaki
+author: John Snow Labs
+name: turkish_zeroshot_large
+date: 2025-01-23
+tags: [tr, open_source, onnx, zero_shot, bert]
+task: Zero-Shot Classification
+language: tr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`turkish_zeroshot_large` is a Turkish model originally trained by kaixkhazaki.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/turkish_zeroshot_large_tr_5.5.1_3.0_1737640825860.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/turkish_zeroshot_large_tr_5.5.1_3.0_1737640825860.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+zeroShotClassifier  = BertForZeroShotClassification.pretrained("turkish_zeroshot_large","tr") \
+     .setInputCols(["document","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, zeroShotClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val zeroShotClassifier  = BertForZeroShotClassification.pretrained("turkish_zeroshot_large", "tr")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, zeroShotClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|turkish_zeroshot_large|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|tr|
+|Size:|689.4 MB|
+
+## References
+
+https://huggingface.co/kaixkhazaki/turkish-zeroshot-large
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-turkish_zeroshot_pipeline_tr.md b/docs/_posts/ahmedlone127/2025-01-23-turkish_zeroshot_pipeline_tr.md
new file mode 100644
index 00000000000000..30c6a17f2168f3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-turkish_zeroshot_pipeline_tr.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Turkish turkish_zeroshot_pipeline pipeline BertForZeroShotClassification from kaixkhazaki
+author: John Snow Labs
+name: turkish_zeroshot_pipeline
+date: 2025-01-23
+tags: [tr, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: tr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`turkish_zeroshot_pipeline` is a Turkish model originally trained by kaixkhazaki.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/turkish_zeroshot_pipeline_tr_5.5.1_3.0_1737640803812.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/turkish_zeroshot_pipeline_tr_5.5.1_3.0_1737640803812.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("turkish_zeroshot_pipeline", lang = "tr")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("turkish_zeroshot_pipeline", lang = "tr")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|turkish_zeroshot_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|tr|
+|Size:|412.3 MB|
+
+## References
+
+https://huggingface.co/kaixkhazaki/turkish-zeroshot
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-turkish_zeroshot_tr.md b/docs/_posts/ahmedlone127/2025-01-23-turkish_zeroshot_tr.md
new file mode 100644
index 00000000000000..35177463258579
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-turkish_zeroshot_tr.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Turkish turkish_zeroshot BertForZeroShotClassification from kaixkhazaki
+author: John Snow Labs
+name: turkish_zeroshot
+date: 2025-01-23
+tags: [tr, open_source, onnx, zero_shot, bert]
+task: Zero-Shot Classification
+language: tr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`turkish_zeroshot` is a Turkish model originally trained by kaixkhazaki.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/turkish_zeroshot_tr_5.5.1_3.0_1737640781323.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/turkish_zeroshot_tr_5.5.1_3.0_1737640781323.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+zeroShotClassifier  = BertForZeroShotClassification.pretrained("turkish_zeroshot","tr") \
+     .setInputCols(["document","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, zeroShotClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val zeroShotClassifier  = BertForZeroShotClassification.pretrained("turkish_zeroshot", "tr")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, zeroShotClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|turkish_zeroshot|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|tr|
+|Size:|412.3 MB|
+
+## References
+
+https://huggingface.co/kaixkhazaki/turkish-zeroshot
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-typhoon2_safety_preview_pipeline_th.md b/docs/_posts/ahmedlone127/2025-01-23-typhoon2_safety_preview_pipeline_th.md
new file mode 100644
index 00000000000000..aed432dbd1dc38
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-typhoon2_safety_preview_pipeline_th.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Thai typhoon2_safety_preview_pipeline pipeline DeBertaForSequenceClassification from scb10x
+author: John Snow Labs
+name: typhoon2_safety_preview_pipeline
+date: 2025-01-23
+tags: [th, open_source, pipeline, onnx]
+task: Text Classification
+language: th
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`typhoon2_safety_preview_pipeline` is a Thai model originally trained by scb10x.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/typhoon2_safety_preview_pipeline_th_5.5.1_3.0_1737647846733.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/typhoon2_safety_preview_pipeline_th_5.5.1_3.0_1737647846733.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("typhoon2_safety_preview_pipeline", lang = "th")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("typhoon2_safety_preview_pipeline", lang = "th")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|typhoon2_safety_preview_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|th|
+|Size:|921.6 MB|
+
+## References
+
+https://huggingface.co/scb10x/typhoon2-safety-preview
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-typhoon2_safety_preview_th.md b/docs/_posts/ahmedlone127/2025-01-23-typhoon2_safety_preview_th.md
new file mode 100644
index 00000000000000..3b0781ab3afd3b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-typhoon2_safety_preview_th.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Thai typhoon2_safety_preview DeBertaForSequenceClassification from scb10x
+author: John Snow Labs
+name: typhoon2_safety_preview
+date: 2025-01-23
+tags: [th, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: th
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`typhoon2_safety_preview` is a Thai model originally trained by scb10x.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/typhoon2_safety_preview_th_5.5.1_3.0_1737647777050.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/typhoon2_safety_preview_th_5.5.1_3.0_1737647777050.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("typhoon2_safety_preview","th") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("typhoon2_safety_preview", "th")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|typhoon2_safety_preview|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|th|
+|Size:|921.6 MB|
+
+## References
+
+https://huggingface.co/scb10x/typhoon2-safety-preview
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-vihos1_en.md b/docs/_posts/ahmedlone127/2025-01-23-vihos1_en.md
new file mode 100644
index 00000000000000..790473bbacf95a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-vihos1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vihos1 XlmRoBertaForTokenClassification from mecoaoge2
+author: John Snow Labs
+name: vihos1
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vihos1` is a English model originally trained by mecoaoge2.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vihos1_en_5.5.1_3.0_1737673621669.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vihos1_en_5.5.1_3.0_1737673621669.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("vihos1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("vihos1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vihos1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|363.7 MB|
+
+## References
+
+https://huggingface.co/mecoaoge2/ViHOS1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-vihos1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-vihos1_pipeline_en.md
new file mode 100644
index 00000000000000..49ec4c9fdfca20
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-vihos1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English vihos1_pipeline pipeline XlmRoBertaForTokenClassification from mecoaoge2
+author: John Snow Labs
+name: vihos1_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vihos1_pipeline` is a English model originally trained by mecoaoge2.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vihos1_pipeline_en_5.5.1_3.0_1737673641919.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vihos1_pipeline_en_5.5.1_3.0_1737673641919.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vihos1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vihos1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vihos1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|363.7 MB|
+
+## References
+
+https://huggingface.co/mecoaoge2/ViHOS1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-weighted_cross_entropy_uniform_minority_weights_en.md b/docs/_posts/ahmedlone127/2025-01-23-weighted_cross_entropy_uniform_minority_weights_en.md
new file mode 100644
index 00000000000000..9ae81ce4cd9d4b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-weighted_cross_entropy_uniform_minority_weights_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English weighted_cross_entropy_uniform_minority_weights DistilBertForTokenClassification from pmpmp74832
+author: John Snow Labs
+name: weighted_cross_entropy_uniform_minority_weights
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`weighted_cross_entropy_uniform_minority_weights` is a English model originally trained by pmpmp74832.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/weighted_cross_entropy_uniform_minority_weights_en_5.5.1_3.0_1737627238141.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/weighted_cross_entropy_uniform_minority_weights_en_5.5.1_3.0_1737627238141.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("weighted_cross_entropy_uniform_minority_weights","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("weighted_cross_entropy_uniform_minority_weights", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|weighted_cross_entropy_uniform_minority_weights|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|329.4 MB|
+
+## References
+
+https://huggingface.co/pmpmp74832/weighted_cross_entropy_uniform_minority_weights
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-weighted_cross_entropy_uniform_minority_weights_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-weighted_cross_entropy_uniform_minority_weights_pipeline_en.md
new file mode 100644
index 00000000000000..6827adb9636102
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-weighted_cross_entropy_uniform_minority_weights_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English weighted_cross_entropy_uniform_minority_weights_pipeline pipeline DistilBertForTokenClassification from pmpmp74832
+author: John Snow Labs
+name: weighted_cross_entropy_uniform_minority_weights_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`weighted_cross_entropy_uniform_minority_weights_pipeline` is a English model originally trained by pmpmp74832.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/weighted_cross_entropy_uniform_minority_weights_pipeline_en_5.5.1_3.0_1737627256616.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/weighted_cross_entropy_uniform_minority_weights_pipeline_en_5.5.1_3.0_1737627256616.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("weighted_cross_entropy_uniform_minority_weights_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("weighted_cross_entropy_uniform_minority_weights_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|weighted_cross_entropy_uniform_minority_weights_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|329.4 MB|
+
+## References
+
+https://huggingface.co/pmpmp74832/weighted_cross_entropy_uniform_minority_weights
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-wikirag_turkish_finetuned_en.md b/docs/_posts/ahmedlone127/2025-01-23-wikirag_turkish_finetuned_en.md
new file mode 100644
index 00000000000000..cb9a1d0bcc305c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-wikirag_turkish_finetuned_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English wikirag_turkish_finetuned DistilBertForQuestionAnswering from muratsimsek003
+author: John Snow Labs
+name: wikirag_turkish_finetuned
+date: 2025-01-23
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`wikirag_turkish_finetuned` is a English model originally trained by muratsimsek003.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/wikirag_turkish_finetuned_en_5.5.1_3.0_1737660800903.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/wikirag_turkish_finetuned_en_5.5.1_3.0_1737660800903.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("wikirag_turkish_finetuned","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("wikirag_turkish_finetuned", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|wikirag_turkish_finetuned|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/muratsimsek003/WikiRAG-turkish-finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-wikirag_turkish_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-wikirag_turkish_finetuned_pipeline_en.md
new file mode 100644
index 00000000000000..ff18649739c8d1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-wikirag_turkish_finetuned_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English wikirag_turkish_finetuned_pipeline pipeline DistilBertForQuestionAnswering from muratsimsek003
+author: John Snow Labs
+name: wikirag_turkish_finetuned_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`wikirag_turkish_finetuned_pipeline` is a English model originally trained by muratsimsek003.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/wikirag_turkish_finetuned_pipeline_en_5.5.1_3.0_1737660817134.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/wikirag_turkish_finetuned_pipeline_en_5.5.1_3.0_1737660817134.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("wikirag_turkish_finetuned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("wikirag_turkish_finetuned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|wikirag_turkish_finetuned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/muratsimsek003/WikiRAG-turkish-finetuned
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-withinapps_ndd_mrbs_test_content_en.md b/docs/_posts/ahmedlone127/2025-01-23-withinapps_ndd_mrbs_test_content_en.md
new file mode 100644
index 00000000000000..ee21ceef1f5102
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-withinapps_ndd_mrbs_test_content_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English withinapps_ndd_mrbs_test_content DistilBertForSequenceClassification from lgk03
+author: John Snow Labs
+name: withinapps_ndd_mrbs_test_content
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`withinapps_ndd_mrbs_test_content` is a English model originally trained by lgk03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/withinapps_ndd_mrbs_test_content_en_5.5.1_3.0_1737650142478.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/withinapps_ndd_mrbs_test_content_en_5.5.1_3.0_1737650142478.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("withinapps_ndd_mrbs_test_content","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("withinapps_ndd_mrbs_test_content", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|withinapps_ndd_mrbs_test_content|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/lgk03/WITHINAPPS_NDD-mrbs_test-content
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-withinapps_ndd_mrbs_test_content_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-withinapps_ndd_mrbs_test_content_pipeline_en.md
new file mode 100644
index 00000000000000..22c646dba55f5d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-withinapps_ndd_mrbs_test_content_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English withinapps_ndd_mrbs_test_content_pipeline pipeline DistilBertForSequenceClassification from lgk03
+author: John Snow Labs
+name: withinapps_ndd_mrbs_test_content_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`withinapps_ndd_mrbs_test_content_pipeline` is a English model originally trained by lgk03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/withinapps_ndd_mrbs_test_content_pipeline_en_5.5.1_3.0_1737650158574.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/withinapps_ndd_mrbs_test_content_pipeline_en_5.5.1_3.0_1737650158574.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("withinapps_ndd_mrbs_test_content_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("withinapps_ndd_mrbs_test_content_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|withinapps_ndd_mrbs_test_content_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/lgk03/WITHINAPPS_NDD-mrbs_test-content
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_deletion_multiclass_spanish_masked_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_deletion_multiclass_spanish_masked_en.md
new file mode 100644
index 00000000000000..7cb10bcbf9646a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_deletion_multiclass_spanish_masked_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_deletion_multiclass_spanish_masked XlmRoBertaForSequenceClassification from research-dump
+author: John Snow Labs
+name: xlm_roberta_base_deletion_multiclass_spanish_masked
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_deletion_multiclass_spanish_masked` is a English model originally trained by research-dump.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_deletion_multiclass_spanish_masked_en_5.5.1_3.0_1737652084042.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_deletion_multiclass_spanish_masked_en_5.5.1_3.0_1737652084042.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_deletion_multiclass_spanish_masked","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_deletion_multiclass_spanish_masked", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_deletion_multiclass_spanish_masked|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|790.3 MB|
+
+## References
+
+https://huggingface.co/research-dump/xlm-roberta-base_deletion_multiclass_es_masked
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_deletion_multiclass_spanish_masked_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_deletion_multiclass_spanish_masked_pipeline_en.md
new file mode 100644
index 00000000000000..b80c8768eea7d9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_deletion_multiclass_spanish_masked_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_deletion_multiclass_spanish_masked_pipeline pipeline XlmRoBertaForSequenceClassification from research-dump
+author: John Snow Labs
+name: xlm_roberta_base_deletion_multiclass_spanish_masked_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_deletion_multiclass_spanish_masked_pipeline` is a English model originally trained by research-dump.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_deletion_multiclass_spanish_masked_pipeline_en_5.5.1_3.0_1737652227731.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_deletion_multiclass_spanish_masked_pipeline_en_5.5.1_3.0_1737652227731.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_deletion_multiclass_spanish_masked_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_deletion_multiclass_spanish_masked_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_deletion_multiclass_spanish_masked_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|790.3 MB|
+
+## References
+
+https://huggingface.co/research-dump/xlm-roberta-base_deletion_multiclass_es_masked
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_tweets_finetuned_kinyarwanda_sent3_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_tweets_finetuned_kinyarwanda_sent3_en.md
new file mode 100644
index 00000000000000..06e89a3c2fa92f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_tweets_finetuned_kinyarwanda_sent3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_tweets_finetuned_kinyarwanda_sent3 XlmRoBertaForSequenceClassification from RogerB
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_tweets_finetuned_kinyarwanda_sent3
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_tweets_finetuned_kinyarwanda_sent3` is a English model originally trained by RogerB.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_tweets_finetuned_kinyarwanda_sent3_en_5.5.1_3.0_1737652220614.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_tweets_finetuned_kinyarwanda_sent3_en_5.5.1_3.0_1737652220614.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_tweets_finetuned_kinyarwanda_sent3","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_tweets_finetuned_kinyarwanda_sent3", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_tweets_finetuned_kinyarwanda_sent3|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/RogerB/xlm-roberta-base-finetuned-kinyarwanda-kin-finetuned-kin-tweets-finetuned-kin-sent3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_tweets_finetuned_kinyarwanda_sent3_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_tweets_finetuned_kinyarwanda_sent3_pipeline_en.md
new file mode 100644
index 00000000000000..8603b1cd5bc5a1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_tweets_finetuned_kinyarwanda_sent3_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_tweets_finetuned_kinyarwanda_sent3_pipeline pipeline XlmRoBertaForSequenceClassification from RogerB
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_tweets_finetuned_kinyarwanda_sent3_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_tweets_finetuned_kinyarwanda_sent3_pipeline` is a English model originally trained by RogerB.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_tweets_finetuned_kinyarwanda_sent3_pipeline_en_5.5.1_3.0_1737652282300.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_tweets_finetuned_kinyarwanda_sent3_pipeline_en_5.5.1_3.0_1737652282300.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_tweets_finetuned_kinyarwanda_sent3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_tweets_finetuned_kinyarwanda_sent3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_tweets_finetuned_kinyarwanda_sent3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/RogerB/xlm-roberta-base-finetuned-kinyarwanda-kin-finetuned-kin-tweets-finetuned-kin-sent3
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_all_cogsci13_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_all_cogsci13_en.md
new file mode 100644
index 00000000000000..336e5cc0375e8d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_all_cogsci13_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_cogsci13 XlmRoBertaForTokenClassification from cogsci13
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_cogsci13
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_cogsci13` is a English model originally trained by cogsci13.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_cogsci13_en_5.5.1_3.0_1737675060039.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_cogsci13_en_5.5.1_3.0_1737675060039.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_cogsci13","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_cogsci13", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_cogsci13|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/cogsci13/xlm-roberta-base-finetuned-panx-all
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_all_cogsci13_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_all_cogsci13_pipeline_en.md
new file mode 100644
index 00000000000000..7766559148d0a0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_all_cogsci13_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_cogsci13_pipeline pipeline XlmRoBertaForTokenClassification from cogsci13
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_cogsci13_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_cogsci13_pipeline` is a English model originally trained by cogsci13.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_cogsci13_pipeline_en_5.5.1_3.0_1737675146522.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_cogsci13_pipeline_en_5.5.1_3.0_1737675146522.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_cogsci13_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_cogsci13_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_cogsci13_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/cogsci13/xlm-roberta-base-finetuned-panx-all
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_all_snagmin_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_all_snagmin_en.md
new file mode 100644
index 00000000000000..1697b2a266356a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_all_snagmin_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_snagmin XlmRoBertaForTokenClassification from snagmin
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_snagmin
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_snagmin` is a English model originally trained by snagmin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_snagmin_en_5.5.1_3.0_1737676199531.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_snagmin_en_5.5.1_3.0_1737676199531.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_snagmin","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_snagmin", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_snagmin|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/snagmin/xlm-roberta-base-finetuned-panx-all
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_all_snagmin_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_all_snagmin_pipeline_en.md
new file mode 100644
index 00000000000000..a09a7e57c06375
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_all_snagmin_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_snagmin_pipeline pipeline XlmRoBertaForTokenClassification from snagmin
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_snagmin_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_snagmin_pipeline` is a English model originally trained by snagmin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_snagmin_pipeline_en_5.5.1_3.0_1737676286641.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_snagmin_pipeline_en_5.5.1_3.0_1737676286641.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_snagmin_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_snagmin_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_snagmin_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/snagmin/xlm-roberta-base-finetuned-panx-all
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_all_vaibhavdlights_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_all_vaibhavdlights_en.md
new file mode 100644
index 00000000000000..21e4316f5bf5f2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_all_vaibhavdlights_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_vaibhavdlights XlmRoBertaForTokenClassification from VaibhavdLights
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_vaibhavdlights
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_vaibhavdlights` is a English model originally trained by VaibhavdLights.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_vaibhavdlights_en_5.5.1_3.0_1737676424735.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_vaibhavdlights_en_5.5.1_3.0_1737676424735.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_vaibhavdlights","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_vaibhavdlights", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_vaibhavdlights|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/VaibhavdLights/xlm-roberta-base-finetuned-panx-all
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_all_vaibhavdlights_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_all_vaibhavdlights_pipeline_en.md
new file mode 100644
index 00000000000000..5e80c551e71e00
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_all_vaibhavdlights_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_vaibhavdlights_pipeline pipeline XlmRoBertaForTokenClassification from VaibhavdLights
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_vaibhavdlights_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_vaibhavdlights_pipeline` is a English model originally trained by VaibhavdLights.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_vaibhavdlights_pipeline_en_5.5.1_3.0_1737676512656.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_vaibhavdlights_pipeline_en_5.5.1_3.0_1737676512656.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_vaibhavdlights_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_vaibhavdlights_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_vaibhavdlights_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/VaibhavdLights/xlm-roberta-base-finetuned-panx-all
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_english_do1232_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_english_do1232_en.md
new file mode 100644
index 00000000000000..55ac41dddb5137
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_english_do1232_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_do1232 XlmRoBertaForTokenClassification from do1232
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_do1232
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_do1232` is a English model originally trained by do1232.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_do1232_en_5.5.1_3.0_1737676005985.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_do1232_en_5.5.1_3.0_1737676005985.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_do1232","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_do1232", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_do1232|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/do1232/xlm-roberta-base-finetuned-panx-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_english_do1232_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_english_do1232_pipeline_en.md
new file mode 100644
index 00000000000000..5f4727ed60e7c3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_english_do1232_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_do1232_pipeline pipeline XlmRoBertaForTokenClassification from do1232
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_do1232_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_do1232_pipeline` is a English model originally trained by do1232.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_do1232_pipeline_en_5.5.1_3.0_1737676116737.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_do1232_pipeline_en_5.5.1_3.0_1737676116737.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_do1232_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_do1232_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_do1232_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/do1232/xlm-roberta-base-finetuned-panx-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_english_vaibhavdlights_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_english_vaibhavdlights_en.md
new file mode 100644
index 00000000000000..7fcf6975eda074
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_english_vaibhavdlights_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_vaibhavdlights XlmRoBertaForTokenClassification from VaibhavdLights
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_vaibhavdlights
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_vaibhavdlights` is a English model originally trained by VaibhavdLights.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_vaibhavdlights_en_5.5.1_3.0_1737675708159.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_vaibhavdlights_en_5.5.1_3.0_1737675708159.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_vaibhavdlights","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_vaibhavdlights", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_vaibhavdlights|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/VaibhavdLights/xlm-roberta-base-finetuned-panx-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_english_vaibhavdlights_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_english_vaibhavdlights_pipeline_en.md
new file mode 100644
index 00000000000000..ac356ba12a0d55
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_english_vaibhavdlights_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_vaibhavdlights_pipeline pipeline XlmRoBertaForTokenClassification from VaibhavdLights
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_vaibhavdlights_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_vaibhavdlights_pipeline` is a English model originally trained by VaibhavdLights.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_vaibhavdlights_pipeline_en_5.5.1_3.0_1737675827889.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_vaibhavdlights_pipeline_en_5.5.1_3.0_1737675827889.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_vaibhavdlights_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_vaibhavdlights_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_vaibhavdlights_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/VaibhavdLights/xlm-roberta-base-finetuned-panx-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_french_arkya_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_french_arkya_en.md
new file mode 100644
index 00000000000000..c0849593401f09
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_french_arkya_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_arkya XlmRoBertaForTokenClassification from Arkya
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_arkya
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_arkya` is a English model originally trained by Arkya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_arkya_en_5.5.1_3.0_1737674438943.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_arkya_en_5.5.1_3.0_1737674438943.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_arkya","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_arkya", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_arkya|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/Arkya/xlm-roberta-base-finetuned-panx-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_french_arkya_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_french_arkya_pipeline_en.md
new file mode 100644
index 00000000000000..d6876d1c14e384
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_french_arkya_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_arkya_pipeline pipeline XlmRoBertaForTokenClassification from Arkya
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_arkya_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_arkya_pipeline` is a English model originally trained by Arkya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_arkya_pipeline_en_5.5.1_3.0_1737674536038.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_arkya_pipeline_en_5.5.1_3.0_1737674536038.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_arkya_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_arkya_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_arkya_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/Arkya/xlm-roberta-base-finetuned-panx-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_french_ashkanero_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_french_ashkanero_en.md
new file mode 100644
index 00000000000000..3d28b1c49896c8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_french_ashkanero_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_ashkanero XlmRoBertaForTokenClassification from Ashkanero
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_ashkanero
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_ashkanero` is a English model originally trained by Ashkanero.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_ashkanero_en_5.5.1_3.0_1737675610855.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_ashkanero_en_5.5.1_3.0_1737675610855.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_ashkanero","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_ashkanero", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_ashkanero|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/Ashkanero/xlm-roberta-base-finetuned-panx-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_french_ashkanero_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_french_ashkanero_pipeline_en.md
new file mode 100644
index 00000000000000..c3b29239453475
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_french_ashkanero_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_ashkanero_pipeline pipeline XlmRoBertaForTokenClassification from Ashkanero
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_ashkanero_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_ashkanero_pipeline` is a English model originally trained by Ashkanero.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_ashkanero_pipeline_en_5.5.1_3.0_1737675707550.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_ashkanero_pipeline_en_5.5.1_3.0_1737675707550.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_ashkanero_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_ashkanero_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_ashkanero_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/Ashkanero/xlm-roberta-base-finetuned-panx-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_french_benjiccee_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_french_benjiccee_en.md
new file mode 100644
index 00000000000000..4a86b4e4955136
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_french_benjiccee_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_benjiccee XlmRoBertaForTokenClassification from Benjiccee
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_benjiccee
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_benjiccee` is a English model originally trained by Benjiccee.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_benjiccee_en_5.5.1_3.0_1737676497551.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_benjiccee_en_5.5.1_3.0_1737676497551.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_benjiccee","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_benjiccee", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_benjiccee|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.9 MB|
+
+## References
+
+https://huggingface.co/Benjiccee/xlm-roberta-base-finetuned-panx-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_french_benjiccee_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_french_benjiccee_pipeline_en.md
new file mode 100644
index 00000000000000..67a875af6dc0cc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_french_benjiccee_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_benjiccee_pipeline pipeline XlmRoBertaForTokenClassification from Benjiccee
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_benjiccee_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_benjiccee_pipeline` is a English model originally trained by Benjiccee.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_benjiccee_pipeline_en_5.5.1_3.0_1737676580095.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_benjiccee_pipeline_en_5.5.1_3.0_1737676580095.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_benjiccee_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_benjiccee_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_benjiccee_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.9 MB|
+
+## References
+
+https://huggingface.co/Benjiccee/xlm-roberta-base-finetuned-panx-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_french_halteroxhunter_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_french_halteroxhunter_en.md
new file mode 100644
index 00000000000000..ac7f163f368004
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_french_halteroxhunter_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_halteroxhunter XlmRoBertaForTokenClassification from HalteroXHunter
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_halteroxhunter
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_halteroxhunter` is a English model originally trained by HalteroXHunter.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_halteroxhunter_en_5.5.1_3.0_1737676328992.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_halteroxhunter_en_5.5.1_3.0_1737676328992.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_halteroxhunter","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_halteroxhunter", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_halteroxhunter|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.9 MB|
+
+## References
+
+https://huggingface.co/HalteroXHunter/xlm-roberta-base-finetuned-panx-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_french_halteroxhunter_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_french_halteroxhunter_pipeline_en.md
new file mode 100644
index 00000000000000..b026f29dd8c6a0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_french_halteroxhunter_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_halteroxhunter_pipeline pipeline XlmRoBertaForTokenClassification from HalteroXHunter
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_halteroxhunter_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_halteroxhunter_pipeline` is a English model originally trained by HalteroXHunter.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_halteroxhunter_pipeline_en_5.5.1_3.0_1737676412901.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_halteroxhunter_pipeline_en_5.5.1_3.0_1737676412901.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_halteroxhunter_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_halteroxhunter_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_halteroxhunter_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.9 MB|
+
+## References
+
+https://huggingface.co/HalteroXHunter/xlm-roberta-base-finetuned-panx-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_french_haoj1_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_french_haoj1_en.md
new file mode 100644
index 00000000000000..44ec8bccb008c9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_french_haoj1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_haoj1 XlmRoBertaForTokenClassification from haoj1
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_haoj1
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_haoj1` is a English model originally trained by haoj1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_haoj1_en_5.5.1_3.0_1737673604008.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_haoj1_en_5.5.1_3.0_1737673604008.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_haoj1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_haoj1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_haoj1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/haoj1/xlm-roberta-base-finetuned-panx-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_french_haoj1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_french_haoj1_pipeline_en.md
new file mode 100644
index 00000000000000..5555d06c65ac2d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_french_haoj1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_haoj1_pipeline pipeline XlmRoBertaForTokenClassification from haoj1
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_haoj1_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_haoj1_pipeline` is a English model originally trained by haoj1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_haoj1_pipeline_en_5.5.1_3.0_1737673705871.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_haoj1_pipeline_en_5.5.1_3.0_1737673705871.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_haoj1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_haoj1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_haoj1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/haoj1/xlm-roberta-base-finetuned-panx-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_french_starklin_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_french_starklin_en.md
new file mode 100644
index 00000000000000..64854f44c5c1d9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_french_starklin_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_starklin XlmRoBertaForTokenClassification from starklin
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_starklin
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_starklin` is a English model originally trained by starklin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_starklin_en_5.5.1_3.0_1737674828168.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_starklin_en_5.5.1_3.0_1737674828168.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_starklin","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_starklin", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_starklin|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/starklin/xlm-roberta-base-finetuned-panx-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_french_starklin_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_french_starklin_pipeline_en.md
new file mode 100644
index 00000000000000..28f7b59f855b26
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_french_starklin_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_starklin_pipeline pipeline XlmRoBertaForTokenClassification from starklin
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_starklin_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_starklin_pipeline` is a English model originally trained by starklin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_starklin_pipeline_en_5.5.1_3.0_1737674922702.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_starklin_pipeline_en_5.5.1_3.0_1737674922702.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_starklin_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_starklin_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_starklin_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/starklin/xlm-roberta-base-finetuned-panx-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_french_thundergod_zenitsu_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_french_thundergod_zenitsu_en.md
new file mode 100644
index 00000000000000..e490fe44b84f7d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_french_thundergod_zenitsu_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_thundergod_zenitsu XlmRoBertaForTokenClassification from thundergod-zenitsu
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_thundergod_zenitsu
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_thundergod_zenitsu` is a English model originally trained by thundergod-zenitsu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_thundergod_zenitsu_en_5.5.1_3.0_1737674181055.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_thundergod_zenitsu_en_5.5.1_3.0_1737674181055.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_thundergod_zenitsu","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_thundergod_zenitsu", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_thundergod_zenitsu|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/thundergod-zenitsu/xlm-roberta-base-finetuned-panx-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_french_thundergod_zenitsu_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_french_thundergod_zenitsu_pipeline_en.md
new file mode 100644
index 00000000000000..54f08cdd955f87
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_french_thundergod_zenitsu_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_thundergod_zenitsu_pipeline pipeline XlmRoBertaForTokenClassification from thundergod-zenitsu
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_thundergod_zenitsu_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_thundergod_zenitsu_pipeline` is a English model originally trained by thundergod-zenitsu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_thundergod_zenitsu_pipeline_en_5.5.1_3.0_1737674277815.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_thundergod_zenitsu_pipeline_en_5.5.1_3.0_1737674277815.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_thundergod_zenitsu_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_thundergod_zenitsu_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_thundergod_zenitsu_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/thundergod-zenitsu/xlm-roberta-base-finetuned-panx-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_adityak10_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_adityak10_en.md
new file mode 100644
index 00000000000000..f916bbd315b5ee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_adityak10_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_adityak10 XlmRoBertaForTokenClassification from AdityaK10
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_adityak10
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_adityak10` is a English model originally trained by AdityaK10.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_adityak10_en_5.5.1_3.0_1737673881331.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_adityak10_en_5.5.1_3.0_1737673881331.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_adityak10","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_adityak10", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_adityak10|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/AdityaK10/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_adityak10_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_adityak10_pipeline_en.md
new file mode 100644
index 00000000000000..0fb27ec1905c4d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_adityak10_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_adityak10_pipeline pipeline XlmRoBertaForTokenClassification from AdityaK10
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_adityak10_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_adityak10_pipeline` is a English model originally trained by AdityaK10.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_adityak10_pipeline_en_5.5.1_3.0_1737673951335.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_adityak10_pipeline_en_5.5.1_3.0_1737673951335.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_adityak10_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_adityak10_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_adityak10_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/AdityaK10/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_arkya_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_arkya_en.md
new file mode 100644
index 00000000000000..346f4b6aadacf0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_arkya_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_arkya XlmRoBertaForTokenClassification from Arkya
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_arkya
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_arkya` is a English model originally trained by Arkya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_arkya_en_5.5.1_3.0_1737675199900.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_arkya_en_5.5.1_3.0_1737675199900.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_arkya","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_arkya", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_arkya|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/Arkya/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_arkya_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_arkya_pipeline_en.md
new file mode 100644
index 00000000000000..a456922ffd90ac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_arkya_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_arkya_pipeline pipeline XlmRoBertaForTokenClassification from Arkya
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_arkya_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_arkya_pipeline` is a English model originally trained by Arkya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_arkya_pipeline_en_5.5.1_3.0_1737675288638.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_arkya_pipeline_en_5.5.1_3.0_1737675288638.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_arkya_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_arkya_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_arkya_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/Arkya/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_buruzaemon_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_buruzaemon_en.md
new file mode 100644
index 00000000000000..9c9e6e9b652e3e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_buruzaemon_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_buruzaemon XlmRoBertaForTokenClassification from buruzaemon
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_buruzaemon
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_buruzaemon` is a English model originally trained by buruzaemon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_buruzaemon_en_5.5.1_3.0_1737673513373.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_buruzaemon_en_5.5.1_3.0_1737673513373.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_buruzaemon","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_buruzaemon", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_buruzaemon|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/buruzaemon/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_buruzaemon_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_buruzaemon_pipeline_en.md
new file mode 100644
index 00000000000000..15b8e786c74a4c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_buruzaemon_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_buruzaemon_pipeline pipeline XlmRoBertaForTokenClassification from buruzaemon
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_buruzaemon_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_buruzaemon_pipeline` is a English model originally trained by buruzaemon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_buruzaemon_pipeline_en_5.5.1_3.0_1737673602636.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_buruzaemon_pipeline_en_5.5.1_3.0_1737673602636.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_buruzaemon_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_buruzaemon_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_buruzaemon_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/buruzaemon/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_french_jongbaly_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_french_jongbaly_en.md
new file mode 100644
index 00000000000000..7d126a6d812d3e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_french_jongbaly_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_jongbaly XlmRoBertaForTokenClassification from jongbaly
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_jongbaly
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_jongbaly` is a English model originally trained by jongbaly.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_jongbaly_en_5.5.1_3.0_1737675761458.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_jongbaly_en_5.5.1_3.0_1737675761458.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_jongbaly","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_jongbaly", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_jongbaly|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/jongbaly/xlm-roberta-base-finetuned-panx-de-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_french_jongbaly_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_french_jongbaly_pipeline_en.md
new file mode 100644
index 00000000000000..8ce0d78146ea3a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_french_jongbaly_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_jongbaly_pipeline pipeline XlmRoBertaForTokenClassification from jongbaly
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_jongbaly_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_jongbaly_pipeline` is a English model originally trained by jongbaly.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_jongbaly_pipeline_en_5.5.1_3.0_1737675850702.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_jongbaly_pipeline_en_5.5.1_3.0_1737675850702.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_jongbaly_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_jongbaly_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_jongbaly_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/jongbaly/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_french_ryatora_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_french_ryatora_en.md
new file mode 100644
index 00000000000000..42fd9de6a9543c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_french_ryatora_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_ryatora XlmRoBertaForTokenClassification from ryatora
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_ryatora
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_ryatora` is a English model originally trained by ryatora.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_ryatora_en_5.5.1_3.0_1737676543225.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_ryatora_en_5.5.1_3.0_1737676543225.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_ryatora","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_ryatora", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_ryatora|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|858.2 MB|
+
+## References
+
+https://huggingface.co/ryatora/xlm-roberta-base-finetuned-panx-de-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_french_ryatora_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_french_ryatora_pipeline_en.md
new file mode 100644
index 00000000000000..af3dc2db071357
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_french_ryatora_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_ryatora_pipeline pipeline XlmRoBertaForTokenClassification from ryatora
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_ryatora_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_ryatora_pipeline` is a English model originally trained by ryatora.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_ryatora_pipeline_en_5.5.1_3.0_1737676611970.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_ryatora_pipeline_en_5.5.1_3.0_1737676611970.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_ryatora_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_ryatora_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_ryatora_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|858.2 MB|
+
+## References
+
+https://huggingface.co/ryatora/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_french_taoyoung_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_french_taoyoung_en.md
new file mode 100644
index 00000000000000..30aa16a677012d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_french_taoyoung_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_taoyoung XlmRoBertaForTokenClassification from taoyoung
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_taoyoung
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_taoyoung` is a English model originally trained by taoyoung.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_taoyoung_en_5.5.1_3.0_1737675462636.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_taoyoung_en_5.5.1_3.0_1737675462636.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_taoyoung","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_taoyoung", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_taoyoung|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|843.0 MB|
+
+## References
+
+https://huggingface.co/taoyoung/xlm-roberta-base-finetuned-panx-de-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_french_taoyoung_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_french_taoyoung_pipeline_en.md
new file mode 100644
index 00000000000000..e8e0b1ab3f262c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_french_taoyoung_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_taoyoung_pipeline pipeline XlmRoBertaForTokenClassification from taoyoung
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_taoyoung_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_taoyoung_pipeline` is a English model originally trained by taoyoung.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_taoyoung_pipeline_en_5.5.1_3.0_1737675550545.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_taoyoung_pipeline_en_5.5.1_3.0_1737675550545.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_taoyoung_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_taoyoung_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_taoyoung_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|843.0 MB|
+
+## References
+
+https://huggingface.co/taoyoung/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_french_vaibhavdlights_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_french_vaibhavdlights_en.md
new file mode 100644
index 00000000000000..c400f95e505fec
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_french_vaibhavdlights_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_vaibhavdlights XlmRoBertaForTokenClassification from VaibhavdLights
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_vaibhavdlights
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_vaibhavdlights` is a English model originally trained by VaibhavdLights.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_vaibhavdlights_en_5.5.1_3.0_1737674246810.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_vaibhavdlights_en_5.5.1_3.0_1737674246810.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_vaibhavdlights","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_vaibhavdlights", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_vaibhavdlights|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/VaibhavdLights/xlm-roberta-base-finetuned-panx-de-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_french_vaibhavdlights_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_french_vaibhavdlights_pipeline_en.md
new file mode 100644
index 00000000000000..f2c4986d30cbe9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_french_vaibhavdlights_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_vaibhavdlights_pipeline pipeline XlmRoBertaForTokenClassification from VaibhavdLights
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_vaibhavdlights_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_vaibhavdlights_pipeline` is a English model originally trained by VaibhavdLights.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_vaibhavdlights_pipeline_en_5.5.1_3.0_1737674337264.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_vaibhavdlights_pipeline_en_5.5.1_3.0_1737674337264.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_vaibhavdlights_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_vaibhavdlights_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_vaibhavdlights_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/VaibhavdLights/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_havagoodday_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_havagoodday_en.md
new file mode 100644
index 00000000000000..4f61ae171e822e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_havagoodday_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_havagoodday XlmRoBertaForTokenClassification from HavaGoodDay
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_havagoodday
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_havagoodday` is a English model originally trained by HavaGoodDay.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_havagoodday_en_5.5.1_3.0_1737676017830.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_havagoodday_en_5.5.1_3.0_1737676017830.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_havagoodday","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_havagoodday", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_havagoodday|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/HavaGoodDay/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_havagoodday_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_havagoodday_pipeline_en.md
new file mode 100644
index 00000000000000..4c8625971499aa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_havagoodday_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_havagoodday_pipeline pipeline XlmRoBertaForTokenClassification from HavaGoodDay
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_havagoodday_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_havagoodday_pipeline` is a English model originally trained by HavaGoodDay.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_havagoodday_pipeline_en_5.5.1_3.0_1737676108243.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_havagoodday_pipeline_en_5.5.1_3.0_1737676108243.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_havagoodday_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_havagoodday_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_havagoodday_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/HavaGoodDay/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_jongbaly_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_jongbaly_en.md
new file mode 100644
index 00000000000000..7eebf856fe83c5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_jongbaly_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_jongbaly XlmRoBertaForTokenClassification from jongbaly
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_jongbaly
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_jongbaly` is a English model originally trained by jongbaly.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_jongbaly_en_5.5.1_3.0_1737674002015.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_jongbaly_en_5.5.1_3.0_1737674002015.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_jongbaly","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_jongbaly", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_jongbaly|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/jongbaly/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_jongbaly_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_jongbaly_pipeline_en.md
new file mode 100644
index 00000000000000..105aaaf25ec815
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_jongbaly_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_jongbaly_pipeline pipeline XlmRoBertaForTokenClassification from jongbaly
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_jongbaly_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_jongbaly_pipeline` is a English model originally trained by jongbaly.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_jongbaly_pipeline_en_5.5.1_3.0_1737674089037.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_jongbaly_pipeline_en_5.5.1_3.0_1737674089037.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_jongbaly_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_jongbaly_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_jongbaly_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/jongbaly/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_lalegumbreartificial_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_lalegumbreartificial_en.md
new file mode 100644
index 00000000000000..91be396e163478
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_lalegumbreartificial_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_lalegumbreartificial XlmRoBertaForTokenClassification from LaLegumbreArtificial
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_lalegumbreartificial
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_lalegumbreartificial` is a English model originally trained by LaLegumbreArtificial.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_lalegumbreartificial_en_5.5.1_3.0_1737675081101.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_lalegumbreartificial_en_5.5.1_3.0_1737675081101.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_lalegumbreartificial","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_lalegumbreartificial", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_lalegumbreartificial|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/LaLegumbreArtificial/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_lalegumbreartificial_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_lalegumbreartificial_pipeline_en.md
new file mode 100644
index 00000000000000..2a07d2acf13d9f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_lalegumbreartificial_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_lalegumbreartificial_pipeline pipeline XlmRoBertaForTokenClassification from LaLegumbreArtificial
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_lalegumbreartificial_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_lalegumbreartificial_pipeline` is a English model originally trained by LaLegumbreArtificial.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_lalegumbreartificial_pipeline_en_5.5.1_3.0_1737675153410.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_lalegumbreartificial_pipeline_en_5.5.1_3.0_1737675153410.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_lalegumbreartificial_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_lalegumbreartificial_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_lalegumbreartificial_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/LaLegumbreArtificial/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_m_usab_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_m_usab_en.md
new file mode 100644
index 00000000000000..0252823ad16437
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_m_usab_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_m_usab XlmRoBertaForTokenClassification from m-usab
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_m_usab
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_m_usab` is a English model originally trained by m-usab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_m_usab_en_5.5.1_3.0_1737674846031.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_m_usab_en_5.5.1_3.0_1737674846031.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_m_usab","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_m_usab", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_m_usab|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/m-usab/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_m_usab_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_m_usab_pipeline_en.md
new file mode 100644
index 00000000000000..490068bbe45568
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_m_usab_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_m_usab_pipeline pipeline XlmRoBertaForTokenClassification from m-usab
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_m_usab_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_m_usab_pipeline` is a English model originally trained by m-usab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_m_usab_pipeline_en_5.5.1_3.0_1737674934736.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_m_usab_pipeline_en_5.5.1_3.0_1737674934736.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_m_usab_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_m_usab_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_m_usab_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/m-usab/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_opengl99_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_opengl99_en.md
new file mode 100644
index 00000000000000..23ea978fe56a0a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_opengl99_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_opengl99 XlmRoBertaForTokenClassification from opengl99
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_opengl99
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_opengl99` is a English model originally trained by opengl99.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_opengl99_en_5.5.1_3.0_1737674523219.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_opengl99_en_5.5.1_3.0_1737674523219.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_opengl99","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_opengl99", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_opengl99|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/opengl99/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_opengl99_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_opengl99_pipeline_en.md
new file mode 100644
index 00000000000000..ad62b19363c2c2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_opengl99_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_opengl99_pipeline pipeline XlmRoBertaForTokenClassification from opengl99
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_opengl99_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_opengl99_pipeline` is a English model originally trained by opengl99.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_opengl99_pipeline_en_5.5.1_3.0_1737674595477.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_opengl99_pipeline_en_5.5.1_3.0_1737674595477.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_opengl99_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_opengl99_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_opengl99_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/opengl99/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_paulisickc_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_paulisickc_en.md
new file mode 100644
index 00000000000000..27cac43e91a30a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_paulisickc_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_paulisickc XlmRoBertaForTokenClassification from paulisickc
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_paulisickc
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_paulisickc` is a English model originally trained by paulisickc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_paulisickc_en_5.5.1_3.0_1737675300807.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_paulisickc_en_5.5.1_3.0_1737675300807.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_paulisickc","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_paulisickc", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_paulisickc|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/paulisickc/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_paulisickc_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_paulisickc_pipeline_en.md
new file mode 100644
index 00000000000000..7d7030d516837d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_paulisickc_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_paulisickc_pipeline pipeline XlmRoBertaForTokenClassification from paulisickc
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_paulisickc_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_paulisickc_pipeline` is a English model originally trained by paulisickc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_paulisickc_pipeline_en_5.5.1_3.0_1737675392185.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_paulisickc_pipeline_en_5.5.1_3.0_1737675392185.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_paulisickc_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_paulisickc_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_paulisickc_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/paulisickc/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_sjsj33_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_sjsj33_en.md
new file mode 100644
index 00000000000000..2bf00545b5f910
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_sjsj33_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_sjsj33 XlmRoBertaForTokenClassification from sjsj33
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_sjsj33
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_sjsj33` is a English model originally trained by sjsj33.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_sjsj33_en_5.5.1_3.0_1737675593243.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_sjsj33_en_5.5.1_3.0_1737675593243.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_sjsj33","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_sjsj33", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_sjsj33|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/sjsj33/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_sjsj33_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_sjsj33_pipeline_en.md
new file mode 100644
index 00000000000000..88868fbf032c4b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_sjsj33_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_sjsj33_pipeline pipeline XlmRoBertaForTokenClassification from sjsj33
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_sjsj33_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_sjsj33_pipeline` is a English model originally trained by sjsj33.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_sjsj33_pipeline_en_5.5.1_3.0_1737675682286.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_sjsj33_pipeline_en_5.5.1_3.0_1737675682286.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_sjsj33_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_sjsj33_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_sjsj33_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/sjsj33/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_souling_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_souling_en.md
new file mode 100644
index 00000000000000..c491a3cbaddc49
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_souling_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_souling XlmRoBertaForTokenClassification from souling
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_souling
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_souling` is a English model originally trained by souling.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_souling_en_5.5.1_3.0_1737673776309.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_souling_en_5.5.1_3.0_1737673776309.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_souling","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_souling", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_souling|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/souling/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_souling_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_souling_pipeline_en.md
new file mode 100644
index 00000000000000..f71e752009c76d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_souling_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_souling_pipeline pipeline XlmRoBertaForTokenClassification from souling
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_souling_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_souling_pipeline` is a English model originally trained by souling.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_souling_pipeline_en_5.5.1_3.0_1737673864177.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_souling_pipeline_en_5.5.1_3.0_1737673864177.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_souling_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_souling_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_souling_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/souling/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_svensk_k_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_svensk_k_en.md
new file mode 100644
index 00000000000000..6233f2aa81eb86
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_svensk_k_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_svensk_k XlmRoBertaForTokenClassification from svensk-k
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_svensk_k
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_svensk_k` is a English model originally trained by svensk-k.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_svensk_k_en_5.5.1_3.0_1737676051985.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_svensk_k_en_5.5.1_3.0_1737676051985.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_svensk_k","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_svensk_k", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_svensk_k|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/svensk-k/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_svensk_k_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_svensk_k_pipeline_en.md
new file mode 100644
index 00000000000000..305d641b7dc63c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_svensk_k_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_svensk_k_pipeline pipeline XlmRoBertaForTokenClassification from svensk-k
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_svensk_k_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_svensk_k_pipeline` is a English model originally trained by svensk-k.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_svensk_k_pipeline_en_5.5.1_3.0_1737676124233.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_svensk_k_pipeline_en_5.5.1_3.0_1737676124233.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_svensk_k_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_svensk_k_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_svensk_k_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/svensk-k/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_tmdqja75_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_tmdqja75_en.md
new file mode 100644
index 00000000000000..f30e7d57263a2c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_tmdqja75_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_tmdqja75 XlmRoBertaForTokenClassification from tmdqja75
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_tmdqja75
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_tmdqja75` is a English model originally trained by tmdqja75.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_tmdqja75_en_5.5.1_3.0_1737676220295.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_tmdqja75_en_5.5.1_3.0_1737676220295.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_tmdqja75","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_tmdqja75", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_tmdqja75|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/tmdqja75/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_tmdqja75_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_tmdqja75_pipeline_en.md
new file mode 100644
index 00000000000000..5084f14783cb2c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_tmdqja75_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_tmdqja75_pipeline pipeline XlmRoBertaForTokenClassification from tmdqja75
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_tmdqja75_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_tmdqja75_pipeline` is a English model originally trained by tmdqja75.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_tmdqja75_pipeline_en_5.5.1_3.0_1737676309189.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_tmdqja75_pipeline_en_5.5.1_3.0_1737676309189.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_tmdqja75_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_tmdqja75_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_tmdqja75_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/tmdqja75/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_zuhayr_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_zuhayr_en.md
new file mode 100644
index 00000000000000..3afdc2c1d68543
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_zuhayr_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_zuhayr XlmRoBertaForTokenClassification from zuhayr
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_zuhayr
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_zuhayr` is a English model originally trained by zuhayr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_zuhayr_en_5.5.1_3.0_1737674353546.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_zuhayr_en_5.5.1_3.0_1737674353546.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_zuhayr","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_zuhayr", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_zuhayr|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|836.1 MB|
+
+## References
+
+https://huggingface.co/zuhayr/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_zuhayr_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_zuhayr_pipeline_en.md
new file mode 100644
index 00000000000000..dfd601e0f1ee05
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_german_zuhayr_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_zuhayr_pipeline pipeline XlmRoBertaForTokenClassification from zuhayr
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_zuhayr_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_zuhayr_pipeline` is a English model originally trained by zuhayr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_zuhayr_pipeline_en_5.5.1_3.0_1737674446670.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_zuhayr_pipeline_en_5.5.1_3.0_1737674446670.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_zuhayr_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_zuhayr_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_zuhayr_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|836.1 MB|
+
+## References
+
+https://huggingface.co/zuhayr/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_italian_0ppxnhximxr_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_italian_0ppxnhximxr_en.md
new file mode 100644
index 00000000000000..790391cc52936a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_italian_0ppxnhximxr_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_0ppxnhximxr XlmRoBertaForTokenClassification from 0ppxnhximxr
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_0ppxnhximxr
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_0ppxnhximxr` is a English model originally trained by 0ppxnhximxr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_0ppxnhximxr_en_5.5.1_3.0_1737674369784.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_0ppxnhximxr_en_5.5.1_3.0_1737674369784.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_0ppxnhximxr","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_0ppxnhximxr", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_0ppxnhximxr|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|816.7 MB|
+
+## References
+
+https://huggingface.co/0ppxnhximxr/xlm-roberta-base-finetuned-panx-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_italian_0ppxnhximxr_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_italian_0ppxnhximxr_pipeline_en.md
new file mode 100644
index 00000000000000..8e2145bd3660aa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_italian_0ppxnhximxr_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_0ppxnhximxr_pipeline pipeline XlmRoBertaForTokenClassification from 0ppxnhximxr
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_0ppxnhximxr_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_0ppxnhximxr_pipeline` is a English model originally trained by 0ppxnhximxr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_0ppxnhximxr_pipeline_en_5.5.1_3.0_1737674473284.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_0ppxnhximxr_pipeline_en_5.5.1_3.0_1737674473284.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_0ppxnhximxr_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_0ppxnhximxr_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_0ppxnhximxr_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|816.7 MB|
+
+## References
+
+https://huggingface.co/0ppxnhximxr/xlm-roberta-base-finetuned-panx-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_italian_arkya_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_italian_arkya_en.md
new file mode 100644
index 00000000000000..9e90085e67cebd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_italian_arkya_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_arkya XlmRoBertaForTokenClassification from Arkya
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_arkya
+date: 2025-01-23
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_arkya` is a English model originally trained by Arkya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_arkya_en_5.5.1_3.0_1737674704118.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_arkya_en_5.5.1_3.0_1737674704118.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_arkya","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_arkya", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_arkya|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|816.7 MB|
+
+## References
+
+https://huggingface.co/Arkya/xlm-roberta-base-finetuned-panx-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_italian_arkya_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_italian_arkya_pipeline_en.md
new file mode 100644
index 00000000000000..ee8f03a46aabb0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_panx_italian_arkya_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_arkya_pipeline pipeline XlmRoBertaForTokenClassification from Arkya
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_arkya_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_arkya_pipeline` is a English model originally trained by Arkya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_arkya_pipeline_en_5.5.1_3.0_1737674806550.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_arkya_pipeline_en_5.5.1_3.0_1737674806550.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_arkya_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_arkya_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_arkya_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|816.8 MB|
+
+## References
+
+https://huggingface.co/Arkya/xlm-roberta-base-finetuned-panx-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_wrime_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_wrime_en.md
new file mode 100644
index 00000000000000..190911ca593289
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_wrime_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_wrime XlmRoBertaForSequenceClassification from MuneK
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_wrime
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_wrime` is a English model originally trained by MuneK.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_wrime_en_5.5.1_3.0_1737651547673.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_wrime_en_5.5.1_3.0_1737651547673.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_finetuned_wrime","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_finetuned_wrime", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_wrime|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|848.8 MB|
+
+## References
+
+https://huggingface.co/MuneK/xlm-roberta-base-finetuned-wrime
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_wrime_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_wrime_pipeline_en.md
new file mode 100644
index 00000000000000..a304ed8d17fc12
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_finetuned_wrime_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_wrime_pipeline pipeline XlmRoBertaForSequenceClassification from MuneK
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_wrime_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_wrime_pipeline` is a English model originally trained by MuneK.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_wrime_pipeline_en_5.5.1_3.0_1737651621072.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_wrime_pipeline_en_5.5.1_3.0_1737651621072.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_wrime_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_wrime_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_wrime_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|848.8 MB|
+
+## References
+
+https://huggingface.co/MuneK/xlm-roberta-base-finetuned-wrime
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_latin_uncased_la.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_latin_uncased_la.md
new file mode 100644
index 00000000000000..797709eaf44c86
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_latin_uncased_la.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Latin xlm_roberta_base_latin_uncased XlmRoBertaEmbeddings from Cicciokr
+author: John Snow Labs
+name: xlm_roberta_base_latin_uncased
+date: 2025-01-23
+tags: [la, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: la
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_latin_uncased` is a Latin model originally trained by Cicciokr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_latin_uncased_la_5.5.1_3.0_1737668765461.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_latin_uncased_la_5.5.1_3.0_1737668765461.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("xlm_roberta_base_latin_uncased","la") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("xlm_roberta_base_latin_uncased","la") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_latin_uncased|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|la|
+|Size:|916.1 MB|
+
+## References
+
+https://huggingface.co/Cicciokr/XLM-Roberta-Base-Latin-Uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_latin_uncased_pipeline_la.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_latin_uncased_pipeline_la.md
new file mode 100644
index 00000000000000..551ba42c8a96d0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_latin_uncased_pipeline_la.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Latin xlm_roberta_base_latin_uncased_pipeline pipeline XlmRoBertaEmbeddings from Cicciokr
+author: John Snow Labs
+name: xlm_roberta_base_latin_uncased_pipeline
+date: 2025-01-23
+tags: [la, open_source, pipeline, onnx]
+task: Embeddings
+language: la
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_latin_uncased_pipeline` is a Latin model originally trained by Cicciokr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_latin_uncased_pipeline_la_5.5.1_3.0_1737668838534.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_latin_uncased_pipeline_la_5.5.1_3.0_1737668838534.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_latin_uncased_pipeline", lang = "la")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_latin_uncased_pipeline", lang = "la")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_latin_uncased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|la|
+|Size:|916.1 MB|
+
+## References
+
+https://huggingface.co/Cicciokr/XLM-Roberta-Base-Latin-Uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_tycholina_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_tycholina_en.md
new file mode 100644
index 00000000000000..59ee20a58bb504
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_tycholina_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_tycholina XlmRoBertaEmbeddings from lailamt
+author: John Snow Labs
+name: xlm_roberta_base_tycholina
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_tycholina` is a English model originally trained by lailamt.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_tycholina_en_5.5.1_3.0_1737668350561.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_tycholina_en_5.5.1_3.0_1737668350561.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("xlm_roberta_base_tycholina","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("xlm_roberta_base_tycholina","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_tycholina|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/lailamt/xlm-roberta-base-tycholina
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_tycholina_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_tycholina_pipeline_en.md
new file mode 100644
index 00000000000000..53e8045600e3a0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_base_tycholina_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_tycholina_pipeline pipeline XlmRoBertaEmbeddings from lailamt
+author: John Snow Labs
+name: xlm_roberta_base_tycholina_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_tycholina_pipeline` is a English model originally trained by lailamt.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_tycholina_pipeline_en_5.5.1_3.0_1737668406806.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_tycholina_pipeline_en_5.5.1_3.0_1737668406806.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_tycholina_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_tycholina_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_tycholina_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/lailamt/xlm-roberta-base-tycholina
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_distilled_v_1_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_distilled_v_1_en.md
new file mode 100644
index 00000000000000..ea61b338c6845a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_distilled_v_1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English xlm_roberta_distilled_v_1 DistilBertForQuestionAnswering from RajeevanL
+author: John Snow Labs
+name: xlm_roberta_distilled_v_1
+date: 2025-01-23
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_distilled_v_1` is a English model originally trained by RajeevanL.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_distilled_v_1_en_5.5.1_3.0_1737660263054.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_distilled_v_1_en_5.5.1_3.0_1737660263054.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("xlm_roberta_distilled_v_1","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("xlm_roberta_distilled_v_1", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_distilled_v_1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|505.4 MB|
+
+## References
+
+https://huggingface.co/RajeevanL/xlm_roberta_distilled_v_1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_distilled_v_1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_distilled_v_1_pipeline_en.md
new file mode 100644
index 00000000000000..a60a03dc801a91
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlm_roberta_distilled_v_1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English xlm_roberta_distilled_v_1_pipeline pipeline DistilBertForQuestionAnswering from RajeevanL
+author: John Snow Labs
+name: xlm_roberta_distilled_v_1_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_distilled_v_1_pipeline` is a English model originally trained by RajeevanL.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_distilled_v_1_pipeline_en_5.5.1_3.0_1737660293134.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_distilled_v_1_pipeline_en_5.5.1_3.0_1737660293134.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_distilled_v_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_distilled_v_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_distilled_v_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|505.4 MB|
+
+## References
+
+https://huggingface.co/RajeevanL/xlm_roberta_distilled_v_1
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlmr_base_emakhuwa_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlmr_base_emakhuwa_en.md
new file mode 100644
index 00000000000000..b7f13a769edc08
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlmr_base_emakhuwa_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlmr_base_emakhuwa XlmRoBertaEmbeddings from felerminoali
+author: John Snow Labs
+name: xlmr_base_emakhuwa
+date: 2025-01-23
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmr_base_emakhuwa` is a English model originally trained by felerminoali.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmr_base_emakhuwa_en_5.5.1_3.0_1737668903902.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmr_base_emakhuwa_en_5.5.1_3.0_1737668903902.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("xlmr_base_emakhuwa","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("xlmr_base_emakhuwa","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmr_base_emakhuwa|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/felerminoali/xlmr_base_emakhuwa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlmr_base_emakhuwa_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlmr_base_emakhuwa_pipeline_en.md
new file mode 100644
index 00000000000000..95d224e315c9a2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlmr_base_emakhuwa_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlmr_base_emakhuwa_pipeline pipeline XlmRoBertaEmbeddings from felerminoali
+author: John Snow Labs
+name: xlmr_base_emakhuwa_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmr_base_emakhuwa_pipeline` is a English model originally trained by felerminoali.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmr_base_emakhuwa_pipeline_en_5.5.1_3.0_1737668960034.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmr_base_emakhuwa_pipeline_en_5.5.1_3.0_1737668960034.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlmr_base_emakhuwa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmr_base_emakhuwa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmr_base_emakhuwa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/felerminoali/xlmr_base_emakhuwa
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlmr_finetuned_cogdist_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlmr_finetuned_cogdist_en.md
new file mode 100644
index 00000000000000..09a04958966669
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlmr_finetuned_cogdist_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlmr_finetuned_cogdist XlmRoBertaForSequenceClassification from abhishekkuber
+author: John Snow Labs
+name: xlmr_finetuned_cogdist
+date: 2025-01-23
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmr_finetuned_cogdist` is a English model originally trained by abhishekkuber.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmr_finetuned_cogdist_en_5.5.1_3.0_1737652403978.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmr_finetuned_cogdist_en_5.5.1_3.0_1737652403978.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlmr_finetuned_cogdist","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlmr_finetuned_cogdist", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmr_finetuned_cogdist|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|784.7 MB|
+
+## References
+
+https://huggingface.co/abhishekkuber/xlmr_finetuned_cogdist
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xlmr_finetuned_cogdist_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-xlmr_finetuned_cogdist_pipeline_en.md
new file mode 100644
index 00000000000000..ad159936419dec
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xlmr_finetuned_cogdist_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlmr_finetuned_cogdist_pipeline pipeline XlmRoBertaForSequenceClassification from abhishekkuber
+author: John Snow Labs
+name: xlmr_finetuned_cogdist_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmr_finetuned_cogdist_pipeline` is a English model originally trained by abhishekkuber.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmr_finetuned_cogdist_pipeline_en_5.5.1_3.0_1737652548864.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmr_finetuned_cogdist_pipeline_en_5.5.1_3.0_1737652548864.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlmr_finetuned_cogdist_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmr_finetuned_cogdist_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmr_finetuned_cogdist_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|784.7 MB|
+
+## References
+
+https://huggingface.co/abhishekkuber/xlmr_finetuned_cogdist
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xrayclip__vit_l_14__laion2b_s32b_b82k_en.md b/docs/_posts/ahmedlone127/2025-01-23-xrayclip__vit_l_14__laion2b_s32b_b82k_en.md
new file mode 100644
index 00000000000000..bceec9cc109851
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xrayclip__vit_l_14__laion2b_s32b_b82k_en.md
@@ -0,0 +1,120 @@
+---
+layout: model
+title: English xrayclip__vit_l_14__laion2b_s32b_b82k CLIPForZeroShotClassification from StanfordAIMI
+author: John Snow Labs
+name: xrayclip__vit_l_14__laion2b_s32b_b82k
+date: 2025-01-23
+tags: [en, open_source, onnx, zero_shot, clip, image]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CLIPForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xrayclip__vit_l_14__laion2b_s32b_b82k` is a English model originally trained by StanfordAIMI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xrayclip__vit_l_14__laion2b_s32b_b82k_en_5.5.1_3.0_1737631070131.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xrayclip__vit_l_14__laion2b_s32b_b82k_en_5.5.1_3.0_1737631070131.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+imageDF = spark.read \
+    .format("image") \
+    .option("dropInvalid", value = True) \
+    .load("src/test/resources/image/")
+    
+candidateLabels = [
+    "a photo of a bird",
+    "a photo of a cat",
+    "a photo of a dog",
+    "a photo of a hen",
+    "a photo of a hippo",
+    "a photo of a room",
+    "a photo of a tractor",
+    "a photo of an ostrich",
+    "a photo of an ox"]
+
+ImageAssembler = ImageAssembler() \
+	.setInputCol("image") \
+	.setOutputCol("image_assembler")
+
+imageClassifier = CLIPForZeroShotClassification.pretrained("xrayclip__vit_l_14__laion2b_s32b_b82k","en") \
+     .setInputCols(["image_assembler"]) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+
+pipeline = Pipeline().setStages([ImageAssembler, imageClassifier])
+pipelineModel = pipeline.fit(imageDF)
+pipelineDF = pipelineModel.transform(imageDF)
+
+
+```
+```scala
+
+		
+val imageDF = ResourceHelper.spark.read
+  .format("image")
+  .option("dropInvalid", value = true)
+  .load("src/test/resources/image/")
+
+val candidateLabels = Array(
+  "a photo of a bird",
+  "a photo of a cat",
+  "a photo of a dog",
+  "a photo of a hen",
+  "a photo of a hippo",
+  "a photo of a room",
+  "a photo of a tractor",
+  "a photo of an ostrich",
+  "a photo of an ox")
+
+val imageAssembler = new ImageAssembler()
+  .setInputCol("image")
+  .setOutputCol("image_assembler")
+  
+val imageClassifier = CLIPForZeroShotClassification.pretrained("xrayclip__vit_l_14__laion2b_s32b_b82k","en") \
+     .setInputCols(Array("image_assembler")) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+  
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+val pipelineModel = pipeline.fit(imageDF)
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xrayclip__vit_l_14__laion2b_s32b_b82k|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/StanfordAIMI/XrayCLIP__vit-l-14__laion2b-s32b-b82k
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xrayclip__vit_l_14__laion2b_s32b_b82k_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-xrayclip__vit_l_14__laion2b_s32b_b82k_pipeline_en.md
new file mode 100644
index 00000000000000..f0ab77f1dc6baa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xrayclip__vit_l_14__laion2b_s32b_b82k_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English xrayclip__vit_l_14__laion2b_s32b_b82k_pipeline pipeline CLIPForZeroShotClassification from StanfordAIMI
+author: John Snow Labs
+name: xrayclip__vit_l_14__laion2b_s32b_b82k_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xrayclip__vit_l_14__laion2b_s32b_b82k_pipeline` is a English model originally trained by StanfordAIMI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xrayclip__vit_l_14__laion2b_s32b_b82k_pipeline_en_5.5.1_3.0_1737631150135.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xrayclip__vit_l_14__laion2b_s32b_b82k_pipeline_en_5.5.1_3.0_1737631150135.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xrayclip__vit_l_14__laion2b_s32b_b82k_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xrayclip__vit_l_14__laion2b_s32b_b82k_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xrayclip__vit_l_14__laion2b_s32b_b82k_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/StanfordAIMI/XrayCLIP__vit-l-14__laion2b-s32b-b82k
+
+## Included Models
+
+- ImageAssembler
+- CLIPForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xraysiglip__vit_b_16__laion2b_s34b_b88k_en.md b/docs/_posts/ahmedlone127/2025-01-23-xraysiglip__vit_b_16__laion2b_s34b_b88k_en.md
new file mode 100644
index 00000000000000..55f5b0748d7547
--- /dev/null
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@@ -0,0 +1,120 @@
+---
+layout: model
+title: English xraysiglip__vit_b_16__laion2b_s34b_b88k CLIPForZeroShotClassification from StanfordAIMI
+author: John Snow Labs
+name: xraysiglip__vit_b_16__laion2b_s34b_b88k
+date: 2025-01-23
+tags: [en, open_source, onnx, zero_shot, clip, image]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CLIPForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xraysiglip__vit_b_16__laion2b_s34b_b88k` is a English model originally trained by StanfordAIMI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xraysiglip__vit_b_16__laion2b_s34b_b88k_en_5.5.1_3.0_1737631716687.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xraysiglip__vit_b_16__laion2b_s34b_b88k_en_5.5.1_3.0_1737631716687.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+imageDF = spark.read \
+    .format("image") \
+    .option("dropInvalid", value = True) \
+    .load("src/test/resources/image/")
+    
+candidateLabels = [
+    "a photo of a bird",
+    "a photo of a cat",
+    "a photo of a dog",
+    "a photo of a hen",
+    "a photo of a hippo",
+    "a photo of a room",
+    "a photo of a tractor",
+    "a photo of an ostrich",
+    "a photo of an ox"]
+
+ImageAssembler = ImageAssembler() \
+	.setInputCol("image") \
+	.setOutputCol("image_assembler")
+
+imageClassifier = CLIPForZeroShotClassification.pretrained("xraysiglip__vit_b_16__laion2b_s34b_b88k","en") \
+     .setInputCols(["image_assembler"]) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+
+pipeline = Pipeline().setStages([ImageAssembler, imageClassifier])
+pipelineModel = pipeline.fit(imageDF)
+pipelineDF = pipelineModel.transform(imageDF)
+
+
+```
+```scala
+
+		
+val imageDF = ResourceHelper.spark.read
+  .format("image")
+  .option("dropInvalid", value = true)
+  .load("src/test/resources/image/")
+
+val candidateLabels = Array(
+  "a photo of a bird",
+  "a photo of a cat",
+  "a photo of a dog",
+  "a photo of a hen",
+  "a photo of a hippo",
+  "a photo of a room",
+  "a photo of a tractor",
+  "a photo of an ostrich",
+  "a photo of an ox")
+
+val imageAssembler = new ImageAssembler()
+  .setInputCol("image")
+  .setOutputCol("image_assembler")
+  
+val imageClassifier = CLIPForZeroShotClassification.pretrained("xraysiglip__vit_b_16__laion2b_s34b_b88k","en") \
+     .setInputCols(Array("image_assembler")) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+  
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+val pipelineModel = pipeline.fit(imageDF)
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xraysiglip__vit_b_16__laion2b_s34b_b88k|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|564.3 MB|
+
+## References
+
+https://huggingface.co/StanfordAIMI/XraySigLIP__vit-b-16__laion2b-s34b-b88k
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xraysiglip__vit_b_16__laion2b_s34b_b88k_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-xraysiglip__vit_b_16__laion2b_s34b_b88k_pipeline_en.md
new file mode 100644
index 00000000000000..b4b618f8ae6d8f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xraysiglip__vit_b_16__laion2b_s34b_b88k_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English xraysiglip__vit_b_16__laion2b_s34b_b88k_pipeline pipeline CLIPForZeroShotClassification from StanfordAIMI
+author: John Snow Labs
+name: xraysiglip__vit_b_16__laion2b_s34b_b88k_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xraysiglip__vit_b_16__laion2b_s34b_b88k_pipeline` is a English model originally trained by StanfordAIMI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xraysiglip__vit_b_16__laion2b_s34b_b88k_pipeline_en_5.5.1_3.0_1737631748985.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xraysiglip__vit_b_16__laion2b_s34b_b88k_pipeline_en_5.5.1_3.0_1737631748985.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xraysiglip__vit_b_16__laion2b_s34b_b88k_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xraysiglip__vit_b_16__laion2b_s34b_b88k_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xraysiglip__vit_b_16__laion2b_s34b_b88k_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|564.3 MB|
+
+## References
+
+https://huggingface.co/StanfordAIMI/XraySigLIP__vit-b-16__laion2b-s34b-b88k
+
+## Included Models
+
+- ImageAssembler
+- CLIPForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xraysiglip__vit_l_14__laion2b_s32b_b82k_en.md b/docs/_posts/ahmedlone127/2025-01-23-xraysiglip__vit_l_14__laion2b_s32b_b82k_en.md
new file mode 100644
index 00000000000000..73535eac4b4293
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xraysiglip__vit_l_14__laion2b_s32b_b82k_en.md
@@ -0,0 +1,120 @@
+---
+layout: model
+title: English xraysiglip__vit_l_14__laion2b_s32b_b82k CLIPForZeroShotClassification from StanfordAIMI
+author: John Snow Labs
+name: xraysiglip__vit_l_14__laion2b_s32b_b82k
+date: 2025-01-23
+tags: [en, open_source, onnx, zero_shot, clip, image]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CLIPForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xraysiglip__vit_l_14__laion2b_s32b_b82k` is a English model originally trained by StanfordAIMI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xraysiglip__vit_l_14__laion2b_s32b_b82k_en_5.5.1_3.0_1737629672045.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xraysiglip__vit_l_14__laion2b_s32b_b82k_en_5.5.1_3.0_1737629672045.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+imageDF = spark.read \
+    .format("image") \
+    .option("dropInvalid", value = True) \
+    .load("src/test/resources/image/")
+    
+candidateLabels = [
+    "a photo of a bird",
+    "a photo of a cat",
+    "a photo of a dog",
+    "a photo of a hen",
+    "a photo of a hippo",
+    "a photo of a room",
+    "a photo of a tractor",
+    "a photo of an ostrich",
+    "a photo of an ox"]
+
+ImageAssembler = ImageAssembler() \
+	.setInputCol("image") \
+	.setOutputCol("image_assembler")
+
+imageClassifier = CLIPForZeroShotClassification.pretrained("xraysiglip__vit_l_14__laion2b_s32b_b82k","en") \
+     .setInputCols(["image_assembler"]) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+
+pipeline = Pipeline().setStages([ImageAssembler, imageClassifier])
+pipelineModel = pipeline.fit(imageDF)
+pipelineDF = pipelineModel.transform(imageDF)
+
+
+```
+```scala
+
+		
+val imageDF = ResourceHelper.spark.read
+  .format("image")
+  .option("dropInvalid", value = true)
+  .load("src/test/resources/image/")
+
+val candidateLabels = Array(
+  "a photo of a bird",
+  "a photo of a cat",
+  "a photo of a dog",
+  "a photo of a hen",
+  "a photo of a hippo",
+  "a photo of a room",
+  "a photo of a tractor",
+  "a photo of an ostrich",
+  "a photo of an ox")
+
+val imageAssembler = new ImageAssembler()
+  .setInputCol("image")
+  .setOutputCol("image_assembler")
+  
+val imageClassifier = CLIPForZeroShotClassification.pretrained("xraysiglip__vit_l_14__laion2b_s32b_b82k","en") \
+     .setInputCols(Array("image_assembler")) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+  
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+val pipelineModel = pipeline.fit(imageDF)
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xraysiglip__vit_l_14__laion2b_s32b_b82k|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/StanfordAIMI/XraySigLIP__vit-l-14__laion2b-s32b-b82k
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-23-xraysiglip__vit_l_14__laion2b_s32b_b82k_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-23-xraysiglip__vit_l_14__laion2b_s32b_b82k_pipeline_en.md
new file mode 100644
index 00000000000000..de59938a93ee5d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-23-xraysiglip__vit_l_14__laion2b_s32b_b82k_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English xraysiglip__vit_l_14__laion2b_s32b_b82k_pipeline pipeline CLIPForZeroShotClassification from StanfordAIMI
+author: John Snow Labs
+name: xraysiglip__vit_l_14__laion2b_s32b_b82k_pipeline
+date: 2025-01-23
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xraysiglip__vit_l_14__laion2b_s32b_b82k_pipeline` is a English model originally trained by StanfordAIMI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xraysiglip__vit_l_14__laion2b_s32b_b82k_pipeline_en_5.5.1_3.0_1737629752291.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xraysiglip__vit_l_14__laion2b_s32b_b82k_pipeline_en_5.5.1_3.0_1737629752291.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xraysiglip__vit_l_14__laion2b_s32b_b82k_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xraysiglip__vit_l_14__laion2b_s32b_b82k_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xraysiglip__vit_l_14__laion2b_s32b_b82k_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/StanfordAIMI/XraySigLIP__vit-l-14__laion2b-s32b-b82k
+
+## Included Models
+
+- ImageAssembler
+- CLIPForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-08062024v1swin_tiny_patch4_window7_224_finetuned_eurosat_en.md b/docs/_posts/ahmedlone127/2025-01-24-08062024v1swin_tiny_patch4_window7_224_finetuned_eurosat_en.md
new file mode 100644
index 00000000000000..b46ac6ed62a8cc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-08062024v1swin_tiny_patch4_window7_224_finetuned_eurosat_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English 08062024v1swin_tiny_patch4_window7_224_finetuned_eurosat SwinForImageClassification from Larbz-7
+author: John Snow Labs
+name: 08062024v1swin_tiny_patch4_window7_224_finetuned_eurosat
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`08062024v1swin_tiny_patch4_window7_224_finetuned_eurosat` is a English model originally trained by Larbz-7.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/08062024v1swin_tiny_patch4_window7_224_finetuned_eurosat_en_5.5.1_3.0_1737715430072.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/08062024v1swin_tiny_patch4_window7_224_finetuned_eurosat_en_5.5.1_3.0_1737715430072.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""08062024v1swin_tiny_patch4_window7_224_finetuned_eurosat","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("08062024v1swin_tiny_patch4_window7_224_finetuned_eurosat","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|08062024v1swin_tiny_patch4_window7_224_finetuned_eurosat|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/Larbz-7/08062024v1swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-08062024v1swin_tiny_patch4_window7_224_finetuned_eurosat_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-08062024v1swin_tiny_patch4_window7_224_finetuned_eurosat_pipeline_en.md
new file mode 100644
index 00000000000000..331362a9d1c128
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-08062024v1swin_tiny_patch4_window7_224_finetuned_eurosat_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English 08062024v1swin_tiny_patch4_window7_224_finetuned_eurosat_pipeline pipeline SwinForImageClassification from Larbz-7
+author: John Snow Labs
+name: 08062024v1swin_tiny_patch4_window7_224_finetuned_eurosat_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`08062024v1swin_tiny_patch4_window7_224_finetuned_eurosat_pipeline` is a English model originally trained by Larbz-7.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/08062024v1swin_tiny_patch4_window7_224_finetuned_eurosat_pipeline_en_5.5.1_3.0_1737715441222.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/08062024v1swin_tiny_patch4_window7_224_finetuned_eurosat_pipeline_en_5.5.1_3.0_1737715441222.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("08062024v1swin_tiny_patch4_window7_224_finetuned_eurosat_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("08062024v1swin_tiny_patch4_window7_224_finetuned_eurosat_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|08062024v1swin_tiny_patch4_window7_224_finetuned_eurosat_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/Larbz-7/08062024v1swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-111m_en.md b/docs/_posts/ahmedlone127/2025-01-24-111m_en.md
new file mode 100644
index 00000000000000..2c82ebbfc3a9bb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-111m_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English 111m GPT2Transformer from Corianas
+author: John Snow Labs
+name: 111m
+date: 2025-01-24
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`111m` is a English model originally trained by Corianas.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/111m_en_5.5.1_3.0_1737718652950.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/111m_en_5.5.1_3.0_1737718652950.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("111m","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("111m","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|111m|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|213.1 MB|
+
+## References
+
+https://huggingface.co/Corianas/111m
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-111m_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-111m_pipeline_en.md
new file mode 100644
index 00000000000000..0a7d9b16443cac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-111m_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English 111m_pipeline pipeline GPT2Transformer from Corianas
+author: John Snow Labs
+name: 111m_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`111m_pipeline` is a English model originally trained by Corianas.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/111m_pipeline_en_5.5.1_3.0_1737718724995.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/111m_pipeline_en_5.5.1_3.0_1737718724995.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("111m_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("111m_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|111m_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|213.2 MB|
+
+## References
+
+https://huggingface.co/Corianas/111m
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-20230813045211_en.md b/docs/_posts/ahmedlone127/2025-01-24-20230813045211_en.md
new file mode 100644
index 00000000000000..9cc8fbe9ad6566
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-20230813045211_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English 20230813045211 BertForQuestionAnswering from dkqjrm
+author: John Snow Labs
+name: 20230813045211
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`20230813045211` is a English model originally trained by dkqjrm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/20230813045211_en_5.5.1_3.0_1737690572742.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/20230813045211_en_5.5.1_3.0_1737690572742.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("20230813045211","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("20230813045211", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|20230813045211|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/dkqjrm/20230813045211
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-20230813045211_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-20230813045211_pipeline_en.md
new file mode 100644
index 00000000000000..e1c49b41a52275
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-20230813045211_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English 20230813045211_pipeline pipeline BertForQuestionAnswering from dkqjrm
+author: John Snow Labs
+name: 20230813045211_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`20230813045211_pipeline` is a English model originally trained by dkqjrm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/20230813045211_pipeline_en_5.5.1_3.0_1737690640142.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/20230813045211_pipeline_en_5.5.1_3.0_1737690640142.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("20230813045211_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("20230813045211_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|20230813045211_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/dkqjrm/20230813045211
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-adminbert_16gb_fr.md b/docs/_posts/ahmedlone127/2025-01-24-adminbert_16gb_fr.md
new file mode 100644
index 00000000000000..af38261823ffc2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-adminbert_16gb_fr.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: French adminbert_16gb CamemBertEmbeddings from taln-ls2n
+author: John Snow Labs
+name: adminbert_16gb
+date: 2025-01-24
+tags: [fr, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: fr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`adminbert_16gb` is a French model originally trained by taln-ls2n.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/adminbert_16gb_fr_5.5.1_3.0_1737695378276.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/adminbert_16gb_fr_5.5.1_3.0_1737695378276.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("adminbert_16gb","fr") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("adminbert_16gb","fr") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|adminbert_16gb|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|fr|
+|Size:|412.9 MB|
+
+## References
+
+https://huggingface.co/taln-ls2n/AdminBERT-16GB
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-adminbert_16gb_pipeline_fr.md b/docs/_posts/ahmedlone127/2025-01-24-adminbert_16gb_pipeline_fr.md
new file mode 100644
index 00000000000000..adb90b092c7292
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-adminbert_16gb_pipeline_fr.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: French adminbert_16gb_pipeline pipeline CamemBertEmbeddings from taln-ls2n
+author: John Snow Labs
+name: adminbert_16gb_pipeline
+date: 2025-01-24
+tags: [fr, open_source, pipeline, onnx]
+task: Embeddings
+language: fr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`adminbert_16gb_pipeline` is a French model originally trained by taln-ls2n.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/adminbert_16gb_pipeline_fr_5.5.1_3.0_1737695400739.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/adminbert_16gb_pipeline_fr_5.5.1_3.0_1737695400739.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("adminbert_16gb_pipeline", lang = "fr")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("adminbert_16gb_pipeline", lang = "fr")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|adminbert_16gb_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|fr|
+|Size:|412.9 MB|
+
+## References
+
+https://huggingface.co/taln-ls2n/AdminBERT-16GB
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-adminbert_4gb_fr.md b/docs/_posts/ahmedlone127/2025-01-24-adminbert_4gb_fr.md
new file mode 100644
index 00000000000000..98712b09d09af0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-adminbert_4gb_fr.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: French adminbert_4gb CamemBertEmbeddings from taln-ls2n
+author: John Snow Labs
+name: adminbert_4gb
+date: 2025-01-24
+tags: [fr, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: fr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`adminbert_4gb` is a French model originally trained by taln-ls2n.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/adminbert_4gb_fr_5.5.1_3.0_1737696819391.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/adminbert_4gb_fr_5.5.1_3.0_1737696819391.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("adminbert_4gb","fr") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("adminbert_4gb","fr") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|adminbert_4gb|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|fr|
+|Size:|412.8 MB|
+
+## References
+
+https://huggingface.co/taln-ls2n/AdminBERT-4GB
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-adminbert_4gb_pipeline_fr.md b/docs/_posts/ahmedlone127/2025-01-24-adminbert_4gb_pipeline_fr.md
new file mode 100644
index 00000000000000..8ce23e7259cc5b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-adminbert_4gb_pipeline_fr.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: French adminbert_4gb_pipeline pipeline CamemBertEmbeddings from taln-ls2n
+author: John Snow Labs
+name: adminbert_4gb_pipeline
+date: 2025-01-24
+tags: [fr, open_source, pipeline, onnx]
+task: Embeddings
+language: fr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`adminbert_4gb_pipeline` is a French model originally trained by taln-ls2n.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/adminbert_4gb_pipeline_fr_5.5.1_3.0_1737696840847.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/adminbert_4gb_pipeline_fr_5.5.1_3.0_1737696840847.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("adminbert_4gb_pipeline", lang = "fr")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("adminbert_4gb_pipeline", lang = "fr")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|adminbert_4gb_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|fr|
+|Size:|412.8 MB|
+
+## References
+
+https://huggingface.co/taln-ls2n/AdminBERT-4GB
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-affilgood_span_v2_en.md b/docs/_posts/ahmedlone127/2025-01-24-affilgood_span_v2_en.md
new file mode 100644
index 00000000000000..94576d7995c3b8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-affilgood_span_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English affilgood_span_v2 RoBertaForTokenClassification from nicolauduran45
+author: John Snow Labs
+name: affilgood_span_v2
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`affilgood_span_v2` is a English model originally trained by nicolauduran45.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/affilgood_span_v2_en_5.5.1_3.0_1737686136288.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/affilgood_span_v2_en_5.5.1_3.0_1737686136288.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("affilgood_span_v2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("affilgood_span_v2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|affilgood_span_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|466.2 MB|
+
+## References
+
+https://huggingface.co/nicolauduran45/affilgood-span-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-affilgood_span_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-affilgood_span_v2_pipeline_en.md
new file mode 100644
index 00000000000000..d800d8fb78cfb8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-affilgood_span_v2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English affilgood_span_v2_pipeline pipeline RoBertaForTokenClassification from nicolauduran45
+author: John Snow Labs
+name: affilgood_span_v2_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`affilgood_span_v2_pipeline` is a English model originally trained by nicolauduran45.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/affilgood_span_v2_pipeline_en_5.5.1_3.0_1737686160471.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/affilgood_span_v2_pipeline_en_5.5.1_3.0_1737686160471.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("affilgood_span_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("affilgood_span_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|affilgood_span_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.3 MB|
+
+## References
+
+https://huggingface.co/nicolauduran45/affilgood-span-v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-afriberta_large_finetuned_hausa_2e_3_en.md b/docs/_posts/ahmedlone127/2025-01-24-afriberta_large_finetuned_hausa_2e_3_en.md
new file mode 100644
index 00000000000000..beba17df1be42b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-afriberta_large_finetuned_hausa_2e_3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English afriberta_large_finetuned_hausa_2e_3 XlmRoBertaForTokenClassification from grace-pro
+author: John Snow Labs
+name: afriberta_large_finetuned_hausa_2e_3
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`afriberta_large_finetuned_hausa_2e_3` is a English model originally trained by grace-pro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/afriberta_large_finetuned_hausa_2e_3_en_5.5.1_3.0_1737680949447.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/afriberta_large_finetuned_hausa_2e_3_en_5.5.1_3.0_1737680949447.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("afriberta_large_finetuned_hausa_2e_3","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("afriberta_large_finetuned_hausa_2e_3", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|afriberta_large_finetuned_hausa_2e_3|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|468.4 MB|
+
+## References
+
+https://huggingface.co/grace-pro/afriberta-large-finetuned-hausa-2e-3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-afriberta_large_finetuned_hausa_2e_3_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-afriberta_large_finetuned_hausa_2e_3_pipeline_en.md
new file mode 100644
index 00000000000000..fcb6836518c62a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-afriberta_large_finetuned_hausa_2e_3_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English afriberta_large_finetuned_hausa_2e_3_pipeline pipeline XlmRoBertaForTokenClassification from grace-pro
+author: John Snow Labs
+name: afriberta_large_finetuned_hausa_2e_3_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`afriberta_large_finetuned_hausa_2e_3_pipeline` is a English model originally trained by grace-pro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/afriberta_large_finetuned_hausa_2e_3_pipeline_en_5.5.1_3.0_1737680975434.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/afriberta_large_finetuned_hausa_2e_3_pipeline_en_5.5.1_3.0_1737680975434.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("afriberta_large_finetuned_hausa_2e_3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("afriberta_large_finetuned_hausa_2e_3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|afriberta_large_finetuned_hausa_2e_3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|468.4 MB|
+
+## References
+
+https://huggingface.co/grace-pro/afriberta-large-finetuned-hausa-2e-3
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-aiornot_en.md b/docs/_posts/ahmedlone127/2025-01-24-aiornot_en.md
new file mode 100644
index 00000000000000..60fa85a7423277
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-aiornot_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English aiornot SwinForImageClassification from Nahrawy
+author: John Snow Labs
+name: aiornot
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`aiornot` is a English model originally trained by Nahrawy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/aiornot_en_5.5.1_3.0_1737694452539.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/aiornot_en_5.5.1_3.0_1737694452539.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""aiornot","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("aiornot","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|aiornot|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/Nahrawy/AIorNot
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-aiornot_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-aiornot_pipeline_en.md
new file mode 100644
index 00000000000000..65cb035962efc9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-aiornot_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English aiornot_pipeline pipeline SwinForImageClassification from Nahrawy
+author: John Snow Labs
+name: aiornot_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`aiornot_pipeline` is a English model originally trained by Nahrawy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/aiornot_pipeline_en_5.5.1_3.0_1737694464062.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/aiornot_pipeline_en_5.5.1_3.0_1737694464062.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("aiornot_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("aiornot_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|aiornot_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/Nahrawy/AIorNot
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-albert_base_v2_v1_en.md b/docs/_posts/ahmedlone127/2025-01-24-albert_base_v2_v1_en.md
new file mode 100644
index 00000000000000..1bd871f22de799
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-albert_base_v2_v1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English albert_base_v2_v1 AlbertForSequenceClassification from csha21047
+author: John Snow Labs
+name: albert_base_v2_v1
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, albert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_v2_v1` is a English model originally trained by csha21047.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_v2_v1_en_5.5.1_3.0_1737750154354.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_v2_v1_en_5.5.1_3.0_1737750154354.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = AlbertForSequenceClassification.pretrained("albert_base_v2_v1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = AlbertForSequenceClassification.pretrained("albert_base_v2_v1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_base_v2_v1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/csha21047/ALBERT-base-v2-v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-albert_base_v2_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-albert_base_v2_v1_pipeline_en.md
new file mode 100644
index 00000000000000..97889092223f64
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-albert_base_v2_v1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English albert_base_v2_v1_pipeline pipeline AlbertForSequenceClassification from csha21047
+author: John Snow Labs
+name: albert_base_v2_v1_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_v2_v1_pipeline` is a English model originally trained by csha21047.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_v2_v1_pipeline_en_5.5.1_3.0_1737750156816.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_v2_v1_pipeline_en_5.5.1_3.0_1737750156816.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("albert_base_v2_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("albert_base_v2_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_base_v2_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/csha21047/ALBERT-base-v2-v1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-albert_dataset2_en.md b/docs/_posts/ahmedlone127/2025-01-24-albert_dataset2_en.md
new file mode 100644
index 00000000000000..2b83eb00a24481
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-albert_dataset2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English albert_dataset2 AlbertForSequenceClassification from aminajunaid0
+author: John Snow Labs
+name: albert_dataset2
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, albert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_dataset2` is a English model originally trained by aminajunaid0.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_dataset2_en_5.5.1_3.0_1737750302103.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_dataset2_en_5.5.1_3.0_1737750302103.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = AlbertForSequenceClassification.pretrained("albert_dataset2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = AlbertForSequenceClassification.pretrained("albert_dataset2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_dataset2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/aminajunaid0/Albert_Dataset2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-albert_dataset2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-albert_dataset2_pipeline_en.md
new file mode 100644
index 00000000000000..03d70dca79d95a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-albert_dataset2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English albert_dataset2_pipeline pipeline AlbertForSequenceClassification from aminajunaid0
+author: John Snow Labs
+name: albert_dataset2_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_dataset2_pipeline` is a English model originally trained by aminajunaid0.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_dataset2_pipeline_en_5.5.1_3.0_1737750304789.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_dataset2_pipeline_en_5.5.1_3.0_1737750304789.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("albert_dataset2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("albert_dataset2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_dataset2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|44.3 MB|
+
+## References
+
+https://huggingface.co/aminajunaid0/Albert_Dataset2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-albert_emotions_big_en.md b/docs/_posts/ahmedlone127/2025-01-24-albert_emotions_big_en.md
new file mode 100644
index 00000000000000..ec6ac025e5d5b9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-albert_emotions_big_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English albert_emotions_big AlbertForSequenceClassification from lewin003
+author: John Snow Labs
+name: albert_emotions_big
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, albert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_emotions_big` is a English model originally trained by lewin003.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_emotions_big_en_5.5.1_3.0_1737750219511.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_emotions_big_en_5.5.1_3.0_1737750219511.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = AlbertForSequenceClassification.pretrained("albert_emotions_big","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = AlbertForSequenceClassification.pretrained("albert_emotions_big", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_emotions_big|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/lewin003/albert-emotions-big
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-albert_emotions_big_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-albert_emotions_big_pipeline_en.md
new file mode 100644
index 00000000000000..c7db7947c34a38
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-albert_emotions_big_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English albert_emotions_big_pipeline pipeline AlbertForSequenceClassification from lewin003
+author: John Snow Labs
+name: albert_emotions_big_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_emotions_big_pipeline` is a English model originally trained by lewin003.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_emotions_big_pipeline_en_5.5.1_3.0_1737750221961.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_emotions_big_pipeline_en_5.5.1_3.0_1737750221961.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("albert_emotions_big_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("albert_emotions_big_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_emotions_big_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|44.3 MB|
+
+## References
+
+https://huggingface.co/lewin003/albert-emotions-big
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-albert_emotions_small_en.md b/docs/_posts/ahmedlone127/2025-01-24-albert_emotions_small_en.md
new file mode 100644
index 00000000000000..009ab0519cb5ab
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-albert_emotions_small_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English albert_emotions_small AlbertForSequenceClassification from lewin003
+author: John Snow Labs
+name: albert_emotions_small
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, albert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_emotions_small` is a English model originally trained by lewin003.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_emotions_small_en_5.5.1_3.0_1737692992323.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_emotions_small_en_5.5.1_3.0_1737692992323.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = AlbertForSequenceClassification.pretrained("albert_emotions_small","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = AlbertForSequenceClassification.pretrained("albert_emotions_small", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_emotions_small|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/lewin003/albert-emotions-small
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-albert_emotions_small_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-albert_emotions_small_pipeline_en.md
new file mode 100644
index 00000000000000..d91706dfa20caf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-albert_emotions_small_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English albert_emotions_small_pipeline pipeline AlbertForSequenceClassification from lewin003
+author: John Snow Labs
+name: albert_emotions_small_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_emotions_small_pipeline` is a English model originally trained by lewin003.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_emotions_small_pipeline_en_5.5.1_3.0_1737692994670.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_emotions_small_pipeline_en_5.5.1_3.0_1737692994670.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("albert_emotions_small_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("albert_emotions_small_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_emotions_small_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|44.3 MB|
+
+## References
+
+https://huggingface.co/lewin003/albert-emotions-small
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-albert_frugal_ai_challenge_en.md b/docs/_posts/ahmedlone127/2025-01-24-albert_frugal_ai_challenge_en.md
new file mode 100644
index 00000000000000..5c9a3e61fc0051
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-albert_frugal_ai_challenge_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English albert_frugal_ai_challenge AlbertForSequenceClassification from maianume
+author: John Snow Labs
+name: albert_frugal_ai_challenge
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, albert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_frugal_ai_challenge` is a English model originally trained by maianume.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_frugal_ai_challenge_en_5.5.1_3.0_1737750499444.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_frugal_ai_challenge_en_5.5.1_3.0_1737750499444.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = AlbertForSequenceClassification.pretrained("albert_frugal_ai_challenge","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = AlbertForSequenceClassification.pretrained("albert_frugal_ai_challenge", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_frugal_ai_challenge|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/maianume/albert-frugal-ai-challenge
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-albert_frugal_ai_challenge_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-albert_frugal_ai_challenge_pipeline_en.md
new file mode 100644
index 00000000000000..c1da0bf0f30859
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-albert_frugal_ai_challenge_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English albert_frugal_ai_challenge_pipeline pipeline AlbertForSequenceClassification from maianume
+author: John Snow Labs
+name: albert_frugal_ai_challenge_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_frugal_ai_challenge_pipeline` is a English model originally trained by maianume.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_frugal_ai_challenge_pipeline_en_5.5.1_3.0_1737750501709.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_frugal_ai_challenge_pipeline_en_5.5.1_3.0_1737750501709.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("albert_frugal_ai_challenge_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("albert_frugal_ai_challenge_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_frugal_ai_challenge_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|44.3 MB|
+
+## References
+
+https://huggingface.co/maianume/albert-frugal-ai-challenge
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-albert_squad_en.md b/docs/_posts/ahmedlone127/2025-01-24-albert_squad_en.md
new file mode 100644
index 00000000000000..171315184c4e1b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-albert_squad_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English albert_squad AlbertForQuestionAnswering from Sadat07
+author: John Snow Labs
+name: albert_squad
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, albert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_squad` is a English model originally trained by Sadat07.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_squad_en_5.5.1_3.0_1737709288422.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_squad_en_5.5.1_3.0_1737709288422.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = AlbertForQuestionAnswering.pretrained("albert_squad","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = AlbertForQuestionAnswering.pretrained("albert_squad", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_squad|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|62.7 MB|
+
+## References
+
+https://huggingface.co/Sadat07/albert_Squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-albert_squad_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-albert_squad_pipeline_en.md
new file mode 100644
index 00000000000000..9bff975ae111c3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-albert_squad_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English albert_squad_pipeline pipeline AlbertForQuestionAnswering from Sadat07
+author: John Snow Labs
+name: albert_squad_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_squad_pipeline` is a English model originally trained by Sadat07.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_squad_pipeline_en_5.5.1_3.0_1737709291584.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_squad_pipeline_en_5.5.1_3.0_1737709291584.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("albert_squad_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("albert_squad_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_squad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|62.8 MB|
+
+## References
+
+https://huggingface.co/Sadat07/albert_Squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- AlbertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-all_minilm_l6_v2_personal_project_default_2024_06_07_en.md b/docs/_posts/ahmedlone127/2025-01-24-all_minilm_l6_v2_personal_project_default_2024_06_07_en.md
new file mode 100644
index 00000000000000..0caf026534ed99
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-all_minilm_l6_v2_personal_project_default_2024_06_07_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English all_minilm_l6_v2_personal_project_default_2024_06_07 BertEmbeddings from brugmark
+author: John Snow Labs
+name: all_minilm_l6_v2_personal_project_default_2024_06_07
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_minilm_l6_v2_personal_project_default_2024_06_07` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_default_2024_06_07_en_5.5.1_3.0_1737708443984.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_default_2024_06_07_en_5.5.1_3.0_1737708443984.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("all_minilm_l6_v2_personal_project_default_2024_06_07","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("all_minilm_l6_v2_personal_project_default_2024_06_07","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_minilm_l6_v2_personal_project_default_2024_06_07|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|83.9 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-default-2024-06-07
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-all_minilm_l6_v2_personal_project_default_2024_06_07_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-all_minilm_l6_v2_personal_project_default_2024_06_07_pipeline_en.md
new file mode 100644
index 00000000000000..d91d317f905348
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-all_minilm_l6_v2_personal_project_default_2024_06_07_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English all_minilm_l6_v2_personal_project_default_2024_06_07_pipeline pipeline BertEmbeddings from brugmark
+author: John Snow Labs
+name: all_minilm_l6_v2_personal_project_default_2024_06_07_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_minilm_l6_v2_personal_project_default_2024_06_07_pipeline` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_default_2024_06_07_pipeline_en_5.5.1_3.0_1737708449061.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_default_2024_06_07_pipeline_en_5.5.1_3.0_1737708449061.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("all_minilm_l6_v2_personal_project_default_2024_06_07_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("all_minilm_l6_v2_personal_project_default_2024_06_07_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_minilm_l6_v2_personal_project_default_2024_06_07_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|83.9 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-default-2024-06-07
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-all_minilm_l6_v2_personal_project_default_2024_06_17_en.md b/docs/_posts/ahmedlone127/2025-01-24-all_minilm_l6_v2_personal_project_default_2024_06_17_en.md
new file mode 100644
index 00000000000000..d031f7c6d2d4c6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-all_minilm_l6_v2_personal_project_default_2024_06_17_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English all_minilm_l6_v2_personal_project_default_2024_06_17 BertEmbeddings from brugmark
+author: John Snow Labs
+name: all_minilm_l6_v2_personal_project_default_2024_06_17
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_minilm_l6_v2_personal_project_default_2024_06_17` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_default_2024_06_17_en_5.5.1_3.0_1737708358321.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_default_2024_06_17_en_5.5.1_3.0_1737708358321.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("all_minilm_l6_v2_personal_project_default_2024_06_17","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("all_minilm_l6_v2_personal_project_default_2024_06_17","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_minilm_l6_v2_personal_project_default_2024_06_17|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|83.9 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-default-2024-06-17
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-all_minilm_l6_v2_personal_project_default_2024_06_17_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-all_minilm_l6_v2_personal_project_default_2024_06_17_pipeline_en.md
new file mode 100644
index 00000000000000..219668b5335457
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-all_minilm_l6_v2_personal_project_default_2024_06_17_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English all_minilm_l6_v2_personal_project_default_2024_06_17_pipeline pipeline BertEmbeddings from brugmark
+author: John Snow Labs
+name: all_minilm_l6_v2_personal_project_default_2024_06_17_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_minilm_l6_v2_personal_project_default_2024_06_17_pipeline` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_default_2024_06_17_pipeline_en_5.5.1_3.0_1737708362850.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_default_2024_06_17_pipeline_en_5.5.1_3.0_1737708362850.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("all_minilm_l6_v2_personal_project_default_2024_06_17_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("all_minilm_l6_v2_personal_project_default_2024_06_17_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_minilm_l6_v2_personal_project_default_2024_06_17_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|83.9 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-default-2024-06-17
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-all_minilm_l6_v2_personal_project_finetuned_2024_05_31_en.md b/docs/_posts/ahmedlone127/2025-01-24-all_minilm_l6_v2_personal_project_finetuned_2024_05_31_en.md
new file mode 100644
index 00000000000000..fc6680f1cf0f4b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-all_minilm_l6_v2_personal_project_finetuned_2024_05_31_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English all_minilm_l6_v2_personal_project_finetuned_2024_05_31 BertEmbeddings from brugmark
+author: John Snow Labs
+name: all_minilm_l6_v2_personal_project_finetuned_2024_05_31
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_minilm_l6_v2_personal_project_finetuned_2024_05_31` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_finetuned_2024_05_31_en_5.5.1_3.0_1737742661867.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_finetuned_2024_05_31_en_5.5.1_3.0_1737742661867.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("all_minilm_l6_v2_personal_project_finetuned_2024_05_31","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("all_minilm_l6_v2_personal_project_finetuned_2024_05_31","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_minilm_l6_v2_personal_project_finetuned_2024_05_31|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|81.7 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-finetuned-2024-05-31
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-all_minilm_l6_v2_personal_project_finetuned_2024_05_31_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-all_minilm_l6_v2_personal_project_finetuned_2024_05_31_pipeline_en.md
new file mode 100644
index 00000000000000..6db88891499f58
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-all_minilm_l6_v2_personal_project_finetuned_2024_05_31_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English all_minilm_l6_v2_personal_project_finetuned_2024_05_31_pipeline pipeline BertEmbeddings from brugmark
+author: John Snow Labs
+name: all_minilm_l6_v2_personal_project_finetuned_2024_05_31_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_minilm_l6_v2_personal_project_finetuned_2024_05_31_pipeline` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_finetuned_2024_05_31_pipeline_en_5.5.1_3.0_1737742666797.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_finetuned_2024_05_31_pipeline_en_5.5.1_3.0_1737742666797.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("all_minilm_l6_v2_personal_project_finetuned_2024_05_31_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("all_minilm_l6_v2_personal_project_finetuned_2024_05_31_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_minilm_l6_v2_personal_project_finetuned_2024_05_31_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|81.7 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-finetuned-2024-05-31
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-all_minilm_l6_v2_personal_project_finetuned_2024_06_05_en.md b/docs/_posts/ahmedlone127/2025-01-24-all_minilm_l6_v2_personal_project_finetuned_2024_06_05_en.md
new file mode 100644
index 00000000000000..4bd124e2c587c6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-all_minilm_l6_v2_personal_project_finetuned_2024_06_05_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English all_minilm_l6_v2_personal_project_finetuned_2024_06_05 BertEmbeddings from brugmark
+author: John Snow Labs
+name: all_minilm_l6_v2_personal_project_finetuned_2024_06_05
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_minilm_l6_v2_personal_project_finetuned_2024_06_05` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_finetuned_2024_06_05_en_5.5.1_3.0_1737707803575.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_finetuned_2024_06_05_en_5.5.1_3.0_1737707803575.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("all_minilm_l6_v2_personal_project_finetuned_2024_06_05","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("all_minilm_l6_v2_personal_project_finetuned_2024_06_05","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_minilm_l6_v2_personal_project_finetuned_2024_06_05|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|80.2 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-finetuned-2024-06-05
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-all_minilm_l6_v2_personal_project_finetuned_2024_06_05_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-all_minilm_l6_v2_personal_project_finetuned_2024_06_05_pipeline_en.md
new file mode 100644
index 00000000000000..b4848722015644
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-all_minilm_l6_v2_personal_project_finetuned_2024_06_05_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English all_minilm_l6_v2_personal_project_finetuned_2024_06_05_pipeline pipeline BertEmbeddings from brugmark
+author: John Snow Labs
+name: all_minilm_l6_v2_personal_project_finetuned_2024_06_05_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_minilm_l6_v2_personal_project_finetuned_2024_06_05_pipeline` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_finetuned_2024_06_05_pipeline_en_5.5.1_3.0_1737707808589.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_finetuned_2024_06_05_pipeline_en_5.5.1_3.0_1737707808589.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("all_minilm_l6_v2_personal_project_finetuned_2024_06_05_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("all_minilm_l6_v2_personal_project_finetuned_2024_06_05_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_minilm_l6_v2_personal_project_finetuned_2024_06_05_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|80.2 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-finetuned-2024-06-05
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-armature_defect_detection_resin_en.md b/docs/_posts/ahmedlone127/2025-01-24-armature_defect_detection_resin_en.md
new file mode 100644
index 00000000000000..a51e5a1cee5a4c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-armature_defect_detection_resin_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English armature_defect_detection_resin SwinForImageClassification from Devarshi
+author: John Snow Labs
+name: armature_defect_detection_resin
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`armature_defect_detection_resin` is a English model originally trained by Devarshi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/armature_defect_detection_resin_en_5.5.1_3.0_1737754632861.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/armature_defect_detection_resin_en_5.5.1_3.0_1737754632861.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""armature_defect_detection_resin","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("armature_defect_detection_resin","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|armature_defect_detection_resin|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|649.8 MB|
+
+## References
+
+https://huggingface.co/Devarshi/Armature_Defect_Detection_Resin
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-armature_defect_detection_resin_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-armature_defect_detection_resin_pipeline_en.md
new file mode 100644
index 00000000000000..51d2800f5386fa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-armature_defect_detection_resin_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English armature_defect_detection_resin_pipeline pipeline SwinForImageClassification from Devarshi
+author: John Snow Labs
+name: armature_defect_detection_resin_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`armature_defect_detection_resin_pipeline` is a English model originally trained by Devarshi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/armature_defect_detection_resin_pipeline_en_5.5.1_3.0_1737754669874.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/armature_defect_detection_resin_pipeline_en_5.5.1_3.0_1737754669874.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("armature_defect_detection_resin_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("armature_defect_detection_resin_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|armature_defect_detection_resin_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|649.8 MB|
+
+## References
+
+https://huggingface.co/Devarshi/Armature_Defect_Detection_Resin
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-arxiv_nlp_en.md b/docs/_posts/ahmedlone127/2025-01-24-arxiv_nlp_en.md
new file mode 100644
index 00000000000000..396c6f9c2a38ee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-arxiv_nlp_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English arxiv_nlp GPT2Transformer from lysandre
+author: John Snow Labs
+name: arxiv_nlp
+date: 2025-01-24
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`arxiv_nlp` is a English model originally trained by lysandre.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/arxiv_nlp_en_5.5.1_3.0_1737717157369.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/arxiv_nlp_en_5.5.1_3.0_1737717157369.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("arxiv_nlp","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("arxiv_nlp","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|arxiv_nlp|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/lysandre/arxiv-nlp
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-arxiv_nlp_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-arxiv_nlp_pipeline_en.md
new file mode 100644
index 00000000000000..4f2a4b69249931
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-arxiv_nlp_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English arxiv_nlp_pipeline pipeline GPT2Transformer from lysandre
+author: John Snow Labs
+name: arxiv_nlp_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`arxiv_nlp_pipeline` is a English model originally trained by lysandre.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/arxiv_nlp_pipeline_en_5.5.1_3.0_1737717181678.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/arxiv_nlp_pipeline_en_5.5.1_3.0_1737717181678.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("arxiv_nlp_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("arxiv_nlp_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|arxiv_nlp_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/lysandre/arxiv-nlp
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-autotrain_autotrain_simple_classifierv2_84935142669_en.md b/docs/_posts/ahmedlone127/2025-01-24-autotrain_autotrain_simple_classifierv2_84935142669_en.md
new file mode 100644
index 00000000000000..80c9cc1b1ee7d2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-autotrain_autotrain_simple_classifierv2_84935142669_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English autotrain_autotrain_simple_classifierv2_84935142669 SwinForImageClassification from fsuarez
+author: John Snow Labs
+name: autotrain_autotrain_simple_classifierv2_84935142669
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_autotrain_simple_classifierv2_84935142669` is a English model originally trained by fsuarez.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_autotrain_simple_classifierv2_84935142669_en_5.5.1_3.0_1737715750622.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_autotrain_simple_classifierv2_84935142669_en_5.5.1_3.0_1737715750622.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""autotrain_autotrain_simple_classifierv2_84935142669","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("autotrain_autotrain_simple_classifierv2_84935142669","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_autotrain_simple_classifierv2_84935142669|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/fsuarez/autotrain-autotrain-simple-classifierv2-84935142669
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-autotrain_autotrain_simple_classifierv2_84935142669_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-autotrain_autotrain_simple_classifierv2_84935142669_pipeline_en.md
new file mode 100644
index 00000000000000..ae34108d900124
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-autotrain_autotrain_simple_classifierv2_84935142669_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English autotrain_autotrain_simple_classifierv2_84935142669_pipeline pipeline SwinForImageClassification from fsuarez
+author: John Snow Labs
+name: autotrain_autotrain_simple_classifierv2_84935142669_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_autotrain_simple_classifierv2_84935142669_pipeline` is a English model originally trained by fsuarez.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_autotrain_simple_classifierv2_84935142669_pipeline_en_5.5.1_3.0_1737715761894.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_autotrain_simple_classifierv2_84935142669_pipeline_en_5.5.1_3.0_1737715761894.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("autotrain_autotrain_simple_classifierv2_84935142669_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("autotrain_autotrain_simple_classifierv2_84935142669_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_autotrain_simple_classifierv2_84935142669_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/fsuarez/autotrain-autotrain-simple-classifierv2-84935142669
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-autotrain_brain_80728141573_en.md b/docs/_posts/ahmedlone127/2025-01-24-autotrain_brain_80728141573_en.md
new file mode 100644
index 00000000000000..0d2b592d9328d3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-autotrain_brain_80728141573_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English autotrain_brain_80728141573 SwinForImageClassification from aksrad
+author: John Snow Labs
+name: autotrain_brain_80728141573
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_brain_80728141573` is a English model originally trained by aksrad.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_brain_80728141573_en_5.5.1_3.0_1737754326459.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_brain_80728141573_en_5.5.1_3.0_1737754326459.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""autotrain_brain_80728141573","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("autotrain_brain_80728141573","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_brain_80728141573|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/aksrad/autotrain-brain-80728141573
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-autotrain_brain_80728141573_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-autotrain_brain_80728141573_pipeline_en.md
new file mode 100644
index 00000000000000..21a89aa656f869
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-autotrain_brain_80728141573_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English autotrain_brain_80728141573_pipeline pipeline SwinForImageClassification from aksrad
+author: John Snow Labs
+name: autotrain_brain_80728141573_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_brain_80728141573_pipeline` is a English model originally trained by aksrad.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_brain_80728141573_pipeline_en_5.5.1_3.0_1737754337586.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_brain_80728141573_pipeline_en_5.5.1_3.0_1737754337586.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("autotrain_brain_80728141573_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("autotrain_brain_80728141573_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_brain_80728141573_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/aksrad/autotrain-brain-80728141573
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-autotrain_cat_dog_testing_81779141856_en.md b/docs/_posts/ahmedlone127/2025-01-24-autotrain_cat_dog_testing_81779141856_en.md
new file mode 100644
index 00000000000000..8a7ed082c9341d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-autotrain_cat_dog_testing_81779141856_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English autotrain_cat_dog_testing_81779141856 SwinForImageClassification from hdduytran
+author: John Snow Labs
+name: autotrain_cat_dog_testing_81779141856
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_cat_dog_testing_81779141856` is a English model originally trained by hdduytran.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_cat_dog_testing_81779141856_en_5.5.1_3.0_1737694826890.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_cat_dog_testing_81779141856_en_5.5.1_3.0_1737694826890.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""autotrain_cat_dog_testing_81779141856","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("autotrain_cat_dog_testing_81779141856","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_cat_dog_testing_81779141856|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/hdduytran/autotrain-cat-dog-testing-81779141856
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-autotrain_cat_dog_testing_81779141856_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-autotrain_cat_dog_testing_81779141856_pipeline_en.md
new file mode 100644
index 00000000000000..2847d7080a9e1d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-autotrain_cat_dog_testing_81779141856_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English autotrain_cat_dog_testing_81779141856_pipeline pipeline SwinForImageClassification from hdduytran
+author: John Snow Labs
+name: autotrain_cat_dog_testing_81779141856_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_cat_dog_testing_81779141856_pipeline` is a English model originally trained by hdduytran.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_cat_dog_testing_81779141856_pipeline_en_5.5.1_3.0_1737694837681.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_cat_dog_testing_81779141856_pipeline_en_5.5.1_3.0_1737694837681.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("autotrain_cat_dog_testing_81779141856_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("autotrain_cat_dog_testing_81779141856_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_cat_dog_testing_81779141856_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/hdduytran/autotrain-cat-dog-testing-81779141856
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-autotrain_concordium_dataaset_from_colab_86147143013_en.md b/docs/_posts/ahmedlone127/2025-01-24-autotrain_concordium_dataaset_from_colab_86147143013_en.md
new file mode 100644
index 00000000000000..c9d2f32d6cd2ac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-autotrain_concordium_dataaset_from_colab_86147143013_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English autotrain_concordium_dataaset_from_colab_86147143013 BertForQuestionAnswering from hasle1975
+author: John Snow Labs
+name: autotrain_concordium_dataaset_from_colab_86147143013
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_concordium_dataaset_from_colab_86147143013` is a English model originally trained by hasle1975.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_concordium_dataaset_from_colab_86147143013_en_5.5.1_3.0_1737691132840.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_concordium_dataaset_from_colab_86147143013_en_5.5.1_3.0_1737691132840.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("autotrain_concordium_dataaset_from_colab_86147143013","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("autotrain_concordium_dataaset_from_colab_86147143013", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_concordium_dataaset_from_colab_86147143013|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/hasle1975/autotrain-concordium-dataaset-from-colab-86147143013
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-autotrain_concordium_dataaset_from_colab_86147143013_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-autotrain_concordium_dataaset_from_colab_86147143013_pipeline_en.md
new file mode 100644
index 00000000000000..f728624613de00
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-autotrain_concordium_dataaset_from_colab_86147143013_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English autotrain_concordium_dataaset_from_colab_86147143013_pipeline pipeline BertForQuestionAnswering from hasle1975
+author: John Snow Labs
+name: autotrain_concordium_dataaset_from_colab_86147143013_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_concordium_dataaset_from_colab_86147143013_pipeline` is a English model originally trained by hasle1975.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_concordium_dataaset_from_colab_86147143013_pipeline_en_5.5.1_3.0_1737691155094.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_concordium_dataaset_from_colab_86147143013_pipeline_en_5.5.1_3.0_1737691155094.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("autotrain_concordium_dataaset_from_colab_86147143013_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("autotrain_concordium_dataaset_from_colab_86147143013_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_concordium_dataaset_from_colab_86147143013_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/hasle1975/autotrain-concordium-dataaset-from-colab-86147143013
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-autotrain_docker_check_1_55215128879_en.md b/docs/_posts/ahmedlone127/2025-01-24-autotrain_docker_check_1_55215128879_en.md
new file mode 100644
index 00000000000000..a1297b83886664
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-autotrain_docker_check_1_55215128879_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English autotrain_docker_check_1_55215128879 SwinForImageClassification from ameerazam08
+author: John Snow Labs
+name: autotrain_docker_check_1_55215128879
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_docker_check_1_55215128879` is a English model originally trained by ameerazam08.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_docker_check_1_55215128879_en_5.5.1_3.0_1737715572882.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_docker_check_1_55215128879_en_5.5.1_3.0_1737715572882.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""autotrain_docker_check_1_55215128879","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("autotrain_docker_check_1_55215128879","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_docker_check_1_55215128879|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/ameerazam08/autotrain-docker-check-1-55215128879
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-autotrain_docker_check_1_55215128879_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-autotrain_docker_check_1_55215128879_pipeline_en.md
new file mode 100644
index 00000000000000..84ef2d6d7278c4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-autotrain_docker_check_1_55215128879_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English autotrain_docker_check_1_55215128879_pipeline pipeline SwinForImageClassification from ameerazam08
+author: John Snow Labs
+name: autotrain_docker_check_1_55215128879_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_docker_check_1_55215128879_pipeline` is a English model originally trained by ameerazam08.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_docker_check_1_55215128879_pipeline_en_5.5.1_3.0_1737715584128.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_docker_check_1_55215128879_pipeline_en_5.5.1_3.0_1737715584128.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("autotrain_docker_check_1_55215128879_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("autotrain_docker_check_1_55215128879_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_docker_check_1_55215128879_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/ameerazam08/autotrain-docker-check-1-55215128879
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-autotrain_gracoproducts_85090142696_en.md b/docs/_posts/ahmedlone127/2025-01-24-autotrain_gracoproducts_85090142696_en.md
new file mode 100644
index 00000000000000..382f56d103c2b8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-autotrain_gracoproducts_85090142696_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English autotrain_gracoproducts_85090142696 SwinForImageClassification from sbruksha
+author: John Snow Labs
+name: autotrain_gracoproducts_85090142696
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_gracoproducts_85090142696` is a English model originally trained by sbruksha.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_gracoproducts_85090142696_en_5.5.1_3.0_1737714938672.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_gracoproducts_85090142696_en_5.5.1_3.0_1737714938672.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""autotrain_gracoproducts_85090142696","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("autotrain_gracoproducts_85090142696","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_gracoproducts_85090142696|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/sbruksha/autotrain-gracoproducts-85090142696
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-autotrain_gracoproducts_85090142696_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-autotrain_gracoproducts_85090142696_pipeline_en.md
new file mode 100644
index 00000000000000..18030ea763b1b6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-autotrain_gracoproducts_85090142696_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English autotrain_gracoproducts_85090142696_pipeline pipeline SwinForImageClassification from sbruksha
+author: John Snow Labs
+name: autotrain_gracoproducts_85090142696_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_gracoproducts_85090142696_pipeline` is a English model originally trained by sbruksha.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_gracoproducts_85090142696_pipeline_en_5.5.1_3.0_1737714951139.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_gracoproducts_85090142696_pipeline_en_5.5.1_3.0_1737714951139.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("autotrain_gracoproducts_85090142696_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("autotrain_gracoproducts_85090142696_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_gracoproducts_85090142696_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/sbruksha/autotrain-gracoproducts-85090142696
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-autotrain_lane_center3_89488143942_en.md b/docs/_posts/ahmedlone127/2025-01-24-autotrain_lane_center3_89488143942_en.md
new file mode 100644
index 00000000000000..6081617aa6d031
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-autotrain_lane_center3_89488143942_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English autotrain_lane_center3_89488143942 SwinForImageClassification from reallygoodtechdeals
+author: John Snow Labs
+name: autotrain_lane_center3_89488143942
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_lane_center3_89488143942` is a English model originally trained by reallygoodtechdeals.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_lane_center3_89488143942_en_5.5.1_3.0_1737715051446.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_lane_center3_89488143942_en_5.5.1_3.0_1737715051446.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""autotrain_lane_center3_89488143942","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("autotrain_lane_center3_89488143942","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_lane_center3_89488143942|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/reallygoodtechdeals/autotrain-lane-center3-89488143942
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-autotrain_lane_center3_89488143942_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-autotrain_lane_center3_89488143942_pipeline_en.md
new file mode 100644
index 00000000000000..5db09bbf610a27
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-autotrain_lane_center3_89488143942_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English autotrain_lane_center3_89488143942_pipeline pipeline SwinForImageClassification from reallygoodtechdeals
+author: John Snow Labs
+name: autotrain_lane_center3_89488143942_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_lane_center3_89488143942_pipeline` is a English model originally trained by reallygoodtechdeals.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_lane_center3_89488143942_pipeline_en_5.5.1_3.0_1737715063744.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_lane_center3_89488143942_pipeline_en_5.5.1_3.0_1737715063744.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("autotrain_lane_center3_89488143942_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("autotrain_lane_center3_89488143942_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_lane_center3_89488143942_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/reallygoodtechdeals/autotrain-lane-center3-89488143942
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-autotrain_multifamily_v2_3736899404_en.md b/docs/_posts/ahmedlone127/2025-01-24-autotrain_multifamily_v2_3736899404_en.md
new file mode 100644
index 00000000000000..cbf9165381c944
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-autotrain_multifamily_v2_3736899404_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English autotrain_multifamily_v2_3736899404 SwinForImageClassification from lineups-io
+author: John Snow Labs
+name: autotrain_multifamily_v2_3736899404
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_multifamily_v2_3736899404` is a English model originally trained by lineups-io.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_multifamily_v2_3736899404_en_5.5.1_3.0_1737762667460.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_multifamily_v2_3736899404_en_5.5.1_3.0_1737762667460.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""autotrain_multifamily_v2_3736899404","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("autotrain_multifamily_v2_3736899404","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_multifamily_v2_3736899404|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|650.1 MB|
+
+## References
+
+https://huggingface.co/lineups-io/autotrain-multifamily_v2-3736899404
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-autotrain_multifamily_v2_3736899404_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-autotrain_multifamily_v2_3736899404_pipeline_en.md
new file mode 100644
index 00000000000000..e324f7220394b2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-autotrain_multifamily_v2_3736899404_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English autotrain_multifamily_v2_3736899404_pipeline pipeline SwinForImageClassification from lineups-io
+author: John Snow Labs
+name: autotrain_multifamily_v2_3736899404_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_multifamily_v2_3736899404_pipeline` is a English model originally trained by lineups-io.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_multifamily_v2_3736899404_pipeline_en_5.5.1_3.0_1737762703651.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_multifamily_v2_3736899404_pipeline_en_5.5.1_3.0_1737762703651.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("autotrain_multifamily_v2_3736899404_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("autotrain_multifamily_v2_3736899404_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_multifamily_v2_3736899404_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|650.1 MB|
+
+## References
+
+https://huggingface.co/lineups-io/autotrain-multifamily_v2-3736899404
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-autotrain_okr_iptal_v6_48529117801_en.md b/docs/_posts/ahmedlone127/2025-01-24-autotrain_okr_iptal_v6_48529117801_en.md
new file mode 100644
index 00000000000000..3cf0a8221950d6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-autotrain_okr_iptal_v6_48529117801_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English autotrain_okr_iptal_v6_48529117801 XlmRoBertaForSequenceClassification from ekincanozcelik
+author: John Snow Labs
+name: autotrain_okr_iptal_v6_48529117801
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_okr_iptal_v6_48529117801` is a English model originally trained by ekincanozcelik.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_okr_iptal_v6_48529117801_en_5.5.1_3.0_1737712927648.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_okr_iptal_v6_48529117801_en_5.5.1_3.0_1737712927648.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("autotrain_okr_iptal_v6_48529117801","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("autotrain_okr_iptal_v6_48529117801", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_okr_iptal_v6_48529117801|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|778.4 MB|
+
+## References
+
+https://huggingface.co/ekincanozcelik/autotrain-okr_iptal_v6-48529117801
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-autotrain_okr_iptal_v6_48529117801_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-autotrain_okr_iptal_v6_48529117801_pipeline_en.md
new file mode 100644
index 00000000000000..cb3d1ab409b646
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-autotrain_okr_iptal_v6_48529117801_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English autotrain_okr_iptal_v6_48529117801_pipeline pipeline XlmRoBertaForSequenceClassification from ekincanozcelik
+author: John Snow Labs
+name: autotrain_okr_iptal_v6_48529117801_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_okr_iptal_v6_48529117801_pipeline` is a English model originally trained by ekincanozcelik.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_okr_iptal_v6_48529117801_pipeline_en_5.5.1_3.0_1737713084707.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_okr_iptal_v6_48529117801_pipeline_en_5.5.1_3.0_1737713084707.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("autotrain_okr_iptal_v6_48529117801_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("autotrain_okr_iptal_v6_48529117801_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_okr_iptal_v6_48529117801_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|778.4 MB|
+
+## References
+
+https://huggingface.co/ekincanozcelik/autotrain-okr_iptal_v6-48529117801
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-autotrain_orbit_millets_2_94372146064_en.md b/docs/_posts/ahmedlone127/2025-01-24-autotrain_orbit_millets_2_94372146064_en.md
new file mode 100644
index 00000000000000..b60d74baec9df5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-autotrain_orbit_millets_2_94372146064_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English autotrain_orbit_millets_2_94372146064 SwinForImageClassification from superdinmc
+author: John Snow Labs
+name: autotrain_orbit_millets_2_94372146064
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_orbit_millets_2_94372146064` is a English model originally trained by superdinmc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_orbit_millets_2_94372146064_en_5.5.1_3.0_1737715244752.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_orbit_millets_2_94372146064_en_5.5.1_3.0_1737715244752.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""autotrain_orbit_millets_2_94372146064","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("autotrain_orbit_millets_2_94372146064","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_orbit_millets_2_94372146064|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/superdinmc/autotrain-orbit-millets-2-94372146064
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-autotrain_orbit_millets_2_94372146064_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-autotrain_orbit_millets_2_94372146064_pipeline_en.md
new file mode 100644
index 00000000000000..b5c04c23cc56c4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-autotrain_orbit_millets_2_94372146064_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English autotrain_orbit_millets_2_94372146064_pipeline pipeline SwinForImageClassification from superdinmc
+author: John Snow Labs
+name: autotrain_orbit_millets_2_94372146064_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_orbit_millets_2_94372146064_pipeline` is a English model originally trained by superdinmc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_orbit_millets_2_94372146064_pipeline_en_5.5.1_3.0_1737715255866.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_orbit_millets_2_94372146064_pipeline_en_5.5.1_3.0_1737715255866.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("autotrain_orbit_millets_2_94372146064_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("autotrain_orbit_millets_2_94372146064_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_orbit_millets_2_94372146064_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/superdinmc/autotrain-orbit-millets-2-94372146064
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-autotrain_orbit_millets_94211146034_en.md b/docs/_posts/ahmedlone127/2025-01-24-autotrain_orbit_millets_94211146034_en.md
new file mode 100644
index 00000000000000..e566eaa6e28af8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-autotrain_orbit_millets_94211146034_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English autotrain_orbit_millets_94211146034 SwinForImageClassification from superdinmc
+author: John Snow Labs
+name: autotrain_orbit_millets_94211146034
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_orbit_millets_94211146034` is a English model originally trained by superdinmc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_orbit_millets_94211146034_en_5.5.1_3.0_1737754174863.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_orbit_millets_94211146034_en_5.5.1_3.0_1737754174863.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""autotrain_orbit_millets_94211146034","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("autotrain_orbit_millets_94211146034","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_orbit_millets_94211146034|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/superdinmc/autotrain-orbit-millets-94211146034
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-autotrain_orbit_millets_94211146034_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-autotrain_orbit_millets_94211146034_pipeline_en.md
new file mode 100644
index 00000000000000..78ac9b7e7697bb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-autotrain_orbit_millets_94211146034_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English autotrain_orbit_millets_94211146034_pipeline pipeline SwinForImageClassification from superdinmc
+author: John Snow Labs
+name: autotrain_orbit_millets_94211146034_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_orbit_millets_94211146034_pipeline` is a English model originally trained by superdinmc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_orbit_millets_94211146034_pipeline_en_5.5.1_3.0_1737754187851.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_orbit_millets_94211146034_pipeline_en_5.5.1_3.0_1737754187851.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("autotrain_orbit_millets_94211146034_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("autotrain_orbit_millets_94211146034_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_orbit_millets_94211146034_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/superdinmc/autotrain-orbit-millets-94211146034
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-autotrain_pneumonia_81787141863_en.md b/docs/_posts/ahmedlone127/2025-01-24-autotrain_pneumonia_81787141863_en.md
new file mode 100644
index 00000000000000..0241008ba04cab
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-autotrain_pneumonia_81787141863_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English autotrain_pneumonia_81787141863 SwinForImageClassification from realzdlegend
+author: John Snow Labs
+name: autotrain_pneumonia_81787141863
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_pneumonia_81787141863` is a English model originally trained by realzdlegend.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_pneumonia_81787141863_en_5.5.1_3.0_1737754506863.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_pneumonia_81787141863_en_5.5.1_3.0_1737754506863.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""autotrain_pneumonia_81787141863","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("autotrain_pneumonia_81787141863","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_pneumonia_81787141863|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/realzdlegend/autotrain-pneumonia-81787141863
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-autotrain_pneumonia_81787141863_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-autotrain_pneumonia_81787141863_pipeline_en.md
new file mode 100644
index 00000000000000..011639e1b98297
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-autotrain_pneumonia_81787141863_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English autotrain_pneumonia_81787141863_pipeline pipeline SwinForImageClassification from realzdlegend
+author: John Snow Labs
+name: autotrain_pneumonia_81787141863_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_pneumonia_81787141863_pipeline` is a English model originally trained by realzdlegend.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_pneumonia_81787141863_pipeline_en_5.5.1_3.0_1737754518589.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_pneumonia_81787141863_pipeline_en_5.5.1_3.0_1737754518589.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("autotrain_pneumonia_81787141863_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("autotrain_pneumonia_81787141863_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_pneumonia_81787141863_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/realzdlegend/autotrain-pneumonia-81787141863
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-autotrain_sessya06201_68135137237_en.md b/docs/_posts/ahmedlone127/2025-01-24-autotrain_sessya06201_68135137237_en.md
new file mode 100644
index 00000000000000..33d6051a832505
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-autotrain_sessya06201_68135137237_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English autotrain_sessya06201_68135137237 SwinForImageClassification from Hokkaiswimming
+author: John Snow Labs
+name: autotrain_sessya06201_68135137237
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_sessya06201_68135137237` is a English model originally trained by Hokkaiswimming.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_sessya06201_68135137237_en_5.5.1_3.0_1737714863652.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_sessya06201_68135137237_en_5.5.1_3.0_1737714863652.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""autotrain_sessya06201_68135137237","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("autotrain_sessya06201_68135137237","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_sessya06201_68135137237|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/Hokkaiswimming/autotrain-sessya06201-68135137237
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-autotrain_sessya06201_68135137237_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-autotrain_sessya06201_68135137237_pipeline_en.md
new file mode 100644
index 00000000000000..59a584c2e669e6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-autotrain_sessya06201_68135137237_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English autotrain_sessya06201_68135137237_pipeline pipeline SwinForImageClassification from Hokkaiswimming
+author: John Snow Labs
+name: autotrain_sessya06201_68135137237_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_sessya06201_68135137237_pipeline` is a English model originally trained by Hokkaiswimming.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_sessya06201_68135137237_pipeline_en_5.5.1_3.0_1737714875108.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_sessya06201_68135137237_pipeline_en_5.5.1_3.0_1737714875108.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("autotrain_sessya06201_68135137237_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("autotrain_sessya06201_68135137237_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_sessya06201_68135137237_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/Hokkaiswimming/autotrain-sessya06201-68135137237
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-autotrain_xray_93756145904_en.md b/docs/_posts/ahmedlone127/2025-01-24-autotrain_xray_93756145904_en.md
new file mode 100644
index 00000000000000..6cee7bae400a71
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-autotrain_xray_93756145904_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English autotrain_xray_93756145904 SwinForImageClassification from luminoussg
+author: John Snow Labs
+name: autotrain_xray_93756145904
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_xray_93756145904` is a English model originally trained by luminoussg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_xray_93756145904_en_5.5.1_3.0_1737754701753.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_xray_93756145904_en_5.5.1_3.0_1737754701753.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""autotrain_xray_93756145904","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("autotrain_xray_93756145904","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_xray_93756145904|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/luminoussg/autotrain-xray-93756145904
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-autotrain_xray_93756145904_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-autotrain_xray_93756145904_pipeline_en.md
new file mode 100644
index 00000000000000..9e78361b5ac911
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-autotrain_xray_93756145904_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English autotrain_xray_93756145904_pipeline pipeline SwinForImageClassification from luminoussg
+author: John Snow Labs
+name: autotrain_xray_93756145904_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_xray_93756145904_pipeline` is a English model originally trained by luminoussg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_xray_93756145904_pipeline_en_5.5.1_3.0_1737754712804.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_xray_93756145904_pipeline_en_5.5.1_3.0_1737754712804.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("autotrain_xray_93756145904_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("autotrain_xray_93756145904_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_xray_93756145904_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/luminoussg/autotrain-xray-93756145904
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-babylm_student_gpt2_eval_1_en.md b/docs/_posts/ahmedlone127/2025-01-24-babylm_student_gpt2_eval_1_en.md
new file mode 100644
index 00000000000000..f277ca86015b09
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-babylm_student_gpt2_eval_1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English babylm_student_gpt2_eval_1 GPT2Transformer from momergul
+author: John Snow Labs
+name: babylm_student_gpt2_eval_1
+date: 2025-01-24
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`babylm_student_gpt2_eval_1` is a English model originally trained by momergul.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/babylm_student_gpt2_eval_1_en_5.5.1_3.0_1737733181094.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/babylm_student_gpt2_eval_1_en_5.5.1_3.0_1737733181094.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("babylm_student_gpt2_eval_1","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("babylm_student_gpt2_eval_1","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|babylm_student_gpt2_eval_1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.6 MB|
+
+## References
+
+https://huggingface.co/momergul/babylm-student-gpt2-eval-1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-babylm_student_gpt2_eval_1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-babylm_student_gpt2_eval_1_pipeline_en.md
new file mode 100644
index 00000000000000..cc603e69a5ac36
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-babylm_student_gpt2_eval_1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English babylm_student_gpt2_eval_1_pipeline pipeline GPT2Transformer from momergul
+author: John Snow Labs
+name: babylm_student_gpt2_eval_1_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`babylm_student_gpt2_eval_1_pipeline` is a English model originally trained by momergul.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/babylm_student_gpt2_eval_1_pipeline_en_5.5.1_3.0_1737733205423.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/babylm_student_gpt2_eval_1_pipeline_en_5.5.1_3.0_1737733205423.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("babylm_student_gpt2_eval_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("babylm_student_gpt2_eval_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|babylm_student_gpt2_eval_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.6 MB|
+
+## References
+
+https://huggingface.co/momergul/babylm-student-gpt2-eval-1
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bangla_bert_base_finetuned_squadbn_en.md b/docs/_posts/ahmedlone127/2025-01-24-bangla_bert_base_finetuned_squadbn_en.md
new file mode 100644
index 00000000000000..ca29dfa137a4c7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bangla_bert_base_finetuned_squadbn_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bangla_bert_base_finetuned_squadbn BertForQuestionAnswering from shakun42
+author: John Snow Labs
+name: bangla_bert_base_finetuned_squadbn
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bangla_bert_base_finetuned_squadbn` is a English model originally trained by shakun42.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bangla_bert_base_finetuned_squadbn_en_5.5.1_3.0_1737757198894.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bangla_bert_base_finetuned_squadbn_en_5.5.1_3.0_1737757198894.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bangla_bert_base_finetuned_squadbn","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bangla_bert_base_finetuned_squadbn", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bangla_bert_base_finetuned_squadbn|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|614.7 MB|
+
+## References
+
+https://huggingface.co/shakun42/bangla-bert-base-finetuned-squadbn
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bangla_bert_base_finetuned_squadbn_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bangla_bert_base_finetuned_squadbn_pipeline_en.md
new file mode 100644
index 00000000000000..ea2a3ec30b5519
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bangla_bert_base_finetuned_squadbn_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bangla_bert_base_finetuned_squadbn_pipeline pipeline BertForQuestionAnswering from shakun42
+author: John Snow Labs
+name: bangla_bert_base_finetuned_squadbn_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bangla_bert_base_finetuned_squadbn_pipeline` is a English model originally trained by shakun42.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bangla_bert_base_finetuned_squadbn_pipeline_en_5.5.1_3.0_1737757233041.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bangla_bert_base_finetuned_squadbn_pipeline_en_5.5.1_3.0_1737757233041.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bangla_bert_base_finetuned_squadbn_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bangla_bert_base_finetuned_squadbn_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bangla_bert_base_finetuned_squadbn_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|614.7 MB|
+
+## References
+
+https://huggingface.co/shakun42/bangla-bert-base-finetuned-squadbn
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bart_base_qa2d_en.md b/docs/_posts/ahmedlone127/2025-01-24-bart_base_qa2d_en.md
new file mode 100644
index 00000000000000..92af19d7845bd5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bart_base_qa2d_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bart_base_qa2d BartTransformer from MarkS
+author: John Snow Labs
+name: bart_base_qa2d
+date: 2025-01-24
+tags: [en, open_source, onnx, text_generation, bart]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BartTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bart_base_qa2d` is a English model originally trained by MarkS.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bart_base_qa2d_en_5.5.1_3.0_1737698651713.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bart_base_qa2d_en_5.5.1_3.0_1737698651713.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = BartTransformer.pretrained("bart_base_qa2d","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = BartTransformer.pretrained("bart_base_qa2d","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bart_base_qa2d|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|809.9 MB|
+
+## References
+
+https://huggingface.co/MarkS/bart-base-qa2d
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bart_base_qa2d_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bart_base_qa2d_pipeline_en.md
new file mode 100644
index 00000000000000..c88b6c35e173a1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bart_base_qa2d_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bart_base_qa2d_pipeline pipeline BartTransformer from MarkS
+author: John Snow Labs
+name: bart_base_qa2d_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bart_base_qa2d_pipeline` is a English model originally trained by MarkS.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bart_base_qa2d_pipeline_en_5.5.1_3.0_1737698697110.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bart_base_qa2d_pipeline_en_5.5.1_3.0_1737698697110.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bart_base_qa2d_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bart_base_qa2d_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bart_base_qa2d_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|809.9 MB|
+
+## References
+
+https://huggingface.co/MarkS/bart-base-qa2d
+
+## Included Models
+
+- DocumentAssembler
+- BartTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bart_conversation_summarizer_en.md b/docs/_posts/ahmedlone127/2025-01-24-bart_conversation_summarizer_en.md
new file mode 100644
index 00000000000000..de7fe239af1b18
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bart_conversation_summarizer_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bart_conversation_summarizer BartTransformer from Azma-AI
+author: John Snow Labs
+name: bart_conversation_summarizer
+date: 2025-01-24
+tags: [en, open_source, onnx, text_generation, bart]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BartTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bart_conversation_summarizer` is a English model originally trained by Azma-AI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bart_conversation_summarizer_en_5.5.1_3.0_1737704150050.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bart_conversation_summarizer_en_5.5.1_3.0_1737704150050.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = BartTransformer.pretrained("bart_conversation_summarizer","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = BartTransformer.pretrained("bart_conversation_summarizer","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bart_conversation_summarizer|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.9 GB|
+
+## References
+
+https://huggingface.co/Azma-AI/bart-conversation-summarizer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bart_conversation_summarizer_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bart_conversation_summarizer_pipeline_en.md
new file mode 100644
index 00000000000000..7f3526df5350da
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bart_conversation_summarizer_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bart_conversation_summarizer_pipeline pipeline BartTransformer from Azma-AI
+author: John Snow Labs
+name: bart_conversation_summarizer_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bart_conversation_summarizer_pipeline` is a English model originally trained by Azma-AI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bart_conversation_summarizer_pipeline_en_5.5.1_3.0_1737704241825.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bart_conversation_summarizer_pipeline_en_5.5.1_3.0_1737704241825.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bart_conversation_summarizer_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bart_conversation_summarizer_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bart_conversation_summarizer_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.9 GB|
+
+## References
+
+https://huggingface.co/Azma-AI/bart-conversation-summarizer
+
+## Included Models
+
+- DocumentAssembler
+- BartTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bart_finetuned_text_summarization_en.md b/docs/_posts/ahmedlone127/2025-01-24-bart_finetuned_text_summarization_en.md
new file mode 100644
index 00000000000000..27982cd8b01d7d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bart_finetuned_text_summarization_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bart_finetuned_text_summarization BartTransformer from suriya7
+author: John Snow Labs
+name: bart_finetuned_text_summarization
+date: 2025-01-24
+tags: [en, open_source, onnx, text_generation, bart]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BartTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bart_finetuned_text_summarization` is a English model originally trained by suriya7.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bart_finetuned_text_summarization_en_5.5.1_3.0_1737699214319.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bart_finetuned_text_summarization_en_5.5.1_3.0_1737699214319.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = BartTransformer.pretrained("bart_finetuned_text_summarization","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = BartTransformer.pretrained("bart_finetuned_text_summarization","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bart_finetuned_text_summarization|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.9 GB|
+
+## References
+
+https://huggingface.co/suriya7/bart-finetuned-text-summarization
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bart_finetuned_text_summarization_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bart_finetuned_text_summarization_pipeline_en.md
new file mode 100644
index 00000000000000..4f93626f8bb1a9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bart_finetuned_text_summarization_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bart_finetuned_text_summarization_pipeline pipeline BartTransformer from suriya7
+author: John Snow Labs
+name: bart_finetuned_text_summarization_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bart_finetuned_text_summarization_pipeline` is a English model originally trained by suriya7.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bart_finetuned_text_summarization_pipeline_en_5.5.1_3.0_1737699310831.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bart_finetuned_text_summarization_pipeline_en_5.5.1_3.0_1737699310831.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bart_finetuned_text_summarization_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bart_finetuned_text_summarization_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bart_finetuned_text_summarization_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.9 GB|
+
+## References
+
+https://huggingface.co/suriya7/bart-finetuned-text-summarization
+
+## Included Models
+
+- DocumentAssembler
+- BartTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bart_large_cnn_samsum_philschmid_en.md b/docs/_posts/ahmedlone127/2025-01-24-bart_large_cnn_samsum_philschmid_en.md
new file mode 100644
index 00000000000000..4f7b2a5610baa8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bart_large_cnn_samsum_philschmid_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bart_large_cnn_samsum_philschmid BartTransformer from philschmid
+author: John Snow Labs
+name: bart_large_cnn_samsum_philschmid
+date: 2025-01-24
+tags: [en, open_source, onnx, text_generation, bart]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BartTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bart_large_cnn_samsum_philschmid` is a English model originally trained by philschmid.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bart_large_cnn_samsum_philschmid_en_5.5.1_3.0_1737698563217.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bart_large_cnn_samsum_philschmid_en_5.5.1_3.0_1737698563217.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = BartTransformer.pretrained("bart_large_cnn_samsum_philschmid","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = BartTransformer.pretrained("bart_large_cnn_samsum_philschmid","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bart_large_cnn_samsum_philschmid|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.9 GB|
+
+## References
+
+https://huggingface.co/philschmid/bart-large-cnn-samsum
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bart_large_cnn_samsum_philschmid_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bart_large_cnn_samsum_philschmid_pipeline_en.md
new file mode 100644
index 00000000000000..3c7fd020547ab7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bart_large_cnn_samsum_philschmid_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bart_large_cnn_samsum_philschmid_pipeline pipeline BartTransformer from philschmid
+author: John Snow Labs
+name: bart_large_cnn_samsum_philschmid_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bart_large_cnn_samsum_philschmid_pipeline` is a English model originally trained by philschmid.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bart_large_cnn_samsum_philschmid_pipeline_en_5.5.1_3.0_1737698664203.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bart_large_cnn_samsum_philschmid_pipeline_en_5.5.1_3.0_1737698664203.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bart_large_cnn_samsum_philschmid_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bart_large_cnn_samsum_philschmid_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bart_large_cnn_samsum_philschmid_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.9 GB|
+
+## References
+
+https://huggingface.co/philschmid/bart-large-cnn-samsum
+
+## Included Models
+
+- DocumentAssembler
+- BartTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-base_full_v0_150_en.md b/docs/_posts/ahmedlone127/2025-01-24-base_full_v0_150_en.md
new file mode 100644
index 00000000000000..952f0b27cd448e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-base_full_v0_150_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English base_full_v0_150 XlmRoBertaForSequenceClassification from sreddy109
+author: John Snow Labs
+name: base_full_v0_150
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`base_full_v0_150` is a English model originally trained by sreddy109.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/base_full_v0_150_en_5.5.1_3.0_1737714260867.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/base_full_v0_150_en_5.5.1_3.0_1737714260867.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("base_full_v0_150","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("base_full_v0_150", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|base_full_v0_150|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|993.8 MB|
+
+## References
+
+https://huggingface.co/sreddy109/base-full-v0-150
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-base_full_v0_150_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-base_full_v0_150_pipeline_en.md
new file mode 100644
index 00000000000000..3927099a6d1bdb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-base_full_v0_150_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English base_full_v0_150_pipeline pipeline XlmRoBertaForSequenceClassification from sreddy109
+author: John Snow Labs
+name: base_full_v0_150_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`base_full_v0_150_pipeline` is a English model originally trained by sreddy109.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/base_full_v0_150_pipeline_en_5.5.1_3.0_1737714324819.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/base_full_v0_150_pipeline_en_5.5.1_3.0_1737714324819.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("base_full_v0_150_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("base_full_v0_150_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|base_full_v0_150_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|993.8 MB|
+
+## References
+
+https://huggingface.co/sreddy109/base-full-v0-150
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-base_full_v0_300_en.md b/docs/_posts/ahmedlone127/2025-01-24-base_full_v0_300_en.md
new file mode 100644
index 00000000000000..8d3ca72ffc8468
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-base_full_v0_300_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English base_full_v0_300 XlmRoBertaForSequenceClassification from sreddy109
+author: John Snow Labs
+name: base_full_v0_300
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`base_full_v0_300` is a English model originally trained by sreddy109.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/base_full_v0_300_en_5.5.1_3.0_1737713257783.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/base_full_v0_300_en_5.5.1_3.0_1737713257783.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("base_full_v0_300","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("base_full_v0_300", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|base_full_v0_300|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|994.1 MB|
+
+## References
+
+https://huggingface.co/sreddy109/base-full-v0-300
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-base_full_v0_300_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-base_full_v0_300_pipeline_en.md
new file mode 100644
index 00000000000000..b5985eadf24bd0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-base_full_v0_300_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English base_full_v0_300_pipeline pipeline XlmRoBertaForSequenceClassification from sreddy109
+author: John Snow Labs
+name: base_full_v0_300_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`base_full_v0_300_pipeline` is a English model originally trained by sreddy109.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/base_full_v0_300_pipeline_en_5.5.1_3.0_1737713314529.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/base_full_v0_300_pipeline_en_5.5.1_3.0_1737713314529.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("base_full_v0_300_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("base_full_v0_300_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|base_full_v0_300_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|994.1 MB|
+
+## References
+
+https://huggingface.co/sreddy109/base-full-v0-300
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-baseline_maj_bert_epic_en.md b/docs/_posts/ahmedlone127/2025-01-24-baseline_maj_bert_epic_en.md
new file mode 100644
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--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-baseline_maj_bert_epic_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English baseline_maj_bert_epic BertForSequenceClassification from bmuscato
+author: John Snow Labs
+name: baseline_maj_bert_epic
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`baseline_maj_bert_epic` is a English model originally trained by bmuscato.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/baseline_maj_bert_epic_en_5.5.1_3.0_1737710823880.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/baseline_maj_bert_epic_en_5.5.1_3.0_1737710823880.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("baseline_maj_bert_epic","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("baseline_maj_bert_epic", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|baseline_maj_bert_epic|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/bmuscato/baseline_maj_bert_epic
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-baseline_maj_bert_epic_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-baseline_maj_bert_epic_pipeline_en.md
new file mode 100644
index 00000000000000..ffb9a1e330fbfd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-baseline_maj_bert_epic_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English baseline_maj_bert_epic_pipeline pipeline BertForSequenceClassification from bmuscato
+author: John Snow Labs
+name: baseline_maj_bert_epic_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`baseline_maj_bert_epic_pipeline` is a English model originally trained by bmuscato.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/baseline_maj_bert_epic_pipeline_en_5.5.1_3.0_1737710888212.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/baseline_maj_bert_epic_pipeline_en_5.5.1_3.0_1737710888212.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("baseline_maj_bert_epic_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("baseline_maj_bert_epic_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|baseline_maj_bert_epic_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/bmuscato/baseline_maj_bert_epic
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-batch_size16_celeb_df_v2_opencv_1fps_faces_expand50_aligned_unaugmentation_en.md b/docs/_posts/ahmedlone127/2025-01-24-batch_size16_celeb_df_v2_opencv_1fps_faces_expand50_aligned_unaugmentation_en.md
new file mode 100644
index 00000000000000..3fdbb6dfc1f4d7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-batch_size16_celeb_df_v2_opencv_1fps_faces_expand50_aligned_unaugmentation_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English batch_size16_celeb_df_v2_opencv_1fps_faces_expand50_aligned_unaugmentation SwinForImageClassification from hchcsuim
+author: John Snow Labs
+name: batch_size16_celeb_df_v2_opencv_1fps_faces_expand50_aligned_unaugmentation
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`batch_size16_celeb_df_v2_opencv_1fps_faces_expand50_aligned_unaugmentation` is a English model originally trained by hchcsuim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/batch_size16_celeb_df_v2_opencv_1fps_faces_expand50_aligned_unaugmentation_en_5.5.1_3.0_1737762401024.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/batch_size16_celeb_df_v2_opencv_1fps_faces_expand50_aligned_unaugmentation_en_5.5.1_3.0_1737762401024.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""batch_size16_celeb_df_v2_opencv_1fps_faces_expand50_aligned_unaugmentation","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("batch_size16_celeb_df_v2_opencv_1fps_faces_expand50_aligned_unaugmentation","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|batch_size16_celeb_df_v2_opencv_1fps_faces_expand50_aligned_unaugmentation|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/hchcsuim/batch-size16_Celeb-DF-v2_opencv-1FPS_faces-expand50-aligned_unaugmentation
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-batch_size16_celeb_df_v2_opencv_1fps_faces_expand50_aligned_unaugmentation_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-batch_size16_celeb_df_v2_opencv_1fps_faces_expand50_aligned_unaugmentation_pipeline_en.md
new file mode 100644
index 00000000000000..cceb365c1be5c5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-batch_size16_celeb_df_v2_opencv_1fps_faces_expand50_aligned_unaugmentation_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English batch_size16_celeb_df_v2_opencv_1fps_faces_expand50_aligned_unaugmentation_pipeline pipeline SwinForImageClassification from hchcsuim
+author: John Snow Labs
+name: batch_size16_celeb_df_v2_opencv_1fps_faces_expand50_aligned_unaugmentation_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`batch_size16_celeb_df_v2_opencv_1fps_faces_expand50_aligned_unaugmentation_pipeline` is a English model originally trained by hchcsuim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/batch_size16_celeb_df_v2_opencv_1fps_faces_expand50_aligned_unaugmentation_pipeline_en_5.5.1_3.0_1737762412720.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/batch_size16_celeb_df_v2_opencv_1fps_faces_expand50_aligned_unaugmentation_pipeline_en_5.5.1_3.0_1737762412720.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("batch_size16_celeb_df_v2_opencv_1fps_faces_expand50_aligned_unaugmentation_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("batch_size16_celeb_df_v2_opencv_1fps_faces_expand50_aligned_unaugmentation_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|batch_size16_celeb_df_v2_opencv_1fps_faces_expand50_aligned_unaugmentation_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/hchcsuim/batch-size16_Celeb-DF-v2_opencv-1FPS_faces-expand50-aligned_unaugmentation
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-batch_size16_celeb_df_v2_opencv_1fps_unaugmentation_en.md b/docs/_posts/ahmedlone127/2025-01-24-batch_size16_celeb_df_v2_opencv_1fps_unaugmentation_en.md
new file mode 100644
index 00000000000000..6525d5004f44dc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-batch_size16_celeb_df_v2_opencv_1fps_unaugmentation_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English batch_size16_celeb_df_v2_opencv_1fps_unaugmentation SwinForImageClassification from hchcsuim
+author: John Snow Labs
+name: batch_size16_celeb_df_v2_opencv_1fps_unaugmentation
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`batch_size16_celeb_df_v2_opencv_1fps_unaugmentation` is a English model originally trained by hchcsuim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/batch_size16_celeb_df_v2_opencv_1fps_unaugmentation_en_5.5.1_3.0_1737715638624.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/batch_size16_celeb_df_v2_opencv_1fps_unaugmentation_en_5.5.1_3.0_1737715638624.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""batch_size16_celeb_df_v2_opencv_1fps_unaugmentation","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("batch_size16_celeb_df_v2_opencv_1fps_unaugmentation","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|batch_size16_celeb_df_v2_opencv_1fps_unaugmentation|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/hchcsuim/batch-size16_Celeb-DF-v2_opencv-1FPS_unaugmentation
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-batch_size16_celeb_df_v2_opencv_1fps_unaugmentation_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-batch_size16_celeb_df_v2_opencv_1fps_unaugmentation_pipeline_en.md
new file mode 100644
index 00000000000000..52d4e5e96ed74c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-batch_size16_celeb_df_v2_opencv_1fps_unaugmentation_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English batch_size16_celeb_df_v2_opencv_1fps_unaugmentation_pipeline pipeline SwinForImageClassification from hchcsuim
+author: John Snow Labs
+name: batch_size16_celeb_df_v2_opencv_1fps_unaugmentation_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`batch_size16_celeb_df_v2_opencv_1fps_unaugmentation_pipeline` is a English model originally trained by hchcsuim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/batch_size16_celeb_df_v2_opencv_1fps_unaugmentation_pipeline_en_5.5.1_3.0_1737715650022.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/batch_size16_celeb_df_v2_opencv_1fps_unaugmentation_pipeline_en_5.5.1_3.0_1737715650022.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("batch_size16_celeb_df_v2_opencv_1fps_unaugmentation_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("batch_size16_celeb_df_v2_opencv_1fps_unaugmentation_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|batch_size16_celeb_df_v2_opencv_1fps_unaugmentation_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/hchcsuim/batch-size16_Celeb-DF-v2_opencv-1FPS_unaugmentation
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-batch_size16_ffpp_c23_ffmpeg_1fps_qv1_faces_expand0_aligned_unaugmentation_en.md b/docs/_posts/ahmedlone127/2025-01-24-batch_size16_ffpp_c23_ffmpeg_1fps_qv1_faces_expand0_aligned_unaugmentation_en.md
new file mode 100644
index 00000000000000..1f9840edf3b8fe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-batch_size16_ffpp_c23_ffmpeg_1fps_qv1_faces_expand0_aligned_unaugmentation_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English batch_size16_ffpp_c23_ffmpeg_1fps_qv1_faces_expand0_aligned_unaugmentation SwinForImageClassification from hchcsuim
+author: John Snow Labs
+name: batch_size16_ffpp_c23_ffmpeg_1fps_qv1_faces_expand0_aligned_unaugmentation
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`batch_size16_ffpp_c23_ffmpeg_1fps_qv1_faces_expand0_aligned_unaugmentation` is a English model originally trained by hchcsuim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/batch_size16_ffpp_c23_ffmpeg_1fps_qv1_faces_expand0_aligned_unaugmentation_en_5.5.1_3.0_1737694252514.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/batch_size16_ffpp_c23_ffmpeg_1fps_qv1_faces_expand0_aligned_unaugmentation_en_5.5.1_3.0_1737694252514.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""batch_size16_ffpp_c23_ffmpeg_1fps_qv1_faces_expand0_aligned_unaugmentation","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("batch_size16_ffpp_c23_ffmpeg_1fps_qv1_faces_expand0_aligned_unaugmentation","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|batch_size16_ffpp_c23_ffmpeg_1fps_qv1_faces_expand0_aligned_unaugmentation|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/hchcsuim/batch-size16_FFPP-c23_ffmpeg-1FPS-qv1_faces-expand0-aligned_unaugmentation
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-batch_size16_ffpp_c23_ffmpeg_1fps_qv1_faces_expand0_aligned_unaugmentation_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-batch_size16_ffpp_c23_ffmpeg_1fps_qv1_faces_expand0_aligned_unaugmentation_pipeline_en.md
new file mode 100644
index 00000000000000..4073e459737284
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-batch_size16_ffpp_c23_ffmpeg_1fps_qv1_faces_expand0_aligned_unaugmentation_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English batch_size16_ffpp_c23_ffmpeg_1fps_qv1_faces_expand0_aligned_unaugmentation_pipeline pipeline SwinForImageClassification from hchcsuim
+author: John Snow Labs
+name: batch_size16_ffpp_c23_ffmpeg_1fps_qv1_faces_expand0_aligned_unaugmentation_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`batch_size16_ffpp_c23_ffmpeg_1fps_qv1_faces_expand0_aligned_unaugmentation_pipeline` is a English model originally trained by hchcsuim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/batch_size16_ffpp_c23_ffmpeg_1fps_qv1_faces_expand0_aligned_unaugmentation_pipeline_en_5.5.1_3.0_1737694266437.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/batch_size16_ffpp_c23_ffmpeg_1fps_qv1_faces_expand0_aligned_unaugmentation_pipeline_en_5.5.1_3.0_1737694266437.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("batch_size16_ffpp_c23_ffmpeg_1fps_qv1_faces_expand0_aligned_unaugmentation_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("batch_size16_ffpp_c23_ffmpeg_1fps_qv1_faces_expand0_aligned_unaugmentation_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|batch_size16_ffpp_c23_ffmpeg_1fps_qv1_faces_expand0_aligned_unaugmentation_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/hchcsuim/batch-size16_FFPP-c23_ffmpeg-1FPS-qv1_faces-expand0-aligned_unaugmentation
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-batch_size16_ffpp_c23_opencv_1fps_faces_expand20_aligned_unaugmentation_en.md b/docs/_posts/ahmedlone127/2025-01-24-batch_size16_ffpp_c23_opencv_1fps_faces_expand20_aligned_unaugmentation_en.md
new file mode 100644
index 00000000000000..6c3c72f1c5dcd4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-batch_size16_ffpp_c23_opencv_1fps_faces_expand20_aligned_unaugmentation_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English batch_size16_ffpp_c23_opencv_1fps_faces_expand20_aligned_unaugmentation SwinForImageClassification from hchcsuim
+author: John Snow Labs
+name: batch_size16_ffpp_c23_opencv_1fps_faces_expand20_aligned_unaugmentation
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`batch_size16_ffpp_c23_opencv_1fps_faces_expand20_aligned_unaugmentation` is a English model originally trained by hchcsuim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/batch_size16_ffpp_c23_opencv_1fps_faces_expand20_aligned_unaugmentation_en_5.5.1_3.0_1737694540646.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/batch_size16_ffpp_c23_opencv_1fps_faces_expand20_aligned_unaugmentation_en_5.5.1_3.0_1737694540646.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""batch_size16_ffpp_c23_opencv_1fps_faces_expand20_aligned_unaugmentation","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("batch_size16_ffpp_c23_opencv_1fps_faces_expand20_aligned_unaugmentation","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|batch_size16_ffpp_c23_opencv_1fps_faces_expand20_aligned_unaugmentation|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/hchcsuim/batch-size16_FFPP-c23_opencv-1FPS_faces-expand20-aligned_unaugmentation
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-batch_size16_ffpp_c23_opencv_1fps_faces_expand20_aligned_unaugmentation_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-batch_size16_ffpp_c23_opencv_1fps_faces_expand20_aligned_unaugmentation_pipeline_en.md
new file mode 100644
index 00000000000000..fb2bf57d2a0f96
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-batch_size16_ffpp_c23_opencv_1fps_faces_expand20_aligned_unaugmentation_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English batch_size16_ffpp_c23_opencv_1fps_faces_expand20_aligned_unaugmentation_pipeline pipeline SwinForImageClassification from hchcsuim
+author: John Snow Labs
+name: batch_size16_ffpp_c23_opencv_1fps_faces_expand20_aligned_unaugmentation_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`batch_size16_ffpp_c23_opencv_1fps_faces_expand20_aligned_unaugmentation_pipeline` is a English model originally trained by hchcsuim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/batch_size16_ffpp_c23_opencv_1fps_faces_expand20_aligned_unaugmentation_pipeline_en_5.5.1_3.0_1737694551943.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/batch_size16_ffpp_c23_opencv_1fps_faces_expand20_aligned_unaugmentation_pipeline_en_5.5.1_3.0_1737694551943.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("batch_size16_ffpp_c23_opencv_1fps_faces_expand20_aligned_unaugmentation_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("batch_size16_ffpp_c23_opencv_1fps_faces_expand20_aligned_unaugmentation_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|batch_size16_ffpp_c23_opencv_1fps_faces_expand20_aligned_unaugmentation_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/hchcsuim/batch-size16_FFPP-c23_opencv-1FPS_faces-expand20-aligned_unaugmentation
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-batch_size16_ffpp_c23_opencv_1fps_faces_expand30_aligned_unaugmentation_en.md b/docs/_posts/ahmedlone127/2025-01-24-batch_size16_ffpp_c23_opencv_1fps_faces_expand30_aligned_unaugmentation_en.md
new file mode 100644
index 00000000000000..384d761aba89cc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-batch_size16_ffpp_c23_opencv_1fps_faces_expand30_aligned_unaugmentation_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English batch_size16_ffpp_c23_opencv_1fps_faces_expand30_aligned_unaugmentation SwinForImageClassification from hchcsuim
+author: John Snow Labs
+name: batch_size16_ffpp_c23_opencv_1fps_faces_expand30_aligned_unaugmentation
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`batch_size16_ffpp_c23_opencv_1fps_faces_expand30_aligned_unaugmentation` is a English model originally trained by hchcsuim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/batch_size16_ffpp_c23_opencv_1fps_faces_expand30_aligned_unaugmentation_en_5.5.1_3.0_1737694349166.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/batch_size16_ffpp_c23_opencv_1fps_faces_expand30_aligned_unaugmentation_en_5.5.1_3.0_1737694349166.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""batch_size16_ffpp_c23_opencv_1fps_faces_expand30_aligned_unaugmentation","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("batch_size16_ffpp_c23_opencv_1fps_faces_expand30_aligned_unaugmentation","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|batch_size16_ffpp_c23_opencv_1fps_faces_expand30_aligned_unaugmentation|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/hchcsuim/batch-size16_FFPP-c23_opencv-1FPS_faces-expand30-aligned_unaugmentation
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-batch_size16_ffpp_c23_opencv_1fps_faces_expand30_aligned_unaugmentation_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-batch_size16_ffpp_c23_opencv_1fps_faces_expand30_aligned_unaugmentation_pipeline_en.md
new file mode 100644
index 00000000000000..2778063e96c566
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-batch_size16_ffpp_c23_opencv_1fps_faces_expand30_aligned_unaugmentation_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English batch_size16_ffpp_c23_opencv_1fps_faces_expand30_aligned_unaugmentation_pipeline pipeline SwinForImageClassification from hchcsuim
+author: John Snow Labs
+name: batch_size16_ffpp_c23_opencv_1fps_faces_expand30_aligned_unaugmentation_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`batch_size16_ffpp_c23_opencv_1fps_faces_expand30_aligned_unaugmentation_pipeline` is a English model originally trained by hchcsuim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/batch_size16_ffpp_c23_opencv_1fps_faces_expand30_aligned_unaugmentation_pipeline_en_5.5.1_3.0_1737694361430.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/batch_size16_ffpp_c23_opencv_1fps_faces_expand30_aligned_unaugmentation_pipeline_en_5.5.1_3.0_1737694361430.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("batch_size16_ffpp_c23_opencv_1fps_faces_expand30_aligned_unaugmentation_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("batch_size16_ffpp_c23_opencv_1fps_faces_expand30_aligned_unaugmentation_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|batch_size16_ffpp_c23_opencv_1fps_faces_expand30_aligned_unaugmentation_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/hchcsuim/batch-size16_FFPP-c23_opencv-1FPS_faces-expand30-aligned_unaugmentation
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-batch_size16_ffpp_c23_opencv_1fps_faces_expand40_aligned_unaugmentation_en.md b/docs/_posts/ahmedlone127/2025-01-24-batch_size16_ffpp_c23_opencv_1fps_faces_expand40_aligned_unaugmentation_en.md
new file mode 100644
index 00000000000000..f636833a335023
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-batch_size16_ffpp_c23_opencv_1fps_faces_expand40_aligned_unaugmentation_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English batch_size16_ffpp_c23_opencv_1fps_faces_expand40_aligned_unaugmentation SwinForImageClassification from hchcsuim
+author: John Snow Labs
+name: batch_size16_ffpp_c23_opencv_1fps_faces_expand40_aligned_unaugmentation
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`batch_size16_ffpp_c23_opencv_1fps_faces_expand40_aligned_unaugmentation` is a English model originally trained by hchcsuim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/batch_size16_ffpp_c23_opencv_1fps_faces_expand40_aligned_unaugmentation_en_5.5.1_3.0_1737754727771.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/batch_size16_ffpp_c23_opencv_1fps_faces_expand40_aligned_unaugmentation_en_5.5.1_3.0_1737754727771.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""batch_size16_ffpp_c23_opencv_1fps_faces_expand40_aligned_unaugmentation","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("batch_size16_ffpp_c23_opencv_1fps_faces_expand40_aligned_unaugmentation","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|batch_size16_ffpp_c23_opencv_1fps_faces_expand40_aligned_unaugmentation|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/hchcsuim/batch-size16_FFPP-c23_opencv-1FPS_faces-expand40-aligned_unaugmentation
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-batch_size16_ffpp_c23_opencv_1fps_faces_expand40_aligned_unaugmentation_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-batch_size16_ffpp_c23_opencv_1fps_faces_expand40_aligned_unaugmentation_pipeline_en.md
new file mode 100644
index 00000000000000..6bb69de892295d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-batch_size16_ffpp_c23_opencv_1fps_faces_expand40_aligned_unaugmentation_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English batch_size16_ffpp_c23_opencv_1fps_faces_expand40_aligned_unaugmentation_pipeline pipeline SwinForImageClassification from hchcsuim
+author: John Snow Labs
+name: batch_size16_ffpp_c23_opencv_1fps_faces_expand40_aligned_unaugmentation_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`batch_size16_ffpp_c23_opencv_1fps_faces_expand40_aligned_unaugmentation_pipeline` is a English model originally trained by hchcsuim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/batch_size16_ffpp_c23_opencv_1fps_faces_expand40_aligned_unaugmentation_pipeline_en_5.5.1_3.0_1737754738990.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/batch_size16_ffpp_c23_opencv_1fps_faces_expand40_aligned_unaugmentation_pipeline_en_5.5.1_3.0_1737754738990.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("batch_size16_ffpp_c23_opencv_1fps_faces_expand40_aligned_unaugmentation_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("batch_size16_ffpp_c23_opencv_1fps_faces_expand40_aligned_unaugmentation_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|batch_size16_ffpp_c23_opencv_1fps_faces_expand40_aligned_unaugmentation_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/hchcsuim/batch-size16_FFPP-c23_opencv-1FPS_faces-expand40-aligned_unaugmentation
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-batch_size16_ffpp_raw_opencv_1fps_faces_expand0_aligned_unaugmentation_seed_random_2_3060_en.md b/docs/_posts/ahmedlone127/2025-01-24-batch_size16_ffpp_raw_opencv_1fps_faces_expand0_aligned_unaugmentation_seed_random_2_3060_en.md
new file mode 100644
index 00000000000000..7bca75151c3387
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-batch_size16_ffpp_raw_opencv_1fps_faces_expand0_aligned_unaugmentation_seed_random_2_3060_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English batch_size16_ffpp_raw_opencv_1fps_faces_expand0_aligned_unaugmentation_seed_random_2_3060 SwinForImageClassification from hchcsuim
+author: John Snow Labs
+name: batch_size16_ffpp_raw_opencv_1fps_faces_expand0_aligned_unaugmentation_seed_random_2_3060
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`batch_size16_ffpp_raw_opencv_1fps_faces_expand0_aligned_unaugmentation_seed_random_2_3060` is a English model originally trained by hchcsuim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/batch_size16_ffpp_raw_opencv_1fps_faces_expand0_aligned_unaugmentation_seed_random_2_3060_en_5.5.1_3.0_1737762607720.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/batch_size16_ffpp_raw_opencv_1fps_faces_expand0_aligned_unaugmentation_seed_random_2_3060_en_5.5.1_3.0_1737762607720.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""batch_size16_ffpp_raw_opencv_1fps_faces_expand0_aligned_unaugmentation_seed_random_2_3060","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("batch_size16_ffpp_raw_opencv_1fps_faces_expand0_aligned_unaugmentation_seed_random_2_3060","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|batch_size16_ffpp_raw_opencv_1fps_faces_expand0_aligned_unaugmentation_seed_random_2_3060|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/hchcsuim/batch-size16_FFPP-raw_opencv-1FPS_faces-expand0-aligned_unaugmentation_seed-random_2_3060
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-batch_size16_ffpp_raw_opencv_1fps_faces_expand0_aligned_unaugmentation_seed_random_2_3060_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-batch_size16_ffpp_raw_opencv_1fps_faces_expand0_aligned_unaugmentation_seed_random_2_3060_pipeline_en.md
new file mode 100644
index 00000000000000..592c0e6142c1e1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-batch_size16_ffpp_raw_opencv_1fps_faces_expand0_aligned_unaugmentation_seed_random_2_3060_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English batch_size16_ffpp_raw_opencv_1fps_faces_expand0_aligned_unaugmentation_seed_random_2_3060_pipeline pipeline SwinForImageClassification from hchcsuim
+author: John Snow Labs
+name: batch_size16_ffpp_raw_opencv_1fps_faces_expand0_aligned_unaugmentation_seed_random_2_3060_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`batch_size16_ffpp_raw_opencv_1fps_faces_expand0_aligned_unaugmentation_seed_random_2_3060_pipeline` is a English model originally trained by hchcsuim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/batch_size16_ffpp_raw_opencv_1fps_faces_expand0_aligned_unaugmentation_seed_random_2_3060_pipeline_en_5.5.1_3.0_1737762619312.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/batch_size16_ffpp_raw_opencv_1fps_faces_expand0_aligned_unaugmentation_seed_random_2_3060_pipeline_en_5.5.1_3.0_1737762619312.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("batch_size16_ffpp_raw_opencv_1fps_faces_expand0_aligned_unaugmentation_seed_random_2_3060_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("batch_size16_ffpp_raw_opencv_1fps_faces_expand0_aligned_unaugmentation_seed_random_2_3060_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|batch_size16_ffpp_raw_opencv_1fps_faces_expand0_aligned_unaugmentation_seed_random_2_3060_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/hchcsuim/batch-size16_FFPP-raw_opencv-1FPS_faces-expand0-aligned_unaugmentation_seed-random_2_3060
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-batch_size_16_ffpp_c23_1fps_faces_expand_0_aligned_unaugmentation_en.md b/docs/_posts/ahmedlone127/2025-01-24-batch_size_16_ffpp_c23_1fps_faces_expand_0_aligned_unaugmentation_en.md
new file mode 100644
index 00000000000000..424a5fb1076c83
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-batch_size_16_ffpp_c23_1fps_faces_expand_0_aligned_unaugmentation_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English batch_size_16_ffpp_c23_1fps_faces_expand_0_aligned_unaugmentation SwinForImageClassification from hchcsuim
+author: John Snow Labs
+name: batch_size_16_ffpp_c23_1fps_faces_expand_0_aligned_unaugmentation
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`batch_size_16_ffpp_c23_1fps_faces_expand_0_aligned_unaugmentation` is a English model originally trained by hchcsuim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/batch_size_16_ffpp_c23_1fps_faces_expand_0_aligned_unaugmentation_en_5.5.1_3.0_1737715607573.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/batch_size_16_ffpp_c23_1fps_faces_expand_0_aligned_unaugmentation_en_5.5.1_3.0_1737715607573.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""batch_size_16_ffpp_c23_1fps_faces_expand_0_aligned_unaugmentation","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("batch_size_16_ffpp_c23_1fps_faces_expand_0_aligned_unaugmentation","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|batch_size_16_ffpp_c23_1fps_faces_expand_0_aligned_unaugmentation|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/hchcsuim/batch-size-16_FFPP-c23_1FPS_faces-expand-0-aligned_unaugmentation
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-batch_size_16_ffpp_c23_1fps_faces_expand_0_aligned_unaugmentation_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-batch_size_16_ffpp_c23_1fps_faces_expand_0_aligned_unaugmentation_pipeline_en.md
new file mode 100644
index 00000000000000..089cff14c0debc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-batch_size_16_ffpp_c23_1fps_faces_expand_0_aligned_unaugmentation_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English batch_size_16_ffpp_c23_1fps_faces_expand_0_aligned_unaugmentation_pipeline pipeline SwinForImageClassification from hchcsuim
+author: John Snow Labs
+name: batch_size_16_ffpp_c23_1fps_faces_expand_0_aligned_unaugmentation_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`batch_size_16_ffpp_c23_1fps_faces_expand_0_aligned_unaugmentation_pipeline` is a English model originally trained by hchcsuim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/batch_size_16_ffpp_c23_1fps_faces_expand_0_aligned_unaugmentation_pipeline_en_5.5.1_3.0_1737715618744.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/batch_size_16_ffpp_c23_1fps_faces_expand_0_aligned_unaugmentation_pipeline_en_5.5.1_3.0_1737715618744.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("batch_size_16_ffpp_c23_1fps_faces_expand_0_aligned_unaugmentation_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("batch_size_16_ffpp_c23_1fps_faces_expand_0_aligned_unaugmentation_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|batch_size_16_ffpp_c23_1fps_faces_expand_0_aligned_unaugmentation_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/hchcsuim/batch-size-16_FFPP-c23_1FPS_faces-expand-0-aligned_unaugmentation
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-batch_size_16_ffpp_c23_1fps_faces_expand_10_aligned_unaugmentation_en.md b/docs/_posts/ahmedlone127/2025-01-24-batch_size_16_ffpp_c23_1fps_faces_expand_10_aligned_unaugmentation_en.md
new file mode 100644
index 00000000000000..0c4b3fce96bb71
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-batch_size_16_ffpp_c23_1fps_faces_expand_10_aligned_unaugmentation_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English batch_size_16_ffpp_c23_1fps_faces_expand_10_aligned_unaugmentation SwinForImageClassification from hchcsuim
+author: John Snow Labs
+name: batch_size_16_ffpp_c23_1fps_faces_expand_10_aligned_unaugmentation
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`batch_size_16_ffpp_c23_1fps_faces_expand_10_aligned_unaugmentation` is a English model originally trained by hchcsuim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/batch_size_16_ffpp_c23_1fps_faces_expand_10_aligned_unaugmentation_en_5.5.1_3.0_1737715716261.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/batch_size_16_ffpp_c23_1fps_faces_expand_10_aligned_unaugmentation_en_5.5.1_3.0_1737715716261.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""batch_size_16_ffpp_c23_1fps_faces_expand_10_aligned_unaugmentation","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("batch_size_16_ffpp_c23_1fps_faces_expand_10_aligned_unaugmentation","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|batch_size_16_ffpp_c23_1fps_faces_expand_10_aligned_unaugmentation|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/hchcsuim/batch-size-16_FFPP-c23_1FPS_faces-expand-10-aligned_unaugmentation
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-batch_size_16_ffpp_c23_1fps_faces_expand_10_aligned_unaugmentation_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-batch_size_16_ffpp_c23_1fps_faces_expand_10_aligned_unaugmentation_pipeline_en.md
new file mode 100644
index 00000000000000..16a885c81cf063
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-batch_size_16_ffpp_c23_1fps_faces_expand_10_aligned_unaugmentation_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English batch_size_16_ffpp_c23_1fps_faces_expand_10_aligned_unaugmentation_pipeline pipeline SwinForImageClassification from hchcsuim
+author: John Snow Labs
+name: batch_size_16_ffpp_c23_1fps_faces_expand_10_aligned_unaugmentation_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`batch_size_16_ffpp_c23_1fps_faces_expand_10_aligned_unaugmentation_pipeline` is a English model originally trained by hchcsuim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/batch_size_16_ffpp_c23_1fps_faces_expand_10_aligned_unaugmentation_pipeline_en_5.5.1_3.0_1737715727416.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/batch_size_16_ffpp_c23_1fps_faces_expand_10_aligned_unaugmentation_pipeline_en_5.5.1_3.0_1737715727416.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("batch_size_16_ffpp_c23_1fps_faces_expand_10_aligned_unaugmentation_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("batch_size_16_ffpp_c23_1fps_faces_expand_10_aligned_unaugmentation_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|batch_size_16_ffpp_c23_1fps_faces_expand_10_aligned_unaugmentation_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/hchcsuim/batch-size-16_FFPP-c23_1FPS_faces-expand-10-aligned_unaugmentation
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_adaptation_martin_fierro_javier_rooster_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_adaptation_martin_fierro_javier_rooster_en.md
new file mode 100644
index 00000000000000..0b6cd6f6c51d47
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_adaptation_martin_fierro_javier_rooster_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_adaptation_martin_fierro_javier_rooster BertEmbeddings from javier-rooster
+author: John Snow Labs
+name: bert_adaptation_martin_fierro_javier_rooster
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_martin_fierro_javier_rooster` is a English model originally trained by javier-rooster.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_martin_fierro_javier_rooster_en_5.5.1_3.0_1737708188571.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_martin_fierro_javier_rooster_en_5.5.1_3.0_1737708188571.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_adaptation_martin_fierro_javier_rooster","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_adaptation_martin_fierro_javier_rooster","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_martin_fierro_javier_rooster|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/javier-rooster/bert_adaptation_martin_fierro
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_adaptation_martin_fierro_javier_rooster_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_adaptation_martin_fierro_javier_rooster_pipeline_en.md
new file mode 100644
index 00000000000000..94d87c30145121
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_adaptation_martin_fierro_javier_rooster_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_adaptation_martin_fierro_javier_rooster_pipeline pipeline BertEmbeddings from javier-rooster
+author: John Snow Labs
+name: bert_adaptation_martin_fierro_javier_rooster_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_martin_fierro_javier_rooster_pipeline` is a English model originally trained by javier-rooster.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_martin_fierro_javier_rooster_pipeline_en_5.5.1_3.0_1737708211249.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_martin_fierro_javier_rooster_pipeline_en_5.5.1_3.0_1737708211249.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_adaptation_martin_fierro_javier_rooster_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_adaptation_martin_fierro_javier_rooster_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_martin_fierro_javier_rooster_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/javier-rooster/bert_adaptation_martin_fierro
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_adaptation_referencias_german_vinos_andrew_xzr_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_adaptation_referencias_german_vinos_andrew_xzr_en.md
new file mode 100644
index 00000000000000..fbc44a865d924d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_adaptation_referencias_german_vinos_andrew_xzr_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_adaptation_referencias_german_vinos_andrew_xzr BertEmbeddings from Andrew-XZR
+author: John Snow Labs
+name: bert_adaptation_referencias_german_vinos_andrew_xzr
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_referencias_german_vinos_andrew_xzr` is a English model originally trained by Andrew-XZR.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_referencias_german_vinos_andrew_xzr_en_5.5.1_3.0_1737708514074.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_referencias_german_vinos_andrew_xzr_en_5.5.1_3.0_1737708514074.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_adaptation_referencias_german_vinos_andrew_xzr","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_adaptation_referencias_german_vinos_andrew_xzr","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_referencias_german_vinos_andrew_xzr|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/Andrew-XZR/bert_adaptation_referencias_de_vinos
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_adaptation_referencias_german_vinos_andrew_xzr_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_adaptation_referencias_german_vinos_andrew_xzr_pipeline_en.md
new file mode 100644
index 00000000000000..af6040de479122
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_adaptation_referencias_german_vinos_andrew_xzr_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_adaptation_referencias_german_vinos_andrew_xzr_pipeline pipeline BertEmbeddings from Andrew-XZR
+author: John Snow Labs
+name: bert_adaptation_referencias_german_vinos_andrew_xzr_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_referencias_german_vinos_andrew_xzr_pipeline` is a English model originally trained by Andrew-XZR.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_referencias_german_vinos_andrew_xzr_pipeline_en_5.5.1_3.0_1737708535798.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_referencias_german_vinos_andrew_xzr_pipeline_en_5.5.1_3.0_1737708535798.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_adaptation_referencias_german_vinos_andrew_xzr_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_adaptation_referencias_german_vinos_andrew_xzr_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_referencias_german_vinos_andrew_xzr_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/Andrew-XZR/bert_adaptation_referencias_de_vinos
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_adaptation_referencias_german_vinos_ferni_riverplate_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_adaptation_referencias_german_vinos_ferni_riverplate_en.md
new file mode 100644
index 00000000000000..d26d2b322e6e86
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_adaptation_referencias_german_vinos_ferni_riverplate_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_adaptation_referencias_german_vinos_ferni_riverplate BertEmbeddings from ferni-riverplate
+author: John Snow Labs
+name: bert_adaptation_referencias_german_vinos_ferni_riverplate
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_referencias_german_vinos_ferni_riverplate` is a English model originally trained by ferni-riverplate.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_referencias_german_vinos_ferni_riverplate_en_5.5.1_3.0_1737742713561.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_referencias_german_vinos_ferni_riverplate_en_5.5.1_3.0_1737742713561.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_adaptation_referencias_german_vinos_ferni_riverplate","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_adaptation_referencias_german_vinos_ferni_riverplate","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_referencias_german_vinos_ferni_riverplate|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/ferni-riverplate/bert_adaptation_referencias_de_vinos
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_adaptation_referencias_german_vinos_ferni_riverplate_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_adaptation_referencias_german_vinos_ferni_riverplate_pipeline_en.md
new file mode 100644
index 00000000000000..a6243d3b962e21
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_adaptation_referencias_german_vinos_ferni_riverplate_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_adaptation_referencias_german_vinos_ferni_riverplate_pipeline pipeline BertEmbeddings from ferni-riverplate
+author: John Snow Labs
+name: bert_adaptation_referencias_german_vinos_ferni_riverplate_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_referencias_german_vinos_ferni_riverplate_pipeline` is a English model originally trained by ferni-riverplate.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_referencias_german_vinos_ferni_riverplate_pipeline_en_5.5.1_3.0_1737742734865.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_referencias_german_vinos_ferni_riverplate_pipeline_en_5.5.1_3.0_1737742734865.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_adaptation_referencias_german_vinos_ferni_riverplate_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_adaptation_referencias_german_vinos_ferni_riverplate_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_referencias_german_vinos_ferni_riverplate_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/ferni-riverplate/bert_adaptation_referencias_de_vinos
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_case_financial_news_twitter_sentiment_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_case_financial_news_twitter_sentiment_en.md
new file mode 100644
index 00000000000000..b5a69b4a1d5e98
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_case_financial_news_twitter_sentiment_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_case_financial_news_twitter_sentiment BertForSequenceClassification from Mikimi
+author: John Snow Labs
+name: bert_base_case_financial_news_twitter_sentiment
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_case_financial_news_twitter_sentiment` is a English model originally trained by Mikimi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_case_financial_news_twitter_sentiment_en_5.5.1_3.0_1737710425531.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_case_financial_news_twitter_sentiment_en_5.5.1_3.0_1737710425531.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("bert_base_case_financial_news_twitter_sentiment","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_case_financial_news_twitter_sentiment", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_case_financial_news_twitter_sentiment|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|405.9 MB|
+
+## References
+
+https://huggingface.co/Mikimi/bert-base-case-financial-news-twitter-sentiment
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_case_financial_news_twitter_sentiment_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_case_financial_news_twitter_sentiment_pipeline_en.md
new file mode 100644
index 00000000000000..58785b100afa5e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_case_financial_news_twitter_sentiment_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_case_financial_news_twitter_sentiment_pipeline pipeline BertForSequenceClassification from Mikimi
+author: John Snow Labs
+name: bert_base_case_financial_news_twitter_sentiment_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_case_financial_news_twitter_sentiment_pipeline` is a English model originally trained by Mikimi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_case_financial_news_twitter_sentiment_pipeline_en_5.5.1_3.0_1737710451121.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_case_financial_news_twitter_sentiment_pipeline_en_5.5.1_3.0_1737710451121.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_case_financial_news_twitter_sentiment_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_case_financial_news_twitter_sentiment_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_case_financial_news_twitter_sentiment_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|405.9 MB|
+
+## References
+
+https://huggingface.co/Mikimi/bert-base-case-financial-news-twitter-sentiment
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_cased_finetuned_bible_accelerate_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_cased_finetuned_bible_accelerate_en.md
new file mode 100644
index 00000000000000..95d3b4200948e9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_cased_finetuned_bible_accelerate_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_cased_finetuned_bible_accelerate BertEmbeddings from Pragash-Mohanarajah
+author: John Snow Labs
+name: bert_base_cased_finetuned_bible_accelerate
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_finetuned_bible_accelerate` is a English model originally trained by Pragash-Mohanarajah.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_finetuned_bible_accelerate_en_5.5.1_3.0_1737742553838.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_finetuned_bible_accelerate_en_5.5.1_3.0_1737742553838.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_base_cased_finetuned_bible_accelerate","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_base_cased_finetuned_bible_accelerate","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_cased_finetuned_bible_accelerate|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/Pragash-Mohanarajah/bert-base-cased-finetuned-bible-accelerate
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_cased_finetuned_bible_accelerate_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_cased_finetuned_bible_accelerate_pipeline_en.md
new file mode 100644
index 00000000000000..7ca9a6d22afcda
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_cased_finetuned_bible_accelerate_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_cased_finetuned_bible_accelerate_pipeline pipeline BertEmbeddings from Pragash-Mohanarajah
+author: John Snow Labs
+name: bert_base_cased_finetuned_bible_accelerate_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_finetuned_bible_accelerate_pipeline` is a English model originally trained by Pragash-Mohanarajah.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_finetuned_bible_accelerate_pipeline_en_5.5.1_3.0_1737742575538.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_finetuned_bible_accelerate_pipeline_en_5.5.1_3.0_1737742575538.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_cased_finetuned_bible_accelerate_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_cased_finetuned_bible_accelerate_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_cased_finetuned_bible_accelerate_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/Pragash-Mohanarajah/bert-base-cased-finetuned-bible-accelerate
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_cased_sclarge_squad_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_cased_sclarge_squad_en.md
new file mode 100644
index 00000000000000..32c5ca3a485941
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_cased_sclarge_squad_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_cased_sclarge_squad BertForQuestionAnswering from CambridgeMolecularEngineering
+author: John Snow Labs
+name: bert_base_cased_sclarge_squad
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_sclarge_squad` is a English model originally trained by CambridgeMolecularEngineering.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_sclarge_squad_en_5.5.1_3.0_1737751935854.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_sclarge_squad_en_5.5.1_3.0_1737751935854.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_cased_sclarge_squad","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_cased_sclarge_squad", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_cased_sclarge_squad|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/CambridgeMolecularEngineering/bert-base-cased-sclarge-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_cased_sclarge_squad_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_cased_sclarge_squad_pipeline_en.md
new file mode 100644
index 00000000000000..e2dddbd3701f17
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_cased_sclarge_squad_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_cased_sclarge_squad_pipeline pipeline BertForQuestionAnswering from CambridgeMolecularEngineering
+author: John Snow Labs
+name: bert_base_cased_sclarge_squad_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_sclarge_squad_pipeline` is a English model originally trained by CambridgeMolecularEngineering.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_sclarge_squad_pipeline_en_5.5.1_3.0_1737751957310.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_sclarge_squad_pipeline_en_5.5.1_3.0_1737751957310.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_cased_sclarge_squad_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_cased_sclarge_squad_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_cased_sclarge_squad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/CambridgeMolecularEngineering/bert-base-cased-sclarge-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_cased_scmedium_squad_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_cased_scmedium_squad_en.md
new file mode 100644
index 00000000000000..b5b53fb0783cf2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_cased_scmedium_squad_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_cased_scmedium_squad BertForQuestionAnswering from CambridgeMolecularEngineering
+author: John Snow Labs
+name: bert_base_cased_scmedium_squad
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_scmedium_squad` is a English model originally trained by CambridgeMolecularEngineering.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_scmedium_squad_en_5.5.1_3.0_1737746803005.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_scmedium_squad_en_5.5.1_3.0_1737746803005.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_cased_scmedium_squad","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_cased_scmedium_squad", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_cased_scmedium_squad|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/CambridgeMolecularEngineering/bert-base-cased-scmedium-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_cased_scmedium_squad_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_cased_scmedium_squad_pipeline_en.md
new file mode 100644
index 00000000000000..d9e85237573b41
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_cased_scmedium_squad_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_cased_scmedium_squad_pipeline pipeline BertForQuestionAnswering from CambridgeMolecularEngineering
+author: John Snow Labs
+name: bert_base_cased_scmedium_squad_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_scmedium_squad_pipeline` is a English model originally trained by CambridgeMolecularEngineering.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_scmedium_squad_pipeline_en_5.5.1_3.0_1737746835881.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_scmedium_squad_pipeline_en_5.5.1_3.0_1737746835881.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_cased_scmedium_squad_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_cased_scmedium_squad_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_cased_scmedium_squad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/CambridgeMolecularEngineering/bert-base-cased-scmedium-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_cased_scsmall_scqa2_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_cased_scsmall_scqa2_en.md
new file mode 100644
index 00000000000000..241dbaf680b01d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_cased_scsmall_scqa2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_cased_scsmall_scqa2 BertForQuestionAnswering from CambridgeMolecularEngineering
+author: John Snow Labs
+name: bert_base_cased_scsmall_scqa2
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_scsmall_scqa2` is a English model originally trained by CambridgeMolecularEngineering.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_scsmall_scqa2_en_5.5.1_3.0_1737752169701.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_scsmall_scqa2_en_5.5.1_3.0_1737752169701.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_cased_scsmall_scqa2","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_cased_scsmall_scqa2", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_cased_scsmall_scqa2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/CambridgeMolecularEngineering/bert-base-cased-scsmall-scqa2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_cased_scsmall_scqa2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_cased_scsmall_scqa2_pipeline_en.md
new file mode 100644
index 00000000000000..a4ef9396499867
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_cased_scsmall_scqa2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_cased_scsmall_scqa2_pipeline pipeline BertForQuestionAnswering from CambridgeMolecularEngineering
+author: John Snow Labs
+name: bert_base_cased_scsmall_scqa2_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_scsmall_scqa2_pipeline` is a English model originally trained by CambridgeMolecularEngineering.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_scsmall_scqa2_pipeline_en_5.5.1_3.0_1737752190943.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_scsmall_scqa2_pipeline_en_5.5.1_3.0_1737752190943.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_cased_scsmall_scqa2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_cased_scsmall_scqa2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_cased_scsmall_scqa2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/CambridgeMolecularEngineering/bert-base-cased-scsmall-scqa2
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_cased_wikitext2_hannahzhanng_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_cased_wikitext2_hannahzhanng_en.md
new file mode 100644
index 00000000000000..5e4eced67a53d4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_cased_wikitext2_hannahzhanng_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_cased_wikitext2_hannahzhanng BertEmbeddings from hannahzhanng
+author: John Snow Labs
+name: bert_base_cased_wikitext2_hannahzhanng
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_wikitext2_hannahzhanng` is a English model originally trained by hannahzhanng.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_wikitext2_hannahzhanng_en_5.5.1_3.0_1737708829601.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_wikitext2_hannahzhanng_en_5.5.1_3.0_1737708829601.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_base_cased_wikitext2_hannahzhanng","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_base_cased_wikitext2_hannahzhanng","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_cased_wikitext2_hannahzhanng|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|403.4 MB|
+
+## References
+
+https://huggingface.co/hannahzhanng/bert-base-cased-wikitext2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_cased_wikitext2_hannahzhanng_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_cased_wikitext2_hannahzhanng_pipeline_en.md
new file mode 100644
index 00000000000000..094e7da25d6647
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_cased_wikitext2_hannahzhanng_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_cased_wikitext2_hannahzhanng_pipeline pipeline BertEmbeddings from hannahzhanng
+author: John Snow Labs
+name: bert_base_cased_wikitext2_hannahzhanng_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_wikitext2_hannahzhanng_pipeline` is a English model originally trained by hannahzhanng.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_wikitext2_hannahzhanng_pipeline_en_5.5.1_3.0_1737708850532.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_wikitext2_hannahzhanng_pipeline_en_5.5.1_3.0_1737708850532.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_cased_wikitext2_hannahzhanng_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_cased_wikitext2_hannahzhanng_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_cased_wikitext2_hannahzhanng_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.5 MB|
+
+## References
+
+https://huggingface.co/hannahzhanng/bert-base-cased-wikitext2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_multilingual_cased_squad_spanish_pipeline_xx.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_multilingual_cased_squad_spanish_pipeline_xx.md
new file mode 100644
index 00000000000000..6932360d1b0d8a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_multilingual_cased_squad_spanish_pipeline_xx.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Multilingual bert_base_multilingual_cased_squad_spanish_pipeline pipeline BertForQuestionAnswering from ani2857
+author: John Snow Labs
+name: bert_base_multilingual_cased_squad_spanish_pipeline
+date: 2025-01-24
+tags: [xx, open_source, pipeline, onnx]
+task: Question Answering
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_cased_squad_spanish_pipeline` is a Multilingual model originally trained by ani2857.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_squad_spanish_pipeline_xx_5.5.1_3.0_1737752150751.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_squad_spanish_pipeline_xx_5.5.1_3.0_1737752150751.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_multilingual_cased_squad_spanish_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_multilingual_cased_squad_spanish_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_multilingual_cased_squad_spanish_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/ani2857/bert-base-multilingual-cased-squad-es
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_multilingual_cased_squad_spanish_xx.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_multilingual_cased_squad_spanish_xx.md
new file mode 100644
index 00000000000000..67ef3d1fd75fe0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_multilingual_cased_squad_spanish_xx.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Multilingual bert_base_multilingual_cased_squad_spanish BertForQuestionAnswering from ani2857
+author: John Snow Labs
+name: bert_base_multilingual_cased_squad_spanish
+date: 2025-01-24
+tags: [xx, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_cased_squad_spanish` is a Multilingual model originally trained by ani2857.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_squad_spanish_xx_5.5.1_3.0_1737752105734.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_squad_spanish_xx_5.5.1_3.0_1737752105734.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_multilingual_cased_squad_spanish","xx") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_multilingual_cased_squad_spanish", "xx")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_multilingual_cased_squad_spanish|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|xx|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/ani2857/bert-base-multilingual-cased-squad-es
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_multilingual_heq_v1_pipeline_xx.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_multilingual_heq_v1_pipeline_xx.md
new file mode 100644
index 00000000000000..2501180e02c401
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_multilingual_heq_v1_pipeline_xx.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Multilingual bert_base_multilingual_heq_v1_pipeline pipeline BertForQuestionAnswering from pig4431
+author: John Snow Labs
+name: bert_base_multilingual_heq_v1_pipeline
+date: 2025-01-24
+tags: [xx, open_source, pipeline, onnx]
+task: Question Answering
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_heq_v1_pipeline` is a Multilingual model originally trained by pig4431.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_heq_v1_pipeline_xx_5.5.1_3.0_1737751138734.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_heq_v1_pipeline_xx_5.5.1_3.0_1737751138734.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_multilingual_heq_v1_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_multilingual_heq_v1_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_multilingual_heq_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/pig4431/bert-base-multilingual-HeQ-v1
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_multilingual_heq_v1_xx.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_multilingual_heq_v1_xx.md
new file mode 100644
index 00000000000000..534b20a3c42b8d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_multilingual_heq_v1_xx.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Multilingual bert_base_multilingual_heq_v1 BertForQuestionAnswering from pig4431
+author: John Snow Labs
+name: bert_base_multilingual_heq_v1
+date: 2025-01-24
+tags: [xx, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_heq_v1` is a Multilingual model originally trained by pig4431.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_heq_v1_xx_5.5.1_3.0_1737751103706.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_heq_v1_xx_5.5.1_3.0_1737751103706.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_multilingual_heq_v1","xx") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_multilingual_heq_v1", "xx")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_multilingual_heq_v1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|xx|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/pig4431/bert-base-multilingual-HeQ-v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_qa_squad_portuguese_breton_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_qa_squad_portuguese_breton_en.md
new file mode 100644
index 00000000000000..9d84aea87ced8a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_qa_squad_portuguese_breton_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_qa_squad_portuguese_breton BertForQuestionAnswering from alexemanuel27
+author: John Snow Labs
+name: bert_base_qa_squad_portuguese_breton
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_qa_squad_portuguese_breton` is a English model originally trained by alexemanuel27.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_qa_squad_portuguese_breton_en_5.5.1_3.0_1737690668369.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_qa_squad_portuguese_breton_en_5.5.1_3.0_1737690668369.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_qa_squad_portuguese_breton","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_qa_squad_portuguese_breton", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_qa_squad_portuguese_breton|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|406.0 MB|
+
+## References
+
+https://huggingface.co/alexemanuel27/bert-base-qa-squad-pt-br
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_qa_squad_portuguese_breton_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_qa_squad_portuguese_breton_pipeline_en.md
new file mode 100644
index 00000000000000..1e63a18f4b4f70
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_qa_squad_portuguese_breton_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_qa_squad_portuguese_breton_pipeline pipeline BertForQuestionAnswering from alexemanuel27
+author: John Snow Labs
+name: bert_base_qa_squad_portuguese_breton_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_qa_squad_portuguese_breton_pipeline` is a English model originally trained by alexemanuel27.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_qa_squad_portuguese_breton_pipeline_en_5.5.1_3.0_1737690690635.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_qa_squad_portuguese_breton_pipeline_en_5.5.1_3.0_1737690690635.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_qa_squad_portuguese_breton_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_qa_squad_portuguese_breton_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_qa_squad_portuguese_breton_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.0 MB|
+
+## References
+
+https://huggingface.co/alexemanuel27/bert-base-qa-squad-pt-br
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_qarib_ar.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_qarib_ar.md
new file mode 100644
index 00000000000000..590a66e7c6cab8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_qarib_ar.md
@@ -0,0 +1,92 @@
+---
+layout: model
+title: Arabic bert_base_qarib BertEmbeddings from qarib
+author: John Snow Labs
+name: bert_base_qarib
+date: 2025-01-24
+tags: [bert, ar, open_source, fill_mask, onnx]
+task: Embeddings
+language: ar
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings  model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_qarib` is a Arabic model originally trained by qarib.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_qarib_ar_5.5.1_3.0_1737708260299.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_qarib_ar_5.5.1_3.0_1737708260299.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("documents")
+    
+    
+embeddings =BertEmbeddings.pretrained("bert_base_qarib","ar") \
+            .setInputCols(["documents","token"]) \
+            .setOutputCol("embeddings")
+
+pipeline = Pipeline().setStages([document_assembler, embeddings])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val document_assembler = new DocumentAssembler()
+    .setInputCol("text") 
+    .setOutputCol("embeddings")
+    
+val embeddings = BertEmbeddings 
+    .pretrained("bert_base_qarib", "ar")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("embeddings") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_qarib|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|ar|
+|Size:|504.0 MB|
+
+## References
+
+References
+
+https://huggingface.co/qarib/bert-base-qarib
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_qarib_pipeline_ar.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_qarib_pipeline_ar.md
new file mode 100644
index 00000000000000..05a26381989f54
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_qarib_pipeline_ar.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Arabic bert_base_qarib_pipeline pipeline BertEmbeddings from ahmedabdelali
+author: John Snow Labs
+name: bert_base_qarib_pipeline
+date: 2025-01-24
+tags: [ar, open_source, pipeline, onnx]
+task: Embeddings
+language: ar
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_qarib_pipeline` is a Arabic model originally trained by ahmedabdelali.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_qarib_pipeline_ar_5.5.1_3.0_1737708287260.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_qarib_pipeline_ar_5.5.1_3.0_1737708287260.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_qarib_pipeline", lang = "ar")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_qarib_pipeline", lang = "ar")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_qarib_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ar|
+|Size:|504.1 MB|
+
+## References
+
+https://huggingface.co/ahmedabdelali/bert-base-qarib
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_turkish_qa_istech_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_turkish_qa_istech_en.md
new file mode 100644
index 00000000000000..e64e75f6a1102d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_turkish_qa_istech_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_turkish_qa_istech BertForQuestionAnswering from muratsimsek003
+author: John Snow Labs
+name: bert_base_turkish_qa_istech
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_turkish_qa_istech` is a English model originally trained by muratsimsek003.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_turkish_qa_istech_en_5.5.1_3.0_1737751844662.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_turkish_qa_istech_en_5.5.1_3.0_1737751844662.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_turkish_qa_istech","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_turkish_qa_istech", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_turkish_qa_istech|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|688.9 MB|
+
+## References
+
+https://huggingface.co/muratsimsek003/bert-base-turkish-qa-istech
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_turkish_qa_istech_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_turkish_qa_istech_pipeline_en.md
new file mode 100644
index 00000000000000..6a7e3501cba778
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_turkish_qa_istech_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_turkish_qa_istech_pipeline pipeline BertForQuestionAnswering from muratsimsek003
+author: John Snow Labs
+name: bert_base_turkish_qa_istech_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_turkish_qa_istech_pipeline` is a English model originally trained by muratsimsek003.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_turkish_qa_istech_pipeline_en_5.5.1_3.0_1737751882716.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_turkish_qa_istech_pipeline_en_5.5.1_3.0_1737751882716.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_turkish_qa_istech_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_turkish_qa_istech_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_turkish_qa_istech_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|688.9 MB|
+
+## References
+
+https://huggingface.co/muratsimsek003/bert-base-turkish-qa-istech
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_0_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_0_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en.md
new file mode 100644
index 00000000000000..f7744d28c0558a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_0_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_ep_1_0_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_1_0_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_1_0_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_0_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en_5.5.1_3.0_1737747925862.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_0_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en_5.5.1_3.0_1737747925862.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_1_0_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_1_0_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_1_0_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-1.0-b-32-lr-4e-07-dp-0.5-ss-0-st-True-fh-False-hs-0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_0_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_0_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en.md
new file mode 100644
index 00000000000000..1751a9028a9c78
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_0_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_ep_1_0_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_1_0_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_1_0_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_0_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en_5.5.1_3.0_1737747950746.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_0_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en_5.5.1_3.0_1737747950746.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_ep_1_0_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_ep_1_0_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_1_0_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-1.0-b-32-lr-4e-07-dp-0.5-ss-0-st-True-fh-False-hs-0
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_0_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_100_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_0_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_100_en.md
new file mode 100644
index 00000000000000..34710b39308abd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_0_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_100_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_ep_1_0_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_100 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_1_0_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_100
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_1_0_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_100` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_0_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_100_en_5.5.1_3.0_1737747635236.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_0_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_100_en_5.5.1_3.0_1737747635236.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_1_0_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_100","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_1_0_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_100", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_1_0_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_100|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-1.0-b-32-lr-8e-07-dp-0.5-ss-0-st-False-fh-False-hs-100
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_0_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_100_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_0_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_100_pipeline_en.md
new file mode 100644
index 00000000000000..7c2e6644e88cd1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_0_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_100_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_ep_1_0_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_100_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_1_0_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_100_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_1_0_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_100_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_0_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_100_pipeline_en_5.5.1_3.0_1737747659735.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_0_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_100_pipeline_en_5.5.1_3.0_1737747659735.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_ep_1_0_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_100_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_ep_1_0_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_100_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_1_0_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_100_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-1.0-b-32-lr-8e-07-dp-0.5-ss-0-st-False-fh-False-hs-100
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_12_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_12_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en.md
new file mode 100644
index 00000000000000..aae8d9a4db2ac6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_12_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_ep_1_12_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_1_12_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_1_12_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_12_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en_5.5.1_3.0_1737738141233.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_12_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en_5.5.1_3.0_1737738141233.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_1_12_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_1_12_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_1_12_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-1.12-b-32-lr-8e-07-dp-0.5-ss-0-st-True-fh-False-hs-0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_12_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_12_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en.md
new file mode 100644
index 00000000000000..6d16a5556c4e87
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_12_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_ep_1_12_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_1_12_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_1_12_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_12_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en_5.5.1_3.0_1737738166061.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_12_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en_5.5.1_3.0_1737738166061.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_ep_1_12_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_ep_1_12_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_1_12_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-1.12-b-32-lr-8e-07-dp-0.5-ss-0-st-True-fh-False-hs-0
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_19_b_32_lr_8e_07_dp_0_5_swati_200_southern_sotho_false_fh_true_hs_0_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_19_b_32_lr_8e_07_dp_0_5_swati_200_southern_sotho_false_fh_true_hs_0_en.md
new file mode 100644
index 00000000000000..23959dead2dcd6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_19_b_32_lr_8e_07_dp_0_5_swati_200_southern_sotho_false_fh_true_hs_0_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_ep_1_19_b_32_lr_8e_07_dp_0_5_swati_200_southern_sotho_false_fh_true_hs_0 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_1_19_b_32_lr_8e_07_dp_0_5_swati_200_southern_sotho_false_fh_true_hs_0
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_1_19_b_32_lr_8e_07_dp_0_5_swati_200_southern_sotho_false_fh_true_hs_0` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_19_b_32_lr_8e_07_dp_0_5_swati_200_southern_sotho_false_fh_true_hs_0_en_5.5.1_3.0_1737747569440.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_19_b_32_lr_8e_07_dp_0_5_swati_200_southern_sotho_false_fh_true_hs_0_en_5.5.1_3.0_1737747569440.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_1_19_b_32_lr_8e_07_dp_0_5_swati_200_southern_sotho_false_fh_true_hs_0","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_1_19_b_32_lr_8e_07_dp_0_5_swati_200_southern_sotho_false_fh_true_hs_0", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_1_19_b_32_lr_8e_07_dp_0_5_swati_200_southern_sotho_false_fh_true_hs_0|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-1.19-b-32-lr-8e-07-dp-0.5-ss-200-st-False-fh-True-hs-0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_19_b_32_lr_8e_07_dp_0_5_swati_200_southern_sotho_false_fh_true_hs_0_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_19_b_32_lr_8e_07_dp_0_5_swati_200_southern_sotho_false_fh_true_hs_0_pipeline_en.md
new file mode 100644
index 00000000000000..da3c83e7be1325
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_19_b_32_lr_8e_07_dp_0_5_swati_200_southern_sotho_false_fh_true_hs_0_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_ep_1_19_b_32_lr_8e_07_dp_0_5_swati_200_southern_sotho_false_fh_true_hs_0_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_1_19_b_32_lr_8e_07_dp_0_5_swati_200_southern_sotho_false_fh_true_hs_0_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_1_19_b_32_lr_8e_07_dp_0_5_swati_200_southern_sotho_false_fh_true_hs_0_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_19_b_32_lr_8e_07_dp_0_5_swati_200_southern_sotho_false_fh_true_hs_0_pipeline_en_5.5.1_3.0_1737747590913.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_19_b_32_lr_8e_07_dp_0_5_swati_200_southern_sotho_false_fh_true_hs_0_pipeline_en_5.5.1_3.0_1737747590913.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_ep_1_19_b_32_lr_8e_07_dp_0_5_swati_200_southern_sotho_false_fh_true_hs_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_ep_1_19_b_32_lr_8e_07_dp_0_5_swati_200_southern_sotho_false_fh_true_hs_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_1_19_b_32_lr_8e_07_dp_0_5_swati_200_southern_sotho_false_fh_true_hs_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-1.19-b-32-lr-8e-07-dp-0.5-ss-200-st-False-fh-True-hs-0
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_56_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_56_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en.md
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+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_56_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_ep_1_56_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_1_56_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_1_56_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_56_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en_5.5.1_3.0_1737690871314.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_56_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en_5.5.1_3.0_1737690871314.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_1_56_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_1_56_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_1_56_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-1.56-b-32-lr-4e-07-dp-0.5-ss-0-st-True-fh-False-hs-0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_56_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_56_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en.md
new file mode 100644
index 00000000000000..e6db11aea720a3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_56_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_ep_1_56_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_1_56_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_1_56_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_56_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en_5.5.1_3.0_1737690892891.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_56_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en_5.5.1_3.0_1737690892891.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_ep_1_56_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_ep_1_56_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_1_56_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-1.56-b-32-lr-4e-07-dp-0.5-ss-0-st-True-fh-False-hs-0
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_79_b_32_lr_8e_07_dp_0_5_swati_400_southern_sotho_false_fh_true_hs_0_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_79_b_32_lr_8e_07_dp_0_5_swati_400_southern_sotho_false_fh_true_hs_0_en.md
new file mode 100644
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--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_79_b_32_lr_8e_07_dp_0_5_swati_400_southern_sotho_false_fh_true_hs_0_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_ep_1_79_b_32_lr_8e_07_dp_0_5_swati_400_southern_sotho_false_fh_true_hs_0 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_1_79_b_32_lr_8e_07_dp_0_5_swati_400_southern_sotho_false_fh_true_hs_0
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_1_79_b_32_lr_8e_07_dp_0_5_swati_400_southern_sotho_false_fh_true_hs_0` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_79_b_32_lr_8e_07_dp_0_5_swati_400_southern_sotho_false_fh_true_hs_0_en_5.5.1_3.0_1737747789098.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_79_b_32_lr_8e_07_dp_0_5_swati_400_southern_sotho_false_fh_true_hs_0_en_5.5.1_3.0_1737747789098.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_1_79_b_32_lr_8e_07_dp_0_5_swati_400_southern_sotho_false_fh_true_hs_0","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_1_79_b_32_lr_8e_07_dp_0_5_swati_400_southern_sotho_false_fh_true_hs_0", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_1_79_b_32_lr_8e_07_dp_0_5_swati_400_southern_sotho_false_fh_true_hs_0|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-1.79-b-32-lr-8e-07-dp-0.5-ss-400-st-False-fh-True-hs-0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_79_b_32_lr_8e_07_dp_0_5_swati_400_southern_sotho_false_fh_true_hs_0_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_79_b_32_lr_8e_07_dp_0_5_swati_400_southern_sotho_false_fh_true_hs_0_pipeline_en.md
new file mode 100644
index 00000000000000..053f5037135646
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_79_b_32_lr_8e_07_dp_0_5_swati_400_southern_sotho_false_fh_true_hs_0_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_ep_1_79_b_32_lr_8e_07_dp_0_5_swati_400_southern_sotho_false_fh_true_hs_0_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_1_79_b_32_lr_8e_07_dp_0_5_swati_400_southern_sotho_false_fh_true_hs_0_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_1_79_b_32_lr_8e_07_dp_0_5_swati_400_southern_sotho_false_fh_true_hs_0_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_79_b_32_lr_8e_07_dp_0_5_swati_400_southern_sotho_false_fh_true_hs_0_pipeline_en_5.5.1_3.0_1737747811270.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_79_b_32_lr_8e_07_dp_0_5_swati_400_southern_sotho_false_fh_true_hs_0_pipeline_en_5.5.1_3.0_1737747811270.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_ep_1_79_b_32_lr_8e_07_dp_0_5_swati_400_southern_sotho_false_fh_true_hs_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_ep_1_79_b_32_lr_8e_07_dp_0_5_swati_400_southern_sotho_false_fh_true_hs_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_1_79_b_32_lr_8e_07_dp_0_5_swati_400_southern_sotho_false_fh_true_hs_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-1.79-b-32-lr-8e-07-dp-0.5-ss-400-st-False-fh-True-hs-0
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_87_b_32_lr_1_2e_06_dp_0_3_swati_0_southern_sotho_true_fh_false_hs_0_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_87_b_32_lr_1_2e_06_dp_0_3_swati_0_southern_sotho_true_fh_false_hs_0_en.md
new file mode 100644
index 00000000000000..f50b76d3b50989
--- /dev/null
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@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_ep_1_87_b_32_lr_1_2e_06_dp_0_3_swati_0_southern_sotho_true_fh_false_hs_0 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_1_87_b_32_lr_1_2e_06_dp_0_3_swati_0_southern_sotho_true_fh_false_hs_0
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_1_87_b_32_lr_1_2e_06_dp_0_3_swati_0_southern_sotho_true_fh_false_hs_0` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_87_b_32_lr_1_2e_06_dp_0_3_swati_0_southern_sotho_true_fh_false_hs_0_en_5.5.1_3.0_1737738895512.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_87_b_32_lr_1_2e_06_dp_0_3_swati_0_southern_sotho_true_fh_false_hs_0_en_5.5.1_3.0_1737738895512.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_1_87_b_32_lr_1_2e_06_dp_0_3_swati_0_southern_sotho_true_fh_false_hs_0","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_1_87_b_32_lr_1_2e_06_dp_0_3_swati_0_southern_sotho_true_fh_false_hs_0", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_1_87_b_32_lr_1_2e_06_dp_0_3_swati_0_southern_sotho_true_fh_false_hs_0|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-1.87-b-32-lr-1.2e-06-dp-0.3-ss-0-st-True-fh-False-hs-0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_87_b_32_lr_1_2e_06_dp_0_3_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_87_b_32_lr_1_2e_06_dp_0_3_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en.md
new file mode 100644
index 00000000000000..03f5cbbce6e727
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_87_b_32_lr_1_2e_06_dp_0_3_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_ep_1_87_b_32_lr_1_2e_06_dp_0_3_swati_0_southern_sotho_true_fh_false_hs_0_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_1_87_b_32_lr_1_2e_06_dp_0_3_swati_0_southern_sotho_true_fh_false_hs_0_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_1_87_b_32_lr_1_2e_06_dp_0_3_swati_0_southern_sotho_true_fh_false_hs_0_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_87_b_32_lr_1_2e_06_dp_0_3_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en_5.5.1_3.0_1737738917393.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_87_b_32_lr_1_2e_06_dp_0_3_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en_5.5.1_3.0_1737738917393.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_ep_1_87_b_32_lr_1_2e_06_dp_0_3_swati_0_southern_sotho_true_fh_false_hs_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_ep_1_87_b_32_lr_1_2e_06_dp_0_3_swati_0_southern_sotho_true_fh_false_hs_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_1_87_b_32_lr_1_2e_06_dp_0_3_swati_0_southern_sotho_true_fh_false_hs_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-1.87-b-32-lr-1.2e-06-dp-0.3-ss-0-st-True-fh-False-hs-0
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_87_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_87_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en.md
new file mode 100644
index 00000000000000..6047248d986525
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_87_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_ep_1_87_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_1_87_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_1_87_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_87_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en_5.5.1_3.0_1737747208481.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_87_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en_5.5.1_3.0_1737747208481.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_1_87_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_1_87_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_1_87_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-1.87-b-32-lr-4e-07-dp-0.5-ss-0-st-True-fh-False-hs-0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_87_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_87_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en.md
new file mode 100644
index 00000000000000..e7b5b539db8732
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_87_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_ep_1_87_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_1_87_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_1_87_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_87_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en_5.5.1_3.0_1737747232163.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_87_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en_5.5.1_3.0_1737747232163.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_ep_1_87_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_ep_1_87_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_1_87_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-1.87-b-32-lr-4e-07-dp-0.5-ss-0-st-True-fh-False-hs-0
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_87_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_500_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_87_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_500_en.md
new file mode 100644
index 00000000000000..daf032956a190d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_87_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_500_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_ep_1_87_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_500 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_1_87_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_500
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_1_87_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_500` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_87_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_500_en_5.5.1_3.0_1737746769862.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_87_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_500_en_5.5.1_3.0_1737746769862.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_1_87_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_500","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_1_87_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_500", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_1_87_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_500|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-1.87-b-32-lr-8e-07-dp-0.5-ss-0-st-False-fh-False-hs-500
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_87_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_500_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_87_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_500_pipeline_en.md
new file mode 100644
index 00000000000000..89f0191689ec5c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_87_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_500_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_ep_1_87_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_500_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_1_87_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_500_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_1_87_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_500_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_87_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_500_pipeline_en_5.5.1_3.0_1737746799457.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_87_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_500_pipeline_en_5.5.1_3.0_1737746799457.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_ep_1_87_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_500_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_ep_1_87_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_500_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_1_87_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_500_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-1.87-b-32-lr-8e-07-dp-0.5-ss-0-st-False-fh-False-hs-500
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_87_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_87_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en.md
new file mode 100644
index 00000000000000..768eccc3c43aba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_87_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_ep_1_87_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_1_87_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_1_87_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_87_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en_5.5.1_3.0_1737747206321.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_87_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en_5.5.1_3.0_1737747206321.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_1_87_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_1_87_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_1_87_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-1.87-b-32-lr-8e-07-dp-0.5-ss-0-st-True-fh-False-hs-0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_87_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_87_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en.md
new file mode 100644
index 00000000000000..1d754438c9224b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_1_87_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_ep_1_87_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_1_87_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_1_87_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_87_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en_5.5.1_3.0_1737747229183.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_87_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en_5.5.1_3.0_1737747229183.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_ep_1_87_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_ep_1_87_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_1_87_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-1.87-b-32-lr-8e-07-dp-0.5-ss-0-st-True-fh-False-hs-0
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_2_25_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_2_25_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en.md
new file mode 100644
index 00000000000000..1c1633ae92ebd2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_2_25_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_ep_2_25_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_2_25_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_2_25_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_2_25_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en_5.5.1_3.0_1737746769587.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_2_25_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en_5.5.1_3.0_1737746769587.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_2_25_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_2_25_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_2_25_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-2.25-b-32-lr-4e-07-dp-0.5-ss-0-st-True-fh-False-hs-0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_2_25_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_2_25_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en.md
new file mode 100644
index 00000000000000..9e0b9e8b2a2366
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_2_25_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_ep_2_25_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_2_25_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_2_25_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_2_25_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en_5.5.1_3.0_1737746793938.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_2_25_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en_5.5.1_3.0_1737746793938.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_ep_2_25_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_ep_2_25_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_2_25_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-2.25-b-32-lr-4e-07-dp-0.5-ss-0-st-True-fh-False-hs-0
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_2_25_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_600_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_2_25_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_600_en.md
new file mode 100644
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--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_2_25_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_600_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_ep_2_25_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_600 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_2_25_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_600
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_2_25_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_600` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_2_25_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_600_en_5.5.1_3.0_1737690971634.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_2_25_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_600_en_5.5.1_3.0_1737690971634.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_2_25_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_600","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_2_25_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_600", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_2_25_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_600|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-2.25-b-32-lr-8e-07-dp-0.5-ss-0-st-False-fh-False-hs-600
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_2_25_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_600_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_2_25_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_600_pipeline_en.md
new file mode 100644
index 00000000000000..89657d285dd0be
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_2_25_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_600_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_ep_2_25_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_600_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_2_25_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_600_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_2_25_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_600_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_2_25_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_600_pipeline_en_5.5.1_3.0_1737690995209.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_2_25_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_600_pipeline_en_5.5.1_3.0_1737690995209.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_ep_2_25_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_600_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_ep_2_25_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_600_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_2_25_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_false_fh_false_hs_600_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-2.25-b-32-lr-8e-07-dp-0.5-ss-0-st-False-fh-False-hs-600
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_2_2_b_32_lr_4e_07_dp_1_0_swati_500_southern_sotho_false_fh_true_hs_0_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_2_2_b_32_lr_4e_07_dp_1_0_swati_500_southern_sotho_false_fh_true_hs_0_en.md
new file mode 100644
index 00000000000000..8a4e62499974ed
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_2_2_b_32_lr_4e_07_dp_1_0_swati_500_southern_sotho_false_fh_true_hs_0_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_ep_2_2_b_32_lr_4e_07_dp_1_0_swati_500_southern_sotho_false_fh_true_hs_0 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_2_2_b_32_lr_4e_07_dp_1_0_swati_500_southern_sotho_false_fh_true_hs_0
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_2_2_b_32_lr_4e_07_dp_1_0_swati_500_southern_sotho_false_fh_true_hs_0` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_2_2_b_32_lr_4e_07_dp_1_0_swati_500_southern_sotho_false_fh_true_hs_0_en_5.5.1_3.0_1737691562250.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_2_2_b_32_lr_4e_07_dp_1_0_swati_500_southern_sotho_false_fh_true_hs_0_en_5.5.1_3.0_1737691562250.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_2_2_b_32_lr_4e_07_dp_1_0_swati_500_southern_sotho_false_fh_true_hs_0","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_2_2_b_32_lr_4e_07_dp_1_0_swati_500_southern_sotho_false_fh_true_hs_0", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_2_2_b_32_lr_4e_07_dp_1_0_swati_500_southern_sotho_false_fh_true_hs_0|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-2.2-b-32-lr-4e-07-dp-1.0-ss-500-st-False-fh-True-hs-0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_2_2_b_32_lr_4e_07_dp_1_0_swati_500_southern_sotho_false_fh_true_hs_0_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_2_2_b_32_lr_4e_07_dp_1_0_swati_500_southern_sotho_false_fh_true_hs_0_pipeline_en.md
new file mode 100644
index 00000000000000..7f9747b72a3879
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_2_2_b_32_lr_4e_07_dp_1_0_swati_500_southern_sotho_false_fh_true_hs_0_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_ep_2_2_b_32_lr_4e_07_dp_1_0_swati_500_southern_sotho_false_fh_true_hs_0_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_2_2_b_32_lr_4e_07_dp_1_0_swati_500_southern_sotho_false_fh_true_hs_0_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_2_2_b_32_lr_4e_07_dp_1_0_swati_500_southern_sotho_false_fh_true_hs_0_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_2_2_b_32_lr_4e_07_dp_1_0_swati_500_southern_sotho_false_fh_true_hs_0_pipeline_en_5.5.1_3.0_1737691584035.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_2_2_b_32_lr_4e_07_dp_1_0_swati_500_southern_sotho_false_fh_true_hs_0_pipeline_en_5.5.1_3.0_1737691584035.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_ep_2_2_b_32_lr_4e_07_dp_1_0_swati_500_southern_sotho_false_fh_true_hs_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_ep_2_2_b_32_lr_4e_07_dp_1_0_swati_500_southern_sotho_false_fh_true_hs_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_2_2_b_32_lr_4e_07_dp_1_0_swati_500_southern_sotho_false_fh_true_hs_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-2.2-b-32-lr-4e-07-dp-1.0-ss-500-st-False-fh-True-hs-0
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_2_62_b_32_lr_8e_07_dp_0_5_swati_600_southern_sotho_false_fh_true_hs_0_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_2_62_b_32_lr_8e_07_dp_0_5_swati_600_southern_sotho_false_fh_true_hs_0_en.md
new file mode 100644
index 00000000000000..bf311c7733f83f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_2_62_b_32_lr_8e_07_dp_0_5_swati_600_southern_sotho_false_fh_true_hs_0_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_ep_2_62_b_32_lr_8e_07_dp_0_5_swati_600_southern_sotho_false_fh_true_hs_0 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_2_62_b_32_lr_8e_07_dp_0_5_swati_600_southern_sotho_false_fh_true_hs_0
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_2_62_b_32_lr_8e_07_dp_0_5_swati_600_southern_sotho_false_fh_true_hs_0` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_2_62_b_32_lr_8e_07_dp_0_5_swati_600_southern_sotho_false_fh_true_hs_0_en_5.5.1_3.0_1737747465447.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_2_62_b_32_lr_8e_07_dp_0_5_swati_600_southern_sotho_false_fh_true_hs_0_en_5.5.1_3.0_1737747465447.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_2_62_b_32_lr_8e_07_dp_0_5_swati_600_southern_sotho_false_fh_true_hs_0","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_2_62_b_32_lr_8e_07_dp_0_5_swati_600_southern_sotho_false_fh_true_hs_0", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_2_62_b_32_lr_8e_07_dp_0_5_swati_600_southern_sotho_false_fh_true_hs_0|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-2.62-b-32-lr-8e-07-dp-0.5-ss-600-st-False-fh-True-hs-0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_2_62_b_32_lr_8e_07_dp_0_5_swati_600_southern_sotho_false_fh_true_hs_0_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_2_62_b_32_lr_8e_07_dp_0_5_swati_600_southern_sotho_false_fh_true_hs_0_pipeline_en.md
new file mode 100644
index 00000000000000..857518b42d6913
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_2_62_b_32_lr_8e_07_dp_0_5_swati_600_southern_sotho_false_fh_true_hs_0_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_ep_2_62_b_32_lr_8e_07_dp_0_5_swati_600_southern_sotho_false_fh_true_hs_0_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_2_62_b_32_lr_8e_07_dp_0_5_swati_600_southern_sotho_false_fh_true_hs_0_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_2_62_b_32_lr_8e_07_dp_0_5_swati_600_southern_sotho_false_fh_true_hs_0_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_2_62_b_32_lr_8e_07_dp_0_5_swati_600_southern_sotho_false_fh_true_hs_0_pipeline_en_5.5.1_3.0_1737747491405.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_2_62_b_32_lr_8e_07_dp_0_5_swati_600_southern_sotho_false_fh_true_hs_0_pipeline_en_5.5.1_3.0_1737747491405.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_ep_2_62_b_32_lr_8e_07_dp_0_5_swati_600_southern_sotho_false_fh_true_hs_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_ep_2_62_b_32_lr_8e_07_dp_0_5_swati_600_southern_sotho_false_fh_true_hs_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_2_62_b_32_lr_8e_07_dp_0_5_swati_600_southern_sotho_false_fh_true_hs_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-2.62-b-32-lr-8e-07-dp-0.5-ss-600-st-False-fh-True-hs-0
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_3_44_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_3_44_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en.md
new file mode 100644
index 00000000000000..0976ce89027ab9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_3_44_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_ep_3_44_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_3_44_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_3_44_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_3_44_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en_5.5.1_3.0_1737747335731.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_3_44_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en_5.5.1_3.0_1737747335731.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_3_44_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_3_44_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_3_44_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-3.44-b-32-lr-4e-07-dp-0.5-ss-0-st-True-fh-False-hs-0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_3_44_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_3_44_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en.md
new file mode 100644
index 00000000000000..d8a49d65ba6924
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_3_44_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_ep_3_44_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_3_44_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_3_44_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_3_44_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en_5.5.1_3.0_1737747359673.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_3_44_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en_5.5.1_3.0_1737747359673.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_ep_3_44_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_ep_3_44_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_3_44_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-3.44-b-32-lr-4e-07-dp-0.5-ss-0-st-True-fh-False-hs-0
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_3_44_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_3_44_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en.md
new file mode 100644
index 00000000000000..213e947c275fe4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_3_44_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_ep_3_44_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_3_44_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_3_44_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_3_44_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en_5.5.1_3.0_1737739285640.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_3_44_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en_5.5.1_3.0_1737739285640.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_3_44_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_3_44_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_3_44_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-3.44-b-32-lr-8e-07-dp-0.5-ss-0-st-True-fh-False-hs-0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_3_44_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_3_44_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en.md
new file mode 100644
index 00000000000000..cb5efa1226cd0f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_3_44_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_ep_3_44_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_3_44_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_3_44_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_3_44_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en_5.5.1_3.0_1737739313306.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_3_44_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en_5.5.1_3.0_1737739313306.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_ep_3_44_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_ep_3_44_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_3_44_b_32_lr_8e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-3.44-b-32-lr-8e-07-dp-0.5-ss-0-st-True-fh-False-hs-0
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_5_02_b_32_lr_8e_07_dp_0_5_swati_900_southern_sotho_false_fh_true_hs_0_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_5_02_b_32_lr_8e_07_dp_0_5_swati_900_southern_sotho_false_fh_true_hs_0_en.md
new file mode 100644
index 00000000000000..59a8996de8b641
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_5_02_b_32_lr_8e_07_dp_0_5_swati_900_southern_sotho_false_fh_true_hs_0_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_ep_5_02_b_32_lr_8e_07_dp_0_5_swati_900_southern_sotho_false_fh_true_hs_0 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_5_02_b_32_lr_8e_07_dp_0_5_swati_900_southern_sotho_false_fh_true_hs_0
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_5_02_b_32_lr_8e_07_dp_0_5_swati_900_southern_sotho_false_fh_true_hs_0` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_5_02_b_32_lr_8e_07_dp_0_5_swati_900_southern_sotho_false_fh_true_hs_0_en_5.5.1_3.0_1737691715914.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_5_02_b_32_lr_8e_07_dp_0_5_swati_900_southern_sotho_false_fh_true_hs_0_en_5.5.1_3.0_1737691715914.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_5_02_b_32_lr_8e_07_dp_0_5_swati_900_southern_sotho_false_fh_true_hs_0","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_5_02_b_32_lr_8e_07_dp_0_5_swati_900_southern_sotho_false_fh_true_hs_0", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_5_02_b_32_lr_8e_07_dp_0_5_swati_900_southern_sotho_false_fh_true_hs_0|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-5.02-b-32-lr-8e-07-dp-0.5-ss-900-st-False-fh-True-hs-0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_5_02_b_32_lr_8e_07_dp_0_5_swati_900_southern_sotho_false_fh_true_hs_0_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_5_02_b_32_lr_8e_07_dp_0_5_swati_900_southern_sotho_false_fh_true_hs_0_pipeline_en.md
new file mode 100644
index 00000000000000..31c4f474691150
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_ep_5_02_b_32_lr_8e_07_dp_0_5_swati_900_southern_sotho_false_fh_true_hs_0_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_ep_5_02_b_32_lr_8e_07_dp_0_5_swati_900_southern_sotho_false_fh_true_hs_0_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_5_02_b_32_lr_8e_07_dp_0_5_swati_900_southern_sotho_false_fh_true_hs_0_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_5_02_b_32_lr_8e_07_dp_0_5_swati_900_southern_sotho_false_fh_true_hs_0_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_5_02_b_32_lr_8e_07_dp_0_5_swati_900_southern_sotho_false_fh_true_hs_0_pipeline_en_5.5.1_3.0_1737691737468.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_5_02_b_32_lr_8e_07_dp_0_5_swati_900_southern_sotho_false_fh_true_hs_0_pipeline_en_5.5.1_3.0_1737691737468.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_ep_5_02_b_32_lr_8e_07_dp_0_5_swati_900_southern_sotho_false_fh_true_hs_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_ep_5_02_b_32_lr_8e_07_dp_0_5_swati_900_southern_sotho_false_fh_true_hs_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_5_02_b_32_lr_8e_07_dp_0_5_swati_900_southern_sotho_false_fh_true_hs_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-5.02-b-32-lr-8e-07-dp-0.5-ss-900-st-False-fh-True-hs-0
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_0_5_lr_1e_05_wd_0_001_dp_0_1_swati_0_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_0_5_lr_1e_05_wd_0_001_dp_0_1_swati_0_en.md
new file mode 100644
index 00000000000000..79966d61633456
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_0_5_lr_1e_05_wd_0_001_dp_0_1_swati_0_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_0_5_lr_1e_05_wd_0_001_dp_0_1_swati_0 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_0_5_lr_1e_05_wd_0_001_dp_0_1_swati_0
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_0_5_lr_1e_05_wd_0_001_dp_0_1_swati_0` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_0_5_lr_1e_05_wd_0_001_dp_0_1_swati_0_en_5.5.1_3.0_1737738281797.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_0_5_lr_1e_05_wd_0_001_dp_0_1_swati_0_en_5.5.1_3.0_1737738281797.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_0_5_lr_1e_05_wd_0_001_dp_0_1_swati_0","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_0_5_lr_1e_05_wd_0_001_dp_0_1_swati_0", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_0_5_lr_1e_05_wd_0_001_dp_0_1_swati_0|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-0.5-lr-1e-05-wd-0.001-dp-0.1-ss-0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_0_5_lr_1e_05_wd_0_001_dp_0_1_swati_0_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_0_5_lr_1e_05_wd_0_001_dp_0_1_swati_0_pipeline_en.md
new file mode 100644
index 00000000000000..28bb0035ccd216
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_0_5_lr_1e_05_wd_0_001_dp_0_1_swati_0_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_0_5_lr_1e_05_wd_0_001_dp_0_1_swati_0_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_0_5_lr_1e_05_wd_0_001_dp_0_1_swati_0_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_0_5_lr_1e_05_wd_0_001_dp_0_1_swati_0_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_0_5_lr_1e_05_wd_0_001_dp_0_1_swati_0_pipeline_en_5.5.1_3.0_1737738303933.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_0_5_lr_1e_05_wd_0_001_dp_0_1_swati_0_pipeline_en_5.5.1_3.0_1737738303933.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_0_5_lr_1e_05_wd_0_001_dp_0_1_swati_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_0_5_lr_1e_05_wd_0_001_dp_0_1_swati_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_0_5_lr_1e_05_wd_0_001_dp_0_1_swati_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-0.5-lr-1e-05-wd-0.001-dp-0.1-ss-0
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_400_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_400_en.md
new file mode 100644
index 00000000000000..93f125d7c433b9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_400_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_400 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_400
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_400` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_400_en_5.5.1_3.0_1737691794610.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_400_en_5.5.1_3.0_1737691794610.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_400","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_400", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_400|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.0-lr-1e-05-wd-0.001-dp-0.2-ss-0-st-False-fh-False-hs-400
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_400_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_400_pipeline_en.md
new file mode 100644
index 00000000000000..5b072c821b4c8e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_400_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_400_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_400_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_400_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_400_pipeline_en_5.5.1_3.0_1737691816419.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_400_pipeline_en_5.5.1_3.0_1737691816419.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_400_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_400_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_400_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.0-lr-1e-05-wd-0.001-dp-0.2-ss-0-st-False-fh-False-hs-400
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_3773_southern_sotho_false_fh_true_hs_666_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_3773_southern_sotho_false_fh_true_hs_666_en.md
new file mode 100644
index 00000000000000..9dbea91ae3f211
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_3773_southern_sotho_false_fh_true_hs_666_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_3773_southern_sotho_false_fh_true_hs_666 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_3773_southern_sotho_false_fh_true_hs_666
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_3773_southern_sotho_false_fh_true_hs_666` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_3773_southern_sotho_false_fh_true_hs_666_en_5.5.1_3.0_1737747823878.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_3773_southern_sotho_false_fh_true_hs_666_en_5.5.1_3.0_1737747823878.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_3773_southern_sotho_false_fh_true_hs_666","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_3773_southern_sotho_false_fh_true_hs_666", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_3773_southern_sotho_false_fh_true_hs_666|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.0-lr-1e-05-wd-0.001-dp-0.2-ss-3773-st-False-fh-True-hs-666
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_3773_southern_sotho_false_fh_true_hs_666_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_3773_southern_sotho_false_fh_true_hs_666_pipeline_en.md
new file mode 100644
index 00000000000000..92f8e6927cde2a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_3773_southern_sotho_false_fh_true_hs_666_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_3773_southern_sotho_false_fh_true_hs_666_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_3773_southern_sotho_false_fh_true_hs_666_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_3773_southern_sotho_false_fh_true_hs_666_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_3773_southern_sotho_false_fh_true_hs_666_pipeline_en_5.5.1_3.0_1737747847180.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_3773_southern_sotho_false_fh_true_hs_666_pipeline_en_5.5.1_3.0_1737747847180.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_3773_southern_sotho_false_fh_true_hs_666_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_3773_southern_sotho_false_fh_true_hs_666_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_3773_southern_sotho_false_fh_true_hs_666_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.0-lr-1e-05-wd-0.001-dp-0.2-ss-3773-st-False-fh-True-hs-666
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_4_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_4_en.md
new file mode 100644
index 00000000000000..b12017f70ffffc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_4_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_4 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_4
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_4` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_4_en_5.5.1_3.0_1737747056055.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_4_en_5.5.1_3.0_1737747056055.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_4","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_4", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_4|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.0-lr-1e-05-wd-0.001-dp-0.4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_4_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_4_pipeline_en.md
new file mode 100644
index 00000000000000..459dc59afcf3bf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_4_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_4_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_4_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_4_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_4_pipeline_en_5.5.1_3.0_1737747077728.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_4_pipeline_en_5.5.1_3.0_1737747077728.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.0-lr-1e-05-wd-0.001-dp-0.4
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_6_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_6_en.md
new file mode 100644
index 00000000000000..f3494a2b01a5e5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_6_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_6 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_6
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_6` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_6_en_5.5.1_3.0_1737738697290.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_6_en_5.5.1_3.0_1737738697290.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_6","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_6", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_6|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.0-lr-1e-05-wd-0.001-dp-0.6
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_6_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_6_pipeline_en.md
new file mode 100644
index 00000000000000..951a8398b089fc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_6_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_6_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_6_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_6_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_6_pipeline_en_5.5.1_3.0_1737738719361.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_6_pipeline_en_5.5.1_3.0_1737738719361.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_6_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_6_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_6_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.0-lr-1e-05-wd-0.001-dp-0.6
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_99999_swati_0_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_99999_swati_0_en.md
new file mode 100644
index 00000000000000..71e984d39d0ae4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_99999_swati_0_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_99999_swati_0 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_99999_swati_0
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_99999_swati_0` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_99999_swati_0_en_5.5.1_3.0_1737747904144.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_99999_swati_0_en_5.5.1_3.0_1737747904144.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_99999_swati_0","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_99999_swati_0", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_99999_swati_0|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.0-lr-1e-05-wd-0.001-dp-0.99999-ss-0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_99999_swati_0_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_99999_swati_0_pipeline_en.md
new file mode 100644
index 00000000000000..2465f1e7e30c41
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_99999_swati_0_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_99999_swati_0_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_99999_swati_0_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_99999_swati_0_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_99999_swati_0_pipeline_en_5.5.1_3.0_1737747926358.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_99999_swati_0_pipeline_en_5.5.1_3.0_1737747926358.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_99999_swati_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_99999_swati_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_99999_swati_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.0-lr-1e-05-wd-0.001-dp-0.99999-ss-0
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_01_swati_0_southern_sotho_true_fh_true_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_01_swati_0_southern_sotho_true_fh_true_en.md
new file mode 100644
index 00000000000000..ace12f1454f168
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_01_swati_0_southern_sotho_true_fh_true_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_01_swati_0_southern_sotho_true_fh_true BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_01_swati_0_southern_sotho_true_fh_true
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_01_swati_0_southern_sotho_true_fh_true` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_01_swati_0_southern_sotho_true_fh_true_en_5.5.1_3.0_1737748085306.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_01_swati_0_southern_sotho_true_fh_true_en_5.5.1_3.0_1737748085306.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_01_swati_0_southern_sotho_true_fh_true","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_01_swati_0_southern_sotho_true_fh_true", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_01_swati_0_southern_sotho_true_fh_true|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.0-lr-1e-06-wd-0.001-dp-0.01-ss-0-st-True-fh-True
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_01_swati_0_southern_sotho_true_fh_true_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_01_swati_0_southern_sotho_true_fh_true_pipeline_en.md
new file mode 100644
index 00000000000000..b5107ce29747d3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_01_swati_0_southern_sotho_true_fh_true_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_01_swati_0_southern_sotho_true_fh_true_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_01_swati_0_southern_sotho_true_fh_true_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_01_swati_0_southern_sotho_true_fh_true_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_01_swati_0_southern_sotho_true_fh_true_pipeline_en_5.5.1_3.0_1737748110316.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_01_swati_0_southern_sotho_true_fh_true_pipeline_en_5.5.1_3.0_1737748110316.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_01_swati_0_southern_sotho_true_fh_true_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_01_swati_0_southern_sotho_true_fh_true_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_01_swati_0_southern_sotho_true_fh_true_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.0-lr-1e-06-wd-0.001-dp-0.01-ss-0-st-True-fh-True
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_02_swati_0_southern_sotho_true_fh_true_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_02_swati_0_southern_sotho_true_fh_true_en.md
new file mode 100644
index 00000000000000..8f722a3bdcd254
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_02_swati_0_southern_sotho_true_fh_true_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_02_swati_0_southern_sotho_true_fh_true BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_02_swati_0_southern_sotho_true_fh_true
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_02_swati_0_southern_sotho_true_fh_true` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_02_swati_0_southern_sotho_true_fh_true_en_5.5.1_3.0_1737738856115.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_02_swati_0_southern_sotho_true_fh_true_en_5.5.1_3.0_1737738856115.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_02_swati_0_southern_sotho_true_fh_true","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_02_swati_0_southern_sotho_true_fh_true", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_02_swati_0_southern_sotho_true_fh_true|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.0-lr-1e-06-wd-0.001-dp-0.02-ss-0-st-True-fh-True
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_02_swati_0_southern_sotho_true_fh_true_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_02_swati_0_southern_sotho_true_fh_true_pipeline_en.md
new file mode 100644
index 00000000000000..b6c598ee1a4759
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_02_swati_0_southern_sotho_true_fh_true_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_02_swati_0_southern_sotho_true_fh_true_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_02_swati_0_southern_sotho_true_fh_true_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_02_swati_0_southern_sotho_true_fh_true_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_02_swati_0_southern_sotho_true_fh_true_pipeline_en_5.5.1_3.0_1737738878133.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_02_swati_0_southern_sotho_true_fh_true_pipeline_en_5.5.1_3.0_1737738878133.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_02_swati_0_southern_sotho_true_fh_true_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_02_swati_0_southern_sotho_true_fh_true_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_02_swati_0_southern_sotho_true_fh_true_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.0-lr-1e-06-wd-0.001-dp-0.02-ss-0-st-True-fh-True
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_1000_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_1000_en.md
new file mode 100644
index 00000000000000..5ee44fcc45582f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_1000_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_1000 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_1000
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_1000` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_1000_en_5.5.1_3.0_1737747277169.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_1000_en_5.5.1_3.0_1737747277169.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_1000","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_1000", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_1000|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.0-lr-1e-06-wd-0.001-dp-0.2-ss-0-st-False-fh-False-hs-1000
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_1000_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_1000_pipeline_en.md
new file mode 100644
index 00000000000000..7848d68d04caea
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_1000_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_1000_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_1000_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_1000_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_1000_pipeline_en_5.5.1_3.0_1737747298783.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_1000_pipeline_en_5.5.1_3.0_1737747298783.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_1000_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_1000_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_1000_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.0-lr-1e-06-wd-0.001-dp-0.2-ss-0-st-False-fh-False-hs-1000
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_300_southern_sotho_true_fh_true_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_300_southern_sotho_true_fh_true_en.md
new file mode 100644
index 00000000000000..fa352ec455dce2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_300_southern_sotho_true_fh_true_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_300_southern_sotho_true_fh_true BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_300_southern_sotho_true_fh_true
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_300_southern_sotho_true_fh_true` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_300_southern_sotho_true_fh_true_en_5.5.1_3.0_1737748142726.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_300_southern_sotho_true_fh_true_en_5.5.1_3.0_1737748142726.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_300_southern_sotho_true_fh_true","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_300_southern_sotho_true_fh_true", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_300_southern_sotho_true_fh_true|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.0-lr-1e-06-wd-0.001-dp-0.2-ss-300-st-True-fh-True
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_300_southern_sotho_true_fh_true_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_300_southern_sotho_true_fh_true_pipeline_en.md
new file mode 100644
index 00000000000000..ac8ca7cf23e272
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_300_southern_sotho_true_fh_true_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_300_southern_sotho_true_fh_true_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_300_southern_sotho_true_fh_true_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_300_southern_sotho_true_fh_true_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_300_southern_sotho_true_fh_true_pipeline_en_5.5.1_3.0_1737748163823.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_300_southern_sotho_true_fh_true_pipeline_en_5.5.1_3.0_1737748163823.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_300_southern_sotho_true_fh_true_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_300_southern_sotho_true_fh_true_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_300_southern_sotho_true_fh_true_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.0-lr-1e-06-wd-0.001-dp-0.2-ss-300-st-True-fh-True
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_6446_southern_sotho_false_fh_true_hs_666_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_6446_southern_sotho_false_fh_true_hs_666_en.md
new file mode 100644
index 00000000000000..a73dbd2b2ebb6e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_6446_southern_sotho_false_fh_true_hs_666_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_6446_southern_sotho_false_fh_true_hs_666 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_6446_southern_sotho_false_fh_true_hs_666
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_6446_southern_sotho_false_fh_true_hs_666` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_6446_southern_sotho_false_fh_true_hs_666_en_5.5.1_3.0_1737738840409.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_6446_southern_sotho_false_fh_true_hs_666_en_5.5.1_3.0_1737738840409.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_6446_southern_sotho_false_fh_true_hs_666","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_6446_southern_sotho_false_fh_true_hs_666", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_6446_southern_sotho_false_fh_true_hs_666|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.0-lr-1e-06-wd-0.001-dp-0.2-ss-6446-st-False-fh-True-hs-666
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_6446_southern_sotho_false_fh_true_hs_666_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_6446_southern_sotho_false_fh_true_hs_666_pipeline_en.md
new file mode 100644
index 00000000000000..b0bdd8833f4e7f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_6446_southern_sotho_false_fh_true_hs_666_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_6446_southern_sotho_false_fh_true_hs_666_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_6446_southern_sotho_false_fh_true_hs_666_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_6446_southern_sotho_false_fh_true_hs_666_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_6446_southern_sotho_false_fh_true_hs_666_pipeline_en_5.5.1_3.0_1737738861958.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_6446_southern_sotho_false_fh_true_hs_666_pipeline_en_5.5.1_3.0_1737738861958.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_6446_southern_sotho_false_fh_true_hs_666_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_6446_southern_sotho_false_fh_true_hs_666_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_6446_southern_sotho_false_fh_true_hs_666_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.0-lr-1e-06-wd-0.001-dp-0.2-ss-6446-st-False-fh-True-hs-666
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_9_swati_0_southern_sotho_true_fh_true_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_9_swati_0_southern_sotho_true_fh_true_en.md
new file mode 100644
index 00000000000000..fa198888695004
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_9_swati_0_southern_sotho_true_fh_true_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_9_swati_0_southern_sotho_true_fh_true BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_9_swati_0_southern_sotho_true_fh_true
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_9_swati_0_southern_sotho_true_fh_true` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_9_swati_0_southern_sotho_true_fh_true_en_5.5.1_3.0_1737747965911.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_9_swati_0_southern_sotho_true_fh_true_en_5.5.1_3.0_1737747965911.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_9_swati_0_southern_sotho_true_fh_true","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_9_swati_0_southern_sotho_true_fh_true", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_9_swati_0_southern_sotho_true_fh_true|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.0-lr-1e-06-wd-0.001-dp-0.9-ss-0-st-True-fh-True
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_9_swati_0_southern_sotho_true_fh_true_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_9_swati_0_southern_sotho_true_fh_true_pipeline_en.md
new file mode 100644
index 00000000000000..b34280af3821e9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_9_swati_0_southern_sotho_true_fh_true_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_9_swati_0_southern_sotho_true_fh_true_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_9_swati_0_southern_sotho_true_fh_true_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_9_swati_0_southern_sotho_true_fh_true_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_9_swati_0_southern_sotho_true_fh_true_pipeline_en_5.5.1_3.0_1737747988255.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_9_swati_0_southern_sotho_true_fh_true_pipeline_en_5.5.1_3.0_1737747988255.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_9_swati_0_southern_sotho_true_fh_true_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_9_swati_0_southern_sotho_true_fh_true_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_9_swati_0_southern_sotho_true_fh_true_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.0-lr-1e-06-wd-0.001-dp-0.9-ss-0-st-True-fh-True
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_07_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_07_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true_en.md
new file mode 100644
index 00000000000000..3fb256441258e7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_07_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_0_lr_1e_07_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_0_lr_1e_07_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_0_lr_1e_07_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_07_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true_en_5.5.1_3.0_1737690985290.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_07_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true_en_5.5.1_3.0_1737690985290.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_07_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_07_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_0_lr_1e_07_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.0-lr-1e-07-wd-0.001-dp-0.2-ss-0-st-True-fh-True
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_07_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_07_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true_pipeline_en.md
new file mode 100644
index 00000000000000..32bc54e17fb1e6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_07_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_0_lr_1e_07_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_0_lr_1e_07_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_0_lr_1e_07_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_07_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true_pipeline_en_5.5.1_3.0_1737691006826.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_07_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true_pipeline_en_5.5.1_3.0_1737691006826.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_07_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_07_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_0_lr_1e_07_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.0-lr-1e-07-wd-0.001-dp-0.2-ss-0-st-True-fh-True
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_4e_06_wd_0_0001_glb_sindhi_1_data_sindhi_0_fx_head_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_4e_06_wd_0_0001_glb_sindhi_1_data_sindhi_0_fx_head_en.md
new file mode 100644
index 00000000000000..12f0dc81d8c29a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_4e_06_wd_0_0001_glb_sindhi_1_data_sindhi_0_fx_head_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_0_lr_4e_06_wd_0_0001_glb_sindhi_1_data_sindhi_0_fx_head BertForQuestionAnswering from aman-mehra
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_0_lr_4e_06_wd_0_0001_glb_sindhi_1_data_sindhi_0_fx_head
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_0_lr_4e_06_wd_0_0001_glb_sindhi_1_data_sindhi_0_fx_head` is a English model originally trained by aman-mehra.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_4e_06_wd_0_0001_glb_sindhi_1_data_sindhi_0_fx_head_en_5.5.1_3.0_1737690482914.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_4e_06_wd_0_0001_glb_sindhi_1_data_sindhi_0_fx_head_en_5.5.1_3.0_1737690482914.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_0_lr_4e_06_wd_0_0001_glb_sindhi_1_data_sindhi_0_fx_head","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_0_lr_4e_06_wd_0_0001_glb_sindhi_1_data_sindhi_0_fx_head", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_0_lr_4e_06_wd_0_0001_glb_sindhi_1_data_sindhi_0_fx_head|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/aman-mehra/bert-base-uncased-finetune-squad-ep-1.0-lr-4e-06-wd-0.0001-glb_sd-1-data_sd-0-fx_head
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_4e_06_wd_0_0001_glb_sindhi_1_data_sindhi_0_fx_head_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_4e_06_wd_0_0001_glb_sindhi_1_data_sindhi_0_fx_head_pipeline_en.md
new file mode 100644
index 00000000000000..57680724b403d5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_4e_06_wd_0_0001_glb_sindhi_1_data_sindhi_0_fx_head_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_0_lr_4e_06_wd_0_0001_glb_sindhi_1_data_sindhi_0_fx_head_pipeline pipeline BertForQuestionAnswering from aman-mehra
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_0_lr_4e_06_wd_0_0001_glb_sindhi_1_data_sindhi_0_fx_head_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_0_lr_4e_06_wd_0_0001_glb_sindhi_1_data_sindhi_0_fx_head_pipeline` is a English model originally trained by aman-mehra.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_4e_06_wd_0_0001_glb_sindhi_1_data_sindhi_0_fx_head_pipeline_en_5.5.1_3.0_1737690508466.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_4e_06_wd_0_0001_glb_sindhi_1_data_sindhi_0_fx_head_pipeline_en_5.5.1_3.0_1737690508466.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_0_lr_4e_06_wd_0_0001_glb_sindhi_1_data_sindhi_0_fx_head_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_0_lr_4e_06_wd_0_0001_glb_sindhi_1_data_sindhi_0_fx_head_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_0_lr_4e_06_wd_0_0001_glb_sindhi_1_data_sindhi_0_fx_head_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/aman-mehra/bert-base-uncased-finetune-squad-ep-1.0-lr-4e-06-wd-0.0001-glb_sd-1-data_sd-0-fx_head
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_100_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_100_en.md
new file mode 100644
index 00000000000000..ab7f3af57b5876
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_100_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_100 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_100
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_100` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_100_en_5.5.1_3.0_1737747420009.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_100_en_5.5.1_3.0_1737747420009.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_100","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_100", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_100|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.0-lr-5e-06-wd-0.001-dp-0.2-ss-0-st-False-fh-False-hs-100
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_100_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_100_pipeline_en.md
new file mode 100644
index 00000000000000..71526c1c715c47
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_100_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_100_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_100_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_100_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_100_pipeline_en_5.5.1_3.0_1737747443442.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_100_pipeline_en_5.5.1_3.0_1737747443442.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_100_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_100_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_100_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.0-lr-5e-06-wd-0.001-dp-0.2-ss-0-st-False-fh-False-hs-100
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_5e_07_wd_0_001_dp_0_999_swati_0_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_5e_07_wd_0_001_dp_0_999_swati_0_en.md
new file mode 100644
index 00000000000000..db80ca80e3c129
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_5e_07_wd_0_001_dp_0_999_swati_0_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_0_lr_5e_07_wd_0_001_dp_0_999_swati_0 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_0_lr_5e_07_wd_0_001_dp_0_999_swati_0
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_0_lr_5e_07_wd_0_001_dp_0_999_swati_0` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_5e_07_wd_0_001_dp_0_999_swati_0_en_5.5.1_3.0_1737747414153.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_5e_07_wd_0_001_dp_0_999_swati_0_en_5.5.1_3.0_1737747414153.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_0_lr_5e_07_wd_0_001_dp_0_999_swati_0","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_0_lr_5e_07_wd_0_001_dp_0_999_swati_0", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_0_lr_5e_07_wd_0_001_dp_0_999_swati_0|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.0-lr-5e-07-wd-0.001-dp-0.999-ss-0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_5e_07_wd_0_001_dp_0_999_swati_0_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_5e_07_wd_0_001_dp_0_999_swati_0_pipeline_en.md
new file mode 100644
index 00000000000000..8d1d31b664fede
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_0_lr_5e_07_wd_0_001_dp_0_999_swati_0_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_0_lr_5e_07_wd_0_001_dp_0_999_swati_0_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_0_lr_5e_07_wd_0_001_dp_0_999_swati_0_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_0_lr_5e_07_wd_0_001_dp_0_999_swati_0_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_5e_07_wd_0_001_dp_0_999_swati_0_pipeline_en_5.5.1_3.0_1737747435815.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_5e_07_wd_0_001_dp_0_999_swati_0_pipeline_en_5.5.1_3.0_1737747435815.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_0_lr_5e_07_wd_0_001_dp_0_999_swati_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_0_lr_5e_07_wd_0_001_dp_0_999_swati_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_0_lr_5e_07_wd_0_001_dp_0_999_swati_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.0-lr-5e-07-wd-0.001-dp-0.999-ss-0
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_4_lr_1e_05_wd_0_001_dp_0_1_swati_0_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_4_lr_1e_05_wd_0_001_dp_0_1_swati_0_en.md
new file mode 100644
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--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_4_lr_1e_05_wd_0_001_dp_0_1_swati_0_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_4_lr_1e_05_wd_0_001_dp_0_1_swati_0 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_4_lr_1e_05_wd_0_001_dp_0_1_swati_0
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_4_lr_1e_05_wd_0_001_dp_0_1_swati_0` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_4_lr_1e_05_wd_0_001_dp_0_1_swati_0_en_5.5.1_3.0_1737746960255.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_4_lr_1e_05_wd_0_001_dp_0_1_swati_0_en_5.5.1_3.0_1737746960255.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_4_lr_1e_05_wd_0_001_dp_0_1_swati_0","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_4_lr_1e_05_wd_0_001_dp_0_1_swati_0", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_4_lr_1e_05_wd_0_001_dp_0_1_swati_0|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.4-lr-1e-05-wd-0.001-dp-0.1-ss-0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_4_lr_1e_05_wd_0_001_dp_0_1_swati_0_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_4_lr_1e_05_wd_0_001_dp_0_1_swati_0_pipeline_en.md
new file mode 100644
index 00000000000000..8a5fd41f0aae02
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_4_lr_1e_05_wd_0_001_dp_0_1_swati_0_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_4_lr_1e_05_wd_0_001_dp_0_1_swati_0_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_4_lr_1e_05_wd_0_001_dp_0_1_swati_0_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_4_lr_1e_05_wd_0_001_dp_0_1_swati_0_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_4_lr_1e_05_wd_0_001_dp_0_1_swati_0_pipeline_en_5.5.1_3.0_1737747004126.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_4_lr_1e_05_wd_0_001_dp_0_1_swati_0_pipeline_en_5.5.1_3.0_1737747004126.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_4_lr_1e_05_wd_0_001_dp_0_1_swati_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_4_lr_1e_05_wd_0_001_dp_0_1_swati_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_4_lr_1e_05_wd_0_001_dp_0_1_swati_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.4-lr-1e-05-wd-0.001-dp-0.1-ss-0
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_56_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_400_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_56_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_400_en.md
new file mode 100644
index 00000000000000..b1749918f3b076
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_56_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_400_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_56_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_400 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_56_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_400
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_56_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_400` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_56_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_400_en_5.5.1_3.0_1737747755156.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_56_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_400_en_5.5.1_3.0_1737747755156.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_56_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_400","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_56_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_400", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_56_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_400|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.56-lr-4e-07-wd-1e-05-dp-0.3-ss-0-st-False-fh-False-hs-400
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_56_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_400_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_56_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_400_pipeline_en.md
new file mode 100644
index 00000000000000..ac154866041498
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_56_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_400_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_56_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_400_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_56_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_400_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_56_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_400_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_56_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_400_pipeline_en_5.5.1_3.0_1737747777585.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_56_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_400_pipeline_en_5.5.1_3.0_1737747777585.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_56_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_400_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_56_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_400_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_56_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_400_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.56-lr-4e-07-wd-1e-05-dp-0.3-ss-0-st-False-fh-False-hs-400
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_6_lr_1e_05_wd_0_001_dp_0_2_swati_0_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_6_lr_1e_05_wd_0_001_dp_0_2_swati_0_en.md
new file mode 100644
index 00000000000000..7c4472790891e9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_6_lr_1e_05_wd_0_001_dp_0_2_swati_0_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_6_lr_1e_05_wd_0_001_dp_0_2_swati_0 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_6_lr_1e_05_wd_0_001_dp_0_2_swati_0
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_6_lr_1e_05_wd_0_001_dp_0_2_swati_0` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_6_lr_1e_05_wd_0_001_dp_0_2_swati_0_en_5.5.1_3.0_1737746769589.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_6_lr_1e_05_wd_0_001_dp_0_2_swati_0_en_5.5.1_3.0_1737746769589.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_6_lr_1e_05_wd_0_001_dp_0_2_swati_0","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_6_lr_1e_05_wd_0_001_dp_0_2_swati_0", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_6_lr_1e_05_wd_0_001_dp_0_2_swati_0|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.6-lr-1e-05-wd-0.001-dp-0.2-ss-0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_6_lr_1e_05_wd_0_001_dp_0_2_swati_0_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_6_lr_1e_05_wd_0_001_dp_0_2_swati_0_pipeline_en.md
new file mode 100644
index 00000000000000..b9d11a30c98644
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_1_6_lr_1e_05_wd_0_001_dp_0_2_swati_0_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_6_lr_1e_05_wd_0_001_dp_0_2_swati_0_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_6_lr_1e_05_wd_0_001_dp_0_2_swati_0_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_6_lr_1e_05_wd_0_001_dp_0_2_swati_0_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_6_lr_1e_05_wd_0_001_dp_0_2_swati_0_pipeline_en_5.5.1_3.0_1737746799378.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_6_lr_1e_05_wd_0_001_dp_0_2_swati_0_pipeline_en_5.5.1_3.0_1737746799378.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_6_lr_1e_05_wd_0_001_dp_0_2_swati_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_6_lr_1e_05_wd_0_001_dp_0_2_swati_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_6_lr_1e_05_wd_0_001_dp_0_2_swati_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.6-lr-1e-05-wd-0.001-dp-0.2-ss-0
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_0_0001_wd_0_001_dp_0_5_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_0_0001_wd_0_001_dp_0_5_en.md
new file mode 100644
index 00000000000000..deebcac11240cd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_0_0001_wd_0_001_dp_0_5_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_2_0_lr_0_0001_wd_0_001_dp_0_5 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_2_0_lr_0_0001_wd_0_001_dp_0_5
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_2_0_lr_0_0001_wd_0_001_dp_0_5` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_0_0001_wd_0_001_dp_0_5_en_5.5.1_3.0_1737739018556.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_0_0001_wd_0_001_dp_0_5_en_5.5.1_3.0_1737739018556.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_2_0_lr_0_0001_wd_0_001_dp_0_5","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_2_0_lr_0_0001_wd_0_001_dp_0_5", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_2_0_lr_0_0001_wd_0_001_dp_0_5|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-2.0-lr-0.0001-wd-0.001-dp-0.5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_0_0001_wd_0_001_dp_0_5_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_0_0001_wd_0_001_dp_0_5_pipeline_en.md
new file mode 100644
index 00000000000000..422a0291c41778
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_0_0001_wd_0_001_dp_0_5_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_2_0_lr_0_0001_wd_0_001_dp_0_5_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_2_0_lr_0_0001_wd_0_001_dp_0_5_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_2_0_lr_0_0001_wd_0_001_dp_0_5_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_0_0001_wd_0_001_dp_0_5_pipeline_en_5.5.1_3.0_1737739039977.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_0_0001_wd_0_001_dp_0_5_pipeline_en_5.5.1_3.0_1737739039977.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_2_0_lr_0_0001_wd_0_001_dp_0_5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_2_0_lr_0_0001_wd_0_001_dp_0_5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_2_0_lr_0_0001_wd_0_001_dp_0_5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-2.0-lr-0.0001-wd-0.001-dp-0.5
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_002_swati_0_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_002_swati_0_en.md
new file mode 100644
index 00000000000000..85b21e09d032a7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_002_swati_0_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_002_swati_0 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_002_swati_0
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_002_swati_0` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_002_swati_0_en_5.5.1_3.0_1737691372073.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_002_swati_0_en_5.5.1_3.0_1737691372073.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_002_swati_0","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_002_swati_0", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_002_swati_0|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-2.0-lr-1e-05-wd-0.001-dp-0.002-ss-0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_002_swati_0_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_002_swati_0_pipeline_en.md
new file mode 100644
index 00000000000000..f013bd2a017f6f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_002_swati_0_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_002_swati_0_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_002_swati_0_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_002_swati_0_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_002_swati_0_pipeline_en_5.5.1_3.0_1737691393569.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_002_swati_0_pipeline_en_5.5.1_3.0_1737691393569.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_002_swati_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_002_swati_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_002_swati_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-2.0-lr-1e-05-wd-0.001-dp-0.002-ss-0
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_008_swati_0_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_008_swati_0_en.md
new file mode 100644
index 00000000000000..99bc03a0e93317
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_008_swati_0_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_008_swati_0 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_008_swati_0
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_008_swati_0` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_008_swati_0_en_5.5.1_3.0_1737747796515.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_008_swati_0_en_5.5.1_3.0_1737747796515.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_008_swati_0","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_008_swati_0", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_008_swati_0|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-2.0-lr-1e-05-wd-0.001-dp-0.008-ss-0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_008_swati_0_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_008_swati_0_pipeline_en.md
new file mode 100644
index 00000000000000..d3b950ca4ed671
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_008_swati_0_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_008_swati_0_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_008_swati_0_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_008_swati_0_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_008_swati_0_pipeline_en_5.5.1_3.0_1737747818371.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_008_swati_0_pipeline_en_5.5.1_3.0_1737747818371.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_008_swati_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_008_swati_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_008_swati_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-2.0-lr-1e-05-wd-0.001-dp-0.008-ss-0
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_08_swati_0_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_08_swati_0_en.md
new file mode 100644
index 00000000000000..0b3222a87f7c50
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_08_swati_0_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_08_swati_0 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_08_swati_0
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_08_swati_0` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_08_swati_0_en_5.5.1_3.0_1737747081748.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_08_swati_0_en_5.5.1_3.0_1737747081748.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_08_swati_0","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_08_swati_0", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_08_swati_0|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-2.0-lr-1e-05-wd-0.001-dp-0.08-ss-0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_08_swati_0_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_08_swati_0_pipeline_en.md
new file mode 100644
index 00000000000000..109185ce1284e8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_08_swati_0_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_08_swati_0_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_08_swati_0_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_08_swati_0_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_08_swati_0_pipeline_en_5.5.1_3.0_1737747106648.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_08_swati_0_pipeline_en_5.5.1_3.0_1737747106648.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_08_swati_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_08_swati_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_08_swati_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-2.0-lr-1e-05-wd-0.001-dp-0.08-ss-0
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500_en.md
new file mode 100644
index 00000000000000..4255ebdb8c4092
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500_en_5.5.1_3.0_1737691010354.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500_en_5.5.1_3.0_1737691010354.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-2.0-lr-1e-05-wd-0.001-dp-0.2-ss-0-st-False-fh-False-hs-500
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500_pipeline_en.md
new file mode 100644
index 00000000000000..e888e6666640c9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500_pipeline_en_5.5.1_3.0_1737691033102.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500_pipeline_en_5.5.1_3.0_1737691033102.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-2.0-lr-1e-05-wd-0.001-dp-0.2-ss-0-st-False-fh-False-hs-500
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_400_southern_sotho_false_fh_true_hs_666_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_400_southern_sotho_false_fh_true_hs_666_en.md
new file mode 100644
index 00000000000000..bdf3e4f6c6c950
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_400_southern_sotho_false_fh_true_hs_666_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_400_southern_sotho_false_fh_true_hs_666 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_400_southern_sotho_false_fh_true_hs_666
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_400_southern_sotho_false_fh_true_hs_666` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_400_southern_sotho_false_fh_true_hs_666_en_5.5.1_3.0_1737746935194.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_400_southern_sotho_false_fh_true_hs_666_en_5.5.1_3.0_1737746935194.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_400_southern_sotho_false_fh_true_hs_666","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_400_southern_sotho_false_fh_true_hs_666", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_400_southern_sotho_false_fh_true_hs_666|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-2.0-lr-1e-05-wd-0.001-dp-0.2-ss-400-st-False-fh-True-hs-666
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_400_southern_sotho_false_fh_true_hs_666_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_400_southern_sotho_false_fh_true_hs_666_pipeline_en.md
new file mode 100644
index 00000000000000..a6960a1f88b5b7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_400_southern_sotho_false_fh_true_hs_666_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_400_southern_sotho_false_fh_true_hs_666_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_400_southern_sotho_false_fh_true_hs_666_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_400_southern_sotho_false_fh_true_hs_666_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_400_southern_sotho_false_fh_true_hs_666_pipeline_en_5.5.1_3.0_1737746966528.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_400_southern_sotho_false_fh_true_hs_666_pipeline_en_5.5.1_3.0_1737746966528.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_400_southern_sotho_false_fh_true_hs_666_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_400_southern_sotho_false_fh_true_hs_666_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_400_southern_sotho_false_fh_true_hs_666_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-2.0-lr-1e-05-wd-0.001-dp-0.2-ss-400-st-False-fh-True-hs-666
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_600_southern_sotho_false_fh_true_hs_666_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_600_southern_sotho_false_fh_true_hs_666_en.md
new file mode 100644
index 00000000000000..81699d905e3b7b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_600_southern_sotho_false_fh_true_hs_666_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_600_southern_sotho_false_fh_true_hs_666 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_600_southern_sotho_false_fh_true_hs_666
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_600_southern_sotho_false_fh_true_hs_666` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_600_southern_sotho_false_fh_true_hs_666_en_5.5.1_3.0_1737747074711.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_600_southern_sotho_false_fh_true_hs_666_en_5.5.1_3.0_1737747074711.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_600_southern_sotho_false_fh_true_hs_666","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_600_southern_sotho_false_fh_true_hs_666", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_600_southern_sotho_false_fh_true_hs_666|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-2.0-lr-1e-05-wd-0.001-dp-0.2-ss-600-st-False-fh-True-hs-666
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_600_southern_sotho_false_fh_true_hs_666_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_600_southern_sotho_false_fh_true_hs_666_pipeline_en.md
new file mode 100644
index 00000000000000..3bf9bca07e974c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_600_southern_sotho_false_fh_true_hs_666_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_600_southern_sotho_false_fh_true_hs_666_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_600_southern_sotho_false_fh_true_hs_666_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_600_southern_sotho_false_fh_true_hs_666_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_600_southern_sotho_false_fh_true_hs_666_pipeline_en_5.5.1_3.0_1737747096500.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_600_southern_sotho_false_fh_true_hs_666_pipeline_en_5.5.1_3.0_1737747096500.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_600_southern_sotho_false_fh_true_hs_666_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_600_southern_sotho_false_fh_true_hs_666_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_600_southern_sotho_false_fh_true_hs_666_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-2.0-lr-1e-05-wd-0.001-dp-0.2-ss-600-st-False-fh-True-hs-666
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_8228_southern_sotho_false_fh_true_hs_666_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_8228_southern_sotho_false_fh_true_hs_666_en.md
new file mode 100644
index 00000000000000..d0c673653e73d5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_8228_southern_sotho_false_fh_true_hs_666_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_8228_southern_sotho_false_fh_true_hs_666 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_8228_southern_sotho_false_fh_true_hs_666
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_8228_southern_sotho_false_fh_true_hs_666` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_8228_southern_sotho_false_fh_true_hs_666_en_5.5.1_3.0_1737747688527.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_8228_southern_sotho_false_fh_true_hs_666_en_5.5.1_3.0_1737747688527.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_8228_southern_sotho_false_fh_true_hs_666","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_8228_southern_sotho_false_fh_true_hs_666", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_8228_southern_sotho_false_fh_true_hs_666|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-2.0-lr-1e-05-wd-0.001-dp-0.2-ss-8228-st-False-fh-True-hs-666
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_8228_southern_sotho_false_fh_true_hs_666_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_8228_southern_sotho_false_fh_true_hs_666_pipeline_en.md
new file mode 100644
index 00000000000000..42c8eae2cad897
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_8228_southern_sotho_false_fh_true_hs_666_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_8228_southern_sotho_false_fh_true_hs_666_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_8228_southern_sotho_false_fh_true_hs_666_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_8228_southern_sotho_false_fh_true_hs_666_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_8228_southern_sotho_false_fh_true_hs_666_pipeline_en_5.5.1_3.0_1737747710341.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_8228_southern_sotho_false_fh_true_hs_666_pipeline_en_5.5.1_3.0_1737747710341.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_8228_southern_sotho_false_fh_true_hs_666_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_8228_southern_sotho_false_fh_true_hs_666_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_8228_southern_sotho_false_fh_true_hs_666_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-2.0-lr-1e-05-wd-0.001-dp-0.2-ss-8228-st-False-fh-True-hs-666
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_6_swati_0_southern_sotho_true_fh_true_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_6_swati_0_southern_sotho_true_fh_true_en.md
new file mode 100644
index 00000000000000..66337c3d85f41d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_6_swati_0_southern_sotho_true_fh_true_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_6_swati_0_southern_sotho_true_fh_true BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_6_swati_0_southern_sotho_true_fh_true
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_6_swati_0_southern_sotho_true_fh_true` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_6_swati_0_southern_sotho_true_fh_true_en_5.5.1_3.0_1737746913448.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_6_swati_0_southern_sotho_true_fh_true_en_5.5.1_3.0_1737746913448.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_6_swati_0_southern_sotho_true_fh_true","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_6_swati_0_southern_sotho_true_fh_true", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_6_swati_0_southern_sotho_true_fh_true|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-2.0-lr-1e-06-wd-0.001-dp-0.6-ss-0-st-True-fh-True
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_6_swati_0_southern_sotho_true_fh_true_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_6_swati_0_southern_sotho_true_fh_true_pipeline_en.md
new file mode 100644
index 00000000000000..16e304fbafc2ac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_6_swati_0_southern_sotho_true_fh_true_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_6_swati_0_southern_sotho_true_fh_true_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_6_swati_0_southern_sotho_true_fh_true_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_6_swati_0_southern_sotho_true_fh_true_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_6_swati_0_southern_sotho_true_fh_true_pipeline_en_5.5.1_3.0_1737746935500.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_6_swati_0_southern_sotho_true_fh_true_pipeline_en_5.5.1_3.0_1737746935500.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_6_swati_0_southern_sotho_true_fh_true_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_6_swati_0_southern_sotho_true_fh_true_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_6_swati_0_southern_sotho_true_fh_true_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-2.0-lr-1e-06-wd-0.001-dp-0.6-ss-0-st-True-fh-True
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_2e_05_wd_0_01_dp_0_2_swati_0_southern_sotho_true_fh_true_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_2e_05_wd_0_01_dp_0_2_swati_0_southern_sotho_true_fh_true_en.md
new file mode 100644
index 00000000000000..7c4fe1235def94
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_2e_05_wd_0_01_dp_0_2_swati_0_southern_sotho_true_fh_true_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_2_0_lr_2e_05_wd_0_01_dp_0_2_swati_0_southern_sotho_true_fh_true BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_2_0_lr_2e_05_wd_0_01_dp_0_2_swati_0_southern_sotho_true_fh_true
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_2_0_lr_2e_05_wd_0_01_dp_0_2_swati_0_southern_sotho_true_fh_true` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_2e_05_wd_0_01_dp_0_2_swati_0_southern_sotho_true_fh_true_en_5.5.1_3.0_1737747461063.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_2e_05_wd_0_01_dp_0_2_swati_0_southern_sotho_true_fh_true_en_5.5.1_3.0_1737747461063.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_2_0_lr_2e_05_wd_0_01_dp_0_2_swati_0_southern_sotho_true_fh_true","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_2_0_lr_2e_05_wd_0_01_dp_0_2_swati_0_southern_sotho_true_fh_true", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_2_0_lr_2e_05_wd_0_01_dp_0_2_swati_0_southern_sotho_true_fh_true|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-2.0-lr-2e-05-wd-0.01-dp-0.2-ss-0-st-True-fh-True
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_2e_05_wd_0_01_dp_0_2_swati_0_southern_sotho_true_fh_true_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_2e_05_wd_0_01_dp_0_2_swati_0_southern_sotho_true_fh_true_pipeline_en.md
new file mode 100644
index 00000000000000..7ceca4dbe18b37
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_2e_05_wd_0_01_dp_0_2_swati_0_southern_sotho_true_fh_true_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_2_0_lr_2e_05_wd_0_01_dp_0_2_swati_0_southern_sotho_true_fh_true_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_2_0_lr_2e_05_wd_0_01_dp_0_2_swati_0_southern_sotho_true_fh_true_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_2_0_lr_2e_05_wd_0_01_dp_0_2_swati_0_southern_sotho_true_fh_true_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_2e_05_wd_0_01_dp_0_2_swati_0_southern_sotho_true_fh_true_pipeline_en_5.5.1_3.0_1737747487359.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_2e_05_wd_0_01_dp_0_2_swati_0_southern_sotho_true_fh_true_pipeline_en_5.5.1_3.0_1737747487359.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_2_0_lr_2e_05_wd_0_01_dp_0_2_swati_0_southern_sotho_true_fh_true_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_2_0_lr_2e_05_wd_0_01_dp_0_2_swati_0_southern_sotho_true_fh_true_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_2_0_lr_2e_05_wd_0_01_dp_0_2_swati_0_southern_sotho_true_fh_true_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-2.0-lr-2e-05-wd-0.01-dp-0.2-ss-0-st-True-fh-True
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_5_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_5_en.md
new file mode 100644
index 00000000000000..e1fae1990d56c1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_5_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_5 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_5
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_5` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_5_en_5.5.1_3.0_1737691254668.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_5_en_5.5.1_3.0_1737691254668.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_5","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_5", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_5|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-2.0-lr-5e-05-wd-0.001-dp-0.5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_5_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_5_pipeline_en.md
new file mode 100644
index 00000000000000..7ddcb867788378
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_5_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_5_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_5_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_5_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_5_pipeline_en_5.5.1_3.0_1737691276169.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_5_pipeline_en_5.5.1_3.0_1737691276169.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-2.0-lr-5e-05-wd-0.001-dp-0.5
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_1000_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_1000_en.md
new file mode 100644
index 00000000000000..a6afb3e7409d0f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_1000_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_2_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_1000 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_2_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_1000
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_2_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_1000` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_1000_en_5.5.1_3.0_1737751446439.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_1000_en_5.5.1_3.0_1737751446439.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_2_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_1000","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_2_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_1000", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_2_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_1000|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-2.0-lr-5e-06-wd-0.001-dp-0.2-ss-0-st-False-fh-False-hs-1000
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_1000_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_1000_pipeline_en.md
new file mode 100644
index 00000000000000..f2ac50e6a6caef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_1000_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_2_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_1000_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_2_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_1000_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_2_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_1000_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_1000_pipeline_en_5.5.1_3.0_1737751471150.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_1000_pipeline_en_5.5.1_3.0_1737751471150.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_2_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_1000_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_2_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_1000_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_2_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_1000_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-2.0-lr-5e-06-wd-0.001-dp-0.2-ss-0-st-False-fh-False-hs-1000
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_8e_07_wd_0_001_dp_0_999_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_8e_07_wd_0_001_dp_0_999_en.md
new file mode 100644
index 00000000000000..d582d3fbffd1f6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_8e_07_wd_0_001_dp_0_999_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_2_0_lr_8e_07_wd_0_001_dp_0_999 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_2_0_lr_8e_07_wd_0_001_dp_0_999
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_2_0_lr_8e_07_wd_0_001_dp_0_999` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_8e_07_wd_0_001_dp_0_999_en_5.5.1_3.0_1737690314362.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_8e_07_wd_0_001_dp_0_999_en_5.5.1_3.0_1737690314362.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_2_0_lr_8e_07_wd_0_001_dp_0_999","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_2_0_lr_8e_07_wd_0_001_dp_0_999", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_2_0_lr_8e_07_wd_0_001_dp_0_999|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-2.0-lr-8e-07-wd-0.001-dp-0.999
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_8e_07_wd_0_001_dp_0_999_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_8e_07_wd_0_001_dp_0_999_pipeline_en.md
new file mode 100644
index 00000000000000..0c563432fbe5d9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_0_lr_8e_07_wd_0_001_dp_0_999_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_2_0_lr_8e_07_wd_0_001_dp_0_999_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_2_0_lr_8e_07_wd_0_001_dp_0_999_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_2_0_lr_8e_07_wd_0_001_dp_0_999_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_8e_07_wd_0_001_dp_0_999_pipeline_en_5.5.1_3.0_1737690342259.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_8e_07_wd_0_001_dp_0_999_pipeline_en_5.5.1_3.0_1737690342259.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_2_0_lr_8e_07_wd_0_001_dp_0_999_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_2_0_lr_8e_07_wd_0_001_dp_0_999_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_2_0_lr_8e_07_wd_0_001_dp_0_999_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-2.0-lr-8e-07-wd-0.001-dp-0.999
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_69_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_700_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_69_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_700_en.md
new file mode 100644
index 00000000000000..6b0b039fff7150
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_69_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_700_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_2_69_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_700 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_2_69_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_700
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_2_69_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_700` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_69_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_700_en_5.5.1_3.0_1737690452223.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_69_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_700_en_5.5.1_3.0_1737690452223.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_2_69_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_700","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_2_69_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_700", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_2_69_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_700|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-2.69-lr-4e-07-wd-1e-05-dp-0.3-ss-0-st-False-fh-False-hs-700
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_69_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_700_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_69_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_700_pipeline_en.md
new file mode 100644
index 00000000000000..a12a7833e1e7d7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_69_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_700_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_2_69_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_700_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_2_69_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_700_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_2_69_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_700_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_69_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_700_pipeline_en_5.5.1_3.0_1737690474358.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_69_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_700_pipeline_en_5.5.1_3.0_1737690474358.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_2_69_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_700_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_2_69_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_700_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_2_69_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_700_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-2.69-lr-4e-07-wd-1e-05-dp-0.3-ss-0-st-False-fh-False-hs-700
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_69_lr_4e_07_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_700_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_69_lr_4e_07_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_700_en.md
new file mode 100644
index 00000000000000..49d7ba7d8f3a1a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_69_lr_4e_07_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_700_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_2_69_lr_4e_07_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_700 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_2_69_lr_4e_07_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_700
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_2_69_lr_4e_07_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_700` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_69_lr_4e_07_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_700_en_5.5.1_3.0_1737738492105.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_69_lr_4e_07_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_700_en_5.5.1_3.0_1737738492105.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_2_69_lr_4e_07_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_700","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_2_69_lr_4e_07_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_700", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_2_69_lr_4e_07_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_700|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-2.69-lr-4e-07-wd-1e-05-dp-1.0-ss-0-st-False-fh-False-hs-700
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_69_lr_4e_07_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_700_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_69_lr_4e_07_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_700_pipeline_en.md
new file mode 100644
index 00000000000000..74f720053f96d9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_2_69_lr_4e_07_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_700_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_2_69_lr_4e_07_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_700_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_2_69_lr_4e_07_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_700_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_2_69_lr_4e_07_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_700_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_69_lr_4e_07_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_700_pipeline_en_5.5.1_3.0_1737738515399.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_69_lr_4e_07_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_700_pipeline_en_5.5.1_3.0_1737738515399.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_2_69_lr_4e_07_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_700_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_2_69_lr_4e_07_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_700_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_2_69_lr_4e_07_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_700_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-2.69-lr-4e-07-wd-1e-05-dp-1.0-ss-0-st-False-fh-False-hs-700
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_900_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_900_en.md
new file mode 100644
index 00000000000000..b025c11981496d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_900_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_900 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_900
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_900` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_900_en_5.5.1_3.0_1737738142070.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_900_en_5.5.1_3.0_1737738142070.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_900","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_900", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_900|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-3.0-lr-1e-05-wd-0.001-dp-0.2-ss-0-st-False-fh-False-hs-900
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_900_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_900_pipeline_en.md
new file mode 100644
index 00000000000000..877d7076722f23
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_900_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_900_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_900_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_900_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_900_pipeline_en_5.5.1_3.0_1737738167552.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_900_pipeline_en_5.5.1_3.0_1737738167552.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_900_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_900_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_900_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-3.0-lr-1e-05-wd-0.001-dp-0.2-ss-0-st-False-fh-False-hs-900
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_200_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_200_en.md
new file mode 100644
index 00000000000000..fa4e2fefae4dfd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_200_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_200 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_200
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_200` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_200_en_5.5.1_3.0_1737691172037.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_200_en_5.5.1_3.0_1737691172037.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_200","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_200", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_200|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-3.0-lr-1e-06-wd-0.001-dp-0.2-ss-0-st-False-fh-False-hs-200
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_200_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_200_pipeline_en.md
new file mode 100644
index 00000000000000..42a46badb9cde5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_200_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_200_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_200_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_200_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_200_pipeline_en_5.5.1_3.0_1737691196984.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_200_pipeline_en_5.5.1_3.0_1737691196984.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_200_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_200_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_200_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-3.0-lr-1e-06-wd-0.001-dp-0.2-ss-0-st-False-fh-False-hs-200
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_3773_southern_sotho_false_fh_true_hs_666_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_3773_southern_sotho_false_fh_true_hs_666_en.md
new file mode 100644
index 00000000000000..0217772583f778
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_3773_southern_sotho_false_fh_true_hs_666_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_3773_southern_sotho_false_fh_true_hs_666 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_3773_southern_sotho_false_fh_true_hs_666
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_3773_southern_sotho_false_fh_true_hs_666` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_3773_southern_sotho_false_fh_true_hs_666_en_5.5.1_3.0_1737691495567.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_3773_southern_sotho_false_fh_true_hs_666_en_5.5.1_3.0_1737691495567.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_3773_southern_sotho_false_fh_true_hs_666","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_3773_southern_sotho_false_fh_true_hs_666", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_3773_southern_sotho_false_fh_true_hs_666|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-3.0-lr-1e-06-wd-0.001-dp-0.2-ss-3773-st-False-fh-True-hs-666
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_3773_southern_sotho_false_fh_true_hs_666_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_3773_southern_sotho_false_fh_true_hs_666_pipeline_en.md
new file mode 100644
index 00000000000000..281661440a7807
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_3773_southern_sotho_false_fh_true_hs_666_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_3773_southern_sotho_false_fh_true_hs_666_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_3773_southern_sotho_false_fh_true_hs_666_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_3773_southern_sotho_false_fh_true_hs_666_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_3773_southern_sotho_false_fh_true_hs_666_pipeline_en_5.5.1_3.0_1737691518696.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_3773_southern_sotho_false_fh_true_hs_666_pipeline_en_5.5.1_3.0_1737691518696.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_3773_southern_sotho_false_fh_true_hs_666_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_3773_southern_sotho_false_fh_true_hs_666_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_3773_southern_sotho_false_fh_true_hs_666_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-3.0-lr-1e-06-wd-0.001-dp-0.2-ss-3773-st-False-fh-True-hs-666
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_02_swati_0_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_02_swati_0_en.md
new file mode 100644
index 00000000000000..976cf10e2fa2df
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_02_swati_0_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_02_swati_0 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_02_swati_0
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_02_swati_0` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_02_swati_0_en_5.5.1_3.0_1737690879476.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_02_swati_0_en_5.5.1_3.0_1737690879476.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_02_swati_0","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_02_swati_0", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_02_swati_0|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-4.0-lr-1e-05-wd-0.001-dp-0.02-ss-0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_02_swati_0_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_02_swati_0_pipeline_en.md
new file mode 100644
index 00000000000000..cc9b0fe164ab50
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_02_swati_0_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_02_swati_0_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_02_swati_0_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_02_swati_0_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_02_swati_0_pipeline_en_5.5.1_3.0_1737690902263.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_02_swati_0_pipeline_en_5.5.1_3.0_1737690902263.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_02_swati_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_02_swati_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_02_swati_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-4.0-lr-1e-05-wd-0.001-dp-0.02-ss-0
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_99999_swati_1000_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_99999_swati_1000_en.md
new file mode 100644
index 00000000000000..e9af766ab0be0f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_99999_swati_1000_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_99999_swati_1000 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_99999_swati_1000
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_99999_swati_1000` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_99999_swati_1000_en_5.5.1_3.0_1737691307553.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_99999_swati_1000_en_5.5.1_3.0_1737691307553.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_99999_swati_1000","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_99999_swati_1000", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_99999_swati_1000|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-4.0-lr-1e-05-wd-0.001-dp-0.99999-ss-1000
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_99999_swati_1000_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_99999_swati_1000_pipeline_en.md
new file mode 100644
index 00000000000000..5b9ad076413f84
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_99999_swati_1000_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_99999_swati_1000_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_99999_swati_1000_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_99999_swati_1000_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_99999_swati_1000_pipeline_en_5.5.1_3.0_1737691334518.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_99999_swati_1000_pipeline_en_5.5.1_3.0_1737691334518.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_99999_swati_1000_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_99999_swati_1000_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_99999_swati_1000_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-4.0-lr-1e-05-wd-0.001-dp-0.99999-ss-1000
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_4_87_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_900_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_4_87_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_900_en.md
new file mode 100644
index 00000000000000..388c0de5911ce3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_4_87_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_900_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_4_87_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_900 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_4_87_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_900
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_4_87_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_900` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_4_87_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_900_en_5.5.1_3.0_1737738295600.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_4_87_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_900_en_5.5.1_3.0_1737738295600.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_4_87_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_900","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_4_87_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_900", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_4_87_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_900|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-4.87-lr-4e-07-wd-1e-05-dp-0.3-ss-0-st-False-fh-False-hs-900
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_4_87_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_900_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_4_87_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_900_pipeline_en.md
new file mode 100644
index 00000000000000..e04da5ea4e5e85
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_4_87_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_900_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_4_87_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_900_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_4_87_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_900_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_4_87_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_900_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_4_87_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_900_pipeline_en_5.5.1_3.0_1737738318154.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_4_87_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_900_pipeline_en_5.5.1_3.0_1737738318154.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_4_87_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_900_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_4_87_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_900_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_4_87_lr_4e_07_wd_1e_05_dp_0_3_swati_0_southern_sotho_false_fh_false_hs_900_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-4.87-lr-4e-07-wd-1e-05-dp-0.3-ss-0-st-False-fh-False-hs-900
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_5_0_lr_1e_05_wd_0_001_dp_0_001_swati_0_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_5_0_lr_1e_05_wd_0_001_dp_0_001_swati_0_en.md
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+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_5_0_lr_1e_05_wd_0_001_dp_0_001_swati_0_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_5_0_lr_1e_05_wd_0_001_dp_0_001_swati_0 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_5_0_lr_1e_05_wd_0_001_dp_0_001_swati_0
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_5_0_lr_1e_05_wd_0_001_dp_0_001_swati_0` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_5_0_lr_1e_05_wd_0_001_dp_0_001_swati_0_en_5.5.1_3.0_1737738412903.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_5_0_lr_1e_05_wd_0_001_dp_0_001_swati_0_en_5.5.1_3.0_1737738412903.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_5_0_lr_1e_05_wd_0_001_dp_0_001_swati_0","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_5_0_lr_1e_05_wd_0_001_dp_0_001_swati_0", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_5_0_lr_1e_05_wd_0_001_dp_0_001_swati_0|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-5.0-lr-1e-05-wd-0.001-dp-0.001-ss-0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_5_0_lr_1e_05_wd_0_001_dp_0_001_swati_0_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_5_0_lr_1e_05_wd_0_001_dp_0_001_swati_0_pipeline_en.md
new file mode 100644
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--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_5_0_lr_1e_05_wd_0_001_dp_0_001_swati_0_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_5_0_lr_1e_05_wd_0_001_dp_0_001_swati_0_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_5_0_lr_1e_05_wd_0_001_dp_0_001_swati_0_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_5_0_lr_1e_05_wd_0_001_dp_0_001_swati_0_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_5_0_lr_1e_05_wd_0_001_dp_0_001_swati_0_pipeline_en_5.5.1_3.0_1737738435707.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_5_0_lr_1e_05_wd_0_001_dp_0_001_swati_0_pipeline_en_5.5.1_3.0_1737738435707.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_5_0_lr_1e_05_wd_0_001_dp_0_001_swati_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_5_0_lr_1e_05_wd_0_001_dp_0_001_swati_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_5_0_lr_1e_05_wd_0_001_dp_0_001_swati_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-5.0-lr-1e-05-wd-0.001-dp-0.001-ss-0
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_5_0_lr_1e_06_wd_0_001_dp_0_2_swati_5555_southern_sotho_false_fh_true_hs_666_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_5_0_lr_1e_06_wd_0_001_dp_0_2_swati_5555_southern_sotho_false_fh_true_hs_666_en.md
new file mode 100644
index 00000000000000..b39989202227d3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_5_0_lr_1e_06_wd_0_001_dp_0_2_swati_5555_southern_sotho_false_fh_true_hs_666_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_5_0_lr_1e_06_wd_0_001_dp_0_2_swati_5555_southern_sotho_false_fh_true_hs_666 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_5_0_lr_1e_06_wd_0_001_dp_0_2_swati_5555_southern_sotho_false_fh_true_hs_666
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_5_0_lr_1e_06_wd_0_001_dp_0_2_swati_5555_southern_sotho_false_fh_true_hs_666` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_5_0_lr_1e_06_wd_0_001_dp_0_2_swati_5555_southern_sotho_false_fh_true_hs_666_en_5.5.1_3.0_1737691309307.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_5_0_lr_1e_06_wd_0_001_dp_0_2_swati_5555_southern_sotho_false_fh_true_hs_666_en_5.5.1_3.0_1737691309307.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_5_0_lr_1e_06_wd_0_001_dp_0_2_swati_5555_southern_sotho_false_fh_true_hs_666","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_5_0_lr_1e_06_wd_0_001_dp_0_2_swati_5555_southern_sotho_false_fh_true_hs_666", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_5_0_lr_1e_06_wd_0_001_dp_0_2_swati_5555_southern_sotho_false_fh_true_hs_666|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-5.0-lr-1e-06-wd-0.001-dp-0.2-ss-5555-st-False-fh-True-hs-666
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_5_0_lr_1e_06_wd_0_001_dp_0_2_swati_5555_southern_sotho_false_fh_true_hs_666_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_5_0_lr_1e_06_wd_0_001_dp_0_2_swati_5555_southern_sotho_false_fh_true_hs_666_pipeline_en.md
new file mode 100644
index 00000000000000..a575fc8f497b5c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_finetune_squad_ep_5_0_lr_1e_06_wd_0_001_dp_0_2_swati_5555_southern_sotho_false_fh_true_hs_666_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_5_0_lr_1e_06_wd_0_001_dp_0_2_swati_5555_southern_sotho_false_fh_true_hs_666_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_5_0_lr_1e_06_wd_0_001_dp_0_2_swati_5555_southern_sotho_false_fh_true_hs_666_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_5_0_lr_1e_06_wd_0_001_dp_0_2_swati_5555_southern_sotho_false_fh_true_hs_666_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_5_0_lr_1e_06_wd_0_001_dp_0_2_swati_5555_southern_sotho_false_fh_true_hs_666_pipeline_en_5.5.1_3.0_1737691334494.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_5_0_lr_1e_06_wd_0_001_dp_0_2_swati_5555_southern_sotho_false_fh_true_hs_666_pipeline_en_5.5.1_3.0_1737691334494.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_5_0_lr_1e_06_wd_0_001_dp_0_2_swati_5555_southern_sotho_false_fh_true_hs_666_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_5_0_lr_1e_06_wd_0_001_dp_0_2_swati_5555_southern_sotho_false_fh_true_hs_666_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_5_0_lr_1e_06_wd_0_001_dp_0_2_swati_5555_southern_sotho_false_fh_true_hs_666_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-5.0-lr-1e-06-wd-0.001-dp-0.2-ss-5555-st-False-fh-True-hs-666
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_product_review_classification_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_product_review_classification_en.md
new file mode 100644
index 00000000000000..ad7bdaa74446a6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_product_review_classification_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_uncased_product_review_classification BertForSequenceClassification from djangodevloper
+author: John Snow Labs
+name: bert_base_uncased_product_review_classification
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_product_review_classification` is a English model originally trained by djangodevloper.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_product_review_classification_en_5.5.1_3.0_1737710575424.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_product_review_classification_en_5.5.1_3.0_1737710575424.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("bert_base_uncased_product_review_classification","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_product_review_classification", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_product_review_classification|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/djangodevloper/bert-base-uncased-product-review-classification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_product_review_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_product_review_classification_pipeline_en.md
new file mode 100644
index 00000000000000..019329497f8d6d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_product_review_classification_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_uncased_product_review_classification_pipeline pipeline BertForSequenceClassification from djangodevloper
+author: John Snow Labs
+name: bert_base_uncased_product_review_classification_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_product_review_classification_pipeline` is a English model originally trained by djangodevloper.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_product_review_classification_pipeline_en_5.5.1_3.0_1737710597037.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_product_review_classification_pipeline_en_5.5.1_3.0_1737710597037.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_product_review_classification_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_product_review_classification_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_product_review_classification_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/djangodevloper/bert-base-uncased-product-review-classification
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_sclarge_squadscqa1_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_sclarge_squadscqa1_en.md
new file mode 100644
index 00000000000000..c3421cfc7eddbc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_sclarge_squadscqa1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_sclarge_squadscqa1 BertForQuestionAnswering from CambridgeMolecularEngineering
+author: John Snow Labs
+name: bert_base_uncased_sclarge_squadscqa1
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_sclarge_squadscqa1` is a English model originally trained by CambridgeMolecularEngineering.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sclarge_squadscqa1_en_5.5.1_3.0_1737752184653.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sclarge_squadscqa1_en_5.5.1_3.0_1737752184653.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_sclarge_squadscqa1","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_sclarge_squadscqa1", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_sclarge_squadscqa1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/CambridgeMolecularEngineering/bert-base-uncased-sclarge-squadscqa1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_sclarge_squadscqa1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_sclarge_squadscqa1_pipeline_en.md
new file mode 100644
index 00000000000000..b0137be27f2e42
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_sclarge_squadscqa1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_sclarge_squadscqa1_pipeline pipeline BertForQuestionAnswering from CambridgeMolecularEngineering
+author: John Snow Labs
+name: bert_base_uncased_sclarge_squadscqa1_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_sclarge_squadscqa1_pipeline` is a English model originally trained by CambridgeMolecularEngineering.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sclarge_squadscqa1_pipeline_en_5.5.1_3.0_1737752218593.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sclarge_squadscqa1_pipeline_en_5.5.1_3.0_1737752218593.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_sclarge_squadscqa1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_sclarge_squadscqa1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_sclarge_squadscqa1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/CambridgeMolecularEngineering/bert-base-uncased-sclarge-squadscqa1
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_scsmall_scqa2_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_scsmall_scqa2_en.md
new file mode 100644
index 00000000000000..4a7256ae423dcc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_scsmall_scqa2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_scsmall_scqa2 BertForQuestionAnswering from CambridgeMolecularEngineering
+author: John Snow Labs
+name: bert_base_uncased_scsmall_scqa2
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_scsmall_scqa2` is a English model originally trained by CambridgeMolecularEngineering.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_scsmall_scqa2_en_5.5.1_3.0_1737747438056.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_scsmall_scqa2_en_5.5.1_3.0_1737747438056.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_scsmall_scqa2","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_scsmall_scqa2", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_scsmall_scqa2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/CambridgeMolecularEngineering/bert-base-uncased-scsmall-scqa2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_scsmall_scqa2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_scsmall_scqa2_pipeline_en.md
new file mode 100644
index 00000000000000..d42c0411a979a4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_base_uncased_scsmall_scqa2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_scsmall_scqa2_pipeline pipeline BertForQuestionAnswering from CambridgeMolecularEngineering
+author: John Snow Labs
+name: bert_base_uncased_scsmall_scqa2_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_scsmall_scqa2_pipeline` is a English model originally trained by CambridgeMolecularEngineering.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_scsmall_scqa2_pipeline_en_5.5.1_3.0_1737747462139.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_scsmall_scqa2_pipeline_en_5.5.1_3.0_1737747462139.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_scsmall_scqa2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_scsmall_scqa2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_scsmall_scqa2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/CambridgeMolecularEngineering/bert-base-uncased-scsmall-scqa2
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_cased_plodcw_sourav_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_cased_plodcw_sourav_en.md
new file mode 100644
index 00000000000000..062d9be0d789f7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_cased_plodcw_sourav_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_cased_plodcw_sourav BertForTokenClassification from LampOfSocrates
+author: John Snow Labs
+name: bert_cased_plodcw_sourav
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_cased_plodcw_sourav` is a English model originally trained by LampOfSocrates.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_cased_plodcw_sourav_en_5.5.1_3.0_1737719997785.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_cased_plodcw_sourav_en_5.5.1_3.0_1737719997785.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_cased_plodcw_sourav","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_cased_plodcw_sourav", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_cased_plodcw_sourav|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/LampOfSocrates/bert-cased-plodcw-sourav
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_cased_plodcw_sourav_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_cased_plodcw_sourav_pipeline_en.md
new file mode 100644
index 00000000000000..d6c3977cf927a0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_cased_plodcw_sourav_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_cased_plodcw_sourav_pipeline pipeline BertForTokenClassification from LampOfSocrates
+author: John Snow Labs
+name: bert_cased_plodcw_sourav_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_cased_plodcw_sourav_pipeline` is a English model originally trained by LampOfSocrates.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_cased_plodcw_sourav_pipeline_en_5.5.1_3.0_1737720023327.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_cased_plodcw_sourav_pipeline_en_5.5.1_3.0_1737720023327.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_cased_plodcw_sourav_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_cased_plodcw_sourav_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_cased_plodcw_sourav_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/LampOfSocrates/bert-cased-plodcw-sourav
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_context_based_qa_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_context_based_qa_en.md
new file mode 100644
index 00000000000000..447b3f1ae168f6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_context_based_qa_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_context_based_qa BertForQuestionAnswering from DracolIA
+author: John Snow Labs
+name: bert_context_based_qa
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_context_based_qa` is a English model originally trained by DracolIA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_context_based_qa_en_5.5.1_3.0_1737738203023.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_context_based_qa_en_5.5.1_3.0_1737738203023.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_context_based_qa","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_context_based_qa", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_context_based_qa|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/DracolIA/BERT-Context-based-QA
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_context_based_qa_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_context_based_qa_pipeline_en.md
new file mode 100644
index 00000000000000..408fd498b59f14
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_context_based_qa_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_context_based_qa_pipeline pipeline BertForQuestionAnswering from DracolIA
+author: John Snow Labs
+name: bert_context_based_qa_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_context_based_qa_pipeline` is a English model originally trained by DracolIA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_context_based_qa_pipeline_en_5.5.1_3.0_1737738226388.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_context_based_qa_pipeline_en_5.5.1_3.0_1737738226388.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_context_based_qa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_context_based_qa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_context_based_qa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/DracolIA/BERT-Context-based-QA
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_en.md
new file mode 100644
index 00000000000000..d198f09bc920c7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_en.md
@@ -0,0 +1,98 @@
+---
+layout: model
+title: English bert RoBertaEmbeddings from ai-ar
+author: John Snow Labs
+name: bert
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert` is a English model originally trained by ai-ar.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_en_5.5.1_3.0_1737757474875.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_en_5.5.1_3.0_1737757474875.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("bert","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("bert","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+References
+
+References
+
+https://huggingface.co/ai-ar/bert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_fine_tune_best_hyberparametes_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_fine_tune_best_hyberparametes_en.md
new file mode 100644
index 00000000000000..acb7534665e204
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_fine_tune_best_hyberparametes_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_fine_tune_best_hyberparametes BertForQuestionAnswering from DataScientist1122
+author: John Snow Labs
+name: bert_fine_tune_best_hyberparametes
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_fine_tune_best_hyberparametes` is a English model originally trained by DataScientist1122.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_fine_tune_best_hyberparametes_en_5.5.1_3.0_1737690349045.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_fine_tune_best_hyberparametes_en_5.5.1_3.0_1737690349045.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_fine_tune_best_hyberparametes","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_fine_tune_best_hyberparametes", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_fine_tune_best_hyberparametes|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/DataScientist1122/BERT_FINE_TUNE_BEST_HYBERPARAMETES
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_fine_tune_best_hyberparametes_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_fine_tune_best_hyberparametes_pipeline_en.md
new file mode 100644
index 00000000000000..7d28c0682f856d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_fine_tune_best_hyberparametes_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_fine_tune_best_hyberparametes_pipeline pipeline BertForQuestionAnswering from DataScientist1122
+author: John Snow Labs
+name: bert_fine_tune_best_hyberparametes_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_fine_tune_best_hyberparametes_pipeline` is a English model originally trained by DataScientist1122.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_fine_tune_best_hyberparametes_pipeline_en_5.5.1_3.0_1737690376629.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_fine_tune_best_hyberparametes_pipeline_en_5.5.1_3.0_1737690376629.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_fine_tune_best_hyberparametes_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_fine_tune_best_hyberparametes_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_fine_tune_best_hyberparametes_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/DataScientist1122/BERT_FINE_TUNE_BEST_HYBERPARAMETES
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_multilingual_xquad2_pipeline_xx.md b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_multilingual_xquad2_pipeline_xx.md
new file mode 100644
index 00000000000000..7b2782a54ec9df
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_multilingual_xquad2_pipeline_xx.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Multilingual bert_finetuned_multilingual_xquad2_pipeline pipeline BertForQuestionAnswering from AnshulRustogi
+author: John Snow Labs
+name: bert_finetuned_multilingual_xquad2_pipeline
+date: 2025-01-24
+tags: [xx, open_source, pipeline, onnx]
+task: Question Answering
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_multilingual_xquad2_pipeline` is a Multilingual model originally trained by AnshulRustogi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_multilingual_xquad2_pipeline_xx_5.5.1_3.0_1737751395261.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_multilingual_xquad2_pipeline_xx_5.5.1_3.0_1737751395261.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_multilingual_xquad2_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_multilingual_xquad2_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_multilingual_xquad2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/AnshulRustogi/bert-finetuned-multilingual-xquad2
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_multilingual_xquad2_xx.md b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_multilingual_xquad2_xx.md
new file mode 100644
index 00000000000000..0c68fb6eb436cc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_multilingual_xquad2_xx.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Multilingual bert_finetuned_multilingual_xquad2 BertForQuestionAnswering from AnshulRustogi
+author: John Snow Labs
+name: bert_finetuned_multilingual_xquad2
+date: 2025-01-24
+tags: [xx, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_multilingual_xquad2` is a Multilingual model originally trained by AnshulRustogi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_multilingual_xquad2_xx_5.5.1_3.0_1737751359567.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_multilingual_xquad2_xx_5.5.1_3.0_1737751359567.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_multilingual_xquad2","xx") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_multilingual_xquad2", "xx")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_multilingual_xquad2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|xx|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/AnshulRustogi/bert-finetuned-multilingual-xquad2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_ner_nickforme_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_ner_nickforme_en.md
new file mode 100644
index 00000000000000..fe2c5ab0883a26
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_ner_nickforme_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_finetuned_ner_nickforme BertForTokenClassification from NickForMe
+author: John Snow Labs
+name: bert_finetuned_ner_nickforme
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_nickforme` is a English model originally trained by NickForMe.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_nickforme_en_5.5.1_3.0_1737719944060.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_nickforme_en_5.5.1_3.0_1737719944060.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_finetuned_ner_nickforme","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner_nickforme", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_nickforme|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.8 MB|
+
+## References
+
+https://huggingface.co/NickForMe/bert-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_ner_nickforme_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_ner_nickforme_pipeline_en.md
new file mode 100644
index 00000000000000..356a1b192a5a4e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_ner_nickforme_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_finetuned_ner_nickforme_pipeline pipeline BertForTokenClassification from NickForMe
+author: John Snow Labs
+name: bert_finetuned_ner_nickforme_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_nickforme_pipeline` is a English model originally trained by NickForMe.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_nickforme_pipeline_en_5.5.1_3.0_1737719965173.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_nickforme_pipeline_en_5.5.1_3.0_1737719965173.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_ner_nickforme_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_ner_nickforme_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_nickforme_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.8 MB|
+
+## References
+
+https://huggingface.co/NickForMe/bert-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_4kew_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_4kew_en.md
new file mode 100644
index 00000000000000..98e3dd3273522f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_4kew_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_finetuned_squad_4kew BertForQuestionAnswering from 4kew
+author: John Snow Labs
+name: bert_finetuned_squad_4kew
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_4kew` is a English model originally trained by 4kew.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_4kew_en_5.5.1_3.0_1737757287759.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_4kew_en_5.5.1_3.0_1737757287759.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_4kew","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_4kew", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_4kew|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/4kew/bert-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_4kew_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_4kew_pipeline_en.md
new file mode 100644
index 00000000000000..211c7846eda0d4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_4kew_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_finetuned_squad_4kew_pipeline pipeline BertForQuestionAnswering from 4kew
+author: John Snow Labs
+name: bert_finetuned_squad_4kew_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_4kew_pipeline` is a English model originally trained by 4kew.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_4kew_pipeline_en_5.5.1_3.0_1737757309524.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_4kew_pipeline_en_5.5.1_3.0_1737757309524.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_squad_4kew_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_squad_4kew_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_4kew_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/4kew/bert-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_accelerate_magnustragardh_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_accelerate_magnustragardh_en.md
new file mode 100644
index 00000000000000..6936c6b9b7e25a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_accelerate_magnustragardh_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_finetuned_squad_accelerate_magnustragardh BertForQuestionAnswering from magnustragardh
+author: John Snow Labs
+name: bert_finetuned_squad_accelerate_magnustragardh
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_accelerate_magnustragardh` is a English model originally trained by magnustragardh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_accelerate_magnustragardh_en_5.5.1_3.0_1737747947337.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_accelerate_magnustragardh_en_5.5.1_3.0_1737747947337.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_accelerate_magnustragardh","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_accelerate_magnustragardh", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_accelerate_magnustragardh|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/magnustragardh/bert-finetuned-squad-accelerate
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_accelerate_magnustragardh_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_accelerate_magnustragardh_pipeline_en.md
new file mode 100644
index 00000000000000..25fe72b01e9146
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_accelerate_magnustragardh_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_finetuned_squad_accelerate_magnustragardh_pipeline pipeline BertForQuestionAnswering from magnustragardh
+author: John Snow Labs
+name: bert_finetuned_squad_accelerate_magnustragardh_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_accelerate_magnustragardh_pipeline` is a English model originally trained by magnustragardh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_accelerate_magnustragardh_pipeline_en_5.5.1_3.0_1737747969596.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_accelerate_magnustragardh_pipeline_en_5.5.1_3.0_1737747969596.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_squad_accelerate_magnustragardh_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_squad_accelerate_magnustragardh_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_accelerate_magnustragardh_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/magnustragardh/bert-finetuned-squad-accelerate
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_accelerate_victor_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_accelerate_victor_en.md
new file mode 100644
index 00000000000000..df804b95373a18
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_accelerate_victor_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_finetuned_squad_accelerate_victor BertForQuestionAnswering from tilnoene
+author: John Snow Labs
+name: bert_finetuned_squad_accelerate_victor
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_accelerate_victor` is a English model originally trained by tilnoene.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_accelerate_victor_en_5.5.1_3.0_1737690346631.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_accelerate_victor_en_5.5.1_3.0_1737690346631.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_accelerate_victor","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_accelerate_victor", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_accelerate_victor|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/tilnoene/bert-finetuned-squad-accelerate-victor
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_accelerate_victor_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_accelerate_victor_pipeline_en.md
new file mode 100644
index 00000000000000..6fd8b88a29ef1b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_accelerate_victor_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_finetuned_squad_accelerate_victor_pipeline pipeline BertForQuestionAnswering from tilnoene
+author: John Snow Labs
+name: bert_finetuned_squad_accelerate_victor_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_accelerate_victor_pipeline` is a English model originally trained by tilnoene.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_accelerate_victor_pipeline_en_5.5.1_3.0_1737690380849.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_accelerate_victor_pipeline_en_5.5.1_3.0_1737690380849.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_squad_accelerate_victor_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_squad_accelerate_victor_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_accelerate_victor_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/tilnoene/bert-finetuned-squad-accelerate-victor
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_ammag_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_ammag_en.md
new file mode 100644
index 00000000000000..79d67c77025a96
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_ammag_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_finetuned_squad_ammag BertForQuestionAnswering from ammag
+author: John Snow Labs
+name: bert_finetuned_squad_ammag
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_ammag` is a English model originally trained by ammag.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_ammag_en_5.5.1_3.0_1737739131080.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_ammag_en_5.5.1_3.0_1737739131080.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_ammag","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_ammag", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_ammag|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/ammag/bert-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_ammag_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_ammag_pipeline_en.md
new file mode 100644
index 00000000000000..b0a2d12fd0a3d9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_ammag_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_finetuned_squad_ammag_pipeline pipeline BertForQuestionAnswering from ammag
+author: John Snow Labs
+name: bert_finetuned_squad_ammag_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_ammag_pipeline` is a English model originally trained by ammag.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_ammag_pipeline_en_5.5.1_3.0_1737739152707.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_ammag_pipeline_en_5.5.1_3.0_1737739152707.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_squad_ammag_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_squad_ammag_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_ammag_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/ammag/bert-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_apps90_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_apps90_en.md
new file mode 100644
index 00000000000000..ca081d35e6b307
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_apps90_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_finetuned_squad_apps90 BertForQuestionAnswering from apps90
+author: John Snow Labs
+name: bert_finetuned_squad_apps90
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_apps90` is a English model originally trained by apps90.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_apps90_en_5.5.1_3.0_1737690347428.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_apps90_en_5.5.1_3.0_1737690347428.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_apps90","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_apps90", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_apps90|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/apps90/bert-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_apps90_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_apps90_pipeline_en.md
new file mode 100644
index 00000000000000..4a7682c78d8bc5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_apps90_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_finetuned_squad_apps90_pipeline pipeline BertForQuestionAnswering from apps90
+author: John Snow Labs
+name: bert_finetuned_squad_apps90_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_apps90_pipeline` is a English model originally trained by apps90.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_apps90_pipeline_en_5.5.1_3.0_1737690381282.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_apps90_pipeline_en_5.5.1_3.0_1737690381282.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_squad_apps90_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_squad_apps90_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_apps90_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/apps90/bert-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_cleandata_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_cleandata_en.md
new file mode 100644
index 00000000000000..4b7bcbeb4451d4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_cleandata_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_finetuned_squad_cleandata BertForQuestionAnswering from cleandata
+author: John Snow Labs
+name: bert_finetuned_squad_cleandata
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_cleandata` is a English model originally trained by cleandata.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_cleandata_en_5.5.1_3.0_1737757341012.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_cleandata_en_5.5.1_3.0_1737757341012.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_cleandata","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_cleandata", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_cleandata|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/cleandata/bert-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_cleandata_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_cleandata_pipeline_en.md
new file mode 100644
index 00000000000000..014d4cb67e55fe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_cleandata_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_finetuned_squad_cleandata_pipeline pipeline BertForQuestionAnswering from cleandata
+author: John Snow Labs
+name: bert_finetuned_squad_cleandata_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_cleandata_pipeline` is a English model originally trained by cleandata.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_cleandata_pipeline_en_5.5.1_3.0_1737757361922.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_cleandata_pipeline_en_5.5.1_3.0_1737757361922.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_squad_cleandata_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_squad_cleandata_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_cleandata_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/cleandata/bert-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_eurosmart_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_eurosmart_en.md
new file mode 100644
index 00000000000000..bc653a8780b73f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_eurosmart_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_finetuned_squad_eurosmart BertForQuestionAnswering from Eurosmart
+author: John Snow Labs
+name: bert_finetuned_squad_eurosmart
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_eurosmart` is a English model originally trained by Eurosmart.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_eurosmart_en_5.5.1_3.0_1737738710161.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_eurosmart_en_5.5.1_3.0_1737738710161.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_eurosmart","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_eurosmart", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_eurosmart|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/Eurosmart/bert-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_eurosmart_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_eurosmart_pipeline_en.md
new file mode 100644
index 00000000000000..5ddb63d2fcb03b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_eurosmart_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_finetuned_squad_eurosmart_pipeline pipeline BertForQuestionAnswering from Eurosmart
+author: John Snow Labs
+name: bert_finetuned_squad_eurosmart_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_eurosmart_pipeline` is a English model originally trained by Eurosmart.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_eurosmart_pipeline_en_5.5.1_3.0_1737738749334.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_eurosmart_pipeline_en_5.5.1_3.0_1737738749334.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_squad_eurosmart_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_squad_eurosmart_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_eurosmart_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/Eurosmart/bert-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_free126_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_free126_en.md
new file mode 100644
index 00000000000000..f81eb38207094b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_free126_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_finetuned_squad_free126 BertForQuestionAnswering from free126
+author: John Snow Labs
+name: bert_finetuned_squad_free126
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_free126` is a English model originally trained by free126.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_free126_en_5.5.1_3.0_1737756728883.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_free126_en_5.5.1_3.0_1737756728883.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_free126","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_free126", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_free126|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/free126/bert-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_free126_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_free126_pipeline_en.md
new file mode 100644
index 00000000000000..06679b8142a774
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_free126_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_finetuned_squad_free126_pipeline pipeline BertForQuestionAnswering from free126
+author: John Snow Labs
+name: bert_finetuned_squad_free126_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_free126_pipeline` is a English model originally trained by free126.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_free126_pipeline_en_5.5.1_3.0_1737756752209.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_free126_pipeline_en_5.5.1_3.0_1737756752209.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_squad_free126_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_squad_free126_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_free126_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/free126/bert-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_hhjingbo_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_hhjingbo_en.md
new file mode 100644
index 00000000000000..e3f0cca3a6f71a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_hhjingbo_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_finetuned_squad_hhjingbo BertForQuestionAnswering from HHJingbo
+author: John Snow Labs
+name: bert_finetuned_squad_hhjingbo
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_hhjingbo` is a English model originally trained by HHJingbo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_hhjingbo_en_5.5.1_3.0_1737757273477.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_hhjingbo_en_5.5.1_3.0_1737757273477.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_hhjingbo","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_hhjingbo", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_hhjingbo|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/HHJingbo/bert-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_hhjingbo_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_hhjingbo_pipeline_en.md
new file mode 100644
index 00000000000000..01466a5ba2af5d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_hhjingbo_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_finetuned_squad_hhjingbo_pipeline pipeline BertForQuestionAnswering from HHJingbo
+author: John Snow Labs
+name: bert_finetuned_squad_hhjingbo_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_hhjingbo_pipeline` is a English model originally trained by HHJingbo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_hhjingbo_pipeline_en_5.5.1_3.0_1737757294945.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_hhjingbo_pipeline_en_5.5.1_3.0_1737757294945.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_squad_hhjingbo_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_squad_hhjingbo_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_hhjingbo_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/HHJingbo/bert-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_jin_cheon_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_jin_cheon_en.md
new file mode 100644
index 00000000000000..e5605723370d18
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_jin_cheon_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_finetuned_squad_jin_cheon BertForQuestionAnswering from jin-cheon
+author: John Snow Labs
+name: bert_finetuned_squad_jin_cheon
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_jin_cheon` is a English model originally trained by jin-cheon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_jin_cheon_en_5.5.1_3.0_1737690542080.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_jin_cheon_en_5.5.1_3.0_1737690542080.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_jin_cheon","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_jin_cheon", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_jin_cheon|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/jin-cheon/bert-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_jin_cheon_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_jin_cheon_pipeline_en.md
new file mode 100644
index 00000000000000..21867a1350540f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_jin_cheon_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_finetuned_squad_jin_cheon_pipeline pipeline BertForQuestionAnswering from jin-cheon
+author: John Snow Labs
+name: bert_finetuned_squad_jin_cheon_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_jin_cheon_pipeline` is a English model originally trained by jin-cheon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_jin_cheon_pipeline_en_5.5.1_3.0_1737690563812.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_jin_cheon_pipeline_en_5.5.1_3.0_1737690563812.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_squad_jin_cheon_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_squad_jin_cheon_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_jin_cheon_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/jin-cheon/bert-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_jtz18_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_jtz18_en.md
new file mode 100644
index 00000000000000..d2ef9a5ba68065
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_jtz18_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_finetuned_squad_jtz18 BertForQuestionAnswering from jtz18
+author: John Snow Labs
+name: bert_finetuned_squad_jtz18
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_jtz18` is a English model originally trained by jtz18.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_jtz18_en_5.5.1_3.0_1737691032379.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_jtz18_en_5.5.1_3.0_1737691032379.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_jtz18","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_jtz18", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_jtz18|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/jtz18/bert-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_jtz18_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_jtz18_pipeline_en.md
new file mode 100644
index 00000000000000..f05b069c64bf0a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_jtz18_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_finetuned_squad_jtz18_pipeline pipeline BertForQuestionAnswering from jtz18
+author: John Snow Labs
+name: bert_finetuned_squad_jtz18_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_jtz18_pipeline` is a English model originally trained by jtz18.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_jtz18_pipeline_en_5.5.1_3.0_1737691056382.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_jtz18_pipeline_en_5.5.1_3.0_1737691056382.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_squad_jtz18_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_squad_jtz18_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_jtz18_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/jtz18/bert-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_magnustragardh_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_magnustragardh_en.md
new file mode 100644
index 00000000000000..4bcd66c8fc2244
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_magnustragardh_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_finetuned_squad_magnustragardh BertForQuestionAnswering from magnustragardh
+author: John Snow Labs
+name: bert_finetuned_squad_magnustragardh
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_magnustragardh` is a English model originally trained by magnustragardh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_magnustragardh_en_5.5.1_3.0_1737751753211.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_magnustragardh_en_5.5.1_3.0_1737751753211.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_magnustragardh","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_magnustragardh", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_magnustragardh|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/magnustragardh/bert-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_magnustragardh_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_magnustragardh_pipeline_en.md
new file mode 100644
index 00000000000000..49ad4f905fb57a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_magnustragardh_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_finetuned_squad_magnustragardh_pipeline pipeline BertForQuestionAnswering from magnustragardh
+author: John Snow Labs
+name: bert_finetuned_squad_magnustragardh_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_magnustragardh_pipeline` is a English model originally trained by magnustragardh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_magnustragardh_pipeline_en_5.5.1_3.0_1737751774719.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_magnustragardh_pipeline_en_5.5.1_3.0_1737751774719.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_squad_magnustragardh_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_squad_magnustragardh_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_magnustragardh_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/magnustragardh/bert-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_marte177_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_marte177_en.md
new file mode 100644
index 00000000000000..0871e612b8aa23
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_marte177_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_finetuned_squad_marte177 BertForQuestionAnswering from marte177
+author: John Snow Labs
+name: bert_finetuned_squad_marte177
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_marte177` is a English model originally trained by marte177.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_marte177_en_5.5.1_3.0_1737747532149.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_marte177_en_5.5.1_3.0_1737747532149.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_marte177","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_marte177", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_marte177|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/marte177/bert-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_marte177_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_marte177_pipeline_en.md
new file mode 100644
index 00000000000000..0c6a0edde3f07a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_marte177_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_finetuned_squad_marte177_pipeline pipeline BertForQuestionAnswering from marte177
+author: John Snow Labs
+name: bert_finetuned_squad_marte177_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_marte177_pipeline` is a English model originally trained by marte177.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_marte177_pipeline_en_5.5.1_3.0_1737747554614.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_marte177_pipeline_en_5.5.1_3.0_1737747554614.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_squad_marte177_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_squad_marte177_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_marte177_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/marte177/bert-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_maxugoodboy_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_maxugoodboy_en.md
new file mode 100644
index 00000000000000..98e7df3ac451ef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_maxugoodboy_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_finetuned_squad_maxugoodboy BertForQuestionAnswering from Maxugoodboy
+author: John Snow Labs
+name: bert_finetuned_squad_maxugoodboy
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_maxugoodboy` is a English model originally trained by Maxugoodboy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_maxugoodboy_en_5.5.1_3.0_1737739262783.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_maxugoodboy_en_5.5.1_3.0_1737739262783.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_maxugoodboy","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_maxugoodboy", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_maxugoodboy|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/Maxugoodboy/bert-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_maxugoodboy_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_maxugoodboy_pipeline_en.md
new file mode 100644
index 00000000000000..1f6c18d314bdc0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_maxugoodboy_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_finetuned_squad_maxugoodboy_pipeline pipeline BertForQuestionAnswering from Maxugoodboy
+author: John Snow Labs
+name: bert_finetuned_squad_maxugoodboy_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_maxugoodboy_pipeline` is a English model originally trained by Maxugoodboy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_maxugoodboy_pipeline_en_5.5.1_3.0_1737739285463.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_maxugoodboy_pipeline_en_5.5.1_3.0_1737739285463.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_squad_maxugoodboy_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_squad_maxugoodboy_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_maxugoodboy_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/Maxugoodboy/bert-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_peteryushunli_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_peteryushunli_en.md
new file mode 100644
index 00000000000000..fc67ced98a7af5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_peteryushunli_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_finetuned_squad_peteryushunli BertForQuestionAnswering from peteryushunli
+author: John Snow Labs
+name: bert_finetuned_squad_peteryushunli
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_peteryushunli` is a English model originally trained by peteryushunli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_peteryushunli_en_5.5.1_3.0_1737690709325.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_peteryushunli_en_5.5.1_3.0_1737690709325.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_peteryushunli","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_peteryushunli", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_peteryushunli|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/peteryushunli/bert-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_peteryushunli_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_peteryushunli_pipeline_en.md
new file mode 100644
index 00000000000000..28e125c5bb6521
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_peteryushunli_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_finetuned_squad_peteryushunli_pipeline pipeline BertForQuestionAnswering from peteryushunli
+author: John Snow Labs
+name: bert_finetuned_squad_peteryushunli_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_peteryushunli_pipeline` is a English model originally trained by peteryushunli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_peteryushunli_pipeline_en_5.5.1_3.0_1737690730626.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_peteryushunli_pipeline_en_5.5.1_3.0_1737690730626.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_squad_peteryushunli_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_squad_peteryushunli_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_peteryushunli_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/peteryushunli/bert-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_physhunter_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_physhunter_en.md
new file mode 100644
index 00000000000000..186485aeffcace
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_physhunter_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_finetuned_squad_physhunter BertForQuestionAnswering from PhysHunter
+author: John Snow Labs
+name: bert_finetuned_squad_physhunter
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_physhunter` is a English model originally trained by PhysHunter.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_physhunter_en_5.5.1_3.0_1737738960337.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_physhunter_en_5.5.1_3.0_1737738960337.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_physhunter","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_physhunter", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_physhunter|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/PhysHunter/bert-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_physhunter_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_physhunter_pipeline_en.md
new file mode 100644
index 00000000000000..f5f55fb1b1e876
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_physhunter_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_finetuned_squad_physhunter_pipeline pipeline BertForQuestionAnswering from PhysHunter
+author: John Snow Labs
+name: bert_finetuned_squad_physhunter_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_physhunter_pipeline` is a English model originally trained by PhysHunter.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_physhunter_pipeline_en_5.5.1_3.0_1737738981689.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_physhunter_pipeline_en_5.5.1_3.0_1737738981689.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_squad_physhunter_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_squad_physhunter_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_physhunter_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/PhysHunter/bert-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_piturrolfio_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_piturrolfio_en.md
new file mode 100644
index 00000000000000..c665c7eba663ef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_piturrolfio_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_finetuned_squad_piturrolfio BertForQuestionAnswering from piturrolfio
+author: John Snow Labs
+name: bert_finetuned_squad_piturrolfio
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_piturrolfio` is a English model originally trained by piturrolfio.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_piturrolfio_en_5.5.1_3.0_1737691490691.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_piturrolfio_en_5.5.1_3.0_1737691490691.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_piturrolfio","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_piturrolfio", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_piturrolfio|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/piturrolfio/bert-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_piturrolfio_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_piturrolfio_pipeline_en.md
new file mode 100644
index 00000000000000..cabc22dc8a4672
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_piturrolfio_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_finetuned_squad_piturrolfio_pipeline pipeline BertForQuestionAnswering from piturrolfio
+author: John Snow Labs
+name: bert_finetuned_squad_piturrolfio_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_piturrolfio_pipeline` is a English model originally trained by piturrolfio.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_piturrolfio_pipeline_en_5.5.1_3.0_1737691512251.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_piturrolfio_pipeline_en_5.5.1_3.0_1737691512251.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_squad_piturrolfio_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_squad_piturrolfio_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_piturrolfio_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/piturrolfio/bert-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_rup_1_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_rup_1_en.md
new file mode 100644
index 00000000000000..35c386b8241b35
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_rup_1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_finetuned_squad_rup_1 BertForQuestionAnswering from abhir00p
+author: John Snow Labs
+name: bert_finetuned_squad_rup_1
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_rup_1` is a English model originally trained by abhir00p.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_rup_1_en_5.5.1_3.0_1737757731749.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_rup_1_en_5.5.1_3.0_1737757731749.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_rup_1","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_rup_1", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_rup_1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/abhir00p/bert-finetuned-squad-rup-1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_rup_1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_rup_1_pipeline_en.md
new file mode 100644
index 00000000000000..aa45544c2f2f64
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_rup_1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_finetuned_squad_rup_1_pipeline pipeline BertForQuestionAnswering from abhir00p
+author: John Snow Labs
+name: bert_finetuned_squad_rup_1_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_rup_1_pipeline` is a English model originally trained by abhir00p.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_rup_1_pipeline_en_5.5.1_3.0_1737757752912.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_rup_1_pipeline_en_5.5.1_3.0_1737757752912.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_squad_rup_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_squad_rup_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_rup_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/abhir00p/bert-finetuned-squad-rup-1
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_seongj_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_seongj_en.md
new file mode 100644
index 00000000000000..7fa9a8c65c6c60
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_seongj_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_finetuned_squad_seongj BertForQuestionAnswering from seongj
+author: John Snow Labs
+name: bert_finetuned_squad_seongj
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_seongj` is a English model originally trained by seongj.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_seongj_en_5.5.1_3.0_1737751873507.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_seongj_en_5.5.1_3.0_1737751873507.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_seongj","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_seongj", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_seongj|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/seongj/bert-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_seongj_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_seongj_pipeline_en.md
new file mode 100644
index 00000000000000..45c38b1c949b30
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_seongj_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_finetuned_squad_seongj_pipeline pipeline BertForQuestionAnswering from seongj
+author: John Snow Labs
+name: bert_finetuned_squad_seongj_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_seongj_pipeline` is a English model originally trained by seongj.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_seongj_pipeline_en_5.5.1_3.0_1737751894735.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_seongj_pipeline_en_5.5.1_3.0_1737751894735.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_squad_seongj_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_squad_seongj_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_seongj_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/seongj/bert-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_sooh098_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_sooh098_en.md
new file mode 100644
index 00000000000000..799fde00b2bccd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_sooh098_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_finetuned_squad_sooh098 BertForQuestionAnswering from sooh098
+author: John Snow Labs
+name: bert_finetuned_squad_sooh098
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_sooh098` is a English model originally trained by sooh098.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_sooh098_en_5.5.1_3.0_1737751807475.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_sooh098_en_5.5.1_3.0_1737751807475.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_sooh098","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_sooh098", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_sooh098|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/sooh098/bert-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_sooh098_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_sooh098_pipeline_en.md
new file mode 100644
index 00000000000000..e5a9009dde4d49
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_sooh098_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_finetuned_squad_sooh098_pipeline pipeline BertForQuestionAnswering from sooh098
+author: John Snow Labs
+name: bert_finetuned_squad_sooh098_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_sooh098_pipeline` is a English model originally trained by sooh098.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_sooh098_pipeline_en_5.5.1_3.0_1737751830223.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_sooh098_pipeline_en_5.5.1_3.0_1737751830223.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_squad_sooh098_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_squad_sooh098_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_sooh098_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/sooh098/bert-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_subhankar98_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_subhankar98_en.md
new file mode 100644
index 00000000000000..3517a6b6a4c631
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_subhankar98_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_finetuned_squad_subhankar98 BertForQuestionAnswering from Subhankar98
+author: John Snow Labs
+name: bert_finetuned_squad_subhankar98
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_subhankar98` is a English model originally trained by Subhankar98.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_subhankar98_en_5.5.1_3.0_1737739097577.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_subhankar98_en_5.5.1_3.0_1737739097577.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_subhankar98","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_subhankar98", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_subhankar98|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/Subhankar98/bert-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_subhankar98_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_subhankar98_pipeline_en.md
new file mode 100644
index 00000000000000..c28d41de8a262b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_finetuned_squad_subhankar98_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_finetuned_squad_subhankar98_pipeline pipeline BertForQuestionAnswering from Subhankar98
+author: John Snow Labs
+name: bert_finetuned_squad_subhankar98_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_subhankar98_pipeline` is a English model originally trained by Subhankar98.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_subhankar98_pipeline_en_5.5.1_3.0_1737739120014.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_subhankar98_pipeline_en_5.5.1_3.0_1737739120014.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_squad_subhankar98_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_squad_subhankar98_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_subhankar98_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/Subhankar98/bert-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_job_german_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_job_german_en.md
new file mode 100644
index 00000000000000..031c3ef46e19c6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_job_german_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_job_german BertEmbeddings from dathi103
+author: John Snow Labs
+name: bert_job_german
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_job_german` is a English model originally trained by dathi103.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_job_german_en_5.5.1_3.0_1737742032416.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_job_german_en_5.5.1_3.0_1737742032416.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_job_german","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_job_german","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_job_german|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/dathi103/bert-job-german
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_job_german_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_job_german_pipeline_en.md
new file mode 100644
index 00000000000000..dcfa27a98131b3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_job_german_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_job_german_pipeline pipeline BertEmbeddings from dathi103
+author: John Snow Labs
+name: bert_job_german_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_job_german_pipeline` is a English model originally trained by dathi103.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_job_german_pipeline_en_5.5.1_3.0_1737742053817.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_job_german_pipeline_en_5.5.1_3.0_1737742053817.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_job_german_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_job_german_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_job_german_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/dathi103/bert-job-german
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_labr_unbalanced_ar.md b/docs/_posts/ahmedlone127/2025-01-24-bert_labr_unbalanced_ar.md
new file mode 100644
index 00000000000000..49cc143df75378
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_labr_unbalanced_ar.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Arabic bert_labr_unbalanced BertForSequenceClassification from mofawzy
+author: John Snow Labs
+name: bert_labr_unbalanced
+date: 2025-01-24
+tags: [ar, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: ar
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_labr_unbalanced` is a Arabic model originally trained by mofawzy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_labr_unbalanced_ar_5.5.1_3.0_1737710883130.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_labr_unbalanced_ar_5.5.1_3.0_1737710883130.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("bert_labr_unbalanced","ar") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("bert_labr_unbalanced", "ar")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_labr_unbalanced|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|ar|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/mofawzy/bert-labr-unbalanced
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_labr_unbalanced_pipeline_ar.md b/docs/_posts/ahmedlone127/2025-01-24-bert_labr_unbalanced_pipeline_ar.md
new file mode 100644
index 00000000000000..004a1fb69093da
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_labr_unbalanced_pipeline_ar.md
@@ -0,0 +1,72 @@
+---
+layout: model
+title: Arabic bert_labr_unbalanced_pipeline pipeline BertForSequenceClassification from mofawzy
+author: John Snow Labs
+name: bert_labr_unbalanced_pipeline
+date: 2025-01-24
+tags: [ar, open_source, pipeline, onnx]
+task: Text Classification
+language: ar
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_labr_unbalanced_pipeline` is a Arabic model originally trained by mofawzy.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_labr_unbalanced_pipeline_ar_5.5.1_3.0_1737710961253.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_labr_unbalanced_pipeline_ar_5.5.1_3.0_1737710961253.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("bert_labr_unbalanced_pipeline", lang = "ar")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("bert_labr_unbalanced_pipeline", lang = "ar")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_labr_unbalanced_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ar|
+|Size:|1.3 GB|
+
+## References
+
+References
+
+https://huggingface.co/mofawzy/bert-labr-unbalanced
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_large_cased_scmedium_squadscqa1_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_large_cased_scmedium_squadscqa1_en.md
new file mode 100644
index 00000000000000..b9104f299a2510
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_large_cased_scmedium_squadscqa1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_large_cased_scmedium_squadscqa1 BertForQuestionAnswering from CambridgeMolecularEngineering
+author: John Snow Labs
+name: bert_large_cased_scmedium_squadscqa1
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_cased_scmedium_squadscqa1` is a English model originally trained by CambridgeMolecularEngineering.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_cased_scmedium_squadscqa1_en_5.5.1_3.0_1737751823494.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_cased_scmedium_squadscqa1_en_5.5.1_3.0_1737751823494.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_large_cased_scmedium_squadscqa1","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_large_cased_scmedium_squadscqa1", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_large_cased_scmedium_squadscqa1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/CambridgeMolecularEngineering/bert-large-cased-scmedium-squadscqa1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_large_cased_scmedium_squadscqa1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_large_cased_scmedium_squadscqa1_pipeline_en.md
new file mode 100644
index 00000000000000..c58142dd6917b5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_large_cased_scmedium_squadscqa1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_large_cased_scmedium_squadscqa1_pipeline pipeline BertForQuestionAnswering from CambridgeMolecularEngineering
+author: John Snow Labs
+name: bert_large_cased_scmedium_squadscqa1_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_cased_scmedium_squadscqa1_pipeline` is a English model originally trained by CambridgeMolecularEngineering.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_cased_scmedium_squadscqa1_pipeline_en_5.5.1_3.0_1737751892208.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_cased_scmedium_squadscqa1_pipeline_en_5.5.1_3.0_1737751892208.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_large_cased_scmedium_squadscqa1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_large_cased_scmedium_squadscqa1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_large_cased_scmedium_squadscqa1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/CambridgeMolecularEngineering/bert-large-cased-scmedium-squadscqa1
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_large_cased_scsmall_squadscqa1_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_large_cased_scsmall_squadscqa1_en.md
new file mode 100644
index 00000000000000..bfe2a1689dc3f0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_large_cased_scsmall_squadscqa1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_large_cased_scsmall_squadscqa1 BertForQuestionAnswering from CambridgeMolecularEngineering
+author: John Snow Labs
+name: bert_large_cased_scsmall_squadscqa1
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_cased_scsmall_squadscqa1` is a English model originally trained by CambridgeMolecularEngineering.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_cased_scsmall_squadscqa1_en_5.5.1_3.0_1737748045793.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_cased_scsmall_squadscqa1_en_5.5.1_3.0_1737748045793.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_large_cased_scsmall_squadscqa1","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_large_cased_scsmall_squadscqa1", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_large_cased_scsmall_squadscqa1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/CambridgeMolecularEngineering/bert-large-cased-scsmall-squadscqa1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_large_cased_scsmall_squadscqa1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_large_cased_scsmall_squadscqa1_pipeline_en.md
new file mode 100644
index 00000000000000..e601cf07a5afdf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_large_cased_scsmall_squadscqa1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_large_cased_scsmall_squadscqa1_pipeline pipeline BertForQuestionAnswering from CambridgeMolecularEngineering
+author: John Snow Labs
+name: bert_large_cased_scsmall_squadscqa1_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_cased_scsmall_squadscqa1_pipeline` is a English model originally trained by CambridgeMolecularEngineering.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_cased_scsmall_squadscqa1_pipeline_en_5.5.1_3.0_1737748111967.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_cased_scsmall_squadscqa1_pipeline_en_5.5.1_3.0_1737748111967.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_large_cased_scsmall_squadscqa1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_large_cased_scsmall_squadscqa1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_large_cased_scsmall_squadscqa1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/CambridgeMolecularEngineering/bert-large-cased-scsmall-squadscqa1
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_large_ner_finetuned_tasteset_spoonacular_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_large_ner_finetuned_tasteset_spoonacular_en.md
new file mode 100644
index 00000000000000..d7654ec9fc65d9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_large_ner_finetuned_tasteset_spoonacular_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_large_ner_finetuned_tasteset_spoonacular BertForTokenClassification from DavidEB2
+author: John Snow Labs
+name: bert_large_ner_finetuned_tasteset_spoonacular
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_ner_finetuned_tasteset_spoonacular` is a English model originally trained by DavidEB2.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_ner_finetuned_tasteset_spoonacular_en_5.5.1_3.0_1737719685434.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_ner_finetuned_tasteset_spoonacular_en_5.5.1_3.0_1737719685434.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_large_ner_finetuned_tasteset_spoonacular","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_large_ner_finetuned_tasteset_spoonacular", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_large_ner_finetuned_tasteset_spoonacular|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/DavidEB2/bert-large-NER-finetuned-Tasteset-spoonacular
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_large_ner_finetuned_tasteset_spoonacular_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_large_ner_finetuned_tasteset_spoonacular_pipeline_en.md
new file mode 100644
index 00000000000000..5b9390fe4a6f22
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_large_ner_finetuned_tasteset_spoonacular_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_large_ner_finetuned_tasteset_spoonacular_pipeline pipeline BertForTokenClassification from DavidEB2
+author: John Snow Labs
+name: bert_large_ner_finetuned_tasteset_spoonacular_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_ner_finetuned_tasteset_spoonacular_pipeline` is a English model originally trained by DavidEB2.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_ner_finetuned_tasteset_spoonacular_pipeline_en_5.5.1_3.0_1737719749860.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_ner_finetuned_tasteset_spoonacular_pipeline_en_5.5.1_3.0_1737719749860.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_large_ner_finetuned_tasteset_spoonacular_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_large_ner_finetuned_tasteset_spoonacular_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_large_ner_finetuned_tasteset_spoonacular_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/DavidEB2/bert-large-NER-finetuned-Tasteset-spoonacular
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_large_uncased_finetuned_squad_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_large_uncased_finetuned_squad_en.md
new file mode 100644
index 00000000000000..031776985112d6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_large_uncased_finetuned_squad_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_large_uncased_finetuned_squad BertForQuestionAnswering from Ghadafares2
+author: John Snow Labs
+name: bert_large_uncased_finetuned_squad
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_finetuned_squad` is a English model originally trained by Ghadafares2.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_finetuned_squad_en_5.5.1_3.0_1737691850853.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_finetuned_squad_en_5.5.1_3.0_1737691850853.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_large_uncased_finetuned_squad","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_large_uncased_finetuned_squad", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_large_uncased_finetuned_squad|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/Ghadafares2/bert-large-uncased-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_large_uncased_finetuned_squad_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_large_uncased_finetuned_squad_pipeline_en.md
new file mode 100644
index 00000000000000..673d692c3c5653
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_large_uncased_finetuned_squad_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_large_uncased_finetuned_squad_pipeline pipeline BertForQuestionAnswering from Ghadafares2
+author: John Snow Labs
+name: bert_large_uncased_finetuned_squad_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_finetuned_squad_pipeline` is a English model originally trained by Ghadafares2.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_finetuned_squad_pipeline_en_5.5.1_3.0_1737691913454.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_finetuned_squad_pipeline_en_5.5.1_3.0_1737691913454.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_large_uncased_finetuned_squad_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_large_uncased_finetuned_squad_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_large_uncased_finetuned_squad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/Ghadafares2/bert-large-uncased-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_large_uncased_qa1_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_large_uncased_qa1_en.md
new file mode 100644
index 00000000000000..3172ba64fede21
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_large_uncased_qa1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_large_uncased_qa1 BertForQuestionAnswering from MattNandavong
+author: John Snow Labs
+name: bert_large_uncased_qa1
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_qa1` is a English model originally trained by MattNandavong.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_qa1_en_5.5.1_3.0_1737690785038.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_qa1_en_5.5.1_3.0_1737690785038.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_large_uncased_qa1","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_large_uncased_qa1", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_large_uncased_qa1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/MattNandavong/bert_large_uncased-QA1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_large_uncased_qa1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_large_uncased_qa1_pipeline_en.md
new file mode 100644
index 00000000000000..570ec58bb49bc3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_large_uncased_qa1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_large_uncased_qa1_pipeline pipeline BertForQuestionAnswering from MattNandavong
+author: John Snow Labs
+name: bert_large_uncased_qa1_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_qa1_pipeline` is a English model originally trained by MattNandavong.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_qa1_pipeline_en_5.5.1_3.0_1737690848748.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_qa1_pipeline_en_5.5.1_3.0_1737690848748.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_large_uncased_qa1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_large_uncased_qa1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_large_uncased_qa1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/MattNandavong/bert_large_uncased-QA1
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_large_uncased_scmedium_scqa1_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_large_uncased_scmedium_scqa1_en.md
new file mode 100644
index 00000000000000..47f04f05796f5f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_large_uncased_scmedium_scqa1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_large_uncased_scmedium_scqa1 BertForQuestionAnswering from CambridgeMolecularEngineering
+author: John Snow Labs
+name: bert_large_uncased_scmedium_scqa1
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_scmedium_scqa1` is a English model originally trained by CambridgeMolecularEngineering.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_scmedium_scqa1_en_5.5.1_3.0_1737751428365.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_scmedium_scqa1_en_5.5.1_3.0_1737751428365.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_large_uncased_scmedium_scqa1","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_large_uncased_scmedium_scqa1", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_large_uncased_scmedium_scqa1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/CambridgeMolecularEngineering/bert-large-uncased-scmedium-scqa1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_large_uncased_scmedium_scqa1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_large_uncased_scmedium_scqa1_pipeline_en.md
new file mode 100644
index 00000000000000..4469bc12768a79
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_large_uncased_scmedium_scqa1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_large_uncased_scmedium_scqa1_pipeline pipeline BertForQuestionAnswering from CambridgeMolecularEngineering
+author: John Snow Labs
+name: bert_large_uncased_scmedium_scqa1_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_scmedium_scqa1_pipeline` is a English model originally trained by CambridgeMolecularEngineering.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_scmedium_scqa1_pipeline_en_5.5.1_3.0_1737751493122.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_scmedium_scqa1_pipeline_en_5.5.1_3.0_1737751493122.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_large_uncased_scmedium_scqa1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_large_uncased_scmedium_scqa1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_large_uncased_scmedium_scqa1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/CambridgeMolecularEngineering/bert-large-uncased-scmedium-scqa1
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_large_uncased_scqa2_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_large_uncased_scqa2_en.md
new file mode 100644
index 00000000000000..e61c76c227b5bc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_large_uncased_scqa2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_large_uncased_scqa2 BertForQuestionAnswering from CambridgeMolecularEngineering
+author: John Snow Labs
+name: bert_large_uncased_scqa2
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_scqa2` is a English model originally trained by CambridgeMolecularEngineering.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_scqa2_en_5.5.1_3.0_1737747215757.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_scqa2_en_5.5.1_3.0_1737747215757.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_large_uncased_scqa2","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_large_uncased_scqa2", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_large_uncased_scqa2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/CambridgeMolecularEngineering/bert-large-uncased-scqa2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_large_uncased_scqa2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_large_uncased_scqa2_pipeline_en.md
new file mode 100644
index 00000000000000..7165014c97b0d1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_large_uncased_scqa2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_large_uncased_scqa2_pipeline pipeline BertForQuestionAnswering from CambridgeMolecularEngineering
+author: John Snow Labs
+name: bert_large_uncased_scqa2_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_scqa2_pipeline` is a English model originally trained by CambridgeMolecularEngineering.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_scqa2_pipeline_en_5.5.1_3.0_1737747284904.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_scqa2_pipeline_en_5.5.1_3.0_1737747284904.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_large_uncased_scqa2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_large_uncased_scqa2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_large_uncased_scqa2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/CambridgeMolecularEngineering/bert-large-uncased-scqa2
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_large_uncased_whole_word_masking_finetuned_squad_finetuned_squad_04satis_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_large_uncased_whole_word_masking_finetuned_squad_finetuned_squad_04satis_en.md
new file mode 100644
index 00000000000000..fc9f471c65c3c1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_large_uncased_whole_word_masking_finetuned_squad_finetuned_squad_04satis_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_large_uncased_whole_word_masking_finetuned_squad_finetuned_squad_04satis BertForQuestionAnswering from 04satis
+author: John Snow Labs
+name: bert_large_uncased_whole_word_masking_finetuned_squad_finetuned_squad_04satis
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_whole_word_masking_finetuned_squad_finetuned_squad_04satis` is a English model originally trained by 04satis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_whole_word_masking_finetuned_squad_finetuned_squad_04satis_en_5.5.1_3.0_1737756808136.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_whole_word_masking_finetuned_squad_finetuned_squad_04satis_en_5.5.1_3.0_1737756808136.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_large_uncased_whole_word_masking_finetuned_squad_finetuned_squad_04satis","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_large_uncased_whole_word_masking_finetuned_squad_finetuned_squad_04satis", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_large_uncased_whole_word_masking_finetuned_squad_finetuned_squad_04satis|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/04satis/bert-large-uncased-whole-word-masking-finetuned-squad-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_large_uncased_whole_word_masking_finetuned_squad_finetuned_squad_04satis_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_large_uncased_whole_word_masking_finetuned_squad_finetuned_squad_04satis_pipeline_en.md
new file mode 100644
index 00000000000000..d7188bea041a24
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_large_uncased_whole_word_masking_finetuned_squad_finetuned_squad_04satis_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_large_uncased_whole_word_masking_finetuned_squad_finetuned_squad_04satis_pipeline pipeline BertForQuestionAnswering from 04satis
+author: John Snow Labs
+name: bert_large_uncased_whole_word_masking_finetuned_squad_finetuned_squad_04satis_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_whole_word_masking_finetuned_squad_finetuned_squad_04satis_pipeline` is a English model originally trained by 04satis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_whole_word_masking_finetuned_squad_finetuned_squad_04satis_pipeline_en_5.5.1_3.0_1737756874414.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_whole_word_masking_finetuned_squad_finetuned_squad_04satis_pipeline_en_5.5.1_3.0_1737756874414.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_large_uncased_whole_word_masking_finetuned_squad_finetuned_squad_04satis_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_large_uncased_whole_word_masking_finetuned_squad_finetuned_squad_04satis_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_large_uncased_whole_word_masking_finetuned_squad_finetuned_squad_04satis_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/04satis/bert-large-uncased-whole-word-masking-finetuned-squad-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_large_uncased_whole_word_masking_finetuned_squad_i_5000_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_large_uncased_whole_word_masking_finetuned_squad_i_5000_en.md
new file mode 100644
index 00000000000000..7a572c0ceabc67
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_large_uncased_whole_word_masking_finetuned_squad_i_5000_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_large_uncased_whole_word_masking_finetuned_squad_i_5000 BertForQuestionAnswering from mdzrg
+author: John Snow Labs
+name: bert_large_uncased_whole_word_masking_finetuned_squad_i_5000
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_whole_word_masking_finetuned_squad_i_5000` is a English model originally trained by mdzrg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_whole_word_masking_finetuned_squad_i_5000_en_5.5.1_3.0_1737757095767.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_whole_word_masking_finetuned_squad_i_5000_en_5.5.1_3.0_1737757095767.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_large_uncased_whole_word_masking_finetuned_squad_i_5000","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_large_uncased_whole_word_masking_finetuned_squad_i_5000", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_large_uncased_whole_word_masking_finetuned_squad_i_5000|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/mdzrg/bert-large-uncased-whole-word-masking-finetuned-squad-I-5000
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_large_uncased_whole_word_masking_finetuned_squad_i_5000_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_large_uncased_whole_word_masking_finetuned_squad_i_5000_pipeline_en.md
new file mode 100644
index 00000000000000..6c205f3c546e39
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_large_uncased_whole_word_masking_finetuned_squad_i_5000_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_large_uncased_whole_word_masking_finetuned_squad_i_5000_pipeline pipeline BertForQuestionAnswering from mdzrg
+author: John Snow Labs
+name: bert_large_uncased_whole_word_masking_finetuned_squad_i_5000_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_whole_word_masking_finetuned_squad_i_5000_pipeline` is a English model originally trained by mdzrg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_whole_word_masking_finetuned_squad_i_5000_pipeline_en_5.5.1_3.0_1737757160724.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_whole_word_masking_finetuned_squad_i_5000_pipeline_en_5.5.1_3.0_1737757160724.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_large_uncased_whole_word_masking_finetuned_squad_i_5000_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_large_uncased_whole_word_masking_finetuned_squad_i_5000_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_large_uncased_whole_word_masking_finetuned_squad_i_5000_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/mdzrg/bert-large-uncased-whole-word-masking-finetuned-squad-I-5000
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_large_uncased_whole_word_masking_squad2_train_one_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_large_uncased_whole_word_masking_squad2_train_one_en.md
new file mode 100644
index 00000000000000..fa02e54b429669
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_large_uncased_whole_word_masking_squad2_train_one_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_large_uncased_whole_word_masking_squad2_train_one BertForQuestionAnswering from mdzrg
+author: John Snow Labs
+name: bert_large_uncased_whole_word_masking_squad2_train_one
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_whole_word_masking_squad2_train_one` is a English model originally trained by mdzrg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_whole_word_masking_squad2_train_one_en_5.5.1_3.0_1737757393307.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_whole_word_masking_squad2_train_one_en_5.5.1_3.0_1737757393307.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_large_uncased_whole_word_masking_squad2_train_one","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_large_uncased_whole_word_masking_squad2_train_one", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_large_uncased_whole_word_masking_squad2_train_one|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/mdzrg/bert-large-uncased-whole-word-masking-squad2-train-one
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_large_uncased_whole_word_masking_squad2_train_one_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_large_uncased_whole_word_masking_squad2_train_one_pipeline_en.md
new file mode 100644
index 00000000000000..a061cf2c21cd36
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_large_uncased_whole_word_masking_squad2_train_one_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_large_uncased_whole_word_masking_squad2_train_one_pipeline pipeline BertForQuestionAnswering from mdzrg
+author: John Snow Labs
+name: bert_large_uncased_whole_word_masking_squad2_train_one_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_whole_word_masking_squad2_train_one_pipeline` is a English model originally trained by mdzrg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_whole_word_masking_squad2_train_one_pipeline_en_5.5.1_3.0_1737757459351.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_whole_word_masking_squad2_train_one_pipeline_en_5.5.1_3.0_1737757459351.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_large_uncased_whole_word_masking_squad2_train_one_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_large_uncased_whole_word_masking_squad2_train_one_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_large_uncased_whole_word_masking_squad2_train_one_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/mdzrg/bert-large-uncased-whole-word-masking-squad2-train-one
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_large_uncased_whole_word_masking_squad_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_large_uncased_whole_word_masking_squad_en.md
new file mode 100644
index 00000000000000..a2c0750e56d1fc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_large_uncased_whole_word_masking_squad_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_large_uncased_whole_word_masking_squad BertForQuestionAnswering from angelogonzales
+author: John Snow Labs
+name: bert_large_uncased_whole_word_masking_squad
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_whole_word_masking_squad` is a English model originally trained by angelogonzales.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_whole_word_masking_squad_en_5.5.1_3.0_1737751166939.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_whole_word_masking_squad_en_5.5.1_3.0_1737751166939.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_large_uncased_whole_word_masking_squad","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_large_uncased_whole_word_masking_squad", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_large_uncased_whole_word_masking_squad|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/angelogonzales/bert-large-uncased-whole-word-masking-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_large_uncased_whole_word_masking_squad_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_large_uncased_whole_word_masking_squad_pipeline_en.md
new file mode 100644
index 00000000000000..557d01bd88a23b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_large_uncased_whole_word_masking_squad_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_large_uncased_whole_word_masking_squad_pipeline pipeline BertForQuestionAnswering from angelogonzales
+author: John Snow Labs
+name: bert_large_uncased_whole_word_masking_squad_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_whole_word_masking_squad_pipeline` is a English model originally trained by angelogonzales.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_whole_word_masking_squad_pipeline_en_5.5.1_3.0_1737751233660.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_whole_word_masking_squad_pipeline_en_5.5.1_3.0_1737751233660.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_large_uncased_whole_word_masking_squad_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_large_uncased_whole_word_masking_squad_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_large_uncased_whole_word_masking_squad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/angelogonzales/bert-large-uncased-whole-word-masking-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_maskedlm_ppt_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_maskedlm_ppt_en.md
new file mode 100644
index 00000000000000..37bada04942846
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_maskedlm_ppt_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_maskedlm_ppt BertEmbeddings from trnthsn
+author: John Snow Labs
+name: bert_maskedlm_ppt
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_maskedlm_ppt` is a English model originally trained by trnthsn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_maskedlm_ppt_en_5.5.1_3.0_1737742680654.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_maskedlm_ppt_en_5.5.1_3.0_1737742680654.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_maskedlm_ppt","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_maskedlm_ppt","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_maskedlm_ppt|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|433.7 MB|
+
+## References
+
+https://huggingface.co/trnthsn/bert-maskedlm-ppt
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_maskedlm_ppt_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_maskedlm_ppt_pipeline_en.md
new file mode 100644
index 00000000000000..5bf06ef8641185
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_maskedlm_ppt_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_maskedlm_ppt_pipeline pipeline BertEmbeddings from trnthsn
+author: John Snow Labs
+name: bert_maskedlm_ppt_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_maskedlm_ppt_pipeline` is a English model originally trained by trnthsn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_maskedlm_ppt_pipeline_en_5.5.1_3.0_1737742704914.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_maskedlm_ppt_pipeline_en_5.5.1_3.0_1737742704914.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_maskedlm_ppt_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_maskedlm_ppt_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_maskedlm_ppt_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|433.8 MB|
+
+## References
+
+https://huggingface.co/trnthsn/bert-maskedlm-ppt
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_medquad_16052024_electra_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_medquad_16052024_electra_en.md
new file mode 100644
index 00000000000000..0720676c1db51e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_medquad_16052024_electra_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_medquad_16052024_electra BertForQuestionAnswering from DataScientist1122
+author: John Snow Labs
+name: bert_medquad_16052024_electra
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_medquad_16052024_electra` is a English model originally trained by DataScientist1122.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_medquad_16052024_electra_en_5.5.1_3.0_1737757905706.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_medquad_16052024_electra_en_5.5.1_3.0_1737757905706.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_medquad_16052024_electra","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_medquad_16052024_electra", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_medquad_16052024_electra|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/DataScientist1122/BERT_MedQuad_16052024_electra
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_medquad_16052024_electra_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_medquad_16052024_electra_pipeline_en.md
new file mode 100644
index 00000000000000..c9181ba92ea7ab
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_medquad_16052024_electra_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_medquad_16052024_electra_pipeline pipeline BertForQuestionAnswering from DataScientist1122
+author: John Snow Labs
+name: bert_medquad_16052024_electra_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_medquad_16052024_electra_pipeline` is a English model originally trained by DataScientist1122.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_medquad_16052024_electra_pipeline_en_5.5.1_3.0_1737757934159.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_medquad_16052024_electra_pipeline_en_5.5.1_3.0_1737757934159.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_medquad_16052024_electra_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_medquad_16052024_electra_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_medquad_16052024_electra_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/DataScientist1122/BERT_MedQuad_16052024_electra
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_multilingual_finetuned_squad_korv1_accelerate_pipeline_xx.md b/docs/_posts/ahmedlone127/2025-01-24-bert_multilingual_finetuned_squad_korv1_accelerate_pipeline_xx.md
new file mode 100644
index 00000000000000..eb980e20609c35
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_multilingual_finetuned_squad_korv1_accelerate_pipeline_xx.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Multilingual bert_multilingual_finetuned_squad_korv1_accelerate_pipeline pipeline BertForQuestionAnswering from sue123456
+author: John Snow Labs
+name: bert_multilingual_finetuned_squad_korv1_accelerate_pipeline
+date: 2025-01-24
+tags: [xx, open_source, pipeline, onnx]
+task: Question Answering
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_multilingual_finetuned_squad_korv1_accelerate_pipeline` is a Multilingual model originally trained by sue123456.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_multilingual_finetuned_squad_korv1_accelerate_pipeline_xx_5.5.1_3.0_1737691603429.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_multilingual_finetuned_squad_korv1_accelerate_pipeline_xx_5.5.1_3.0_1737691603429.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_multilingual_finetuned_squad_korv1_accelerate_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_multilingual_finetuned_squad_korv1_accelerate_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_multilingual_finetuned_squad_korv1_accelerate_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/sue123456/BERT-multilingual-finetuned-squad_korv1-accelerate
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_multilingual_finetuned_squad_korv1_accelerate_xx.md b/docs/_posts/ahmedlone127/2025-01-24-bert_multilingual_finetuned_squad_korv1_accelerate_xx.md
new file mode 100644
index 00000000000000..d30647ade0e0d5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_multilingual_finetuned_squad_korv1_accelerate_xx.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Multilingual bert_multilingual_finetuned_squad_korv1_accelerate BertForQuestionAnswering from sue123456
+author: John Snow Labs
+name: bert_multilingual_finetuned_squad_korv1_accelerate
+date: 2025-01-24
+tags: [xx, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_multilingual_finetuned_squad_korv1_accelerate` is a Multilingual model originally trained by sue123456.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_multilingual_finetuned_squad_korv1_accelerate_xx_5.5.1_3.0_1737691568020.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_multilingual_finetuned_squad_korv1_accelerate_xx_5.5.1_3.0_1737691568020.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_multilingual_finetuned_squad_korv1_accelerate","xx") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_multilingual_finetuned_squad_korv1_accelerate", "xx")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_multilingual_finetuned_squad_korv1_accelerate|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|xx|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/sue123456/BERT-multilingual-finetuned-squad_korv1-accelerate
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_multilingual_nature_limit_preprocessed_1000_rouge_pipeline_xx.md b/docs/_posts/ahmedlone127/2025-01-24-bert_multilingual_nature_limit_preprocessed_1000_rouge_pipeline_xx.md
new file mode 100644
index 00000000000000..38c2aef6b968eb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_multilingual_nature_limit_preprocessed_1000_rouge_pipeline_xx.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Multilingual bert_multilingual_nature_limit_preprocessed_1000_rouge_pipeline pipeline BertForQuestionAnswering from mlnha
+author: John Snow Labs
+name: bert_multilingual_nature_limit_preprocessed_1000_rouge_pipeline
+date: 2025-01-24
+tags: [xx, open_source, pipeline, onnx]
+task: Question Answering
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_multilingual_nature_limit_preprocessed_1000_rouge_pipeline` is a Multilingual model originally trained by mlnha.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_multilingual_nature_limit_preprocessed_1000_rouge_pipeline_xx_5.5.1_3.0_1737691932132.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_multilingual_nature_limit_preprocessed_1000_rouge_pipeline_xx_5.5.1_3.0_1737691932132.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_multilingual_nature_limit_preprocessed_1000_rouge_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_multilingual_nature_limit_preprocessed_1000_rouge_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_multilingual_nature_limit_preprocessed_1000_rouge_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/mlnha/bert-multilingual-nature-limit-preprocessed-1000-rouge
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_multilingual_nature_limit_preprocessed_1000_rouge_xx.md b/docs/_posts/ahmedlone127/2025-01-24-bert_multilingual_nature_limit_preprocessed_1000_rouge_xx.md
new file mode 100644
index 00000000000000..d75551c70f0a84
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_multilingual_nature_limit_preprocessed_1000_rouge_xx.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Multilingual bert_multilingual_nature_limit_preprocessed_1000_rouge BertForQuestionAnswering from mlnha
+author: John Snow Labs
+name: bert_multilingual_nature_limit_preprocessed_1000_rouge
+date: 2025-01-24
+tags: [xx, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_multilingual_nature_limit_preprocessed_1000_rouge` is a Multilingual model originally trained by mlnha.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_multilingual_nature_limit_preprocessed_1000_rouge_xx_5.5.1_3.0_1737691898047.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_multilingual_nature_limit_preprocessed_1000_rouge_xx_5.5.1_3.0_1737691898047.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_multilingual_nature_limit_preprocessed_1000_rouge","xx") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_multilingual_nature_limit_preprocessed_1000_rouge", "xx")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_multilingual_nature_limit_preprocessed_1000_rouge|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|xx|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/mlnha/bert-multilingual-nature-limit-preprocessed-1000-rouge
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_multilingual_nature_limit_preprocessed_3000_test1_pipeline_xx.md b/docs/_posts/ahmedlone127/2025-01-24-bert_multilingual_nature_limit_preprocessed_3000_test1_pipeline_xx.md
new file mode 100644
index 00000000000000..2e7649d3200885
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_multilingual_nature_limit_preprocessed_3000_test1_pipeline_xx.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Multilingual bert_multilingual_nature_limit_preprocessed_3000_test1_pipeline pipeline BertForQuestionAnswering from mlnha
+author: John Snow Labs
+name: bert_multilingual_nature_limit_preprocessed_3000_test1_pipeline
+date: 2025-01-24
+tags: [xx, open_source, pipeline, onnx]
+task: Question Answering
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_multilingual_nature_limit_preprocessed_3000_test1_pipeline` is a Multilingual model originally trained by mlnha.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_multilingual_nature_limit_preprocessed_3000_test1_pipeline_xx_5.5.1_3.0_1737690771198.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_multilingual_nature_limit_preprocessed_3000_test1_pipeline_xx_5.5.1_3.0_1737690771198.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_multilingual_nature_limit_preprocessed_3000_test1_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_multilingual_nature_limit_preprocessed_3000_test1_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_multilingual_nature_limit_preprocessed_3000_test1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|665.0 MB|
+
+## References
+
+https://huggingface.co/mlnha/bert-multilingual-nature-limit-preprocessed-3000-test1
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_multilingual_nature_limit_preprocessed_3000_test1_xx.md b/docs/_posts/ahmedlone127/2025-01-24-bert_multilingual_nature_limit_preprocessed_3000_test1_xx.md
new file mode 100644
index 00000000000000..e3bd25575a6bf1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_multilingual_nature_limit_preprocessed_3000_test1_xx.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Multilingual bert_multilingual_nature_limit_preprocessed_3000_test1 BertForQuestionAnswering from mlnha
+author: John Snow Labs
+name: bert_multilingual_nature_limit_preprocessed_3000_test1
+date: 2025-01-24
+tags: [xx, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_multilingual_nature_limit_preprocessed_3000_test1` is a Multilingual model originally trained by mlnha.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_multilingual_nature_limit_preprocessed_3000_test1_xx_5.5.1_3.0_1737690736169.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_multilingual_nature_limit_preprocessed_3000_test1_xx_5.5.1_3.0_1737690736169.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_multilingual_nature_limit_preprocessed_3000_test1","xx") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_multilingual_nature_limit_preprocessed_3000_test1", "xx")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_multilingual_nature_limit_preprocessed_3000_test1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|xx|
+|Size:|665.0 MB|
+
+## References
+
+https://huggingface.co/mlnha/bert-multilingual-nature-limit-preprocessed-3000-test1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_pipeline_en.md
new file mode 100644
index 00000000000000..e1c4111641c006
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_pipeline_en.md
@@ -0,0 +1,73 @@
+---
+layout: model
+title: English bert_pipeline pipeline RoBertaEmbeddings from ai-ar
+author: John Snow Labs
+name: bert_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_pipeline` is a English model originally trained by ai-ar.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_pipeline_en_5.5.1_3.0_1737757498256.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_pipeline_en_5.5.1_3.0_1737757498256.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("bert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("bert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+References
+
+References
+
+https://huggingface.co/ai-ar/bert
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_qa_cosuleabianca_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_qa_cosuleabianca_en.md
new file mode 100644
index 00000000000000..768a24877ff40c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_qa_cosuleabianca_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_qa_cosuleabianca BertForQuestionAnswering from cosuleabianca
+author: John Snow Labs
+name: bert_qa_cosuleabianca
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_qa_cosuleabianca` is a English model originally trained by cosuleabianca.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_cosuleabianca_en_5.5.1_3.0_1737691427375.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_cosuleabianca_en_5.5.1_3.0_1737691427375.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_cosuleabianca","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_cosuleabianca", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_cosuleabianca|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|464.1 MB|
+
+## References
+
+https://huggingface.co/cosuleabianca/bert_qa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_qa_cosuleabianca_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_qa_cosuleabianca_pipeline_en.md
new file mode 100644
index 00000000000000..0e93bf61bb7fce
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_qa_cosuleabianca_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_qa_cosuleabianca_pipeline pipeline BertForQuestionAnswering from cosuleabianca
+author: John Snow Labs
+name: bert_qa_cosuleabianca_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_qa_cosuleabianca_pipeline` is a English model originally trained by cosuleabianca.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_cosuleabianca_pipeline_en_5.5.1_3.0_1737691451877.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_cosuleabianca_pipeline_en_5.5.1_3.0_1737691451877.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_qa_cosuleabianca_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_qa_cosuleabianca_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_cosuleabianca_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|464.1 MB|
+
+## References
+
+https://huggingface.co/cosuleabianca/bert_qa
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_query_classifier_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_query_classifier_en.md
new file mode 100644
index 00000000000000..a3b6919112f0ef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_query_classifier_en.md
@@ -0,0 +1,96 @@
+---
+layout: model
+title: English bert_query_classifier BertForSequenceClassification from wanderer2k1
+author: John Snow Labs
+name: bert_query_classifier
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_query_classifier` is a English model originally trained by wanderer2k1.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_query_classifier_en_5.5.1_3.0_1737710945006.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_query_classifier_en_5.5.1_3.0_1737710945006.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("bert_query_classifier","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("bert_query_classifier", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_query_classifier|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|501.4 MB|
+
+## References
+
+References
+
+https://huggingface.co/wanderer2k1/BERT-query-classifier
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_query_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_query_classifier_pipeline_en.md
new file mode 100644
index 00000000000000..a430ff7da6480e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_query_classifier_pipeline_en.md
@@ -0,0 +1,72 @@
+---
+layout: model
+title: English bert_query_classifier_pipeline pipeline BertForSequenceClassification from wanderer2k1
+author: John Snow Labs
+name: bert_query_classifier_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_query_classifier_pipeline` is a English model originally trained by wanderer2k1.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_query_classifier_pipeline_en_5.5.1_3.0_1737710972440.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_query_classifier_pipeline_en_5.5.1_3.0_1737710972440.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("bert_query_classifier_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("bert_query_classifier_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_query_classifier_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|501.4 MB|
+
+## References
+
+References
+
+https://huggingface.co/wanderer2k1/BERT-query-classifier
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_swahili_x_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_swahili_x_en.md
new file mode 100644
index 00000000000000..74f687ac6a675a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_swahili_x_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_swahili_x DistilBertForQuestionAnswering from Whalejay
+author: John Snow Labs
+name: bert_swahili_x
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_swahili_x` is a English model originally trained by Whalejay.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_swahili_x_en_5.5.1_3.0_1737741113878.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_swahili_x_en_5.5.1_3.0_1737741113878.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("bert_swahili_x","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("bert_swahili_x", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_swahili_x|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/Whalejay/bert-sw_x
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_swahili_x_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_swahili_x_pipeline_en.md
new file mode 100644
index 00000000000000..506afbddb3d8f3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_swahili_x_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_swahili_x_pipeline pipeline DistilBertForQuestionAnswering from Whalejay
+author: John Snow Labs
+name: bert_swahili_x_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_swahili_x_pipeline` is a English model originally trained by Whalejay.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_swahili_x_pipeline_en_5.5.1_3.0_1737741127165.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_swahili_x_pipeline_en_5.5.1_3.0_1737741127165.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_swahili_x_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_swahili_x_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_swahili_x_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/Whalejay/bert-sw_x
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_swahili_x_small_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_swahili_x_small_en.md
new file mode 100644
index 00000000000000..372c22d43f55e5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_swahili_x_small_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_swahili_x_small DistilBertForQuestionAnswering from Whalejay
+author: John Snow Labs
+name: bert_swahili_x_small
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_swahili_x_small` is a English model originally trained by Whalejay.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_swahili_x_small_en_5.5.1_3.0_1737741213337.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_swahili_x_small_en_5.5.1_3.0_1737741213337.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("bert_swahili_x_small","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("bert_swahili_x_small", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_swahili_x_small|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/Whalejay/bert-sw_x_small
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_swahili_x_small_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_swahili_x_small_pipeline_en.md
new file mode 100644
index 00000000000000..f3e1c211344f44
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_swahili_x_small_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_swahili_x_small_pipeline pipeline DistilBertForQuestionAnswering from Whalejay
+author: John Snow Labs
+name: bert_swahili_x_small_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_swahili_x_small_pipeline` is a English model originally trained by Whalejay.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_swahili_x_small_pipeline_en_5.5.1_3.0_1737741226420.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_swahili_x_small_pipeline_en_5.5.1_3.0_1737741226420.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_swahili_x_small_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_swahili_x_small_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_swahili_x_small_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/Whalejay/bert-sw_x_small
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_tiny_finetuned_squad_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_tiny_finetuned_squad_en.md
new file mode 100644
index 00000000000000..34f8fb7ccd52c0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_tiny_finetuned_squad_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_tiny_finetuned_squad BertForQuestionAnswering from ghostdivisio
+author: John Snow Labs
+name: bert_tiny_finetuned_squad
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_tiny_finetuned_squad` is a English model originally trained by ghostdivisio.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_tiny_finetuned_squad_en_5.5.1_3.0_1737691283307.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_tiny_finetuned_squad_en_5.5.1_3.0_1737691283307.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_tiny_finetuned_squad","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_tiny_finetuned_squad", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_tiny_finetuned_squad|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|16.7 MB|
+
+## References
+
+https://huggingface.co/ghostdivisio/bert-tiny-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_tiny_finetuned_squad_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_tiny_finetuned_squad_pipeline_en.md
new file mode 100644
index 00000000000000..fe6c35a71ac637
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_tiny_finetuned_squad_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_tiny_finetuned_squad_pipeline pipeline BertForQuestionAnswering from ghostdivisio
+author: John Snow Labs
+name: bert_tiny_finetuned_squad_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_tiny_finetuned_squad_pipeline` is a English model originally trained by ghostdivisio.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_tiny_finetuned_squad_pipeline_en_5.5.1_3.0_1737691284489.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_tiny_finetuned_squad_pipeline_en_5.5.1_3.0_1737691284489.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_tiny_finetuned_squad_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_tiny_finetuned_squad_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_tiny_finetuned_squad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|16.7 MB|
+
+## References
+
+https://huggingface.co/ghostdivisio/bert-tiny-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_uncased_finetuned_csv_qa_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_uncased_finetuned_csv_qa_en.md
new file mode 100644
index 00000000000000..31c057dc4b672c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_uncased_finetuned_csv_qa_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_uncased_finetuned_csv_qa BertForQuestionAnswering from SzymonKozl
+author: John Snow Labs
+name: bert_uncased_finetuned_csv_qa
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_uncased_finetuned_csv_qa` is a English model originally trained by SzymonKozl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_uncased_finetuned_csv_qa_en_5.5.1_3.0_1737751444436.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_uncased_finetuned_csv_qa_en_5.5.1_3.0_1737751444436.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_uncased_finetuned_csv_qa","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_uncased_finetuned_csv_qa", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_uncased_finetuned_csv_qa|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/SzymonKozl/bert-uncased-finetuned-csv-qa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bert_uncased_finetuned_csv_qa_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bert_uncased_finetuned_csv_qa_pipeline_en.md
new file mode 100644
index 00000000000000..e07a189313987a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bert_uncased_finetuned_csv_qa_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_uncased_finetuned_csv_qa_pipeline pipeline BertForQuestionAnswering from SzymonKozl
+author: John Snow Labs
+name: bert_uncased_finetuned_csv_qa_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_uncased_finetuned_csv_qa_pipeline` is a English model originally trained by SzymonKozl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_uncased_finetuned_csv_qa_pipeline_en_5.5.1_3.0_1737751471068.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_uncased_finetuned_csv_qa_pipeline_en_5.5.1_3.0_1737751471068.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_uncased_finetuned_csv_qa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_uncased_finetuned_csv_qa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_uncased_finetuned_csv_qa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/SzymonKozl/bert-uncased-finetuned-csv-qa
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bertskill_relative_key_en.md b/docs/_posts/ahmedlone127/2025-01-24-bertskill_relative_key_en.md
new file mode 100644
index 00000000000000..7f8e9c24e9c396
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bertskill_relative_key_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bertskill_relative_key BertEmbeddings from meilanynonsitentua
+author: John Snow Labs
+name: bertskill_relative_key
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bertskill_relative_key` is a English model originally trained by meilanynonsitentua.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bertskill_relative_key_en_5.5.1_3.0_1737742127500.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bertskill_relative_key_en_5.5.1_3.0_1737742127500.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bertskill_relative_key","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bertskill_relative_key","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bertskill_relative_key|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|413.8 MB|
+
+## References
+
+https://huggingface.co/meilanynonsitentua/bertskill-relative-key
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bertskill_relative_key_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bertskill_relative_key_pipeline_en.md
new file mode 100644
index 00000000000000..f10f12132dbfa5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bertskill_relative_key_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bertskill_relative_key_pipeline pipeline BertEmbeddings from meilanynonsitentua
+author: John Snow Labs
+name: bertskill_relative_key_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bertskill_relative_key_pipeline` is a English model originally trained by meilanynonsitentua.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bertskill_relative_key_pipeline_en_5.5.1_3.0_1737742151213.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bertskill_relative_key_pipeline_en_5.5.1_3.0_1737742151213.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bertskill_relative_key_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bertskill_relative_key_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bertskill_relative_key_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|413.8 MB|
+
+## References
+
+https://huggingface.co/meilanynonsitentua/bertskill-relative-key
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bertturk_ottoman_raw_en.md b/docs/_posts/ahmedlone127/2025-01-24-bertturk_ottoman_raw_en.md
new file mode 100644
index 00000000000000..177f6aef147292
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bertturk_ottoman_raw_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bertturk_ottoman_raw BertEmbeddings from onurkeles
+author: John Snow Labs
+name: bertturk_ottoman_raw
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bertturk_ottoman_raw` is a English model originally trained by onurkeles.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bertturk_ottoman_raw_en_5.5.1_3.0_1737742112179.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bertturk_ottoman_raw_en_5.5.1_3.0_1737742112179.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bertturk_ottoman_raw","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bertturk_ottoman_raw","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bertturk_ottoman_raw|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|412.0 MB|
+
+## References
+
+https://huggingface.co/onurkeles/bertturk-ottoman-raw
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bertturk_ottoman_raw_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bertturk_ottoman_raw_pipeline_en.md
new file mode 100644
index 00000000000000..ed494aab5d90a6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bertturk_ottoman_raw_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bertturk_ottoman_raw_pipeline pipeline BertEmbeddings from onurkeles
+author: John Snow Labs
+name: bertturk_ottoman_raw_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bertturk_ottoman_raw_pipeline` is a English model originally trained by onurkeles.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bertturk_ottoman_raw_pipeline_en_5.5.1_3.0_1737742134102.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bertturk_ottoman_raw_pipeline_en_5.5.1_3.0_1737742134102.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bertturk_ottoman_raw_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bertturk_ottoman_raw_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bertturk_ottoman_raw_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|412.0 MB|
+
+## References
+
+https://huggingface.co/onurkeles/bertturk-ottoman-raw
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-beto_finetuned_ner_1_pln_t4_j_d_w_en.md b/docs/_posts/ahmedlone127/2025-01-24-beto_finetuned_ner_1_pln_t4_j_d_w_en.md
new file mode 100644
index 00000000000000..7e85f6aad0e7df
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-beto_finetuned_ner_1_pln_t4_j_d_w_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English beto_finetuned_ner_1_pln_t4_j_d_w BertForTokenClassification from PLN-T4-J-D-W
+author: John Snow Labs
+name: beto_finetuned_ner_1_pln_t4_j_d_w
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`beto_finetuned_ner_1_pln_t4_j_d_w` is a English model originally trained by PLN-T4-J-D-W.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/beto_finetuned_ner_1_pln_t4_j_d_w_en_5.5.1_3.0_1737720025944.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/beto_finetuned_ner_1_pln_t4_j_d_w_en_5.5.1_3.0_1737720025944.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("beto_finetuned_ner_1_pln_t4_j_d_w","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("beto_finetuned_ner_1_pln_t4_j_d_w", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|beto_finetuned_ner_1_pln_t4_j_d_w|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|409.5 MB|
+
+## References
+
+https://huggingface.co/PLN-T4-J-D-W/beto-finetuned-ner-1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-beto_finetuned_ner_1_pln_t4_j_d_w_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-beto_finetuned_ner_1_pln_t4_j_d_w_pipeline_en.md
new file mode 100644
index 00000000000000..a6161ea11db405
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-beto_finetuned_ner_1_pln_t4_j_d_w_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English beto_finetuned_ner_1_pln_t4_j_d_w_pipeline pipeline BertForTokenClassification from PLN-T4-J-D-W
+author: John Snow Labs
+name: beto_finetuned_ner_1_pln_t4_j_d_w_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`beto_finetuned_ner_1_pln_t4_j_d_w_pipeline` is a English model originally trained by PLN-T4-J-D-W.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/beto_finetuned_ner_1_pln_t4_j_d_w_pipeline_en_5.5.1_3.0_1737720049035.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/beto_finetuned_ner_1_pln_t4_j_d_w_pipeline_en_5.5.1_3.0_1737720049035.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("beto_finetuned_ner_1_pln_t4_j_d_w_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("beto_finetuned_ner_1_pln_t4_j_d_w_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|beto_finetuned_ner_1_pln_t4_j_d_w_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.5 MB|
+
+## References
+
+https://huggingface.co/PLN-T4-J-D-W/beto-finetuned-ner-1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bge_reranker_base_fine_tuning_en.md b/docs/_posts/ahmedlone127/2025-01-24-bge_reranker_base_fine_tuning_en.md
new file mode 100644
index 00000000000000..f9eb26767d33ee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bge_reranker_base_fine_tuning_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bge_reranker_base_fine_tuning XlmRoBertaForSequenceClassification from bespin-global
+author: John Snow Labs
+name: bge_reranker_base_fine_tuning
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_reranker_base_fine_tuning` is a English model originally trained by bespin-global.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_reranker_base_fine_tuning_en_5.5.1_3.0_1737713647608.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_reranker_base_fine_tuning_en_5.5.1_3.0_1737713647608.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("bge_reranker_base_fine_tuning","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("bge_reranker_base_fine_tuning", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_reranker_base_fine_tuning|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|994.0 MB|
+
+## References
+
+https://huggingface.co/bespin-global/bge-reranker-base-fine-tuning
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bge_reranker_base_fine_tuning_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bge_reranker_base_fine_tuning_pipeline_en.md
new file mode 100644
index 00000000000000..0abe198835c923
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bge_reranker_base_fine_tuning_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bge_reranker_base_fine_tuning_pipeline pipeline XlmRoBertaForSequenceClassification from bespin-global
+author: John Snow Labs
+name: bge_reranker_base_fine_tuning_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_reranker_base_fine_tuning_pipeline` is a English model originally trained by bespin-global.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_reranker_base_fine_tuning_pipeline_en_5.5.1_3.0_1737713705579.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_reranker_base_fine_tuning_pipeline_en_5.5.1_3.0_1737713705579.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_reranker_base_fine_tuning_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_reranker_base_fine_tuning_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_reranker_base_fine_tuning_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|994.1 MB|
+
+## References
+
+https://huggingface.co/bespin-global/bge-reranker-base-fine-tuning
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bge_reranker_skillfit_en.md b/docs/_posts/ahmedlone127/2025-01-24-bge_reranker_skillfit_en.md
new file mode 100644
index 00000000000000..d5e2a10bc17217
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bge_reranker_skillfit_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bge_reranker_skillfit XlmRoBertaForSequenceClassification from pascalhuerten
+author: John Snow Labs
+name: bge_reranker_skillfit
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_reranker_skillfit` is a English model originally trained by pascalhuerten.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_reranker_skillfit_en_5.5.1_3.0_1737712426261.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_reranker_skillfit_en_5.5.1_3.0_1737712426261.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("bge_reranker_skillfit","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("bge_reranker_skillfit", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_reranker_skillfit|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|994.2 MB|
+
+## References
+
+https://huggingface.co/pascalhuerten/bge_reranker_skillfit
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bge_reranker_skillfit_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bge_reranker_skillfit_pipeline_en.md
new file mode 100644
index 00000000000000..020521085aa604
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bge_reranker_skillfit_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bge_reranker_skillfit_pipeline pipeline XlmRoBertaForSequenceClassification from pascalhuerten
+author: John Snow Labs
+name: bge_reranker_skillfit_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_reranker_skillfit_pipeline` is a English model originally trained by pascalhuerten.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_reranker_skillfit_pipeline_en_5.5.1_3.0_1737712483263.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_reranker_skillfit_pipeline_en_5.5.1_3.0_1737712483263.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_reranker_skillfit_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_reranker_skillfit_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_reranker_skillfit_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|994.3 MB|
+
+## References
+
+https://huggingface.co/pascalhuerten/bge_reranker_skillfit
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bhagwat11_en.md b/docs/_posts/ahmedlone127/2025-01-24-bhagwat11_en.md
new file mode 100644
index 00000000000000..6c2c8f72fde90d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bhagwat11_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bhagwat11 BertForQuestionAnswering from SanskarSharma12
+author: John Snow Labs
+name: bhagwat11
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bhagwat11` is a English model originally trained by SanskarSharma12.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bhagwat11_en_5.5.1_3.0_1737738452832.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bhagwat11_en_5.5.1_3.0_1737738452832.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bhagwat11","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bhagwat11", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bhagwat11|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/SanskarSharma12/bhagwat11
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bhagwat11_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bhagwat11_pipeline_en.md
new file mode 100644
index 00000000000000..063d4a3fc668c7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bhagwat11_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bhagwat11_pipeline pipeline BertForQuestionAnswering from SanskarSharma12
+author: John Snow Labs
+name: bhagwat11_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bhagwat11_pipeline` is a English model originally trained by SanskarSharma12.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bhagwat11_pipeline_en_5.5.1_3.0_1737738477932.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bhagwat11_pipeline_en_5.5.1_3.0_1737738477932.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bhagwat11_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bhagwat11_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bhagwat11_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/SanskarSharma12/bhagwat11
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bias_type_classifier_en.md b/docs/_posts/ahmedlone127/2025-01-24-bias_type_classifier_en.md
new file mode 100644
index 00000000000000..9fc6b99e955cca
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bias_type_classifier_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bias_type_classifier BertForSequenceClassification from maximuspowers
+author: John Snow Labs
+name: bias_type_classifier
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bias_type_classifier` is a English model originally trained by maximuspowers.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bias_type_classifier_en_5.5.1_3.0_1737710586207.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bias_type_classifier_en_5.5.1_3.0_1737710586207.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("bias_type_classifier","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("bias_type_classifier", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bias_type_classifier|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/maximuspowers/bias-type-classifier
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bias_type_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bias_type_classifier_pipeline_en.md
new file mode 100644
index 00000000000000..a889ab865a37c1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bias_type_classifier_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bias_type_classifier_pipeline pipeline BertForSequenceClassification from maximuspowers
+author: John Snow Labs
+name: bias_type_classifier_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bias_type_classifier_pipeline` is a English model originally trained by maximuspowers.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bias_type_classifier_pipeline_en_5.5.1_3.0_1737710608461.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bias_type_classifier_pipeline_en_5.5.1_3.0_1737710608461.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bias_type_classifier_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bias_type_classifier_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bias_type_classifier_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/maximuspowers/bias-type-classifier
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bilingualchildemoec_en.md b/docs/_posts/ahmedlone127/2025-01-24-bilingualchildemoec_en.md
new file mode 100644
index 00000000000000..56fec4d084bfbb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bilingualchildemoec_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bilingualchildemoec XlmRoBertaForSequenceClassification from nanaaaa
+author: John Snow Labs
+name: bilingualchildemoec
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bilingualchildemoec` is a English model originally trained by nanaaaa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bilingualchildemoec_en_5.5.1_3.0_1737713825827.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bilingualchildemoec_en_5.5.1_3.0_1737713825827.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("bilingualchildemoec","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("bilingualchildemoec", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bilingualchildemoec|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|803.9 MB|
+
+## References
+
+https://huggingface.co/nanaaaa/BilingualChildEmoEC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bilingualchildemoec_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bilingualchildemoec_pipeline_en.md
new file mode 100644
index 00000000000000..19d2cba90c3e83
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bilingualchildemoec_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bilingualchildemoec_pipeline pipeline XlmRoBertaForSequenceClassification from nanaaaa
+author: John Snow Labs
+name: bilingualchildemoec_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bilingualchildemoec_pipeline` is a English model originally trained by nanaaaa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bilingualchildemoec_pipeline_en_5.5.1_3.0_1737713954120.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bilingualchildemoec_pipeline_en_5.5.1_3.0_1737713954120.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bilingualchildemoec_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bilingualchildemoec_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bilingualchildemoec_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|803.9 MB|
+
+## References
+
+https://huggingface.co/nanaaaa/BilingualChildEmoEC
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bio_clinicalbert_finetuned_imdb_en.md b/docs/_posts/ahmedlone127/2025-01-24-bio_clinicalbert_finetuned_imdb_en.md
new file mode 100644
index 00000000000000..ece1ccd3a1e6c4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bio_clinicalbert_finetuned_imdb_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bio_clinicalbert_finetuned_imdb BertEmbeddings from reza93v
+author: John Snow Labs
+name: bio_clinicalbert_finetuned_imdb
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bio_clinicalbert_finetuned_imdb` is a English model originally trained by reza93v.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bio_clinicalbert_finetuned_imdb_en_5.5.1_3.0_1737708706022.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bio_clinicalbert_finetuned_imdb_en_5.5.1_3.0_1737708706022.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bio_clinicalbert_finetuned_imdb","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bio_clinicalbert_finetuned_imdb","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bio_clinicalbert_finetuned_imdb|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|403.3 MB|
+
+## References
+
+https://huggingface.co/reza93v/Bio_ClinicalBERT-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bio_clinicalbert_finetuned_imdb_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-bio_clinicalbert_finetuned_imdb_pipeline_en.md
new file mode 100644
index 00000000000000..b3bf08aa9913ff
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bio_clinicalbert_finetuned_imdb_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bio_clinicalbert_finetuned_imdb_pipeline pipeline BertEmbeddings from reza93v
+author: John Snow Labs
+name: bio_clinicalbert_finetuned_imdb_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bio_clinicalbert_finetuned_imdb_pipeline` is a English model originally trained by reza93v.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bio_clinicalbert_finetuned_imdb_pipeline_en_5.5.1_3.0_1737708726689.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bio_clinicalbert_finetuned_imdb_pipeline_en_5.5.1_3.0_1737708726689.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bio_clinicalbert_finetuned_imdb_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bio_clinicalbert_finetuned_imdb_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bio_clinicalbert_finetuned_imdb_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.3 MB|
+
+## References
+
+https://huggingface.co/reza93v/Bio_ClinicalBERT-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-biobart_base_en.md b/docs/_posts/ahmedlone127/2025-01-24-biobart_base_en.md
new file mode 100644
index 00000000000000..d6da34815924b2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-biobart_base_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English biobart_base BartTransformer from GanjinZero
+author: John Snow Labs
+name: biobart_base
+date: 2025-01-24
+tags: [en, open_source, onnx, text_generation, bart]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BartTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biobart_base` is a English model originally trained by GanjinZero.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biobart_base_en_5.5.1_3.0_1737698579565.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biobart_base_en_5.5.1_3.0_1737698579565.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = BartTransformer.pretrained("biobart_base","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = BartTransformer.pretrained("biobart_base","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|biobart_base|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|518.1 MB|
+
+## References
+
+https://huggingface.co/GanjinZero/biobart-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-biobart_base_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-biobart_base_pipeline_en.md
new file mode 100644
index 00000000000000..5f0644e3c7af34
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-biobart_base_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English biobart_base_pipeline pipeline BartTransformer from GanjinZero
+author: John Snow Labs
+name: biobart_base_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biobart_base_pipeline` is a English model originally trained by GanjinZero.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biobart_base_pipeline_en_5.5.1_3.0_1737698735913.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biobart_base_pipeline_en_5.5.1_3.0_1737698735913.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("biobart_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("biobart_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|biobart_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|518.1 MB|
+
+## References
+
+https://huggingface.co/GanjinZero/biobart-base
+
+## Included Models
+
+- DocumentAssembler
+- BartTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-biobert_finetuned_ner_en.md b/docs/_posts/ahmedlone127/2025-01-24-biobert_finetuned_ner_en.md
new file mode 100644
index 00000000000000..53a24dabf363d0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-biobert_finetuned_ner_en.md
@@ -0,0 +1,96 @@
+---
+layout: model
+title: English biobert_finetuned_ner BertForTokenClassification from jialinselenasong
+author: John Snow Labs
+name: biobert_finetuned_ner
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biobert_finetuned_ner` is a English model originally trained by jialinselenasong.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biobert_finetuned_ner_en_5.5.1_3.0_1737720673579.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biobert_finetuned_ner_en_5.5.1_3.0_1737720673579.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("biobert_finetuned_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("biobert_finetuned_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|biobert_finetuned_ner|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+References
+
+https://huggingface.co/jialinselenasong/biobert-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-biobert_finetuned_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-biobert_finetuned_ner_pipeline_en.md
new file mode 100644
index 00000000000000..299b1562cc4a25
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-biobert_finetuned_ner_pipeline_en.md
@@ -0,0 +1,72 @@
+---
+layout: model
+title: English biobert_finetuned_ner_pipeline pipeline BertForTokenClassification from jialinselenasong
+author: John Snow Labs
+name: biobert_finetuned_ner_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biobert_finetuned_ner_pipeline` is a English model originally trained by jialinselenasong.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biobert_finetuned_ner_pipeline_en_5.5.1_3.0_1737720694837.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biobert_finetuned_ner_pipeline_en_5.5.1_3.0_1737720694837.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("biobert_finetuned_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("biobert_finetuned_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|biobert_finetuned_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+References
+
+https://huggingface.co/jialinselenasong/biobert-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-biobert_finetuned_squadcovid_en.md b/docs/_posts/ahmedlone127/2025-01-24-biobert_finetuned_squadcovid_en.md
new file mode 100644
index 00000000000000..32a66744580383
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-biobert_finetuned_squadcovid_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English biobert_finetuned_squadcovid BertForQuestionAnswering from Rahul13
+author: John Snow Labs
+name: biobert_finetuned_squadcovid
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biobert_finetuned_squadcovid` is a English model originally trained by Rahul13.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biobert_finetuned_squadcovid_en_5.5.1_3.0_1737691151425.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biobert_finetuned_squadcovid_en_5.5.1_3.0_1737691151425.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("biobert_finetuned_squadcovid","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("biobert_finetuned_squadcovid", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|biobert_finetuned_squadcovid|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/Rahul13/biobert-finetuned-squadcovid
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-biobert_finetuned_squadcovid_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-biobert_finetuned_squadcovid_pipeline_en.md
new file mode 100644
index 00000000000000..a5b507e61f9104
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-biobert_finetuned_squadcovid_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English biobert_finetuned_squadcovid_pipeline pipeline BertForQuestionAnswering from Rahul13
+author: John Snow Labs
+name: biobert_finetuned_squadcovid_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biobert_finetuned_squadcovid_pipeline` is a English model originally trained by Rahul13.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biobert_finetuned_squadcovid_pipeline_en_5.5.1_3.0_1737691172728.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biobert_finetuned_squadcovid_pipeline_en_5.5.1_3.0_1737691172728.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("biobert_finetuned_squadcovid_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("biobert_finetuned_squadcovid_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|biobert_finetuned_squadcovid_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/Rahul13/biobert-finetuned-squadcovid
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-brain_tumor_class_swin_en.md b/docs/_posts/ahmedlone127/2025-01-24-brain_tumor_class_swin_en.md
new file mode 100644
index 00000000000000..6caff7499d1383
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-brain_tumor_class_swin_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English brain_tumor_class_swin SwinForImageClassification from Devarshi
+author: John Snow Labs
+name: brain_tumor_class_swin
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`brain_tumor_class_swin` is a English model originally trained by Devarshi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/brain_tumor_class_swin_en_5.5.1_3.0_1737762437598.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/brain_tumor_class_swin_en_5.5.1_3.0_1737762437598.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""brain_tumor_class_swin","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("brain_tumor_class_swin","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|brain_tumor_class_swin|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|649.8 MB|
+
+## References
+
+https://huggingface.co/Devarshi/Brain_Tumor_Class_swin
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-brain_tumor_class_swin_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-brain_tumor_class_swin_pipeline_en.md
new file mode 100644
index 00000000000000..99d49fd6b8532c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-brain_tumor_class_swin_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English brain_tumor_class_swin_pipeline pipeline SwinForImageClassification from Devarshi
+author: John Snow Labs
+name: brain_tumor_class_swin_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`brain_tumor_class_swin_pipeline` is a English model originally trained by Devarshi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/brain_tumor_class_swin_pipeline_en_5.5.1_3.0_1737762474509.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/brain_tumor_class_swin_pipeline_en_5.5.1_3.0_1737762474509.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("brain_tumor_class_swin_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("brain_tumor_class_swin_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|brain_tumor_class_swin_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|649.8 MB|
+
+## References
+
+https://huggingface.co/Devarshi/Brain_Tumor_Class_swin
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-brain_tumor_classification_dheiver_en.md b/docs/_posts/ahmedlone127/2025-01-24-brain_tumor_classification_dheiver_en.md
new file mode 100644
index 00000000000000..330130c4d97b42
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-brain_tumor_classification_dheiver_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English brain_tumor_classification_dheiver SwinForImageClassification from DHEIVER
+author: John Snow Labs
+name: brain_tumor_classification_dheiver
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`brain_tumor_classification_dheiver` is a English model originally trained by DHEIVER.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/brain_tumor_classification_dheiver_en_5.5.1_3.0_1737754081194.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/brain_tumor_classification_dheiver_en_5.5.1_3.0_1737754081194.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""brain_tumor_classification_dheiver","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("brain_tumor_classification_dheiver","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|brain_tumor_classification_dheiver|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/DHEIVER/Brain_Tumor_Classification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-brain_tumor_classification_dheiver_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-brain_tumor_classification_dheiver_pipeline_en.md
new file mode 100644
index 00000000000000..7ee72d5d58883b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-brain_tumor_classification_dheiver_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English brain_tumor_classification_dheiver_pipeline pipeline SwinForImageClassification from DHEIVER
+author: John Snow Labs
+name: brain_tumor_classification_dheiver_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`brain_tumor_classification_dheiver_pipeline` is a English model originally trained by DHEIVER.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/brain_tumor_classification_dheiver_pipeline_en_5.5.1_3.0_1737754099270.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/brain_tumor_classification_dheiver_pipeline_en_5.5.1_3.0_1737754099270.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("brain_tumor_classification_dheiver_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("brain_tumor_classification_dheiver_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|brain_tumor_classification_dheiver_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/DHEIVER/Brain_Tumor_Classification
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-brainbolt_qna_model_en.md b/docs/_posts/ahmedlone127/2025-01-24-brainbolt_qna_model_en.md
new file mode 100644
index 00000000000000..8196d81c805d60
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-brainbolt_qna_model_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English brainbolt_qna_model BertForQuestionAnswering from Priyanshuchaudhary2425
+author: John Snow Labs
+name: brainbolt_qna_model
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`brainbolt_qna_model` is a English model originally trained by Priyanshuchaudhary2425.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/brainbolt_qna_model_en_5.5.1_3.0_1737738146826.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/brainbolt_qna_model_en_5.5.1_3.0_1737738146826.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("brainbolt_qna_model","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("brainbolt_qna_model", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|brainbolt_qna_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/Priyanshuchaudhary2425/BrainBolt-QnA-Model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-brainbolt_qna_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-brainbolt_qna_model_pipeline_en.md
new file mode 100644
index 00000000000000..822626fa8dd400
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-brainbolt_qna_model_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English brainbolt_qna_model_pipeline pipeline BertForQuestionAnswering from Priyanshuchaudhary2425
+author: John Snow Labs
+name: brainbolt_qna_model_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`brainbolt_qna_model_pipeline` is a English model originally trained by Priyanshuchaudhary2425.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/brainbolt_qna_model_pipeline_en_5.5.1_3.0_1737738178069.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/brainbolt_qna_model_pipeline_en_5.5.1_3.0_1737738178069.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("brainbolt_qna_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("brainbolt_qna_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|brainbolt_qna_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/Priyanshuchaudhary2425/BrainBolt-QnA-Model
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bsc_bio_ehr_spanish_carmen_livingner_species_es.md b/docs/_posts/ahmedlone127/2025-01-24-bsc_bio_ehr_spanish_carmen_livingner_species_es.md
new file mode 100644
index 00000000000000..4abf44eafa9db0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bsc_bio_ehr_spanish_carmen_livingner_species_es.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Castilian, Spanish bsc_bio_ehr_spanish_carmen_livingner_species RoBertaForTokenClassification from BSC-NLP4BIA
+author: John Snow Labs
+name: bsc_bio_ehr_spanish_carmen_livingner_species
+date: 2025-01-24
+tags: [es, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: es
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bsc_bio_ehr_spanish_carmen_livingner_species` is a Castilian, Spanish model originally trained by BSC-NLP4BIA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bsc_bio_ehr_spanish_carmen_livingner_species_es_5.5.1_3.0_1737755496768.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bsc_bio_ehr_spanish_carmen_livingner_species_es_5.5.1_3.0_1737755496768.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("bsc_bio_ehr_spanish_carmen_livingner_species","es") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("bsc_bio_ehr_spanish_carmen_livingner_species", "es")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bsc_bio_ehr_spanish_carmen_livingner_species|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|es|
+|Size:|454.6 MB|
+
+## References
+
+https://huggingface.co/BSC-NLP4BIA/bsc-bio-ehr-es-carmen-livingner-species
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-bsc_bio_ehr_spanish_carmen_livingner_species_pipeline_es.md b/docs/_posts/ahmedlone127/2025-01-24-bsc_bio_ehr_spanish_carmen_livingner_species_pipeline_es.md
new file mode 100644
index 00000000000000..7f48eb2ba9bc5f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-bsc_bio_ehr_spanish_carmen_livingner_species_pipeline_es.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Castilian, Spanish bsc_bio_ehr_spanish_carmen_livingner_species_pipeline pipeline RoBertaForTokenClassification from BSC-NLP4BIA
+author: John Snow Labs
+name: bsc_bio_ehr_spanish_carmen_livingner_species_pipeline
+date: 2025-01-24
+tags: [es, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: es
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bsc_bio_ehr_spanish_carmen_livingner_species_pipeline` is a Castilian, Spanish model originally trained by BSC-NLP4BIA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bsc_bio_ehr_spanish_carmen_livingner_species_pipeline_es_5.5.1_3.0_1737755522232.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bsc_bio_ehr_spanish_carmen_livingner_species_pipeline_es_5.5.1_3.0_1737755522232.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bsc_bio_ehr_spanish_carmen_livingner_species_pipeline", lang = "es")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bsc_bio_ehr_spanish_carmen_livingner_species_pipeline", lang = "es")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bsc_bio_ehr_spanish_carmen_livingner_species_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|es|
+|Size:|454.6 MB|
+
+## References
+
+https://huggingface.co/BSC-NLP4BIA/bsc-bio-ehr-es-carmen-livingner-species
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-burmese_awesome_model_seq_cl_en.md b/docs/_posts/ahmedlone127/2025-01-24-burmese_awesome_model_seq_cl_en.md
new file mode 100644
index 00000000000000..0ad25639de79a1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-burmese_awesome_model_seq_cl_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_seq_cl AlbertForSequenceClassification from yunzliang
+author: John Snow Labs
+name: burmese_awesome_model_seq_cl
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, albert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_seq_cl` is a English model originally trained by yunzliang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_seq_cl_en_5.5.1_3.0_1737750204455.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_seq_cl_en_5.5.1_3.0_1737750204455.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = AlbertForSequenceClassification.pretrained("burmese_awesome_model_seq_cl","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = AlbertForSequenceClassification.pretrained("burmese_awesome_model_seq_cl", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_seq_cl|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/yunzliang/my_awesome_model_seq_cl
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-burmese_awesome_model_seq_cl_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-burmese_awesome_model_seq_cl_pipeline_en.md
new file mode 100644
index 00000000000000..7bc5df2150f435
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-burmese_awesome_model_seq_cl_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_seq_cl_pipeline pipeline AlbertForSequenceClassification from yunzliang
+author: John Snow Labs
+name: burmese_awesome_model_seq_cl_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_seq_cl_pipeline` is a English model originally trained by yunzliang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_seq_cl_pipeline_en_5.5.1_3.0_1737750206686.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_seq_cl_pipeline_en_5.5.1_3.0_1737750206686.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_seq_cl_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_seq_cl_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_seq_cl_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/yunzliang/my_awesome_model_seq_cl
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-burmese_awesome_qa_model_ananyalahiri2003_en.md b/docs/_posts/ahmedlone127/2025-01-24-burmese_awesome_qa_model_ananyalahiri2003_en.md
new file mode 100644
index 00000000000000..a2b19872cfe5e0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-burmese_awesome_qa_model_ananyalahiri2003_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_ananyalahiri2003 DistilBertForQuestionAnswering from ananyalahiri2003
+author: John Snow Labs
+name: burmese_awesome_qa_model_ananyalahiri2003
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_ananyalahiri2003` is a English model originally trained by ananyalahiri2003.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_ananyalahiri2003_en_5.5.1_3.0_1737741336287.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_ananyalahiri2003_en_5.5.1_3.0_1737741336287.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_ananyalahiri2003","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_ananyalahiri2003", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_ananyalahiri2003|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/ananyalahiri2003/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-burmese_awesome_qa_model_ananyalahiri2003_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-burmese_awesome_qa_model_ananyalahiri2003_pipeline_en.md
new file mode 100644
index 00000000000000..2ca8795ddec927
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-burmese_awesome_qa_model_ananyalahiri2003_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_ananyalahiri2003_pipeline pipeline DistilBertForQuestionAnswering from ananyalahiri2003
+author: John Snow Labs
+name: burmese_awesome_qa_model_ananyalahiri2003_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_ananyalahiri2003_pipeline` is a English model originally trained by ananyalahiri2003.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_ananyalahiri2003_pipeline_en_5.5.1_3.0_1737741349223.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_ananyalahiri2003_pipeline_en_5.5.1_3.0_1737741349223.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_ananyalahiri2003_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_ananyalahiri2003_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_ananyalahiri2003_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/ananyalahiri2003/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-burmese_awesome_qa_model_ditherr_en.md b/docs/_posts/ahmedlone127/2025-01-24-burmese_awesome_qa_model_ditherr_en.md
new file mode 100644
index 00000000000000..d08b3f30a05420
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-burmese_awesome_qa_model_ditherr_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_ditherr DistilBertForQuestionAnswering from ditherr
+author: John Snow Labs
+name: burmese_awesome_qa_model_ditherr
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_ditherr` is a English model originally trained by ditherr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_ditherr_en_5.5.1_3.0_1737741133417.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_ditherr_en_5.5.1_3.0_1737741133417.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_ditherr","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_ditherr", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_ditherr|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/ditherr/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-burmese_awesome_qa_model_ditherr_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-burmese_awesome_qa_model_ditherr_pipeline_en.md
new file mode 100644
index 00000000000000..5056ed70d22882
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-burmese_awesome_qa_model_ditherr_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_ditherr_pipeline pipeline DistilBertForQuestionAnswering from ditherr
+author: John Snow Labs
+name: burmese_awesome_qa_model_ditherr_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_ditherr_pipeline` is a English model originally trained by ditherr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_ditherr_pipeline_en_5.5.1_3.0_1737741146810.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_ditherr_pipeline_en_5.5.1_3.0_1737741146810.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_ditherr_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_ditherr_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_ditherr_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/ditherr/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-burmese_awesome_qa_model_ram9801_en.md b/docs/_posts/ahmedlone127/2025-01-24-burmese_awesome_qa_model_ram9801_en.md
new file mode 100644
index 00000000000000..ce73f49384bce9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-burmese_awesome_qa_model_ram9801_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_ram9801 DistilBertForQuestionAnswering from ram9801
+author: John Snow Labs
+name: burmese_awesome_qa_model_ram9801
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_ram9801` is a English model originally trained by ram9801.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_ram9801_en_5.5.1_3.0_1737741343665.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_ram9801_en_5.5.1_3.0_1737741343665.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_ram9801","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_ram9801", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_ram9801|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/ram9801/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-burmese_awesome_qa_model_ram9801_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-burmese_awesome_qa_model_ram9801_pipeline_en.md
new file mode 100644
index 00000000000000..93b39bc1ded025
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-burmese_awesome_qa_model_ram9801_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_ram9801_pipeline pipeline DistilBertForQuestionAnswering from ram9801
+author: John Snow Labs
+name: burmese_awesome_qa_model_ram9801_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_ram9801_pipeline` is a English model originally trained by ram9801.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_ram9801_pipeline_en_5.5.1_3.0_1737741356883.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_ram9801_pipeline_en_5.5.1_3.0_1737741356883.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_ram9801_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_ram9801_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_ram9801_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/ram9801/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-burmese_awesome_qa_model_rsml_en.md b/docs/_posts/ahmedlone127/2025-01-24-burmese_awesome_qa_model_rsml_en.md
new file mode 100644
index 00000000000000..8899d07294dd4f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-burmese_awesome_qa_model_rsml_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_rsml BertForQuestionAnswering from rsml
+author: John Snow Labs
+name: burmese_awesome_qa_model_rsml
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_rsml` is a English model originally trained by rsml.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_rsml_en_5.5.1_3.0_1737690314376.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_rsml_en_5.5.1_3.0_1737690314376.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("burmese_awesome_qa_model_rsml","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("burmese_awesome_qa_model_rsml", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_rsml|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/rsml/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-burmese_awesome_qa_model_rsml_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-burmese_awesome_qa_model_rsml_pipeline_en.md
new file mode 100644
index 00000000000000..50bebb5b83bee1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-burmese_awesome_qa_model_rsml_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_rsml_pipeline pipeline BertForQuestionAnswering from rsml
+author: John Snow Labs
+name: burmese_awesome_qa_model_rsml_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_rsml_pipeline` is a English model originally trained by rsml.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_rsml_pipeline_en_5.5.1_3.0_1737690342291.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_rsml_pipeline_en_5.5.1_3.0_1737690342291.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_rsml_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_rsml_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_rsml_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/rsml/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-burmese_awesome_qa_model_shahidnasimkhan_en.md b/docs/_posts/ahmedlone127/2025-01-24-burmese_awesome_qa_model_shahidnasimkhan_en.md
new file mode 100644
index 00000000000000..8605115443a471
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-burmese_awesome_qa_model_shahidnasimkhan_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_shahidnasimkhan DistilBertForQuestionAnswering from shahidnasimkhan
+author: John Snow Labs
+name: burmese_awesome_qa_model_shahidnasimkhan
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_shahidnasimkhan` is a English model originally trained by shahidnasimkhan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_shahidnasimkhan_en_5.5.1_3.0_1737741012845.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_shahidnasimkhan_en_5.5.1_3.0_1737741012845.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_shahidnasimkhan","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_shahidnasimkhan", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_shahidnasimkhan|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/shahidnasimkhan/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-burmese_awesome_qa_model_shahidnasimkhan_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-burmese_awesome_qa_model_shahidnasimkhan_pipeline_en.md
new file mode 100644
index 00000000000000..bcb44682a72261
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-burmese_awesome_qa_model_shahidnasimkhan_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_shahidnasimkhan_pipeline pipeline DistilBertForQuestionAnswering from shahidnasimkhan
+author: John Snow Labs
+name: burmese_awesome_qa_model_shahidnasimkhan_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_shahidnasimkhan_pipeline` is a English model originally trained by shahidnasimkhan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_shahidnasimkhan_pipeline_en_5.5.1_3.0_1737741031665.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_shahidnasimkhan_pipeline_en_5.5.1_3.0_1737741031665.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_shahidnasimkhan_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_shahidnasimkhan_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_shahidnasimkhan_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/shahidnasimkhan/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-burmese_awesome_token_classification_v2_en.md b/docs/_posts/ahmedlone127/2025-01-24-burmese_awesome_token_classification_v2_en.md
new file mode 100644
index 00000000000000..dfd252d583acc1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-burmese_awesome_token_classification_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_token_classification_v2 XlmRoBertaForTokenClassification from lilyyellow
+author: John Snow Labs
+name: burmese_awesome_token_classification_v2
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_token_classification_v2` is a English model originally trained by lilyyellow.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_token_classification_v2_en_5.5.1_3.0_1737678036625.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_token_classification_v2_en_5.5.1_3.0_1737678036625.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("burmese_awesome_token_classification_v2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("burmese_awesome_token_classification_v2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_token_classification_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|808.6 MB|
+
+## References
+
+https://huggingface.co/lilyyellow/my_awesome_token_classification_v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-burmese_awesome_token_classification_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-burmese_awesome_token_classification_v2_pipeline_en.md
new file mode 100644
index 00000000000000..bc8adc0d05efc9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-burmese_awesome_token_classification_v2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_token_classification_v2_pipeline pipeline XlmRoBertaForTokenClassification from lilyyellow
+author: John Snow Labs
+name: burmese_awesome_token_classification_v2_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_token_classification_v2_pipeline` is a English model originally trained by lilyyellow.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_token_classification_v2_pipeline_en_5.5.1_3.0_1737678158625.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_token_classification_v2_pipeline_en_5.5.1_3.0_1737678158625.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_token_classification_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_token_classification_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_token_classification_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|808.6 MB|
+
+## References
+
+https://huggingface.co/lilyyellow/my_awesome_token_classification_v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-burmese_awesome_wnut_model_randheerk_en.md b/docs/_posts/ahmedlone127/2025-01-24-burmese_awesome_wnut_model_randheerk_en.md
new file mode 100644
index 00000000000000..646d3136c2dfe3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-burmese_awesome_wnut_model_randheerk_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_randheerk DistilBertForTokenClassification from randheerk
+author: John Snow Labs
+name: burmese_awesome_wnut_model_randheerk
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_randheerk` is a English model originally trained by randheerk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_randheerk_en_5.5.1_3.0_1737692497766.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_randheerk_en_5.5.1_3.0_1737692497766.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_randheerk","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_randheerk", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_randheerk|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/randheerk/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-burmese_awesome_wnut_model_randheerk_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-burmese_awesome_wnut_model_randheerk_pipeline_en.md
new file mode 100644
index 00000000000000..f2babd52be49c3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-burmese_awesome_wnut_model_randheerk_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_randheerk_pipeline pipeline DistilBertForTokenClassification from randheerk
+author: John Snow Labs
+name: burmese_awesome_wnut_model_randheerk_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_randheerk_pipeline` is a English model originally trained by randheerk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_randheerk_pipeline_en_5.5.1_3.0_1737692518902.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_randheerk_pipeline_en_5.5.1_3.0_1737692518902.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_wnut_model_randheerk_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_wnut_model_randheerk_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_randheerk_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/randheerk/my_awesome_wnut_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-burmese_eli5_clm_model_en.md b/docs/_posts/ahmedlone127/2025-01-24-burmese_eli5_clm_model_en.md
new file mode 100644
index 00000000000000..aeda29a35c0b3a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-burmese_eli5_clm_model_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_eli5_clm_model GPT2Transformer from giantkylin
+author: John Snow Labs
+name: burmese_eli5_clm_model
+date: 2025-01-24
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_eli5_clm_model` is a English model originally trained by giantkylin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_eli5_clm_model_en_5.5.1_3.0_1737716482293.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_eli5_clm_model_en_5.5.1_3.0_1737716482293.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("burmese_eli5_clm_model","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("burmese_eli5_clm_model","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_eli5_clm_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|308.4 MB|
+
+## References
+
+https://huggingface.co/giantkylin/my_eli5_clm-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-burmese_eli5_clm_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-burmese_eli5_clm_model_pipeline_en.md
new file mode 100644
index 00000000000000..d6bbd3bbfe3025
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-burmese_eli5_clm_model_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_eli5_clm_model_pipeline pipeline GPT2Transformer from giantkylin
+author: John Snow Labs
+name: burmese_eli5_clm_model_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_eli5_clm_model_pipeline` is a English model originally trained by giantkylin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_eli5_clm_model_pipeline_en_5.5.1_3.0_1737716498463.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_eli5_clm_model_pipeline_en_5.5.1_3.0_1737716498463.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_eli5_clm_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_eli5_clm_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_eli5_clm_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|308.4 MB|
+
+## References
+
+https://huggingface.co/giantkylin/my_eli5_clm-model
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-burmese_model_en.md b/docs/_posts/ahmedlone127/2025-01-24-burmese_model_en.md
new file mode 100644
index 00000000000000..fdc5765eb36806
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-burmese_model_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English burmese_model RoBertaForSequenceClassification from dadashzadeh
+author: John Snow Labs
+name: burmese_model
+date: 2025-01-24
+tags: [roberta, en, open_source, sequence_classification, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_model` is a English model originally trained by dadashzadeh.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_model_en_5.5.1_3.0_1737757029326.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_model_en_5.5.1_3.0_1737757029326.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = DocumentAssembler()\
+    .setInputCol("text")\
+    .setOutputCol("document")
+
+tokenizer = Tokenizer()\
+    .setInputCols("document")\
+    .setOutputCol("token")  
+    
+sequenceClassifier = RoBertaForSequenceClassification.pretrained("burmese_model","en")\
+            .setInputCols(["document","token"])\
+            .setOutputCol("class")
+
+pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val document_assembler = new DocumentAssembler()
+    .setInputCol("text")
+    .setOutputCol("document")
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document") 
+    .setOutputCol("token")  
+    
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("burmese_model","en")
+            .setInputCols(Array("document","token"))
+            .setOutputCol("class")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|411.7 MB|
+
+## References
+
+References
+
+References
+
+https://huggingface.co/dadashzadeh/my_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-burmese_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-burmese_model_pipeline_en.md
new file mode 100644
index 00000000000000..50aa6e250e78bd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-burmese_model_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English burmese_model_pipeline pipeline DistilBertForTokenClassification from shubhamgantayat
+author: John Snow Labs
+name: burmese_model_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_model_pipeline` is a English model originally trained by shubhamgantayat.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_model_pipeline_en_5.5.1_3.0_1737757054557.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_model_pipeline_en_5.5.1_3.0_1737757054557.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("burmese_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("burmese_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|411.7 MB|
+
+## References
+
+References
+
+https://huggingface.co/shubhamgantayat/my_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-burmese_ner_model_en.md b/docs/_posts/ahmedlone127/2025-01-24-burmese_ner_model_en.md
new file mode 100644
index 00000000000000..64d7976f72a2f1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-burmese_ner_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_ner_model XlmRoBertaForTokenClassification from eludan
+author: John Snow Labs
+name: burmese_ner_model
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_ner_model` is a English model originally trained by eludan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_ner_model_en_5.5.1_3.0_1737679936586.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_ner_model_en_5.5.1_3.0_1737679936586.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("burmese_ner_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("burmese_ner_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_ner_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|795.1 MB|
+
+## References
+
+https://huggingface.co/eludan/my_ner_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-burmese_ner_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-burmese_ner_model_pipeline_en.md
new file mode 100644
index 00000000000000..2684e3881107ff
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-burmese_ner_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_ner_model_pipeline pipeline XlmRoBertaForTokenClassification from eludan
+author: John Snow Labs
+name: burmese_ner_model_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_ner_model_pipeline` is a English model originally trained by eludan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_ner_model_pipeline_en_5.5.1_3.0_1737680064545.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_ner_model_pipeline_en_5.5.1_3.0_1737680064545.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_ner_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_ner_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_ner_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|795.1 MB|
+
+## References
+
+https://huggingface.co/eludan/my_ner_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-burmese_qa_model_en.md b/docs/_posts/ahmedlone127/2025-01-24-burmese_qa_model_en.md
new file mode 100644
index 00000000000000..aca29487415f8c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-burmese_qa_model_en.md
@@ -0,0 +1,88 @@
+---
+layout: model
+title: English burmese_qa_model CamemBertForQuestionAnswering from al123
+author: John Snow Labs
+name: burmese_qa_model
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, camembert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_qa_model` is a English model originally trained by al123.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_qa_model_en_5.5.1_3.0_1737709280822.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_qa_model_en_5.5.1_3.0_1737709280822.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = CamemBertForQuestionAnswering.pretrained("burmese_qa_model","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = CamemBertForQuestionAnswering.pretrained("burmese_qa_model", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_qa_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|42.0 MB|
+
+## References
+
+References
+
+https://huggingface.co/al123/my_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-burmese_qa_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-burmese_qa_model_pipeline_en.md
new file mode 100644
index 00000000000000..c4f06b867690d1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-burmese_qa_model_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English burmese_qa_model_pipeline pipeline CamemBertForQuestionAnswering from al123
+author: John Snow Labs
+name: burmese_qa_model_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_qa_model_pipeline` is a English model originally trained by al123.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_qa_model_pipeline_en_5.5.1_3.0_1737709283280.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_qa_model_pipeline_en_5.5.1_3.0_1737709283280.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("burmese_qa_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("burmese_qa_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_qa_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|42.0 MB|
+
+## References
+
+References
+
+https://huggingface.co/al123/my_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- AlbertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-capstone_erica_bert_en.md b/docs/_posts/ahmedlone127/2025-01-24-capstone_erica_bert_en.md
new file mode 100644
index 00000000000000..ccae27c2a23328
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-capstone_erica_bert_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English capstone_erica_bert BertForQuestionAnswering from Kdogs
+author: John Snow Labs
+name: capstone_erica_bert
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`capstone_erica_bert` is a English model originally trained by Kdogs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/capstone_erica_bert_en_5.5.1_3.0_1737746932304.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/capstone_erica_bert_en_5.5.1_3.0_1737746932304.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("capstone_erica_bert","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("capstone_erica_bert", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|capstone_erica_bert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|412.4 MB|
+
+## References
+
+https://huggingface.co/Kdogs/Capstone_ERICA_BERT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-capstone_erica_bert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-capstone_erica_bert_pipeline_en.md
new file mode 100644
index 00000000000000..90b74d0361612f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-capstone_erica_bert_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English capstone_erica_bert_pipeline pipeline BertForQuestionAnswering from Kdogs
+author: John Snow Labs
+name: capstone_erica_bert_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`capstone_erica_bert_pipeline` is a English model originally trained by Kdogs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/capstone_erica_bert_pipeline_en_5.5.1_3.0_1737746956014.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/capstone_erica_bert_pipeline_en_5.5.1_3.0_1737746956014.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("capstone_erica_bert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("capstone_erica_bert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|capstone_erica_bert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|412.4 MB|
+
+## References
+
+https://huggingface.co/Kdogs/Capstone_ERICA_BERT
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-cards_blt_swin_tiny_patch4_window7_224_finetuned_v2_en.md b/docs/_posts/ahmedlone127/2025-01-24-cards_blt_swin_tiny_patch4_window7_224_finetuned_v2_en.md
new file mode 100644
index 00000000000000..d0b232aa524f96
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-cards_blt_swin_tiny_patch4_window7_224_finetuned_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English cards_blt_swin_tiny_patch4_window7_224_finetuned_v2 SwinForImageClassification from ansilmbabl
+author: John Snow Labs
+name: cards_blt_swin_tiny_patch4_window7_224_finetuned_v2
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cards_blt_swin_tiny_patch4_window7_224_finetuned_v2` is a English model originally trained by ansilmbabl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cards_blt_swin_tiny_patch4_window7_224_finetuned_v2_en_5.5.1_3.0_1737762678591.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cards_blt_swin_tiny_patch4_window7_224_finetuned_v2_en_5.5.1_3.0_1737762678591.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""cards_blt_swin_tiny_patch4_window7_224_finetuned_v2","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("cards_blt_swin_tiny_patch4_window7_224_finetuned_v2","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cards_blt_swin_tiny_patch4_window7_224_finetuned_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/ansilmbabl/cards-blt-swin-tiny-patch4-window7-224-finetuned-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-cards_blt_swin_tiny_patch4_window7_224_finetuned_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-cards_blt_swin_tiny_patch4_window7_224_finetuned_v2_pipeline_en.md
new file mode 100644
index 00000000000000..b583878ccc4563
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-cards_blt_swin_tiny_patch4_window7_224_finetuned_v2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English cards_blt_swin_tiny_patch4_window7_224_finetuned_v2_pipeline pipeline SwinForImageClassification from ansilmbabl
+author: John Snow Labs
+name: cards_blt_swin_tiny_patch4_window7_224_finetuned_v2_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cards_blt_swin_tiny_patch4_window7_224_finetuned_v2_pipeline` is a English model originally trained by ansilmbabl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cards_blt_swin_tiny_patch4_window7_224_finetuned_v2_pipeline_en_5.5.1_3.0_1737762690724.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cards_blt_swin_tiny_patch4_window7_224_finetuned_v2_pipeline_en_5.5.1_3.0_1737762690724.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("cards_blt_swin_tiny_patch4_window7_224_finetuned_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cards_blt_swin_tiny_patch4_window7_224_finetuned_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cards_blt_swin_tiny_patch4_window7_224_finetuned_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/ansilmbabl/cards-blt-swin-tiny-patch4-window7-224-finetuned-v2
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-cards_top_left_swin_tiny_patch4_window7_224_finetuned_v3_more_data_en.md b/docs/_posts/ahmedlone127/2025-01-24-cards_top_left_swin_tiny_patch4_window7_224_finetuned_v3_more_data_en.md
new file mode 100644
index 00000000000000..315e8cf4ebeaf0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-cards_top_left_swin_tiny_patch4_window7_224_finetuned_v3_more_data_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English cards_top_left_swin_tiny_patch4_window7_224_finetuned_v3_more_data SwinForImageClassification from sai17
+author: John Snow Labs
+name: cards_top_left_swin_tiny_patch4_window7_224_finetuned_v3_more_data
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cards_top_left_swin_tiny_patch4_window7_224_finetuned_v3_more_data` is a English model originally trained by sai17.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cards_top_left_swin_tiny_patch4_window7_224_finetuned_v3_more_data_en_5.5.1_3.0_1737694465614.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cards_top_left_swin_tiny_patch4_window7_224_finetuned_v3_more_data_en_5.5.1_3.0_1737694465614.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""cards_top_left_swin_tiny_patch4_window7_224_finetuned_v3_more_data","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("cards_top_left_swin_tiny_patch4_window7_224_finetuned_v3_more_data","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cards_top_left_swin_tiny_patch4_window7_224_finetuned_v3_more_data|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/sai17/cards-top_left_swin-tiny-patch4-window7-224-finetuned-v3_more_data
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-cards_top_left_swin_tiny_patch4_window7_224_finetuned_v3_more_data_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-cards_top_left_swin_tiny_patch4_window7_224_finetuned_v3_more_data_pipeline_en.md
new file mode 100644
index 00000000000000..a27c1312462963
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-cards_top_left_swin_tiny_patch4_window7_224_finetuned_v3_more_data_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English cards_top_left_swin_tiny_patch4_window7_224_finetuned_v3_more_data_pipeline pipeline SwinForImageClassification from sai17
+author: John Snow Labs
+name: cards_top_left_swin_tiny_patch4_window7_224_finetuned_v3_more_data_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cards_top_left_swin_tiny_patch4_window7_224_finetuned_v3_more_data_pipeline` is a English model originally trained by sai17.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cards_top_left_swin_tiny_patch4_window7_224_finetuned_v3_more_data_pipeline_en_5.5.1_3.0_1737694478140.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cards_top_left_swin_tiny_patch4_window7_224_finetuned_v3_more_data_pipeline_en_5.5.1_3.0_1737694478140.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("cards_top_left_swin_tiny_patch4_window7_224_finetuned_v3_more_data_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cards_top_left_swin_tiny_patch4_window7_224_finetuned_v3_more_data_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cards_top_left_swin_tiny_patch4_window7_224_finetuned_v3_more_data_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/sai17/cards-top_left_swin-tiny-patch4-window7-224-finetuned-v3_more_data
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-cat_sayula_popoluca_iw_4_en.md b/docs/_posts/ahmedlone127/2025-01-24-cat_sayula_popoluca_iw_4_en.md
new file mode 100644
index 00000000000000..3f9f33a80a0647
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-cat_sayula_popoluca_iw_4_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English cat_sayula_popoluca_iw_4 XlmRoBertaForTokenClassification from homersimpson
+author: John Snow Labs
+name: cat_sayula_popoluca_iw_4
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cat_sayula_popoluca_iw_4` is a English model originally trained by homersimpson.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cat_sayula_popoluca_iw_4_en_5.5.1_3.0_1737677653423.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cat_sayula_popoluca_iw_4_en_5.5.1_3.0_1737677653423.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("cat_sayula_popoluca_iw_4","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("cat_sayula_popoluca_iw_4", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cat_sayula_popoluca_iw_4|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|424.4 MB|
+
+## References
+
+https://huggingface.co/homersimpson/cat-pos-iw-4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-cat_sayula_popoluca_iw_4_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-cat_sayula_popoluca_iw_4_pipeline_en.md
new file mode 100644
index 00000000000000..89d3e5d3023cd5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-cat_sayula_popoluca_iw_4_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English cat_sayula_popoluca_iw_4_pipeline pipeline XlmRoBertaForTokenClassification from homersimpson
+author: John Snow Labs
+name: cat_sayula_popoluca_iw_4_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cat_sayula_popoluca_iw_4_pipeline` is a English model originally trained by homersimpson.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cat_sayula_popoluca_iw_4_pipeline_en_5.5.1_3.0_1737677683411.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cat_sayula_popoluca_iw_4_pipeline_en_5.5.1_3.0_1737677683411.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("cat_sayula_popoluca_iw_4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cat_sayula_popoluca_iw_4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cat_sayula_popoluca_iw_4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|424.4 MB|
+
+## References
+
+https://huggingface.co/homersimpson/cat-pos-iw-4
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-cat_sayula_popoluca_spanish_en.md b/docs/_posts/ahmedlone127/2025-01-24-cat_sayula_popoluca_spanish_en.md
new file mode 100644
index 00000000000000..0f4e3c26a48b81
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-cat_sayula_popoluca_spanish_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English cat_sayula_popoluca_spanish RoBertaForTokenClassification from homersimpson
+author: John Snow Labs
+name: cat_sayula_popoluca_spanish
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cat_sayula_popoluca_spanish` is a English model originally trained by homersimpson.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cat_sayula_popoluca_spanish_en_5.5.1_3.0_1737703368669.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cat_sayula_popoluca_spanish_en_5.5.1_3.0_1737703368669.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("cat_sayula_popoluca_spanish","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("cat_sayula_popoluca_spanish", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cat_sayula_popoluca_spanish|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|462.3 MB|
+
+## References
+
+https://huggingface.co/homersimpson/cat-pos-es
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-cat_sayula_popoluca_spanish_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-cat_sayula_popoluca_spanish_pipeline_en.md
new file mode 100644
index 00000000000000..4cb7dbef5c20c3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-cat_sayula_popoluca_spanish_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English cat_sayula_popoluca_spanish_pipeline pipeline RoBertaForTokenClassification from homersimpson
+author: John Snow Labs
+name: cat_sayula_popoluca_spanish_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cat_sayula_popoluca_spanish_pipeline` is a English model originally trained by homersimpson.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cat_sayula_popoluca_spanish_pipeline_en_5.5.1_3.0_1737703393408.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cat_sayula_popoluca_spanish_pipeline_en_5.5.1_3.0_1737703393408.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("cat_sayula_popoluca_spanish_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cat_sayula_popoluca_spanish_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cat_sayula_popoluca_spanish_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|462.3 MB|
+
+## References
+
+https://huggingface.co/homersimpson/cat-pos-es
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-cerebras_gpt_256m_en.md b/docs/_posts/ahmedlone127/2025-01-24-cerebras_gpt_256m_en.md
new file mode 100644
index 00000000000000..f3c29037569fb7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-cerebras_gpt_256m_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English cerebras_gpt_256m GPT2Transformer from cerebras
+author: John Snow Labs
+name: cerebras_gpt_256m
+date: 2025-01-24
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cerebras_gpt_256m` is a English model originally trained by cerebras.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cerebras_gpt_256m_en_5.5.1_3.0_1737718087550.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cerebras_gpt_256m_en_5.5.1_3.0_1737718087550.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("cerebras_gpt_256m","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("cerebras_gpt_256m","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cerebras_gpt_256m|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|960.6 MB|
+
+## References
+
+https://huggingface.co/cerebras/Cerebras-GPT-256M
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-cerebras_gpt_256m_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-cerebras_gpt_256m_pipeline_en.md
new file mode 100644
index 00000000000000..d80381a8e51292
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-cerebras_gpt_256m_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English cerebras_gpt_256m_pipeline pipeline GPT2Transformer from cerebras
+author: John Snow Labs
+name: cerebras_gpt_256m_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cerebras_gpt_256m_pipeline` is a English model originally trained by cerebras.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cerebras_gpt_256m_pipeline_en_5.5.1_3.0_1737718137240.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cerebras_gpt_256m_pipeline_en_5.5.1_3.0_1737718137240.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("cerebras_gpt_256m_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cerebras_gpt_256m_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cerebras_gpt_256m_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|960.6 MB|
+
+## References
+
+https://huggingface.co/cerebras/Cerebras-GPT-256M
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-code_search_codebert_base_2_random_trimmed_with_g_and_spaces_en.md b/docs/_posts/ahmedlone127/2025-01-24-code_search_codebert_base_2_random_trimmed_with_g_and_spaces_en.md
new file mode 100644
index 00000000000000..fe610e0f77b379
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-code_search_codebert_base_2_random_trimmed_with_g_and_spaces_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English code_search_codebert_base_2_random_trimmed_with_g_and_spaces RoBertaForTokenClassification from DianaIulia
+author: John Snow Labs
+name: code_search_codebert_base_2_random_trimmed_with_g_and_spaces
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`code_search_codebert_base_2_random_trimmed_with_g_and_spaces` is a English model originally trained by DianaIulia.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/code_search_codebert_base_2_random_trimmed_with_g_and_spaces_en_5.5.1_3.0_1737686916909.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/code_search_codebert_base_2_random_trimmed_with_g_and_spaces_en_5.5.1_3.0_1737686916909.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("code_search_codebert_base_2_random_trimmed_with_g_and_spaces","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("code_search_codebert_base_2_random_trimmed_with_g_and_spaces", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|code_search_codebert_base_2_random_trimmed_with_g_and_spaces|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|466.1 MB|
+
+## References
+
+https://huggingface.co/DianaIulia/code_search_codebert_base_2_random_trimmed_with_g_and_spaces
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-code_search_codebert_base_2_random_trimmed_with_g_and_spaces_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-code_search_codebert_base_2_random_trimmed_with_g_and_spaces_pipeline_en.md
new file mode 100644
index 00000000000000..65f8c2f1550e02
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-code_search_codebert_base_2_random_trimmed_with_g_and_spaces_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English code_search_codebert_base_2_random_trimmed_with_g_and_spaces_pipeline pipeline RoBertaForTokenClassification from DianaIulia
+author: John Snow Labs
+name: code_search_codebert_base_2_random_trimmed_with_g_and_spaces_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`code_search_codebert_base_2_random_trimmed_with_g_and_spaces_pipeline` is a English model originally trained by DianaIulia.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/code_search_codebert_base_2_random_trimmed_with_g_and_spaces_pipeline_en_5.5.1_3.0_1737686941633.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/code_search_codebert_base_2_random_trimmed_with_g_and_spaces_pipeline_en_5.5.1_3.0_1737686941633.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("code_search_codebert_base_2_random_trimmed_with_g_and_spaces_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("code_search_codebert_base_2_random_trimmed_with_g_and_spaces_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|code_search_codebert_base_2_random_trimmed_with_g_and_spaces_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.2 MB|
+
+## References
+
+https://huggingface.co/DianaIulia/code_search_codebert_base_2_random_trimmed_with_g_and_spaces
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-code_search_codebert_base_3_en.md b/docs/_posts/ahmedlone127/2025-01-24-code_search_codebert_base_3_en.md
new file mode 100644
index 00000000000000..aaf467969bfadf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-code_search_codebert_base_3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English code_search_codebert_base_3 RoBertaForTokenClassification from DianaIulia
+author: John Snow Labs
+name: code_search_codebert_base_3
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`code_search_codebert_base_3` is a English model originally trained by DianaIulia.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/code_search_codebert_base_3_en_5.5.1_3.0_1737702244730.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/code_search_codebert_base_3_en_5.5.1_3.0_1737702244730.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("code_search_codebert_base_3","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("code_search_codebert_base_3", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|code_search_codebert_base_3|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|466.1 MB|
+
+## References
+
+https://huggingface.co/DianaIulia/code_search_codebert_base_3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-code_search_codebert_base_3_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-code_search_codebert_base_3_pipeline_en.md
new file mode 100644
index 00000000000000..a94fde29cf1320
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-code_search_codebert_base_3_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English code_search_codebert_base_3_pipeline pipeline RoBertaForTokenClassification from DianaIulia
+author: John Snow Labs
+name: code_search_codebert_base_3_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`code_search_codebert_base_3_pipeline` is a English model originally trained by DianaIulia.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/code_search_codebert_base_3_pipeline_en_5.5.1_3.0_1737702272337.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/code_search_codebert_base_3_pipeline_en_5.5.1_3.0_1737702272337.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("code_search_codebert_base_3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("code_search_codebert_base_3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|code_search_codebert_base_3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.1 MB|
+
+## References
+
+https://huggingface.co/DianaIulia/code_search_codebert_base_3
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-code_search_codebert_base_4_en.md b/docs/_posts/ahmedlone127/2025-01-24-code_search_codebert_base_4_en.md
new file mode 100644
index 00000000000000..d29ac13507bf91
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-code_search_codebert_base_4_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English code_search_codebert_base_4 RoBertaForTokenClassification from DianaIulia
+author: John Snow Labs
+name: code_search_codebert_base_4
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`code_search_codebert_base_4` is a English model originally trained by DianaIulia.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/code_search_codebert_base_4_en_5.5.1_3.0_1737755673322.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/code_search_codebert_base_4_en_5.5.1_3.0_1737755673322.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("code_search_codebert_base_4","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("code_search_codebert_base_4", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|code_search_codebert_base_4|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|466.1 MB|
+
+## References
+
+https://huggingface.co/DianaIulia/code_search_codebert_base_4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-code_search_codebert_base_4_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-code_search_codebert_base_4_pipeline_en.md
new file mode 100644
index 00000000000000..447d5e8cf02691
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-code_search_codebert_base_4_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English code_search_codebert_base_4_pipeline pipeline RoBertaForTokenClassification from DianaIulia
+author: John Snow Labs
+name: code_search_codebert_base_4_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`code_search_codebert_base_4_pipeline` is a English model originally trained by DianaIulia.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/code_search_codebert_base_4_pipeline_en_5.5.1_3.0_1737755699049.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/code_search_codebert_base_4_pipeline_en_5.5.1_3.0_1737755699049.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("code_search_codebert_base_4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("code_search_codebert_base_4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|code_search_codebert_base_4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.1 MB|
+
+## References
+
+https://huggingface.co/DianaIulia/code_search_codebert_base_4
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-code_search_trained_base_random_trimmed_with_g_en.md b/docs/_posts/ahmedlone127/2025-01-24-code_search_trained_base_random_trimmed_with_g_en.md
new file mode 100644
index 00000000000000..31f1ce3350bd9a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-code_search_trained_base_random_trimmed_with_g_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English code_search_trained_base_random_trimmed_with_g RoBertaForTokenClassification from DianaIulia
+author: John Snow Labs
+name: code_search_trained_base_random_trimmed_with_g
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`code_search_trained_base_random_trimmed_with_g` is a English model originally trained by DianaIulia.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/code_search_trained_base_random_trimmed_with_g_en_5.5.1_3.0_1737703055368.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/code_search_trained_base_random_trimmed_with_g_en_5.5.1_3.0_1737703055368.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("code_search_trained_base_random_trimmed_with_g","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("code_search_trained_base_random_trimmed_with_g", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|code_search_trained_base_random_trimmed_with_g|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|466.1 MB|
+
+## References
+
+https://huggingface.co/DianaIulia/code_search_trained_base_random_trimmed_with_g
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-code_search_trained_base_random_trimmed_with_g_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-code_search_trained_base_random_trimmed_with_g_pipeline_en.md
new file mode 100644
index 00000000000000..add63daaeeef9d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-code_search_trained_base_random_trimmed_with_g_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English code_search_trained_base_random_trimmed_with_g_pipeline pipeline RoBertaForTokenClassification from DianaIulia
+author: John Snow Labs
+name: code_search_trained_base_random_trimmed_with_g_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`code_search_trained_base_random_trimmed_with_g_pipeline` is a English model originally trained by DianaIulia.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/code_search_trained_base_random_trimmed_with_g_pipeline_en_5.5.1_3.0_1737703079223.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/code_search_trained_base_random_trimmed_with_g_pipeline_en_5.5.1_3.0_1737703079223.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("code_search_trained_base_random_trimmed_with_g_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("code_search_trained_base_random_trimmed_with_g_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|code_search_trained_base_random_trimmed_with_g_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.1 MB|
+
+## References
+
+https://huggingface.co/DianaIulia/code_search_trained_base_random_trimmed_with_g
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-conflibert_satp_binary_classification_en.md b/docs/_posts/ahmedlone127/2025-01-24-conflibert_satp_binary_classification_en.md
new file mode 100644
index 00000000000000..306c3a09eb788d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-conflibert_satp_binary_classification_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English conflibert_satp_binary_classification BertForTokenClassification from eventdata-utd
+author: John Snow Labs
+name: conflibert_satp_binary_classification
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`conflibert_satp_binary_classification` is a English model originally trained by eventdata-utd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/conflibert_satp_binary_classification_en_5.5.1_3.0_1737719722147.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/conflibert_satp_binary_classification_en_5.5.1_3.0_1737719722147.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("conflibert_satp_binary_classification","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("conflibert_satp_binary_classification", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|conflibert_satp_binary_classification|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|406.0 MB|
+
+## References
+
+https://huggingface.co/eventdata-utd/conflibert-satp-binary-classification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-conflibert_satp_binary_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-conflibert_satp_binary_classification_pipeline_en.md
new file mode 100644
index 00000000000000..a9729b15ef9a7c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-conflibert_satp_binary_classification_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English conflibert_satp_binary_classification_pipeline pipeline BertForTokenClassification from eventdata-utd
+author: John Snow Labs
+name: conflibert_satp_binary_classification_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`conflibert_satp_binary_classification_pipeline` is a English model originally trained by eventdata-utd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/conflibert_satp_binary_classification_pipeline_en_5.5.1_3.0_1737719747245.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/conflibert_satp_binary_classification_pipeline_en_5.5.1_3.0_1737719747245.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("conflibert_satp_binary_classification_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("conflibert_satp_binary_classification_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|conflibert_satp_binary_classification_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.0 MB|
+
+## References
+
+https://huggingface.co/eventdata-utd/conflibert-satp-binary-classification
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-conll_en.md b/docs/_posts/ahmedlone127/2025-01-24-conll_en.md
new file mode 100644
index 00000000000000..82963f1a8afabb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-conll_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English conll DistilBertForTokenClassification from smoeina
+author: John Snow Labs
+name: conll
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`conll` is a English model originally trained by smoeina.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/conll_en_5.5.1_3.0_1737692497747.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/conll_en_5.5.1_3.0_1737692497747.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("conll","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("conll", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|conll|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/smoeina/CoNLL
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-conll_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-conll_pipeline_en.md
new file mode 100644
index 00000000000000..c98bc7fea00568
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-conll_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English conll_pipeline pipeline DistilBertForTokenClassification from smoeina
+author: John Snow Labs
+name: conll_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`conll_pipeline` is a English model originally trained by smoeina.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/conll_pipeline_en_5.5.1_3.0_1737692518800.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/conll_pipeline_en_5.5.1_3.0_1737692518800.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("conll_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("conll_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|conll_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/smoeina/CoNLL
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-conversational_spanish_gpt_es.md b/docs/_posts/ahmedlone127/2025-01-24-conversational_spanish_gpt_es.md
new file mode 100644
index 00000000000000..02ec42a02d8913
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-conversational_spanish_gpt_es.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Castilian, Spanish conversational_spanish_gpt GPT2Transformer from ostorc
+author: John Snow Labs
+name: conversational_spanish_gpt
+date: 2025-01-24
+tags: [es, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: es
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`conversational_spanish_gpt` is a Castilian, Spanish model originally trained by ostorc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/conversational_spanish_gpt_es_5.5.1_3.0_1737716526207.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/conversational_spanish_gpt_es_5.5.1_3.0_1737716526207.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("conversational_spanish_gpt","es") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("conversational_spanish_gpt","es") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|conversational_spanish_gpt|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|es|
+|Size:|466.8 MB|
+
+## References
+
+https://huggingface.co/ostorc/Conversational_Spanish_GPT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-conversational_spanish_gpt_pipeline_es.md b/docs/_posts/ahmedlone127/2025-01-24-conversational_spanish_gpt_pipeline_es.md
new file mode 100644
index 00000000000000..12a719a8149e05
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-conversational_spanish_gpt_pipeline_es.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Castilian, Spanish conversational_spanish_gpt_pipeline pipeline GPT2Transformer from ostorc
+author: John Snow Labs
+name: conversational_spanish_gpt_pipeline
+date: 2025-01-24
+tags: [es, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: es
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`conversational_spanish_gpt_pipeline` is a Castilian, Spanish model originally trained by ostorc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/conversational_spanish_gpt_pipeline_es_5.5.1_3.0_1737716551063.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/conversational_spanish_gpt_pipeline_es_5.5.1_3.0_1737716551063.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("conversational_spanish_gpt_pipeline", lang = "es")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("conversational_spanish_gpt_pipeline", lang = "es")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|conversational_spanish_gpt_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|es|
+|Size:|466.8 MB|
+
+## References
+
+https://huggingface.co/ostorc/Conversational_Spanish_GPT
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-cs221_deberta_v3_large_finetuned_augmentation_en.md b/docs/_posts/ahmedlone127/2025-01-24-cs221_deberta_v3_large_finetuned_augmentation_en.md
new file mode 100644
index 00000000000000..c047d1f32b6cb9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-cs221_deberta_v3_large_finetuned_augmentation_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English cs221_deberta_v3_large_finetuned_augmentation DeBertaForSequenceClassification from Kuongan
+author: John Snow Labs
+name: cs221_deberta_v3_large_finetuned_augmentation
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cs221_deberta_v3_large_finetuned_augmentation` is a English model originally trained by Kuongan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cs221_deberta_v3_large_finetuned_augmentation_en_5.5.1_3.0_1737728208618.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cs221_deberta_v3_large_finetuned_augmentation_en_5.5.1_3.0_1737728208618.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("cs221_deberta_v3_large_finetuned_augmentation","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("cs221_deberta_v3_large_finetuned_augmentation", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cs221_deberta_v3_large_finetuned_augmentation|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/Kuongan/CS221-deberta-v3-large-finetuned-augmentation
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-cs221_deberta_v3_large_finetuned_augmentation_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-cs221_deberta_v3_large_finetuned_augmentation_pipeline_en.md
new file mode 100644
index 00000000000000..ab3628f9a3ac17
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-cs221_deberta_v3_large_finetuned_augmentation_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English cs221_deberta_v3_large_finetuned_augmentation_pipeline pipeline DeBertaForSequenceClassification from Kuongan
+author: John Snow Labs
+name: cs221_deberta_v3_large_finetuned_augmentation_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cs221_deberta_v3_large_finetuned_augmentation_pipeline` is a English model originally trained by Kuongan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cs221_deberta_v3_large_finetuned_augmentation_pipeline_en_5.5.1_3.0_1737728346132.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cs221_deberta_v3_large_finetuned_augmentation_pipeline_en_5.5.1_3.0_1737728346132.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("cs221_deberta_v3_large_finetuned_augmentation_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cs221_deberta_v3_large_finetuned_augmentation_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cs221_deberta_v3_large_finetuned_augmentation_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/Kuongan/CS221-deberta-v3-large-finetuned-augmentation
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-ct_001_20230813_en.md b/docs/_posts/ahmedlone127/2025-01-24-ct_001_20230813_en.md
new file mode 100644
index 00000000000000..2d59f879d56ef1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-ct_001_20230813_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English ct_001_20230813 BertForQuestionAnswering from intanm
+author: John Snow Labs
+name: ct_001_20230813
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ct_001_20230813` is a English model originally trained by intanm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ct_001_20230813_en_5.5.1_3.0_1737747626705.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ct_001_20230813_en_5.5.1_3.0_1737747626705.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("ct_001_20230813","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("ct_001_20230813", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ct_001_20230813|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/intanm/ct-001-20230813
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-ct_001_20230813_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-ct_001_20230813_pipeline_en.md
new file mode 100644
index 00000000000000..9528dd164ded56
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-ct_001_20230813_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English ct_001_20230813_pipeline pipeline BertForQuestionAnswering from intanm
+author: John Snow Labs
+name: ct_001_20230813_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ct_001_20230813_pipeline` is a English model originally trained by intanm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ct_001_20230813_pipeline_en_5.5.1_3.0_1737747663134.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ct_001_20230813_pipeline_en_5.5.1_3.0_1737747663134.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ct_001_20230813_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ct_001_20230813_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ct_001_20230813_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/intanm/ct-001-20230813
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-ct_kld_mbert_20230913_2_en.md b/docs/_posts/ahmedlone127/2025-01-24-ct_kld_mbert_20230913_2_en.md
new file mode 100644
index 00000000000000..f4d17e392f87ef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-ct_kld_mbert_20230913_2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English ct_kld_mbert_20230913_2 BertForQuestionAnswering from intanm
+author: John Snow Labs
+name: ct_kld_mbert_20230913_2
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ct_kld_mbert_20230913_2` is a English model originally trained by intanm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ct_kld_mbert_20230913_2_en_5.5.1_3.0_1737751311225.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ct_kld_mbert_20230913_2_en_5.5.1_3.0_1737751311225.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("ct_kld_mbert_20230913_2","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("ct_kld_mbert_20230913_2", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ct_kld_mbert_20230913_2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/intanm/ct-kld-mbert-20230913-2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-ct_kld_mbert_20230913_2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-ct_kld_mbert_20230913_2_pipeline_en.md
new file mode 100644
index 00000000000000..ebffda4fb62336
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-ct_kld_mbert_20230913_2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English ct_kld_mbert_20230913_2_pipeline pipeline BertForQuestionAnswering from intanm
+author: John Snow Labs
+name: ct_kld_mbert_20230913_2_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ct_kld_mbert_20230913_2_pipeline` is a English model originally trained by intanm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ct_kld_mbert_20230913_2_pipeline_en_5.5.1_3.0_1737751347376.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ct_kld_mbert_20230913_2_pipeline_en_5.5.1_3.0_1737751347376.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ct_kld_mbert_20230913_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ct_kld_mbert_20230913_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ct_kld_mbert_20230913_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/intanm/ct-kld-mbert-20230913-2
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-ct_mse_mbert_20230814_en.md b/docs/_posts/ahmedlone127/2025-01-24-ct_mse_mbert_20230814_en.md
new file mode 100644
index 00000000000000..8ef010e0dbe31a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-ct_mse_mbert_20230814_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English ct_mse_mbert_20230814 BertForQuestionAnswering from intanm
+author: John Snow Labs
+name: ct_mse_mbert_20230814
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ct_mse_mbert_20230814` is a English model originally trained by intanm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ct_mse_mbert_20230814_en_5.5.1_3.0_1737750879219.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ct_mse_mbert_20230814_en_5.5.1_3.0_1737750879219.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("ct_mse_mbert_20230814","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("ct_mse_mbert_20230814", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ct_mse_mbert_20230814|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/intanm/ct-mse-mbert-20230814
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-ct_mse_mbert_20230814_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-ct_mse_mbert_20230814_pipeline_en.md
new file mode 100644
index 00000000000000..6b0e5ed0065f4c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-ct_mse_mbert_20230814_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English ct_mse_mbert_20230814_pipeline pipeline BertForQuestionAnswering from intanm
+author: John Snow Labs
+name: ct_mse_mbert_20230814_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ct_mse_mbert_20230814_pipeline` is a English model originally trained by intanm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ct_mse_mbert_20230814_pipeline_en_5.5.1_3.0_1737750913531.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ct_mse_mbert_20230814_pipeline_en_5.5.1_3.0_1737750913531.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ct_mse_mbert_20230814_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ct_mse_mbert_20230814_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ct_mse_mbert_20230814_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/intanm/ct-mse-mbert-20230814
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-cybert_attacker_en.md b/docs/_posts/ahmedlone127/2025-01-24-cybert_attacker_en.md
new file mode 100644
index 00000000000000..9881bc4939d7f5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-cybert_attacker_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English cybert_attacker RoBertaForTokenClassification from Cyber-ThreaD
+author: John Snow Labs
+name: cybert_attacker
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cybert_attacker` is a English model originally trained by Cyber-ThreaD.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cybert_attacker_en_5.5.1_3.0_1737685716654.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cybert_attacker_en_5.5.1_3.0_1737685716654.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("cybert_attacker","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("cybert_attacker", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cybert_attacker|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|311.4 MB|
+
+## References
+
+https://huggingface.co/Cyber-ThreaD/CyBERT-AttackER
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-cybert_attacker_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-cybert_attacker_pipeline_en.md
new file mode 100644
index 00000000000000..80e3a0bf30e931
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-cybert_attacker_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English cybert_attacker_pipeline pipeline RoBertaForTokenClassification from Cyber-ThreaD
+author: John Snow Labs
+name: cybert_attacker_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cybert_attacker_pipeline` is a English model originally trained by Cyber-ThreaD.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cybert_attacker_pipeline_en_5.5.1_3.0_1737685733503.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cybert_attacker_pipeline_en_5.5.1_3.0_1737685733503.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("cybert_attacker_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cybert_attacker_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cybert_attacker_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|311.4 MB|
+
+## References
+
+https://huggingface.co/Cyber-ThreaD/CyBERT-AttackER
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-czegpt_2_cs.md b/docs/_posts/ahmedlone127/2025-01-24-czegpt_2_cs.md
new file mode 100644
index 00000000000000..b6332bfc349075
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-czegpt_2_cs.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Czech czegpt_2 GPT2Transformer from MU-NLPC
+author: John Snow Labs
+name: czegpt_2
+date: 2025-01-24
+tags: [cs, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: cs
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`czegpt_2` is a Czech model originally trained by MU-NLPC.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/czegpt_2_cs_5.5.1_3.0_1737731918853.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/czegpt_2_cs_5.5.1_3.0_1737731918853.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("czegpt_2","cs") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("czegpt_2","cs") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|czegpt_2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|cs|
+|Size:|299.1 MB|
+
+## References
+
+https://huggingface.co/MU-NLPC/CzeGPT-2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-czegpt_2_pipeline_cs.md b/docs/_posts/ahmedlone127/2025-01-24-czegpt_2_pipeline_cs.md
new file mode 100644
index 00000000000000..0e9810c8a23132
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-czegpt_2_pipeline_cs.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Czech czegpt_2_pipeline pipeline GPT2Transformer from MU-NLPC
+author: John Snow Labs
+name: czegpt_2_pipeline
+date: 2025-01-24
+tags: [cs, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: cs
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`czegpt_2_pipeline` is a Czech model originally trained by MU-NLPC.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/czegpt_2_pipeline_cs_5.5.1_3.0_1737732005591.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/czegpt_2_pipeline_cs_5.5.1_3.0_1737732005591.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("czegpt_2_pipeline", lang = "cs")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("czegpt_2_pipeline", lang = "cs")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|czegpt_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|cs|
+|Size:|299.1 MB|
+
+## References
+
+https://huggingface.co/MU-NLPC/CzeGPT-2
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-danskbert_2_nd_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-danskbert_2_nd_pipeline_en.md
new file mode 100644
index 00000000000000..ada40c72586717
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-danskbert_2_nd_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English danskbert_2_nd_pipeline pipeline XlmRoBertaForSequenceClassification from yemen2016
+author: John Snow Labs
+name: danskbert_2_nd_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`danskbert_2_nd_pipeline` is a English model originally trained by yemen2016.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/danskbert_2_nd_pipeline_en_5.5.1_3.0_1737713238951.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/danskbert_2_nd_pipeline_en_5.5.1_3.0_1737713238951.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("danskbert_2_nd_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("danskbert_2_nd_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|danskbert_2_nd_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|424.8 MB|
+
+## References
+
+https://huggingface.co/yemen2016/danskbert_2_ND
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-deberta_v3_xsmall_tasksource_nli_en.md b/docs/_posts/ahmedlone127/2025-01-24-deberta_v3_xsmall_tasksource_nli_en.md
new file mode 100644
index 00000000000000..2bc8fb06baa0c4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-deberta_v3_xsmall_tasksource_nli_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_xsmall_tasksource_nli DeBertaForZeroShotClassification from sileod
+author: John Snow Labs
+name: deberta_v3_xsmall_tasksource_nli
+date: 2025-01-24
+tags: [en, open_source, onnx, zero_shot, deberta]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_xsmall_tasksource_nli` is a English model originally trained by sileod.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_tasksource_nli_en_5.5.1_3.0_1737701466647.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_tasksource_nli_en_5.5.1_3.0_1737701466647.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+zeroShotClassifier  = DeBertaForZeroShotClassification.pretrained("deberta_v3_xsmall_tasksource_nli","en") \
+     .setInputCols(["document","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, zeroShotClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val zeroShotClassifier  = DeBertaForZeroShotClassification.pretrained("deberta_v3_xsmall_tasksource_nli", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, zeroShotClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_xsmall_tasksource_nli|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|265.4 MB|
+
+## References
+
+https://huggingface.co/sileod/deberta-v3-xsmall-tasksource-nli
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-deberta_v3_xsmall_tasksource_nli_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-deberta_v3_xsmall_tasksource_nli_pipeline_en.md
new file mode 100644
index 00000000000000..d1fdbc217fc19c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-deberta_v3_xsmall_tasksource_nli_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_xsmall_tasksource_nli_pipeline pipeline DeBertaForZeroShotClassification from sileod
+author: John Snow Labs
+name: deberta_v3_xsmall_tasksource_nli_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_xsmall_tasksource_nli_pipeline` is a English model originally trained by sileod.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_tasksource_nli_pipeline_en_5.5.1_3.0_1737701481557.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_tasksource_nli_pipeline_en_5.5.1_3.0_1737701481557.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_xsmall_tasksource_nli_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_xsmall_tasksource_nli_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_xsmall_tasksource_nli_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|265.4 MB|
+
+## References
+
+https://huggingface.co/sileod/deberta-v3-xsmall-tasksource-nli
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-deepfake_vs_real_image_detection_dhruvjariwala_en.md b/docs/_posts/ahmedlone127/2025-01-24-deepfake_vs_real_image_detection_dhruvjariwala_en.md
new file mode 100644
index 00000000000000..6a9d151c6602b7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-deepfake_vs_real_image_detection_dhruvjariwala_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deepfake_vs_real_image_detection_dhruvjariwala ViTForImageClassification from DhruvJariwala
+author: John Snow Labs
+name: deepfake_vs_real_image_detection_dhruvjariwala
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deepfake_vs_real_image_detection_dhruvjariwala` is a English model originally trained by DhruvJariwala.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deepfake_vs_real_image_detection_dhruvjariwala_en_5.5.1_3.0_1737744658175.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deepfake_vs_real_image_detection_dhruvjariwala_en_5.5.1_3.0_1737744658175.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""deepfake_vs_real_image_detection_dhruvjariwala","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("deepfake_vs_real_image_detection_dhruvjariwala","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deepfake_vs_real_image_detection_dhruvjariwala|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/DhruvJariwala/deepfake_vs_real_image_detection
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-deepfake_vs_real_image_detection_dhruvjariwala_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-deepfake_vs_real_image_detection_dhruvjariwala_pipeline_en.md
new file mode 100644
index 00000000000000..1242542272a57e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-deepfake_vs_real_image_detection_dhruvjariwala_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English deepfake_vs_real_image_detection_dhruvjariwala_pipeline pipeline ViTForImageClassification from DhruvJariwala
+author: John Snow Labs
+name: deepfake_vs_real_image_detection_dhruvjariwala_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deepfake_vs_real_image_detection_dhruvjariwala_pipeline` is a English model originally trained by DhruvJariwala.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deepfake_vs_real_image_detection_dhruvjariwala_pipeline_en_5.5.1_3.0_1737744674682.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deepfake_vs_real_image_detection_dhruvjariwala_pipeline_en_5.5.1_3.0_1737744674682.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deepfake_vs_real_image_detection_dhruvjariwala_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deepfake_vs_real_image_detection_dhruvjariwala_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deepfake_vs_real_image_detection_dhruvjariwala_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/DhruvJariwala/deepfake_vs_real_image_detection
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dialoggpt_psycho8k_en.md b/docs/_posts/ahmedlone127/2025-01-24-dialoggpt_psycho8k_en.md
new file mode 100644
index 00000000000000..6818c99c81acf0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dialoggpt_psycho8k_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English dialoggpt_psycho8k GPT2Transformer from qazws345
+author: John Snow Labs
+name: dialoggpt_psycho8k
+date: 2025-01-24
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dialoggpt_psycho8k` is a English model originally trained by qazws345.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dialoggpt_psycho8k_en_5.5.1_3.0_1737733009703.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dialoggpt_psycho8k_en_5.5.1_3.0_1737733009703.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("dialoggpt_psycho8k","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("dialoggpt_psycho8k","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dialoggpt_psycho8k|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|466.8 MB|
+
+## References
+
+https://huggingface.co/qazws345/DialogGPT_Psycho8k
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dialoggpt_psycho8k_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-dialoggpt_psycho8k_pipeline_en.md
new file mode 100644
index 00000000000000..a2b27d364a14b2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dialoggpt_psycho8k_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English dialoggpt_psycho8k_pipeline pipeline GPT2Transformer from qazws345
+author: John Snow Labs
+name: dialoggpt_psycho8k_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dialoggpt_psycho8k_pipeline` is a English model originally trained by qazws345.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dialoggpt_psycho8k_pipeline_en_5.5.1_3.0_1737733034109.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dialoggpt_psycho8k_pipeline_en_5.5.1_3.0_1737733034109.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dialoggpt_psycho8k_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dialoggpt_psycho8k_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dialoggpt_psycho8k_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.9 MB|
+
+## References
+
+https://huggingface.co/qazws345/DialogGPT_Psycho8k
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dialogpt_medium_spanish_chitchat_es.md b/docs/_posts/ahmedlone127/2025-01-24-dialogpt_medium_spanish_chitchat_es.md
new file mode 100644
index 00000000000000..864c14ad697811
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dialogpt_medium_spanish_chitchat_es.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Castilian, Spanish dialogpt_medium_spanish_chitchat GPT2Transformer from ITG
+author: John Snow Labs
+name: dialogpt_medium_spanish_chitchat
+date: 2025-01-24
+tags: [es, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: es
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dialogpt_medium_spanish_chitchat` is a Castilian, Spanish model originally trained by ITG.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dialogpt_medium_spanish_chitchat_es_5.5.1_3.0_1737732522177.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dialogpt_medium_spanish_chitchat_es_5.5.1_3.0_1737732522177.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("dialogpt_medium_spanish_chitchat","es") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("dialogpt_medium_spanish_chitchat","es") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dialogpt_medium_spanish_chitchat|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|es|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/ITG/DialoGPT-medium-spanish-chitchat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dialogpt_medium_spanish_chitchat_pipeline_es.md b/docs/_posts/ahmedlone127/2025-01-24-dialogpt_medium_spanish_chitchat_pipeline_es.md
new file mode 100644
index 00000000000000..5e4ef5e56c2445
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dialogpt_medium_spanish_chitchat_pipeline_es.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Castilian, Spanish dialogpt_medium_spanish_chitchat_pipeline pipeline GPT2Transformer from ITG
+author: John Snow Labs
+name: dialogpt_medium_spanish_chitchat_pipeline
+date: 2025-01-24
+tags: [es, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: es
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dialogpt_medium_spanish_chitchat_pipeline` is a Castilian, Spanish model originally trained by ITG.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dialogpt_medium_spanish_chitchat_pipeline_es_5.5.1_3.0_1737732589843.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dialogpt_medium_spanish_chitchat_pipeline_es_5.5.1_3.0_1737732589843.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dialogpt_medium_spanish_chitchat_pipeline", lang = "es")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dialogpt_medium_spanish_chitchat_pipeline", lang = "es")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dialogpt_medium_spanish_chitchat_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|es|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/ITG/DialoGPT-medium-spanish-chitchat
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dialogpt_small_ruckussmart3_en.md b/docs/_posts/ahmedlone127/2025-01-24-dialogpt_small_ruckussmart3_en.md
new file mode 100644
index 00000000000000..26a9a5e83f7e6e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dialogpt_small_ruckussmart3_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English dialogpt_small_ruckussmart3 GPT2Transformer from botman1775
+author: John Snow Labs
+name: dialogpt_small_ruckussmart3
+date: 2025-01-24
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dialogpt_small_ruckussmart3` is a English model originally trained by botman1775.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dialogpt_small_ruckussmart3_en_5.5.1_3.0_1737718470101.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dialogpt_small_ruckussmart3_en_5.5.1_3.0_1737718470101.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("dialogpt_small_ruckussmart3","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("dialogpt_small_ruckussmart3","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dialogpt_small_ruckussmart3|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.3 MB|
+
+## References
+
+https://huggingface.co/botman1775/DialoGPT-small-ruckussmart3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dialogpt_small_ruckussmart3_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-dialogpt_small_ruckussmart3_pipeline_en.md
new file mode 100644
index 00000000000000..a6513497ad4c2b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dialogpt_small_ruckussmart3_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English dialogpt_small_ruckussmart3_pipeline pipeline GPT2Transformer from botman1775
+author: John Snow Labs
+name: dialogpt_small_ruckussmart3_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dialogpt_small_ruckussmart3_pipeline` is a English model originally trained by botman1775.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dialogpt_small_ruckussmart3_pipeline_en_5.5.1_3.0_1737718494532.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dialogpt_small_ruckussmart3_pipeline_en_5.5.1_3.0_1737718494532.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dialogpt_small_ruckussmart3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dialogpt_small_ruckussmart3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dialogpt_small_ruckussmart3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.3 MB|
+
+## References
+
+https://huggingface.co/botman1775/DialoGPT-small-ruckussmart3
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-disclaimer_finder_en.md b/docs/_posts/ahmedlone127/2025-01-24-disclaimer_finder_en.md
new file mode 100644
index 00000000000000..dd8667ed32c24d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-disclaimer_finder_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English disclaimer_finder BertForQuestionAnswering from daksh024
+author: John Snow Labs
+name: disclaimer_finder
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`disclaimer_finder` is a English model originally trained by daksh024.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/disclaimer_finder_en_5.5.1_3.0_1737691040070.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/disclaimer_finder_en_5.5.1_3.0_1737691040070.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("disclaimer_finder","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("disclaimer_finder", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|disclaimer_finder|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/daksh024/Disclaimer_finder
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-disclaimer_finder_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-disclaimer_finder_pipeline_en.md
new file mode 100644
index 00000000000000..31e2bbfd25926a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-disclaimer_finder_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English disclaimer_finder_pipeline pipeline BertForQuestionAnswering from daksh024
+author: John Snow Labs
+name: disclaimer_finder_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`disclaimer_finder_pipeline` is a English model originally trained by daksh024.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/disclaimer_finder_pipeline_en_5.5.1_3.0_1737691064320.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/disclaimer_finder_pipeline_en_5.5.1_3.0_1737691064320.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("disclaimer_finder_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("disclaimer_finder_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|disclaimer_finder_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/daksh024/Disclaimer_finder
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-distil_bert_ft_qa_model_7up_v5_en.md b/docs/_posts/ahmedlone127/2025-01-24-distil_bert_ft_qa_model_7up_v5_en.md
new file mode 100644
index 00000000000000..051d2726ad03f2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-distil_bert_ft_qa_model_7up_v5_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distil_bert_ft_qa_model_7up_v5 BertForQuestionAnswering from cadzchua
+author: John Snow Labs
+name: distil_bert_ft_qa_model_7up_v5
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distil_bert_ft_qa_model_7up_v5` is a English model originally trained by cadzchua.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distil_bert_ft_qa_model_7up_v5_en_5.5.1_3.0_1737738147614.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distil_bert_ft_qa_model_7up_v5_en_5.5.1_3.0_1737738147614.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("distil_bert_ft_qa_model_7up_v5","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("distil_bert_ft_qa_model_7up_v5", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distil_bert_ft_qa_model_7up_v5|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/cadzchua/distil-bert-ft-qa-model-7up-v5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-distil_bert_ft_qa_model_7up_v5_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-distil_bert_ft_qa_model_7up_v5_pipeline_en.md
new file mode 100644
index 00000000000000..c682da91c750aa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-distil_bert_ft_qa_model_7up_v5_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distil_bert_ft_qa_model_7up_v5_pipeline pipeline BertForQuestionAnswering from cadzchua
+author: John Snow Labs
+name: distil_bert_ft_qa_model_7up_v5_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distil_bert_ft_qa_model_7up_v5_pipeline` is a English model originally trained by cadzchua.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distil_bert_ft_qa_model_7up_v5_pipeline_en_5.5.1_3.0_1737738178287.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distil_bert_ft_qa_model_7up_v5_pipeline_en_5.5.1_3.0_1737738178287.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distil_bert_ft_qa_model_7up_v5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distil_bert_ft_qa_model_7up_v5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distil_bert_ft_qa_model_7up_v5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/cadzchua/distil-bert-ft-qa-model-7up-v5
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-distil_bert_ft_qa_model_7up_v6_en.md b/docs/_posts/ahmedlone127/2025-01-24-distil_bert_ft_qa_model_7up_v6_en.md
new file mode 100644
index 00000000000000..bd43ae42e6a632
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-distil_bert_ft_qa_model_7up_v6_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distil_bert_ft_qa_model_7up_v6 BertForQuestionAnswering from cadzchua
+author: John Snow Labs
+name: distil_bert_ft_qa_model_7up_v6
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distil_bert_ft_qa_model_7up_v6` is a English model originally trained by cadzchua.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distil_bert_ft_qa_model_7up_v6_en_5.5.1_3.0_1737691339004.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distil_bert_ft_qa_model_7up_v6_en_5.5.1_3.0_1737691339004.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("distil_bert_ft_qa_model_7up_v6","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("distil_bert_ft_qa_model_7up_v6", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distil_bert_ft_qa_model_7up_v6|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/cadzchua/distil-bert-ft-qa-model-7up-v6
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-distil_bert_ft_qa_model_7up_v6_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-distil_bert_ft_qa_model_7up_v6_pipeline_en.md
new file mode 100644
index 00000000000000..9a0b44c565e54a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-distil_bert_ft_qa_model_7up_v6_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distil_bert_ft_qa_model_7up_v6_pipeline pipeline BertForQuestionAnswering from cadzchua
+author: John Snow Labs
+name: distil_bert_ft_qa_model_7up_v6_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distil_bert_ft_qa_model_7up_v6_pipeline` is a English model originally trained by cadzchua.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distil_bert_ft_qa_model_7up_v6_pipeline_en_5.5.1_3.0_1737691363588.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distil_bert_ft_qa_model_7up_v6_pipeline_en_5.5.1_3.0_1737691363588.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distil_bert_ft_qa_model_7up_v6_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distil_bert_ft_qa_model_7up_v6_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distil_bert_ft_qa_model_7up_v6_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/cadzchua/distil-bert-ft-qa-model-7up-v6
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-distilbert_base_uncased_finetuned_imdb_ricard1406_en.md b/docs/_posts/ahmedlone127/2025-01-24-distilbert_base_uncased_finetuned_imdb_ricard1406_en.md
new file mode 100644
index 00000000000000..6439ad740bca7f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-distilbert_base_uncased_finetuned_imdb_ricard1406_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_ricard1406 DistilBertEmbeddings from ricard1406
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_ricard1406
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_ricard1406` is a English model originally trained by ricard1406.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_ricard1406_en_5.5.1_3.0_1737721298846.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_ricard1406_en_5.5.1_3.0_1737721298846.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_ricard1406","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_ricard1406","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_ricard1406|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/ricard1406/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-distilbert_base_uncased_finetuned_imdb_ricard1406_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-distilbert_base_uncased_finetuned_imdb_ricard1406_pipeline_en.md
new file mode 100644
index 00000000000000..f329320d165798
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-distilbert_base_uncased_finetuned_imdb_ricard1406_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_ricard1406_pipeline pipeline DistilBertEmbeddings from ricard1406
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_ricard1406_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_ricard1406_pipeline` is a English model originally trained by ricard1406.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_ricard1406_pipeline_en_5.5.1_3.0_1737721314100.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_ricard1406_pipeline_en_5.5.1_3.0_1737721314100.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_ricard1406_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_ricard1406_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_ricard1406_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/ricard1406/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-distilbert_base_uncased_finetuned_imdb_xonic48_en.md b/docs/_posts/ahmedlone127/2025-01-24-distilbert_base_uncased_finetuned_imdb_xonic48_en.md
new file mode 100644
index 00000000000000..db063353489406
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-distilbert_base_uncased_finetuned_imdb_xonic48_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_xonic48 DistilBertEmbeddings from xonic48
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_xonic48
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_xonic48` is a English model originally trained by xonic48.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_xonic48_en_5.5.1_3.0_1737721298737.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_xonic48_en_5.5.1_3.0_1737721298737.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_xonic48","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_xonic48","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_xonic48|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/xonic48/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-distilbert_base_uncased_finetuned_imdb_xonic48_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-distilbert_base_uncased_finetuned_imdb_xonic48_pipeline_en.md
new file mode 100644
index 00000000000000..d0d39b8b5a7750
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-distilbert_base_uncased_finetuned_imdb_xonic48_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_xonic48_pipeline pipeline DistilBertEmbeddings from xonic48
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_xonic48_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_xonic48_pipeline` is a English model originally trained by xonic48.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_xonic48_pipeline_en_5.5.1_3.0_1737721312388.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_xonic48_pipeline_en_5.5.1_3.0_1737721312388.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_xonic48_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_xonic48_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_xonic48_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/xonic48/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-distilbert_base_uncased_finetuned_squad_albertorovelli_en.md b/docs/_posts/ahmedlone127/2025-01-24-distilbert_base_uncased_finetuned_squad_albertorovelli_en.md
new file mode 100644
index 00000000000000..6edfc6448cfa2a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-distilbert_base_uncased_finetuned_squad_albertorovelli_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_albertorovelli DistilBertForQuestionAnswering from albertorovelli
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_albertorovelli
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_albertorovelli` is a English model originally trained by albertorovelli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_albertorovelli_en_5.5.1_3.0_1737741145264.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_albertorovelli_en_5.5.1_3.0_1737741145264.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_albertorovelli","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_albertorovelli", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_albertorovelli|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/albertorovelli/distilbert-base-uncased-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-distilbert_base_uncased_finetuned_squad_albertorovelli_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-distilbert_base_uncased_finetuned_squad_albertorovelli_pipeline_en.md
new file mode 100644
index 00000000000000..c753ed7513b21c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-distilbert_base_uncased_finetuned_squad_albertorovelli_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_albertorovelli_pipeline pipeline DistilBertForQuestionAnswering from albertorovelli
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_albertorovelli_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_albertorovelli_pipeline` is a English model originally trained by albertorovelli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_albertorovelli_pipeline_en_5.5.1_3.0_1737741165327.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_albertorovelli_pipeline_en_5.5.1_3.0_1737741165327.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_squad_albertorovelli_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_squad_albertorovelli_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_albertorovelli_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/albertorovelli/distilbert-base-uncased-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-distilbert_base_uncased_finetuned_squad_d5716d28_en.md b/docs/_posts/ahmedlone127/2025-01-24-distilbert_base_uncased_finetuned_squad_d5716d28_en.md
new file mode 100644
index 00000000000000..46472a3e4ef869
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-distilbert_base_uncased_finetuned_squad_d5716d28_en.md
@@ -0,0 +1,92 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_d5716d28 DistilBertEmbeddings from ysugawa
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_d5716d28
+date: 2025-01-24
+tags: [distilbert, en, open_source, fill_mask, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings  model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_d5716d28` is a English model originally trained by ysugawa.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_d5716d28_en_5.5.1_3.0_1737741247571.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_d5716d28_en_5.5.1_3.0_1737741247571.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("documents")
+    
+    
+embeddings =DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_squad_d5716d28","en") \
+            .setInputCols(["documents","token"]) \
+            .setOutputCol("embeddings")
+
+pipeline = Pipeline().setStages([document_assembler, embeddings])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val document_assembler = new DocumentAssembler()
+    .setInputCol("text") 
+    .setOutputCol("embeddings")
+    
+val embeddings = DistilBertEmbeddings 
+    .pretrained("distilbert_base_uncased_finetuned_squad_d5716d28", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("embeddings") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_d5716d28|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+References
+
+https://huggingface.co/ysugawa/distilbert-base-uncased-finetuned-squad-d5716d28
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-distilbert_base_uncased_finetuned_squad_d5716d28_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-distilbert_base_uncased_finetuned_squad_d5716d28_pipeline_en.md
new file mode 100644
index 00000000000000..e3849844759dc3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-distilbert_base_uncased_finetuned_squad_d5716d28_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_d5716d28_pipeline pipeline DistilBertForQuestionAnswering from Croneker
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_d5716d28_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_d5716d28_pipeline` is a English model originally trained by Croneker.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_d5716d28_pipeline_en_5.5.1_3.0_1737741261341.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_d5716d28_pipeline_en_5.5.1_3.0_1737741261341.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_squad_d5716d28_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_squad_d5716d28_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_d5716d28_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Croneker/distilbert-base-uncased-finetuned-squad-d5716d28
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-distilbert_base_uncased_finetuned_squad_frizmo_en.md b/docs/_posts/ahmedlone127/2025-01-24-distilbert_base_uncased_finetuned_squad_frizmo_en.md
new file mode 100644
index 00000000000000..928eff997a9ed2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-distilbert_base_uncased_finetuned_squad_frizmo_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_frizmo DistilBertForQuestionAnswering from Frizmo
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_frizmo
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_frizmo` is a English model originally trained by Frizmo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_frizmo_en_5.5.1_3.0_1737741143201.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_frizmo_en_5.5.1_3.0_1737741143201.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_frizmo","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_frizmo", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_frizmo|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Frizmo/distilbert-base-uncased-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-distilbert_base_uncased_finetuned_squad_frizmo_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-distilbert_base_uncased_finetuned_squad_frizmo_pipeline_en.md
new file mode 100644
index 00000000000000..600f0958f5875e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-distilbert_base_uncased_finetuned_squad_frizmo_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_frizmo_pipeline pipeline DistilBertForQuestionAnswering from Frizmo
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_frizmo_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_frizmo_pipeline` is a English model originally trained by Frizmo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_frizmo_pipeline_en_5.5.1_3.0_1737741156360.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_frizmo_pipeline_en_5.5.1_3.0_1737741156360.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_squad_frizmo_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_squad_frizmo_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_frizmo_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Frizmo/distilbert-base-uncased-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-distilbert_base_uncased_finetuned_squad_ram9801_en.md b/docs/_posts/ahmedlone127/2025-01-24-distilbert_base_uncased_finetuned_squad_ram9801_en.md
new file mode 100644
index 00000000000000..bb0b94bef892ce
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-distilbert_base_uncased_finetuned_squad_ram9801_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_ram9801 DistilBertForQuestionAnswering from ram9801
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_ram9801
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_ram9801` is a English model originally trained by ram9801.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_ram9801_en_5.5.1_3.0_1737741010755.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_ram9801_en_5.5.1_3.0_1737741010755.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_ram9801","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_ram9801", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_ram9801|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/ram9801/distilbert-base-uncased-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-distilbert_base_uncased_finetuned_squad_ram9801_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-distilbert_base_uncased_finetuned_squad_ram9801_pipeline_en.md
new file mode 100644
index 00000000000000..461310bec40d7e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-distilbert_base_uncased_finetuned_squad_ram9801_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_ram9801_pipeline pipeline DistilBertForQuestionAnswering from ram9801
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_ram9801_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_ram9801_pipeline` is a English model originally trained by ram9801.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_ram9801_pipeline_en_5.5.1_3.0_1737741025242.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_ram9801_pipeline_en_5.5.1_3.0_1737741025242.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_squad_ram9801_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_squad_ram9801_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_ram9801_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/ram9801/distilbert-base-uncased-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-distilbert_finetuned_squadv2_en.md b/docs/_posts/ahmedlone127/2025-01-24-distilbert_finetuned_squadv2_en.md
new file mode 100644
index 00000000000000..b49728e1db0c49
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-distilbert_finetuned_squadv2_en.md
@@ -0,0 +1,88 @@
+---
+layout: model
+title: English distilbert_finetuned_squadv2 RoBertaForQuestionAnswering from quocviethere
+author: John Snow Labs
+name: distilbert_finetuned_squadv2
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetuned_squadv2` is a English model originally trained by quocviethere.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_squadv2_en_5.5.1_3.0_1737741243033.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_squadv2_en_5.5.1_3.0_1737741243033.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("distilbert_finetuned_squadv2","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("distilbert_finetuned_squadv2", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_finetuned_squadv2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+References
+
+https://huggingface.co/quocviethere/distilbert-finetuned-squadv2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-distilbert_finetuned_squadv2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-distilbert_finetuned_squadv2_pipeline_en.md
new file mode 100644
index 00000000000000..ebecf6fc363d7e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-distilbert_finetuned_squadv2_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English distilbert_finetuned_squadv2_pipeline pipeline RoBertaForQuestionAnswering from quocviethere
+author: John Snow Labs
+name: distilbert_finetuned_squadv2_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetuned_squadv2_pipeline` is a English model originally trained by quocviethere.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_squadv2_pipeline_en_5.5.1_3.0_1737741257265.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_squadv2_pipeline_en_5.5.1_3.0_1737741257265.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("distilbert_finetuned_squadv2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("distilbert_finetuned_squadv2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_finetuned_squadv2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+References
+
+https://huggingface.co/quocviethere/distilbert-finetuned-squadv2
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-distilbert_token_classification_v3_en.md b/docs/_posts/ahmedlone127/2025-01-24-distilbert_token_classification_v3_en.md
new file mode 100644
index 00000000000000..e2e5961b888dc1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-distilbert_token_classification_v3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_token_classification_v3 DistilBertForTokenClassification from Useer923
+author: John Snow Labs
+name: distilbert_token_classification_v3
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_token_classification_v3` is a English model originally trained by Useer923.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_token_classification_v3_en_5.5.1_3.0_1737692497693.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_token_classification_v3_en_5.5.1_3.0_1737692497693.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_token_classification_v3","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_token_classification_v3", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_token_classification_v3|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Useer923/distilbert-token-classification-v3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-distilbert_token_classification_v3_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-distilbert_token_classification_v3_pipeline_en.md
new file mode 100644
index 00000000000000..f2630627d8f026
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-distilbert_token_classification_v3_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_token_classification_v3_pipeline pipeline DistilBertForTokenClassification from Useer923
+author: John Snow Labs
+name: distilbert_token_classification_v3_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_token_classification_v3_pipeline` is a English model originally trained by Useer923.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_token_classification_v3_pipeline_en_5.5.1_3.0_1737692517255.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_token_classification_v3_pipeline_en_5.5.1_3.0_1737692517255.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_token_classification_v3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_token_classification_v3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_token_classification_v3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Useer923/distilbert-token-classification-v3
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-distilgpt2_finetuned_cybersecurity_en.md b/docs/_posts/ahmedlone127/2025-01-24-distilgpt2_finetuned_cybersecurity_en.md
new file mode 100644
index 00000000000000..8342a82662d97b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-distilgpt2_finetuned_cybersecurity_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilgpt2_finetuned_cybersecurity GPT2Transformer from Miti-H
+author: John Snow Labs
+name: distilgpt2_finetuned_cybersecurity
+date: 2025-01-24
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilgpt2_finetuned_cybersecurity` is a English model originally trained by Miti-H.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilgpt2_finetuned_cybersecurity_en_5.5.1_3.0_1737732409030.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilgpt2_finetuned_cybersecurity_en_5.5.1_3.0_1737732409030.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("distilgpt2_finetuned_cybersecurity","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("distilgpt2_finetuned_cybersecurity","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilgpt2_finetuned_cybersecurity|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|308.4 MB|
+
+## References
+
+https://huggingface.co/Miti-H/distilgpt2-finetuned-Cybersecurity
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-distilgpt2_finetuned_cybersecurity_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-distilgpt2_finetuned_cybersecurity_pipeline_en.md
new file mode 100644
index 00000000000000..06e176ec9f168b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-distilgpt2_finetuned_cybersecurity_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilgpt2_finetuned_cybersecurity_pipeline pipeline GPT2Transformer from Miti-H
+author: John Snow Labs
+name: distilgpt2_finetuned_cybersecurity_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilgpt2_finetuned_cybersecurity_pipeline` is a English model originally trained by Miti-H.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilgpt2_finetuned_cybersecurity_pipeline_en_5.5.1_3.0_1737732426200.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilgpt2_finetuned_cybersecurity_pipeline_en_5.5.1_3.0_1737732426200.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilgpt2_finetuned_cybersecurity_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilgpt2_finetuned_cybersecurity_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilgpt2_finetuned_cybersecurity_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|308.4 MB|
+
+## References
+
+https://huggingface.co/Miti-H/distilgpt2-finetuned-Cybersecurity
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-distilgpt2_finetuned_wikitext2_agu_en.md b/docs/_posts/ahmedlone127/2025-01-24-distilgpt2_finetuned_wikitext2_agu_en.md
new file mode 100644
index 00000000000000..48865f9171f8bc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-distilgpt2_finetuned_wikitext2_agu_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilgpt2_finetuned_wikitext2_agu GPT2Transformer from arminmehrabian
+author: John Snow Labs
+name: distilgpt2_finetuned_wikitext2_agu
+date: 2025-01-24
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilgpt2_finetuned_wikitext2_agu` is a English model originally trained by arminmehrabian.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilgpt2_finetuned_wikitext2_agu_en_5.5.1_3.0_1737718947748.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilgpt2_finetuned_wikitext2_agu_en_5.5.1_3.0_1737718947748.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("distilgpt2_finetuned_wikitext2_agu","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("distilgpt2_finetuned_wikitext2_agu","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilgpt2_finetuned_wikitext2_agu|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|308.5 MB|
+
+## References
+
+https://huggingface.co/arminmehrabian/distilgpt2-finetuned-wikitext2-agu
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-distilgpt2_finetuned_wikitext2_agu_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-distilgpt2_finetuned_wikitext2_agu_pipeline_en.md
new file mode 100644
index 00000000000000..7b4b67d81665aa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-distilgpt2_finetuned_wikitext2_agu_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilgpt2_finetuned_wikitext2_agu_pipeline pipeline GPT2Transformer from arminmehrabian
+author: John Snow Labs
+name: distilgpt2_finetuned_wikitext2_agu_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilgpt2_finetuned_wikitext2_agu_pipeline` is a English model originally trained by arminmehrabian.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilgpt2_finetuned_wikitext2_agu_pipeline_en_5.5.1_3.0_1737718964673.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilgpt2_finetuned_wikitext2_agu_pipeline_en_5.5.1_3.0_1737718964673.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilgpt2_finetuned_wikitext2_agu_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilgpt2_finetuned_wikitext2_agu_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilgpt2_finetuned_wikitext2_agu_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|308.5 MB|
+
+## References
+
+https://huggingface.co/arminmehrabian/distilgpt2-finetuned-wikitext2-agu
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dnabert_2_117m_ft_hepg2_1kbphg19_dhss_h3k27ac_10xcontrol_en.md b/docs/_posts/ahmedlone127/2025-01-24-dnabert_2_117m_ft_hepg2_1kbphg19_dhss_h3k27ac_10xcontrol_en.md
new file mode 100644
index 00000000000000..1bce420ea791b5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dnabert_2_117m_ft_hepg2_1kbphg19_dhss_h3k27ac_10xcontrol_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dnabert_2_117m_ft_hepg2_1kbphg19_dhss_h3k27ac_10xcontrol BertForSequenceClassification from tanoManzo
+author: John Snow Labs
+name: dnabert_2_117m_ft_hepg2_1kbphg19_dhss_h3k27ac_10xcontrol
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dnabert_2_117m_ft_hepg2_1kbphg19_dhss_h3k27ac_10xcontrol` is a English model originally trained by tanoManzo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dnabert_2_117m_ft_hepg2_1kbphg19_dhss_h3k27ac_10xcontrol_en_5.5.1_3.0_1737710593828.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dnabert_2_117m_ft_hepg2_1kbphg19_dhss_h3k27ac_10xcontrol_en_5.5.1_3.0_1737710593828.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("dnabert_2_117m_ft_hepg2_1kbphg19_dhss_h3k27ac_10xcontrol","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("dnabert_2_117m_ft_hepg2_1kbphg19_dhss_h3k27ac_10xcontrol", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dnabert_2_117m_ft_hepg2_1kbphg19_dhss_h3k27ac_10xcontrol|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|333.8 MB|
+
+## References
+
+https://huggingface.co/tanoManzo/DNABERT-2-117M_ft_Hepg2_1kbpHG19_DHSs_H3K27AC_10xControl
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dnabert_2_117m_ft_hepg2_1kbphg19_dhss_h3k27ac_10xcontrol_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-dnabert_2_117m_ft_hepg2_1kbphg19_dhss_h3k27ac_10xcontrol_pipeline_en.md
new file mode 100644
index 00000000000000..df9341e420f55e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dnabert_2_117m_ft_hepg2_1kbphg19_dhss_h3k27ac_10xcontrol_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dnabert_2_117m_ft_hepg2_1kbphg19_dhss_h3k27ac_10xcontrol_pipeline pipeline BertForSequenceClassification from tanoManzo
+author: John Snow Labs
+name: dnabert_2_117m_ft_hepg2_1kbphg19_dhss_h3k27ac_10xcontrol_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dnabert_2_117m_ft_hepg2_1kbphg19_dhss_h3k27ac_10xcontrol_pipeline` is a English model originally trained by tanoManzo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dnabert_2_117m_ft_hepg2_1kbphg19_dhss_h3k27ac_10xcontrol_pipeline_en_5.5.1_3.0_1737710611611.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dnabert_2_117m_ft_hepg2_1kbphg19_dhss_h3k27ac_10xcontrol_pipeline_en_5.5.1_3.0_1737710611611.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dnabert_2_117m_ft_hepg2_1kbphg19_dhss_h3k27ac_10xcontrol_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dnabert_2_117m_ft_hepg2_1kbphg19_dhss_h3k27ac_10xcontrol_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dnabert_2_117m_ft_hepg2_1kbphg19_dhss_h3k27ac_10xcontrol_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|333.8 MB|
+
+## References
+
+https://huggingface.co/tanoManzo/DNABERT-2-117M_ft_Hepg2_1kbpHG19_DHSs_H3K27AC_10xControl
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-drugimproverllm_v6_en.md b/docs/_posts/ahmedlone127/2025-01-24-drugimproverllm_v6_en.md
new file mode 100644
index 00000000000000..14395ae914f303
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-drugimproverllm_v6_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English drugimproverllm_v6 GPT2Transformer from jarod0411
+author: John Snow Labs
+name: drugimproverllm_v6
+date: 2025-01-24
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`drugimproverllm_v6` is a English model originally trained by jarod0411.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/drugimproverllm_v6_en_5.5.1_3.0_1737733872391.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/drugimproverllm_v6_en_5.5.1_3.0_1737733872391.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("drugimproverllm_v6","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("drugimproverllm_v6","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|drugimproverllm_v6|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|466.8 MB|
+
+## References
+
+https://huggingface.co/jarod0411/DrugImproverLLM_v6
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-drugimproverllm_v6_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-drugimproverllm_v6_pipeline_en.md
new file mode 100644
index 00000000000000..3c5bb4c86240c8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-drugimproverllm_v6_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English drugimproverllm_v6_pipeline pipeline GPT2Transformer from jarod0411
+author: John Snow Labs
+name: drugimproverllm_v6_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`drugimproverllm_v6_pipeline` is a English model originally trained by jarod0411.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/drugimproverllm_v6_pipeline_en_5.5.1_3.0_1737733896246.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/drugimproverllm_v6_pipeline_en_5.5.1_3.0_1737733896246.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("drugimproverllm_v6_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("drugimproverllm_v6_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|drugimproverllm_v6_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.8 MB|
+
+## References
+
+https://huggingface.co/jarod0411/DrugImproverLLM_v6
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dummy_gpt2_correct_vocab_en.md b/docs/_posts/ahmedlone127/2025-01-24-dummy_gpt2_correct_vocab_en.md
new file mode 100644
index 00000000000000..d34856ed95eca9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dummy_gpt2_correct_vocab_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English dummy_gpt2_correct_vocab GPT2Transformer from trl-internal-testing
+author: John Snow Labs
+name: dummy_gpt2_correct_vocab
+date: 2025-01-24
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_gpt2_correct_vocab` is a English model originally trained by trl-internal-testing.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_gpt2_correct_vocab_en_5.5.1_3.0_1737718876817.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_gpt2_correct_vocab_en_5.5.1_3.0_1737718876817.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("dummy_gpt2_correct_vocab","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("dummy_gpt2_correct_vocab","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_gpt2_correct_vocab|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|7.3 MB|
+
+## References
+
+https://huggingface.co/trl-internal-testing/dummy-GPT2-correct-vocab
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dummy_gpt2_correct_vocab_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-dummy_gpt2_correct_vocab_pipeline_en.md
new file mode 100644
index 00000000000000..1abfa941cd2c59
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dummy_gpt2_correct_vocab_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English dummy_gpt2_correct_vocab_pipeline pipeline GPT2Transformer from trl-internal-testing
+author: John Snow Labs
+name: dummy_gpt2_correct_vocab_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_gpt2_correct_vocab_pipeline` is a English model originally trained by trl-internal-testing.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_gpt2_correct_vocab_pipeline_en_5.5.1_3.0_1737718877610.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_gpt2_correct_vocab_pipeline_en_5.5.1_3.0_1737718877610.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_gpt2_correct_vocab_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_gpt2_correct_vocab_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_gpt2_correct_vocab_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|7.3 MB|
+
+## References
+
+https://huggingface.co/trl-internal-testing/dummy-GPT2-correct-vocab
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dummy_model_a2thompson_en.md b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_a2thompson_en.md
new file mode 100644
index 00000000000000..ab210e96f7e7b6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_a2thompson_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_a2thompson CamemBertEmbeddings from a2thompson
+author: John Snow Labs
+name: dummy_model_a2thompson
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_a2thompson` is a English model originally trained by a2thompson.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_a2thompson_en_5.5.1_3.0_1737695592773.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_a2thompson_en_5.5.1_3.0_1737695592773.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_a2thompson","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_a2thompson","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_a2thompson|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/a2thompson/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dummy_model_a2thompson_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_a2thompson_pipeline_en.md
new file mode 100644
index 00000000000000..b0c01debd3e236
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_a2thompson_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_a2thompson_pipeline pipeline CamemBertEmbeddings from a2thompson
+author: John Snow Labs
+name: dummy_model_a2thompson_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_a2thompson_pipeline` is a English model originally trained by a2thompson.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_a2thompson_pipeline_en_5.5.1_3.0_1737695671194.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_a2thompson_pipeline_en_5.5.1_3.0_1737695671194.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_a2thompson_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_a2thompson_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_a2thompson_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/a2thompson/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dummy_model_ahmadtalha_en.md b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_ahmadtalha_en.md
new file mode 100644
index 00000000000000..6a2350e97099dd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_ahmadtalha_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_ahmadtalha CamemBertEmbeddings from ahmadtalha
+author: John Snow Labs
+name: dummy_model_ahmadtalha
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_ahmadtalha` is a English model originally trained by ahmadtalha.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_ahmadtalha_en_5.5.1_3.0_1737695725713.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_ahmadtalha_en_5.5.1_3.0_1737695725713.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_ahmadtalha","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_ahmadtalha","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_ahmadtalha|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/ahmadtalha/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dummy_model_ahmadtalha_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_ahmadtalha_pipeline_en.md
new file mode 100644
index 00000000000000..ed380b53563a44
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_ahmadtalha_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_ahmadtalha_pipeline pipeline CamemBertEmbeddings from ahmadtalha
+author: John Snow Labs
+name: dummy_model_ahmadtalha_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_ahmadtalha_pipeline` is a English model originally trained by ahmadtalha.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_ahmadtalha_pipeline_en_5.5.1_3.0_1737695804394.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_ahmadtalha_pipeline_en_5.5.1_3.0_1737695804394.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_ahmadtalha_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_ahmadtalha_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_ahmadtalha_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/ahmadtalha/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dummy_model_croneker_en.md b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_croneker_en.md
new file mode 100644
index 00000000000000..ac9a2772a26eb1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_croneker_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_croneker CamemBertEmbeddings from Croneker
+author: John Snow Labs
+name: dummy_model_croneker
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_croneker` is a English model originally trained by Croneker.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_croneker_en_5.5.1_3.0_1737695437591.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_croneker_en_5.5.1_3.0_1737695437591.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_croneker","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_croneker","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_croneker|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/Croneker/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dummy_model_croneker_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_croneker_pipeline_en.md
new file mode 100644
index 00000000000000..3aaf829a56d324
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_croneker_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_croneker_pipeline pipeline CamemBertEmbeddings from Croneker
+author: John Snow Labs
+name: dummy_model_croneker_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_croneker_pipeline` is a English model originally trained by Croneker.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_croneker_pipeline_en_5.5.1_3.0_1737695522060.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_croneker_pipeline_en_5.5.1_3.0_1737695522060.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_croneker_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_croneker_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_croneker_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/Croneker/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dummy_model_dhivyasri_en.md b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_dhivyasri_en.md
new file mode 100644
index 00000000000000..ac3827e0b78833
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_dhivyasri_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_dhivyasri CamemBertEmbeddings from Dhivyasri
+author: John Snow Labs
+name: dummy_model_dhivyasri
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_dhivyasri` is a English model originally trained by Dhivyasri.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_dhivyasri_en_5.5.1_3.0_1737695821091.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_dhivyasri_en_5.5.1_3.0_1737695821091.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_dhivyasri","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_dhivyasri","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_dhivyasri|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/Dhivyasri/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dummy_model_dhivyasri_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_dhivyasri_pipeline_en.md
new file mode 100644
index 00000000000000..329893e0d5e611
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_dhivyasri_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_dhivyasri_pipeline pipeline CamemBertEmbeddings from Dhivyasri
+author: John Snow Labs
+name: dummy_model_dhivyasri_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_dhivyasri_pipeline` is a English model originally trained by Dhivyasri.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_dhivyasri_pipeline_en_5.5.1_3.0_1737695900301.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_dhivyasri_pipeline_en_5.5.1_3.0_1737695900301.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_dhivyasri_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_dhivyasri_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_dhivyasri_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/Dhivyasri/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dummy_model_en.md b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_en.md
new file mode 100644
index 00000000000000..bde8fe31b102e7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_en.md
@@ -0,0 +1,96 @@
+---
+layout: model
+title: English dummy_model DistilBertEmbeddings from luoweijie
+author: John Snow Labs
+name: dummy_model
+date: 2025-01-24
+tags: [distilbert, en, open_source, fill_mask, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings  model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model` is a English model originally trained by luoweijie.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_en_5.5.1_3.0_1737756730222.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_en_5.5.1_3.0_1737756730222.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("documents")
+    
+    
+embeddings =DistilBertEmbeddings.pretrained("dummy_model","en") \
+            .setInputCols(["documents","token"]) \
+            .setOutputCol("embeddings")
+
+pipeline = Pipeline().setStages([document_assembler, embeddings])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val document_assembler = new DocumentAssembler()
+    .setInputCol("text") 
+    .setOutputCol("embeddings")
+    
+val embeddings = DistilBertEmbeddings 
+    .pretrained("dummy_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("embeddings") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+References
+
+References
+
+References
+
+https://huggingface.co/luoweijie/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dummy_model_fikrialnfjr_en.md b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_fikrialnfjr_en.md
new file mode 100644
index 00000000000000..5c2df396f6bb63
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_fikrialnfjr_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_fikrialnfjr CamemBertEmbeddings from fikrialnfjr
+author: John Snow Labs
+name: dummy_model_fikrialnfjr
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_fikrialnfjr` is a English model originally trained by fikrialnfjr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_fikrialnfjr_en_5.5.1_3.0_1737696717209.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_fikrialnfjr_en_5.5.1_3.0_1737696717209.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_fikrialnfjr","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_fikrialnfjr","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_fikrialnfjr|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/fikrialnfjr/dummy_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dummy_model_fikrialnfjr_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_fikrialnfjr_pipeline_en.md
new file mode 100644
index 00000000000000..8d56c0852e5cc2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_fikrialnfjr_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_fikrialnfjr_pipeline pipeline CamemBertEmbeddings from fikrialnfjr
+author: John Snow Labs
+name: dummy_model_fikrialnfjr_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_fikrialnfjr_pipeline` is a English model originally trained by fikrialnfjr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_fikrialnfjr_pipeline_en_5.5.1_3.0_1737696796078.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_fikrialnfjr_pipeline_en_5.5.1_3.0_1737696796078.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_fikrialnfjr_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_fikrialnfjr_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_fikrialnfjr_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/fikrialnfjr/dummy_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dummy_model_finn08_en.md b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_finn08_en.md
new file mode 100644
index 00000000000000..aa34a3f1e8f591
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_finn08_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_finn08 CamemBertEmbeddings from Finn08
+author: John Snow Labs
+name: dummy_model_finn08
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_finn08` is a English model originally trained by Finn08.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_finn08_en_5.5.1_3.0_1737695437454.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_finn08_en_5.5.1_3.0_1737695437454.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_finn08","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_finn08","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_finn08|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/Finn08/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dummy_model_finn08_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_finn08_pipeline_en.md
new file mode 100644
index 00000000000000..5aaaf01ab9d6d6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_finn08_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_finn08_pipeline pipeline CamemBertEmbeddings from Finn08
+author: John Snow Labs
+name: dummy_model_finn08_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_finn08_pipeline` is a English model originally trained by Finn08.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_finn08_pipeline_en_5.5.1_3.0_1737695517721.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_finn08_pipeline_en_5.5.1_3.0_1737695517721.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_finn08_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_finn08_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_finn08_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/Finn08/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dummy_model_hey_en.md b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_hey_en.md
new file mode 100644
index 00000000000000..cd5e2f1d8ab140
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_hey_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_hey CamemBertEmbeddings from sashashghome
+author: John Snow Labs
+name: dummy_model_hey
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_hey` is a English model originally trained by sashashghome.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_hey_en_5.5.1_3.0_1737696405279.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_hey_en_5.5.1_3.0_1737696405279.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_hey","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_hey","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_hey|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/sashashghome/dummy-model-hey
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dummy_model_hey_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_hey_pipeline_en.md
new file mode 100644
index 00000000000000..769065df01dd1c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_hey_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_hey_pipeline pipeline CamemBertEmbeddings from sashashghome
+author: John Snow Labs
+name: dummy_model_hey_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_hey_pipeline` is a English model originally trained by sashashghome.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_hey_pipeline_en_5.5.1_3.0_1737696483617.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_hey_pipeline_en_5.5.1_3.0_1737696483617.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_hey_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_hey_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_hey_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/sashashghome/dummy-model-hey
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dummy_model_hkodimuddana_en.md b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_hkodimuddana_en.md
new file mode 100644
index 00000000000000..8d049808925308
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_hkodimuddana_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_hkodimuddana CamemBertEmbeddings from hkodimuddana
+author: John Snow Labs
+name: dummy_model_hkodimuddana
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_hkodimuddana` is a English model originally trained by hkodimuddana.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_hkodimuddana_en_5.5.1_3.0_1737696050649.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_hkodimuddana_en_5.5.1_3.0_1737696050649.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_hkodimuddana","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_hkodimuddana","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_hkodimuddana|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/hkodimuddana/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dummy_model_hkodimuddana_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_hkodimuddana_pipeline_en.md
new file mode 100644
index 00000000000000..43263d31f7d30c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_hkodimuddana_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_hkodimuddana_pipeline pipeline CamemBertEmbeddings from hkodimuddana
+author: John Snow Labs
+name: dummy_model_hkodimuddana_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_hkodimuddana_pipeline` is a English model originally trained by hkodimuddana.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_hkodimuddana_pipeline_en_5.5.1_3.0_1737696130718.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_hkodimuddana_pipeline_en_5.5.1_3.0_1737696130718.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_hkodimuddana_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_hkodimuddana_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_hkodimuddana_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/hkodimuddana/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dummy_model_hzeroxium_en.md b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_hzeroxium_en.md
new file mode 100644
index 00000000000000..dfa45eeabaa2c8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_hzeroxium_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_hzeroxium CamemBertEmbeddings from HZeroxium
+author: John Snow Labs
+name: dummy_model_hzeroxium
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_hzeroxium` is a English model originally trained by HZeroxium.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_hzeroxium_en_5.5.1_3.0_1737695856736.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_hzeroxium_en_5.5.1_3.0_1737695856736.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_hzeroxium","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_hzeroxium","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_hzeroxium|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/HZeroxium/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dummy_model_hzeroxium_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_hzeroxium_pipeline_en.md
new file mode 100644
index 00000000000000..eaec83ff936e13
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_hzeroxium_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_hzeroxium_pipeline pipeline CamemBertEmbeddings from HZeroxium
+author: John Snow Labs
+name: dummy_model_hzeroxium_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_hzeroxium_pipeline` is a English model originally trained by HZeroxium.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_hzeroxium_pipeline_en_5.5.1_3.0_1737695936166.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_hzeroxium_pipeline_en_5.5.1_3.0_1737695936166.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_hzeroxium_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_hzeroxium_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_hzeroxium_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/HZeroxium/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dummy_model_jeremyong96_en.md b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_jeremyong96_en.md
new file mode 100644
index 00000000000000..e97b9024898ac7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_jeremyong96_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_jeremyong96 CamemBertEmbeddings from jeremyong96
+author: John Snow Labs
+name: dummy_model_jeremyong96
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_jeremyong96` is a English model originally trained by jeremyong96.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_jeremyong96_en_5.5.1_3.0_1737696399682.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_jeremyong96_en_5.5.1_3.0_1737696399682.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_jeremyong96","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_jeremyong96","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_jeremyong96|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/jeremyong96/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dummy_model_jeremyong96_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_jeremyong96_pipeline_en.md
new file mode 100644
index 00000000000000..ca2bff0046052b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_jeremyong96_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_jeremyong96_pipeline pipeline CamemBertEmbeddings from jeremyong96
+author: John Snow Labs
+name: dummy_model_jeremyong96_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_jeremyong96_pipeline` is a English model originally trained by jeremyong96.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_jeremyong96_pipeline_en_5.5.1_3.0_1737696478008.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_jeremyong96_pipeline_en_5.5.1_3.0_1737696478008.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_jeremyong96_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_jeremyong96_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_jeremyong96_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/jeremyong96/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dummy_model_jmjeon94_en.md b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_jmjeon94_en.md
new file mode 100644
index 00000000000000..be2dccf5613561
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_jmjeon94_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_jmjeon94 CamemBertEmbeddings from jmjeon94
+author: John Snow Labs
+name: dummy_model_jmjeon94
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_jmjeon94` is a English model originally trained by jmjeon94.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_jmjeon94_en_5.5.1_3.0_1737696942003.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_jmjeon94_en_5.5.1_3.0_1737696942003.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_jmjeon94","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_jmjeon94","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_jmjeon94|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/jmjeon94/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dummy_model_jmjeon94_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_jmjeon94_pipeline_en.md
new file mode 100644
index 00000000000000..e9ce96bbe7893a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_jmjeon94_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_jmjeon94_pipeline pipeline CamemBertEmbeddings from jmjeon94
+author: John Snow Labs
+name: dummy_model_jmjeon94_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_jmjeon94_pipeline` is a English model originally trained by jmjeon94.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_jmjeon94_pipeline_en_5.5.1_3.0_1737697018263.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_jmjeon94_pipeline_en_5.5.1_3.0_1737697018263.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_jmjeon94_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_jmjeon94_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_jmjeon94_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/jmjeon94/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dummy_model_justin_2024_en.md b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_justin_2024_en.md
new file mode 100644
index 00000000000000..44bc974d26842e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_justin_2024_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_justin_2024 CamemBertEmbeddings from Justin-2024
+author: John Snow Labs
+name: dummy_model_justin_2024
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_justin_2024` is a English model originally trained by Justin-2024.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_justin_2024_en_5.5.1_3.0_1737696145710.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_justin_2024_en_5.5.1_3.0_1737696145710.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_justin_2024","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_justin_2024","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_justin_2024|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/Justin-2024/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dummy_model_justin_2024_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_justin_2024_pipeline_en.md
new file mode 100644
index 00000000000000..2052e6e97ca7e5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_justin_2024_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_justin_2024_pipeline pipeline CamemBertEmbeddings from Justin-2024
+author: John Snow Labs
+name: dummy_model_justin_2024_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_justin_2024_pipeline` is a English model originally trained by Justin-2024.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_justin_2024_pipeline_en_5.5.1_3.0_1737696224785.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_justin_2024_pipeline_en_5.5.1_3.0_1737696224785.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_justin_2024_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_justin_2024_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_justin_2024_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/Justin-2024/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dummy_model_kangyuliu_en.md b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_kangyuliu_en.md
new file mode 100644
index 00000000000000..ee25b048706e92
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_kangyuliu_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_kangyuliu CamemBertEmbeddings from kangyuliu
+author: John Snow Labs
+name: dummy_model_kangyuliu
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_kangyuliu` is a English model originally trained by kangyuliu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_kangyuliu_en_5.5.1_3.0_1737695538836.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_kangyuliu_en_5.5.1_3.0_1737695538836.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_kangyuliu","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_kangyuliu","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_kangyuliu|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/kangyuliu/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dummy_model_kangyuliu_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_kangyuliu_pipeline_en.md
new file mode 100644
index 00000000000000..379dfecb9a98f0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_kangyuliu_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_kangyuliu_pipeline pipeline CamemBertEmbeddings from kangyuliu
+author: John Snow Labs
+name: dummy_model_kangyuliu_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_kangyuliu_pipeline` is a English model originally trained by kangyuliu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_kangyuliu_pipeline_en_5.5.1_3.0_1737695616478.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_kangyuliu_pipeline_en_5.5.1_3.0_1737695616478.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_kangyuliu_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_kangyuliu_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_kangyuliu_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/kangyuliu/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dummy_model_lakuna_en.md b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_lakuna_en.md
new file mode 100644
index 00000000000000..e0ac7624a35d52
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_lakuna_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_lakuna CamemBertEmbeddings from Lakuna
+author: John Snow Labs
+name: dummy_model_lakuna
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_lakuna` is a English model originally trained by Lakuna.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_lakuna_en_5.5.1_3.0_1737696286593.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_lakuna_en_5.5.1_3.0_1737696286593.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_lakuna","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_lakuna","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_lakuna|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/Lakuna/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dummy_model_lakuna_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_lakuna_pipeline_en.md
new file mode 100644
index 00000000000000..e119a029cb3cf3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_lakuna_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_lakuna_pipeline pipeline CamemBertEmbeddings from Lakuna
+author: John Snow Labs
+name: dummy_model_lakuna_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_lakuna_pipeline` is a English model originally trained by Lakuna.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_lakuna_pipeline_en_5.5.1_3.0_1737696365607.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_lakuna_pipeline_en_5.5.1_3.0_1737696365607.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_lakuna_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_lakuna_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_lakuna_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/Lakuna/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dummy_model_mrcolley_en.md b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_mrcolley_en.md
new file mode 100644
index 00000000000000..bf1ba2e89f7997
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_mrcolley_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_mrcolley CamemBertEmbeddings from mrcolley
+author: John Snow Labs
+name: dummy_model_mrcolley
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_mrcolley` is a English model originally trained by mrcolley.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_mrcolley_en_5.5.1_3.0_1737696518726.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_mrcolley_en_5.5.1_3.0_1737696518726.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_mrcolley","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_mrcolley","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_mrcolley|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/mrcolley/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dummy_model_mrcolley_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_mrcolley_pipeline_en.md
new file mode 100644
index 00000000000000..383bb38fff89c6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_mrcolley_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_mrcolley_pipeline pipeline CamemBertEmbeddings from mrcolley
+author: John Snow Labs
+name: dummy_model_mrcolley_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_mrcolley_pipeline` is a English model originally trained by mrcolley.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_mrcolley_pipeline_en_5.5.1_3.0_1737696597924.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_mrcolley_pipeline_en_5.5.1_3.0_1737696597924.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_mrcolley_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_mrcolley_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_mrcolley_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/mrcolley/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dummy_model_nkoki_en.md b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_nkoki_en.md
new file mode 100644
index 00000000000000..296ca0b0e4e557
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_nkoki_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_nkoki CamemBertEmbeddings from NKoki
+author: John Snow Labs
+name: dummy_model_nkoki
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_nkoki` is a English model originally trained by NKoki.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_nkoki_en_5.5.1_3.0_1737696639030.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_nkoki_en_5.5.1_3.0_1737696639030.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_nkoki","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_nkoki","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_nkoki|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/NKoki/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dummy_model_nkoki_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_nkoki_pipeline_en.md
new file mode 100644
index 00000000000000..1294656fbae93b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_nkoki_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_nkoki_pipeline pipeline CamemBertEmbeddings from NKoki
+author: John Snow Labs
+name: dummy_model_nkoki_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_nkoki_pipeline` is a English model originally trained by NKoki.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_nkoki_pipeline_en_5.5.1_3.0_1737696717803.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_nkoki_pipeline_en_5.5.1_3.0_1737696717803.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_nkoki_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_nkoki_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_nkoki_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/NKoki/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dummy_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_pipeline_en.md
new file mode 100644
index 00000000000000..61951b24c231f3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English dummy_model_pipeline pipeline MarianTransformer from caoyq
+author: John Snow Labs
+name: dummy_model_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_pipeline` is a English model originally trained by caoyq.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_pipeline_en_5.5.1_3.0_1737756754611.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_pipeline_en_5.5.1_3.0_1737756754611.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("dummy_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("dummy_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+References
+
+https://huggingface.co/caoyq/dummy-model
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dummy_model_princend_en.md b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_princend_en.md
new file mode 100644
index 00000000000000..5fd1260fd02b1d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_princend_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_princend CamemBertEmbeddings from princend
+author: John Snow Labs
+name: dummy_model_princend
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_princend` is a English model originally trained by princend.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_princend_en_5.5.1_3.0_1737695889960.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_princend_en_5.5.1_3.0_1737695889960.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_princend","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_princend","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_princend|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/princend/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dummy_model_princend_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_princend_pipeline_en.md
new file mode 100644
index 00000000000000..23e7f6ecc90689
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_princend_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_princend_pipeline pipeline CamemBertEmbeddings from princend
+author: John Snow Labs
+name: dummy_model_princend_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_princend_pipeline` is a English model originally trained by princend.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_princend_pipeline_en_5.5.1_3.0_1737695969020.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_princend_pipeline_en_5.5.1_3.0_1737695969020.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_princend_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_princend_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_princend_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/princend/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dummy_model_sajjadismail_en.md b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_sajjadismail_en.md
new file mode 100644
index 00000000000000..66da693a75437c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_sajjadismail_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_sajjadismail CamemBertEmbeddings from sajjadismail
+author: John Snow Labs
+name: dummy_model_sajjadismail
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_sajjadismail` is a English model originally trained by sajjadismail.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_sajjadismail_en_5.5.1_3.0_1737695900580.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_sajjadismail_en_5.5.1_3.0_1737695900580.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_sajjadismail","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_sajjadismail","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_sajjadismail|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/sajjadismail/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dummy_model_sajjadismail_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_sajjadismail_pipeline_en.md
new file mode 100644
index 00000000000000..608cb6866962fe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_sajjadismail_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_sajjadismail_pipeline pipeline CamemBertEmbeddings from sajjadismail
+author: John Snow Labs
+name: dummy_model_sajjadismail_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_sajjadismail_pipeline` is a English model originally trained by sajjadismail.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_sajjadismail_pipeline_en_5.5.1_3.0_1737695981985.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_sajjadismail_pipeline_en_5.5.1_3.0_1737695981985.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_sajjadismail_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_sajjadismail_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_sajjadismail_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/sajjadismail/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dummy_model_sashashghome_en.md b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_sashashghome_en.md
new file mode 100644
index 00000000000000..b13dda2a7074e4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_sashashghome_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_sashashghome CamemBertEmbeddings from sashashghome
+author: John Snow Labs
+name: dummy_model_sashashghome
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_sashashghome` is a English model originally trained by sashashghome.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_sashashghome_en_5.5.1_3.0_1737696841962.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_sashashghome_en_5.5.1_3.0_1737696841962.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_sashashghome","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_sashashghome","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_sashashghome|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/sashashghome/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dummy_model_sashashghome_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_sashashghome_pipeline_en.md
new file mode 100644
index 00000000000000..0fbc6bcb0e3022
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_sashashghome_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_sashashghome_pipeline pipeline CamemBertEmbeddings from sashashghome
+author: John Snow Labs
+name: dummy_model_sashashghome_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_sashashghome_pipeline` is a English model originally trained by sashashghome.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_sashashghome_pipeline_en_5.5.1_3.0_1737696924670.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_sashashghome_pipeline_en_5.5.1_3.0_1737696924670.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_sashashghome_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_sashashghome_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_sashashghome_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/sashashghome/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dummy_model_sayed99_en.md b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_sayed99_en.md
new file mode 100644
index 00000000000000..9b466f04ea4962
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_sayed99_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_sayed99 CamemBertEmbeddings from sayed99
+author: John Snow Labs
+name: dummy_model_sayed99
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_sayed99` is a English model originally trained by sayed99.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_sayed99_en_5.5.1_3.0_1737696855481.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_sayed99_en_5.5.1_3.0_1737696855481.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_sayed99","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_sayed99","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_sayed99|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/sayed99/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dummy_model_sayed99_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_sayed99_pipeline_en.md
new file mode 100644
index 00000000000000..47841ae272fa70
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_sayed99_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_sayed99_pipeline pipeline CamemBertEmbeddings from sayed99
+author: John Snow Labs
+name: dummy_model_sayed99_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_sayed99_pipeline` is a English model originally trained by sayed99.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_sayed99_pipeline_en_5.5.1_3.0_1737696933047.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_sayed99_pipeline_en_5.5.1_3.0_1737696933047.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_sayed99_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_sayed99_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_sayed99_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/sayed99/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dummy_model_thomaspurk_en.md b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_thomaspurk_en.md
new file mode 100644
index 00000000000000..7810f115da18df
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_thomaspurk_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_thomaspurk CamemBertEmbeddings from thomaspurk
+author: John Snow Labs
+name: dummy_model_thomaspurk
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_thomaspurk` is a English model originally trained by thomaspurk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_thomaspurk_en_5.5.1_3.0_1737695437412.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_thomaspurk_en_5.5.1_3.0_1737695437412.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_thomaspurk","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_thomaspurk","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_thomaspurk|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/thomaspurk/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dummy_model_thomaspurk_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_thomaspurk_pipeline_en.md
new file mode 100644
index 00000000000000..7a453789538e55
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_thomaspurk_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_thomaspurk_pipeline pipeline CamemBertEmbeddings from thomaspurk
+author: John Snow Labs
+name: dummy_model_thomaspurk_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_thomaspurk_pipeline` is a English model originally trained by thomaspurk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_thomaspurk_pipeline_en_5.5.1_3.0_1737695522124.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_thomaspurk_pipeline_en_5.5.1_3.0_1737695522124.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_thomaspurk_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_thomaspurk_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_thomaspurk_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/thomaspurk/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dummy_model_wangxuefeng_en.md b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_wangxuefeng_en.md
new file mode 100644
index 00000000000000..5753b8bf74f2f6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_wangxuefeng_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_wangxuefeng CamemBertEmbeddings from wangxuefeng
+author: John Snow Labs
+name: dummy_model_wangxuefeng
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_wangxuefeng` is a English model originally trained by wangxuefeng.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_wangxuefeng_en_5.5.1_3.0_1737696163171.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_wangxuefeng_en_5.5.1_3.0_1737696163171.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_wangxuefeng","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_wangxuefeng","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_wangxuefeng|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/wangxuefeng/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dummy_model_wangxuefeng_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_wangxuefeng_pipeline_en.md
new file mode 100644
index 00000000000000..97f84a3aef2fa1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dummy_model_wangxuefeng_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_wangxuefeng_pipeline pipeline CamemBertEmbeddings from wangxuefeng
+author: John Snow Labs
+name: dummy_model_wangxuefeng_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_wangxuefeng_pipeline` is a English model originally trained by wangxuefeng.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_wangxuefeng_pipeline_en_5.5.1_3.0_1737696243792.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_wangxuefeng_pipeline_en_5.5.1_3.0_1737696243792.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_wangxuefeng_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_wangxuefeng_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_wangxuefeng_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/wangxuefeng/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dummy_mrcolley_en.md b/docs/_posts/ahmedlone127/2025-01-24-dummy_mrcolley_en.md
new file mode 100644
index 00000000000000..f3c09a1ba7a8ed
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dummy_mrcolley_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_mrcolley CamemBertEmbeddings from mrcolley
+author: John Snow Labs
+name: dummy_mrcolley
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_mrcolley` is a English model originally trained by mrcolley.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_mrcolley_en_5.5.1_3.0_1737696570938.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_mrcolley_en_5.5.1_3.0_1737696570938.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_mrcolley","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_mrcolley","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_mrcolley|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/mrcolley/dummy
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-dummy_mrcolley_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-dummy_mrcolley_pipeline_en.md
new file mode 100644
index 00000000000000..9c652938f831b3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-dummy_mrcolley_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_mrcolley_pipeline pipeline CamemBertEmbeddings from mrcolley
+author: John Snow Labs
+name: dummy_mrcolley_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_mrcolley_pipeline` is a English model originally trained by mrcolley.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_mrcolley_pipeline_en_5.5.1_3.0_1737696649819.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_mrcolley_pipeline_en_5.5.1_3.0_1737696649819.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_mrcolley_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_mrcolley_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_mrcolley_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/mrcolley/dummy
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-durin_gpt2_medium_x343_en.md b/docs/_posts/ahmedlone127/2025-01-24-durin_gpt2_medium_x343_en.md
new file mode 100644
index 00000000000000..161c58ee68bf6c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-durin_gpt2_medium_x343_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English durin_gpt2_medium_x343 GPT2Transformer from stanford-crfm
+author: John Snow Labs
+name: durin_gpt2_medium_x343
+date: 2025-01-24
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`durin_gpt2_medium_x343` is a English model originally trained by stanford-crfm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/durin_gpt2_medium_x343_en_5.5.1_3.0_1737716877354.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/durin_gpt2_medium_x343_en_5.5.1_3.0_1737716877354.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("durin_gpt2_medium_x343","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("durin_gpt2_medium_x343","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|durin_gpt2_medium_x343|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|852.3 MB|
+
+## References
+
+https://huggingface.co/stanford-crfm/durin-gpt2-medium-x343
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-durin_gpt2_medium_x343_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-durin_gpt2_medium_x343_pipeline_en.md
new file mode 100644
index 00000000000000..76dd54ce28b35e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-durin_gpt2_medium_x343_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English durin_gpt2_medium_x343_pipeline pipeline GPT2Transformer from stanford-crfm
+author: John Snow Labs
+name: durin_gpt2_medium_x343_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`durin_gpt2_medium_x343_pipeline` is a English model originally trained by stanford-crfm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/durin_gpt2_medium_x343_pipeline_en_5.5.1_3.0_1737717120222.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/durin_gpt2_medium_x343_pipeline_en_5.5.1_3.0_1737717120222.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("durin_gpt2_medium_x343_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("durin_gpt2_medium_x343_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|durin_gpt2_medium_x343_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|852.3 MB|
+
+## References
+
+https://huggingface.co/stanford-crfm/durin-gpt2-medium-x343
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-e5_large_v2_4096_lsg_patched_en.md b/docs/_posts/ahmedlone127/2025-01-24-e5_large_v2_4096_lsg_patched_en.md
new file mode 100644
index 00000000000000..072157dd33af5a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-e5_large_v2_4096_lsg_patched_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English e5_large_v2_4096_lsg_patched E5Embeddings from guymorganb
+author: John Snow Labs
+name: e5_large_v2_4096_lsg_patched
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, e5]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: E5Embeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_large_v2_4096_lsg_patched` is a English model originally trained by guymorganb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_large_v2_4096_lsg_patched_en_5.5.1_3.0_1737700786186.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_large_v2_4096_lsg_patched_en_5.5.1_3.0_1737700786186.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = E5Embeddings.pretrained("e5_large_v2_4096_lsg_patched","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = E5Embeddings.pretrained("e5_large_v2_4096_lsg_patched","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|e5_large_v2_4096_lsg_patched|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[E5]|
+|Language:|en|
+|Size:|805.0 MB|
+
+## References
+
+https://huggingface.co/guymorganb/e5-large-v2-4096-lsg-patched
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-e5_large_v2_4096_lsg_patched_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-e5_large_v2_4096_lsg_patched_pipeline_en.md
new file mode 100644
index 00000000000000..d8026da4ce7ff4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-e5_large_v2_4096_lsg_patched_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English e5_large_v2_4096_lsg_patched_pipeline pipeline E5Embeddings from guymorganb
+author: John Snow Labs
+name: e5_large_v2_4096_lsg_patched_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_large_v2_4096_lsg_patched_pipeline` is a English model originally trained by guymorganb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_large_v2_4096_lsg_patched_pipeline_en_5.5.1_3.0_1737701023298.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_large_v2_4096_lsg_patched_pipeline_en_5.5.1_3.0_1737701023298.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("e5_large_v2_4096_lsg_patched_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("e5_large_v2_4096_lsg_patched_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|e5_large_v2_4096_lsg_patched_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|805.0 MB|
+
+## References
+
+https://huggingface.co/guymorganb/e5-large-v2-4096-lsg-patched
+
+## Included Models
+
+- DocumentAssembler
+- E5Embeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-elhberteu_nerc_eu.md b/docs/_posts/ahmedlone127/2025-01-24-elhberteu_nerc_eu.md
new file mode 100644
index 00000000000000..640d473fbaa336
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-elhberteu_nerc_eu.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Basque elhberteu_nerc BertForTokenClassification from orai-nlp
+author: John Snow Labs
+name: elhberteu_nerc
+date: 2025-01-24
+tags: [eu, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: eu
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`elhberteu_nerc` is a Basque model originally trained by orai-nlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/elhberteu_nerc_eu_5.5.1_3.0_1737720134336.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/elhberteu_nerc_eu_5.5.1_3.0_1737720134336.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("elhberteu_nerc","eu") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("elhberteu_nerc", "eu")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|elhberteu_nerc|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|eu|
+|Size:|464.7 MB|
+
+## References
+
+https://huggingface.co/orai-nlp/ElhBERTeu-nerc
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-elhberteu_nerc_pipeline_eu.md b/docs/_posts/ahmedlone127/2025-01-24-elhberteu_nerc_pipeline_eu.md
new file mode 100644
index 00000000000000..1eb2e700c97c83
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-elhberteu_nerc_pipeline_eu.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Basque elhberteu_nerc_pipeline pipeline BertForTokenClassification from orai-nlp
+author: John Snow Labs
+name: elhberteu_nerc_pipeline
+date: 2025-01-24
+tags: [eu, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: eu
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`elhberteu_nerc_pipeline` is a Basque model originally trained by orai-nlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/elhberteu_nerc_pipeline_eu_5.5.1_3.0_1737720159044.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/elhberteu_nerc_pipeline_eu_5.5.1_3.0_1737720159044.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("elhberteu_nerc_pipeline", lang = "eu")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("elhberteu_nerc_pipeline", lang = "eu")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|elhberteu_nerc_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|eu|
+|Size:|464.7 MB|
+
+## References
+
+https://huggingface.co/orai-nlp/ElhBERTeu-nerc
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-event_message_detector_en.md b/docs/_posts/ahmedlone127/2025-01-24-event_message_detector_en.md
new file mode 100644
index 00000000000000..cf986e723b9be7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-event_message_detector_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English event_message_detector XlmRoBertaForTokenClassification from oleksiydolgykh
+author: John Snow Labs
+name: event_message_detector
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`event_message_detector` is a English model originally trained by oleksiydolgykh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/event_message_detector_en_5.5.1_3.0_1737676932664.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/event_message_detector_en_5.5.1_3.0_1737676932664.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("event_message_detector","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("event_message_detector", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|event_message_detector|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|778.6 MB|
+
+## References
+
+https://huggingface.co/oleksiydolgykh/event-message-detector
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-event_message_detector_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-event_message_detector_pipeline_en.md
new file mode 100644
index 00000000000000..98c5d95182fafc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-event_message_detector_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English event_message_detector_pipeline pipeline XlmRoBertaForTokenClassification from oleksiydolgykh
+author: John Snow Labs
+name: event_message_detector_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`event_message_detector_pipeline` is a English model originally trained by oleksiydolgykh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/event_message_detector_pipeline_en_5.5.1_3.0_1737677076897.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/event_message_detector_pipeline_en_5.5.1_3.0_1737677076897.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("event_message_detector_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("event_message_detector_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|event_message_detector_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|778.6 MB|
+
+## References
+
+https://huggingface.co/oleksiydolgykh/event-message-detector
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-facial_age_image_detection_dima806_en.md b/docs/_posts/ahmedlone127/2025-01-24-facial_age_image_detection_dima806_en.md
new file mode 100644
index 00000000000000..aece673c510319
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-facial_age_image_detection_dima806_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English facial_age_image_detection_dima806 ViTForImageClassification from dima806
+author: John Snow Labs
+name: facial_age_image_detection_dima806
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`facial_age_image_detection_dima806` is a English model originally trained by dima806.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/facial_age_image_detection_dima806_en_5.5.1_3.0_1737744076822.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/facial_age_image_detection_dima806_en_5.5.1_3.0_1737744076822.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""facial_age_image_detection_dima806","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("facial_age_image_detection_dima806","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|facial_age_image_detection_dima806|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.4 MB|
+
+## References
+
+https://huggingface.co/dima806/facial_age_image_detection
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-facial_age_image_detection_dima806_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-facial_age_image_detection_dima806_pipeline_en.md
new file mode 100644
index 00000000000000..140aa236b4c3f9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-facial_age_image_detection_dima806_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English facial_age_image_detection_dima806_pipeline pipeline ViTForImageClassification from dima806
+author: John Snow Labs
+name: facial_age_image_detection_dima806_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`facial_age_image_detection_dima806_pipeline` is a English model originally trained by dima806.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/facial_age_image_detection_dima806_pipeline_en_5.5.1_3.0_1737744098564.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/facial_age_image_detection_dima806_pipeline_en_5.5.1_3.0_1737744098564.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("facial_age_image_detection_dima806_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("facial_age_image_detection_dima806_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|facial_age_image_detection_dima806_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.4 MB|
+
+## References
+
+https://huggingface.co/dima806/facial_age_image_detection
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-ffpp_raw_1fps_en.md b/docs/_posts/ahmedlone127/2025-01-24-ffpp_raw_1fps_en.md
new file mode 100644
index 00000000000000..6c29ec45d1ec19
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-ffpp_raw_1fps_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ffpp_raw_1fps SwinForImageClassification from hchcsuim
+author: John Snow Labs
+name: ffpp_raw_1fps
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ffpp_raw_1fps` is a English model originally trained by hchcsuim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ffpp_raw_1fps_en_5.5.1_3.0_1737754081467.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ffpp_raw_1fps_en_5.5.1_3.0_1737754081467.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""ffpp_raw_1fps","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("ffpp_raw_1fps","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ffpp_raw_1fps|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/hchcsuim/FFPP-Raw_1FPS
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-ffpp_raw_1fps_faces_expand_30_aligned_en.md b/docs/_posts/ahmedlone127/2025-01-24-ffpp_raw_1fps_faces_expand_30_aligned_en.md
new file mode 100644
index 00000000000000..15c7087df9eb13
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-ffpp_raw_1fps_faces_expand_30_aligned_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ffpp_raw_1fps_faces_expand_30_aligned SwinForImageClassification from hchcsuim
+author: John Snow Labs
+name: ffpp_raw_1fps_faces_expand_30_aligned
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ffpp_raw_1fps_faces_expand_30_aligned` is a English model originally trained by hchcsuim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ffpp_raw_1fps_faces_expand_30_aligned_en_5.5.1_3.0_1737693950830.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ffpp_raw_1fps_faces_expand_30_aligned_en_5.5.1_3.0_1737693950830.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""ffpp_raw_1fps_faces_expand_30_aligned","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("ffpp_raw_1fps_faces_expand_30_aligned","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ffpp_raw_1fps_faces_expand_30_aligned|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/hchcsuim/FFPP-Raw_1FPS_faces-expand-30-aligned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-ffpp_raw_1fps_faces_expand_30_aligned_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-ffpp_raw_1fps_faces_expand_30_aligned_pipeline_en.md
new file mode 100644
index 00000000000000..8a6ee4b9de4895
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-ffpp_raw_1fps_faces_expand_30_aligned_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English ffpp_raw_1fps_faces_expand_30_aligned_pipeline pipeline SwinForImageClassification from hchcsuim
+author: John Snow Labs
+name: ffpp_raw_1fps_faces_expand_30_aligned_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ffpp_raw_1fps_faces_expand_30_aligned_pipeline` is a English model originally trained by hchcsuim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ffpp_raw_1fps_faces_expand_30_aligned_pipeline_en_5.5.1_3.0_1737693962011.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ffpp_raw_1fps_faces_expand_30_aligned_pipeline_en_5.5.1_3.0_1737693962011.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ffpp_raw_1fps_faces_expand_30_aligned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ffpp_raw_1fps_faces_expand_30_aligned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ffpp_raw_1fps_faces_expand_30_aligned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/hchcsuim/FFPP-Raw_1FPS_faces-expand-30-aligned
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-ffpp_raw_1fps_faces_expand_50_aligned_en.md b/docs/_posts/ahmedlone127/2025-01-24-ffpp_raw_1fps_faces_expand_50_aligned_en.md
new file mode 100644
index 00000000000000..4420eeb3d96604
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-ffpp_raw_1fps_faces_expand_50_aligned_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ffpp_raw_1fps_faces_expand_50_aligned SwinForImageClassification from hchcsuim
+author: John Snow Labs
+name: ffpp_raw_1fps_faces_expand_50_aligned
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ffpp_raw_1fps_faces_expand_50_aligned` is a English model originally trained by hchcsuim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ffpp_raw_1fps_faces_expand_50_aligned_en_5.5.1_3.0_1737694249274.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ffpp_raw_1fps_faces_expand_50_aligned_en_5.5.1_3.0_1737694249274.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""ffpp_raw_1fps_faces_expand_50_aligned","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("ffpp_raw_1fps_faces_expand_50_aligned","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ffpp_raw_1fps_faces_expand_50_aligned|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/hchcsuim/FFPP-Raw_1FPS_faces-expand-50-aligned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-ffpp_raw_1fps_faces_expand_50_aligned_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-ffpp_raw_1fps_faces_expand_50_aligned_pipeline_en.md
new file mode 100644
index 00000000000000..bb038ddf8d324c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-ffpp_raw_1fps_faces_expand_50_aligned_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English ffpp_raw_1fps_faces_expand_50_aligned_pipeline pipeline SwinForImageClassification from hchcsuim
+author: John Snow Labs
+name: ffpp_raw_1fps_faces_expand_50_aligned_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ffpp_raw_1fps_faces_expand_50_aligned_pipeline` is a English model originally trained by hchcsuim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ffpp_raw_1fps_faces_expand_50_aligned_pipeline_en_5.5.1_3.0_1737694263230.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ffpp_raw_1fps_faces_expand_50_aligned_pipeline_en_5.5.1_3.0_1737694263230.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ffpp_raw_1fps_faces_expand_50_aligned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ffpp_raw_1fps_faces_expand_50_aligned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ffpp_raw_1fps_faces_expand_50_aligned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/hchcsuim/FFPP-Raw_1FPS_faces-expand-50-aligned
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-ffpp_raw_1fps_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-ffpp_raw_1fps_pipeline_en.md
new file mode 100644
index 00000000000000..37e5a393273cd1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-ffpp_raw_1fps_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English ffpp_raw_1fps_pipeline pipeline SwinForImageClassification from hchcsuim
+author: John Snow Labs
+name: ffpp_raw_1fps_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ffpp_raw_1fps_pipeline` is a English model originally trained by hchcsuim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ffpp_raw_1fps_pipeline_en_5.5.1_3.0_1737754099334.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ffpp_raw_1fps_pipeline_en_5.5.1_3.0_1737754099334.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ffpp_raw_1fps_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ffpp_raw_1fps_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ffpp_raw_1fps_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/hchcsuim/FFPP-Raw_1FPS
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-fierro_4_en.md b/docs/_posts/ahmedlone127/2025-01-24-fierro_4_en.md
new file mode 100644
index 00000000000000..ca93140dfe0e5b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-fierro_4_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English fierro_4 GPT2Transformer from Kinga1BK
+author: John Snow Labs
+name: fierro_4
+date: 2025-01-24
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fierro_4` is a English model originally trained by Kinga1BK.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fierro_4_en_5.5.1_3.0_1737733284511.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fierro_4_en_5.5.1_3.0_1737733284511.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("fierro_4","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("fierro_4","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fierro_4|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/Kinga1BK/FIERRO_4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-fierro_4_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-fierro_4_pipeline_en.md
new file mode 100644
index 00000000000000..41743f1f1a40a7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-fierro_4_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English fierro_4_pipeline pipeline GPT2Transformer from Kinga1BK
+author: John Snow Labs
+name: fierro_4_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fierro_4_pipeline` is a English model originally trained by Kinga1BK.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fierro_4_pipeline_en_5.5.1_3.0_1737733308628.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fierro_4_pipeline_en_5.5.1_3.0_1737733308628.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fierro_4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fierro_4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fierro_4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/Kinga1BK/FIERRO_4
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-final_ft__roberta_base_biomedical_clinical_spanish__70k_ultrasounds_ner_en.md b/docs/_posts/ahmedlone127/2025-01-24-final_ft__roberta_base_biomedical_clinical_spanish__70k_ultrasounds_ner_en.md
new file mode 100644
index 00000000000000..66d4df4483dd1d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-final_ft__roberta_base_biomedical_clinical_spanish__70k_ultrasounds_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English final_ft__roberta_base_biomedical_clinical_spanish__70k_ultrasounds_ner RoBertaForTokenClassification from manucos
+author: John Snow Labs
+name: final_ft__roberta_base_biomedical_clinical_spanish__70k_ultrasounds_ner
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`final_ft__roberta_base_biomedical_clinical_spanish__70k_ultrasounds_ner` is a English model originally trained by manucos.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/final_ft__roberta_base_biomedical_clinical_spanish__70k_ultrasounds_ner_en_5.5.1_3.0_1737703437468.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/final_ft__roberta_base_biomedical_clinical_spanish__70k_ultrasounds_ner_en_5.5.1_3.0_1737703437468.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("final_ft__roberta_base_biomedical_clinical_spanish__70k_ultrasounds_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("final_ft__roberta_base_biomedical_clinical_spanish__70k_ultrasounds_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|final_ft__roberta_base_biomedical_clinical_spanish__70k_ultrasounds_ner|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|469.4 MB|
+
+## References
+
+https://huggingface.co/manucos/final-ft__roberta-base-biomedical-clinical-es__70k-ultrasounds-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-final_ft__roberta_base_biomedical_clinical_spanish__70k_ultrasounds_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-final_ft__roberta_base_biomedical_clinical_spanish__70k_ultrasounds_ner_pipeline_en.md
new file mode 100644
index 00000000000000..64dc01eb2c9909
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-final_ft__roberta_base_biomedical_clinical_spanish__70k_ultrasounds_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English final_ft__roberta_base_biomedical_clinical_spanish__70k_ultrasounds_ner_pipeline pipeline RoBertaForTokenClassification from manucos
+author: John Snow Labs
+name: final_ft__roberta_base_biomedical_clinical_spanish__70k_ultrasounds_ner_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`final_ft__roberta_base_biomedical_clinical_spanish__70k_ultrasounds_ner_pipeline` is a English model originally trained by manucos.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/final_ft__roberta_base_biomedical_clinical_spanish__70k_ultrasounds_ner_pipeline_en_5.5.1_3.0_1737703462591.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/final_ft__roberta_base_biomedical_clinical_spanish__70k_ultrasounds_ner_pipeline_en_5.5.1_3.0_1737703462591.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("final_ft__roberta_base_biomedical_clinical_spanish__70k_ultrasounds_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("final_ft__roberta_base_biomedical_clinical_spanish__70k_ultrasounds_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|final_ft__roberta_base_biomedical_clinical_spanish__70k_ultrasounds_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|469.5 MB|
+
+## References
+
+https://huggingface.co/manucos/final-ft__roberta-base-biomedical-clinical-es__70k-ultrasounds-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-final_ft__roberta_clinical_wl_spanish__70k_ultrasounds_ner_en.md b/docs/_posts/ahmedlone127/2025-01-24-final_ft__roberta_clinical_wl_spanish__70k_ultrasounds_ner_en.md
new file mode 100644
index 00000000000000..72c5b242792011
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-final_ft__roberta_clinical_wl_spanish__70k_ultrasounds_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English final_ft__roberta_clinical_wl_spanish__70k_ultrasounds_ner RoBertaForTokenClassification from manucos
+author: John Snow Labs
+name: final_ft__roberta_clinical_wl_spanish__70k_ultrasounds_ner
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`final_ft__roberta_clinical_wl_spanish__70k_ultrasounds_ner` is a English model originally trained by manucos.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/final_ft__roberta_clinical_wl_spanish__70k_ultrasounds_ner_en_5.5.1_3.0_1737702471278.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/final_ft__roberta_clinical_wl_spanish__70k_ultrasounds_ner_en_5.5.1_3.0_1737702471278.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("final_ft__roberta_clinical_wl_spanish__70k_ultrasounds_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("final_ft__roberta_clinical_wl_spanish__70k_ultrasounds_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|final_ft__roberta_clinical_wl_spanish__70k_ultrasounds_ner|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|469.7 MB|
+
+## References
+
+https://huggingface.co/manucos/final-ft__roberta-clinical-wl-es__70k-ultrasounds-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-final_ft__roberta_clinical_wl_spanish__70k_ultrasounds_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-final_ft__roberta_clinical_wl_spanish__70k_ultrasounds_ner_pipeline_en.md
new file mode 100644
index 00000000000000..117687cc5c1f29
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-final_ft__roberta_clinical_wl_spanish__70k_ultrasounds_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English final_ft__roberta_clinical_wl_spanish__70k_ultrasounds_ner_pipeline pipeline RoBertaForTokenClassification from manucos
+author: John Snow Labs
+name: final_ft__roberta_clinical_wl_spanish__70k_ultrasounds_ner_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`final_ft__roberta_clinical_wl_spanish__70k_ultrasounds_ner_pipeline` is a English model originally trained by manucos.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/final_ft__roberta_clinical_wl_spanish__70k_ultrasounds_ner_pipeline_en_5.5.1_3.0_1737702496860.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/final_ft__roberta_clinical_wl_spanish__70k_ultrasounds_ner_pipeline_en_5.5.1_3.0_1737702496860.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("final_ft__roberta_clinical_wl_spanish__70k_ultrasounds_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("final_ft__roberta_clinical_wl_spanish__70k_ultrasounds_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|final_ft__roberta_clinical_wl_spanish__70k_ultrasounds_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|469.8 MB|
+
+## References
+
+https://huggingface.co/manucos/final-ft__roberta-clinical-wl-es__70k-ultrasounds-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-fine_tuned_16384_pubmed_en.md b/docs/_posts/ahmedlone127/2025-01-24-fine_tuned_16384_pubmed_en.md
new file mode 100644
index 00000000000000..0f0702b097e548
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-fine_tuned_16384_pubmed_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English fine_tuned_16384_pubmed BartTransformer from thanhkt
+author: John Snow Labs
+name: fine_tuned_16384_pubmed
+date: 2025-01-24
+tags: [en, open_source, onnx, text_generation, bart]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BartTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_16384_pubmed` is a English model originally trained by thanhkt.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_16384_pubmed_en_5.5.1_3.0_1737705147240.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_16384_pubmed_en_5.5.1_3.0_1737705147240.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = BartTransformer.pretrained("fine_tuned_16384_pubmed","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = BartTransformer.pretrained("fine_tuned_16384_pubmed","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_16384_pubmed|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|886.6 MB|
+
+## References
+
+https://huggingface.co/thanhkt/fine-tuned-16384-pubmed
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-fine_tuned_16384_pubmed_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-fine_tuned_16384_pubmed_pipeline_en.md
new file mode 100644
index 00000000000000..c675b6eee5fe8b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-fine_tuned_16384_pubmed_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English fine_tuned_16384_pubmed_pipeline pipeline BartTransformer from thanhkt
+author: John Snow Labs
+name: fine_tuned_16384_pubmed_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_16384_pubmed_pipeline` is a English model originally trained by thanhkt.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_16384_pubmed_pipeline_en_5.5.1_3.0_1737705197348.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_16384_pubmed_pipeline_en_5.5.1_3.0_1737705197348.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fine_tuned_16384_pubmed_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fine_tuned_16384_pubmed_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_16384_pubmed_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|886.6 MB|
+
+## References
+
+https://huggingface.co/thanhkt/fine-tuned-16384-pubmed
+
+## Included Models
+
+- DocumentAssembler
+- BartTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-fine_tuned_bert_for_liquidity_q_en.md b/docs/_posts/ahmedlone127/2025-01-24-fine_tuned_bert_for_liquidity_q_en.md
new file mode 100644
index 00000000000000..f56ac745ffaef3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-fine_tuned_bert_for_liquidity_q_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English fine_tuned_bert_for_liquidity_q BertEmbeddings from punchnami
+author: John Snow Labs
+name: fine_tuned_bert_for_liquidity_q
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_bert_for_liquidity_q` is a English model originally trained by punchnami.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_bert_for_liquidity_q_en_5.5.1_3.0_1737708057081.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_bert_for_liquidity_q_en_5.5.1_3.0_1737708057081.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("fine_tuned_bert_for_liquidity_q","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("fine_tuned_bert_for_liquidity_q","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_bert_for_liquidity_q|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/punchnami/fine-tuned-BERT-for-liquidity-q
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-fine_tuned_bert_for_liquidity_q_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-fine_tuned_bert_for_liquidity_q_pipeline_en.md
new file mode 100644
index 00000000000000..d8857615b4507f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-fine_tuned_bert_for_liquidity_q_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English fine_tuned_bert_for_liquidity_q_pipeline pipeline BertEmbeddings from punchnami
+author: John Snow Labs
+name: fine_tuned_bert_for_liquidity_q_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_bert_for_liquidity_q_pipeline` is a English model originally trained by punchnami.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_bert_for_liquidity_q_pipeline_en_5.5.1_3.0_1737708078852.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_bert_for_liquidity_q_pipeline_en_5.5.1_3.0_1737708078852.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fine_tuned_bert_for_liquidity_q_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fine_tuned_bert_for_liquidity_q_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_bert_for_liquidity_q_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/punchnami/fine-tuned-BERT-for-liquidity-q
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-fine_tuned_gpt_2_en.md b/docs/_posts/ahmedlone127/2025-01-24-fine_tuned_gpt_2_en.md
new file mode 100644
index 00000000000000..00080a7effd108
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-fine_tuned_gpt_2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English fine_tuned_gpt_2 GPT2Transformer from khalednabawi11
+author: John Snow Labs
+name: fine_tuned_gpt_2
+date: 2025-01-24
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_gpt_2` is a English model originally trained by khalednabawi11.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_gpt_2_en_5.5.1_3.0_1737733638154.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_gpt_2_en_5.5.1_3.0_1737733638154.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("fine_tuned_gpt_2","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("fine_tuned_gpt_2","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_gpt_2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/khalednabawi11/fine_tuned_gpt-2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-fine_tuned_gpt_2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-fine_tuned_gpt_2_pipeline_en.md
new file mode 100644
index 00000000000000..6673c8abf901d5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-fine_tuned_gpt_2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English fine_tuned_gpt_2_pipeline pipeline GPT2Transformer from khalednabawi11
+author: John Snow Labs
+name: fine_tuned_gpt_2_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_gpt_2_pipeline` is a English model originally trained by khalednabawi11.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_gpt_2_pipeline_en_5.5.1_3.0_1737733706011.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_gpt_2_pipeline_en_5.5.1_3.0_1737733706011.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fine_tuned_gpt_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fine_tuned_gpt_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_gpt_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/khalednabawi11/fine_tuned_gpt-2
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-finetune_xlm_r_base_uit_visquad_v1_2_en.md b/docs/_posts/ahmedlone127/2025-01-24-finetune_xlm_r_base_uit_visquad_v1_2_en.md
new file mode 100644
index 00000000000000..c7a96fc331ad9a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-finetune_xlm_r_base_uit_visquad_v1_2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English finetune_xlm_r_base_uit_visquad_v1_2 XlmRoBertaForQuestionAnswering from haidangnguyen467
+author: John Snow Labs
+name: finetune_xlm_r_base_uit_visquad_v1_2
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, xlm_roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetune_xlm_r_base_uit_visquad_v1_2` is a English model originally trained by haidangnguyen467.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetune_xlm_r_base_uit_visquad_v1_2_en_5.5.1_3.0_1737753387308.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetune_xlm_r_base_uit_visquad_v1_2_en_5.5.1_3.0_1737753387308.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("finetune_xlm_r_base_uit_visquad_v1_2","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("finetune_xlm_r_base_uit_visquad_v1_2", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetune_xlm_r_base_uit_visquad_v1_2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|814.8 MB|
+
+## References
+
+https://huggingface.co/haidangnguyen467/finetune-xlm-r-base-uit-visquad-v1_2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-finetune_xlm_r_base_uit_visquad_v1_2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-finetune_xlm_r_base_uit_visquad_v1_2_pipeline_en.md
new file mode 100644
index 00000000000000..20d891c3450c42
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-finetune_xlm_r_base_uit_visquad_v1_2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English finetune_xlm_r_base_uit_visquad_v1_2_pipeline pipeline XlmRoBertaForQuestionAnswering from haidangnguyen467
+author: John Snow Labs
+name: finetune_xlm_r_base_uit_visquad_v1_2_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetune_xlm_r_base_uit_visquad_v1_2_pipeline` is a English model originally trained by haidangnguyen467.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetune_xlm_r_base_uit_visquad_v1_2_pipeline_en_5.5.1_3.0_1737753503830.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetune_xlm_r_base_uit_visquad_v1_2_pipeline_en_5.5.1_3.0_1737753503830.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetune_xlm_r_base_uit_visquad_v1_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetune_xlm_r_base_uit_visquad_v1_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetune_xlm_r_base_uit_visquad_v1_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|814.8 MB|
+
+## References
+
+https://huggingface.co/haidangnguyen467/finetune-xlm-r-base-uit-visquad-v1_2
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-finetune_xlm_r_base_uit_visquad_v1_en.md b/docs/_posts/ahmedlone127/2025-01-24-finetune_xlm_r_base_uit_visquad_v1_en.md
new file mode 100644
index 00000000000000..6c68f19cd9b6f1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-finetune_xlm_r_base_uit_visquad_v1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English finetune_xlm_r_base_uit_visquad_v1 XlmRoBertaForQuestionAnswering from haidangnguyen467
+author: John Snow Labs
+name: finetune_xlm_r_base_uit_visquad_v1
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, xlm_roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetune_xlm_r_base_uit_visquad_v1` is a English model originally trained by haidangnguyen467.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetune_xlm_r_base_uit_visquad_v1_en_5.5.1_3.0_1737753208908.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetune_xlm_r_base_uit_visquad_v1_en_5.5.1_3.0_1737753208908.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("finetune_xlm_r_base_uit_visquad_v1","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("finetune_xlm_r_base_uit_visquad_v1", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetune_xlm_r_base_uit_visquad_v1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|810.5 MB|
+
+## References
+
+https://huggingface.co/haidangnguyen467/finetune-xlm-r-base-uit-visquad-v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-finetune_xlm_r_base_uit_visquad_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-finetune_xlm_r_base_uit_visquad_v1_pipeline_en.md
new file mode 100644
index 00000000000000..4b8714e40bed04
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-finetune_xlm_r_base_uit_visquad_v1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English finetune_xlm_r_base_uit_visquad_v1_pipeline pipeline XlmRoBertaForQuestionAnswering from haidangnguyen467
+author: John Snow Labs
+name: finetune_xlm_r_base_uit_visquad_v1_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetune_xlm_r_base_uit_visquad_v1_pipeline` is a English model originally trained by haidangnguyen467.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetune_xlm_r_base_uit_visquad_v1_pipeline_en_5.5.1_3.0_1737753335307.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetune_xlm_r_base_uit_visquad_v1_pipeline_en_5.5.1_3.0_1737753335307.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetune_xlm_r_base_uit_visquad_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetune_xlm_r_base_uit_visquad_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetune_xlm_r_base_uit_visquad_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|810.5 MB|
+
+## References
+
+https://huggingface.co/haidangnguyen467/finetune-xlm-r-base-uit-visquad-v1
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-finetuned_swint_indian_food_classification_v1_en.md b/docs/_posts/ahmedlone127/2025-01-24-finetuned_swint_indian_food_classification_v1_en.md
new file mode 100644
index 00000000000000..d6d047f7d36cb8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-finetuned_swint_indian_food_classification_v1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuned_swint_indian_food_classification_v1 SwinForImageClassification from DrishtiSharma
+author: John Snow Labs
+name: finetuned_swint_indian_food_classification_v1
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_swint_indian_food_classification_v1` is a English model originally trained by DrishtiSharma.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_swint_indian_food_classification_v1_en_5.5.1_3.0_1737763032287.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_swint_indian_food_classification_v1_en_5.5.1_3.0_1737763032287.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""finetuned_swint_indian_food_classification_v1","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("finetuned_swint_indian_food_classification_v1","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_swint_indian_food_classification_v1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|817.7 MB|
+
+## References
+
+https://huggingface.co/DrishtiSharma/finetuned-SwinT-Indian-Food-Classification-v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-finetuned_swint_indian_food_classification_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-finetuned_swint_indian_food_classification_v1_pipeline_en.md
new file mode 100644
index 00000000000000..8086aa9dbc662e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-finetuned_swint_indian_food_classification_v1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English finetuned_swint_indian_food_classification_v1_pipeline pipeline SwinForImageClassification from DrishtiSharma
+author: John Snow Labs
+name: finetuned_swint_indian_food_classification_v1_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_swint_indian_food_classification_v1_pipeline` is a English model originally trained by DrishtiSharma.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_swint_indian_food_classification_v1_pipeline_en_5.5.1_3.0_1737763076820.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_swint_indian_food_classification_v1_pipeline_en_5.5.1_3.0_1737763076820.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuned_swint_indian_food_classification_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuned_swint_indian_food_classification_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_swint_indian_food_classification_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|817.7 MB|
+
+## References
+
+https://huggingface.co/DrishtiSharma/finetuned-SwinT-Indian-Food-Classification-v1
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-finetuned_swint_indian_food_classification_v2_en.md b/docs/_posts/ahmedlone127/2025-01-24-finetuned_swint_indian_food_classification_v2_en.md
new file mode 100644
index 00000000000000..c6ca97f4a3d00c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-finetuned_swint_indian_food_classification_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuned_swint_indian_food_classification_v2 SwinForImageClassification from DrishtiSharma
+author: John Snow Labs
+name: finetuned_swint_indian_food_classification_v2
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_swint_indian_food_classification_v2` is a English model originally trained by DrishtiSharma.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_swint_indian_food_classification_v2_en_5.5.1_3.0_1737762882462.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_swint_indian_food_classification_v2_en_5.5.1_3.0_1737762882462.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""finetuned_swint_indian_food_classification_v2","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("finetuned_swint_indian_food_classification_v2","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_swint_indian_food_classification_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|649.9 MB|
+
+## References
+
+https://huggingface.co/DrishtiSharma/finetuned-SwinT-Indian-Food-Classification-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-finetuned_swint_indian_food_classification_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-finetuned_swint_indian_food_classification_v2_pipeline_en.md
new file mode 100644
index 00000000000000..477afb8fda7328
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-finetuned_swint_indian_food_classification_v2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English finetuned_swint_indian_food_classification_v2_pipeline pipeline SwinForImageClassification from DrishtiSharma
+author: John Snow Labs
+name: finetuned_swint_indian_food_classification_v2_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_swint_indian_food_classification_v2_pipeline` is a English model originally trained by DrishtiSharma.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_swint_indian_food_classification_v2_pipeline_en_5.5.1_3.0_1737762916703.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_swint_indian_food_classification_v2_pipeline_en_5.5.1_3.0_1737762916703.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuned_swint_indian_food_classification_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuned_swint_indian_food_classification_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_swint_indian_food_classification_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|649.9 MB|
+
+## References
+
+https://huggingface.co/DrishtiSharma/finetuned-SwinT-Indian-Food-Classification-v2
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-food_category_classification_v2_0_en.md b/docs/_posts/ahmedlone127/2025-01-24-food_category_classification_v2_0_en.md
new file mode 100644
index 00000000000000..e8b2fd131075d1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-food_category_classification_v2_0_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English food_category_classification_v2_0 SwinForImageClassification from Kaludi
+author: John Snow Labs
+name: food_category_classification_v2_0
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`food_category_classification_v2_0` is a English model originally trained by Kaludi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/food_category_classification_v2_0_en_5.5.1_3.0_1737762273065.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/food_category_classification_v2_0_en_5.5.1_3.0_1737762273065.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""food_category_classification_v2_0","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("food_category_classification_v2_0","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|food_category_classification_v2_0|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|649.8 MB|
+
+## References
+
+https://huggingface.co/Kaludi/food-category-classification-v2.0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-food_category_classification_v2_0_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-food_category_classification_v2_0_pipeline_en.md
new file mode 100644
index 00000000000000..0e0aa2fcba7b1a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-food_category_classification_v2_0_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English food_category_classification_v2_0_pipeline pipeline SwinForImageClassification from Kaludi
+author: John Snow Labs
+name: food_category_classification_v2_0_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`food_category_classification_v2_0_pipeline` is a English model originally trained by Kaludi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/food_category_classification_v2_0_pipeline_en_5.5.1_3.0_1737762308067.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/food_category_classification_v2_0_pipeline_en_5.5.1_3.0_1737762308067.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("food_category_classification_v2_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("food_category_classification_v2_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|food_category_classification_v2_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|649.9 MB|
+
+## References
+
+https://huggingface.co/Kaludi/food-category-classification-v2.0
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-food_classification_en.md b/docs/_posts/ahmedlone127/2025-01-24-food_classification_en.md
new file mode 100644
index 00000000000000..2fba1486be5c6c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-food_classification_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English food_classification SwinForImageClassification from Kaludi
+author: John Snow Labs
+name: food_classification
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`food_classification` is a English model originally trained by Kaludi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/food_classification_en_5.5.1_3.0_1737762915605.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/food_classification_en_5.5.1_3.0_1737762915605.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""food_classification","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("food_classification","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|food_classification|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|649.8 MB|
+
+## References
+
+https://huggingface.co/Kaludi/Food-Classification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-food_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-food_classification_pipeline_en.md
new file mode 100644
index 00000000000000..bb6e19c3558d14
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-food_classification_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English food_classification_pipeline pipeline SwinForImageClassification from Kaludi
+author: John Snow Labs
+name: food_classification_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`food_classification_pipeline` is a English model originally trained by Kaludi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/food_classification_pipeline_en_5.5.1_3.0_1737762958763.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/food_classification_pipeline_en_5.5.1_3.0_1737762958763.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("food_classification_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("food_classification_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|food_classification_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|649.8 MB|
+
+## References
+
+https://huggingface.co/Kaludi/Food-Classification
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-fp_mbert_en.md b/docs/_posts/ahmedlone127/2025-01-24-fp_mbert_en.md
new file mode 100644
index 00000000000000..cdfbe4fb27ed94
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-fp_mbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English fp_mbert BertEmbeddings from Sadia2000
+author: John Snow Labs
+name: fp_mbert
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fp_mbert` is a English model originally trained by Sadia2000.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fp_mbert_en_5.5.1_3.0_1737708134819.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fp_mbert_en_5.5.1_3.0_1737708134819.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("fp_mbert","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("fp_mbert","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fp_mbert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|664.1 MB|
+
+## References
+
+https://huggingface.co/Sadia2000/fp_mbert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-fp_mbert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-fp_mbert_pipeline_en.md
new file mode 100644
index 00000000000000..110ae7178c2ec2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-fp_mbert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English fp_mbert_pipeline pipeline BertEmbeddings from Sadia2000
+author: John Snow Labs
+name: fp_mbert_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fp_mbert_pipeline` is a English model originally trained by Sadia2000.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fp_mbert_pipeline_en_5.5.1_3.0_1737708170474.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fp_mbert_pipeline_en_5.5.1_3.0_1737708170474.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fp_mbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fp_mbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fp_mbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|664.1 MB|
+
+## References
+
+https://huggingface.co/Sadia2000/fp_mbert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-gate_softmax_bert_base_en.md b/docs/_posts/ahmedlone127/2025-01-24-gate_softmax_bert_base_en.md
new file mode 100644
index 00000000000000..56b969aee46506
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-gate_softmax_bert_base_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English gate_softmax_bert_base BertEmbeddings from magicslabnu
+author: John Snow Labs
+name: gate_softmax_bert_base
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gate_softmax_bert_base` is a English model originally trained by magicslabnu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gate_softmax_bert_base_en_5.5.1_3.0_1737708322052.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gate_softmax_bert_base_en_5.5.1_3.0_1737708322052.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("gate_softmax_bert_base","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("gate_softmax_bert_base","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gate_softmax_bert_base|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|408.4 MB|
+
+## References
+
+https://huggingface.co/magicslabnu/gate_softmax_bert_base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-gate_softmax_bert_base_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-gate_softmax_bert_base_pipeline_en.md
new file mode 100644
index 00000000000000..004cf0847c6b18
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-gate_softmax_bert_base_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English gate_softmax_bert_base_pipeline pipeline BertEmbeddings from magicslabnu
+author: John Snow Labs
+name: gate_softmax_bert_base_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gate_softmax_bert_base_pipeline` is a English model originally trained by magicslabnu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gate_softmax_bert_base_pipeline_en_5.5.1_3.0_1737708343651.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gate_softmax_bert_base_pipeline_en_5.5.1_3.0_1737708343651.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gate_softmax_bert_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gate_softmax_bert_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gate_softmax_bert_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|408.4 MB|
+
+## References
+
+https://huggingface.co/magicslabnu/gate_softmax_bert_base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-genderage2_en.md b/docs/_posts/ahmedlone127/2025-01-24-genderage2_en.md
new file mode 100644
index 00000000000000..d2b75e16b9c609
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-genderage2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English genderage2 ViTForImageClassification from ivensamdh
+author: John Snow Labs
+name: genderage2
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`genderage2` is a English model originally trained by ivensamdh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/genderage2_en_5.5.1_3.0_1737744552147.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/genderage2_en_5.5.1_3.0_1737744552147.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""genderage2","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("genderage2","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|genderage2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/ivensamdh/genderage2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-genderage2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-genderage2_pipeline_en.md
new file mode 100644
index 00000000000000..dd699cb4caead0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-genderage2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English genderage2_pipeline pipeline ViTForImageClassification from ivensamdh
+author: John Snow Labs
+name: genderage2_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`genderage2_pipeline` is a English model originally trained by ivensamdh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/genderage2_pipeline_en_5.5.1_3.0_1737744569591.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/genderage2_pipeline_en_5.5.1_3.0_1737744569591.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("genderage2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("genderage2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|genderage2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/ivensamdh/genderage2
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-germedbert_ner_v01_bronco_cardio_de.md b/docs/_posts/ahmedlone127/2025-01-24-germedbert_ner_v01_bronco_cardio_de.md
new file mode 100644
index 00000000000000..70d27436bece54
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-germedbert_ner_v01_bronco_cardio_de.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: German germedbert_ner_v01_bronco_cardio BertForTokenClassification from BachelorThesis
+author: John Snow Labs
+name: germedbert_ner_v01_bronco_cardio
+date: 2025-01-24
+tags: [de, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: de
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`germedbert_ner_v01_bronco_cardio` is a German model originally trained by BachelorThesis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/germedbert_ner_v01_bronco_cardio_de_5.5.1_3.0_1737719867306.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/germedbert_ner_v01_bronco_cardio_de_5.5.1_3.0_1737719867306.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("germedbert_ner_v01_bronco_cardio","de") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("germedbert_ner_v01_bronco_cardio", "de")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|germedbert_ner_v01_bronco_cardio|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|de|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/BachelorThesis/GerMedBERT_NER_V01_BRONCO_CARDIO
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-germedbert_ner_v01_bronco_cardio_pipeline_de.md b/docs/_posts/ahmedlone127/2025-01-24-germedbert_ner_v01_bronco_cardio_pipeline_de.md
new file mode 100644
index 00000000000000..391bfff0a556c6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-germedbert_ner_v01_bronco_cardio_pipeline_de.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: German germedbert_ner_v01_bronco_cardio_pipeline pipeline BertForTokenClassification from BachelorThesis
+author: John Snow Labs
+name: germedbert_ner_v01_bronco_cardio_pipeline
+date: 2025-01-24
+tags: [de, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: de
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`germedbert_ner_v01_bronco_cardio_pipeline` is a German model originally trained by BachelorThesis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/germedbert_ner_v01_bronco_cardio_pipeline_de_5.5.1_3.0_1737719896815.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/germedbert_ner_v01_bronco_cardio_pipeline_de_5.5.1_3.0_1737719896815.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("germedbert_ner_v01_bronco_cardio_pipeline", lang = "de")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("germedbert_ner_v01_bronco_cardio_pipeline", lang = "de")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|germedbert_ner_v01_bronco_cardio_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|de|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/BachelorThesis/GerMedBERT_NER_V01_BRONCO_CARDIO
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-goemotions_bertspanish_finetunig_g_en.md b/docs/_posts/ahmedlone127/2025-01-24-goemotions_bertspanish_finetunig_g_en.md
new file mode 100644
index 00000000000000..aa8d4a30207352
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-goemotions_bertspanish_finetunig_g_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English goemotions_bertspanish_finetunig_g BertForSequenceClassification from mrovejaxd
+author: John Snow Labs
+name: goemotions_bertspanish_finetunig_g
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goemotions_bertspanish_finetunig_g` is a English model originally trained by mrovejaxd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goemotions_bertspanish_finetunig_g_en_5.5.1_3.0_1737710912175.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goemotions_bertspanish_finetunig_g_en_5.5.1_3.0_1737710912175.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("goemotions_bertspanish_finetunig_g","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("goemotions_bertspanish_finetunig_g", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|goemotions_bertspanish_finetunig_g|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|411.8 MB|
+
+## References
+
+https://huggingface.co/mrovejaxd/goemotions_bertspanish_finetunig_g
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-goemotions_bertspanish_finetunig_g_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-goemotions_bertspanish_finetunig_g_pipeline_en.md
new file mode 100644
index 00000000000000..da8e41ef9f9148
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-goemotions_bertspanish_finetunig_g_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English goemotions_bertspanish_finetunig_g_pipeline pipeline BertForSequenceClassification from mrovejaxd
+author: John Snow Labs
+name: goemotions_bertspanish_finetunig_g_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goemotions_bertspanish_finetunig_g_pipeline` is a English model originally trained by mrovejaxd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goemotions_bertspanish_finetunig_g_pipeline_en_5.5.1_3.0_1737710934435.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goemotions_bertspanish_finetunig_g_pipeline_en_5.5.1_3.0_1737710934435.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("goemotions_bertspanish_finetunig_g_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("goemotions_bertspanish_finetunig_g_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|goemotions_bertspanish_finetunig_g_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|411.8 MB|
+
+## References
+
+https://huggingface.co/mrovejaxd/goemotions_bertspanish_finetunig_g
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-gpt2_124m_edu_fineweb_10b_en.md b/docs/_posts/ahmedlone127/2025-01-24-gpt2_124m_edu_fineweb_10b_en.md
new file mode 100644
index 00000000000000..db43c95df56c76
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-gpt2_124m_edu_fineweb_10b_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English gpt2_124m_edu_fineweb_10b GPT2Transformer from rhysjones
+author: John Snow Labs
+name: gpt2_124m_edu_fineweb_10b
+date: 2025-01-24
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_124m_edu_fineweb_10b` is a English model originally trained by rhysjones.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_124m_edu_fineweb_10b_en_5.5.1_3.0_1737716308826.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_124m_edu_fineweb_10b_en_5.5.1_3.0_1737716308826.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("gpt2_124m_edu_fineweb_10b","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("gpt2_124m_edu_fineweb_10b","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_124m_edu_fineweb_10b|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|239.0 MB|
+
+## References
+
+https://huggingface.co/rhysjones/gpt2-124M-edu-fineweb-10B
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-gpt2_124m_edu_fineweb_10b_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-gpt2_124m_edu_fineweb_10b_pipeline_en.md
new file mode 100644
index 00000000000000..01bbcba1791a0b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-gpt2_124m_edu_fineweb_10b_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English gpt2_124m_edu_fineweb_10b_pipeline pipeline GPT2Transformer from rhysjones
+author: John Snow Labs
+name: gpt2_124m_edu_fineweb_10b_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_124m_edu_fineweb_10b_pipeline` is a English model originally trained by rhysjones.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_124m_edu_fineweb_10b_pipeline_en_5.5.1_3.0_1737716393760.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_124m_edu_fineweb_10b_pipeline_en_5.5.1_3.0_1737716393760.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpt2_124m_edu_fineweb_10b_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpt2_124m_edu_fineweb_10b_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_124m_edu_fineweb_10b_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|239.0 MB|
+
+## References
+
+https://huggingface.co/rhysjones/gpt2-124M-edu-fineweb-10B
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-gpt2_medium_650k_stable_diffusion_prompt_generator_en.md b/docs/_posts/ahmedlone127/2025-01-24-gpt2_medium_650k_stable_diffusion_prompt_generator_en.md
new file mode 100644
index 00000000000000..c545290b84be68
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-gpt2_medium_650k_stable_diffusion_prompt_generator_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English gpt2_medium_650k_stable_diffusion_prompt_generator GPT2Transformer from Ar4ikov
+author: John Snow Labs
+name: gpt2_medium_650k_stable_diffusion_prompt_generator
+date: 2025-01-24
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_medium_650k_stable_diffusion_prompt_generator` is a English model originally trained by Ar4ikov.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_medium_650k_stable_diffusion_prompt_generator_en_5.5.1_3.0_1737717659002.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_medium_650k_stable_diffusion_prompt_generator_en_5.5.1_3.0_1737717659002.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("gpt2_medium_650k_stable_diffusion_prompt_generator","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("gpt2_medium_650k_stable_diffusion_prompt_generator","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_medium_650k_stable_diffusion_prompt_generator|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/Ar4ikov/gpt2-medium-650k-stable-diffusion-prompt-generator
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-gpt2_medium_650k_stable_diffusion_prompt_generator_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-gpt2_medium_650k_stable_diffusion_prompt_generator_pipeline_en.md
new file mode 100644
index 00000000000000..3daf69f22d7eb3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-gpt2_medium_650k_stable_diffusion_prompt_generator_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English gpt2_medium_650k_stable_diffusion_prompt_generator_pipeline pipeline GPT2Transformer from Ar4ikov
+author: John Snow Labs
+name: gpt2_medium_650k_stable_diffusion_prompt_generator_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_medium_650k_stable_diffusion_prompt_generator_pipeline` is a English model originally trained by Ar4ikov.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_medium_650k_stable_diffusion_prompt_generator_pipeline_en_5.5.1_3.0_1737717727148.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_medium_650k_stable_diffusion_prompt_generator_pipeline_en_5.5.1_3.0_1737717727148.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpt2_medium_650k_stable_diffusion_prompt_generator_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpt2_medium_650k_stable_diffusion_prompt_generator_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_medium_650k_stable_diffusion_prompt_generator_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/Ar4ikov/gpt2-medium-650k-stable-diffusion-prompt-generator
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-gpt2_medium_openai_community_en.md b/docs/_posts/ahmedlone127/2025-01-24-gpt2_medium_openai_community_en.md
new file mode 100644
index 00000000000000..26bf797925019c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-gpt2_medium_openai_community_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English gpt2_medium_openai_community GPT2Transformer from openai-community
+author: John Snow Labs
+name: gpt2_medium_openai_community
+date: 2025-01-24
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_medium_openai_community` is a English model originally trained by openai-community.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_medium_openai_community_en_5.5.1_3.0_1737718162242.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_medium_openai_community_en_5.5.1_3.0_1737718162242.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("gpt2_medium_openai_community","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("gpt2_medium_openai_community","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_medium_openai_community|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/openai-community/gpt2-medium
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-gpt2_medium_openai_community_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-gpt2_medium_openai_community_pipeline_en.md
new file mode 100644
index 00000000000000..89caa4b78c704b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-gpt2_medium_openai_community_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English gpt2_medium_openai_community_pipeline pipeline GPT2Transformer from openai-community
+author: John Snow Labs
+name: gpt2_medium_openai_community_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_medium_openai_community_pipeline` is a English model originally trained by openai-community.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_medium_openai_community_pipeline_en_5.5.1_3.0_1737718230500.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_medium_openai_community_pipeline_en_5.5.1_3.0_1737718230500.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpt2_medium_openai_community_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpt2_medium_openai_community_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_medium_openai_community_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/openai-community/gpt2-medium
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-gpt2_small_comcom_en.md b/docs/_posts/ahmedlone127/2025-01-24-gpt2_small_comcom_en.md
new file mode 100644
index 00000000000000..0f3de9c6972c2f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-gpt2_small_comcom_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English gpt2_small_comcom GPT2Transformer from ComCom
+author: John Snow Labs
+name: gpt2_small_comcom
+date: 2025-01-24
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_small_comcom` is a English model originally trained by ComCom.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_small_comcom_en_5.5.1_3.0_1737733682164.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_small_comcom_en_5.5.1_3.0_1737733682164.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("gpt2_small_comcom","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("gpt2_small_comcom","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_small_comcom|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/ComCom/gpt2-small
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-gpt2_small_comcom_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-gpt2_small_comcom_pipeline_en.md
new file mode 100644
index 00000000000000..57ac19558267a1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-gpt2_small_comcom_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English gpt2_small_comcom_pipeline pipeline GPT2Transformer from ComCom
+author: John Snow Labs
+name: gpt2_small_comcom_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_small_comcom_pipeline` is a English model originally trained by ComCom.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_small_comcom_pipeline_en_5.5.1_3.0_1737733707295.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_small_comcom_pipeline_en_5.5.1_3.0_1737733707295.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpt2_small_comcom_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpt2_small_comcom_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_small_comcom_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/ComCom/gpt2-small
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-gpt2_turkish_writer_pipeline_tr.md b/docs/_posts/ahmedlone127/2025-01-24-gpt2_turkish_writer_pipeline_tr.md
new file mode 100644
index 00000000000000..f3e06a0a61216d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-gpt2_turkish_writer_pipeline_tr.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Turkish gpt2_turkish_writer_pipeline pipeline GPT2Transformer from gorkemgoknar
+author: John Snow Labs
+name: gpt2_turkish_writer_pipeline
+date: 2025-01-24
+tags: [tr, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: tr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_turkish_writer_pipeline` is a Turkish model originally trained by gorkemgoknar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_turkish_writer_pipeline_tr_5.5.1_3.0_1737732933393.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_turkish_writer_pipeline_tr_5.5.1_3.0_1737732933393.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpt2_turkish_writer_pipeline", lang = "tr")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpt2_turkish_writer_pipeline", lang = "tr")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_turkish_writer_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|tr|
+|Size:|298.5 MB|
+
+## References
+
+https://huggingface.co/gorkemgoknar/gpt2-turkish-writer
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-gpt2_turkish_writer_tr.md b/docs/_posts/ahmedlone127/2025-01-24-gpt2_turkish_writer_tr.md
new file mode 100644
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--- /dev/null
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@@ -0,0 +1,86 @@
+---
+layout: model
+title: Turkish gpt2_turkish_writer GPT2Transformer from gorkemgoknar
+author: John Snow Labs
+name: gpt2_turkish_writer
+date: 2025-01-24
+tags: [tr, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: tr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_turkish_writer` is a Turkish model originally trained by gorkemgoknar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_turkish_writer_tr_5.5.1_3.0_1737732844906.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_turkish_writer_tr_5.5.1_3.0_1737732844906.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("gpt2_turkish_writer","tr") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("gpt2_turkish_writer","tr") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_turkish_writer|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|tr|
+|Size:|298.5 MB|
+
+## References
+
+https://huggingface.co/gorkemgoknar/gpt2-turkish-writer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-gpt2news_pipeline_vi.md b/docs/_posts/ahmedlone127/2025-01-24-gpt2news_pipeline_vi.md
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--- /dev/null
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+---
+layout: model
+title: Vietnamese gpt2news_pipeline pipeline GPT2Transformer from imthanhlv
+author: John Snow Labs
+name: gpt2news_pipeline
+date: 2025-01-24
+tags: [vi, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: vi
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2news_pipeline` is a Vietnamese model originally trained by imthanhlv.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2news_pipeline_vi_5.5.1_3.0_1737717588775.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2news_pipeline_vi_5.5.1_3.0_1737717588775.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpt2news_pipeline", lang = "vi")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpt2news_pipeline", lang = "vi")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2news_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|vi|
+|Size:|466.7 MB|
+
+## References
+
+https://huggingface.co/imthanhlv/gpt2news
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-gpt2news_vi.md b/docs/_posts/ahmedlone127/2025-01-24-gpt2news_vi.md
new file mode 100644
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--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-gpt2news_vi.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Vietnamese gpt2news GPT2Transformer from imthanhlv
+author: John Snow Labs
+name: gpt2news
+date: 2025-01-24
+tags: [vi, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: vi
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2news` is a Vietnamese model originally trained by imthanhlv.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2news_vi_5.5.1_3.0_1737717564379.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2news_vi_5.5.1_3.0_1737717564379.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("gpt2news","vi") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("gpt2news","vi") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2news|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|vi|
+|Size:|466.7 MB|
+
+## References
+
+https://huggingface.co/imthanhlv/gpt2news
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-gpt_neo_125m_dutch_nl.md b/docs/_posts/ahmedlone127/2025-01-24-gpt_neo_125m_dutch_nl.md
new file mode 100644
index 00000000000000..513442ddeade76
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-gpt_neo_125m_dutch_nl.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Dutch, Flemish gpt_neo_125m_dutch GPT2Transformer from yhavinga
+author: John Snow Labs
+name: gpt_neo_125m_dutch
+date: 2025-01-24
+tags: [nl, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: nl
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt_neo_125m_dutch` is a Dutch, Flemish model originally trained by yhavinga.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt_neo_125m_dutch_nl_5.5.1_3.0_1737716314021.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt_neo_125m_dutch_nl_5.5.1_3.0_1737716314021.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("gpt_neo_125m_dutch","nl") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("gpt_neo_125m_dutch","nl") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt_neo_125m_dutch|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|nl|
+|Size:|470.5 MB|
+
+## References
+
+https://huggingface.co/yhavinga/gpt-neo-125M-dutch
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-gpt_neo_125m_dutch_pipeline_nl.md b/docs/_posts/ahmedlone127/2025-01-24-gpt_neo_125m_dutch_pipeline_nl.md
new file mode 100644
index 00000000000000..d4bca19e9d7509
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-gpt_neo_125m_dutch_pipeline_nl.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Dutch, Flemish gpt_neo_125m_dutch_pipeline pipeline GPT2Transformer from yhavinga
+author: John Snow Labs
+name: gpt_neo_125m_dutch_pipeline
+date: 2025-01-24
+tags: [nl, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: nl
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt_neo_125m_dutch_pipeline` is a Dutch, Flemish model originally trained by yhavinga.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt_neo_125m_dutch_pipeline_nl_5.5.1_3.0_1737716339099.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt_neo_125m_dutch_pipeline_nl_5.5.1_3.0_1737716339099.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpt_neo_125m_dutch_pipeline", lang = "nl")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpt_neo_125m_dutch_pipeline", lang = "nl")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt_neo_125m_dutch_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|nl|
+|Size:|470.5 MB|
+
+## References
+
+https://huggingface.co/yhavinga/gpt-neo-125M-dutch
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-hero_finetuned_ner_en.md b/docs/_posts/ahmedlone127/2025-01-24-hero_finetuned_ner_en.md
new file mode 100644
index 00000000000000..9b8741daca0c47
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-hero_finetuned_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English hero_finetuned_ner RoBertaForTokenClassification from msperka
+author: John Snow Labs
+name: hero_finetuned_ner
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hero_finetuned_ner` is a English model originally trained by msperka.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hero_finetuned_ner_en_5.5.1_3.0_1737702542993.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hero_finetuned_ner_en_5.5.1_3.0_1737702542993.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("hero_finetuned_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("hero_finetuned_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hero_finetuned_ner|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|466.0 MB|
+
+## References
+
+https://huggingface.co/msperka/HeRo-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-hero_finetuned_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-hero_finetuned_ner_pipeline_en.md
new file mode 100644
index 00000000000000..513638a673d00b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-hero_finetuned_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English hero_finetuned_ner_pipeline pipeline RoBertaForTokenClassification from msperka
+author: John Snow Labs
+name: hero_finetuned_ner_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hero_finetuned_ner_pipeline` is a English model originally trained by msperka.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hero_finetuned_ner_pipeline_en_5.5.1_3.0_1737702568822.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hero_finetuned_ner_pipeline_en_5.5.1_3.0_1737702568822.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("hero_finetuned_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hero_finetuned_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hero_finetuned_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.0 MB|
+
+## References
+
+https://huggingface.co/msperka/HeRo-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-high_4_en.md b/docs/_posts/ahmedlone127/2025-01-24-high_4_en.md
new file mode 100644
index 00000000000000..88d046a23f14ba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-high_4_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English high_4 BertForQuestionAnswering from Jing24
+author: John Snow Labs
+name: high_4
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`high_4` is a English model originally trained by Jing24.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/high_4_en_5.5.1_3.0_1737751612374.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/high_4_en_5.5.1_3.0_1737751612374.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("high_4","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("high_4", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|high_4|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/Jing24/high-4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-high_4_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-high_4_pipeline_en.md
new file mode 100644
index 00000000000000..1f7fe346f4fdad
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-high_4_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English high_4_pipeline pipeline BertForQuestionAnswering from Jing24
+author: John Snow Labs
+name: high_4_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`high_4_pipeline` is a English model originally trained by Jing24.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/high_4_pipeline_en_5.5.1_3.0_1737751636708.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/high_4_pipeline_en_5.5.1_3.0_1737751636708.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("high_4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("high_4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|high_4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/Jing24/high-4
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-hindiemotion_hi.md b/docs/_posts/ahmedlone127/2025-01-24-hindiemotion_hi.md
new file mode 100644
index 00000000000000..b1eb2273d2059f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-hindiemotion_hi.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Hindi hindiemotion AlbertForSequenceClassification from vashuag
+author: John Snow Labs
+name: hindiemotion
+date: 2025-01-24
+tags: [hi, open_source, onnx, sequence_classification, albert]
+task: Text Classification
+language: hi
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hindiemotion` is a Hindi model originally trained by vashuag.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hindiemotion_hi_5.5.1_3.0_1737692958634.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hindiemotion_hi_5.5.1_3.0_1737692958634.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = AlbertForSequenceClassification.pretrained("hindiemotion","hi") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = AlbertForSequenceClassification.pretrained("hindiemotion", "hi")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hindiemotion|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|hi|
+|Size:|127.8 MB|
+
+## References
+
+https://huggingface.co/vashuag/HindiEmotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-hindiemotion_pipeline_hi.md b/docs/_posts/ahmedlone127/2025-01-24-hindiemotion_pipeline_hi.md
new file mode 100644
index 00000000000000..af3f41f8313b36
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-hindiemotion_pipeline_hi.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Hindi hindiemotion_pipeline pipeline AlbertForSequenceClassification from vashuag
+author: John Snow Labs
+name: hindiemotion_pipeline
+date: 2025-01-24
+tags: [hi, open_source, pipeline, onnx]
+task: Text Classification
+language: hi
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hindiemotion_pipeline` is a Hindi model originally trained by vashuag.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hindiemotion_pipeline_hi_5.5.1_3.0_1737692965039.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hindiemotion_pipeline_hi_5.5.1_3.0_1737692965039.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("hindiemotion_pipeline", lang = "hi")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hindiemotion_pipeline", lang = "hi")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hindiemotion_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|hi|
+|Size:|127.8 MB|
+
+## References
+
+https://huggingface.co/vashuag/HindiEmotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-how_tonga_tonga_islands_fine_tune_a_model_for_common_downstream_tasks_v2_en.md b/docs/_posts/ahmedlone127/2025-01-24-how_tonga_tonga_islands_fine_tune_a_model_for_common_downstream_tasks_v2_en.md
new file mode 100644
index 00000000000000..40a54d13e62f60
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-how_tonga_tonga_islands_fine_tune_a_model_for_common_downstream_tasks_v2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English how_tonga_tonga_islands_fine_tune_a_model_for_common_downstream_tasks_v2 BertForQuestionAnswering from Tural
+author: John Snow Labs
+name: how_tonga_tonga_islands_fine_tune_a_model_for_common_downstream_tasks_v2
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`how_tonga_tonga_islands_fine_tune_a_model_for_common_downstream_tasks_v2` is a English model originally trained by Tural.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/how_tonga_tonga_islands_fine_tune_a_model_for_common_downstream_tasks_v2_en_5.5.1_3.0_1737690576423.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/how_tonga_tonga_islands_fine_tune_a_model_for_common_downstream_tasks_v2_en_5.5.1_3.0_1737690576423.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("how_tonga_tonga_islands_fine_tune_a_model_for_common_downstream_tasks_v2","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("how_tonga_tonga_islands_fine_tune_a_model_for_common_downstream_tasks_v2", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|how_tonga_tonga_islands_fine_tune_a_model_for_common_downstream_tasks_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.8 MB|
+
+## References
+
+https://huggingface.co/Tural/How_to_fine-tune_a_model_for_common_downstream_tasks_V2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-how_tonga_tonga_islands_fine_tune_a_model_for_common_downstream_tasks_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-how_tonga_tonga_islands_fine_tune_a_model_for_common_downstream_tasks_v2_pipeline_en.md
new file mode 100644
index 00000000000000..99563131931767
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-how_tonga_tonga_islands_fine_tune_a_model_for_common_downstream_tasks_v2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English how_tonga_tonga_islands_fine_tune_a_model_for_common_downstream_tasks_v2_pipeline pipeline BertForQuestionAnswering from Tural
+author: John Snow Labs
+name: how_tonga_tonga_islands_fine_tune_a_model_for_common_downstream_tasks_v2_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`how_tonga_tonga_islands_fine_tune_a_model_for_common_downstream_tasks_v2_pipeline` is a English model originally trained by Tural.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/how_tonga_tonga_islands_fine_tune_a_model_for_common_downstream_tasks_v2_pipeline_en_5.5.1_3.0_1737690610659.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/how_tonga_tonga_islands_fine_tune_a_model_for_common_downstream_tasks_v2_pipeline_en_5.5.1_3.0_1737690610659.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("how_tonga_tonga_islands_fine_tune_a_model_for_common_downstream_tasks_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("how_tonga_tonga_islands_fine_tune_a_model_for_common_downstream_tasks_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|how_tonga_tonga_islands_fine_tune_a_model_for_common_downstream_tasks_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.8 MB|
+
+## References
+
+https://huggingface.co/Tural/How_to_fine-tune_a_model_for_common_downstream_tasks_V2
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-hub_report_20241130161450_en.md b/docs/_posts/ahmedlone127/2025-01-24-hub_report_20241130161450_en.md
new file mode 100644
index 00000000000000..450a25d01ddb6b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-hub_report_20241130161450_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English hub_report_20241130161450 MPNetForSequenceClassification from Kevinger
+author: John Snow Labs
+name: hub_report_20241130161450
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, mpnet]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hub_report_20241130161450` is a English model originally trained by Kevinger.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hub_report_20241130161450_en_5.5.1_3.0_1737711671525.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hub_report_20241130161450_en_5.5.1_3.0_1737711671525.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = MPNetForSequenceClassification.pretrained("hub_report_20241130161450","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = MPNetForSequenceClassification.pretrained("hub_report_20241130161450", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hub_report_20241130161450|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.2 MB|
+
+## References
+
+https://huggingface.co/Kevinger/Hub-Report-20241130161450
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-hub_report_20241130161450_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-hub_report_20241130161450_pipeline_en.md
new file mode 100644
index 00000000000000..bf98e2aff89c2d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-hub_report_20241130161450_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English hub_report_20241130161450_pipeline pipeline MPNetForSequenceClassification from Kevinger
+author: John Snow Labs
+name: hub_report_20241130161450_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hub_report_20241130161450_pipeline` is a English model originally trained by Kevinger.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hub_report_20241130161450_pipeline_en_5.5.1_3.0_1737711693057.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hub_report_20241130161450_pipeline_en_5.5.1_3.0_1737711693057.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("hub_report_20241130161450_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hub_report_20241130161450_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hub_report_20241130161450_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.2 MB|
+
+## References
+
+https://huggingface.co/Kevinger/Hub-Report-20241130161450
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- MPNetForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-hubert_kakeiken_w_clean_en.md b/docs/_posts/ahmedlone127/2025-01-24-hubert_kakeiken_w_clean_en.md
new file mode 100644
index 00000000000000..bf6c2611057d26
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-hubert_kakeiken_w_clean_en.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: English hubert_kakeiken_w_clean HubertForCTC from utakumi
+author: John Snow Labs
+name: hubert_kakeiken_w_clean
+date: 2025-01-24
+tags: [en, open_source, onnx, asr, hubert]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: HubertForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_kakeiken_w_clean` is a English model originally trained by utakumi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_kakeiken_w_clean_en_5.5.1_3.0_1737736887100.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_kakeiken_w_clean_en_5.5.1_3.0_1737736887100.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = HubertForCTC.pretrained("hubert_kakeiken_w_clean","en") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = HubertForCTC.pretrained("hubert_kakeiken_w_clean", "en")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hubert_kakeiken_w_clean|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|en|
+|Size:|697.9 MB|
+
+## References
+
+https://huggingface.co/utakumi/Hubert-kakeiken-W-clean
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-hubert_kakeiken_w_clean_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-hubert_kakeiken_w_clean_pipeline_en.md
new file mode 100644
index 00000000000000..7a105545a9921f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-hubert_kakeiken_w_clean_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English hubert_kakeiken_w_clean_pipeline pipeline HubertForCTC from utakumi
+author: John Snow Labs
+name: hubert_kakeiken_w_clean_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_kakeiken_w_clean_pipeline` is a English model originally trained by utakumi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_kakeiken_w_clean_pipeline_en_5.5.1_3.0_1737736927468.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_kakeiken_w_clean_pipeline_en_5.5.1_3.0_1737736927468.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("hubert_kakeiken_w_clean_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hubert_kakeiken_w_clean_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hubert_kakeiken_w_clean_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|697.9 MB|
+
+## References
+
+https://huggingface.co/utakumi/Hubert-kakeiken-W-clean
+
+## Included Models
+
+- AudioAssembler
+- HubertForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-hupunct_hu.md b/docs/_posts/ahmedlone127/2025-01-24-hupunct_hu.md
new file mode 100644
index 00000000000000..0b58068a0af6cf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-hupunct_hu.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Hungarian hupunct BertForTokenClassification from gyenist
+author: John Snow Labs
+name: hupunct
+date: 2025-01-24
+tags: [hu, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: hu
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hupunct` is a Hungarian model originally trained by gyenist.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hupunct_hu_5.5.1_3.0_1737719866450.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hupunct_hu_5.5.1_3.0_1737719866450.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("hupunct","hu") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("hupunct", "hu")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hupunct|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|hu|
+|Size:|412.5 MB|
+
+## References
+
+https://huggingface.co/gyenist/hupunct
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-hupunct_pipeline_hu.md b/docs/_posts/ahmedlone127/2025-01-24-hupunct_pipeline_hu.md
new file mode 100644
index 00000000000000..bd41c9b8e33970
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-hupunct_pipeline_hu.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Hungarian hupunct_pipeline pipeline BertForTokenClassification from gyenist
+author: John Snow Labs
+name: hupunct_pipeline
+date: 2025-01-24
+tags: [hu, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: hu
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hupunct_pipeline` is a Hungarian model originally trained by gyenist.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hupunct_pipeline_hu_5.5.1_3.0_1737719891142.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hupunct_pipeline_hu_5.5.1_3.0_1737719891142.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("hupunct_pipeline", lang = "hu")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hupunct_pipeline", lang = "hu")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hupunct_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|hu|
+|Size:|412.5 MB|
+
+## References
+
+https://huggingface.co/gyenist/hupunct
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-ibama_dataset2_teste_20250105145342_en.md b/docs/_posts/ahmedlone127/2025-01-24-ibama_dataset2_teste_20250105145342_en.md
new file mode 100644
index 00000000000000..bc94297df58143
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-ibama_dataset2_teste_20250105145342_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English ibama_dataset2_teste_20250105145342 BertForQuestionAnswering from alcalazans
+author: John Snow Labs
+name: ibama_dataset2_teste_20250105145342
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ibama_dataset2_teste_20250105145342` is a English model originally trained by alcalazans.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ibama_dataset2_teste_20250105145342_en_5.5.1_3.0_1737746803516.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ibama_dataset2_teste_20250105145342_en_5.5.1_3.0_1737746803516.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("ibama_dataset2_teste_20250105145342","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("ibama_dataset2_teste_20250105145342", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ibama_dataset2_teste_20250105145342|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|405.9 MB|
+
+## References
+
+https://huggingface.co/alcalazans/ibama_dataset2_teste_20250105145342
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-ibama_dataset2_teste_20250105145342_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-ibama_dataset2_teste_20250105145342_pipeline_en.md
new file mode 100644
index 00000000000000..5d051f023519b7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-ibama_dataset2_teste_20250105145342_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English ibama_dataset2_teste_20250105145342_pipeline pipeline BertForQuestionAnswering from alcalazans
+author: John Snow Labs
+name: ibama_dataset2_teste_20250105145342_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ibama_dataset2_teste_20250105145342_pipeline` is a English model originally trained by alcalazans.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ibama_dataset2_teste_20250105145342_pipeline_en_5.5.1_3.0_1737746836662.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ibama_dataset2_teste_20250105145342_pipeline_en_5.5.1_3.0_1737746836662.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ibama_dataset2_teste_20250105145342_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ibama_dataset2_teste_20250105145342_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ibama_dataset2_teste_20250105145342_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.0 MB|
+
+## References
+
+https://huggingface.co/alcalazans/ibama_dataset2_teste_20250105145342
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-image_classifier_swin_base_patch4_window12_384_in22k_en.md b/docs/_posts/ahmedlone127/2025-01-24-image_classifier_swin_base_patch4_window12_384_in22k_en.md
new file mode 100644
index 00000000000000..cb7f0904947ecd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-image_classifier_swin_base_patch4_window12_384_in22k_en.md
@@ -0,0 +1,96 @@
+---
+layout: model
+title: SwinForImageClassification - image_classifier_swin_base_patch4_window12_384_in22k
+author: John Snow Labs
+name: image_classifier_swin_base_patch4_window12_384_in22k
+date: 2025-01-24
+tags: [open_source, swin, image, en, english, image_classification, imagenet, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Swin model for Image Classification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.
+
+Swin Transformer was introduced in the paper [Swin Transformer: Hierarchical Vision Transformer using Shifted Windows](https://arxiv.org/abs/2103.14030) by Liu et al.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/image_classifier_swin_base_patch4_window12_384_in22k_en_5.5.1_3.0_1737715262755.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/image_classifier_swin_base_patch4_window12_384_in22k_en_5.5.1_3.0_1737715262755.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+image_assembler = ImageAssembler()\
+  .setInputCol("image")
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained("image_classifier_swin_base_patch4_window12_384_in22k", "en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+```
+```scala
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier = SwinForImageClassification
+    .pretrained("image_classifier_swin_base_patch4_window12_384_in22k", "en")
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|image_classifier_swin_base_patch4_window12_384_in22k|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|1.7 GB|
+
+## References
+
+References
+
+[https://huggingface.co/microsoft/swin-large-patch4-window12-384-in22k](https://huggingface.co/microsoft/swin-large-patch4-window12-384-in22k)
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-image_classifier_swin_base_patch4_window12_384_in22k_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-image_classifier_swin_base_patch4_window12_384_in22k_pipeline_en.md
new file mode 100644
index 00000000000000..5f499c497a374b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-image_classifier_swin_base_patch4_window12_384_in22k_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English image_classifier_swin_base_patch4_window12_384_in22k_pipeline pipeline SwinForImageClassification from microsoft
+author: John Snow Labs
+name: image_classifier_swin_base_patch4_window12_384_in22k_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`image_classifier_swin_base_patch4_window12_384_in22k_pipeline` is a English model originally trained by microsoft.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/image_classifier_swin_base_patch4_window12_384_in22k_pipeline_en_5.5.1_3.0_1737715351573.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/image_classifier_swin_base_patch4_window12_384_in22k_pipeline_en_5.5.1_3.0_1737715351573.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("image_classifier_swin_base_patch4_window12_384_in22k_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("image_classifier_swin_base_patch4_window12_384_in22k_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|image_classifier_swin_base_patch4_window12_384_in22k_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/microsoft/swin-large-patch4-window12-384-in22k
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-image_classifier_swin_tiny_patch4_window7_224_en.md b/docs/_posts/ahmedlone127/2025-01-24-image_classifier_swin_tiny_patch4_window7_224_en.md
new file mode 100644
index 00000000000000..3c97836ee1f67d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-image_classifier_swin_tiny_patch4_window7_224_en.md
@@ -0,0 +1,106 @@
+---
+layout: model
+title: SwinForImageClassification - image_classifier_swin_tiny_patch4_window7_224
+author: John Snow Labs
+name: image_classifier_swin_tiny_patch4_window7_224
+date: 2025-01-24
+tags: [open_source, swin, image, en, english, image_classification, imagenet, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Swin model for Image Classification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.
+
+Swin Transformer was introduced in the paper [Swin Transformer: Hierarchical Vision Transformer using Shifted Windows](https://arxiv.org/abs/2103.14030) by Liu et al.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/image_classifier_swin_tiny_patch4_window7_224_en_5.5.1_3.0_1737715181288.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/image_classifier_swin_tiny_patch4_window7_224_en_5.5.1_3.0_1737715181288.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained("image_classifier_swin_tiny_patch4_window7_224", "en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+```
+```scala
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier = SwinForImageClassification
+    .pretrained("image_classifier_swin_tiny_patch4_window7_224", "en")
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+```
+
+{:.nlu-block}
+```python
+import nlu
+import requests
+response = requests.get('https://raw.githubusercontent.com/JohnSnowLabs/spark-nlp/master/docs/assets/images/hen.JPEG')
+with open('hen.JPEG', 'wb') as f:
+    f.write(response.content)
+nlu.load("en.classify_image.swin.tiny").predict("hen.JPEG")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|image_classifier_swin_tiny_patch4_window7_224|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|212.1 MB|
+
+## References
+
+References
+
+[https://huggingface.co/microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224)
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-image_classifier_swin_tiny_patch4_window7_224_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-image_classifier_swin_tiny_patch4_window7_224_pipeline_en.md
new file mode 100644
index 00000000000000..1ee30b4d7907be
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-image_classifier_swin_tiny_patch4_window7_224_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English image_classifier_swin_tiny_patch4_window7_224_pipeline pipeline SwinForImageClassification from microsoft
+author: John Snow Labs
+name: image_classifier_swin_tiny_patch4_window7_224_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`image_classifier_swin_tiny_patch4_window7_224_pipeline` is a English model originally trained by microsoft.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/image_classifier_swin_tiny_patch4_window7_224_pipeline_en_5.5.1_3.0_1737715193331.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/image_classifier_swin_tiny_patch4_window7_224_pipeline_en_5.5.1_3.0_1737715193331.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("image_classifier_swin_tiny_patch4_window7_224_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("image_classifier_swin_tiny_patch4_window7_224_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|image_classifier_swin_tiny_patch4_window7_224_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|212.1 MB|
+
+## References
+
+https://huggingface.co/microsoft/swin-tiny-patch4-window7-224
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-incosai_qa_finetuned_model_en.md b/docs/_posts/ahmedlone127/2025-01-24-incosai_qa_finetuned_model_en.md
new file mode 100644
index 00000000000000..8b86c8b909e1f1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-incosai_qa_finetuned_model_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English incosai_qa_finetuned_model DistilBertForQuestionAnswering from Sai-Harsha-k
+author: John Snow Labs
+name: incosai_qa_finetuned_model
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`incosai_qa_finetuned_model` is a English model originally trained by Sai-Harsha-k.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/incosai_qa_finetuned_model_en_5.5.1_3.0_1737741260267.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/incosai_qa_finetuned_model_en_5.5.1_3.0_1737741260267.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("incosai_qa_finetuned_model","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("incosai_qa_finetuned_model", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|incosai_qa_finetuned_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Sai-Harsha-k/incosai_qa_finetuned_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-incosai_qa_finetuned_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-incosai_qa_finetuned_model_pipeline_en.md
new file mode 100644
index 00000000000000..51990be5fd99ea
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-incosai_qa_finetuned_model_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English incosai_qa_finetuned_model_pipeline pipeline DistilBertForQuestionAnswering from Sai-Harsha-k
+author: John Snow Labs
+name: incosai_qa_finetuned_model_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`incosai_qa_finetuned_model_pipeline` is a English model originally trained by Sai-Harsha-k.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/incosai_qa_finetuned_model_pipeline_en_5.5.1_3.0_1737741278504.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/incosai_qa_finetuned_model_pipeline_en_5.5.1_3.0_1737741278504.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("incosai_qa_finetuned_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("incosai_qa_finetuned_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|incosai_qa_finetuned_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Sai-Harsha-k/incosai_qa_finetuned_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-indic_bert_abusive_comments_tamil_en.md b/docs/_posts/ahmedlone127/2025-01-24-indic_bert_abusive_comments_tamil_en.md
new file mode 100644
index 00000000000000..0e28ee1dcea356
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-indic_bert_abusive_comments_tamil_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English indic_bert_abusive_comments_tamil AlbertForSequenceClassification from callmesan
+author: John Snow Labs
+name: indic_bert_abusive_comments_tamil
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, albert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indic_bert_abusive_comments_tamil` is a English model originally trained by callmesan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indic_bert_abusive_comments_tamil_en_5.5.1_3.0_1737693133342.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indic_bert_abusive_comments_tamil_en_5.5.1_3.0_1737693133342.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = AlbertForSequenceClassification.pretrained("indic_bert_abusive_comments_tamil","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = AlbertForSequenceClassification.pretrained("indic_bert_abusive_comments_tamil", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|indic_bert_abusive_comments_tamil|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|127.8 MB|
+
+## References
+
+https://huggingface.co/callmesan/indic-bert-abusive-comments-ta
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-indic_bert_abusive_comments_tamil_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-indic_bert_abusive_comments_tamil_pipeline_en.md
new file mode 100644
index 00000000000000..6020d37d3c88de
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-indic_bert_abusive_comments_tamil_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English indic_bert_abusive_comments_tamil_pipeline pipeline AlbertForSequenceClassification from callmesan
+author: John Snow Labs
+name: indic_bert_abusive_comments_tamil_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indic_bert_abusive_comments_tamil_pipeline` is a English model originally trained by callmesan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indic_bert_abusive_comments_tamil_pipeline_en_5.5.1_3.0_1737693140004.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indic_bert_abusive_comments_tamil_pipeline_en_5.5.1_3.0_1737693140004.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("indic_bert_abusive_comments_tamil_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("indic_bert_abusive_comments_tamil_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|indic_bert_abusive_comments_tamil_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|127.8 MB|
+
+## References
+
+https://huggingface.co/callmesan/indic-bert-abusive-comments-ta
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-indic_bert_hate_marathi_marh_en.md b/docs/_posts/ahmedlone127/2025-01-24-indic_bert_hate_marathi_marh_en.md
new file mode 100644
index 00000000000000..43325a50c66e09
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-indic_bert_hate_marathi_marh_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English indic_bert_hate_marathi_marh AlbertForSequenceClassification from callmesan
+author: John Snow Labs
+name: indic_bert_hate_marathi_marh
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, albert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indic_bert_hate_marathi_marh` is a English model originally trained by callmesan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indic_bert_hate_marathi_marh_en_5.5.1_3.0_1737693099171.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indic_bert_hate_marathi_marh_en_5.5.1_3.0_1737693099171.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = AlbertForSequenceClassification.pretrained("indic_bert_hate_marathi_marh","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = AlbertForSequenceClassification.pretrained("indic_bert_hate_marathi_marh", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|indic_bert_hate_marathi_marh|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|127.7 MB|
+
+## References
+
+https://huggingface.co/callmesan/indic-bert-hate-mr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-indic_bert_hate_marathi_marh_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-indic_bert_hate_marathi_marh_pipeline_en.md
new file mode 100644
index 00000000000000..1c267c50f8ded5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-indic_bert_hate_marathi_marh_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English indic_bert_hate_marathi_marh_pipeline pipeline AlbertForSequenceClassification from callmesan
+author: John Snow Labs
+name: indic_bert_hate_marathi_marh_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indic_bert_hate_marathi_marh_pipeline` is a English model originally trained by callmesan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indic_bert_hate_marathi_marh_pipeline_en_5.5.1_3.0_1737693105284.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indic_bert_hate_marathi_marh_pipeline_en_5.5.1_3.0_1737693105284.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("indic_bert_hate_marathi_marh_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("indic_bert_hate_marathi_marh_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|indic_bert_hate_marathi_marh_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|127.8 MB|
+
+## References
+
+https://huggingface.co/callmesan/indic-bert-hate-mr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-indic_bert_hinglish_binary_en.md b/docs/_posts/ahmedlone127/2025-01-24-indic_bert_hinglish_binary_en.md
new file mode 100644
index 00000000000000..57086447179e66
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-indic_bert_hinglish_binary_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English indic_bert_hinglish_binary AlbertForSequenceClassification from callmesan
+author: John Snow Labs
+name: indic_bert_hinglish_binary
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, albert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indic_bert_hinglish_binary` is a English model originally trained by callmesan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indic_bert_hinglish_binary_en_5.5.1_3.0_1737693458453.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indic_bert_hinglish_binary_en_5.5.1_3.0_1737693458453.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = AlbertForSequenceClassification.pretrained("indic_bert_hinglish_binary","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = AlbertForSequenceClassification.pretrained("indic_bert_hinglish_binary", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|indic_bert_hinglish_binary|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|127.7 MB|
+
+## References
+
+https://huggingface.co/callmesan/indic-bert-hinglish-binary
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-indic_bert_hinglish_binary_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-indic_bert_hinglish_binary_pipeline_en.md
new file mode 100644
index 00000000000000..18d304f2661887
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-indic_bert_hinglish_binary_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English indic_bert_hinglish_binary_pipeline pipeline AlbertForSequenceClassification from callmesan
+author: John Snow Labs
+name: indic_bert_hinglish_binary_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indic_bert_hinglish_binary_pipeline` is a English model originally trained by callmesan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indic_bert_hinglish_binary_pipeline_en_5.5.1_3.0_1737693464569.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indic_bert_hinglish_binary_pipeline_en_5.5.1_3.0_1737693464569.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("indic_bert_hinglish_binary_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("indic_bert_hinglish_binary_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|indic_bert_hinglish_binary_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|127.8 MB|
+
+## References
+
+https://huggingface.co/callmesan/indic-bert-hinglish-binary
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-indic_bert_roman_urdu_fine_grained_en.md b/docs/_posts/ahmedlone127/2025-01-24-indic_bert_roman_urdu_fine_grained_en.md
new file mode 100644
index 00000000000000..a0f99fc4cda1cc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-indic_bert_roman_urdu_fine_grained_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English indic_bert_roman_urdu_fine_grained AlbertForSequenceClassification from callmesan
+author: John Snow Labs
+name: indic_bert_roman_urdu_fine_grained
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, albert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indic_bert_roman_urdu_fine_grained` is a English model originally trained by callmesan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indic_bert_roman_urdu_fine_grained_en_5.5.1_3.0_1737750390494.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indic_bert_roman_urdu_fine_grained_en_5.5.1_3.0_1737750390494.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = AlbertForSequenceClassification.pretrained("indic_bert_roman_urdu_fine_grained","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = AlbertForSequenceClassification.pretrained("indic_bert_roman_urdu_fine_grained", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|indic_bert_roman_urdu_fine_grained|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|127.8 MB|
+
+## References
+
+https://huggingface.co/callmesan/indic-bert-roman-urdu-fine-grained
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-indic_bert_roman_urdu_fine_grained_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-indic_bert_roman_urdu_fine_grained_pipeline_en.md
new file mode 100644
index 00000000000000..1a42ee5f8a99bf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-indic_bert_roman_urdu_fine_grained_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English indic_bert_roman_urdu_fine_grained_pipeline pipeline AlbertForSequenceClassification from callmesan
+author: John Snow Labs
+name: indic_bert_roman_urdu_fine_grained_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indic_bert_roman_urdu_fine_grained_pipeline` is a English model originally trained by callmesan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indic_bert_roman_urdu_fine_grained_pipeline_en_5.5.1_3.0_1737750396946.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indic_bert_roman_urdu_fine_grained_pipeline_en_5.5.1_3.0_1737750396946.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("indic_bert_roman_urdu_fine_grained_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("indic_bert_roman_urdu_fine_grained_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|indic_bert_roman_urdu_fine_grained_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|127.8 MB|
+
+## References
+
+https://huggingface.co/callmesan/indic-bert-roman-urdu-fine-grained
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-indicbert_pun_detection_en.md b/docs/_posts/ahmedlone127/2025-01-24-indicbert_pun_detection_en.md
new file mode 100644
index 00000000000000..6f486ff27392dc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-indicbert_pun_detection_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English indicbert_pun_detection AlbertForSequenceClassification from likhithasapu
+author: John Snow Labs
+name: indicbert_pun_detection
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, albert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indicbert_pun_detection` is a English model originally trained by likhithasapu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indicbert_pun_detection_en_5.5.1_3.0_1737749971163.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indicbert_pun_detection_en_5.5.1_3.0_1737749971163.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = AlbertForSequenceClassification.pretrained("indicbert_pun_detection","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = AlbertForSequenceClassification.pretrained("indicbert_pun_detection", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|indicbert_pun_detection|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|127.8 MB|
+
+## References
+
+https://huggingface.co/likhithasapu/indicbert-pun-detection
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-indicbert_pun_detection_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-indicbert_pun_detection_pipeline_en.md
new file mode 100644
index 00000000000000..b7136182904d95
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-indicbert_pun_detection_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English indicbert_pun_detection_pipeline pipeline AlbertForSequenceClassification from likhithasapu
+author: John Snow Labs
+name: indicbert_pun_detection_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indicbert_pun_detection_pipeline` is a English model originally trained by likhithasapu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indicbert_pun_detection_pipeline_en_5.5.1_3.0_1737749978042.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indicbert_pun_detection_pipeline_en_5.5.1_3.0_1737749978042.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("indicbert_pun_detection_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("indicbert_pun_detection_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|indicbert_pun_detection_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|127.8 MB|
+
+## References
+
+https://huggingface.co/likhithasapu/indicbert-pun-detection
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-indobert_large_p2_finetuned_tydiqa_en.md b/docs/_posts/ahmedlone127/2025-01-24-indobert_large_p2_finetuned_tydiqa_en.md
new file mode 100644
index 00000000000000..c74d38a2a641ac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-indobert_large_p2_finetuned_tydiqa_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English indobert_large_p2_finetuned_tydiqa BertForQuestionAnswering from ageng-anugrah
+author: John Snow Labs
+name: indobert_large_p2_finetuned_tydiqa
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indobert_large_p2_finetuned_tydiqa` is a English model originally trained by ageng-anugrah.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indobert_large_p2_finetuned_tydiqa_en_5.5.1_3.0_1737738370889.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indobert_large_p2_finetuned_tydiqa_en_5.5.1_3.0_1737738370889.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("indobert_large_p2_finetuned_tydiqa","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("indobert_large_p2_finetuned_tydiqa", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|indobert_large_p2_finetuned_tydiqa|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/ageng-anugrah/indobert-large-p2-finetuned-tydiqa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-indobert_large_p2_finetuned_tydiqa_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-indobert_large_p2_finetuned_tydiqa_pipeline_en.md
new file mode 100644
index 00000000000000..87d7d6aa40c420
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-indobert_large_p2_finetuned_tydiqa_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English indobert_large_p2_finetuned_tydiqa_pipeline pipeline BertForQuestionAnswering from ageng-anugrah
+author: John Snow Labs
+name: indobert_large_p2_finetuned_tydiqa_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indobert_large_p2_finetuned_tydiqa_pipeline` is a English model originally trained by ageng-anugrah.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indobert_large_p2_finetuned_tydiqa_pipeline_en_5.5.1_3.0_1737738437565.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indobert_large_p2_finetuned_tydiqa_pipeline_en_5.5.1_3.0_1737738437565.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("indobert_large_p2_finetuned_tydiqa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("indobert_large_p2_finetuned_tydiqa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|indobert_large_p2_finetuned_tydiqa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/ageng-anugrah/indobert-large-p2-finetuned-tydiqa
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-iotnation_qa_model_2_15_bert_original_and_enawennaw_dataset_en.md b/docs/_posts/ahmedlone127/2025-01-24-iotnation_qa_model_2_15_bert_original_and_enawennaw_dataset_en.md
new file mode 100644
index 00000000000000..fa3b908d20f884
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-iotnation_qa_model_2_15_bert_original_and_enawennaw_dataset_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English iotnation_qa_model_2_15_bert_original_and_enawennaw_dataset BertForQuestionAnswering from chriskim2273
+author: John Snow Labs
+name: iotnation_qa_model_2_15_bert_original_and_enawennaw_dataset
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`iotnation_qa_model_2_15_bert_original_and_enawennaw_dataset` is a English model originally trained by chriskim2273.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/iotnation_qa_model_2_15_bert_original_and_enawennaw_dataset_en_5.5.1_3.0_1737752068487.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/iotnation_qa_model_2_15_bert_original_and_enawennaw_dataset_en_5.5.1_3.0_1737752068487.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("iotnation_qa_model_2_15_bert_original_and_enawennaw_dataset","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("iotnation_qa_model_2_15_bert_original_and_enawennaw_dataset", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|iotnation_qa_model_2_15_bert_original_and_enawennaw_dataset|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/chriskim2273/IOTNation_QA_Model_2.15_BERT_ORIGINAL_AND_UNK_DATASET
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-iotnation_qa_model_2_15_bert_original_and_enawennaw_dataset_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-iotnation_qa_model_2_15_bert_original_and_enawennaw_dataset_pipeline_en.md
new file mode 100644
index 00000000000000..1be43cc0578256
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-iotnation_qa_model_2_15_bert_original_and_enawennaw_dataset_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English iotnation_qa_model_2_15_bert_original_and_enawennaw_dataset_pipeline pipeline BertForQuestionAnswering from chriskim2273
+author: John Snow Labs
+name: iotnation_qa_model_2_15_bert_original_and_enawennaw_dataset_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`iotnation_qa_model_2_15_bert_original_and_enawennaw_dataset_pipeline` is a English model originally trained by chriskim2273.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/iotnation_qa_model_2_15_bert_original_and_enawennaw_dataset_pipeline_en_5.5.1_3.0_1737752090153.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/iotnation_qa_model_2_15_bert_original_and_enawennaw_dataset_pipeline_en_5.5.1_3.0_1737752090153.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("iotnation_qa_model_2_15_bert_original_and_enawennaw_dataset_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("iotnation_qa_model_2_15_bert_original_and_enawennaw_dataset_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|iotnation_qa_model_2_15_bert_original_and_enawennaw_dataset_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/chriskim2273/IOTNation_QA_Model_2.15_BERT_ORIGINAL_AND_UNK_DATASET
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-iotnation_qa_model_2_1_bert_original_dataset_only_en.md b/docs/_posts/ahmedlone127/2025-01-24-iotnation_qa_model_2_1_bert_original_dataset_only_en.md
new file mode 100644
index 00000000000000..59bda3f1095269
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-iotnation_qa_model_2_1_bert_original_dataset_only_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English iotnation_qa_model_2_1_bert_original_dataset_only BertForQuestionAnswering from chriskim2273
+author: John Snow Labs
+name: iotnation_qa_model_2_1_bert_original_dataset_only
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`iotnation_qa_model_2_1_bert_original_dataset_only` is a English model originally trained by chriskim2273.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/iotnation_qa_model_2_1_bert_original_dataset_only_en_5.5.1_3.0_1737751344855.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/iotnation_qa_model_2_1_bert_original_dataset_only_en_5.5.1_3.0_1737751344855.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("iotnation_qa_model_2_1_bert_original_dataset_only","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("iotnation_qa_model_2_1_bert_original_dataset_only", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|iotnation_qa_model_2_1_bert_original_dataset_only|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/chriskim2273/IOTNation_QA_Model_2.1_BERT_ORIGINAL_DATASET_ONLY
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-iotnation_qa_model_2_1_bert_original_dataset_only_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-iotnation_qa_model_2_1_bert_original_dataset_only_pipeline_en.md
new file mode 100644
index 00000000000000..8189cd5b1a8eb0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-iotnation_qa_model_2_1_bert_original_dataset_only_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English iotnation_qa_model_2_1_bert_original_dataset_only_pipeline pipeline BertForQuestionAnswering from chriskim2273
+author: John Snow Labs
+name: iotnation_qa_model_2_1_bert_original_dataset_only_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`iotnation_qa_model_2_1_bert_original_dataset_only_pipeline` is a English model originally trained by chriskim2273.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/iotnation_qa_model_2_1_bert_original_dataset_only_pipeline_en_5.5.1_3.0_1737751366676.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/iotnation_qa_model_2_1_bert_original_dataset_only_pipeline_en_5.5.1_3.0_1737751366676.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("iotnation_qa_model_2_1_bert_original_dataset_only_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("iotnation_qa_model_2_1_bert_original_dataset_only_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|iotnation_qa_model_2_1_bert_original_dataset_only_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/chriskim2273/IOTNation_QA_Model_2.1_BERT_ORIGINAL_DATASET_ONLY
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-japanese_bert_1_en.md b/docs/_posts/ahmedlone127/2025-01-24-japanese_bert_1_en.md
new file mode 100644
index 00000000000000..b9b7ade66f2dac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-japanese_bert_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English japanese_bert_1 BertEmbeddings from neody
+author: John Snow Labs
+name: japanese_bert_1
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`japanese_bert_1` is a English model originally trained by neody.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/japanese_bert_1_en_5.5.1_3.0_1737708087954.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/japanese_bert_1_en_5.5.1_3.0_1737708087954.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("japanese_bert_1","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("japanese_bert_1","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|japanese_bert_1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|253.4 MB|
+
+## References
+
+https://huggingface.co/neody/ja-bert-1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-japanese_bert_1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-japanese_bert_1_pipeline_en.md
new file mode 100644
index 00000000000000..9ada65604ba226
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-japanese_bert_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English japanese_bert_1_pipeline pipeline BertEmbeddings from neody
+author: John Snow Labs
+name: japanese_bert_1_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`japanese_bert_1_pipeline` is a English model originally trained by neody.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/japanese_bert_1_pipeline_en_5.5.1_3.0_1737708101403.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/japanese_bert_1_pipeline_en_5.5.1_3.0_1737708101403.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("japanese_bert_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("japanese_bert_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|japanese_bert_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|253.4 MB|
+
+## References
+
+https://huggingface.co/neody/ja-bert-1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-jat_gpt_en.md b/docs/_posts/ahmedlone127/2025-01-24-jat_gpt_en.md
new file mode 100644
index 00000000000000..783f808b66628f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-jat_gpt_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English jat_gpt GPT2Transformer from itsme-nishanth
+author: John Snow Labs
+name: jat_gpt
+date: 2025-01-24
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`jat_gpt` is a English model originally trained by itsme-nishanth.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/jat_gpt_en_5.5.1_3.0_1737732086252.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/jat_gpt_en_5.5.1_3.0_1737732086252.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("jat_gpt","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("jat_gpt","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|jat_gpt|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|68.0 MB|
+
+## References
+
+https://huggingface.co/itsme-nishanth/JAT-GPT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-jat_gpt_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-jat_gpt_pipeline_en.md
new file mode 100644
index 00000000000000..40064cd8f0e8f0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-jat_gpt_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English jat_gpt_pipeline pipeline GPT2Transformer from itsme-nishanth
+author: John Snow Labs
+name: jat_gpt_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`jat_gpt_pipeline` is a English model originally trained by itsme-nishanth.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/jat_gpt_pipeline_en_5.5.1_3.0_1737732089646.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/jat_gpt_pipeline_en_5.5.1_3.0_1737732089646.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("jat_gpt_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("jat_gpt_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|jat_gpt_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|68.0 MB|
+
+## References
+
+https://huggingface.co/itsme-nishanth/JAT-GPT
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-jobert_en.md b/docs/_posts/ahmedlone127/2025-01-24-jobert_en.md
new file mode 100644
index 00000000000000..88c2507d1617e1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-jobert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English jobert BertForSequenceClassification from AhmedBou
+author: John Snow Labs
+name: jobert
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`jobert` is a English model originally trained by AhmedBou.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/jobert_en_5.5.1_3.0_1737710346370.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/jobert_en_5.5.1_3.0_1737710346370.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("jobert","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("jobert", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|jobert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/AhmedBou/JoBert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-jobert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-jobert_pipeline_en.md
new file mode 100644
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@@ -0,0 +1,70 @@
+---
+layout: model
+title: English jobert_pipeline pipeline BertForSequenceClassification from AhmedBou
+author: John Snow Labs
+name: jobert_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`jobert_pipeline` is a English model originally trained by AhmedBou.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/jobert_pipeline_en_5.5.1_3.0_1737710411238.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/jobert_pipeline_en_5.5.1_3.0_1737710411238.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("jobert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("jobert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|jobert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/AhmedBou/JoBert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-judge_answer__22_deberta_v3_large_fresh_repo_en.md b/docs/_posts/ahmedlone127/2025-01-24-judge_answer__22_deberta_v3_large_fresh_repo_en.md
new file mode 100644
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@@ -0,0 +1,94 @@
+---
+layout: model
+title: English judge_answer__22_deberta_v3_large_fresh_repo DeBertaForSequenceClassification from tom-010
+author: John Snow Labs
+name: judge_answer__22_deberta_v3_large_fresh_repo
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`judge_answer__22_deberta_v3_large_fresh_repo` is a English model originally trained by tom-010.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/judge_answer__22_deberta_v3_large_fresh_repo_en_5.5.1_3.0_1737728167299.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/judge_answer__22_deberta_v3_large_fresh_repo_en_5.5.1_3.0_1737728167299.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("judge_answer__22_deberta_v3_large_fresh_repo","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("judge_answer__22_deberta_v3_large_fresh_repo", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|judge_answer__22_deberta_v3_large_fresh_repo|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/tom-010/judge_answer__22_deberta_v3_large_fresh_repo
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-judge_answer__22_deberta_v3_large_fresh_repo_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-judge_answer__22_deberta_v3_large_fresh_repo_pipeline_en.md
new file mode 100644
index 00000000000000..b14bb08a3562cb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-judge_answer__22_deberta_v3_large_fresh_repo_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English judge_answer__22_deberta_v3_large_fresh_repo_pipeline pipeline DeBertaForSequenceClassification from tom-010
+author: John Snow Labs
+name: judge_answer__22_deberta_v3_large_fresh_repo_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`judge_answer__22_deberta_v3_large_fresh_repo_pipeline` is a English model originally trained by tom-010.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/judge_answer__22_deberta_v3_large_fresh_repo_pipeline_en_5.5.1_3.0_1737728264386.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/judge_answer__22_deberta_v3_large_fresh_repo_pipeline_en_5.5.1_3.0_1737728264386.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("judge_answer__22_deberta_v3_large_fresh_repo_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("judge_answer__22_deberta_v3_large_fresh_repo_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|judge_answer__22_deberta_v3_large_fresh_repo_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/tom-010/judge_answer__22_deberta_v3_large_fresh_repo
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-kailas_en.md b/docs/_posts/ahmedlone127/2025-01-24-kailas_en.md
new file mode 100644
index 00000000000000..fd454b7aed0790
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-kailas_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English kailas RoBertaForTokenClassification from adsabs
+author: John Snow Labs
+name: kailas
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kailas` is a English model originally trained by adsabs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kailas_en_5.5.1_3.0_1737686734853.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kailas_en_5.5.1_3.0_1737686734853.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("kailas","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("kailas", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|kailas|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|472.8 MB|
+
+## References
+
+https://huggingface.co/adsabs/KAILAS
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-kailas_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-kailas_pipeline_en.md
new file mode 100644
index 00000000000000..547a3d3aaceffa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-kailas_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English kailas_pipeline pipeline RoBertaForTokenClassification from adsabs
+author: John Snow Labs
+name: kailas_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kailas_pipeline` is a English model originally trained by adsabs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kailas_pipeline_en_5.5.1_3.0_1737686759587.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kailas_pipeline_en_5.5.1_3.0_1737686759587.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("kailas_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("kailas_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|kailas_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|472.8 MB|
+
+## References
+
+https://huggingface.co/adsabs/KAILAS
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-kateai50m_en.md b/docs/_posts/ahmedlone127/2025-01-24-kateai50m_en.md
new file mode 100644
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--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-kateai50m_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English kateai50m GPT2Transformer from Sparkoo
+author: John Snow Labs
+name: kateai50m
+date: 2025-01-24
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kateai50m` is a English model originally trained by Sparkoo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kateai50m_en_5.5.1_3.0_1737718239614.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kateai50m_en_5.5.1_3.0_1737718239614.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("kateai50m","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("kateai50m","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|kateai50m|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|169.2 MB|
+
+## References
+
+https://huggingface.co/Sparkoo/KateAI50m
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-kateai50m_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-kateai50m_pipeline_en.md
new file mode 100644
index 00000000000000..64599c538c1d04
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-kateai50m_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English kateai50m_pipeline pipeline GPT2Transformer from Sparkoo
+author: John Snow Labs
+name: kateai50m_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kateai50m_pipeline` is a English model originally trained by Sparkoo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kateai50m_pipeline_en_5.5.1_3.0_1737718258673.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kateai50m_pipeline_en_5.5.1_3.0_1737718258673.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("kateai50m_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("kateai50m_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|kateai50m_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|169.2 MB|
+
+## References
+
+https://huggingface.co/Sparkoo/KateAI50m
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-kia_qa_model_en.md b/docs/_posts/ahmedlone127/2025-01-24-kia_qa_model_en.md
new file mode 100644
index 00000000000000..05f57c8f8c4c31
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-kia_qa_model_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English kia_qa_model BertForQuestionAnswering from YogaCr
+author: John Snow Labs
+name: kia_qa_model
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kia_qa_model` is a English model originally trained by YogaCr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kia_qa_model_en_5.5.1_3.0_1737751658731.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kia_qa_model_en_5.5.1_3.0_1737751658731.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("kia_qa_model","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("kia_qa_model", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|kia_qa_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|411.7 MB|
+
+## References
+
+https://huggingface.co/YogaCr/kia-qa-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-kia_qa_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-kia_qa_model_pipeline_en.md
new file mode 100644
index 00000000000000..9f30c4f7e8a989
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-kia_qa_model_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English kia_qa_model_pipeline pipeline BertForQuestionAnswering from YogaCr
+author: John Snow Labs
+name: kia_qa_model_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kia_qa_model_pipeline` is a English model originally trained by YogaCr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kia_qa_model_pipeline_en_5.5.1_3.0_1737751681009.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kia_qa_model_pipeline_en_5.5.1_3.0_1737751681009.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("kia_qa_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("kia_qa_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|kia_qa_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|411.7 MB|
+
+## References
+
+https://huggingface.co/YogaCr/kia-qa-model
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-knesset_dictabert_he.md b/docs/_posts/ahmedlone127/2025-01-24-knesset_dictabert_he.md
new file mode 100644
index 00000000000000..d49b1a6831f9a8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-knesset_dictabert_he.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Hebrew knesset_dictabert BertEmbeddings from GiliGold
+author: John Snow Labs
+name: knesset_dictabert
+date: 2025-01-24
+tags: [he, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: he
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`knesset_dictabert` is a Hebrew model originally trained by GiliGold.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/knesset_dictabert_he_5.5.1_3.0_1737707903839.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/knesset_dictabert_he_5.5.1_3.0_1737707903839.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("knesset_dictabert","he") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("knesset_dictabert","he") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|knesset_dictabert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|he|
+|Size:|689.1 MB|
+
+## References
+
+https://huggingface.co/GiliGold/Knesset-DictaBERT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-knesset_dictabert_pipeline_he.md b/docs/_posts/ahmedlone127/2025-01-24-knesset_dictabert_pipeline_he.md
new file mode 100644
index 00000000000000..f146d50f0cd62c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-knesset_dictabert_pipeline_he.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Hebrew knesset_dictabert_pipeline pipeline BertEmbeddings from GiliGold
+author: John Snow Labs
+name: knesset_dictabert_pipeline
+date: 2025-01-24
+tags: [he, open_source, pipeline, onnx]
+task: Embeddings
+language: he
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`knesset_dictabert_pipeline` is a Hebrew model originally trained by GiliGold.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/knesset_dictabert_pipeline_he_5.5.1_3.0_1737707939916.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/knesset_dictabert_pipeline_he_5.5.1_3.0_1737707939916.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("knesset_dictabert_pipeline", lang = "he")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("knesset_dictabert_pipeline", lang = "he")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|knesset_dictabert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|he|
+|Size:|689.1 MB|
+
+## References
+
+https://huggingface.co/GiliGold/Knesset-DictaBERT
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-l1_classifier_transliteration_en.md b/docs/_posts/ahmedlone127/2025-01-24-l1_classifier_transliteration_en.md
new file mode 100644
index 00000000000000..f1ffed775ded90
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-l1_classifier_transliteration_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English l1_classifier_transliteration XlmRoBertaForSequenceClassification from Zlovoblachko
+author: John Snow Labs
+name: l1_classifier_transliteration
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`l1_classifier_transliteration` is a English model originally trained by Zlovoblachko.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/l1_classifier_transliteration_en_5.5.1_3.0_1737714084761.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/l1_classifier_transliteration_en_5.5.1_3.0_1737714084761.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("l1_classifier_transliteration","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("l1_classifier_transliteration", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|l1_classifier_transliteration|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|801.1 MB|
+
+## References
+
+https://huggingface.co/Zlovoblachko/L1-classifier-Transliteration
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-l1_classifier_transliteration_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-l1_classifier_transliteration_pipeline_en.md
new file mode 100644
index 00000000000000..b513d46aea2cfd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-l1_classifier_transliteration_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English l1_classifier_transliteration_pipeline pipeline XlmRoBertaForSequenceClassification from Zlovoblachko
+author: John Snow Labs
+name: l1_classifier_transliteration_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`l1_classifier_transliteration_pipeline` is a English model originally trained by Zlovoblachko.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/l1_classifier_transliteration_pipeline_en_5.5.1_3.0_1737714215776.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/l1_classifier_transliteration_pipeline_en_5.5.1_3.0_1737714215776.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("l1_classifier_transliteration_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("l1_classifier_transliteration_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|l1_classifier_transliteration_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|801.1 MB|
+
+## References
+
+https://huggingface.co/Zlovoblachko/L1-classifier-Transliteration
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-labse_english_russian_chemprot_ner_en.md b/docs/_posts/ahmedlone127/2025-01-24-labse_english_russian_chemprot_ner_en.md
new file mode 100644
index 00000000000000..de519ee49b2eab
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-labse_english_russian_chemprot_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English labse_english_russian_chemprot_ner BertForTokenClassification from la1login
+author: John Snow Labs
+name: labse_english_russian_chemprot_ner
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`labse_english_russian_chemprot_ner` is a English model originally trained by la1login.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/labse_english_russian_chemprot_ner_en_5.5.1_3.0_1737719883559.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/labse_english_russian_chemprot_ner_en_5.5.1_3.0_1737719883559.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("labse_english_russian_chemprot_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("labse_english_russian_chemprot_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|labse_english_russian_chemprot_ner|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|480.4 MB|
+
+## References
+
+https://huggingface.co/la1login/labse_en_ru_chemprot_ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-labse_english_russian_chemprot_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-labse_english_russian_chemprot_ner_pipeline_en.md
new file mode 100644
index 00000000000000..82b117b52563c3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-labse_english_russian_chemprot_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English labse_english_russian_chemprot_ner_pipeline pipeline BertForTokenClassification from la1login
+author: John Snow Labs
+name: labse_english_russian_chemprot_ner_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`labse_english_russian_chemprot_ner_pipeline` is a English model originally trained by la1login.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/labse_english_russian_chemprot_ner_pipeline_en_5.5.1_3.0_1737719908758.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/labse_english_russian_chemprot_ner_pipeline_en_5.5.1_3.0_1737719908758.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("labse_english_russian_chemprot_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("labse_english_russian_chemprot_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|labse_english_russian_chemprot_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|480.4 MB|
+
+## References
+
+https://huggingface.co/la1login/labse_en_ru_chemprot_ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-lease_slovak_ner_non_emph_bsci_en.md b/docs/_posts/ahmedlone127/2025-01-24-lease_slovak_ner_non_emph_bsci_en.md
new file mode 100644
index 00000000000000..887f5e4b64566f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-lease_slovak_ner_non_emph_bsci_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English lease_slovak_ner_non_emph_bsci RoBertaForTokenClassification from ttnksm
+author: John Snow Labs
+name: lease_slovak_ner_non_emph_bsci
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lease_slovak_ner_non_emph_bsci` is a English model originally trained by ttnksm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lease_slovak_ner_non_emph_bsci_en_5.5.1_3.0_1737702922977.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lease_slovak_ner_non_emph_bsci_en_5.5.1_3.0_1737702922977.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("lease_slovak_ner_non_emph_bsci","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("lease_slovak_ner_non_emph_bsci", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lease_slovak_ner_non_emph_bsci|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|438.9 MB|
+
+## References
+
+https://huggingface.co/ttnksm/lease_sk_ner_non_emph_bsci
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-lease_slovak_ner_non_emph_bsci_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-lease_slovak_ner_non_emph_bsci_pipeline_en.md
new file mode 100644
index 00000000000000..0ec8d9705825b4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-lease_slovak_ner_non_emph_bsci_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English lease_slovak_ner_non_emph_bsci_pipeline pipeline RoBertaForTokenClassification from ttnksm
+author: John Snow Labs
+name: lease_slovak_ner_non_emph_bsci_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lease_slovak_ner_non_emph_bsci_pipeline` is a English model originally trained by ttnksm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lease_slovak_ner_non_emph_bsci_pipeline_en_5.5.1_3.0_1737702954573.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lease_slovak_ner_non_emph_bsci_pipeline_en_5.5.1_3.0_1737702954573.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("lease_slovak_ner_non_emph_bsci_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("lease_slovak_ner_non_emph_bsci_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lease_slovak_ner_non_emph_bsci_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|438.9 MB|
+
+## References
+
+https://huggingface.co/ttnksm/lease_sk_ner_non_emph_bsci
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-lee_qa_en.md b/docs/_posts/ahmedlone127/2025-01-24-lee_qa_en.md
new file mode 100644
index 00000000000000..f973df440a4bfb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-lee_qa_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English lee_qa BertForQuestionAnswering from Seogmin
+author: John Snow Labs
+name: lee_qa
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lee_qa` is a English model originally trained by Seogmin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lee_qa_en_5.5.1_3.0_1737747653819.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lee_qa_en_5.5.1_3.0_1737747653819.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("lee_qa","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("lee_qa", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lee_qa|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|412.4 MB|
+
+## References
+
+https://huggingface.co/Seogmin/lee-QA
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-lee_qa_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-lee_qa_pipeline_en.md
new file mode 100644
index 00000000000000..fabf7ced90f17f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-lee_qa_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English lee_qa_pipeline pipeline BertForQuestionAnswering from Seogmin
+author: John Snow Labs
+name: lee_qa_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lee_qa_pipeline` is a English model originally trained by Seogmin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lee_qa_pipeline_en_5.5.1_3.0_1737747675805.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lee_qa_pipeline_en_5.5.1_3.0_1737747675805.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("lee_qa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("lee_qa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lee_qa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|412.4 MB|
+
+## References
+
+https://huggingface.co/Seogmin/lee-QA
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-levit_128s_en.md b/docs/_posts/ahmedlone127/2025-01-24-levit_128s_en.md
new file mode 100644
index 00000000000000..464c6d5ec58d00
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-levit_128s_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English levit_128s ViTForImageClassification from facebook
+author: John Snow Labs
+name: levit_128s
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`levit_128s` is a English model originally trained by facebook.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/levit_128s_en_5.5.1_3.0_1737743969869.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/levit_128s_en_5.5.1_3.0_1737743969869.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""levit_128s","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("levit_128s","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|levit_128s|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|29.4 MB|
+
+## References
+
+https://huggingface.co/facebook/levit-128S
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-levit_128s_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-levit_128s_pipeline_en.md
new file mode 100644
index 00000000000000..4ad4e6fa7ac870
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-levit_128s_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English levit_128s_pipeline pipeline ViTForImageClassification from facebook
+author: John Snow Labs
+name: levit_128s_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`levit_128s_pipeline` is a English model originally trained by facebook.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/levit_128s_pipeline_en_5.5.1_3.0_1737743971697.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/levit_128s_pipeline_en_5.5.1_3.0_1737743971697.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("levit_128s_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("levit_128s_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|levit_128s_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|29.4 MB|
+
+## References
+
+https://huggingface.co/facebook/levit-128S
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-lm_giga_en.md b/docs/_posts/ahmedlone127/2025-01-24-lm_giga_en.md
new file mode 100644
index 00000000000000..0bbe168ab8c5b5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-lm_giga_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English lm_giga GPT2Transformer from anonsubms
+author: John Snow Labs
+name: lm_giga
+date: 2025-01-24
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lm_giga` is a English model originally trained by anonsubms.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lm_giga_en_5.5.1_3.0_1737732583033.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lm_giga_en_5.5.1_3.0_1737732583033.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("lm_giga","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("lm_giga","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lm_giga|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|308.4 MB|
+
+## References
+
+https://huggingface.co/anonsubms/lm_giga
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-lm_giga_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-lm_giga_pipeline_en.md
new file mode 100644
index 00000000000000..8d7f586863c3a7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-lm_giga_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English lm_giga_pipeline pipeline GPT2Transformer from anonsubms
+author: John Snow Labs
+name: lm_giga_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lm_giga_pipeline` is a English model originally trained by anonsubms.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lm_giga_pipeline_en_5.5.1_3.0_1737732599108.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lm_giga_pipeline_en_5.5.1_3.0_1737732599108.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("lm_giga_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("lm_giga_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lm_giga_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|308.4 MB|
+
+## References
+
+https://huggingface.co/anonsubms/lm_giga
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-long_bert_2024_05_25_12_02_52_en.md b/docs/_posts/ahmedlone127/2025-01-24-long_bert_2024_05_25_12_02_52_en.md
new file mode 100644
index 00000000000000..88b040f87bd7a2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-long_bert_2024_05_25_12_02_52_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English long_bert_2024_05_25_12_02_52 BertEmbeddings from andersonbcdefg
+author: John Snow Labs
+name: long_bert_2024_05_25_12_02_52
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`long_bert_2024_05_25_12_02_52` is a English model originally trained by andersonbcdefg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/long_bert_2024_05_25_12_02_52_en_5.5.1_3.0_1737742023585.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/long_bert_2024_05_25_12_02_52_en_5.5.1_3.0_1737742023585.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("long_bert_2024_05_25_12_02_52","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("long_bert_2024_05_25_12_02_52","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|long_bert_2024_05_25_12_02_52|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|17.4 MB|
+
+## References
+
+https://huggingface.co/andersonbcdefg/long-bert-2024-05-25_12-02-52
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-long_bert_2024_05_25_12_02_52_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-long_bert_2024_05_25_12_02_52_pipeline_en.md
new file mode 100644
index 00000000000000..bc4975eb41c304
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-long_bert_2024_05_25_12_02_52_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English long_bert_2024_05_25_12_02_52_pipeline pipeline BertEmbeddings from andersonbcdefg
+author: John Snow Labs
+name: long_bert_2024_05_25_12_02_52_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`long_bert_2024_05_25_12_02_52_pipeline` is a English model originally trained by andersonbcdefg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/long_bert_2024_05_25_12_02_52_pipeline_en_5.5.1_3.0_1737742024790.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/long_bert_2024_05_25_12_02_52_pipeline_en_5.5.1_3.0_1737742024790.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("long_bert_2024_05_25_12_02_52_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("long_bert_2024_05_25_12_02_52_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|long_bert_2024_05_25_12_02_52_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|17.5 MB|
+
+## References
+
+https://huggingface.co/andersonbcdefg/long-bert-2024-05-25_12-02-52
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-low11_en.md b/docs/_posts/ahmedlone127/2025-01-24-low11_en.md
new file mode 100644
index 00000000000000..9b63e10da0d836
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-low11_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English low11 BertForQuestionAnswering from Jing24
+author: John Snow Labs
+name: low11
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`low11` is a English model originally trained by Jing24.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/low11_en_5.5.1_3.0_1737756719621.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/low11_en_5.5.1_3.0_1737756719621.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("low11","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("low11", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|low11|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/Jing24/low11
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-low11_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-low11_pipeline_en.md
new file mode 100644
index 00000000000000..79e36858e17d59
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-low11_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English low11_pipeline pipeline BertForQuestionAnswering from Jing24
+author: John Snow Labs
+name: low11_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`low11_pipeline` is a English model originally trained by Jing24.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/low11_pipeline_en_5.5.1_3.0_1737756741091.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/low11_pipeline_en_5.5.1_3.0_1737756741091.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("low11_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("low11_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|low11_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/Jing24/low11
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-ltgbert_qa_en.md b/docs/_posts/ahmedlone127/2025-01-24-ltgbert_qa_en.md
new file mode 100644
index 00000000000000..a2774da5964cb1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-ltgbert_qa_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English ltgbert_qa BertForQuestionAnswering from amroadel1
+author: John Snow Labs
+name: ltgbert_qa
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ltgbert_qa` is a English model originally trained by amroadel1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ltgbert_qa_en_5.5.1_3.0_1737750939504.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ltgbert_qa_en_5.5.1_3.0_1737750939504.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("ltgbert_qa","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("ltgbert_qa", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ltgbert_qa|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|295.5 MB|
+
+## References
+
+https://huggingface.co/amroadel1/ltgbert-qa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-ltgbert_qa_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-ltgbert_qa_pipeline_en.md
new file mode 100644
index 00000000000000..350a4206379d4b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-ltgbert_qa_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English ltgbert_qa_pipeline pipeline BertForQuestionAnswering from amroadel1
+author: John Snow Labs
+name: ltgbert_qa_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ltgbert_qa_pipeline` is a English model originally trained by amroadel1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ltgbert_qa_pipeline_en_5.5.1_3.0_1737750955300.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ltgbert_qa_pipeline_en_5.5.1_3.0_1737750955300.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ltgbert_qa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ltgbert_qa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ltgbert_qa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|295.5 MB|
+
+## References
+
+https://huggingface.co/amroadel1/ltgbert-qa
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-malay_sentiment2_en.md b/docs/_posts/ahmedlone127/2025-01-24-malay_sentiment2_en.md
new file mode 100644
index 00000000000000..a1d524cd57872d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-malay_sentiment2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English malay_sentiment2 XlmRoBertaForSequenceClassification from afiqlol
+author: John Snow Labs
+name: malay_sentiment2
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`malay_sentiment2` is a English model originally trained by afiqlol.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/malay_sentiment2_en_5.5.1_3.0_1737713893046.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/malay_sentiment2_en_5.5.1_3.0_1737713893046.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("malay_sentiment2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("malay_sentiment2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|malay_sentiment2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/afiqlol/Malay-Sentiment2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-malay_sentiment2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-malay_sentiment2_pipeline_en.md
new file mode 100644
index 00000000000000..64c658674f9cce
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-malay_sentiment2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English malay_sentiment2_pipeline pipeline XlmRoBertaForSequenceClassification from afiqlol
+author: John Snow Labs
+name: malay_sentiment2_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`malay_sentiment2_pipeline` is a English model originally trained by afiqlol.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/malay_sentiment2_pipeline_en_5.5.1_3.0_1737713948108.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/malay_sentiment2_pipeline_en_5.5.1_3.0_1737713948108.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("malay_sentiment2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("malay_sentiment2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|malay_sentiment2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/afiqlol/Malay-Sentiment2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-malayalam_bert_fakenews_dravidian_en.md b/docs/_posts/ahmedlone127/2025-01-24-malayalam_bert_fakenews_dravidian_en.md
new file mode 100644
index 00000000000000..b8aab8a1c5a200
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-malayalam_bert_fakenews_dravidian_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English malayalam_bert_fakenews_dravidian BertForSequenceClassification from mdosama39
+author: John Snow Labs
+name: malayalam_bert_fakenews_dravidian
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`malayalam_bert_fakenews_dravidian` is a English model originally trained by mdosama39.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/malayalam_bert_fakenews_dravidian_en_5.5.1_3.0_1737711067269.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/malayalam_bert_fakenews_dravidian_en_5.5.1_3.0_1737711067269.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("malayalam_bert_fakenews_dravidian","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("malayalam_bert_fakenews_dravidian", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|malayalam_bert_fakenews_dravidian|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|892.7 MB|
+
+## References
+
+https://huggingface.co/mdosama39/malayalam-bert-FakeNews-Dravidian
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-malayalam_bert_fakenews_dravidian_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-malayalam_bert_fakenews_dravidian_pipeline_en.md
new file mode 100644
index 00000000000000..a89b792b206704
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-malayalam_bert_fakenews_dravidian_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English malayalam_bert_fakenews_dravidian_pipeline pipeline BertForSequenceClassification from mdosama39
+author: John Snow Labs
+name: malayalam_bert_fakenews_dravidian_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`malayalam_bert_fakenews_dravidian_pipeline` is a English model originally trained by mdosama39.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/malayalam_bert_fakenews_dravidian_pipeline_en_5.5.1_3.0_1737711115577.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/malayalam_bert_fakenews_dravidian_pipeline_en_5.5.1_3.0_1737711115577.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("malayalam_bert_fakenews_dravidian_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("malayalam_bert_fakenews_dravidian_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|malayalam_bert_fakenews_dravidian_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|892.8 MB|
+
+## References
+
+https://huggingface.co/mdosama39/malayalam-bert-FakeNews-Dravidian
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-man_woman_face_image_detection_en.md b/docs/_posts/ahmedlone127/2025-01-24-man_woman_face_image_detection_en.md
new file mode 100644
index 00000000000000..b19f2919c90d36
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-man_woman_face_image_detection_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English man_woman_face_image_detection ViTForImageClassification from dima806
+author: John Snow Labs
+name: man_woman_face_image_detection
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`man_woman_face_image_detection` is a English model originally trained by dima806.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/man_woman_face_image_detection_en_5.5.1_3.0_1737744309532.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/man_woman_face_image_detection_en_5.5.1_3.0_1737744309532.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""man_woman_face_image_detection","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("man_woman_face_image_detection","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|man_woman_face_image_detection|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/dima806/man_woman_face_image_detection
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-man_woman_face_image_detection_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-man_woman_face_image_detection_pipeline_en.md
new file mode 100644
index 00000000000000..c3fdb843a46fb9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-man_woman_face_image_detection_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English man_woman_face_image_detection_pipeline pipeline ViTForImageClassification from dima806
+author: John Snow Labs
+name: man_woman_face_image_detection_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`man_woman_face_image_detection_pipeline` is a English model originally trained by dima806.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/man_woman_face_image_detection_pipeline_en_5.5.1_3.0_1737744327552.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/man_woman_face_image_detection_pipeline_en_5.5.1_3.0_1737744327552.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("man_woman_face_image_detection_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("man_woman_face_image_detection_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|man_woman_face_image_detection_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/dima806/man_woman_face_image_detection
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-mbert_bengali_tydiqa_qa_finetuned_rqa_factoid_bn.md b/docs/_posts/ahmedlone127/2025-01-24-mbert_bengali_tydiqa_qa_finetuned_rqa_factoid_bn.md
new file mode 100644
index 00000000000000..64e377992f5a1f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-mbert_bengali_tydiqa_qa_finetuned_rqa_factoid_bn.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Bengali mbert_bengali_tydiqa_qa_finetuned_rqa_factoid BertForQuestionAnswering from AsifAbrar6
+author: John Snow Labs
+name: mbert_bengali_tydiqa_qa_finetuned_rqa_factoid
+date: 2025-01-24
+tags: [bn, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: bn
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mbert_bengali_tydiqa_qa_finetuned_rqa_factoid` is a Bengali model originally trained by AsifAbrar6.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mbert_bengali_tydiqa_qa_finetuned_rqa_factoid_bn_5.5.1_3.0_1737757906287.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mbert_bengali_tydiqa_qa_finetuned_rqa_factoid_bn_5.5.1_3.0_1737757906287.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("mbert_bengali_tydiqa_qa_finetuned_rqa_factoid","bn") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("mbert_bengali_tydiqa_qa_finetuned_rqa_factoid", "bn")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mbert_bengali_tydiqa_qa_finetuned_rqa_factoid|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|bn|
+|Size:|625.5 MB|
+
+## References
+
+https://huggingface.co/AsifAbrar6/mbert-bengali-tydiqa-qa-finetuned-RQA-factoid
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-mbert_bengali_tydiqa_qa_finetuned_rqa_factoid_pipeline_bn.md b/docs/_posts/ahmedlone127/2025-01-24-mbert_bengali_tydiqa_qa_finetuned_rqa_factoid_pipeline_bn.md
new file mode 100644
index 00000000000000..61589ab304427d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-mbert_bengali_tydiqa_qa_finetuned_rqa_factoid_pipeline_bn.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Bengali mbert_bengali_tydiqa_qa_finetuned_rqa_factoid_pipeline pipeline BertForQuestionAnswering from AsifAbrar6
+author: John Snow Labs
+name: mbert_bengali_tydiqa_qa_finetuned_rqa_factoid_pipeline
+date: 2025-01-24
+tags: [bn, open_source, pipeline, onnx]
+task: Question Answering
+language: bn
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mbert_bengali_tydiqa_qa_finetuned_rqa_factoid_pipeline` is a Bengali model originally trained by AsifAbrar6.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mbert_bengali_tydiqa_qa_finetuned_rqa_factoid_pipeline_bn_5.5.1_3.0_1737757942106.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mbert_bengali_tydiqa_qa_finetuned_rqa_factoid_pipeline_bn_5.5.1_3.0_1737757942106.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mbert_bengali_tydiqa_qa_finetuned_rqa_factoid_pipeline", lang = "bn")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mbert_bengali_tydiqa_qa_finetuned_rqa_factoid_pipeline", lang = "bn")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mbert_bengali_tydiqa_qa_finetuned_rqa_factoid_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|bn|
+|Size:|625.5 MB|
+
+## References
+
+https://huggingface.co/AsifAbrar6/mbert-bengali-tydiqa-qa-finetuned-RQA-factoid
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-mbert_hindi_telugu_mlm_squad_tydi_mlqa_hi.md b/docs/_posts/ahmedlone127/2025-01-24-mbert_hindi_telugu_mlm_squad_tydi_mlqa_hi.md
new file mode 100644
index 00000000000000..ca8e60540ebc45
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-mbert_hindi_telugu_mlm_squad_tydi_mlqa_hi.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Hindi mbert_hindi_telugu_mlm_squad_tydi_mlqa BertForQuestionAnswering from hapandya
+author: John Snow Labs
+name: mbert_hindi_telugu_mlm_squad_tydi_mlqa
+date: 2025-01-24
+tags: [hi, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: hi
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mbert_hindi_telugu_mlm_squad_tydi_mlqa` is a Hindi model originally trained by hapandya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mbert_hindi_telugu_mlm_squad_tydi_mlqa_hi_5.5.1_3.0_1737690478664.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mbert_hindi_telugu_mlm_squad_tydi_mlqa_hi_5.5.1_3.0_1737690478664.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("mbert_hindi_telugu_mlm_squad_tydi_mlqa","hi") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("mbert_hindi_telugu_mlm_squad_tydi_mlqa", "hi")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mbert_hindi_telugu_mlm_squad_tydi_mlqa|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|hi|
+|Size:|663.1 MB|
+
+## References
+
+https://huggingface.co/hapandya/mBERT-hi-te-MLM-SQuAD-TyDi-MLQA
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-mbert_hindi_telugu_mlm_squad_tydi_mlqa_pipeline_hi.md b/docs/_posts/ahmedlone127/2025-01-24-mbert_hindi_telugu_mlm_squad_tydi_mlqa_pipeline_hi.md
new file mode 100644
index 00000000000000..2fabade9158abb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-mbert_hindi_telugu_mlm_squad_tydi_mlqa_pipeline_hi.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Hindi mbert_hindi_telugu_mlm_squad_tydi_mlqa_pipeline pipeline BertForQuestionAnswering from hapandya
+author: John Snow Labs
+name: mbert_hindi_telugu_mlm_squad_tydi_mlqa_pipeline
+date: 2025-01-24
+tags: [hi, open_source, pipeline, onnx]
+task: Question Answering
+language: hi
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mbert_hindi_telugu_mlm_squad_tydi_mlqa_pipeline` is a Hindi model originally trained by hapandya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mbert_hindi_telugu_mlm_squad_tydi_mlqa_pipeline_hi_5.5.1_3.0_1737690520714.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mbert_hindi_telugu_mlm_squad_tydi_mlqa_pipeline_hi_5.5.1_3.0_1737690520714.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mbert_hindi_telugu_mlm_squad_tydi_mlqa_pipeline", lang = "hi")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mbert_hindi_telugu_mlm_squad_tydi_mlqa_pipeline", lang = "hi")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mbert_hindi_telugu_mlm_squad_tydi_mlqa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|hi|
+|Size:|663.1 MB|
+
+## References
+
+https://huggingface.co/hapandya/mBERT-hi-te-MLM-SQuAD-TyDi-MLQA
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-mbert_indosquadv2_1691852823_8_2e_06_0_01_5_en.md b/docs/_posts/ahmedlone127/2025-01-24-mbert_indosquadv2_1691852823_8_2e_06_0_01_5_en.md
new file mode 100644
index 00000000000000..3306719a7d41ed
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-mbert_indosquadv2_1691852823_8_2e_06_0_01_5_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mbert_indosquadv2_1691852823_8_2e_06_0_01_5 BertForQuestionAnswering from rizquuula
+author: John Snow Labs
+name: mbert_indosquadv2_1691852823_8_2e_06_0_01_5
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mbert_indosquadv2_1691852823_8_2e_06_0_01_5` is a English model originally trained by rizquuula.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mbert_indosquadv2_1691852823_8_2e_06_0_01_5_en_5.5.1_3.0_1737747120886.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mbert_indosquadv2_1691852823_8_2e_06_0_01_5_en_5.5.1_3.0_1737747120886.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("mbert_indosquadv2_1691852823_8_2e_06_0_01_5","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("mbert_indosquadv2_1691852823_8_2e_06_0_01_5", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mbert_indosquadv2_1691852823_8_2e_06_0_01_5|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/rizquuula/mBERT-IndoSQuADv2_1691852823-8-2e-06-0.01-5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-mbert_indosquadv2_1691852823_8_2e_06_0_01_5_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-mbert_indosquadv2_1691852823_8_2e_06_0_01_5_pipeline_en.md
new file mode 100644
index 00000000000000..49a434e035bf18
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-mbert_indosquadv2_1691852823_8_2e_06_0_01_5_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mbert_indosquadv2_1691852823_8_2e_06_0_01_5_pipeline pipeline BertForQuestionAnswering from rizquuula
+author: John Snow Labs
+name: mbert_indosquadv2_1691852823_8_2e_06_0_01_5_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mbert_indosquadv2_1691852823_8_2e_06_0_01_5_pipeline` is a English model originally trained by rizquuula.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mbert_indosquadv2_1691852823_8_2e_06_0_01_5_pipeline_en_5.5.1_3.0_1737747156452.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mbert_indosquadv2_1691852823_8_2e_06_0_01_5_pipeline_en_5.5.1_3.0_1737747156452.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mbert_indosquadv2_1691852823_8_2e_06_0_01_5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mbert_indosquadv2_1691852823_8_2e_06_0_01_5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mbert_indosquadv2_1691852823_8_2e_06_0_01_5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/rizquuula/mBERT-IndoSQuADv2_1691852823-8-2e-06-0.01-5
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-med2_4_en.md b/docs/_posts/ahmedlone127/2025-01-24-med2_4_en.md
new file mode 100644
index 00000000000000..365a703b9b134d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-med2_4_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English med2_4 GPT2Transformer from umar-naveed
+author: John Snow Labs
+name: med2_4
+date: 2025-01-24
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`med2_4` is a English model originally trained by umar-naveed.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/med2_4_en_5.5.1_3.0_1737732286860.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/med2_4_en_5.5.1_3.0_1737732286860.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("med2_4","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("med2_4","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|med2_4|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.2 MB|
+
+## References
+
+https://huggingface.co/umar-naveed/med2.4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-med2_4_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-med2_4_pipeline_en.md
new file mode 100644
index 00000000000000..2fabe89ea6386d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-med2_4_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English med2_4_pipeline pipeline GPT2Transformer from umar-naveed
+author: John Snow Labs
+name: med2_4_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`med2_4_pipeline` is a English model originally trained by umar-naveed.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/med2_4_pipeline_en_5.5.1_3.0_1737732312843.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/med2_4_pipeline_en_5.5.1_3.0_1737732312843.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("med2_4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("med2_4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|med2_4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.3 MB|
+
+## References
+
+https://huggingface.co/umar-naveed/med2.4
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-medbert_clinical_ner_en.md b/docs/_posts/ahmedlone127/2025-01-24-medbert_clinical_ner_en.md
new file mode 100644
index 00000000000000..eaf90f1ee1ded2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-medbert_clinical_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English medbert_clinical_ner BertForTokenClassification from ribhu
+author: John Snow Labs
+name: medbert_clinical_ner
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`medbert_clinical_ner` is a English model originally trained by ribhu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/medbert_clinical_ner_en_5.5.1_3.0_1737720014503.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/medbert_clinical_ner_en_5.5.1_3.0_1737720014503.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("medbert_clinical_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("medbert_clinical_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|medbert_clinical_ner|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.2 MB|
+
+## References
+
+https://huggingface.co/ribhu/medbert-clinical-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-medbert_clinical_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-medbert_clinical_ner_pipeline_en.md
new file mode 100644
index 00000000000000..d7471d34c16a2d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-medbert_clinical_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English medbert_clinical_ner_pipeline pipeline BertForTokenClassification from ribhu
+author: John Snow Labs
+name: medbert_clinical_ner_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`medbert_clinical_ner_pipeline` is a English model originally trained by ribhu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/medbert_clinical_ner_pipeline_en_5.5.1_3.0_1737720036428.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/medbert_clinical_ner_pipeline_en_5.5.1_3.0_1737720036428.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("medbert_clinical_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("medbert_clinical_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|medbert_clinical_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.2 MB|
+
+## References
+
+https://huggingface.co/ribhu/medbert-clinical-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-medgpt_rabbiaaa_en.md b/docs/_posts/ahmedlone127/2025-01-24-medgpt_rabbiaaa_en.md
new file mode 100644
index 00000000000000..fb360a8c92caf7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-medgpt_rabbiaaa_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English medgpt_rabbiaaa GPT2Transformer from Rabbiaaa
+author: John Snow Labs
+name: medgpt_rabbiaaa
+date: 2025-01-24
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`medgpt_rabbiaaa` is a English model originally trained by Rabbiaaa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/medgpt_rabbiaaa_en_5.5.1_3.0_1737732150349.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/medgpt_rabbiaaa_en_5.5.1_3.0_1737732150349.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("medgpt_rabbiaaa","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("medgpt_rabbiaaa","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|medgpt_rabbiaaa|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.2 MB|
+
+## References
+
+https://huggingface.co/Rabbiaaa/MedGPT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-medgpt_rabbiaaa_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-medgpt_rabbiaaa_pipeline_en.md
new file mode 100644
index 00000000000000..265c7a387db594
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-medgpt_rabbiaaa_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English medgpt_rabbiaaa_pipeline pipeline GPT2Transformer from Rabbiaaa
+author: John Snow Labs
+name: medgpt_rabbiaaa_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`medgpt_rabbiaaa_pipeline` is a English model originally trained by Rabbiaaa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/medgpt_rabbiaaa_pipeline_en_5.5.1_3.0_1737732174550.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/medgpt_rabbiaaa_pipeline_en_5.5.1_3.0_1737732174550.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("medgpt_rabbiaaa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("medgpt_rabbiaaa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|medgpt_rabbiaaa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.2 MB|
+
+## References
+
+https://huggingface.co/Rabbiaaa/MedGPT
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-medgpt_umar_naveed_en.md b/docs/_posts/ahmedlone127/2025-01-24-medgpt_umar_naveed_en.md
new file mode 100644
index 00000000000000..a7cfb063b2a457
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-medgpt_umar_naveed_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English medgpt_umar_naveed GPT2Transformer from umar-naveed
+author: John Snow Labs
+name: medgpt_umar_naveed
+date: 2025-01-24
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`medgpt_umar_naveed` is a English model originally trained by umar-naveed.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/medgpt_umar_naveed_en_5.5.1_3.0_1737733002365.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/medgpt_umar_naveed_en_5.5.1_3.0_1737733002365.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("medgpt_umar_naveed","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("medgpt_umar_naveed","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|medgpt_umar_naveed|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.2 MB|
+
+## References
+
+https://huggingface.co/umar-naveed/medgpt
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-medgpt_umar_naveed_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-medgpt_umar_naveed_pipeline_en.md
new file mode 100644
index 00000000000000..fe79965372d483
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-medgpt_umar_naveed_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English medgpt_umar_naveed_pipeline pipeline GPT2Transformer from umar-naveed
+author: John Snow Labs
+name: medgpt_umar_naveed_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`medgpt_umar_naveed_pipeline` is a English model originally trained by umar-naveed.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/medgpt_umar_naveed_pipeline_en_5.5.1_3.0_1737733027156.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/medgpt_umar_naveed_pipeline_en_5.5.1_3.0_1737733027156.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("medgpt_umar_naveed_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("medgpt_umar_naveed_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|medgpt_umar_naveed_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.2 MB|
+
+## References
+
+https://huggingface.co/umar-naveed/medgpt
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-medmodel_en.md b/docs/_posts/ahmedlone127/2025-01-24-medmodel_en.md
new file mode 100644
index 00000000000000..01871e2f53868e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-medmodel_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English medmodel GPT2Transformer from umar-naveed
+author: John Snow Labs
+name: medmodel
+date: 2025-01-24
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`medmodel` is a English model originally trained by umar-naveed.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/medmodel_en_5.5.1_3.0_1737732823340.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/medmodel_en_5.5.1_3.0_1737732823340.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("medmodel","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("medmodel","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|medmodel|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.2 MB|
+
+## References
+
+https://huggingface.co/umar-naveed/medmodel
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-medmodel_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-medmodel_pipeline_en.md
new file mode 100644
index 00000000000000..cc7d9a33ed574c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-medmodel_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English medmodel_pipeline pipeline GPT2Transformer from umar-naveed
+author: John Snow Labs
+name: medmodel_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`medmodel_pipeline` is a English model originally trained by umar-naveed.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/medmodel_pipeline_en_5.5.1_3.0_1737732847663.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/medmodel_pipeline_en_5.5.1_3.0_1737732847663.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("medmodel_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("medmodel_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|medmodel_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.2 MB|
+
+## References
+
+https://huggingface.co/umar-naveed/medmodel
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-memo_positive_nd_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-memo_positive_nd_pipeline_en.md
new file mode 100644
index 00000000000000..57f7fc5961aa5f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-memo_positive_nd_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English memo_positive_nd_pipeline pipeline XlmRoBertaForSequenceClassification from yemen2016
+author: John Snow Labs
+name: memo_positive_nd_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`memo_positive_nd_pipeline` is a English model originally trained by yemen2016.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/memo_positive_nd_pipeline_en_5.5.1_3.0_1737713461963.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/memo_positive_nd_pipeline_en_5.5.1_3.0_1737713461963.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("memo_positive_nd_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("memo_positive_nd_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|memo_positive_nd_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.6 MB|
+
+## References
+
+https://huggingface.co/yemen2016/memo_positive_ND
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-merged_albert_agnews_lora_en.md b/docs/_posts/ahmedlone127/2025-01-24-merged_albert_agnews_lora_en.md
new file mode 100644
index 00000000000000..3dd3341616cf76
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-merged_albert_agnews_lora_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English merged_albert_agnews_lora AlbertForSequenceClassification from asm3515
+author: John Snow Labs
+name: merged_albert_agnews_lora
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, albert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`merged_albert_agnews_lora` is a English model originally trained by asm3515.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/merged_albert_agnews_lora_en_5.5.1_3.0_1737692937370.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/merged_albert_agnews_lora_en_5.5.1_3.0_1737692937370.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = AlbertForSequenceClassification.pretrained("merged_albert_agnews_lora","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = AlbertForSequenceClassification.pretrained("merged_albert_agnews_lora", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|merged_albert_agnews_lora|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/asm3515/merged-albert-agnews-lora
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-merged_albert_agnews_lora_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-merged_albert_agnews_lora_pipeline_en.md
new file mode 100644
index 00000000000000..ac1b7a521a4ddc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-merged_albert_agnews_lora_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English merged_albert_agnews_lora_pipeline pipeline AlbertForSequenceClassification from asm3515
+author: John Snow Labs
+name: merged_albert_agnews_lora_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`merged_albert_agnews_lora_pipeline` is a English model originally trained by asm3515.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/merged_albert_agnews_lora_pipeline_en_5.5.1_3.0_1737692939796.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/merged_albert_agnews_lora_pipeline_en_5.5.1_3.0_1737692939796.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("merged_albert_agnews_lora_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("merged_albert_agnews_lora_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|merged_albert_agnews_lora_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/asm3515/merged-albert-agnews-lora
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-merged_albert_imdb_lora_en.md b/docs/_posts/ahmedlone127/2025-01-24-merged_albert_imdb_lora_en.md
new file mode 100644
index 00000000000000..bdd8570715ac7e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-merged_albert_imdb_lora_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English merged_albert_imdb_lora AlbertForSequenceClassification from asm3515
+author: John Snow Labs
+name: merged_albert_imdb_lora
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, albert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`merged_albert_imdb_lora` is a English model originally trained by asm3515.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/merged_albert_imdb_lora_en_5.5.1_3.0_1737749947502.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/merged_albert_imdb_lora_en_5.5.1_3.0_1737749947502.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = AlbertForSequenceClassification.pretrained("merged_albert_imdb_lora","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = AlbertForSequenceClassification.pretrained("merged_albert_imdb_lora", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|merged_albert_imdb_lora|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/asm3515/merged-albert-imdb-lora
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-merged_albert_imdb_lora_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-merged_albert_imdb_lora_pipeline_en.md
new file mode 100644
index 00000000000000..2d0c2b115d0fab
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-merged_albert_imdb_lora_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English merged_albert_imdb_lora_pipeline pipeline AlbertForSequenceClassification from asm3515
+author: John Snow Labs
+name: merged_albert_imdb_lora_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`merged_albert_imdb_lora_pipeline` is a English model originally trained by asm3515.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/merged_albert_imdb_lora_pipeline_en_5.5.1_3.0_1737749950252.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/merged_albert_imdb_lora_pipeline_en_5.5.1_3.0_1737749950252.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("merged_albert_imdb_lora_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("merged_albert_imdb_lora_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|merged_albert_imdb_lora_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/asm3515/merged-albert-imdb-lora
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-mitsua_japanese_tagger_en.md b/docs/_posts/ahmedlone127/2025-01-24-mitsua_japanese_tagger_en.md
new file mode 100644
index 00000000000000..ae987faae063c2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-mitsua_japanese_tagger_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mitsua_japanese_tagger SwinForImageClassification from Mitsua
+author: John Snow Labs
+name: mitsua_japanese_tagger
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mitsua_japanese_tagger` is a English model originally trained by Mitsua.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mitsua_japanese_tagger_en_5.5.1_3.0_1737763105068.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mitsua_japanese_tagger_en_5.5.1_3.0_1737763105068.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""mitsua_japanese_tagger","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("mitsua_japanese_tagger","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mitsua_japanese_tagger|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|684.6 MB|
+
+## References
+
+https://huggingface.co/Mitsua/mitsua-japanese-tagger
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-mitsua_japanese_tagger_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-mitsua_japanese_tagger_pipeline_en.md
new file mode 100644
index 00000000000000..e1bf9401a0ee15
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-mitsua_japanese_tagger_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mitsua_japanese_tagger_pipeline pipeline SwinForImageClassification from Mitsua
+author: John Snow Labs
+name: mitsua_japanese_tagger_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mitsua_japanese_tagger_pipeline` is a English model originally trained by Mitsua.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mitsua_japanese_tagger_pipeline_en_5.5.1_3.0_1737763142562.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mitsua_japanese_tagger_pipeline_en_5.5.1_3.0_1737763142562.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mitsua_japanese_tagger_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mitsua_japanese_tagger_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mitsua_japanese_tagger_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|684.6 MB|
+
+## References
+
+https://huggingface.co/Mitsua/mitsua-japanese-tagger
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-model_for_fun_en.md b/docs/_posts/ahmedlone127/2025-01-24-model_for_fun_en.md
new file mode 100644
index 00000000000000..ccd474f4b4e091
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-model_for_fun_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English model_for_fun CamemBertEmbeddings from sashashghome
+author: John Snow Labs
+name: model_for_fun
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_for_fun` is a English model originally trained by sashashghome.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_for_fun_en_5.5.1_3.0_1737696164123.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_for_fun_en_5.5.1_3.0_1737696164123.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("model_for_fun","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("model_for_fun","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|model_for_fun|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/sashashghome/model-for-fun
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-model_for_fun_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-model_for_fun_pipeline_en.md
new file mode 100644
index 00000000000000..2af0a5ff85ef6b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-model_for_fun_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English model_for_fun_pipeline pipeline CamemBertEmbeddings from sashashghome
+author: John Snow Labs
+name: model_for_fun_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_for_fun_pipeline` is a English model originally trained by sashashghome.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_for_fun_pipeline_en_5.5.1_3.0_1737696245473.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_for_fun_pipeline_en_5.5.1_3.0_1737696245473.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("model_for_fun_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("model_for_fun_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|model_for_fun_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/sashashghome/model-for-fun
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-model_q1_en.md b/docs/_posts/ahmedlone127/2025-01-24-model_q1_en.md
new file mode 100644
index 00000000000000..6d692db34cf189
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-model_q1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English model_q1 DistilBertForQuestionAnswering from Hana-12345
+author: John Snow Labs
+name: model_q1
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_q1` is a English model originally trained by Hana-12345.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_q1_en_5.5.1_3.0_1737740995322.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_q1_en_5.5.1_3.0_1737740995322.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("model_q1","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("model_q1", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|model_q1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Hana-12345/model_Q1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-model_q1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-model_q1_pipeline_en.md
new file mode 100644
index 00000000000000..620b1ce6fa7d99
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-model_q1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English model_q1_pipeline pipeline DistilBertForQuestionAnswering from Hana-12345
+author: John Snow Labs
+name: model_q1_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_q1_pipeline` is a English model originally trained by Hana-12345.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_q1_pipeline_en_5.5.1_3.0_1737741009076.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_q1_pipeline_en_5.5.1_3.0_1737741009076.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("model_q1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("model_q1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|model_q1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Hana-12345/model_Q1
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-modelo_cobranzas_tfn_en.md b/docs/_posts/ahmedlone127/2025-01-24-modelo_cobranzas_tfn_en.md
new file mode 100644
index 00000000000000..aa544099f41496
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-modelo_cobranzas_tfn_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English modelo_cobranzas_tfn BertForQuestionAnswering from JuanKBracho
+author: John Snow Labs
+name: modelo_cobranzas_tfn
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`modelo_cobranzas_tfn` is a English model originally trained by JuanKBracho.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/modelo_cobranzas_tfn_en_5.5.1_3.0_1737738357827.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/modelo_cobranzas_tfn_en_5.5.1_3.0_1737738357827.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("modelo_cobranzas_tfn","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("modelo_cobranzas_tfn", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|modelo_cobranzas_tfn|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/JuanKBracho/modelo_cobranzas_TFN
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-modelo_cobranzas_tfn_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-modelo_cobranzas_tfn_pipeline_en.md
new file mode 100644
index 00000000000000..d38d88d9ed781e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-modelo_cobranzas_tfn_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English modelo_cobranzas_tfn_pipeline pipeline BertForQuestionAnswering from JuanKBracho
+author: John Snow Labs
+name: modelo_cobranzas_tfn_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`modelo_cobranzas_tfn_pipeline` is a English model originally trained by JuanKBracho.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/modelo_cobranzas_tfn_pipeline_en_5.5.1_3.0_1737738395020.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/modelo_cobranzas_tfn_pipeline_en_5.5.1_3.0_1737738395020.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("modelo_cobranzas_tfn_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("modelo_cobranzas_tfn_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|modelo_cobranzas_tfn_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/JuanKBracho/modelo_cobranzas_TFN
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-modelo_llm_en.md b/docs/_posts/ahmedlone127/2025-01-24-modelo_llm_en.md
new file mode 100644
index 00000000000000..a4249788d61b85
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-modelo_llm_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English modelo_llm BertForQuestionAnswering from BernardoMSV
+author: John Snow Labs
+name: modelo_llm
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`modelo_llm` is a English model originally trained by BernardoMSV.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/modelo_llm_en_5.5.1_3.0_1737757395463.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/modelo_llm_en_5.5.1_3.0_1737757395463.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("modelo_llm","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("modelo_llm", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|modelo_llm|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|405.9 MB|
+
+## References
+
+https://huggingface.co/BernardoMSV/modelo_llm
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-modelo_llm_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-modelo_llm_pipeline_en.md
new file mode 100644
index 00000000000000..d5f6068572284f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-modelo_llm_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English modelo_llm_pipeline pipeline BertForQuestionAnswering from BernardoMSV
+author: John Snow Labs
+name: modelo_llm_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`modelo_llm_pipeline` is a English model originally trained by BernardoMSV.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/modelo_llm_pipeline_en_5.5.1_3.0_1737757420499.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/modelo_llm_pipeline_en_5.5.1_3.0_1737757420499.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("modelo_llm_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("modelo_llm_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|modelo_llm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.0 MB|
+
+## References
+
+https://huggingface.co/BernardoMSV/modelo_llm
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-modelo_qa_beto_squad_spanish_en.md b/docs/_posts/ahmedlone127/2025-01-24-modelo_qa_beto_squad_spanish_en.md
new file mode 100644
index 00000000000000..337f2ce3afeea1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-modelo_qa_beto_squad_spanish_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English modelo_qa_beto_squad_spanish BertForQuestionAnswering from Lisibonny
+author: John Snow Labs
+name: modelo_qa_beto_squad_spanish
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`modelo_qa_beto_squad_spanish` is a English model originally trained by Lisibonny.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/modelo_qa_beto_squad_spanish_en_5.5.1_3.0_1737758072928.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/modelo_qa_beto_squad_spanish_en_5.5.1_3.0_1737758072928.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("modelo_qa_beto_squad_spanish","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("modelo_qa_beto_squad_spanish", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|modelo_qa_beto_squad_spanish|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/Lisibonny/modelo_qa_beto_squad_es
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-modelo_qa_beto_squad_spanish_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-modelo_qa_beto_squad_spanish_pipeline_en.md
new file mode 100644
index 00000000000000..31b5fddbf0da34
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-modelo_qa_beto_squad_spanish_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English modelo_qa_beto_squad_spanish_pipeline pipeline BertForQuestionAnswering from Lisibonny
+author: John Snow Labs
+name: modelo_qa_beto_squad_spanish_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`modelo_qa_beto_squad_spanish_pipeline` is a English model originally trained by Lisibonny.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/modelo_qa_beto_squad_spanish_pipeline_en_5.5.1_3.0_1737758093876.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/modelo_qa_beto_squad_spanish_pipeline_en_5.5.1_3.0_1737758093876.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("modelo_qa_beto_squad_spanish_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("modelo_qa_beto_squad_spanish_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|modelo_qa_beto_squad_spanish_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/Lisibonny/modelo_qa_beto_squad_es
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-modernbert_finetuned_squad_en.md b/docs/_posts/ahmedlone127/2025-01-24-modernbert_finetuned_squad_en.md
new file mode 100644
index 00000000000000..7d0a4a2063fe04
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-modernbert_finetuned_squad_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English modernbert_finetuned_squad BertForQuestionAnswering from gemskani
+author: John Snow Labs
+name: modernbert_finetuned_squad
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`modernbert_finetuned_squad` is a English model originally trained by gemskani.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/modernbert_finetuned_squad_en_5.5.1_3.0_1737739517491.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/modernbert_finetuned_squad_en_5.5.1_3.0_1737739517491.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("modernbert_finetuned_squad","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("modernbert_finetuned_squad", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|modernbert_finetuned_squad|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/gemskani/ModernBERT-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-modernbert_finetuned_squad_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-modernbert_finetuned_squad_pipeline_en.md
new file mode 100644
index 00000000000000..a7b7f8765fa152
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-modernbert_finetuned_squad_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English modernbert_finetuned_squad_pipeline pipeline BertForQuestionAnswering from gemskani
+author: John Snow Labs
+name: modernbert_finetuned_squad_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`modernbert_finetuned_squad_pipeline` is a English model originally trained by gemskani.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/modernbert_finetuned_squad_pipeline_en_5.5.1_3.0_1737739581522.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/modernbert_finetuned_squad_pipeline_en_5.5.1_3.0_1737739581522.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("modernbert_finetuned_squad_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("modernbert_finetuned_squad_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|modernbert_finetuned_squad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/gemskani/ModernBERT-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-movement_pruned_en.md b/docs/_posts/ahmedlone127/2025-01-24-movement_pruned_en.md
new file mode 100644
index 00000000000000..3ddd0e88507fd1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-movement_pruned_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English movement_pruned BertForQuestionAnswering from xihajun
+author: John Snow Labs
+name: movement_pruned
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`movement_pruned` is a English model originally trained by xihajun.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/movement_pruned_en_5.5.1_3.0_1737691176774.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/movement_pruned_en_5.5.1_3.0_1737691176774.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("movement_pruned","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("movement_pruned", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|movement_pruned|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/xihajun/movement_pruned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-movement_pruned_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-movement_pruned_pipeline_en.md
new file mode 100644
index 00000000000000..c36bc4bca5ef18
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-movement_pruned_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English movement_pruned_pipeline pipeline BertForQuestionAnswering from xihajun
+author: John Snow Labs
+name: movement_pruned_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`movement_pruned_pipeline` is a English model originally trained by xihajun.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/movement_pruned_pipeline_en_5.5.1_3.0_1737691207471.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/movement_pruned_pipeline_en_5.5.1_3.0_1737691207471.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("movement_pruned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("movement_pruned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|movement_pruned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/xihajun/movement_pruned
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-multilingual_xlm_roberta_ner_pipeline_xx.md b/docs/_posts/ahmedlone127/2025-01-24-multilingual_xlm_roberta_ner_pipeline_xx.md
new file mode 100644
index 00000000000000..487bd3afd4e786
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-multilingual_xlm_roberta_ner_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual multilingual_xlm_roberta_ner_pipeline pipeline XlmRoBertaForTokenClassification from enesmanan
+author: John Snow Labs
+name: multilingual_xlm_roberta_ner_pipeline
+date: 2025-01-24
+tags: [xx, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multilingual_xlm_roberta_ner_pipeline` is a Multilingual model originally trained by enesmanan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multilingual_xlm_roberta_ner_pipeline_xx_5.5.1_3.0_1737681104851.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multilingual_xlm_roberta_ner_pipeline_xx_5.5.1_3.0_1737681104851.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("multilingual_xlm_roberta_ner_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("multilingual_xlm_roberta_ner_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|multilingual_xlm_roberta_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/enesmanan/multilingual-xlm-roberta-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-multilingual_xlm_roberta_ner_xx.md b/docs/_posts/ahmedlone127/2025-01-24-multilingual_xlm_roberta_ner_xx.md
new file mode 100644
index 00000000000000..9efcc2d066cbe6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-multilingual_xlm_roberta_ner_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual multilingual_xlm_roberta_ner XlmRoBertaForTokenClassification from enesmanan
+author: John Snow Labs
+name: multilingual_xlm_roberta_ner
+date: 2025-01-24
+tags: [xx, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multilingual_xlm_roberta_ner` is a Multilingual model originally trained by enesmanan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multilingual_xlm_roberta_ner_xx_5.5.1_3.0_1737681017413.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multilingual_xlm_roberta_ner_xx_5.5.1_3.0_1737681017413.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("multilingual_xlm_roberta_ner","xx") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("multilingual_xlm_roberta_ner", "xx")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|multilingual_xlm_roberta_ner|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|xx|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/enesmanan/multilingual-xlm-roberta-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-muril_large_squad_slow_en.md b/docs/_posts/ahmedlone127/2025-01-24-muril_large_squad_slow_en.md
new file mode 100644
index 00000000000000..143c3b2bc1711c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-muril_large_squad_slow_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English muril_large_squad_slow BertForQuestionAnswering from Yunika
+author: John Snow Labs
+name: muril_large_squad_slow
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`muril_large_squad_slow` is a English model originally trained by Yunika.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/muril_large_squad_slow_en_5.5.1_3.0_1737757587930.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/muril_large_squad_slow_en_5.5.1_3.0_1737757587930.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("muril_large_squad_slow","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("muril_large_squad_slow", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|muril_large_squad_slow|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.9 GB|
+
+## References
+
+https://huggingface.co/Yunika/muril-large-squad-slow
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-muril_large_squad_slow_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-muril_large_squad_slow_pipeline_en.md
new file mode 100644
index 00000000000000..850585979b9a43
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-muril_large_squad_slow_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English muril_large_squad_slow_pipeline pipeline BertForQuestionAnswering from Yunika
+author: John Snow Labs
+name: muril_large_squad_slow_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`muril_large_squad_slow_pipeline` is a English model originally trained by Yunika.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/muril_large_squad_slow_pipeline_en_5.5.1_3.0_1737757683177.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/muril_large_squad_slow_pipeline_en_5.5.1_3.0_1737757683177.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("muril_large_squad_slow_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("muril_large_squad_slow_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|muril_large_squad_slow_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.9 GB|
+
+## References
+
+https://huggingface.co/Yunika/muril-large-squad-slow
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-myqamodel_en.md b/docs/_posts/ahmedlone127/2025-01-24-myqamodel_en.md
new file mode 100644
index 00000000000000..6a944cf172bc8a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-myqamodel_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English myqamodel BertForQuestionAnswering from Mandy234
+author: John Snow Labs
+name: myqamodel
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`myqamodel` is a English model originally trained by Mandy234.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/myqamodel_en_5.5.1_3.0_1737691157467.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/myqamodel_en_5.5.1_3.0_1737691157467.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("myqamodel","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("myqamodel", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|myqamodel|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/Mandy234/myQAmodel
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-myqamodel_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-myqamodel_pipeline_en.md
new file mode 100644
index 00000000000000..7a65c564c127b5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-myqamodel_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English myqamodel_pipeline pipeline BertForQuestionAnswering from Mandy234
+author: John Snow Labs
+name: myqamodel_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`myqamodel_pipeline` is a English model originally trained by Mandy234.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/myqamodel_pipeline_en_5.5.1_3.0_1737691181003.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/myqamodel_pipeline_en_5.5.1_3.0_1737691181003.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("myqamodel_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("myqamodel_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|myqamodel_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/Mandy234/myQAmodel
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-mytoken_model_1_en.md b/docs/_posts/ahmedlone127/2025-01-24-mytoken_model_1_en.md
new file mode 100644
index 00000000000000..bdb58648edae35
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-mytoken_model_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mytoken_model_1 BertEmbeddings from kumarme072
+author: John Snow Labs
+name: mytoken_model_1
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mytoken_model_1` is a English model originally trained by kumarme072.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mytoken_model_1_en_5.5.1_3.0_1737742325149.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mytoken_model_1_en_5.5.1_3.0_1737742325149.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("mytoken_model_1","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("mytoken_model_1","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mytoken_model_1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/kumarme072/mytoken_model_1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-mytoken_model_1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-mytoken_model_1_pipeline_en.md
new file mode 100644
index 00000000000000..411d389ae8b3af
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-mytoken_model_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mytoken_model_1_pipeline pipeline BertEmbeddings from kumarme072
+author: John Snow Labs
+name: mytoken_model_1_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mytoken_model_1_pipeline` is a English model originally trained by kumarme072.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mytoken_model_1_pipeline_en_5.5.1_3.0_1737742348175.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mytoken_model_1_pipeline_en_5.5.1_3.0_1737742348175.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mytoken_model_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mytoken_model_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mytoken_model_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.8 MB|
+
+## References
+
+https://huggingface.co/kumarme072/mytoken_model_1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-ner_test_bert_base_uncased_finetuned_500k_5_epoch_en.md b/docs/_posts/ahmedlone127/2025-01-24-ner_test_bert_base_uncased_finetuned_500k_5_epoch_en.md
new file mode 100644
index 00000000000000..bb9b86d95d17d8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-ner_test_bert_base_uncased_finetuned_500k_5_epoch_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ner_test_bert_base_uncased_finetuned_500k_5_epoch BertForTokenClassification from adambuttrick
+author: John Snow Labs
+name: ner_test_bert_base_uncased_finetuned_500k_5_epoch
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_test_bert_base_uncased_finetuned_500k_5_epoch` is a English model originally trained by adambuttrick.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_test_bert_base_uncased_finetuned_500k_5_epoch_en_5.5.1_3.0_1737719866901.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_test_bert_base_uncased_finetuned_500k_5_epoch_en_5.5.1_3.0_1737719866901.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("ner_test_bert_base_uncased_finetuned_500k_5_epoch","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("ner_test_bert_base_uncased_finetuned_500k_5_epoch", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_test_bert_base_uncased_finetuned_500k_5_epoch|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/adambuttrick/ner-test-bert-base-uncased-finetuned-500K-5-epoch
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-ner_test_bert_base_uncased_finetuned_500k_5_epoch_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-ner_test_bert_base_uncased_finetuned_500k_5_epoch_pipeline_en.md
new file mode 100644
index 00000000000000..7da77643d2c3da
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-ner_test_bert_base_uncased_finetuned_500k_5_epoch_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ner_test_bert_base_uncased_finetuned_500k_5_epoch_pipeline pipeline BertForTokenClassification from adambuttrick
+author: John Snow Labs
+name: ner_test_bert_base_uncased_finetuned_500k_5_epoch_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_test_bert_base_uncased_finetuned_500k_5_epoch_pipeline` is a English model originally trained by adambuttrick.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_test_bert_base_uncased_finetuned_500k_5_epoch_pipeline_en_5.5.1_3.0_1737719896591.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_test_bert_base_uncased_finetuned_500k_5_epoch_pipeline_en_5.5.1_3.0_1737719896591.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ner_test_bert_base_uncased_finetuned_500k_5_epoch_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ner_test_bert_base_uncased_finetuned_500k_5_epoch_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_test_bert_base_uncased_finetuned_500k_5_epoch_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/adambuttrick/ner-test-bert-base-uncased-finetuned-500K-5-epoch
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-nlp_task_en.md b/docs/_posts/ahmedlone127/2025-01-24-nlp_task_en.md
new file mode 100644
index 00000000000000..287d6d86c10e51
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-nlp_task_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English nlp_task DistilBertForQuestionAnswering from Stucknight
+author: John Snow Labs
+name: nlp_task
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nlp_task` is a English model originally trained by Stucknight.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nlp_task_en_5.5.1_3.0_1737741147192.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nlp_task_en_5.5.1_3.0_1737741147192.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("nlp_task","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("nlp_task", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nlp_task|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Stucknight/nlp_task
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-nlp_task_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-nlp_task_pipeline_en.md
new file mode 100644
index 00000000000000..29af2ea84b77b8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-nlp_task_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English nlp_task_pipeline pipeline DistilBertForQuestionAnswering from Stucknight
+author: John Snow Labs
+name: nlp_task_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nlp_task_pipeline` is a English model originally trained by Stucknight.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nlp_task_pipeline_en_5.5.1_3.0_1737741165477.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nlp_task_pipeline_en_5.5.1_3.0_1737741165477.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("nlp_task_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("nlp_task_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nlp_task_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Stucknight/nlp_task
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-nlp_tp_4_ner_croato_en.md b/docs/_posts/ahmedlone127/2025-01-24-nlp_tp_4_ner_croato_en.md
new file mode 100644
index 00000000000000..8a2b3f5aac66ec
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-nlp_tp_4_ner_croato_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English nlp_tp_4_ner_croato DistilBertForTokenClassification from marcocarotta
+author: John Snow Labs
+name: nlp_tp_4_ner_croato
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nlp_tp_4_ner_croato` is a English model originally trained by marcocarotta.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nlp_tp_4_ner_croato_en_5.5.1_3.0_1737692630069.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nlp_tp_4_ner_croato_en_5.5.1_3.0_1737692630069.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("nlp_tp_4_ner_croato","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("nlp_tp_4_ner_croato", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nlp_tp_4_ner_croato|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/marcocarotta/NLP-tp-4-ner-croato
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-nlp_tp_4_ner_croato_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-nlp_tp_4_ner_croato_pipeline_en.md
new file mode 100644
index 00000000000000..f782b5926c9c9c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-nlp_tp_4_ner_croato_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English nlp_tp_4_ner_croato_pipeline pipeline DistilBertForTokenClassification from marcocarotta
+author: John Snow Labs
+name: nlp_tp_4_ner_croato_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nlp_tp_4_ner_croato_pipeline` is a English model originally trained by marcocarotta.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nlp_tp_4_ner_croato_pipeline_en_5.5.1_3.0_1737692643586.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nlp_tp_4_ner_croato_pipeline_en_5.5.1_3.0_1737692643586.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("nlp_tp_4_ner_croato_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("nlp_tp_4_ner_croato_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nlp_tp_4_ner_croato_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/marcocarotta/NLP-tp-4-ner-croato
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-nlp_tp_4_ner_inglese_en.md b/docs/_posts/ahmedlone127/2025-01-24-nlp_tp_4_ner_inglese_en.md
new file mode 100644
index 00000000000000..9add548d1bb655
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-nlp_tp_4_ner_inglese_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English nlp_tp_4_ner_inglese DistilBertForTokenClassification from marcocarotta
+author: John Snow Labs
+name: nlp_tp_4_ner_inglese
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nlp_tp_4_ner_inglese` is a English model originally trained by marcocarotta.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nlp_tp_4_ner_inglese_en_5.5.1_3.0_1737692625053.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nlp_tp_4_ner_inglese_en_5.5.1_3.0_1737692625053.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("nlp_tp_4_ner_inglese","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("nlp_tp_4_ner_inglese", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nlp_tp_4_ner_inglese|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/marcocarotta/NLP-tp-4-ner-inglese
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-nlp_tp_4_ner_inglese_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-nlp_tp_4_ner_inglese_pipeline_en.md
new file mode 100644
index 00000000000000..3566dd9f8d5512
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-nlp_tp_4_ner_inglese_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English nlp_tp_4_ner_inglese_pipeline pipeline DistilBertForTokenClassification from marcocarotta
+author: John Snow Labs
+name: nlp_tp_4_ner_inglese_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nlp_tp_4_ner_inglese_pipeline` is a English model originally trained by marcocarotta.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nlp_tp_4_ner_inglese_pipeline_en_5.5.1_3.0_1737692638654.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nlp_tp_4_ner_inglese_pipeline_en_5.5.1_3.0_1737692638654.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("nlp_tp_4_ner_inglese_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("nlp_tp_4_ner_inglese_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nlp_tp_4_ner_inglese_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/marcocarotta/NLP-tp-4-ner-inglese
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-nlpex6_en.md b/docs/_posts/ahmedlone127/2025-01-24-nlpex6_en.md
new file mode 100644
index 00000000000000..f0db67884e077b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-nlpex6_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English nlpex6 BertForQuestionAnswering from d3t0oo
+author: John Snow Labs
+name: nlpex6
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nlpex6` is a English model originally trained by d3t0oo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nlpex6_en_5.5.1_3.0_1737756822420.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nlpex6_en_5.5.1_3.0_1737756822420.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("nlpex6","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("nlpex6", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nlpex6|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|53.8 MB|
+
+## References
+
+https://huggingface.co/d3t0oo/nlpEx6
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-nlpex6_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-nlpex6_pipeline_en.md
new file mode 100644
index 00000000000000..9e34caab72d8c0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-nlpex6_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English nlpex6_pipeline pipeline BertForQuestionAnswering from d3t0oo
+author: John Snow Labs
+name: nlpex6_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nlpex6_pipeline` is a English model originally trained by d3t0oo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nlpex6_pipeline_en_5.5.1_3.0_1737756830439.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nlpex6_pipeline_en_5.5.1_3.0_1737756830439.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("nlpex6_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("nlpex6_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nlpex6_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|53.9 MB|
+
+## References
+
+https://huggingface.co/d3t0oo/nlpEx6
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-nominal_groups_recognition_bert_base_spanish_wwm_cased_charqican_es.md b/docs/_posts/ahmedlone127/2025-01-24-nominal_groups_recognition_bert_base_spanish_wwm_cased_charqican_es.md
new file mode 100644
index 00000000000000..1408de12238d56
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-nominal_groups_recognition_bert_base_spanish_wwm_cased_charqican_es.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Castilian, Spanish nominal_groups_recognition_bert_base_spanish_wwm_cased_charqican BertForTokenClassification from charqican
+author: John Snow Labs
+name: nominal_groups_recognition_bert_base_spanish_wwm_cased_charqican
+date: 2025-01-24
+tags: [es, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: es
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nominal_groups_recognition_bert_base_spanish_wwm_cased_charqican` is a Castilian, Spanish model originally trained by charqican.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nominal_groups_recognition_bert_base_spanish_wwm_cased_charqican_es_5.5.1_3.0_1737719717119.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nominal_groups_recognition_bert_base_spanish_wwm_cased_charqican_es_5.5.1_3.0_1737719717119.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("nominal_groups_recognition_bert_base_spanish_wwm_cased_charqican","es") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("nominal_groups_recognition_bert_base_spanish_wwm_cased_charqican", "es")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nominal_groups_recognition_bert_base_spanish_wwm_cased_charqican|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|es|
+|Size:|409.5 MB|
+
+## References
+
+https://huggingface.co/charqican/nominal-groups-recognition-bert-base-spanish-wwm-cased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-nominal_groups_recognition_bert_base_spanish_wwm_cased_charqican_pipeline_es.md b/docs/_posts/ahmedlone127/2025-01-24-nominal_groups_recognition_bert_base_spanish_wwm_cased_charqican_pipeline_es.md
new file mode 100644
index 00000000000000..6730bf2eb2259e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-nominal_groups_recognition_bert_base_spanish_wwm_cased_charqican_pipeline_es.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Castilian, Spanish nominal_groups_recognition_bert_base_spanish_wwm_cased_charqican_pipeline pipeline BertForTokenClassification from charqican
+author: John Snow Labs
+name: nominal_groups_recognition_bert_base_spanish_wwm_cased_charqican_pipeline
+date: 2025-01-24
+tags: [es, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: es
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nominal_groups_recognition_bert_base_spanish_wwm_cased_charqican_pipeline` is a Castilian, Spanish model originally trained by charqican.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nominal_groups_recognition_bert_base_spanish_wwm_cased_charqican_pipeline_es_5.5.1_3.0_1737719739509.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nominal_groups_recognition_bert_base_spanish_wwm_cased_charqican_pipeline_es_5.5.1_3.0_1737719739509.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("nominal_groups_recognition_bert_base_spanish_wwm_cased_charqican_pipeline", lang = "es")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("nominal_groups_recognition_bert_base_spanish_wwm_cased_charqican_pipeline", lang = "es")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nominal_groups_recognition_bert_base_spanish_wwm_cased_charqican_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|es|
+|Size:|409.5 MB|
+
+## References
+
+https://huggingface.co/charqican/nominal-groups-recognition-bert-base-spanish-wwm-cased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-nsfw_filterization_decentscan_en.md b/docs/_posts/ahmedlone127/2025-01-24-nsfw_filterization_decentscan_en.md
new file mode 100644
index 00000000000000..6de2a2b329e29a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-nsfw_filterization_decentscan_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English nsfw_filterization_decentscan SwinForImageClassification from DamarJati
+author: John Snow Labs
+name: nsfw_filterization_decentscan
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nsfw_filterization_decentscan` is a English model originally trained by DamarJati.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nsfw_filterization_decentscan_en_5.5.1_3.0_1737694428875.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nsfw_filterization_decentscan_en_5.5.1_3.0_1737694428875.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""nsfw_filterization_decentscan","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("nsfw_filterization_decentscan","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nsfw_filterization_decentscan|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/DamarJati/NSFW-Filterization-DecentScan
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-nsfw_filterization_decentscan_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-nsfw_filterization_decentscan_pipeline_en.md
new file mode 100644
index 00000000000000..25955311e6fa42
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-nsfw_filterization_decentscan_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English nsfw_filterization_decentscan_pipeline pipeline SwinForImageClassification from DamarJati
+author: John Snow Labs
+name: nsfw_filterization_decentscan_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nsfw_filterization_decentscan_pipeline` is a English model originally trained by DamarJati.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nsfw_filterization_decentscan_pipeline_en_5.5.1_3.0_1737694440213.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nsfw_filterization_decentscan_pipeline_en_5.5.1_3.0_1737694440213.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("nsfw_filterization_decentscan_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("nsfw_filterization_decentscan_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nsfw_filterization_decentscan_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/DamarJati/NSFW-Filterization-DecentScan
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-nsmc_model_bin_en.md b/docs/_posts/ahmedlone127/2025-01-24-nsmc_model_bin_en.md
new file mode 100644
index 00000000000000..e3bc12d358d537
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-nsmc_model_bin_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English nsmc_model_bin BertForSequenceClassification from JOOMINJI
+author: John Snow Labs
+name: nsmc_model_bin
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nsmc_model_bin` is a English model originally trained by JOOMINJI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nsmc_model_bin_en_5.5.1_3.0_1737710267595.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nsmc_model_bin_en_5.5.1_3.0_1737710267595.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("nsmc_model_bin","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("nsmc_model_bin", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nsmc_model_bin|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|345.1 MB|
+
+## References
+
+https://huggingface.co/JOOMINJI/NSMC_model.bin
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-nsmc_model_bin_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-nsmc_model_bin_pipeline_en.md
new file mode 100644
index 00000000000000..e27f0cf3c5e033
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-nsmc_model_bin_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English nsmc_model_bin_pipeline pipeline BertForSequenceClassification from JOOMINJI
+author: John Snow Labs
+name: nsmc_model_bin_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nsmc_model_bin_pipeline` is a English model originally trained by JOOMINJI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nsmc_model_bin_pipeline_en_5.5.1_3.0_1737710286074.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nsmc_model_bin_pipeline_en_5.5.1_3.0_1737710286074.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("nsmc_model_bin_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("nsmc_model_bin_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nsmc_model_bin_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|345.1 MB|
+
+## References
+
+https://huggingface.co/JOOMINJI/NSMC_model.bin
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-osf_swinv2_base_patch4_window7_cifar100_en.md b/docs/_posts/ahmedlone127/2025-01-24-osf_swinv2_base_patch4_window7_cifar100_en.md
new file mode 100644
index 00000000000000..b30188d2aa31f3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-osf_swinv2_base_patch4_window7_cifar100_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English osf_swinv2_base_patch4_window7_cifar100 SwinForImageClassification from anonymous-429
+author: John Snow Labs
+name: osf_swinv2_base_patch4_window7_cifar100
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`osf_swinv2_base_patch4_window7_cifar100` is a English model originally trained by anonymous-429.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/osf_swinv2_base_patch4_window7_cifar100_en_5.5.1_3.0_1737715557480.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/osf_swinv2_base_patch4_window7_cifar100_en_5.5.1_3.0_1737715557480.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""osf_swinv2_base_patch4_window7_cifar100","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("osf_swinv2_base_patch4_window7_cifar100","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|osf_swinv2_base_patch4_window7_cifar100|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|650.5 MB|
+
+## References
+
+https://huggingface.co/anonymous-429/osf-swinv2-base-patch4-window7-cifar100
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-osf_swinv2_base_patch4_window7_cifar100_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-osf_swinv2_base_patch4_window7_cifar100_pipeline_en.md
new file mode 100644
index 00000000000000..0154a3debe4d1f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-osf_swinv2_base_patch4_window7_cifar100_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English osf_swinv2_base_patch4_window7_cifar100_pipeline pipeline SwinForImageClassification from anonymous-429
+author: John Snow Labs
+name: osf_swinv2_base_patch4_window7_cifar100_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`osf_swinv2_base_patch4_window7_cifar100_pipeline` is a English model originally trained by anonymous-429.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/osf_swinv2_base_patch4_window7_cifar100_pipeline_en_5.5.1_3.0_1737715592921.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/osf_swinv2_base_patch4_window7_cifar100_pipeline_en_5.5.1_3.0_1737715592921.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("osf_swinv2_base_patch4_window7_cifar100_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("osf_swinv2_base_patch4_window7_cifar100_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|osf_swinv2_base_patch4_window7_cifar100_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|650.5 MB|
+
+## References
+
+https://huggingface.co/anonymous-429/osf-swinv2-base-patch4-window7-cifar100
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-otterchat_en.md b/docs/_posts/ahmedlone127/2025-01-24-otterchat_en.md
new file mode 100644
index 00000000000000..0d5739c38549c3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-otterchat_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English otterchat BertForQuestionAnswering from OtterDev
+author: John Snow Labs
+name: otterchat
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`otterchat` is a English model originally trained by OtterDev.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/otterchat_en_5.5.1_3.0_1737757768855.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/otterchat_en_5.5.1_3.0_1737757768855.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("otterchat","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("otterchat", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|otterchat|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/OtterDev/otterchat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-otterchat_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-otterchat_pipeline_en.md
new file mode 100644
index 00000000000000..6c2ba470176e02
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-otterchat_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English otterchat_pipeline pipeline BertForQuestionAnswering from OtterDev
+author: John Snow Labs
+name: otterchat_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`otterchat_pipeline` is a English model originally trained by OtterDev.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/otterchat_pipeline_en_5.5.1_3.0_1737757833226.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/otterchat_pipeline_en_5.5.1_3.0_1737757833226.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("otterchat_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("otterchat_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|otterchat_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/OtterDev/otterchat
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-practice_swin1_en.md b/docs/_posts/ahmedlone127/2025-01-24-practice_swin1_en.md
new file mode 100644
index 00000000000000..3b47ee2092237e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-practice_swin1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English practice_swin1 SwinForImageClassification from HITMYM
+author: John Snow Labs
+name: practice_swin1
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`practice_swin1` is a English model originally trained by HITMYM.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/practice_swin1_en_5.5.1_3.0_1737693897987.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/practice_swin1_en_5.5.1_3.0_1737693897987.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""practice_swin1","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("practice_swin1","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|practice_swin1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/HITMYM/practice_swin1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-practice_swin1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-practice_swin1_pipeline_en.md
new file mode 100644
index 00000000000000..4a777c75d4cdfb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-practice_swin1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English practice_swin1_pipeline pipeline SwinForImageClassification from HITMYM
+author: John Snow Labs
+name: practice_swin1_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`practice_swin1_pipeline` is a English model originally trained by HITMYM.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/practice_swin1_pipeline_en_5.5.1_3.0_1737693911839.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/practice_swin1_pipeline_en_5.5.1_3.0_1737693911839.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("practice_swin1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("practice_swin1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|practice_swin1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/HITMYM/practice_swin1
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-pre_train_mbertv2_en.md b/docs/_posts/ahmedlone127/2025-01-24-pre_train_mbertv2_en.md
new file mode 100644
index 00000000000000..757fedd34b7a5a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-pre_train_mbertv2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English pre_train_mbertv2 BertEmbeddings from morten-j
+author: John Snow Labs
+name: pre_train_mbertv2
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pre_train_mbertv2` is a English model originally trained by morten-j.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pre_train_mbertv2_en_5.5.1_3.0_1737742593634.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pre_train_mbertv2_en_5.5.1_3.0_1737742593634.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("pre_train_mbertv2","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("pre_train_mbertv2","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pre_train_mbertv2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|658.6 MB|
+
+## References
+
+https://huggingface.co/morten-j/pre-train_mBERTv2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-pre_train_mbertv2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-pre_train_mbertv2_pipeline_en.md
new file mode 100644
index 00000000000000..312e6f92b78d56
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-pre_train_mbertv2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English pre_train_mbertv2_pipeline pipeline BertEmbeddings from morten-j
+author: John Snow Labs
+name: pre_train_mbertv2_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pre_train_mbertv2_pipeline` is a English model originally trained by morten-j.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pre_train_mbertv2_pipeline_en_5.5.1_3.0_1737742629296.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pre_train_mbertv2_pipeline_en_5.5.1_3.0_1737742629296.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("pre_train_mbertv2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("pre_train_mbertv2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pre_train_mbertv2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|658.6 MB|
+
+## References
+
+https://huggingface.co/morten-j/pre-train_mBERTv2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-product_name_ner_model_pipeline_zh.md b/docs/_posts/ahmedlone127/2025-01-24-product_name_ner_model_pipeline_zh.md
new file mode 100644
index 00000000000000..ef3a2d2765fb01
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-product_name_ner_model_pipeline_zh.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Chinese product_name_ner_model_pipeline pipeline BertForTokenClassification from clw8998
+author: John Snow Labs
+name: product_name_ner_model_pipeline
+date: 2025-01-24
+tags: [zh, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: zh
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`product_name_ner_model_pipeline` is a Chinese model originally trained by clw8998.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/product_name_ner_model_pipeline_zh_5.5.1_3.0_1737719999850.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/product_name_ner_model_pipeline_zh_5.5.1_3.0_1737719999850.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("product_name_ner_model_pipeline", lang = "zh")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("product_name_ner_model_pipeline", lang = "zh")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|product_name_ner_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|zh|
+|Size:|142.0 MB|
+
+## References
+
+https://huggingface.co/clw8998/Product-Name-NER-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-product_name_ner_model_zh.md b/docs/_posts/ahmedlone127/2025-01-24-product_name_ner_model_zh.md
new file mode 100644
index 00000000000000..fe47782ab5a212
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-product_name_ner_model_zh.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Chinese product_name_ner_model BertForTokenClassification from clw8998
+author: John Snow Labs
+name: product_name_ner_model
+date: 2025-01-24
+tags: [zh, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: zh
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`product_name_ner_model` is a Chinese model originally trained by clw8998.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/product_name_ner_model_zh_5.5.1_3.0_1737719992399.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/product_name_ner_model_zh_5.5.1_3.0_1737719992399.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("product_name_ner_model","zh") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("product_name_ner_model", "zh")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|product_name_ner_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|zh|
+|Size:|142.0 MB|
+
+## References
+
+https://huggingface.co/clw8998/Product-Name-NER-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-prof_ner_cat_v1_ca.md b/docs/_posts/ahmedlone127/2025-01-24-prof_ner_cat_v1_ca.md
new file mode 100644
index 00000000000000..527dc0f09cef76
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-prof_ner_cat_v1_ca.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Catalan, Valencian prof_ner_cat_v1 RoBertaForTokenClassification from BSC-NLP4BIA
+author: John Snow Labs
+name: prof_ner_cat_v1
+date: 2025-01-24
+tags: [ca, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: ca
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`prof_ner_cat_v1` is a Catalan, Valencian model originally trained by BSC-NLP4BIA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/prof_ner_cat_v1_ca_5.5.1_3.0_1737702688299.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/prof_ner_cat_v1_ca_5.5.1_3.0_1737702688299.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("prof_ner_cat_v1","ca") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("prof_ner_cat_v1", "ca")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|prof_ner_cat_v1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|ca|
+|Size:|443.0 MB|
+
+## References
+
+https://huggingface.co/BSC-NLP4BIA/prof-ner-cat-v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-prof_ner_cat_v1_pipeline_ca.md b/docs/_posts/ahmedlone127/2025-01-24-prof_ner_cat_v1_pipeline_ca.md
new file mode 100644
index 00000000000000..9868415d23a969
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-prof_ner_cat_v1_pipeline_ca.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Catalan, Valencian prof_ner_cat_v1_pipeline pipeline RoBertaForTokenClassification from BSC-NLP4BIA
+author: John Snow Labs
+name: prof_ner_cat_v1_pipeline
+date: 2025-01-24
+tags: [ca, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: ca
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`prof_ner_cat_v1_pipeline` is a Catalan, Valencian model originally trained by BSC-NLP4BIA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/prof_ner_cat_v1_pipeline_ca_5.5.1_3.0_1737702713253.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/prof_ner_cat_v1_pipeline_ca_5.5.1_3.0_1737702713253.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("prof_ner_cat_v1_pipeline", lang = "ca")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("prof_ner_cat_v1_pipeline", lang = "ca")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|prof_ner_cat_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ca|
+|Size:|443.0 MB|
+
+## References
+
+https://huggingface.co/BSC-NLP4BIA/prof-ner-cat-v1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-promptgen_lexart_en.md b/docs/_posts/ahmedlone127/2025-01-24-promptgen_lexart_en.md
new file mode 100644
index 00000000000000..947425d55cad28
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-promptgen_lexart_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English promptgen_lexart GPT2Transformer from AUTOMATIC
+author: John Snow Labs
+name: promptgen_lexart
+date: 2025-01-24
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`promptgen_lexart` is a English model originally trained by AUTOMATIC.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/promptgen_lexart_en_5.5.1_3.0_1737718692225.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/promptgen_lexart_en_5.5.1_3.0_1737718692225.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("promptgen_lexart","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("promptgen_lexart","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|promptgen_lexart|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|308.4 MB|
+
+## References
+
+https://huggingface.co/AUTOMATIC/promptgen-lexart
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-promptgen_lexart_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-promptgen_lexart_pipeline_en.md
new file mode 100644
index 00000000000000..a479f9710b16ee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-promptgen_lexart_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English promptgen_lexart_pipeline pipeline GPT2Transformer from AUTOMATIC
+author: John Snow Labs
+name: promptgen_lexart_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`promptgen_lexart_pipeline` is a English model originally trained by AUTOMATIC.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/promptgen_lexart_pipeline_en_5.5.1_3.0_1737718708292.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/promptgen_lexart_pipeline_en_5.5.1_3.0_1737718708292.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("promptgen_lexart_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("promptgen_lexart_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|promptgen_lexart_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|308.4 MB|
+
+## References
+
+https://huggingface.co/AUTOMATIC/promptgen-lexart
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-promptist_en.md b/docs/_posts/ahmedlone127/2025-01-24-promptist_en.md
new file mode 100644
index 00000000000000..8da38db7f5bd4a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-promptist_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English promptist GPT2Transformer from microsoft
+author: John Snow Labs
+name: promptist
+date: 2025-01-24
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`promptist` is a English model originally trained by microsoft.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/promptist_en_5.5.1_3.0_1737716326658.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/promptist_en_5.5.1_3.0_1737716326658.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("promptist","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("promptist","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|promptist|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.9 MB|
+
+## References
+
+https://huggingface.co/microsoft/Promptist
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-promptist_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-promptist_pipeline_en.md
new file mode 100644
index 00000000000000..98bf275cca070b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-promptist_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English promptist_pipeline pipeline GPT2Transformer from microsoft
+author: John Snow Labs
+name: promptist_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`promptist_pipeline` is a English model originally trained by microsoft.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/promptist_pipeline_en_5.5.1_3.0_1737716360724.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/promptist_pipeline_en_5.5.1_3.0_1737716360724.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("promptist_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("promptist_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|promptist_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.9 MB|
+
+## References
+
+https://huggingface.co/microsoft/Promptist
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-protgpt2_distilled_medium_en.md b/docs/_posts/ahmedlone127/2025-01-24-protgpt2_distilled_medium_en.md
new file mode 100644
index 00000000000000..de061e040d29f2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-protgpt2_distilled_medium_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English protgpt2_distilled_medium GPT2Transformer from littleworth
+author: John Snow Labs
+name: protgpt2_distilled_medium
+date: 2025-01-24
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`protgpt2_distilled_medium` is a English model originally trained by littleworth.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/protgpt2_distilled_medium_en_5.5.1_3.0_1737731947341.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/protgpt2_distilled_medium_en_5.5.1_3.0_1737731947341.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("protgpt2_distilled_medium","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("protgpt2_distilled_medium","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|protgpt2_distilled_medium|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|763.9 MB|
+
+## References
+
+https://huggingface.co/littleworth/protgpt2-distilled-medium
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-protgpt2_distilled_medium_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-protgpt2_distilled_medium_pipeline_en.md
new file mode 100644
index 00000000000000..d8e5cba9959256
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-protgpt2_distilled_medium_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English protgpt2_distilled_medium_pipeline pipeline GPT2Transformer from littleworth
+author: John Snow Labs
+name: protgpt2_distilled_medium_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`protgpt2_distilled_medium_pipeline` is a English model originally trained by littleworth.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/protgpt2_distilled_medium_pipeline_en_5.5.1_3.0_1737731987408.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/protgpt2_distilled_medium_pipeline_en_5.5.1_3.0_1737731987408.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("protgpt2_distilled_medium_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("protgpt2_distilled_medium_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|protgpt2_distilled_medium_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|763.9 MB|
+
+## References
+
+https://huggingface.co/littleworth/protgpt2-distilled-medium
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-pubmedbert_tlink_en.md b/docs/_posts/ahmedlone127/2025-01-24-pubmedbert_tlink_en.md
new file mode 100644
index 00000000000000..d8b0e38d2de793
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-pubmedbert_tlink_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English pubmedbert_tlink BertForSequenceClassification from HealthNLP
+author: John Snow Labs
+name: pubmedbert_tlink
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pubmedbert_tlink` is a English model originally trained by HealthNLP.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pubmedbert_tlink_en_5.5.1_3.0_1737711025052.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pubmedbert_tlink_en_5.5.1_3.0_1737711025052.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("pubmedbert_tlink","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("pubmedbert_tlink", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pubmedbert_tlink|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|410.3 MB|
+
+## References
+
+https://huggingface.co/HealthNLP/pubmedbert_tlink
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-pubmedbert_tlink_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-pubmedbert_tlink_pipeline_en.md
new file mode 100644
index 00000000000000..29b36cd3e35b2b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-pubmedbert_tlink_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English pubmedbert_tlink_pipeline pipeline BertForSequenceClassification from HealthNLP
+author: John Snow Labs
+name: pubmedbert_tlink_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pubmedbert_tlink_pipeline` is a English model originally trained by HealthNLP.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pubmedbert_tlink_pipeline_en_5.5.1_3.0_1737711047323.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pubmedbert_tlink_pipeline_en_5.5.1_3.0_1737711047323.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("pubmedbert_tlink_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("pubmedbert_tlink_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pubmedbert_tlink_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.3 MB|
+
+## References
+
+https://huggingface.co/HealthNLP/pubmedbert_tlink
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-qa_distillbert_en.md b/docs/_posts/ahmedlone127/2025-01-24-qa_distillbert_en.md
new file mode 100644
index 00000000000000..4b119c9b160554
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-qa_distillbert_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English qa_distillbert DistilBertForQuestionAnswering from aanwar
+author: John Snow Labs
+name: qa_distillbert
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_distillbert` is a English model originally trained by aanwar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_distillbert_en_5.5.1_3.0_1737741011882.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_distillbert_en_5.5.1_3.0_1737741011882.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("qa_distillbert","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("qa_distillbert", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_distillbert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/aanwar/QA_distillBERT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-qa_distillbert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-qa_distillbert_pipeline_en.md
new file mode 100644
index 00000000000000..fcdaba83403099
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-qa_distillbert_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English qa_distillbert_pipeline pipeline DistilBertForQuestionAnswering from aanwar
+author: John Snow Labs
+name: qa_distillbert_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_distillbert_pipeline` is a English model originally trained by aanwar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_distillbert_pipeline_en_5.5.1_3.0_1737741033503.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_distillbert_pipeline_en_5.5.1_3.0_1737741033503.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("qa_distillbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("qa_distillbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_distillbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/aanwar/QA_distillBERT
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-qa_finetuned_arabert_ar.md b/docs/_posts/ahmedlone127/2025-01-24-qa_finetuned_arabert_ar.md
new file mode 100644
index 00000000000000..801df427bbd20d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-qa_finetuned_arabert_ar.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Arabic qa_finetuned_arabert BertForQuestionAnswering from gp-tar4
+author: John Snow Labs
+name: qa_finetuned_arabert
+date: 2025-01-24
+tags: [ar, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: ar
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_finetuned_arabert` is a Arabic model originally trained by gp-tar4.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_finetuned_arabert_ar_5.5.1_3.0_1737691687473.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_finetuned_arabert_ar_5.5.1_3.0_1737691687473.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("qa_finetuned_arabert","ar") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("qa_finetuned_arabert", "ar")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_finetuned_arabert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|ar|
+|Size:|504.6 MB|
+
+## References
+
+https://huggingface.co/gp-tar4/QA_FineTuned_Arabert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-qa_finetuned_arabert_pipeline_ar.md b/docs/_posts/ahmedlone127/2025-01-24-qa_finetuned_arabert_pipeline_ar.md
new file mode 100644
index 00000000000000..2d6db5f46337d2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-qa_finetuned_arabert_pipeline_ar.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Arabic qa_finetuned_arabert_pipeline pipeline BertForQuestionAnswering from gp-tar4
+author: John Snow Labs
+name: qa_finetuned_arabert_pipeline
+date: 2025-01-24
+tags: [ar, open_source, pipeline, onnx]
+task: Question Answering
+language: ar
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_finetuned_arabert_pipeline` is a Arabic model originally trained by gp-tar4.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_finetuned_arabert_pipeline_ar_5.5.1_3.0_1737691724065.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_finetuned_arabert_pipeline_ar_5.5.1_3.0_1737691724065.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("qa_finetuned_arabert_pipeline", lang = "ar")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("qa_finetuned_arabert_pipeline", lang = "ar")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_finetuned_arabert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ar|
+|Size:|504.6 MB|
+
+## References
+
+https://huggingface.co/gp-tar4/QA_FineTuned_Arabert
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-qa_jimbohsueh_en.md b/docs/_posts/ahmedlone127/2025-01-24-qa_jimbohsueh_en.md
new file mode 100644
index 00000000000000..86f5e53d562c9a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-qa_jimbohsueh_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English qa_jimbohsueh BertForQuestionAnswering from jimboHsueh
+author: John Snow Labs
+name: qa_jimbohsueh
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_jimbohsueh` is a English model originally trained by jimboHsueh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_jimbohsueh_en_5.5.1_3.0_1737751007198.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_jimbohsueh_en_5.5.1_3.0_1737751007198.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("qa_jimbohsueh","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("qa_jimbohsueh", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_jimbohsueh|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/jimboHsueh/QA
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-qa_jimbohsueh_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-qa_jimbohsueh_pipeline_en.md
new file mode 100644
index 00000000000000..8b6f970f4b73cf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-qa_jimbohsueh_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English qa_jimbohsueh_pipeline pipeline BertForQuestionAnswering from jimboHsueh
+author: John Snow Labs
+name: qa_jimbohsueh_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_jimbohsueh_pipeline` is a English model originally trained by jimboHsueh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_jimbohsueh_pipeline_en_5.5.1_3.0_1737751071162.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_jimbohsueh_pipeline_en_5.5.1_3.0_1737751071162.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("qa_jimbohsueh_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("qa_jimbohsueh_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_jimbohsueh_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/jimboHsueh/QA
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-qa_model_catpawdev_en.md b/docs/_posts/ahmedlone127/2025-01-24-qa_model_catpawdev_en.md
new file mode 100644
index 00000000000000..66d0a14cc84665
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-qa_model_catpawdev_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English qa_model_catpawdev BertForQuestionAnswering from catpawdev
+author: John Snow Labs
+name: qa_model_catpawdev
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_model_catpawdev` is a English model originally trained by catpawdev.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_model_catpawdev_en_5.5.1_3.0_1737756875459.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_model_catpawdev_en_5.5.1_3.0_1737756875459.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("qa_model_catpawdev","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("qa_model_catpawdev", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_model_catpawdev|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/catpawdev/QA_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-qa_model_catpawdev_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-qa_model_catpawdev_pipeline_en.md
new file mode 100644
index 00000000000000..1fb367bb57cac6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-qa_model_catpawdev_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English qa_model_catpawdev_pipeline pipeline BertForQuestionAnswering from catpawdev
+author: John Snow Labs
+name: qa_model_catpawdev_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_model_catpawdev_pipeline` is a English model originally trained by catpawdev.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_model_catpawdev_pipeline_en_5.5.1_3.0_1737756908750.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_model_catpawdev_pipeline_en_5.5.1_3.0_1737756908750.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("qa_model_catpawdev_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("qa_model_catpawdev_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_model_catpawdev_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/catpawdev/QA_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-qa_model_silxxor_en.md b/docs/_posts/ahmedlone127/2025-01-24-qa_model_silxxor_en.md
new file mode 100644
index 00000000000000..8148ad9271052d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-qa_model_silxxor_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English qa_model_silxxor BertForQuestionAnswering from Silxxor
+author: John Snow Labs
+name: qa_model_silxxor
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_model_silxxor` is a English model originally trained by Silxxor.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_model_silxxor_en_5.5.1_3.0_1737757029868.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_model_silxxor_en_5.5.1_3.0_1737757029868.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("qa_model_silxxor","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("qa_model_silxxor", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_model_silxxor|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|664.3 MB|
+
+## References
+
+https://huggingface.co/Silxxor/qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-qa_model_silxxor_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-qa_model_silxxor_pipeline_en.md
new file mode 100644
index 00000000000000..abe3c31264de31
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-qa_model_silxxor_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English qa_model_silxxor_pipeline pipeline BertForQuestionAnswering from Silxxor
+author: John Snow Labs
+name: qa_model_silxxor_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_model_silxxor_pipeline` is a English model originally trained by Silxxor.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_model_silxxor_pipeline_en_5.5.1_3.0_1737757067708.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_model_silxxor_pipeline_en_5.5.1_3.0_1737757067708.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("qa_model_silxxor_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("qa_model_silxxor_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_model_silxxor_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|664.3 MB|
+
+## References
+
+https://huggingface.co/Silxxor/qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-qa_nlp_model_en.md b/docs/_posts/ahmedlone127/2025-01-24-qa_nlp_model_en.md
new file mode 100644
index 00000000000000..7633a72e5e2fb6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-qa_nlp_model_en.md
@@ -0,0 +1,92 @@
+---
+layout: model
+title: English qa_nlp_model DistilBertForQuestionAnswering from jolual2747
+author: John Snow Labs
+name: qa_nlp_model
+date: 2025-01-24
+tags: [distilbert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_nlp_model` is a English model originally trained by jolual2747.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_nlp_model_en_5.5.1_3.0_1737741012819.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_nlp_model_en_5.5.1_3.0_1737741012819.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("qa_nlp_model","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering  
+    .pretrained("qa_nlp_model", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_nlp_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+References
+
+https://huggingface.co/jolual2747/qa_nlp_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-qa_nlp_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-qa_nlp_model_pipeline_en.md
new file mode 100644
index 00000000000000..f539c3b07f1280
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-qa_nlp_model_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English qa_nlp_model_pipeline pipeline DistilBertForQuestionAnswering from OmidSakaki
+author: John Snow Labs
+name: qa_nlp_model_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_nlp_model_pipeline` is a English model originally trained by OmidSakaki.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_nlp_model_pipeline_en_5.5.1_3.0_1737741033416.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_nlp_model_pipeline_en_5.5.1_3.0_1737741033416.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("qa_nlp_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("qa_nlp_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_nlp_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/OmidSakaki/qa_nlp_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-qa_nomsgadded_en.md b/docs/_posts/ahmedlone127/2025-01-24-qa_nomsgadded_en.md
new file mode 100644
index 00000000000000..a7ba21b9180828
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-qa_nomsgadded_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English qa_nomsgadded BertForQuestionAnswering from nomsgadded
+author: John Snow Labs
+name: qa_nomsgadded
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_nomsgadded` is a English model originally trained by nomsgadded.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_nomsgadded_en_5.5.1_3.0_1737747269448.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_nomsgadded_en_5.5.1_3.0_1737747269448.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("qa_nomsgadded","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("qa_nomsgadded", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_nomsgadded|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/nomsgadded/qa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-qa_nomsgadded_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-qa_nomsgadded_pipeline_en.md
new file mode 100644
index 00000000000000..847a87c9a0b161
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-qa_nomsgadded_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English qa_nomsgadded_pipeline pipeline BertForQuestionAnswering from nomsgadded
+author: John Snow Labs
+name: qa_nomsgadded_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_nomsgadded_pipeline` is a English model originally trained by nomsgadded.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_nomsgadded_pipeline_en_5.5.1_3.0_1737747291024.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_nomsgadded_pipeline_en_5.5.1_3.0_1737747291024.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("qa_nomsgadded_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("qa_nomsgadded_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_nomsgadded_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/nomsgadded/qa
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-qa_python_en.md b/docs/_posts/ahmedlone127/2025-01-24-qa_python_en.md
new file mode 100644
index 00000000000000..cbd2edd2373b3b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-qa_python_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English qa_python RoBertaForQuestionAnswering from Aya4567
+author: John Snow Labs
+name: qa_python
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_python` is a English model originally trained by Aya4567.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_python_en_5.5.1_3.0_1737687675049.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_python_en_5.5.1_3.0_1737687675049.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("qa_python","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("qa_python", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_python|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|465.5 MB|
+
+## References
+
+https://huggingface.co/Aya4567/QA_Python
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-qa_python_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-qa_python_pipeline_en.md
new file mode 100644
index 00000000000000..a2c0b4e072e848
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-qa_python_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English qa_python_pipeline pipeline RoBertaForQuestionAnswering from Aya4567
+author: John Snow Labs
+name: qa_python_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_python_pipeline` is a English model originally trained by Aya4567.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_python_pipeline_en_5.5.1_3.0_1737687700015.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_python_pipeline_en_5.5.1_3.0_1737687700015.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("qa_python_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("qa_python_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_python_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|465.5 MB|
+
+## References
+
+https://huggingface.co/Aya4567/QA_Python
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-qa_tquad_convbert_base_turkish_en.md b/docs/_posts/ahmedlone127/2025-01-24-qa_tquad_convbert_base_turkish_en.md
new file mode 100644
index 00000000000000..4a85926dc41eed
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-qa_tquad_convbert_base_turkish_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English qa_tquad_convbert_base_turkish BertForQuestionAnswering from Izzet
+author: John Snow Labs
+name: qa_tquad_convbert_base_turkish
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_tquad_convbert_base_turkish` is a English model originally trained by Izzet.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_tquad_convbert_base_turkish_en_5.5.1_3.0_1737757422954.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_tquad_convbert_base_turkish_en_5.5.1_3.0_1737757422954.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("qa_tquad_convbert_base_turkish","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("qa_tquad_convbert_base_turkish", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_tquad_convbert_base_turkish|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|400.1 MB|
+
+## References
+
+https://huggingface.co/Izzet/qa_tquad_convbert-base-turkish
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-qa_tquad_convbert_base_turkish_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-qa_tquad_convbert_base_turkish_pipeline_en.md
new file mode 100644
index 00000000000000..264b500322e4d4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-qa_tquad_convbert_base_turkish_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English qa_tquad_convbert_base_turkish_pipeline pipeline BertForQuestionAnswering from Izzet
+author: John Snow Labs
+name: qa_tquad_convbert_base_turkish_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_tquad_convbert_base_turkish_pipeline` is a English model originally trained by Izzet.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_tquad_convbert_base_turkish_pipeline_en_5.5.1_3.0_1737757446282.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_tquad_convbert_base_turkish_pipeline_en_5.5.1_3.0_1737757446282.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("qa_tquad_convbert_base_turkish_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("qa_tquad_convbert_base_turkish_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_tquad_convbert_base_turkish_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|400.1 MB|
+
+## References
+
+https://huggingface.co/Izzet/qa_tquad_convbert-base-turkish
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-question_answering_bert_en.md b/docs/_posts/ahmedlone127/2025-01-24-question_answering_bert_en.md
new file mode 100644
index 00000000000000..43f4f9112faba4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-question_answering_bert_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English question_answering_bert BertForQuestionAnswering from khaledsayed1
+author: John Snow Labs
+name: question_answering_bert
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`question_answering_bert` is a English model originally trained by khaledsayed1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/question_answering_bert_en_5.5.1_3.0_1737738927935.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/question_answering_bert_en_5.5.1_3.0_1737738927935.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("question_answering_bert","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("question_answering_bert", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|question_answering_bert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/khaledsayed1/Question_answering_bert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-question_answering_bert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-question_answering_bert_pipeline_en.md
new file mode 100644
index 00000000000000..90cb68e6430597
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-question_answering_bert_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English question_answering_bert_pipeline pipeline BertForQuestionAnswering from khaledsayed1
+author: John Snow Labs
+name: question_answering_bert_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`question_answering_bert_pipeline` is a English model originally trained by khaledsayed1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/question_answering_bert_pipeline_en_5.5.1_3.0_1737738950554.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/question_answering_bert_pipeline_en_5.5.1_3.0_1737738950554.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("question_answering_bert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("question_answering_bert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|question_answering_bert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/khaledsayed1/Question_answering_bert
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-question_answering_qa_may_tablang_local_en.md b/docs/_posts/ahmedlone127/2025-01-24-question_answering_qa_may_tablang_local_en.md
new file mode 100644
index 00000000000000..cecf4b8013f2a7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-question_answering_qa_may_tablang_local_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English question_answering_qa_may_tablang_local BertForQuestionAnswering from nathantablang
+author: John Snow Labs
+name: question_answering_qa_may_tablang_local
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`question_answering_qa_may_tablang_local` is a English model originally trained by nathantablang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/question_answering_qa_may_tablang_local_en_5.5.1_3.0_1737738706668.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/question_answering_qa_may_tablang_local_en_5.5.1_3.0_1737738706668.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("question_answering_qa_may_tablang_local","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("question_answering_qa_may_tablang_local", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|question_answering_qa_may_tablang_local|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/nathantablang/question-answering-qa-may-tablang-LOCAL
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-question_answering_qa_may_tablang_local_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-question_answering_qa_may_tablang_local_pipeline_en.md
new file mode 100644
index 00000000000000..baf5cf9449d36c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-question_answering_qa_may_tablang_local_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English question_answering_qa_may_tablang_local_pipeline pipeline BertForQuestionAnswering from nathantablang
+author: John Snow Labs
+name: question_answering_qa_may_tablang_local_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`question_answering_qa_may_tablang_local_pipeline` is a English model originally trained by nathantablang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/question_answering_qa_may_tablang_local_pipeline_en_5.5.1_3.0_1737738779843.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/question_answering_qa_may_tablang_local_pipeline_en_5.5.1_3.0_1737738779843.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("question_answering_qa_may_tablang_local_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("question_answering_qa_may_tablang_local_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|question_answering_qa_may_tablang_local_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/nathantablang/question-answering-qa-may-tablang-LOCAL
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-question_answering_tablang_en.md b/docs/_posts/ahmedlone127/2025-01-24-question_answering_tablang_en.md
new file mode 100644
index 00000000000000..6cae9c02adc9c3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-question_answering_tablang_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English question_answering_tablang BertForQuestionAnswering from nathantablang
+author: John Snow Labs
+name: question_answering_tablang
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`question_answering_tablang` is a English model originally trained by nathantablang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/question_answering_tablang_en_5.5.1_3.0_1737691620386.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/question_answering_tablang_en_5.5.1_3.0_1737691620386.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("question_answering_tablang","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("question_answering_tablang", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|question_answering_tablang|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/nathantablang/question-answering-tablang
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-question_answering_tablang_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-question_answering_tablang_pipeline_en.md
new file mode 100644
index 00000000000000..426da808fad336
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-question_answering_tablang_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English question_answering_tablang_pipeline pipeline BertForQuestionAnswering from nathantablang
+author: John Snow Labs
+name: question_answering_tablang_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`question_answering_tablang_pipeline` is a English model originally trained by nathantablang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/question_answering_tablang_pipeline_en_5.5.1_3.0_1737691683120.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/question_answering_tablang_pipeline_en_5.5.1_3.0_1737691683120.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("question_answering_tablang_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("question_answering_tablang_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|question_answering_tablang_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/nathantablang/question-answering-tablang
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-quinto_question_answear_en.md b/docs/_posts/ahmedlone127/2025-01-24-quinto_question_answear_en.md
new file mode 100644
index 00000000000000..ee17619e8ff983
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-quinto_question_answear_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English quinto_question_answear BertForQuestionAnswering from Meziane
+author: John Snow Labs
+name: quinto_question_answear
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`quinto_question_answear` is a English model originally trained by Meziane.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/quinto_question_answear_en_5.5.1_3.0_1737739458493.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/quinto_question_answear_en_5.5.1_3.0_1737739458493.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("quinto_question_answear","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("quinto_question_answear", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|quinto_question_answear|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/Meziane/quinto_question_answear
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-quinto_question_answear_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-quinto_question_answear_pipeline_en.md
new file mode 100644
index 00000000000000..976f9f2a2087c0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-quinto_question_answear_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English quinto_question_answear_pipeline pipeline BertForQuestionAnswering from Meziane
+author: John Snow Labs
+name: quinto_question_answear_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`quinto_question_answear_pipeline` is a English model originally trained by Meziane.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/quinto_question_answear_pipeline_en_5.5.1_3.0_1737739480695.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/quinto_question_answear_pipeline_en_5.5.1_3.0_1737739480695.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("quinto_question_answear_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("quinto_question_answear_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|quinto_question_answear_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/Meziane/quinto_question_answear
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-rahul_context_ai_01_en.md b/docs/_posts/ahmedlone127/2025-01-24-rahul_context_ai_01_en.md
new file mode 100644
index 00000000000000..f14483858fbdfa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-rahul_context_ai_01_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English rahul_context_ai_01 BertForQuestionAnswering from rahul7star
+author: John Snow Labs
+name: rahul_context_ai_01
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rahul_context_ai_01` is a English model originally trained by rahul7star.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rahul_context_ai_01_en_5.5.1_3.0_1737739475078.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rahul_context_ai_01_en_5.5.1_3.0_1737739475078.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("rahul_context_ai_01","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("rahul_context_ai_01", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rahul_context_ai_01|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/rahul7star/Rahul-Context-AI-01
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-rahul_context_ai_01_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-rahul_context_ai_01_pipeline_en.md
new file mode 100644
index 00000000000000..664bb9abe98a66
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-rahul_context_ai_01_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English rahul_context_ai_01_pipeline pipeline BertForQuestionAnswering from rahul7star
+author: John Snow Labs
+name: rahul_context_ai_01_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rahul_context_ai_01_pipeline` is a English model originally trained by rahul7star.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rahul_context_ai_01_pipeline_en_5.5.1_3.0_1737739541908.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rahul_context_ai_01_pipeline_en_5.5.1_3.0_1737739541908.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("rahul_context_ai_01_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("rahul_context_ai_01_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rahul_context_ai_01_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/rahul7star/Rahul-Context-AI-01
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-remote_sensing_image_swin_transformer_en.md b/docs/_posts/ahmedlone127/2025-01-24-remote_sensing_image_swin_transformer_en.md
new file mode 100644
index 00000000000000..6920eb704b4baf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-remote_sensing_image_swin_transformer_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English remote_sensing_image_swin_transformer SwinForImageClassification from SeyedAli
+author: John Snow Labs
+name: remote_sensing_image_swin_transformer
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`remote_sensing_image_swin_transformer` is a English model originally trained by SeyedAli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/remote_sensing_image_swin_transformer_en_5.5.1_3.0_1737715750074.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/remote_sensing_image_swin_transformer_en_5.5.1_3.0_1737715750074.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""remote_sensing_image_swin_transformer","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("remote_sensing_image_swin_transformer","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|remote_sensing_image_swin_transformer|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|649.8 MB|
+
+## References
+
+https://huggingface.co/SeyedAli/Remote_Sensing_Image_Swin_Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-remote_sensing_image_swin_transformer_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-remote_sensing_image_swin_transformer_pipeline_en.md
new file mode 100644
index 00000000000000..747f57467ce386
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-remote_sensing_image_swin_transformer_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English remote_sensing_image_swin_transformer_pipeline pipeline SwinForImageClassification from SeyedAli
+author: John Snow Labs
+name: remote_sensing_image_swin_transformer_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`remote_sensing_image_swin_transformer_pipeline` is a English model originally trained by SeyedAli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/remote_sensing_image_swin_transformer_pipeline_en_5.5.1_3.0_1737715784627.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/remote_sensing_image_swin_transformer_pipeline_en_5.5.1_3.0_1737715784627.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("remote_sensing_image_swin_transformer_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("remote_sensing_image_swin_transformer_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|remote_sensing_image_swin_transformer_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|649.8 MB|
+
+## References
+
+https://huggingface.co/SeyedAli/Remote_Sensing_Image_Swin_Transformer
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-results_aren_golazizian_en.md b/docs/_posts/ahmedlone127/2025-01-24-results_aren_golazizian_en.md
new file mode 100644
index 00000000000000..6ac9482eacb491
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-results_aren_golazizian_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English results_aren_golazizian DistilBertForTokenClassification from aren-golazizian
+author: John Snow Labs
+name: results_aren_golazizian
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_aren_golazizian` is a English model originally trained by aren-golazizian.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_aren_golazizian_en_5.5.1_3.0_1737692621491.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_aren_golazizian_en_5.5.1_3.0_1737692621491.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("results_aren_golazizian","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("results_aren_golazizian", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_aren_golazizian|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/aren-golazizian/results
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-results_aren_golazizian_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-results_aren_golazizian_pipeline_en.md
new file mode 100644
index 00000000000000..353c73f114782c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-results_aren_golazizian_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English results_aren_golazizian_pipeline pipeline DistilBertForTokenClassification from aren-golazizian
+author: John Snow Labs
+name: results_aren_golazizian_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_aren_golazizian_pipeline` is a English model originally trained by aren-golazizian.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_aren_golazizian_pipeline_en_5.5.1_3.0_1737692634489.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_aren_golazizian_pipeline_en_5.5.1_3.0_1737692634489.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("results_aren_golazizian_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("results_aren_golazizian_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_aren_golazizian_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/aren-golazizian/results
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-results_pipeline_uz.md b/docs/_posts/ahmedlone127/2025-01-24-results_pipeline_uz.md
new file mode 100644
index 00000000000000..52f7ad841cb3f3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-results_pipeline_uz.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Uzbek results_pipeline pipeline XlmRoBertaForTokenClassification from Xojakbar
+author: John Snow Labs
+name: results_pipeline
+date: 2025-01-24
+tags: [uz, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: uz
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_pipeline` is a Uzbek model originally trained by Xojakbar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_pipeline_uz_5.5.1_3.0_1737679850612.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_pipeline_uz_5.5.1_3.0_1737679850612.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("results_pipeline", lang = "uz")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("results_pipeline", lang = "uz")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|uz|
+|Size:|819.0 MB|
+
+## References
+
+https://huggingface.co/Xojakbar/results
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-results_uz.md b/docs/_posts/ahmedlone127/2025-01-24-results_uz.md
new file mode 100644
index 00000000000000..d789060abb9fe5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-results_uz.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Uzbek results XlmRoBertaForTokenClassification from Xojakbar
+author: John Snow Labs
+name: results
+date: 2025-01-24
+tags: [uz, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: uz
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results` is a Uzbek model originally trained by Xojakbar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_uz_5.5.1_3.0_1737679727517.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_uz_5.5.1_3.0_1737679727517.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("results","uz") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("results", "uz")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|uz|
+|Size:|819.0 MB|
+
+## References
+
+https://huggingface.co/Xojakbar/results
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-rgai_emotion_recognition_en.md b/docs/_posts/ahmedlone127/2025-01-24-rgai_emotion_recognition_en.md
new file mode 100644
index 00000000000000..6409af551663a8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-rgai_emotion_recognition_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English rgai_emotion_recognition SwinForImageClassification from aswincandra
+author: John Snow Labs
+name: rgai_emotion_recognition
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rgai_emotion_recognition` is a English model originally trained by aswincandra.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rgai_emotion_recognition_en_5.5.1_3.0_1737754620669.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rgai_emotion_recognition_en_5.5.1_3.0_1737754620669.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""rgai_emotion_recognition","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("rgai_emotion_recognition","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rgai_emotion_recognition|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|642.7 MB|
+
+## References
+
+https://huggingface.co/aswincandra/rgai_emotion_recognition
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-rgai_emotion_recognition_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-rgai_emotion_recognition_pipeline_en.md
new file mode 100644
index 00000000000000..11fce44c3c50d9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-rgai_emotion_recognition_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English rgai_emotion_recognition_pipeline pipeline SwinForImageClassification from aswincandra
+author: John Snow Labs
+name: rgai_emotion_recognition_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rgai_emotion_recognition_pipeline` is a English model originally trained by aswincandra.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rgai_emotion_recognition_pipeline_en_5.5.1_3.0_1737754655490.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rgai_emotion_recognition_pipeline_en_5.5.1_3.0_1737754655490.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("rgai_emotion_recognition_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("rgai_emotion_recognition_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rgai_emotion_recognition_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|642.7 MB|
+
+## References
+
+https://huggingface.co/aswincandra/rgai_emotion_recognition
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-rinna_arabert22_qa_ar2_en.md b/docs/_posts/ahmedlone127/2025-01-24-rinna_arabert22_qa_ar2_en.md
new file mode 100644
index 00000000000000..53b7a08a39c5e4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-rinna_arabert22_qa_ar2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English rinna_arabert22_qa_ar2 BertForQuestionAnswering from Echiguerkh
+author: John Snow Labs
+name: rinna_arabert22_qa_ar2
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rinna_arabert22_qa_ar2` is a English model originally trained by Echiguerkh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rinna_arabert22_qa_ar2_en_5.5.1_3.0_1737751609677.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rinna_arabert22_qa_ar2_en_5.5.1_3.0_1737751609677.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("rinna_arabert22_qa_ar2","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("rinna_arabert22_qa_ar2", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rinna_arabert22_qa_ar2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|504.3 MB|
+
+## References
+
+https://huggingface.co/Echiguerkh/rinna-arabert22-qa-ar2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-rinna_arabert22_qa_ar2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-rinna_arabert22_qa_ar2_pipeline_en.md
new file mode 100644
index 00000000000000..9ac07e7f8cc383
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-rinna_arabert22_qa_ar2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English rinna_arabert22_qa_ar2_pipeline pipeline BertForQuestionAnswering from Echiguerkh
+author: John Snow Labs
+name: rinna_arabert22_qa_ar2_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rinna_arabert22_qa_ar2_pipeline` is a English model originally trained by Echiguerkh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rinna_arabert22_qa_ar2_pipeline_en_5.5.1_3.0_1737751641791.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rinna_arabert22_qa_ar2_pipeline_en_5.5.1_3.0_1737751641791.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("rinna_arabert22_qa_ar2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("rinna_arabert22_qa_ar2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rinna_arabert22_qa_ar2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|504.3 MB|
+
+## References
+
+https://huggingface.co/Echiguerkh/rinna-arabert22-qa-ar2
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-robbert_timostrijbis_en.md b/docs/_posts/ahmedlone127/2025-01-24-robbert_timostrijbis_en.md
new file mode 100644
index 00000000000000..592d89f4c24ae5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-robbert_timostrijbis_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English robbert_timostrijbis BertForQuestionAnswering from Timostrijbis
+author: John Snow Labs
+name: robbert_timostrijbis
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`robbert_timostrijbis` is a English model originally trained by Timostrijbis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/robbert_timostrijbis_en_5.5.1_3.0_1737751769069.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/robbert_timostrijbis_en_5.5.1_3.0_1737751769069.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("robbert_timostrijbis","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("robbert_timostrijbis", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|robbert_timostrijbis|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/Timostrijbis/RobBERT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-robbert_timostrijbis_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-robbert_timostrijbis_pipeline_en.md
new file mode 100644
index 00000000000000..ee7e9d9393ebdf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-robbert_timostrijbis_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English robbert_timostrijbis_pipeline pipeline BertForQuestionAnswering from Timostrijbis
+author: John Snow Labs
+name: robbert_timostrijbis_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`robbert_timostrijbis_pipeline` is a English model originally trained by Timostrijbis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/robbert_timostrijbis_pipeline_en_5.5.1_3.0_1737751791394.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/robbert_timostrijbis_pipeline_en_5.5.1_3.0_1737751791394.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("robbert_timostrijbis_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("robbert_timostrijbis_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|robbert_timostrijbis_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/Timostrijbis/RobBERT
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-roberta_base_anatem_en.md b/docs/_posts/ahmedlone127/2025-01-24-roberta_base_anatem_en.md
new file mode 100644
index 00000000000000..5850935f3cdd70
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-roberta_base_anatem_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_base_anatem RoBertaForTokenClassification from CheccoCando
+author: John Snow Labs
+name: roberta_base_anatem
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_anatem` is a English model originally trained by CheccoCando.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_anatem_en_5.5.1_3.0_1737755952293.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_anatem_en_5.5.1_3.0_1737755952293.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("roberta_base_anatem","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_base_anatem", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_anatem|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|437.4 MB|
+
+## References
+
+https://huggingface.co/CheccoCando/roberta-base_AnatEM
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-roberta_base_anatem_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-roberta_base_anatem_pipeline_en.md
new file mode 100644
index 00000000000000..aa68c4db2579dd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-roberta_base_anatem_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_base_anatem_pipeline pipeline RoBertaForTokenClassification from CheccoCando
+author: John Snow Labs
+name: roberta_base_anatem_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_anatem_pipeline` is a English model originally trained by CheccoCando.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_anatem_pipeline_en_5.5.1_3.0_1737755980364.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_anatem_pipeline_en_5.5.1_3.0_1737755980364.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_base_anatem_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_anatem_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_anatem_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|437.5 MB|
+
+## References
+
+https://huggingface.co/CheccoCando/roberta-base_AnatEM
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-roberta_base_biomedical_clinical_spanish_ner_en.md b/docs/_posts/ahmedlone127/2025-01-24-roberta_base_biomedical_clinical_spanish_ner_en.md
new file mode 100644
index 00000000000000..9e67e7933fa949
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-roberta_base_biomedical_clinical_spanish_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_base_biomedical_clinical_spanish_ner RoBertaForTokenClassification from manucos
+author: John Snow Labs
+name: roberta_base_biomedical_clinical_spanish_ner
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_biomedical_clinical_spanish_ner` is a English model originally trained by manucos.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_biomedical_clinical_spanish_ner_en_5.5.1_3.0_1737685786567.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_biomedical_clinical_spanish_ner_en_5.5.1_3.0_1737685786567.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("roberta_base_biomedical_clinical_spanish_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_base_biomedical_clinical_spanish_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_biomedical_clinical_spanish_ner|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|422.8 MB|
+
+## References
+
+https://huggingface.co/manucos/roberta-base-biomedical-clinical-es-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-roberta_base_biomedical_clinical_spanish_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-roberta_base_biomedical_clinical_spanish_ner_pipeline_en.md
new file mode 100644
index 00000000000000..23b327ecf98314
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-roberta_base_biomedical_clinical_spanish_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_base_biomedical_clinical_spanish_ner_pipeline pipeline RoBertaForTokenClassification from manucos
+author: John Snow Labs
+name: roberta_base_biomedical_clinical_spanish_ner_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_biomedical_clinical_spanish_ner_pipeline` is a English model originally trained by manucos.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_biomedical_clinical_spanish_ner_pipeline_en_5.5.1_3.0_1737685824725.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_biomedical_clinical_spanish_ner_pipeline_en_5.5.1_3.0_1737685824725.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_base_biomedical_clinical_spanish_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_biomedical_clinical_spanish_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_biomedical_clinical_spanish_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|422.8 MB|
+
+## References
+
+https://huggingface.co/manucos/roberta-base-biomedical-clinical-es-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-roberta_base_bne_ner_en.md b/docs/_posts/ahmedlone127/2025-01-24-roberta_base_bne_ner_en.md
new file mode 100644
index 00000000000000..3efb95dc898574
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-roberta_base_bne_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_base_bne_ner RoBertaForTokenClassification from manucos
+author: John Snow Labs
+name: roberta_base_bne_ner
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_bne_ner` is a English model originally trained by manucos.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_bne_ner_en_5.5.1_3.0_1737703581675.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_bne_ner_en_5.5.1_3.0_1737703581675.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("roberta_base_bne_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_base_bne_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_bne_ner|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|418.2 MB|
+
+## References
+
+https://huggingface.co/manucos/roberta-base-bne-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-roberta_base_bne_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-roberta_base_bne_ner_pipeline_en.md
new file mode 100644
index 00000000000000..a6179df97ba202
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-roberta_base_bne_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_base_bne_ner_pipeline pipeline RoBertaForTokenClassification from manucos
+author: John Snow Labs
+name: roberta_base_bne_ner_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_bne_ner_pipeline` is a English model originally trained by manucos.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_bne_ner_pipeline_en_5.5.1_3.0_1737703617876.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_bne_ner_pipeline_en_5.5.1_3.0_1737703617876.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_base_bne_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_bne_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_bne_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|418.3 MB|
+
+## References
+
+https://huggingface.co/manucos/roberta-base-bne-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-roberta_base_broad_tweet_corpus_en.md b/docs/_posts/ahmedlone127/2025-01-24-roberta_base_broad_tweet_corpus_en.md
new file mode 100644
index 00000000000000..8f1e8a69905906
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-roberta_base_broad_tweet_corpus_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_base_broad_tweet_corpus RoBertaForTokenClassification from CheccoCando
+author: John Snow Labs
+name: roberta_base_broad_tweet_corpus
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_broad_tweet_corpus` is a English model originally trained by CheccoCando.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_broad_tweet_corpus_en_5.5.1_3.0_1737702247378.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_broad_tweet_corpus_en_5.5.1_3.0_1737702247378.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("roberta_base_broad_tweet_corpus","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_base_broad_tweet_corpus", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_broad_tweet_corpus|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|442.4 MB|
+
+## References
+
+https://huggingface.co/CheccoCando/roberta-base_Broad_Tweet_Corpus
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-roberta_base_broad_tweet_corpus_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-roberta_base_broad_tweet_corpus_pipeline_en.md
new file mode 100644
index 00000000000000..df0339f8815d7e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-roberta_base_broad_tweet_corpus_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_base_broad_tweet_corpus_pipeline pipeline RoBertaForTokenClassification from CheccoCando
+author: John Snow Labs
+name: roberta_base_broad_tweet_corpus_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_broad_tweet_corpus_pipeline` is a English model originally trained by CheccoCando.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_broad_tweet_corpus_pipeline_en_5.5.1_3.0_1737702276836.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_broad_tweet_corpus_pipeline_en_5.5.1_3.0_1737702276836.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_base_broad_tweet_corpus_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_broad_tweet_corpus_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_broad_tweet_corpus_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|442.4 MB|
+
+## References
+
+https://huggingface.co/CheccoCando/roberta-base_Broad_Tweet_Corpus
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-roberta_base_coco_ner_en.md b/docs/_posts/ahmedlone127/2025-01-24-roberta_base_coco_ner_en.md
new file mode 100644
index 00000000000000..fe438e8f3534ba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-roberta_base_coco_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_base_coco_ner RoBertaForTokenClassification from A-dung-ng31
+author: John Snow Labs
+name: roberta_base_coco_ner
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_coco_ner` is a English model originally trained by A-dung-ng31.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_coco_ner_en_5.5.1_3.0_1737755908860.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_coco_ner_en_5.5.1_3.0_1737755908860.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("roberta_base_coco_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_base_coco_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_coco_ner|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|427.6 MB|
+
+## References
+
+https://huggingface.co/A-dung-ng31/roberta-base-coco-NER
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-roberta_base_coco_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-roberta_base_coco_ner_pipeline_en.md
new file mode 100644
index 00000000000000..4601f5dab0ed73
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-roberta_base_coco_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_base_coco_ner_pipeline pipeline RoBertaForTokenClassification from A-dung-ng31
+author: John Snow Labs
+name: roberta_base_coco_ner_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_coco_ner_pipeline` is a English model originally trained by A-dung-ng31.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_coco_ner_pipeline_en_5.5.1_3.0_1737755945916.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_coco_ner_pipeline_en_5.5.1_3.0_1737755945916.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_base_coco_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_coco_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_coco_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|427.7 MB|
+
+## References
+
+https://huggingface.co/A-dung-ng31/roberta-base-coco-NER
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-roberta_base_finetuned_ner_cadec_en.md b/docs/_posts/ahmedlone127/2025-01-24-roberta_base_finetuned_ner_cadec_en.md
new file mode 100644
index 00000000000000..3f27a11c38968f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-roberta_base_finetuned_ner_cadec_en.md
@@ -0,0 +1,96 @@
+---
+layout: model
+title: English roberta_base_finetuned_ner_cadec RoBertaForTokenClassification from csNoHug
+author: John Snow Labs
+name: roberta_base_finetuned_ner_cadec
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_finetuned_ner_cadec` is a English model originally trained by csNoHug.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_finetuned_ner_cadec_en_5.5.1_3.0_1737755507524.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_finetuned_ner_cadec_en_5.5.1_3.0_1737755507524.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("roberta_base_finetuned_ner_cadec","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_base_finetuned_ner_cadec", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_finetuned_ner_cadec|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|427.6 MB|
+
+## References
+
+References
+
+https://huggingface.co/csNoHug/roberta-base-finetuned-ner-cadec
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-roberta_base_finetuned_ner_cadec_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-roberta_base_finetuned_ner_cadec_pipeline_en.md
new file mode 100644
index 00000000000000..93a54871ec0022
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-roberta_base_finetuned_ner_cadec_pipeline_en.md
@@ -0,0 +1,72 @@
+---
+layout: model
+title: English roberta_base_finetuned_ner_cadec_pipeline pipeline RoBertaForTokenClassification from csNoHug
+author: John Snow Labs
+name: roberta_base_finetuned_ner_cadec_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_finetuned_ner_cadec_pipeline` is a English model originally trained by csNoHug.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_finetuned_ner_cadec_pipeline_en_5.5.1_3.0_1737755542681.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_finetuned_ner_cadec_pipeline_en_5.5.1_3.0_1737755542681.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("roberta_base_finetuned_ner_cadec_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("roberta_base_finetuned_ner_cadec_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_finetuned_ner_cadec_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|427.6 MB|
+
+## References
+
+References
+
+https://huggingface.co/csNoHug/roberta-base-finetuned-ner-cadec
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-roberta_base_finetuned_ner_en.md b/docs/_posts/ahmedlone127/2025-01-24-roberta_base_finetuned_ner_en.md
new file mode 100644
index 00000000000000..4353469f722186
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-roberta_base_finetuned_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_base_finetuned_ner RoBertaForTokenClassification from heisenberg3376
+author: John Snow Labs
+name: roberta_base_finetuned_ner
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_finetuned_ner` is a English model originally trained by heisenberg3376.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_finetuned_ner_en_5.5.1_3.0_1737702726557.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_finetuned_ner_en_5.5.1_3.0_1737702726557.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("roberta_base_finetuned_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_base_finetuned_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_finetuned_ner|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|440.3 MB|
+
+## References
+
+https://huggingface.co/heisenberg3376/roberta-base-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-roberta_base_finetuned_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-roberta_base_finetuned_ner_pipeline_en.md
new file mode 100644
index 00000000000000..76d975d3ef38ba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-roberta_base_finetuned_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_base_finetuned_ner_pipeline pipeline RoBertaForTokenClassification from heisenberg3376
+author: John Snow Labs
+name: roberta_base_finetuned_ner_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_finetuned_ner_pipeline` is a English model originally trained by heisenberg3376.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_finetuned_ner_pipeline_en_5.5.1_3.0_1737702757994.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_finetuned_ner_pipeline_en_5.5.1_3.0_1737702757994.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_base_finetuned_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_finetuned_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_finetuned_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|440.3 MB|
+
+## References
+
+https://huggingface.co/heisenberg3376/roberta-base-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-roberta_base_harveyner_en.md b/docs/_posts/ahmedlone127/2025-01-24-roberta_base_harveyner_en.md
new file mode 100644
index 00000000000000..15fe0346fee1b1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-roberta_base_harveyner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_base_harveyner RoBertaForTokenClassification from CheccoCando
+author: John Snow Labs
+name: roberta_base_harveyner
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_harveyner` is a English model originally trained by CheccoCando.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_harveyner_en_5.5.1_3.0_1737702532177.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_harveyner_en_5.5.1_3.0_1737702532177.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("roberta_base_harveyner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_base_harveyner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_harveyner|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|435.9 MB|
+
+## References
+
+https://huggingface.co/CheccoCando/roberta-base_HarveyNER
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-roberta_base_harveyner_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-roberta_base_harveyner_pipeline_en.md
new file mode 100644
index 00000000000000..ff455c57128442
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-roberta_base_harveyner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_base_harveyner_pipeline pipeline RoBertaForTokenClassification from CheccoCando
+author: John Snow Labs
+name: roberta_base_harveyner_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_harveyner_pipeline` is a English model originally trained by CheccoCando.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_harveyner_pipeline_en_5.5.1_3.0_1737702560798.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_harveyner_pipeline_en_5.5.1_3.0_1737702560798.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_base_harveyner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_harveyner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_harveyner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|435.9 MB|
+
+## References
+
+https://huggingface.co/CheccoCando/roberta-base_HarveyNER
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-roberta_base_ner_demo_turshilt4_mn.md b/docs/_posts/ahmedlone127/2025-01-24-roberta_base_ner_demo_turshilt4_mn.md
new file mode 100644
index 00000000000000..bb46a81b49020f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-roberta_base_ner_demo_turshilt4_mn.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Mongolian roberta_base_ner_demo_turshilt4 RoBertaForTokenClassification from sanchirjav
+author: John Snow Labs
+name: roberta_base_ner_demo_turshilt4
+date: 2025-01-24
+tags: [mn, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: mn
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_ner_demo_turshilt4` is a Mongolian model originally trained by sanchirjav.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_ner_demo_turshilt4_mn_5.5.1_3.0_1737703748978.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_ner_demo_turshilt4_mn_5.5.1_3.0_1737703748978.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("roberta_base_ner_demo_turshilt4","mn") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_base_ner_demo_turshilt4", "mn")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_ner_demo_turshilt4|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|mn|
+|Size:|465.7 MB|
+
+## References
+
+https://huggingface.co/sanchirjav/roberta-base-ner-demo-turshilt4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-roberta_base_ner_demo_turshilt4_pipeline_mn.md b/docs/_posts/ahmedlone127/2025-01-24-roberta_base_ner_demo_turshilt4_pipeline_mn.md
new file mode 100644
index 00000000000000..9991a9c5850077
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-roberta_base_ner_demo_turshilt4_pipeline_mn.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Mongolian roberta_base_ner_demo_turshilt4_pipeline pipeline RoBertaForTokenClassification from sanchirjav
+author: John Snow Labs
+name: roberta_base_ner_demo_turshilt4_pipeline
+date: 2025-01-24
+tags: [mn, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: mn
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_ner_demo_turshilt4_pipeline` is a Mongolian model originally trained by sanchirjav.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_ner_demo_turshilt4_pipeline_mn_5.5.1_3.0_1737703773158.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_ner_demo_turshilt4_pipeline_mn_5.5.1_3.0_1737703773158.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_base_ner_demo_turshilt4_pipeline", lang = "mn")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_ner_demo_turshilt4_pipeline", lang = "mn")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_ner_demo_turshilt4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|mn|
+|Size:|465.7 MB|
+
+## References
+
+https://huggingface.co/sanchirjav/roberta-base-ner-demo-turshilt4
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-roberta_base_tweetner7_en.md b/docs/_posts/ahmedlone127/2025-01-24-roberta_base_tweetner7_en.md
new file mode 100644
index 00000000000000..fcd032d352b040
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-roberta_base_tweetner7_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_base_tweetner7 RoBertaForTokenClassification from CheccoCando
+author: John Snow Labs
+name: roberta_base_tweetner7
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_tweetner7` is a English model originally trained by CheccoCando.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_tweetner7_en_5.5.1_3.0_1737701937639.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_tweetner7_en_5.5.1_3.0_1737701937639.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("roberta_base_tweetner7","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_base_tweetner7", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_tweetner7|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|449.1 MB|
+
+## References
+
+https://huggingface.co/CheccoCando/roberta-base_TweetNER7
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-roberta_base_tweetner7_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-roberta_base_tweetner7_pipeline_en.md
new file mode 100644
index 00000000000000..160384ea177a25
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-roberta_base_tweetner7_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_base_tweetner7_pipeline pipeline RoBertaForTokenClassification from CheccoCando
+author: John Snow Labs
+name: roberta_base_tweetner7_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_tweetner7_pipeline` is a English model originally trained by CheccoCando.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_tweetner7_pipeline_en_5.5.1_3.0_1737701963716.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_tweetner7_pipeline_en_5.5.1_3.0_1737701963716.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_base_tweetner7_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_tweetner7_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_tweetner7_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|449.1 MB|
+
+## References
+
+https://huggingface.co/CheccoCando/roberta-base_TweetNER7
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-roberta_base_wikiann_en.md b/docs/_posts/ahmedlone127/2025-01-24-roberta_base_wikiann_en.md
new file mode 100644
index 00000000000000..b8f3db9f8f7ecc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-roberta_base_wikiann_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_base_wikiann RoBertaForTokenClassification from CheccoCando
+author: John Snow Labs
+name: roberta_base_wikiann
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_wikiann` is a English model originally trained by CheccoCando.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_wikiann_en_5.5.1_3.0_1737755659671.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_wikiann_en_5.5.1_3.0_1737755659671.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("roberta_base_wikiann","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_base_wikiann", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_wikiann|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|440.6 MB|
+
+## References
+
+https://huggingface.co/CheccoCando/roberta-base_WikiANN
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-roberta_base_wikiann_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-roberta_base_wikiann_pipeline_en.md
new file mode 100644
index 00000000000000..668998fa755a9b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-roberta_base_wikiann_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_base_wikiann_pipeline pipeline RoBertaForTokenClassification from CheccoCando
+author: John Snow Labs
+name: roberta_base_wikiann_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_wikiann_pipeline` is a English model originally trained by CheccoCando.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_wikiann_pipeline_en_5.5.1_3.0_1737755687033.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_wikiann_pipeline_en_5.5.1_3.0_1737755687033.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_base_wikiann_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_wikiann_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_wikiann_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|440.7 MB|
+
+## References
+
+https://huggingface.co/CheccoCando/roberta-base_WikiANN
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-roberta_base_wikineural_en.md b/docs/_posts/ahmedlone127/2025-01-24-roberta_base_wikineural_en.md
new file mode 100644
index 00000000000000..bde06d5c1ea046
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-roberta_base_wikineural_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_base_wikineural RoBertaForTokenClassification from CheccoCando
+author: John Snow Labs
+name: roberta_base_wikineural
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_wikineural` is a English model originally trained by CheccoCando.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_wikineural_en_5.5.1_3.0_1737755483374.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_wikineural_en_5.5.1_3.0_1737755483374.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("roberta_base_wikineural","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_base_wikineural", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_wikineural|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|449.5 MB|
+
+## References
+
+https://huggingface.co/CheccoCando/roberta-base_WikiNeural
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-roberta_base_wikineural_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-roberta_base_wikineural_pipeline_en.md
new file mode 100644
index 00000000000000..ca7839565d2e08
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-roberta_base_wikineural_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_base_wikineural_pipeline pipeline RoBertaForTokenClassification from CheccoCando
+author: John Snow Labs
+name: roberta_base_wikineural_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_wikineural_pipeline` is a English model originally trained by CheccoCando.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_wikineural_pipeline_en_5.5.1_3.0_1737755511029.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_wikineural_pipeline_en_5.5.1_3.0_1737755511029.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_base_wikineural_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_wikineural_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_wikineural_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|449.5 MB|
+
+## References
+
+https://huggingface.co/CheccoCando/roberta-base_WikiNeural
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-roberta_combined_generated_epoch_8_en.md b/docs/_posts/ahmedlone127/2025-01-24-roberta_combined_generated_epoch_8_en.md
new file mode 100644
index 00000000000000..1eabaa80267b7d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-roberta_combined_generated_epoch_8_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_combined_generated_epoch_8 RoBertaForTokenClassification from ICT2214Team7
+author: John Snow Labs
+name: roberta_combined_generated_epoch_8
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_combined_generated_epoch_8` is a English model originally trained by ICT2214Team7.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_combined_generated_epoch_8_en_5.5.1_3.0_1737755731678.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_combined_generated_epoch_8_en_5.5.1_3.0_1737755731678.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("roberta_combined_generated_epoch_8","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_combined_generated_epoch_8", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_combined_generated_epoch_8|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|306.6 MB|
+
+## References
+
+https://huggingface.co/ICT2214Team7/RoBERTa_Combined_Generated_epoch_8
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-roberta_combined_generated_epoch_8_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-roberta_combined_generated_epoch_8_pipeline_en.md
new file mode 100644
index 00000000000000..132a58f6b108f7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-roberta_combined_generated_epoch_8_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_combined_generated_epoch_8_pipeline pipeline RoBertaForTokenClassification from ICT2214Team7
+author: John Snow Labs
+name: roberta_combined_generated_epoch_8_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_combined_generated_epoch_8_pipeline` is a English model originally trained by ICT2214Team7.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_combined_generated_epoch_8_pipeline_en_5.5.1_3.0_1737755748015.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_combined_generated_epoch_8_pipeline_en_5.5.1_3.0_1737755748015.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_combined_generated_epoch_8_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_combined_generated_epoch_8_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_combined_generated_epoch_8_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|306.6 MB|
+
+## References
+
+https://huggingface.co/ICT2214Team7/RoBERTa_Combined_Generated_epoch_8
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-roberta_combined_generated_v1_1_epoch_4_en.md b/docs/_posts/ahmedlone127/2025-01-24-roberta_combined_generated_v1_1_epoch_4_en.md
new file mode 100644
index 00000000000000..36267a2eca77c4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-roberta_combined_generated_v1_1_epoch_4_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_combined_generated_v1_1_epoch_4 RoBertaForTokenClassification from ICT2214Team7
+author: John Snow Labs
+name: roberta_combined_generated_v1_1_epoch_4
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_combined_generated_v1_1_epoch_4` is a English model originally trained by ICT2214Team7.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_combined_generated_v1_1_epoch_4_en_5.5.1_3.0_1737703706296.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_combined_generated_v1_1_epoch_4_en_5.5.1_3.0_1737703706296.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("roberta_combined_generated_v1_1_epoch_4","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_combined_generated_v1_1_epoch_4", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_combined_generated_v1_1_epoch_4|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|306.6 MB|
+
+## References
+
+https://huggingface.co/ICT2214Team7/RoBERTa_Combined_Generated_v1.1_epoch_4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-roberta_combined_generated_v1_1_epoch_4_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-roberta_combined_generated_v1_1_epoch_4_pipeline_en.md
new file mode 100644
index 00000000000000..70b64b6c90617d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-roberta_combined_generated_v1_1_epoch_4_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_combined_generated_v1_1_epoch_4_pipeline pipeline RoBertaForTokenClassification from ICT2214Team7
+author: John Snow Labs
+name: roberta_combined_generated_v1_1_epoch_4_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_combined_generated_v1_1_epoch_4_pipeline` is a English model originally trained by ICT2214Team7.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_combined_generated_v1_1_epoch_4_pipeline_en_5.5.1_3.0_1737703722473.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_combined_generated_v1_1_epoch_4_pipeline_en_5.5.1_3.0_1737703722473.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_combined_generated_v1_1_epoch_4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_combined_generated_v1_1_epoch_4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_combined_generated_v1_1_epoch_4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|306.6 MB|
+
+## References
+
+https://huggingface.co/ICT2214Team7/RoBERTa_Combined_Generated_v1.1_epoch_4
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-roberta_combined_generated_v1_1_epoch_6_en.md b/docs/_posts/ahmedlone127/2025-01-24-roberta_combined_generated_v1_1_epoch_6_en.md
new file mode 100644
index 00000000000000..e0361b6f41d161
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-roberta_combined_generated_v1_1_epoch_6_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_combined_generated_v1_1_epoch_6 RoBertaForTokenClassification from ICT2214Team7
+author: John Snow Labs
+name: roberta_combined_generated_v1_1_epoch_6
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_combined_generated_v1_1_epoch_6` is a English model originally trained by ICT2214Team7.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_combined_generated_v1_1_epoch_6_en_5.5.1_3.0_1737702572844.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_combined_generated_v1_1_epoch_6_en_5.5.1_3.0_1737702572844.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("roberta_combined_generated_v1_1_epoch_6","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_combined_generated_v1_1_epoch_6", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_combined_generated_v1_1_epoch_6|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|306.6 MB|
+
+## References
+
+https://huggingface.co/ICT2214Team7/RoBERTa_Combined_Generated_v1.1_epoch_6
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-roberta_combined_generated_v1_1_epoch_6_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-roberta_combined_generated_v1_1_epoch_6_pipeline_en.md
new file mode 100644
index 00000000000000..89ea7b78e00def
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-roberta_combined_generated_v1_1_epoch_6_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_combined_generated_v1_1_epoch_6_pipeline pipeline RoBertaForTokenClassification from ICT2214Team7
+author: John Snow Labs
+name: roberta_combined_generated_v1_1_epoch_6_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_combined_generated_v1_1_epoch_6_pipeline` is a English model originally trained by ICT2214Team7.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_combined_generated_v1_1_epoch_6_pipeline_en_5.5.1_3.0_1737702592470.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_combined_generated_v1_1_epoch_6_pipeline_en_5.5.1_3.0_1737702592470.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_combined_generated_v1_1_epoch_6_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_combined_generated_v1_1_epoch_6_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_combined_generated_v1_1_epoch_6_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|306.6 MB|
+
+## References
+
+https://huggingface.co/ICT2214Team7/RoBERTa_Combined_Generated_v1.1_epoch_6
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-roberta_combined_squad_turkish_5epoch_pipeline_tr.md b/docs/_posts/ahmedlone127/2025-01-24-roberta_combined_squad_turkish_5epoch_pipeline_tr.md
new file mode 100644
index 00000000000000..f1999646e4756d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-roberta_combined_squad_turkish_5epoch_pipeline_tr.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Turkish roberta_combined_squad_turkish_5epoch_pipeline pipeline XlmRoBertaForQuestionAnswering from muratsimsek003
+author: John Snow Labs
+name: roberta_combined_squad_turkish_5epoch_pipeline
+date: 2025-01-24
+tags: [tr, open_source, pipeline, onnx]
+task: Question Answering
+language: tr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_combined_squad_turkish_5epoch_pipeline` is a Turkish model originally trained by muratsimsek003.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_combined_squad_turkish_5epoch_pipeline_tr_5.5.1_3.0_1737753016562.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_combined_squad_turkish_5epoch_pipeline_tr_5.5.1_3.0_1737753016562.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_combined_squad_turkish_5epoch_pipeline", lang = "tr")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_combined_squad_turkish_5epoch_pipeline", lang = "tr")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_combined_squad_turkish_5epoch_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|tr|
+|Size:|791.4 MB|
+
+## References
+
+https://huggingface.co/muratsimsek003/roberta-combined-squad-turkish-5epoch
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-roberta_combined_squad_turkish_5epoch_tr.md b/docs/_posts/ahmedlone127/2025-01-24-roberta_combined_squad_turkish_5epoch_tr.md
new file mode 100644
index 00000000000000..42f9e1ee4f9cbb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-roberta_combined_squad_turkish_5epoch_tr.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Turkish roberta_combined_squad_turkish_5epoch XlmRoBertaForQuestionAnswering from muratsimsek003
+author: John Snow Labs
+name: roberta_combined_squad_turkish_5epoch
+date: 2025-01-24
+tags: [tr, open_source, onnx, question_answering, xlm_roberta]
+task: Question Answering
+language: tr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_combined_squad_turkish_5epoch` is a Turkish model originally trained by muratsimsek003.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_combined_squad_turkish_5epoch_tr_5.5.1_3.0_1737752877412.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_combined_squad_turkish_5epoch_tr_5.5.1_3.0_1737752877412.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("roberta_combined_squad_turkish_5epoch","tr") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("roberta_combined_squad_turkish_5epoch", "tr")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_combined_squad_turkish_5epoch|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|tr|
+|Size:|791.4 MB|
+
+## References
+
+https://huggingface.co/muratsimsek003/roberta-combined-squad-turkish-5epoch
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-roberta_conll_learning_rate3e5_en.md b/docs/_posts/ahmedlone127/2025-01-24-roberta_conll_learning_rate3e5_en.md
new file mode 100644
index 00000000000000..0a31ba0364f50b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-roberta_conll_learning_rate3e5_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_conll_learning_rate3e5 RoBertaForTokenClassification from ICT2214Team7
+author: John Snow Labs
+name: roberta_conll_learning_rate3e5
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_conll_learning_rate3e5` is a English model originally trained by ICT2214Team7.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_conll_learning_rate3e5_en_5.5.1_3.0_1737755972389.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_conll_learning_rate3e5_en_5.5.1_3.0_1737755972389.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("roberta_conll_learning_rate3e5","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_conll_learning_rate3e5", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_conll_learning_rate3e5|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/ICT2214Team7/RoBERTa_conll_learning_rate3e5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-roberta_conll_learning_rate3e5_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-roberta_conll_learning_rate3e5_pipeline_en.md
new file mode 100644
index 00000000000000..508ff028d3e137
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-roberta_conll_learning_rate3e5_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_conll_learning_rate3e5_pipeline pipeline RoBertaForTokenClassification from ICT2214Team7
+author: John Snow Labs
+name: roberta_conll_learning_rate3e5_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_conll_learning_rate3e5_pipeline` is a English model originally trained by ICT2214Team7.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_conll_learning_rate3e5_pipeline_en_5.5.1_3.0_1737755988508.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_conll_learning_rate3e5_pipeline_en_5.5.1_3.0_1737755988508.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_conll_learning_rate3e5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_conll_learning_rate3e5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_conll_learning_rate3e5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|306.6 MB|
+
+## References
+
+https://huggingface.co/ICT2214Team7/RoBERTa_conll_learning_rate3e5
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-roberta_large_broad_tweet_corpus_en.md b/docs/_posts/ahmedlone127/2025-01-24-roberta_large_broad_tweet_corpus_en.md
new file mode 100644
index 00000000000000..6b5884def35ae2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-roberta_large_broad_tweet_corpus_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_large_broad_tweet_corpus RoBertaForTokenClassification from CheccoCando
+author: John Snow Labs
+name: roberta_large_broad_tweet_corpus
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_broad_tweet_corpus` is a English model originally trained by CheccoCando.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_broad_tweet_corpus_en_5.5.1_3.0_1737703243947.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_broad_tweet_corpus_en_5.5.1_3.0_1737703243947.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("roberta_large_broad_tweet_corpus","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_large_broad_tweet_corpus", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_large_broad_tweet_corpus|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/CheccoCando/roberta-large_Broad_Tweet_Corpus
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-roberta_large_broad_tweet_corpus_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-roberta_large_broad_tweet_corpus_pipeline_en.md
new file mode 100644
index 00000000000000..56a757402d3404
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-roberta_large_broad_tweet_corpus_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_large_broad_tweet_corpus_pipeline pipeline RoBertaForTokenClassification from CheccoCando
+author: John Snow Labs
+name: roberta_large_broad_tweet_corpus_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_broad_tweet_corpus_pipeline` is a English model originally trained by CheccoCando.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_broad_tweet_corpus_pipeline_en_5.5.1_3.0_1737703315441.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_broad_tweet_corpus_pipeline_en_5.5.1_3.0_1737703315441.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_large_broad_tweet_corpus_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_large_broad_tweet_corpus_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_large_broad_tweet_corpus_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/CheccoCando/roberta-large_Broad_Tweet_Corpus
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-roberta_large_harveyner_en.md b/docs/_posts/ahmedlone127/2025-01-24-roberta_large_harveyner_en.md
new file mode 100644
index 00000000000000..50eb4582f3c80b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-roberta_large_harveyner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_large_harveyner RoBertaForTokenClassification from CheccoCando
+author: John Snow Labs
+name: roberta_large_harveyner
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_harveyner` is a English model originally trained by CheccoCando.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_harveyner_en_5.5.1_3.0_1737756467413.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_harveyner_en_5.5.1_3.0_1737756467413.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("roberta_large_harveyner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_large_harveyner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_large_harveyner|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/CheccoCando/roberta-large_HarveyNER
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-roberta_large_harveyner_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-roberta_large_harveyner_pipeline_en.md
new file mode 100644
index 00000000000000..1390b29444fd03
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-roberta_large_harveyner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_large_harveyner_pipeline pipeline RoBertaForTokenClassification from CheccoCando
+author: John Snow Labs
+name: roberta_large_harveyner_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_harveyner_pipeline` is a English model originally trained by CheccoCando.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_harveyner_pipeline_en_5.5.1_3.0_1737756539762.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_harveyner_pipeline_en_5.5.1_3.0_1737756539762.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_large_harveyner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_large_harveyner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_large_harveyner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/CheccoCando/roberta-large_HarveyNER
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-roberta_large_multinerd_en.md b/docs/_posts/ahmedlone127/2025-01-24-roberta_large_multinerd_en.md
new file mode 100644
index 00000000000000..bb5a7ad1b37d1d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-roberta_large_multinerd_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_large_multinerd RoBertaForTokenClassification from CheccoCando
+author: John Snow Labs
+name: roberta_large_multinerd
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_multinerd` is a English model originally trained by CheccoCando.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_multinerd_en_5.5.1_3.0_1737702804366.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_multinerd_en_5.5.1_3.0_1737702804366.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("roberta_large_multinerd","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_large_multinerd", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_large_multinerd|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/CheccoCando/roberta-large_MultiNERD
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-roberta_large_multinerd_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-roberta_large_multinerd_pipeline_en.md
new file mode 100644
index 00000000000000..c3fb2ee5a462f0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-roberta_large_multinerd_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_large_multinerd_pipeline pipeline RoBertaForTokenClassification from CheccoCando
+author: John Snow Labs
+name: roberta_large_multinerd_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_multinerd_pipeline` is a English model originally trained by CheccoCando.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_multinerd_pipeline_en_5.5.1_3.0_1737702875976.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_multinerd_pipeline_en_5.5.1_3.0_1737702875976.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_large_multinerd_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_large_multinerd_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_large_multinerd_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/CheccoCando/roberta-large_MultiNERD
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-roberta_large_wikiann_en.md b/docs/_posts/ahmedlone127/2025-01-24-roberta_large_wikiann_en.md
new file mode 100644
index 00000000000000..038d7119531384
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-roberta_large_wikiann_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_large_wikiann RoBertaForTokenClassification from CheccoCando
+author: John Snow Labs
+name: roberta_large_wikiann
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_wikiann` is a English model originally trained by CheccoCando.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_wikiann_en_5.5.1_3.0_1737702421674.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_wikiann_en_5.5.1_3.0_1737702421674.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("roberta_large_wikiann","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_large_wikiann", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_large_wikiann|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/CheccoCando/roberta-large_WikiANN
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-roberta_large_wikiann_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-roberta_large_wikiann_pipeline_en.md
new file mode 100644
index 00000000000000..21536372771fa6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-roberta_large_wikiann_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_large_wikiann_pipeline pipeline RoBertaForTokenClassification from CheccoCando
+author: John Snow Labs
+name: roberta_large_wikiann_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_wikiann_pipeline` is a English model originally trained by CheccoCando.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_wikiann_pipeline_en_5.5.1_3.0_1737702496651.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_wikiann_pipeline_en_5.5.1_3.0_1737702496651.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_large_wikiann_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_large_wikiann_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_large_wikiann_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/CheccoCando/roberta-large_WikiANN
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-rubert_finetuned_squad_en.md b/docs/_posts/ahmedlone127/2025-01-24-rubert_finetuned_squad_en.md
new file mode 100644
index 00000000000000..3f919630a30e88
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-rubert_finetuned_squad_en.md
@@ -0,0 +1,88 @@
+---
+layout: model
+title: English rubert_finetuned_squad BertForQuestionAnswering from sad-bkt
+author: John Snow Labs
+name: rubert_finetuned_squad
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_finetuned_squad` is a English model originally trained by sad-bkt.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_finetuned_squad_en_5.5.1_3.0_1737757934180.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_finetuned_squad_en_5.5.1_3.0_1737757934180.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("rubert_finetuned_squad","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("rubert_finetuned_squad", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rubert_finetuned_squad|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|664.3 MB|
+
+## References
+
+References
+
+https://huggingface.co/sad-bkt/rubert-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-rubert_finetuned_squad_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-rubert_finetuned_squad_pipeline_en.md
new file mode 100644
index 00000000000000..c74a6a664f473d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-rubert_finetuned_squad_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English rubert_finetuned_squad_pipeline pipeline BertForQuestionAnswering from sad-bkt
+author: John Snow Labs
+name: rubert_finetuned_squad_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_finetuned_squad_pipeline` is a English model originally trained by sad-bkt.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_finetuned_squad_pipeline_en_5.5.1_3.0_1737757973518.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_finetuned_squad_pipeline_en_5.5.1_3.0_1737757973518.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("rubert_finetuned_squad_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("rubert_finetuned_squad_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rubert_finetuned_squad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|664.3 MB|
+
+## References
+
+References
+
+https://huggingface.co/sad-bkt/rubert-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-rubert_tiny2_odonata_ner_en.md b/docs/_posts/ahmedlone127/2025-01-24-rubert_tiny2_odonata_ner_en.md
new file mode 100644
index 00000000000000..9822afd177d2b3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-rubert_tiny2_odonata_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English rubert_tiny2_odonata_ner BertForTokenClassification from Ilya-Nazimov
+author: John Snow Labs
+name: rubert_tiny2_odonata_ner
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_tiny2_odonata_ner` is a English model originally trained by Ilya-Nazimov.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_tiny2_odonata_ner_en_5.5.1_3.0_1737719649517.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_tiny2_odonata_ner_en_5.5.1_3.0_1737719649517.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("rubert_tiny2_odonata_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("rubert_tiny2_odonata_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rubert_tiny2_odonata_ner|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|109.1 MB|
+
+## References
+
+https://huggingface.co/Ilya-Nazimov/rubert-tiny2-odonata-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-rubert_tiny2_odonata_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-rubert_tiny2_odonata_ner_pipeline_en.md
new file mode 100644
index 00000000000000..b16d89cd44727b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-rubert_tiny2_odonata_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English rubert_tiny2_odonata_ner_pipeline pipeline BertForTokenClassification from Ilya-Nazimov
+author: John Snow Labs
+name: rubert_tiny2_odonata_ner_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_tiny2_odonata_ner_pipeline` is a English model originally trained by Ilya-Nazimov.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_tiny2_odonata_ner_pipeline_en_5.5.1_3.0_1737719655088.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_tiny2_odonata_ner_pipeline_en_5.5.1_3.0_1737719655088.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("rubert_tiny2_odonata_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("rubert_tiny2_odonata_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rubert_tiny2_odonata_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|109.2 MB|
+
+## References
+
+https://huggingface.co/Ilya-Nazimov/rubert-tiny2-odonata-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-s10_en.md b/docs/_posts/ahmedlone127/2025-01-24-s10_en.md
new file mode 100644
index 00000000000000..b0c0582fd4e5b1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-s10_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English s10 BertForQuestionAnswering from ShynBui
+author: John Snow Labs
+name: s10
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`s10` is a English model originally trained by ShynBui.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/s10_en_5.5.1_3.0_1737748047006.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/s10_en_5.5.1_3.0_1737748047006.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("s10","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("s10", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|s10|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.5 MB|
+
+## References
+
+https://huggingface.co/ShynBui/s10
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-s10_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-s10_pipeline_en.md
new file mode 100644
index 00000000000000..4ed0443c153098
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-s10_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English s10_pipeline pipeline BertForQuestionAnswering from ShynBui
+author: John Snow Labs
+name: s10_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`s10_pipeline` is a English model originally trained by ShynBui.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/s10_pipeline_en_5.5.1_3.0_1737748082466.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/s10_pipeline_en_5.5.1_3.0_1737748082466.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("s10_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("s10_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|s10_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.5 MB|
+
+## References
+
+https://huggingface.co/ShynBui/s10
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-s11_en.md b/docs/_posts/ahmedlone127/2025-01-24-s11_en.md
new file mode 100644
index 00000000000000..77ebe96db34bac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-s11_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English s11 BertForQuestionAnswering from ShynBui
+author: John Snow Labs
+name: s11
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`s11` is a English model originally trained by ShynBui.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/s11_en_5.5.1_3.0_1737746917589.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/s11_en_5.5.1_3.0_1737746917589.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("s11","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("s11", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|s11|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.5 MB|
+
+## References
+
+https://huggingface.co/ShynBui/s11
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-s11_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-s11_pipeline_en.md
new file mode 100644
index 00000000000000..8307de807ed03f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-s11_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English s11_pipeline pipeline BertForQuestionAnswering from ShynBui
+author: John Snow Labs
+name: s11_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`s11_pipeline` is a English model originally trained by ShynBui.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/s11_pipeline_en_5.5.1_3.0_1737746941977.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/s11_pipeline_en_5.5.1_3.0_1737746941977.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("s11_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("s11_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|s11_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.5 MB|
+
+## References
+
+https://huggingface.co/ShynBui/s11
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-s17_en.md b/docs/_posts/ahmedlone127/2025-01-24-s17_en.md
new file mode 100644
index 00000000000000..4f40b7855450a4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-s17_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English s17 BertForQuestionAnswering from ShynBui
+author: John Snow Labs
+name: s17
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`s17` is a English model originally trained by ShynBui.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/s17_en_5.5.1_3.0_1737747813006.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/s17_en_5.5.1_3.0_1737747813006.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("s17","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("s17", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|s17|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.5 MB|
+
+## References
+
+https://huggingface.co/ShynBui/s17
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-s17_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-s17_pipeline_en.md
new file mode 100644
index 00000000000000..610814924813b1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-s17_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English s17_pipeline pipeline BertForQuestionAnswering from ShynBui
+author: John Snow Labs
+name: s17_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`s17_pipeline` is a English model originally trained by ShynBui.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/s17_pipeline_en_5.5.1_3.0_1737747836560.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/s17_pipeline_en_5.5.1_3.0_1737747836560.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("s17_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("s17_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|s17_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.5 MB|
+
+## References
+
+https://huggingface.co/ShynBui/s17
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-s21_en.md b/docs/_posts/ahmedlone127/2025-01-24-s21_en.md
new file mode 100644
index 00000000000000..7e7053d0830e8d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-s21_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English s21 BertForQuestionAnswering from ShynBui
+author: John Snow Labs
+name: s21
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`s21` is a English model originally trained by ShynBui.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/s21_en_5.5.1_3.0_1737738970491.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/s21_en_5.5.1_3.0_1737738970491.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("s21","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("s21", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|s21|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.3 MB|
+
+## References
+
+https://huggingface.co/ShynBui/s21
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-s21_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-s21_pipeline_en.md
new file mode 100644
index 00000000000000..c0cfa1ddc955f9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-s21_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English s21_pipeline pipeline BertForQuestionAnswering from ShynBui
+author: John Snow Labs
+name: s21_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`s21_pipeline` is a English model originally trained by ShynBui.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/s21_pipeline_en_5.5.1_3.0_1737738991943.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/s21_pipeline_en_5.5.1_3.0_1737738991943.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("s21_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("s21_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|s21_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.3 MB|
+
+## References
+
+https://huggingface.co/ShynBui/s21
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-s23_en.md b/docs/_posts/ahmedlone127/2025-01-24-s23_en.md
new file mode 100644
index 00000000000000..0fb9ed234facd1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-s23_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English s23 BertForQuestionAnswering from ShynBui
+author: John Snow Labs
+name: s23
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`s23` is a English model originally trained by ShynBui.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/s23_en_5.5.1_3.0_1737738719108.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/s23_en_5.5.1_3.0_1737738719108.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("s23","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("s23", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|s23|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.2 MB|
+
+## References
+
+https://huggingface.co/ShynBui/s23
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-s23_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-s23_pipeline_en.md
new file mode 100644
index 00000000000000..dd591dff5ddcf6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-s23_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English s23_pipeline pipeline BertForQuestionAnswering from ShynBui
+author: John Snow Labs
+name: s23_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`s23_pipeline` is a English model originally trained by ShynBui.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/s23_pipeline_en_5.5.1_3.0_1737738745997.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/s23_pipeline_en_5.5.1_3.0_1737738745997.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("s23_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("s23_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|s23_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.3 MB|
+
+## References
+
+https://huggingface.co/ShynBui/s23
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-s28_en.md b/docs/_posts/ahmedlone127/2025-01-24-s28_en.md
new file mode 100644
index 00000000000000..943c98305f9e5d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-s28_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English s28 BertForQuestionAnswering from ShynBui
+author: John Snow Labs
+name: s28
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`s28` is a English model originally trained by ShynBui.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/s28_en_5.5.1_3.0_1737739066475.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/s28_en_5.5.1_3.0_1737739066475.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("s28","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("s28", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|s28|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.5 MB|
+
+## References
+
+https://huggingface.co/ShynBui/s28
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-s28_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-s28_pipeline_en.md
new file mode 100644
index 00000000000000..eae08e36079df8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-s28_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English s28_pipeline pipeline BertForQuestionAnswering from ShynBui
+author: John Snow Labs
+name: s28_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`s28_pipeline` is a English model originally trained by ShynBui.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/s28_pipeline_en_5.5.1_3.0_1737739088650.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/s28_pipeline_en_5.5.1_3.0_1737739088650.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("s28_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("s28_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|s28_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.5 MB|
+
+## References
+
+https://huggingface.co/ShynBui/s28
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-s3_en.md b/docs/_posts/ahmedlone127/2025-01-24-s3_en.md
new file mode 100644
index 00000000000000..8d42043cd3af3b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-s3_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English s3 BertForQuestionAnswering from ShynBui
+author: John Snow Labs
+name: s3
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`s3` is a English model originally trained by ShynBui.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/s3_en_5.5.1_3.0_1737747339034.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/s3_en_5.5.1_3.0_1737747339034.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("s3","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("s3", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|s3|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/ShynBui/s3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-s3_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-s3_pipeline_en.md
new file mode 100644
index 00000000000000..65c625dcd04dd6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-s3_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English s3_pipeline pipeline BertForQuestionAnswering from ShynBui
+author: John Snow Labs
+name: s3_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`s3_pipeline` is a English model originally trained by ShynBui.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/s3_pipeline_en_5.5.1_3.0_1737747361449.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/s3_pipeline_en_5.5.1_3.0_1737747361449.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("s3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("s3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|s3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/ShynBui/s3
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-s9_en.md b/docs/_posts/ahmedlone127/2025-01-24-s9_en.md
new file mode 100644
index 00000000000000..b99f8454009f7c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-s9_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English s9 BertForQuestionAnswering from ShynBui
+author: John Snow Labs
+name: s9
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`s9` is a English model originally trained by ShynBui.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/s9_en_5.5.1_3.0_1737738276577.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/s9_en_5.5.1_3.0_1737738276577.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("s9","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("s9", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|s9|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/ShynBui/s9
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-s9_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-s9_pipeline_en.md
new file mode 100644
index 00000000000000..a9426a0a76f8fd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-s9_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English s9_pipeline pipeline BertForQuestionAnswering from ShynBui
+author: John Snow Labs
+name: s9_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`s9_pipeline` is a English model originally trained by ShynBui.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/s9_pipeline_en_5.5.1_3.0_1737738298786.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/s9_pipeline_en_5.5.1_3.0_1737738298786.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("s9_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("s9_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|s9_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/ShynBui/s9
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-saved_model_en.md b/docs/_posts/ahmedlone127/2025-01-24-saved_model_en.md
new file mode 100644
index 00000000000000..d53879706272c1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-saved_model_en.md
@@ -0,0 +1,96 @@
+---
+layout: model
+title: English saved_model DistilBertForSequenceClassification from hanyp
+author: John Snow Labs
+name: saved_model
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`saved_model` is a English model originally trained by hanyp.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/saved_model_en_5.5.1_3.0_1737753181448.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/saved_model_en_5.5.1_3.0_1737753181448.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("saved_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("saved_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|saved_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|797.1 MB|
+
+## References
+
+References
+
+https://huggingface.co/hanyp/saved_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-saved_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-saved_model_pipeline_en.md
new file mode 100644
index 00000000000000..d057bdbbd013fb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-saved_model_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English saved_model_pipeline pipeline DistilBertForSequenceClassification from hanyp
+author: John Snow Labs
+name: saved_model_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`saved_model_pipeline` is a English model originally trained by hanyp.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/saved_model_pipeline_en_5.5.1_3.0_1737753305969.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/saved_model_pipeline_en_5.5.1_3.0_1737753305969.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("saved_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("saved_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|saved_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|797.1 MB|
+
+## References
+
+References
+
+https://huggingface.co/hanyp/saved_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sdxl_detector_en.md b/docs/_posts/ahmedlone127/2025-01-24-sdxl_detector_en.md
new file mode 100644
index 00000000000000..0c5ff40ba24273
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sdxl_detector_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sdxl_detector SwinForImageClassification from Organika
+author: John Snow Labs
+name: sdxl_detector
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sdxl_detector` is a English model originally trained by Organika.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sdxl_detector_en_5.5.1_3.0_1737694169475.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sdxl_detector_en_5.5.1_3.0_1737694169475.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""sdxl_detector","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("sdxl_detector","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sdxl_detector|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|649.8 MB|
+
+## References
+
+https://huggingface.co/Organika/sdxl-detector
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sdxl_detector_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sdxl_detector_pipeline_en.md
new file mode 100644
index 00000000000000..e972030445a670
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sdxl_detector_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English sdxl_detector_pipeline pipeline SwinForImageClassification from Organika
+author: John Snow Labs
+name: sdxl_detector_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sdxl_detector_pipeline` is a English model originally trained by Organika.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sdxl_detector_pipeline_en_5.5.1_3.0_1737694203746.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sdxl_detector_pipeline_en_5.5.1_3.0_1737694203746.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sdxl_detector_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sdxl_detector_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sdxl_detector_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|649.8 MB|
+
+## References
+
+https://huggingface.co/Organika/sdxl-detector
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_063165e4_8904_42bd_9b41_c71649d3ef9d_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_063165e4_8904_42bd_9b41_c71649d3ef9d_en.md
new file mode 100644
index 00000000000000..9be3a9ce911d6d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_063165e4_8904_42bd_9b41_c71649d3ef9d_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_063165e4_8904_42bd_9b41_c71649d3ef9d BertSentenceEmbeddings from ismailpolas
+author: John Snow Labs
+name: sent_063165e4_8904_42bd_9b41_c71649d3ef9d
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_063165e4_8904_42bd_9b41_c71649d3ef9d` is a English model originally trained by ismailpolas.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_063165e4_8904_42bd_9b41_c71649d3ef9d_en_5.5.1_3.0_1737745810926.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_063165e4_8904_42bd_9b41_c71649d3ef9d_en_5.5.1_3.0_1737745810926.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_063165e4_8904_42bd_9b41_c71649d3ef9d","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_063165e4_8904_42bd_9b41_c71649d3ef9d","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_063165e4_8904_42bd_9b41_c71649d3ef9d|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/ismailpolas/063165e4-8904-42bd-9b41-c71649d3ef9d
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_063165e4_8904_42bd_9b41_c71649d3ef9d_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_063165e4_8904_42bd_9b41_c71649d3ef9d_pipeline_en.md
new file mode 100644
index 00000000000000..f0aa21e0ef7499
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_063165e4_8904_42bd_9b41_c71649d3ef9d_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_063165e4_8904_42bd_9b41_c71649d3ef9d_pipeline pipeline BertSentenceEmbeddings from ismailpolas
+author: John Snow Labs
+name: sent_063165e4_8904_42bd_9b41_c71649d3ef9d_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_063165e4_8904_42bd_9b41_c71649d3ef9d_pipeline` is a English model originally trained by ismailpolas.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_063165e4_8904_42bd_9b41_c71649d3ef9d_pipeline_en_5.5.1_3.0_1737745833293.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_063165e4_8904_42bd_9b41_c71649d3ef9d_pipeline_en_5.5.1_3.0_1737745833293.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_063165e4_8904_42bd_9b41_c71649d3ef9d_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_063165e4_8904_42bd_9b41_c71649d3ef9d_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_063165e4_8904_42bd_9b41_c71649d3ef9d_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.7 MB|
+
+## References
+
+https://huggingface.co/ismailpolas/063165e4-8904-42bd-9b41-c71649d3ef9d
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_adapter_model_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_adapter_model_en.md
new file mode 100644
index 00000000000000..d8aa4c463f1c25
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_adapter_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_adapter_model BertSentenceEmbeddings from asalmsk
+author: John Snow Labs
+name: sent_adapter_model
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_adapter_model` is a English model originally trained by asalmsk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_adapter_model_en_5.5.1_3.0_1737748605928.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_adapter_model_en_5.5.1_3.0_1737748605928.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_adapter_model","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_adapter_model","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_adapter_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|624.4 MB|
+
+## References
+
+https://huggingface.co/asalmsk/adapter_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_adapter_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_adapter_model_pipeline_en.md
new file mode 100644
index 00000000000000..1067d07beda969
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_adapter_model_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_adapter_model_pipeline pipeline BertSentenceEmbeddings from asalmsk
+author: John Snow Labs
+name: sent_adapter_model_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_adapter_model_pipeline` is a English model originally trained by asalmsk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_adapter_model_pipeline_en_5.5.1_3.0_1737748639550.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_adapter_model_pipeline_en_5.5.1_3.0_1737748639550.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_adapter_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_adapter_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_adapter_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|624.9 MB|
+
+## References
+
+https://huggingface.co/asalmsk/adapter_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_adopted_bert_base_cased_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_adopted_bert_base_cased_en.md
new file mode 100644
index 00000000000000..bb3375ac247af0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_adopted_bert_base_cased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_adopted_bert_base_cased BertSentenceEmbeddings from sivanravid
+author: John Snow Labs
+name: sent_adopted_bert_base_cased
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_adopted_bert_base_cased` is a English model originally trained by sivanravid.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_adopted_bert_base_cased_en_5.5.1_3.0_1737748799020.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_adopted_bert_base_cased_en_5.5.1_3.0_1737748799020.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_adopted_bert_base_cased","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_adopted_bert_base_cased","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_adopted_bert_base_cased|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/sivanravid/adopted-bert-base-cased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_adopted_bert_base_cased_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_adopted_bert_base_cased_pipeline_en.md
new file mode 100644
index 00000000000000..8888599be7b4c4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_adopted_bert_base_cased_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_adopted_bert_base_cased_pipeline pipeline BertSentenceEmbeddings from sivanravid
+author: John Snow Labs
+name: sent_adopted_bert_base_cased_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_adopted_bert_base_cased_pipeline` is a English model originally trained by sivanravid.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_adopted_bert_base_cased_pipeline_en_5.5.1_3.0_1737748821203.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_adopted_bert_base_cased_pipeline_en_5.5.1_3.0_1737748821203.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_adopted_bert_base_cased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_adopted_bert_base_cased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_adopted_bert_base_cased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|404.2 MB|
+
+## References
+
+https://huggingface.co/sivanravid/adopted-bert-base-cased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_alephbertgimmel_base_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_alephbertgimmel_base_en.md
new file mode 100644
index 00000000000000..100bced0402815
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_alephbertgimmel_base_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_alephbertgimmel_base BertSentenceEmbeddings from dicta-il
+author: John Snow Labs
+name: sent_alephbertgimmel_base
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_alephbertgimmel_base` is a English model originally trained by dicta-il.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_alephbertgimmel_base_en_5.5.1_3.0_1737745562859.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_alephbertgimmel_base_en_5.5.1_3.0_1737745562859.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_alephbertgimmel_base","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_alephbertgimmel_base","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_alephbertgimmel_base|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|690.4 MB|
+
+## References
+
+https://huggingface.co/dicta-il/alephbertgimmel-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_alephbertgimmel_base_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_alephbertgimmel_base_pipeline_en.md
new file mode 100644
index 00000000000000..79764073056df0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_alephbertgimmel_base_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_alephbertgimmel_base_pipeline pipeline BertSentenceEmbeddings from dicta-il
+author: John Snow Labs
+name: sent_alephbertgimmel_base_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_alephbertgimmel_base_pipeline` is a English model originally trained by dicta-il.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_alephbertgimmel_base_pipeline_en_5.5.1_3.0_1737745598682.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_alephbertgimmel_base_pipeline_en_5.5.1_3.0_1737745598682.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_alephbertgimmel_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_alephbertgimmel_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_alephbertgimmel_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|691.0 MB|
+
+## References
+
+https://huggingface.co/dicta-il/alephbertgimmel-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_all_minilm_l6_v2_personal_project_default_2024_05_17_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_all_minilm_l6_v2_personal_project_default_2024_05_17_en.md
new file mode 100644
index 00000000000000..174c162b67ccc5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_all_minilm_l6_v2_personal_project_default_2024_05_17_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_all_minilm_l6_v2_personal_project_default_2024_05_17 BertSentenceEmbeddings from brugmark
+author: John Snow Labs
+name: sent_all_minilm_l6_v2_personal_project_default_2024_05_17
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_all_minilm_l6_v2_personal_project_default_2024_05_17` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_default_2024_05_17_en_5.5.1_3.0_1737746015127.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_default_2024_05_17_en_5.5.1_3.0_1737746015127.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_all_minilm_l6_v2_personal_project_default_2024_05_17","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_all_minilm_l6_v2_personal_project_default_2024_05_17","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_all_minilm_l6_v2_personal_project_default_2024_05_17|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|83.9 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-default-2024-05-17
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_all_minilm_l6_v2_personal_project_default_2024_05_17_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_all_minilm_l6_v2_personal_project_default_2024_05_17_pipeline_en.md
new file mode 100644
index 00000000000000..e448541c199e20
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_all_minilm_l6_v2_personal_project_default_2024_05_17_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_all_minilm_l6_v2_personal_project_default_2024_05_17_pipeline pipeline BertSentenceEmbeddings from brugmark
+author: John Snow Labs
+name: sent_all_minilm_l6_v2_personal_project_default_2024_05_17_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_all_minilm_l6_v2_personal_project_default_2024_05_17_pipeline` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_default_2024_05_17_pipeline_en_5.5.1_3.0_1737746019926.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_default_2024_05_17_pipeline_en_5.5.1_3.0_1737746019926.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_all_minilm_l6_v2_personal_project_default_2024_05_17_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_all_minilm_l6_v2_personal_project_default_2024_05_17_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_all_minilm_l6_v2_personal_project_default_2024_05_17_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|84.5 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-default-2024-05-17
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_all_minilm_l6_v2_personal_project_default_2024_06_07_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_all_minilm_l6_v2_personal_project_default_2024_06_07_en.md
new file mode 100644
index 00000000000000..402ba57cfa38f6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_all_minilm_l6_v2_personal_project_default_2024_06_07_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_all_minilm_l6_v2_personal_project_default_2024_06_07 BertSentenceEmbeddings from brugmark
+author: John Snow Labs
+name: sent_all_minilm_l6_v2_personal_project_default_2024_06_07
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_all_minilm_l6_v2_personal_project_default_2024_06_07` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_default_2024_06_07_en_5.5.1_3.0_1737745211960.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_default_2024_06_07_en_5.5.1_3.0_1737745211960.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_all_minilm_l6_v2_personal_project_default_2024_06_07","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_all_minilm_l6_v2_personal_project_default_2024_06_07","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_all_minilm_l6_v2_personal_project_default_2024_06_07|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|83.9 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-default-2024-06-07
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_all_minilm_l6_v2_personal_project_default_2024_06_07_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_all_minilm_l6_v2_personal_project_default_2024_06_07_pipeline_en.md
new file mode 100644
index 00000000000000..31ba14c8b783d2
--- /dev/null
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@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_all_minilm_l6_v2_personal_project_default_2024_06_07_pipeline pipeline BertSentenceEmbeddings from brugmark
+author: John Snow Labs
+name: sent_all_minilm_l6_v2_personal_project_default_2024_06_07_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_all_minilm_l6_v2_personal_project_default_2024_06_07_pipeline` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_default_2024_06_07_pipeline_en_5.5.1_3.0_1737745217301.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_default_2024_06_07_pipeline_en_5.5.1_3.0_1737745217301.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_all_minilm_l6_v2_personal_project_default_2024_06_07_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_all_minilm_l6_v2_personal_project_default_2024_06_07_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_all_minilm_l6_v2_personal_project_default_2024_06_07_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|84.5 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-default-2024-06-07
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_all_minilm_l6_v2_personal_project_default_2024_06_14_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_all_minilm_l6_v2_personal_project_default_2024_06_14_en.md
new file mode 100644
index 00000000000000..0d800756a1b869
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_all_minilm_l6_v2_personal_project_default_2024_06_14_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_all_minilm_l6_v2_personal_project_default_2024_06_14 BertSentenceEmbeddings from brugmark
+author: John Snow Labs
+name: sent_all_minilm_l6_v2_personal_project_default_2024_06_14
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_all_minilm_l6_v2_personal_project_default_2024_06_14` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_default_2024_06_14_en_5.5.1_3.0_1737684550991.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_default_2024_06_14_en_5.5.1_3.0_1737684550991.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_all_minilm_l6_v2_personal_project_default_2024_06_14","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_all_minilm_l6_v2_personal_project_default_2024_06_14","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_all_minilm_l6_v2_personal_project_default_2024_06_14|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|83.9 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-default-2024-06-14
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_all_minilm_l6_v2_personal_project_default_2024_06_14_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_all_minilm_l6_v2_personal_project_default_2024_06_14_pipeline_en.md
new file mode 100644
index 00000000000000..a3a704b8885a18
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_all_minilm_l6_v2_personal_project_default_2024_06_14_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_all_minilm_l6_v2_personal_project_default_2024_06_14_pipeline pipeline BertSentenceEmbeddings from brugmark
+author: John Snow Labs
+name: sent_all_minilm_l6_v2_personal_project_default_2024_06_14_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_all_minilm_l6_v2_personal_project_default_2024_06_14_pipeline` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_default_2024_06_14_pipeline_en_5.5.1_3.0_1737684555392.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_default_2024_06_14_pipeline_en_5.5.1_3.0_1737684555392.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_all_minilm_l6_v2_personal_project_default_2024_06_14_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_all_minilm_l6_v2_personal_project_default_2024_06_14_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_all_minilm_l6_v2_personal_project_default_2024_06_14_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|84.5 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-default-2024-06-14
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_all_minilm_l6_v2_personal_project_finetuned_2024_05_31_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_all_minilm_l6_v2_personal_project_finetuned_2024_05_31_en.md
new file mode 100644
index 00000000000000..6c09a29e137570
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_all_minilm_l6_v2_personal_project_finetuned_2024_05_31_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_all_minilm_l6_v2_personal_project_finetuned_2024_05_31 BertSentenceEmbeddings from brugmark
+author: John Snow Labs
+name: sent_all_minilm_l6_v2_personal_project_finetuned_2024_05_31
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_all_minilm_l6_v2_personal_project_finetuned_2024_05_31` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_finetuned_2024_05_31_en_5.5.1_3.0_1737689672483.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_finetuned_2024_05_31_en_5.5.1_3.0_1737689672483.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_all_minilm_l6_v2_personal_project_finetuned_2024_05_31","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_all_minilm_l6_v2_personal_project_finetuned_2024_05_31","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_all_minilm_l6_v2_personal_project_finetuned_2024_05_31|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|81.7 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-finetuned-2024-05-31
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_all_minilm_l6_v2_personal_project_finetuned_2024_05_31_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_all_minilm_l6_v2_personal_project_finetuned_2024_05_31_pipeline_en.md
new file mode 100644
index 00000000000000..54d0efd21549ed
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_all_minilm_l6_v2_personal_project_finetuned_2024_05_31_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_all_minilm_l6_v2_personal_project_finetuned_2024_05_31_pipeline pipeline BertSentenceEmbeddings from brugmark
+author: John Snow Labs
+name: sent_all_minilm_l6_v2_personal_project_finetuned_2024_05_31_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_all_minilm_l6_v2_personal_project_finetuned_2024_05_31_pipeline` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_finetuned_2024_05_31_pipeline_en_5.5.1_3.0_1737689677293.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_finetuned_2024_05_31_pipeline_en_5.5.1_3.0_1737689677293.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_all_minilm_l6_v2_personal_project_finetuned_2024_05_31_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_all_minilm_l6_v2_personal_project_finetuned_2024_05_31_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_all_minilm_l6_v2_personal_project_finetuned_2024_05_31_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|82.2 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-finetuned-2024-05-31
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_17_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_17_en.md
new file mode 100644
index 00000000000000..4afe375beb5809
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_17_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_17 BertSentenceEmbeddings from brugmark
+author: John Snow Labs
+name: sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_17
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_17` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_17_en_5.5.1_3.0_1737683990128.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_17_en_5.5.1_3.0_1737683990128.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_17","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_17","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_17|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|84.7 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-finetuned-2024-06-17
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_17_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_17_pipeline_en.md
new file mode 100644
index 00000000000000..03e90a73458c72
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_17_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_17_pipeline pipeline BertSentenceEmbeddings from brugmark
+author: John Snow Labs
+name: sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_17_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_17_pipeline` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_17_pipeline_en_5.5.1_3.0_1737683994429.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_17_pipeline_en_5.5.1_3.0_1737683994429.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_17_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_17_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_17_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|85.2 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-finetuned-2024-06-17
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_assamese_bert_as.md b/docs/_posts/ahmedlone127/2025-01-24-sent_assamese_bert_as.md
new file mode 100644
index 00000000000000..f6f3b18cab4d93
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_assamese_bert_as.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Assamese sent_assamese_bert BertSentenceEmbeddings from l3cube-pune
+author: John Snow Labs
+name: sent_assamese_bert
+date: 2025-01-24
+tags: [as, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: as
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_assamese_bert` is a Assamese model originally trained by l3cube-pune.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_assamese_bert_as_5.5.1_3.0_1737684001049.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_assamese_bert_as_5.5.1_3.0_1737684001049.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_assamese_bert","as") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_assamese_bert","as") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_assamese_bert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|as|
+|Size:|890.4 MB|
+
+## References
+
+https://huggingface.co/l3cube-pune/assamese-bert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_assamese_bert_pipeline_as.md b/docs/_posts/ahmedlone127/2025-01-24-sent_assamese_bert_pipeline_as.md
new file mode 100644
index 00000000000000..810b631c94e248
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_assamese_bert_pipeline_as.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Assamese sent_assamese_bert_pipeline pipeline BertSentenceEmbeddings from l3cube-pune
+author: John Snow Labs
+name: sent_assamese_bert_pipeline
+date: 2025-01-24
+tags: [as, open_source, pipeline, onnx]
+task: Embeddings
+language: as
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_assamese_bert_pipeline` is a Assamese model originally trained by l3cube-pune.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_assamese_bert_pipeline_as_5.5.1_3.0_1737684047927.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_assamese_bert_pipeline_as_5.5.1_3.0_1737684047927.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_assamese_bert_pipeline", lang = "as")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_assamese_bert_pipeline", lang = "as")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_assamese_bert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|as|
+|Size:|891.0 MB|
+
+## References
+
+https://huggingface.co/l3cube-pune/assamese-bert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_base_mlm_imdb_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_base_mlm_imdb_en.md
new file mode 100644
index 00000000000000..25660e4774f354
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_base_mlm_imdb_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_base_mlm_imdb BertSentenceEmbeddings from muhtasham
+author: John Snow Labs
+name: sent_base_mlm_imdb
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_base_mlm_imdb` is a English model originally trained by muhtasham.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_base_mlm_imdb_en_5.5.1_3.0_1737746345421.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_base_mlm_imdb_en_5.5.1_3.0_1737746345421.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_base_mlm_imdb","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_base_mlm_imdb","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_base_mlm_imdb|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.6 MB|
+
+## References
+
+https://huggingface.co/muhtasham/base-mlm-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_base_mlm_imdb_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_base_mlm_imdb_pipeline_en.md
new file mode 100644
index 00000000000000..16616397a3192c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_base_mlm_imdb_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_base_mlm_imdb_pipeline pipeline BertSentenceEmbeddings from muhtasham
+author: John Snow Labs
+name: sent_base_mlm_imdb_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_base_mlm_imdb_pipeline` is a English model originally trained by muhtasham.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_base_mlm_imdb_pipeline_en_5.5.1_3.0_1737746367127.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_base_mlm_imdb_pipeline_en_5.5.1_3.0_1737746367127.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_base_mlm_imdb_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_base_mlm_imdb_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_base_mlm_imdb_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|408.1 MB|
+
+## References
+
+https://huggingface.co/muhtasham/base-mlm-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bengali_bert_bn.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bengali_bert_bn.md
new file mode 100644
index 00000000000000..83e0120c526bfe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bengali_bert_bn.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Bengali sent_bengali_bert BertSentenceEmbeddings from l3cube-pune
+author: John Snow Labs
+name: sent_bengali_bert
+date: 2025-01-24
+tags: [bn, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: bn
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bengali_bert` is a Bengali model originally trained by l3cube-pune.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bengali_bert_bn_5.5.1_3.0_1737745660285.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bengali_bert_bn_5.5.1_3.0_1737745660285.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bengali_bert","bn") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bengali_bert","bn") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bengali_bert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|bn|
+|Size:|890.6 MB|
+
+## References
+
+https://huggingface.co/l3cube-pune/bengali-bert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bengali_bert_pipeline_bn.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bengali_bert_pipeline_bn.md
new file mode 100644
index 00000000000000..c65a33b6a07514
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bengali_bert_pipeline_bn.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Bengali sent_bengali_bert_pipeline pipeline BertSentenceEmbeddings from l3cube-pune
+author: John Snow Labs
+name: sent_bengali_bert_pipeline
+date: 2025-01-24
+tags: [bn, open_source, pipeline, onnx]
+task: Embeddings
+language: bn
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bengali_bert_pipeline` is a Bengali model originally trained by l3cube-pune.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bengali_bert_pipeline_bn_5.5.1_3.0_1737745707869.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bengali_bert_pipeline_bn_5.5.1_3.0_1737745707869.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bengali_bert_pipeline", lang = "bn")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bengali_bert_pipeline", lang = "bn")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bengali_bert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|bn|
+|Size:|891.1 MB|
+
+## References
+
+https://huggingface.co/l3cube-pune/bengali-bert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_1ds_domain_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_1ds_domain_en.md
new file mode 100644
index 00000000000000..29f5a738131ff2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_1ds_domain_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_1ds_domain BertSentenceEmbeddings from Vishal24
+author: John Snow Labs
+name: sent_bert_1ds_domain
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_1ds_domain` is a English model originally trained by Vishal24.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_1ds_domain_en_5.5.1_3.0_1737748771356.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_1ds_domain_en_5.5.1_3.0_1737748771356.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_1ds_domain","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_1ds_domain","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_1ds_domain|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/Vishal24/bert-1ds-domain
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_1ds_domain_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_1ds_domain_pipeline_en.md
new file mode 100644
index 00000000000000..55371e0bd22235
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_1ds_domain_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_1ds_domain_pipeline pipeline BertSentenceEmbeddings from Vishal24
+author: John Snow Labs
+name: sent_bert_1ds_domain_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_1ds_domain_pipeline` is a English model originally trained by Vishal24.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_1ds_domain_pipeline_en_5.5.1_3.0_1737748793182.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_1ds_domain_pipeline_en_5.5.1_3.0_1737748793182.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_1ds_domain_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_1ds_domain_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_1ds_domain_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|404.3 MB|
+
+## References
+
+https://huggingface.co/Vishal24/bert-1ds-domain
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_martin_fierro_didicito_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_martin_fierro_didicito_en.md
new file mode 100644
index 00000000000000..6acbef1f4a519f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_martin_fierro_didicito_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_adaptation_martin_fierro_didicito BertSentenceEmbeddings from didicito
+author: John Snow Labs
+name: sent_bert_adaptation_martin_fierro_didicito
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_adaptation_martin_fierro_didicito` is a English model originally trained by didicito.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_martin_fierro_didicito_en_5.5.1_3.0_1737689350113.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_martin_fierro_didicito_en_5.5.1_3.0_1737689350113.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_adaptation_martin_fierro_didicito","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_adaptation_martin_fierro_didicito","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_adaptation_martin_fierro_didicito|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/didicito/bert_adaptation_martin_fierro
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_martin_fierro_didicito_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_martin_fierro_didicito_pipeline_en.md
new file mode 100644
index 00000000000000..e36c4c27b6a1b7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_martin_fierro_didicito_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_adaptation_martin_fierro_didicito_pipeline pipeline BertSentenceEmbeddings from didicito
+author: John Snow Labs
+name: sent_bert_adaptation_martin_fierro_didicito_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_adaptation_martin_fierro_didicito_pipeline` is a English model originally trained by didicito.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_martin_fierro_didicito_pipeline_en_5.5.1_3.0_1737689372083.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_martin_fierro_didicito_pipeline_en_5.5.1_3.0_1737689372083.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_adaptation_martin_fierro_didicito_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_adaptation_martin_fierro_didicito_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_adaptation_martin_fierro_didicito_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.2 MB|
+
+## References
+
+https://huggingface.co/didicito/bert_adaptation_martin_fierro
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_martin_fierro_javier_rooster_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_martin_fierro_javier_rooster_en.md
new file mode 100644
index 00000000000000..cc15e6e497eeef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_martin_fierro_javier_rooster_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_adaptation_martin_fierro_javier_rooster BertSentenceEmbeddings from javier-rooster
+author: John Snow Labs
+name: sent_bert_adaptation_martin_fierro_javier_rooster
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_adaptation_martin_fierro_javier_rooster` is a English model originally trained by javier-rooster.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_martin_fierro_javier_rooster_en_5.5.1_3.0_1737688420762.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_martin_fierro_javier_rooster_en_5.5.1_3.0_1737688420762.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_adaptation_martin_fierro_javier_rooster","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_adaptation_martin_fierro_javier_rooster","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_adaptation_martin_fierro_javier_rooster|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/javier-rooster/bert_adaptation_martin_fierro
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_martin_fierro_javier_rooster_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_martin_fierro_javier_rooster_pipeline_en.md
new file mode 100644
index 00000000000000..fd5ec3738c3596
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_martin_fierro_javier_rooster_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_adaptation_martin_fierro_javier_rooster_pipeline pipeline BertSentenceEmbeddings from javier-rooster
+author: John Snow Labs
+name: sent_bert_adaptation_martin_fierro_javier_rooster_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_adaptation_martin_fierro_javier_rooster_pipeline` is a English model originally trained by javier-rooster.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_martin_fierro_javier_rooster_pipeline_en_5.5.1_3.0_1737688445162.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_martin_fierro_javier_rooster_pipeline_en_5.5.1_3.0_1737688445162.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_adaptation_martin_fierro_javier_rooster_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_adaptation_martin_fierro_javier_rooster_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_adaptation_martin_fierro_javier_rooster_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.2 MB|
+
+## References
+
+https://huggingface.co/javier-rooster/bert_adaptation_martin_fierro
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_martin_fierro_martinnnuez_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_martin_fierro_martinnnuez_en.md
new file mode 100644
index 00000000000000..f0b4751dd5ba8e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_martin_fierro_martinnnuez_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_adaptation_martin_fierro_martinnnuez BertSentenceEmbeddings from martinnnuez
+author: John Snow Labs
+name: sent_bert_adaptation_martin_fierro_martinnnuez
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_adaptation_martin_fierro_martinnnuez` is a English model originally trained by martinnnuez.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_martin_fierro_martinnnuez_en_5.5.1_3.0_1737688531441.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_martin_fierro_martinnnuez_en_5.5.1_3.0_1737688531441.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_adaptation_martin_fierro_martinnnuez","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_adaptation_martin_fierro_martinnnuez","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_adaptation_martin_fierro_martinnnuez|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/martinnnuez/bert_adaptation_martin_fierro
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_martin_fierro_martinnnuez_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_martin_fierro_martinnnuez_pipeline_en.md
new file mode 100644
index 00000000000000..44ec00ce38dea0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_martin_fierro_martinnnuez_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_adaptation_martin_fierro_martinnnuez_pipeline pipeline BertSentenceEmbeddings from martinnnuez
+author: John Snow Labs
+name: sent_bert_adaptation_martin_fierro_martinnnuez_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_adaptation_martin_fierro_martinnnuez_pipeline` is a English model originally trained by martinnnuez.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_martin_fierro_martinnnuez_pipeline_en_5.5.1_3.0_1737688553383.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_martin_fierro_martinnnuez_pipeline_en_5.5.1_3.0_1737688553383.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_adaptation_martin_fierro_martinnnuez_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_adaptation_martin_fierro_martinnnuez_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_adaptation_martin_fierro_martinnnuez_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.2 MB|
+
+## References
+
+https://huggingface.co/martinnnuez/bert_adaptation_martin_fierro
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_martin_fierro_martinrobins_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_martin_fierro_martinrobins_en.md
new file mode 100644
index 00000000000000..3e8e649770ef1b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_martin_fierro_martinrobins_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_adaptation_martin_fierro_martinrobins BertSentenceEmbeddings from MartinRobins
+author: John Snow Labs
+name: sent_bert_adaptation_martin_fierro_martinrobins
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_adaptation_martin_fierro_martinrobins` is a English model originally trained by MartinRobins.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_martin_fierro_martinrobins_en_5.5.1_3.0_1737745713141.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_martin_fierro_martinrobins_en_5.5.1_3.0_1737745713141.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_adaptation_martin_fierro_martinrobins","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_adaptation_martin_fierro_martinrobins","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_adaptation_martin_fierro_martinrobins|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/MartinRobins/bert_adaptation_martin_fierro
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_martin_fierro_martinrobins_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_martin_fierro_martinrobins_pipeline_en.md
new file mode 100644
index 00000000000000..226a102c9813f1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_martin_fierro_martinrobins_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_adaptation_martin_fierro_martinrobins_pipeline pipeline BertSentenceEmbeddings from MartinRobins
+author: John Snow Labs
+name: sent_bert_adaptation_martin_fierro_martinrobins_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_adaptation_martin_fierro_martinrobins_pipeline` is a English model originally trained by MartinRobins.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_martin_fierro_martinrobins_pipeline_en_5.5.1_3.0_1737745737557.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_martin_fierro_martinrobins_pipeline_en_5.5.1_3.0_1737745737557.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_adaptation_martin_fierro_martinrobins_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_adaptation_martin_fierro_martinrobins_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_adaptation_martin_fierro_martinrobins_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.2 MB|
+
+## References
+
+https://huggingface.co/MartinRobins/bert_adaptation_martin_fierro
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_peppa_pig_cniclis_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_peppa_pig_cniclis_en.md
new file mode 100644
index 00000000000000..16ed84e0ec64ee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_peppa_pig_cniclis_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_adaptation_peppa_pig_cniclis BertSentenceEmbeddings from cniclis
+author: John Snow Labs
+name: sent_bert_adaptation_peppa_pig_cniclis
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_adaptation_peppa_pig_cniclis` is a English model originally trained by cniclis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_peppa_pig_cniclis_en_5.5.1_3.0_1737748599502.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_peppa_pig_cniclis_en_5.5.1_3.0_1737748599502.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_adaptation_peppa_pig_cniclis","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_adaptation_peppa_pig_cniclis","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_adaptation_peppa_pig_cniclis|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/cniclis/bert_adaptation_peppa_pig
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_peppa_pig_cniclis_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_peppa_pig_cniclis_pipeline_en.md
new file mode 100644
index 00000000000000..0628ae303b40ca
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_peppa_pig_cniclis_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_adaptation_peppa_pig_cniclis_pipeline pipeline BertSentenceEmbeddings from cniclis
+author: John Snow Labs
+name: sent_bert_adaptation_peppa_pig_cniclis_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_adaptation_peppa_pig_cniclis_pipeline` is a English model originally trained by cniclis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_peppa_pig_cniclis_pipeline_en_5.5.1_3.0_1737748621463.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_peppa_pig_cniclis_pipeline_en_5.5.1_3.0_1737748621463.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_adaptation_peppa_pig_cniclis_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_adaptation_peppa_pig_cniclis_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_adaptation_peppa_pig_cniclis_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.2 MB|
+
+## References
+
+https://huggingface.co/cniclis/bert_adaptation_peppa_pig
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_peppa_pig_eugeniahaluszka_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_peppa_pig_eugeniahaluszka_en.md
new file mode 100644
index 00000000000000..e4077c7f58d098
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_peppa_pig_eugeniahaluszka_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_adaptation_peppa_pig_eugeniahaluszka BertSentenceEmbeddings from eugeniahaluszka
+author: John Snow Labs
+name: sent_bert_adaptation_peppa_pig_eugeniahaluszka
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_adaptation_peppa_pig_eugeniahaluszka` is a English model originally trained by eugeniahaluszka.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_peppa_pig_eugeniahaluszka_en_5.5.1_3.0_1737688361179.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_peppa_pig_eugeniahaluszka_en_5.5.1_3.0_1737688361179.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_adaptation_peppa_pig_eugeniahaluszka","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_adaptation_peppa_pig_eugeniahaluszka","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_adaptation_peppa_pig_eugeniahaluszka|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/eugeniahaluszka/bert_adaptation_peppa_pig
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_peppa_pig_eugeniahaluszka_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_peppa_pig_eugeniahaluszka_pipeline_en.md
new file mode 100644
index 00000000000000..950e41bdd11e70
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_peppa_pig_eugeniahaluszka_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_adaptation_peppa_pig_eugeniahaluszka_pipeline pipeline BertSentenceEmbeddings from eugeniahaluszka
+author: John Snow Labs
+name: sent_bert_adaptation_peppa_pig_eugeniahaluszka_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_adaptation_peppa_pig_eugeniahaluszka_pipeline` is a English model originally trained by eugeniahaluszka.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_peppa_pig_eugeniahaluszka_pipeline_en_5.5.1_3.0_1737688388251.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_peppa_pig_eugeniahaluszka_pipeline_en_5.5.1_3.0_1737688388251.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_adaptation_peppa_pig_eugeniahaluszka_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_adaptation_peppa_pig_eugeniahaluszka_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_adaptation_peppa_pig_eugeniahaluszka_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.2 MB|
+
+## References
+
+https://huggingface.co/eugeniahaluszka/bert_adaptation_peppa_pig
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_peppa_pig_mauroandres_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_peppa_pig_mauroandres_en.md
new file mode 100644
index 00000000000000..31db0388f1987d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_peppa_pig_mauroandres_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_adaptation_peppa_pig_mauroandres BertSentenceEmbeddings from mauroandres
+author: John Snow Labs
+name: sent_bert_adaptation_peppa_pig_mauroandres
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_adaptation_peppa_pig_mauroandres` is a English model originally trained by mauroandres.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_peppa_pig_mauroandres_en_5.5.1_3.0_1737748874864.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_peppa_pig_mauroandres_en_5.5.1_3.0_1737748874864.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_adaptation_peppa_pig_mauroandres","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_adaptation_peppa_pig_mauroandres","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_adaptation_peppa_pig_mauroandres|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/mauroandres/bert_adaptation_peppa_pig
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_peppa_pig_mauroandres_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_peppa_pig_mauroandres_pipeline_en.md
new file mode 100644
index 00000000000000..ccb00f1e639770
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_peppa_pig_mauroandres_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_adaptation_peppa_pig_mauroandres_pipeline pipeline BertSentenceEmbeddings from mauroandres
+author: John Snow Labs
+name: sent_bert_adaptation_peppa_pig_mauroandres_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_adaptation_peppa_pig_mauroandres_pipeline` is a English model originally trained by mauroandres.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_peppa_pig_mauroandres_pipeline_en_5.5.1_3.0_1737748897257.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_peppa_pig_mauroandres_pipeline_en_5.5.1_3.0_1737748897257.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_adaptation_peppa_pig_mauroandres_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_adaptation_peppa_pig_mauroandres_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_adaptation_peppa_pig_mauroandres_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.2 MB|
+
+## References
+
+https://huggingface.co/mauroandres/bert_adaptation_peppa_pig
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_peppa_pig_maximilianoeze_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_peppa_pig_maximilianoeze_en.md
new file mode 100644
index 00000000000000..b6c74fa6786f56
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_peppa_pig_maximilianoeze_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_adaptation_peppa_pig_maximilianoeze BertSentenceEmbeddings from Maximilianoeze
+author: John Snow Labs
+name: sent_bert_adaptation_peppa_pig_maximilianoeze
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_adaptation_peppa_pig_maximilianoeze` is a English model originally trained by Maximilianoeze.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_peppa_pig_maximilianoeze_en_5.5.1_3.0_1737689055332.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_peppa_pig_maximilianoeze_en_5.5.1_3.0_1737689055332.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_adaptation_peppa_pig_maximilianoeze","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_adaptation_peppa_pig_maximilianoeze","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_adaptation_peppa_pig_maximilianoeze|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/Maximilianoeze/bert_adaptation_peppa_pig
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_peppa_pig_maximilianoeze_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_peppa_pig_maximilianoeze_pipeline_en.md
new file mode 100644
index 00000000000000..238808ea50ddeb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_peppa_pig_maximilianoeze_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_adaptation_peppa_pig_maximilianoeze_pipeline pipeline BertSentenceEmbeddings from Maximilianoeze
+author: John Snow Labs
+name: sent_bert_adaptation_peppa_pig_maximilianoeze_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_adaptation_peppa_pig_maximilianoeze_pipeline` is a English model originally trained by Maximilianoeze.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_peppa_pig_maximilianoeze_pipeline_en_5.5.1_3.0_1737689077130.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_peppa_pig_maximilianoeze_pipeline_en_5.5.1_3.0_1737689077130.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_adaptation_peppa_pig_maximilianoeze_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_adaptation_peppa_pig_maximilianoeze_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_adaptation_peppa_pig_maximilianoeze_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.2 MB|
+
+## References
+
+https://huggingface.co/Maximilianoeze/bert_adaptation_peppa_pig
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_preguntas_german_norwegian_videntes_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_preguntas_german_norwegian_videntes_en.md
new file mode 100644
index 00000000000000..309e6a75a6de3a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_preguntas_german_norwegian_videntes_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_adaptation_preguntas_german_norwegian_videntes BertSentenceEmbeddings from FAyrolo
+author: John Snow Labs
+name: sent_bert_adaptation_preguntas_german_norwegian_videntes
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_adaptation_preguntas_german_norwegian_videntes` is a English model originally trained by FAyrolo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_preguntas_german_norwegian_videntes_en_5.5.1_3.0_1737689097534.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_preguntas_german_norwegian_videntes_en_5.5.1_3.0_1737689097534.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_adaptation_preguntas_german_norwegian_videntes","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_adaptation_preguntas_german_norwegian_videntes","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_adaptation_preguntas_german_norwegian_videntes|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/FAyrolo/bert_adaptation_preguntas_de_no_videntes
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_preguntas_german_norwegian_videntes_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_preguntas_german_norwegian_videntes_pipeline_en.md
new file mode 100644
index 00000000000000..6834d04f2028bd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_preguntas_german_norwegian_videntes_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_adaptation_preguntas_german_norwegian_videntes_pipeline pipeline BertSentenceEmbeddings from FAyrolo
+author: John Snow Labs
+name: sent_bert_adaptation_preguntas_german_norwegian_videntes_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_adaptation_preguntas_german_norwegian_videntes_pipeline` is a English model originally trained by FAyrolo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_preguntas_german_norwegian_videntes_pipeline_en_5.5.1_3.0_1737689119378.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_preguntas_german_norwegian_videntes_pipeline_en_5.5.1_3.0_1737689119378.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_adaptation_preguntas_german_norwegian_videntes_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_adaptation_preguntas_german_norwegian_videntes_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_adaptation_preguntas_german_norwegian_videntes_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.7 MB|
+
+## References
+
+https://huggingface.co/FAyrolo/bert_adaptation_preguntas_de_no_videntes
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_referencias_german_vinos_andrew_xzr_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_referencias_german_vinos_andrew_xzr_en.md
new file mode 100644
index 00000000000000..168509a56f0075
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_referencias_german_vinos_andrew_xzr_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_adaptation_referencias_german_vinos_andrew_xzr BertSentenceEmbeddings from Andrew-XZR
+author: John Snow Labs
+name: sent_bert_adaptation_referencias_german_vinos_andrew_xzr
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_adaptation_referencias_german_vinos_andrew_xzr` is a English model originally trained by Andrew-XZR.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_referencias_german_vinos_andrew_xzr_en_5.5.1_3.0_1737688361048.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_referencias_german_vinos_andrew_xzr_en_5.5.1_3.0_1737688361048.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_adaptation_referencias_german_vinos_andrew_xzr","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_adaptation_referencias_german_vinos_andrew_xzr","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_adaptation_referencias_german_vinos_andrew_xzr|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/Andrew-XZR/bert_adaptation_referencias_de_vinos
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_referencias_german_vinos_andrew_xzr_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_referencias_german_vinos_andrew_xzr_pipeline_en.md
new file mode 100644
index 00000000000000..7b41e3e8c57857
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_referencias_german_vinos_andrew_xzr_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_adaptation_referencias_german_vinos_andrew_xzr_pipeline pipeline BertSentenceEmbeddings from Andrew-XZR
+author: John Snow Labs
+name: sent_bert_adaptation_referencias_german_vinos_andrew_xzr_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_adaptation_referencias_german_vinos_andrew_xzr_pipeline` is a English model originally trained by Andrew-XZR.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_referencias_german_vinos_andrew_xzr_pipeline_en_5.5.1_3.0_1737688387967.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_referencias_german_vinos_andrew_xzr_pipeline_en_5.5.1_3.0_1737688387967.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_adaptation_referencias_german_vinos_andrew_xzr_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_adaptation_referencias_german_vinos_andrew_xzr_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_adaptation_referencias_german_vinos_andrew_xzr_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.2 MB|
+
+## References
+
+https://huggingface.co/Andrew-XZR/bert_adaptation_referencias_de_vinos
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_referencias_german_vinos_ferni_riverplate_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_referencias_german_vinos_ferni_riverplate_en.md
new file mode 100644
index 00000000000000..8ce203ea1c09fa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_referencias_german_vinos_ferni_riverplate_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_adaptation_referencias_german_vinos_ferni_riverplate BertSentenceEmbeddings from ferni-riverplate
+author: John Snow Labs
+name: sent_bert_adaptation_referencias_german_vinos_ferni_riverplate
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_adaptation_referencias_german_vinos_ferni_riverplate` is a English model originally trained by ferni-riverplate.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_referencias_german_vinos_ferni_riverplate_en_5.5.1_3.0_1737689043347.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_referencias_german_vinos_ferni_riverplate_en_5.5.1_3.0_1737689043347.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_adaptation_referencias_german_vinos_ferni_riverplate","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_adaptation_referencias_german_vinos_ferni_riverplate","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_adaptation_referencias_german_vinos_ferni_riverplate|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/ferni-riverplate/bert_adaptation_referencias_de_vinos
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_referencias_german_vinos_ferni_riverplate_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_referencias_german_vinos_ferni_riverplate_pipeline_en.md
new file mode 100644
index 00000000000000..95fedd501e27be
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_referencias_german_vinos_ferni_riverplate_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_adaptation_referencias_german_vinos_ferni_riverplate_pipeline pipeline BertSentenceEmbeddings from ferni-riverplate
+author: John Snow Labs
+name: sent_bert_adaptation_referencias_german_vinos_ferni_riverplate_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_adaptation_referencias_german_vinos_ferni_riverplate_pipeline` is a English model originally trained by ferni-riverplate.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_referencias_german_vinos_ferni_riverplate_pipeline_en_5.5.1_3.0_1737689064961.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_referencias_german_vinos_ferni_riverplate_pipeline_en_5.5.1_3.0_1737689064961.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_adaptation_referencias_german_vinos_ferni_riverplate_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_adaptation_referencias_german_vinos_ferni_riverplate_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_adaptation_referencias_german_vinos_ferni_riverplate_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.2 MB|
+
+## References
+
+https://huggingface.co/ferni-riverplate/bert_adaptation_referencias_de_vinos
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_referencias_german_vinos_gongoody_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_referencias_german_vinos_gongoody_en.md
new file mode 100644
index 00000000000000..353d4996bf54c4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_referencias_german_vinos_gongoody_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_adaptation_referencias_german_vinos_gongoody BertSentenceEmbeddings from gongoody
+author: John Snow Labs
+name: sent_bert_adaptation_referencias_german_vinos_gongoody
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_adaptation_referencias_german_vinos_gongoody` is a English model originally trained by gongoody.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_referencias_german_vinos_gongoody_en_5.5.1_3.0_1737748471713.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_referencias_german_vinos_gongoody_en_5.5.1_3.0_1737748471713.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_adaptation_referencias_german_vinos_gongoody","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_adaptation_referencias_german_vinos_gongoody","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_adaptation_referencias_german_vinos_gongoody|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/gongoody/bert_adaptation_referencias_de_vinos
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_referencias_german_vinos_gongoody_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_referencias_german_vinos_gongoody_pipeline_en.md
new file mode 100644
index 00000000000000..d70fda3cfdb4ac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_referencias_german_vinos_gongoody_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_adaptation_referencias_german_vinos_gongoody_pipeline pipeline BertSentenceEmbeddings from gongoody
+author: John Snow Labs
+name: sent_bert_adaptation_referencias_german_vinos_gongoody_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_adaptation_referencias_german_vinos_gongoody_pipeline` is a English model originally trained by gongoody.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_referencias_german_vinos_gongoody_pipeline_en_5.5.1_3.0_1737748493480.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_referencias_german_vinos_gongoody_pipeline_en_5.5.1_3.0_1737748493480.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_adaptation_referencias_german_vinos_gongoody_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_adaptation_referencias_german_vinos_gongoody_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_adaptation_referencias_german_vinos_gongoody_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.2 MB|
+
+## References
+
+https://huggingface.co/gongoody/bert_adaptation_referencias_de_vinos
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_referencias_german_vinos_naevier_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_referencias_german_vinos_naevier_en.md
new file mode 100644
index 00000000000000..86ee11144002ea
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_referencias_german_vinos_naevier_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_adaptation_referencias_german_vinos_naevier BertSentenceEmbeddings from Naevier
+author: John Snow Labs
+name: sent_bert_adaptation_referencias_german_vinos_naevier
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_adaptation_referencias_german_vinos_naevier` is a English model originally trained by Naevier.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_referencias_german_vinos_naevier_en_5.5.1_3.0_1737689188321.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_referencias_german_vinos_naevier_en_5.5.1_3.0_1737689188321.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_adaptation_referencias_german_vinos_naevier","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_adaptation_referencias_german_vinos_naevier","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_adaptation_referencias_german_vinos_naevier|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/Naevier/bert_adaptation_referencias_de_vinos
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_referencias_german_vinos_naevier_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_referencias_german_vinos_naevier_pipeline_en.md
new file mode 100644
index 00000000000000..e17646b862024d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_referencias_german_vinos_naevier_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_adaptation_referencias_german_vinos_naevier_pipeline pipeline BertSentenceEmbeddings from Naevier
+author: John Snow Labs
+name: sent_bert_adaptation_referencias_german_vinos_naevier_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_adaptation_referencias_german_vinos_naevier_pipeline` is a English model originally trained by Naevier.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_referencias_german_vinos_naevier_pipeline_en_5.5.1_3.0_1737689210285.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_referencias_german_vinos_naevier_pipeline_en_5.5.1_3.0_1737689210285.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_adaptation_referencias_german_vinos_naevier_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_adaptation_referencias_german_vinos_naevier_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_adaptation_referencias_german_vinos_naevier_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.2 MB|
+
+## References
+
+https://huggingface.co/Naevier/bert_adaptation_referencias_de_vinos
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_referencias_german_vinos_sofiabobbiesi_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_referencias_german_vinos_sofiabobbiesi_en.md
new file mode 100644
index 00000000000000..fd2c0a527dedea
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_referencias_german_vinos_sofiabobbiesi_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_adaptation_referencias_german_vinos_sofiabobbiesi BertSentenceEmbeddings from sofiabobbiesi
+author: John Snow Labs
+name: sent_bert_adaptation_referencias_german_vinos_sofiabobbiesi
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_adaptation_referencias_german_vinos_sofiabobbiesi` is a English model originally trained by sofiabobbiesi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_referencias_german_vinos_sofiabobbiesi_en_5.5.1_3.0_1737688634838.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_referencias_german_vinos_sofiabobbiesi_en_5.5.1_3.0_1737688634838.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_adaptation_referencias_german_vinos_sofiabobbiesi","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_adaptation_referencias_german_vinos_sofiabobbiesi","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_adaptation_referencias_german_vinos_sofiabobbiesi|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/sofiabobbiesi/bert_adaptation_referencias_de_vinos
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_referencias_german_vinos_sofiabobbiesi_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_referencias_german_vinos_sofiabobbiesi_pipeline_en.md
new file mode 100644
index 00000000000000..4fdd2fc7687cf4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_adaptation_referencias_german_vinos_sofiabobbiesi_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_adaptation_referencias_german_vinos_sofiabobbiesi_pipeline pipeline BertSentenceEmbeddings from sofiabobbiesi
+author: John Snow Labs
+name: sent_bert_adaptation_referencias_german_vinos_sofiabobbiesi_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_adaptation_referencias_german_vinos_sofiabobbiesi_pipeline` is a English model originally trained by sofiabobbiesi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_referencias_german_vinos_sofiabobbiesi_pipeline_en_5.5.1_3.0_1737688659397.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_referencias_german_vinos_sofiabobbiesi_pipeline_en_5.5.1_3.0_1737688659397.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_adaptation_referencias_german_vinos_sofiabobbiesi_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_adaptation_referencias_german_vinos_sofiabobbiesi_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_adaptation_referencias_german_vinos_sofiabobbiesi_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.2 MB|
+
+## References
+
+https://huggingface.co/sofiabobbiesi/bert_adaptation_referencias_de_vinos
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_cased_10_mlm_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_cased_10_mlm_en.md
new file mode 100644
index 00000000000000..1ff6f8c1c1e805
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_cased_10_mlm_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_base_cased_10_mlm BertSentenceEmbeddings from rithwik-db
+author: John Snow Labs
+name: sent_bert_base_cased_10_mlm
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_cased_10_mlm` is a English model originally trained by rithwik-db.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_cased_10_mlm_en_5.5.1_3.0_1737749202219.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_cased_10_mlm_en_5.5.1_3.0_1737749202219.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_cased_10_mlm","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_cased_10_mlm","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_cased_10_mlm|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/rithwik-db/bert-base-cased-10-MLM
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_cased_10_mlm_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_cased_10_mlm_pipeline_en.md
new file mode 100644
index 00000000000000..a651e7322974bf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_cased_10_mlm_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_base_cased_10_mlm_pipeline pipeline BertSentenceEmbeddings from rithwik-db
+author: John Snow Labs
+name: sent_bert_base_cased_10_mlm_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_cased_10_mlm_pipeline` is a English model originally trained by rithwik-db.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_cased_10_mlm_pipeline_en_5.5.1_3.0_1737749224227.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_cased_10_mlm_pipeline_en_5.5.1_3.0_1737749224227.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_base_cased_10_mlm_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_cased_10_mlm_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_cased_10_mlm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|404.2 MB|
+
+## References
+
+https://huggingface.co/rithwik-db/bert-base-cased-10-MLM
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_cased_b4h7_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_cased_b4h7_en.md
new file mode 100644
index 00000000000000..1d4280cc9d369f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_cased_b4h7_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_base_cased_b4h7 BertSentenceEmbeddings from mdroth
+author: John Snow Labs
+name: sent_bert_base_cased_b4h7
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_cased_b4h7` is a English model originally trained by mdroth.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_cased_b4h7_en_5.5.1_3.0_1737689514163.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_cased_b4h7_en_5.5.1_3.0_1737689514163.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_cased_b4h7","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_cased_b4h7","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_cased_b4h7|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/mdroth/bert-base-cased_B4H7
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_cased_b4h7_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_cased_b4h7_pipeline_en.md
new file mode 100644
index 00000000000000..c3aba814aff6df
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_cased_b4h7_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_base_cased_b4h7_pipeline pipeline BertSentenceEmbeddings from mdroth
+author: John Snow Labs
+name: sent_bert_base_cased_b4h7_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_cased_b4h7_pipeline` is a English model originally trained by mdroth.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_cased_b4h7_pipeline_en_5.5.1_3.0_1737689536133.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_cased_b4h7_pipeline_en_5.5.1_3.0_1737689536133.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_base_cased_b4h7_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_cased_b4h7_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_cased_b4h7_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|404.2 MB|
+
+## References
+
+https://huggingface.co/mdroth/bert-base-cased_B4H7
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_cased_wikitext2_klee_9_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_cased_wikitext2_klee_9_en.md
new file mode 100644
index 00000000000000..d3f99cbe9e9bf4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_cased_wikitext2_klee_9_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_base_cased_wikitext2_klee_9 BertSentenceEmbeddings from klee-9
+author: John Snow Labs
+name: sent_bert_base_cased_wikitext2_klee_9
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_cased_wikitext2_klee_9` is a English model originally trained by klee-9.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_cased_wikitext2_klee_9_en_5.5.1_3.0_1737745262492.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_cased_wikitext2_klee_9_en_5.5.1_3.0_1737745262492.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_cased_wikitext2_klee_9","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_cased_wikitext2_klee_9","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_cased_wikitext2_klee_9|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|403.4 MB|
+
+## References
+
+https://huggingface.co/klee-9/bert-base-cased-wikitext2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_cased_wikitext2_klee_9_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_cased_wikitext2_klee_9_pipeline_en.md
new file mode 100644
index 00000000000000..a99ec6c26d9c73
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_cased_wikitext2_klee_9_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_base_cased_wikitext2_klee_9_pipeline pipeline BertSentenceEmbeddings from klee-9
+author: John Snow Labs
+name: sent_bert_base_cased_wikitext2_klee_9_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_cased_wikitext2_klee_9_pipeline` is a English model originally trained by klee-9.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_cased_wikitext2_klee_9_pipeline_en_5.5.1_3.0_1737745283811.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_cased_wikitext2_klee_9_pipeline_en_5.5.1_3.0_1737745283811.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_base_cased_wikitext2_klee_9_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_cased_wikitext2_klee_9_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_cased_wikitext2_klee_9_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|404.0 MB|
+
+## References
+
+https://huggingface.co/klee-9/bert-base-cased-wikitext2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_english_french_german_cased_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_english_french_german_cased_en.md
new file mode 100644
index 00000000000000..503f442d6ade22
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_english_french_german_cased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_base_english_french_german_cased BertSentenceEmbeddings from Geotrend
+author: John Snow Labs
+name: sent_bert_base_english_french_german_cased
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_english_french_german_cased` is a English model originally trained by Geotrend.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_english_french_german_cased_en_5.5.1_3.0_1737688656405.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_english_french_german_cased_en_5.5.1_3.0_1737688656405.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_english_french_german_cased","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_english_french_german_cased","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_english_french_german_cased|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|432.7 MB|
+
+## References
+
+https://huggingface.co/Geotrend/bert-base-en-fr-de-cased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_english_french_german_cased_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_english_french_german_cased_pipeline_en.md
new file mode 100644
index 00000000000000..22b494f07bcc40
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_english_french_german_cased_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_base_english_french_german_cased_pipeline pipeline BertSentenceEmbeddings from Geotrend
+author: John Snow Labs
+name: sent_bert_base_english_french_german_cased_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_english_french_german_cased_pipeline` is a English model originally trained by Geotrend.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_english_french_german_cased_pipeline_en_5.5.1_3.0_1737688681466.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_english_french_german_cased_pipeline_en_5.5.1_3.0_1737688681466.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_base_english_french_german_cased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_english_french_german_cased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_english_french_german_cased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|433.3 MB|
+
+## References
+
+https://huggingface.co/Geotrend/bert-base-en-fr-de-cased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_german_cased_mlm_basque_chemistry_regulation_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_german_cased_mlm_basque_chemistry_regulation_en.md
new file mode 100644
index 00000000000000..048e5c0025826d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_german_cased_mlm_basque_chemistry_regulation_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_base_german_cased_mlm_basque_chemistry_regulation BertSentenceEmbeddings from jonas-luehrs
+author: John Snow Labs
+name: sent_bert_base_german_cased_mlm_basque_chemistry_regulation
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_german_cased_mlm_basque_chemistry_regulation` is a English model originally trained by jonas-luehrs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_german_cased_mlm_basque_chemistry_regulation_en_5.5.1_3.0_1737688859823.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_german_cased_mlm_basque_chemistry_regulation_en_5.5.1_3.0_1737688859823.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_german_cased_mlm_basque_chemistry_regulation","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_german_cased_mlm_basque_chemistry_regulation","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_german_cased_mlm_basque_chemistry_regulation|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/jonas-luehrs/bert-base-german-cased-MLM-eu_chemistry_regulation
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_german_cased_mlm_basque_chemistry_regulation_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_german_cased_mlm_basque_chemistry_regulation_pipeline_en.md
new file mode 100644
index 00000000000000..f991b3ec5fe20b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_german_cased_mlm_basque_chemistry_regulation_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_base_german_cased_mlm_basque_chemistry_regulation_pipeline pipeline BertSentenceEmbeddings from jonas-luehrs
+author: John Snow Labs
+name: sent_bert_base_german_cased_mlm_basque_chemistry_regulation_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_german_cased_mlm_basque_chemistry_regulation_pipeline` is a English model originally trained by jonas-luehrs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_german_cased_mlm_basque_chemistry_regulation_pipeline_en_5.5.1_3.0_1737688883914.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_german_cased_mlm_basque_chemistry_regulation_pipeline_en_5.5.1_3.0_1737688883914.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_base_german_cased_mlm_basque_chemistry_regulation_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_german_cased_mlm_basque_chemistry_regulation_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_german_cased_mlm_basque_chemistry_regulation_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.4 MB|
+
+## References
+
+https://huggingface.co/jonas-luehrs/bert-base-german-cased-MLM-eu_chemistry_regulation
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_german_cased_mlm_basque_oriya_ddr_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_german_cased_mlm_basque_oriya_ddr_en.md
new file mode 100644
index 00000000000000..5cf142b95d76f1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_german_cased_mlm_basque_oriya_ddr_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_base_german_cased_mlm_basque_oriya_ddr BertSentenceEmbeddings from jonas-luehrs
+author: John Snow Labs
+name: sent_bert_base_german_cased_mlm_basque_oriya_ddr
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_german_cased_mlm_basque_oriya_ddr` is a English model originally trained by jonas-luehrs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_german_cased_mlm_basque_oriya_ddr_en_5.5.1_3.0_1737689346150.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_german_cased_mlm_basque_oriya_ddr_en_5.5.1_3.0_1737689346150.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_german_cased_mlm_basque_oriya_ddr","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_german_cased_mlm_basque_oriya_ddr","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_german_cased_mlm_basque_oriya_ddr|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/jonas-luehrs/bert-base-german-cased-MLM-eu-or-ddr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_german_cased_mlm_basque_oriya_ddr_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_german_cased_mlm_basque_oriya_ddr_pipeline_en.md
new file mode 100644
index 00000000000000..219af8e7ee7799
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_german_cased_mlm_basque_oriya_ddr_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_base_german_cased_mlm_basque_oriya_ddr_pipeline pipeline BertSentenceEmbeddings from jonas-luehrs
+author: John Snow Labs
+name: sent_bert_base_german_cased_mlm_basque_oriya_ddr_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_german_cased_mlm_basque_oriya_ddr_pipeline` is a English model originally trained by jonas-luehrs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_german_cased_mlm_basque_oriya_ddr_pipeline_en_5.5.1_3.0_1737689367194.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_german_cased_mlm_basque_oriya_ddr_pipeline_en_5.5.1_3.0_1737689367194.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_base_german_cased_mlm_basque_oriya_ddr_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_german_cased_mlm_basque_oriya_ddr_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_german_cased_mlm_basque_oriya_ddr_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.4 MB|
+
+## References
+
+https://huggingface.co/jonas-luehrs/bert-base-german-cased-MLM-eu-or-ddr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_mm_awesomealignindic_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_mm_awesomealignindic_en.md
new file mode 100644
index 00000000000000..a5aaa22a518399
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_mm_awesomealignindic_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_base_mm_awesomealignindic BertSentenceEmbeddings from ABHIiiii1
+author: John Snow Labs
+name: sent_bert_base_mm_awesomealignindic
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_mm_awesomealignindic` is a English model originally trained by ABHIiiii1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_mm_awesomealignindic_en_5.5.1_3.0_1737748994072.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_mm_awesomealignindic_en_5.5.1_3.0_1737748994072.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_mm_awesomealignindic","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_mm_awesomealignindic","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_mm_awesomealignindic|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/ABHIiiii1/bert-base-mm-awesomeAlignIndic
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_mm_awesomealignindic_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_mm_awesomealignindic_pipeline_en.md
new file mode 100644
index 00000000000000..d225bbe96007ab
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_mm_awesomealignindic_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_base_mm_awesomealignindic_pipeline pipeline BertSentenceEmbeddings from ABHIiiii1
+author: John Snow Labs
+name: sent_bert_base_mm_awesomealignindic_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_mm_awesomealignindic_pipeline` is a English model originally trained by ABHIiiii1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_mm_awesomealignindic_pipeline_en_5.5.1_3.0_1737749036672.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_mm_awesomealignindic_pipeline_en_5.5.1_3.0_1737749036672.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_base_mm_awesomealignindic_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_mm_awesomealignindic_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_mm_awesomealignindic_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|665.6 MB|
+
+## References
+
+https://huggingface.co/ABHIiiii1/bert-base-mm-awesomeAlignIndic
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_qarib_ar.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_qarib_ar.md
new file mode 100644
index 00000000000000..4004819bd1bde4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_qarib_ar.md
@@ -0,0 +1,96 @@
+---
+layout: model
+title: Arabic sent_bert_base_qarib BertSentenceEmbeddings from qarib
+author: John Snow Labs
+name: sent_bert_base_qarib
+date: 2025-01-24
+tags: [ar, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: ar
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_qarib` is a Arabic model originally trained by qarib.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_qarib_ar_5.5.1_3.0_1737684013196.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_qarib_ar_5.5.1_3.0_1737684013196.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_qarib","ar") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_qarib","ar") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_qarib|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|ar|
+|Size:|504.0 MB|
+
+## References
+
+References
+
+https://huggingface.co/qarib/bert-base-qarib
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_qarib_pipeline_ar.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_qarib_pipeline_ar.md
new file mode 100644
index 00000000000000..f5fb38f79bc51b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_qarib_pipeline_ar.md
@@ -0,0 +1,73 @@
+---
+layout: model
+title: Arabic sent_bert_base_qarib_pipeline pipeline BertSentenceEmbeddings from qarib
+author: John Snow Labs
+name: sent_bert_base_qarib_pipeline
+date: 2025-01-24
+tags: [ar, open_source, pipeline, onnx]
+task: Embeddings
+language: ar
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_qarib_pipeline` is a Arabic model originally trained by qarib.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_qarib_pipeline_ar_5.5.1_3.0_1737684042644.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_qarib_pipeline_ar_5.5.1_3.0_1737684042644.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("sent_bert_base_qarib_pipeline", lang = "ar")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("sent_bert_base_qarib_pipeline", lang = "ar")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_qarib_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ar|
+|Size:|504.6 MB|
+
+## References
+
+References
+
+https://huggingface.co/qarib/bert-base-qarib
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_spanish_wwm_cased_finetuned_peppa_pig_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_spanish_wwm_cased_finetuned_peppa_pig_en.md
new file mode 100644
index 00000000000000..64d0f75a134c89
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_spanish_wwm_cased_finetuned_peppa_pig_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_base_spanish_wwm_cased_finetuned_peppa_pig BertSentenceEmbeddings from guidoivetta
+author: John Snow Labs
+name: sent_bert_base_spanish_wwm_cased_finetuned_peppa_pig
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_spanish_wwm_cased_finetuned_peppa_pig` is a English model originally trained by guidoivetta.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_spanish_wwm_cased_finetuned_peppa_pig_en_5.5.1_3.0_1737689567387.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_spanish_wwm_cased_finetuned_peppa_pig_en_5.5.1_3.0_1737689567387.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_spanish_wwm_cased_finetuned_peppa_pig","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_spanish_wwm_cased_finetuned_peppa_pig","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_spanish_wwm_cased_finetuned_peppa_pig|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|409.5 MB|
+
+## References
+
+https://huggingface.co/guidoivetta/bert-base-spanish-wwm-cased-finetuned-peppa-pig
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_spanish_wwm_cased_finetuned_peppa_pig_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_spanish_wwm_cased_finetuned_peppa_pig_pipeline_en.md
new file mode 100644
index 00000000000000..6e6554a76f0c76
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_spanish_wwm_cased_finetuned_peppa_pig_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_base_spanish_wwm_cased_finetuned_peppa_pig_pipeline pipeline BertSentenceEmbeddings from guidoivetta
+author: John Snow Labs
+name: sent_bert_base_spanish_wwm_cased_finetuned_peppa_pig_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_spanish_wwm_cased_finetuned_peppa_pig_pipeline` is a English model originally trained by guidoivetta.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_spanish_wwm_cased_finetuned_peppa_pig_pipeline_en_5.5.1_3.0_1737689589368.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_spanish_wwm_cased_finetuned_peppa_pig_pipeline_en_5.5.1_3.0_1737689589368.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_base_spanish_wwm_cased_finetuned_peppa_pig_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_spanish_wwm_cased_finetuned_peppa_pig_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_spanish_wwm_cased_finetuned_peppa_pig_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.0 MB|
+
+## References
+
+https://huggingface.co/guidoivetta/bert-base-spanish-wwm-cased-finetuned-peppa-pig
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_uncased_finetuned_mlm_nef_20240325_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_uncased_finetuned_mlm_nef_20240325_en.md
new file mode 100644
index 00000000000000..cba93bdd44294e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_uncased_finetuned_mlm_nef_20240325_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_base_uncased_finetuned_mlm_nef_20240325 BertSentenceEmbeddings from JTh34
+author: John Snow Labs
+name: sent_bert_base_uncased_finetuned_mlm_nef_20240325
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_uncased_finetuned_mlm_nef_20240325` is a English model originally trained by JTh34.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_finetuned_mlm_nef_20240325_en_5.5.1_3.0_1737748444159.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_finetuned_mlm_nef_20240325_en_5.5.1_3.0_1737748444159.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_uncased_finetuned_mlm_nef_20240325","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_uncased_finetuned_mlm_nef_20240325","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_uncased_finetuned_mlm_nef_20240325|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|417.5 MB|
+
+## References
+
+https://huggingface.co/JTh34/bert-base-uncased-finetuned-mlm-nef-20240325
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_uncased_finetuned_mlm_nef_20240325_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_uncased_finetuned_mlm_nef_20240325_pipeline_en.md
new file mode 100644
index 00000000000000..ab1ae820566dfb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_uncased_finetuned_mlm_nef_20240325_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_base_uncased_finetuned_mlm_nef_20240325_pipeline pipeline BertSentenceEmbeddings from JTh34
+author: John Snow Labs
+name: sent_bert_base_uncased_finetuned_mlm_nef_20240325_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_uncased_finetuned_mlm_nef_20240325_pipeline` is a English model originally trained by JTh34.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_finetuned_mlm_nef_20240325_pipeline_en_5.5.1_3.0_1737748466916.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_finetuned_mlm_nef_20240325_pipeline_en_5.5.1_3.0_1737748466916.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_base_uncased_finetuned_mlm_nef_20240325_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_uncased_finetuned_mlm_nef_20240325_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_uncased_finetuned_mlm_nef_20240325_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|418.0 MB|
+
+## References
+
+https://huggingface.co/JTh34/bert-base-uncased-finetuned-mlm-nef-20240325
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_uncased_finetuned_wallisian_lower_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_uncased_finetuned_wallisian_lower_en.md
new file mode 100644
index 00000000000000..992ea23d1e5306
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_uncased_finetuned_wallisian_lower_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_base_uncased_finetuned_wallisian_lower BertSentenceEmbeddings from btamm12
+author: John Snow Labs
+name: sent_bert_base_uncased_finetuned_wallisian_lower
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_uncased_finetuned_wallisian_lower` is a English model originally trained by btamm12.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_finetuned_wallisian_lower_en_5.5.1_3.0_1737745939836.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_finetuned_wallisian_lower_en_5.5.1_3.0_1737745939836.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_uncased_finetuned_wallisian_lower","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_uncased_finetuned_wallisian_lower","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_uncased_finetuned_wallisian_lower|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/btamm12/bert-base-uncased-finetuned-wls-lower
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_uncased_finetuned_wallisian_lower_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_uncased_finetuned_wallisian_lower_pipeline_en.md
new file mode 100644
index 00000000000000..66c2aaacafb99a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_uncased_finetuned_wallisian_lower_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_base_uncased_finetuned_wallisian_lower_pipeline pipeline BertSentenceEmbeddings from btamm12
+author: John Snow Labs
+name: sent_bert_base_uncased_finetuned_wallisian_lower_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_uncased_finetuned_wallisian_lower_pipeline` is a English model originally trained by btamm12.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_finetuned_wallisian_lower_pipeline_en_5.5.1_3.0_1737745961884.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_finetuned_wallisian_lower_pipeline_en_5.5.1_3.0_1737745961884.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_base_uncased_finetuned_wallisian_lower_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_uncased_finetuned_wallisian_lower_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_uncased_finetuned_wallisian_lower_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.7 MB|
+
+## References
+
+https://huggingface.co/btamm12/bert-base-uncased-finetuned-wls-lower
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_uncased_issues_128_vantaa32_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_uncased_issues_128_vantaa32_en.md
new file mode 100644
index 00000000000000..d142a1b2804c1b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_uncased_issues_128_vantaa32_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_base_uncased_issues_128_vantaa32 BertSentenceEmbeddings from vantaa32
+author: John Snow Labs
+name: sent_bert_base_uncased_issues_128_vantaa32
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_uncased_issues_128_vantaa32` is a English model originally trained by vantaa32.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_issues_128_vantaa32_en_5.5.1_3.0_1737684552775.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_issues_128_vantaa32_en_5.5.1_3.0_1737684552775.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_uncased_issues_128_vantaa32","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_uncased_issues_128_vantaa32","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_uncased_issues_128_vantaa32|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/vantaa32/bert-base-uncased-issues-128
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_uncased_issues_128_vantaa32_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_uncased_issues_128_vantaa32_pipeline_en.md
new file mode 100644
index 00000000000000..8d9f5c71559c7e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_base_uncased_issues_128_vantaa32_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_base_uncased_issues_128_vantaa32_pipeline pipeline BertSentenceEmbeddings from vantaa32
+author: John Snow Labs
+name: sent_bert_base_uncased_issues_128_vantaa32_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_uncased_issues_128_vantaa32_pipeline` is a English model originally trained by vantaa32.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_issues_128_vantaa32_pipeline_en_5.5.1_3.0_1737684574682.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_issues_128_vantaa32_pipeline_en_5.5.1_3.0_1737684574682.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_base_uncased_issues_128_vantaa32_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_uncased_issues_128_vantaa32_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_uncased_issues_128_vantaa32_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.7 MB|
+
+## References
+
+https://huggingface.co/vantaa32/bert-base-uncased-issues-128
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_job_german_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_job_german_en.md
new file mode 100644
index 00000000000000..dccf66c87c0d22
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_job_german_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_job_german BertSentenceEmbeddings from dathi103
+author: John Snow Labs
+name: sent_bert_job_german
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_job_german` is a English model originally trained by dathi103.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_job_german_en_5.5.1_3.0_1737689059147.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_job_german_en_5.5.1_3.0_1737689059147.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_job_german","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_job_german","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_job_german|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/dathi103/bert-job-german
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_job_german_extended_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_job_german_extended_en.md
new file mode 100644
index 00000000000000..ab13b7f8c686b3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_job_german_extended_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_job_german_extended BertSentenceEmbeddings from dathi103
+author: John Snow Labs
+name: sent_bert_job_german_extended
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_job_german_extended` is a English model originally trained by dathi103.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_job_german_extended_en_5.5.1_3.0_1737745483710.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_job_german_extended_en_5.5.1_3.0_1737745483710.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_job_german_extended","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_job_german_extended","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_job_german_extended|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|418.3 MB|
+
+## References
+
+https://huggingface.co/dathi103/bert-job-german-extended
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_job_german_extended_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_job_german_extended_pipeline_en.md
new file mode 100644
index 00000000000000..e6795f0d6e949e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_job_german_extended_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_job_german_extended_pipeline pipeline BertSentenceEmbeddings from dathi103
+author: John Snow Labs
+name: sent_bert_job_german_extended_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_job_german_extended_pipeline` is a English model originally trained by dathi103.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_job_german_extended_pipeline_en_5.5.1_3.0_1737745505670.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_job_german_extended_pipeline_en_5.5.1_3.0_1737745505670.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_job_german_extended_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_job_german_extended_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_job_german_extended_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|418.8 MB|
+
+## References
+
+https://huggingface.co/dathi103/bert-job-german-extended
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_job_german_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_job_german_pipeline_en.md
new file mode 100644
index 00000000000000..2b51fc90e5ac80
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_job_german_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_job_german_pipeline pipeline BertSentenceEmbeddings from dathi103
+author: John Snow Labs
+name: sent_bert_job_german_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_job_german_pipeline` is a English model originally trained by dathi103.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_job_german_pipeline_en_5.5.1_3.0_1737689083934.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_job_german_pipeline_en_5.5.1_3.0_1737689083934.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_job_german_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_job_german_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_job_german_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.4 MB|
+
+## References
+
+https://huggingface.co/dathi103/bert-job-german
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_lorafinetuned_covidqa_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_lorafinetuned_covidqa_en.md
new file mode 100644
index 00000000000000..0f81e8520df63f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_lorafinetuned_covidqa_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_lorafinetuned_covidqa BertSentenceEmbeddings from dqduong2003
+author: John Snow Labs
+name: sent_bert_lorafinetuned_covidqa
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_lorafinetuned_covidqa` is a English model originally trained by dqduong2003.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_lorafinetuned_covidqa_en_5.5.1_3.0_1737749364821.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_lorafinetuned_covidqa_en_5.5.1_3.0_1737749364821.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_lorafinetuned_covidqa","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_lorafinetuned_covidqa","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_lorafinetuned_covidqa|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|402.3 MB|
+
+## References
+
+https://huggingface.co/dqduong2003/bert-lorafinetuned-covidqa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_lorafinetuned_covidqa_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_lorafinetuned_covidqa_pipeline_en.md
new file mode 100644
index 00000000000000..f0d3ac6fb34d02
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_lorafinetuned_covidqa_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_lorafinetuned_covidqa_pipeline pipeline BertSentenceEmbeddings from dqduong2003
+author: John Snow Labs
+name: sent_bert_lorafinetuned_covidqa_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_lorafinetuned_covidqa_pipeline` is a English model originally trained by dqduong2003.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_lorafinetuned_covidqa_pipeline_en_5.5.1_3.0_1737749392157.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_lorafinetuned_covidqa_pipeline_en_5.5.1_3.0_1737749392157.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_lorafinetuned_covidqa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_lorafinetuned_covidqa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_lorafinetuned_covidqa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|402.9 MB|
+
+## References
+
+https://huggingface.co/dqduong2003/bert-lorafinetuned-covidqa
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_pretrained_litcov10k_paraphrased_all_shuffled_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_pretrained_litcov10k_paraphrased_all_shuffled_en.md
new file mode 100644
index 00000000000000..af1c5fb76028cc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_pretrained_litcov10k_paraphrased_all_shuffled_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_pretrained_litcov10k_paraphrased_all_shuffled BertSentenceEmbeddings from IneG
+author: John Snow Labs
+name: sent_bert_pretrained_litcov10k_paraphrased_all_shuffled
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_pretrained_litcov10k_paraphrased_all_shuffled` is a English model originally trained by IneG.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_pretrained_litcov10k_paraphrased_all_shuffled_en_5.5.1_3.0_1737683832996.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_pretrained_litcov10k_paraphrased_all_shuffled_en_5.5.1_3.0_1737683832996.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_pretrained_litcov10k_paraphrased_all_shuffled","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_pretrained_litcov10k_paraphrased_all_shuffled","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_pretrained_litcov10k_paraphrased_all_shuffled|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/IneG/BERT_pretrained_litcov10K_paraphrased_all-shuffled
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_pretrained_litcov10k_paraphrased_all_shuffled_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_pretrained_litcov10k_paraphrased_all_shuffled_pipeline_en.md
new file mode 100644
index 00000000000000..38465fbd32750f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_pretrained_litcov10k_paraphrased_all_shuffled_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_pretrained_litcov10k_paraphrased_all_shuffled_pipeline pipeline BertSentenceEmbeddings from IneG
+author: John Snow Labs
+name: sent_bert_pretrained_litcov10k_paraphrased_all_shuffled_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_pretrained_litcov10k_paraphrased_all_shuffled_pipeline` is a English model originally trained by IneG.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_pretrained_litcov10k_paraphrased_all_shuffled_pipeline_en_5.5.1_3.0_1737683855750.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_pretrained_litcov10k_paraphrased_all_shuffled_pipeline_en_5.5.1_3.0_1737683855750.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_pretrained_litcov10k_paraphrased_all_shuffled_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_pretrained_litcov10k_paraphrased_all_shuffled_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_pretrained_litcov10k_paraphrased_all_shuffled_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.7 MB|
+
+## References
+
+https://huggingface.co/IneG/BERT_pretrained_litcov10K_paraphrased_all-shuffled
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_small_finetuned_eurlex_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_small_finetuned_eurlex_en.md
new file mode 100644
index 00000000000000..efd626c5bd49b6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_small_finetuned_eurlex_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_small_finetuned_eurlex BertSentenceEmbeddings from muhtasham
+author: John Snow Labs
+name: sent_bert_small_finetuned_eurlex
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_small_finetuned_eurlex` is a English model originally trained by muhtasham.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_small_finetuned_eurlex_en_5.5.1_3.0_1737683835373.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_small_finetuned_eurlex_en_5.5.1_3.0_1737683835373.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_small_finetuned_eurlex","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_small_finetuned_eurlex","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_small_finetuned_eurlex|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|107.0 MB|
+
+## References
+
+https://huggingface.co/muhtasham/bert-small-finetuned-eurlex
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_small_finetuned_eurlex_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_small_finetuned_eurlex_pipeline_en.md
new file mode 100644
index 00000000000000..05a567d2f16087
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_small_finetuned_eurlex_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_small_finetuned_eurlex_pipeline pipeline BertSentenceEmbeddings from muhtasham
+author: John Snow Labs
+name: sent_bert_small_finetuned_eurlex_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_small_finetuned_eurlex_pipeline` is a English model originally trained by muhtasham.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_small_finetuned_eurlex_pipeline_en_5.5.1_3.0_1737683842555.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_small_finetuned_eurlex_pipeline_en_5.5.1_3.0_1737683842555.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_small_finetuned_eurlex_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_small_finetuned_eurlex_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_small_finetuned_eurlex_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|107.5 MB|
+
+## References
+
+https://huggingface.co/muhtasham/bert-small-finetuned-eurlex
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_wordpiece_phonetic_wikitext_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_wordpiece_phonetic_wikitext_en.md
new file mode 100644
index 00000000000000..aab996f2272d37
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_wordpiece_phonetic_wikitext_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_wordpiece_phonetic_wikitext BertSentenceEmbeddings from psktoure
+author: John Snow Labs
+name: sent_bert_wordpiece_phonetic_wikitext
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_wordpiece_phonetic_wikitext` is a English model originally trained by psktoure.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_wordpiece_phonetic_wikitext_en_5.5.1_3.0_1737684284941.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_wordpiece_phonetic_wikitext_en_5.5.1_3.0_1737684284941.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_wordpiece_phonetic_wikitext","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_wordpiece_phonetic_wikitext","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_wordpiece_phonetic_wikitext|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|408.1 MB|
+
+## References
+
+https://huggingface.co/psktoure/BERT_WordPiece_phonetic_wikitext
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bert_wordpiece_phonetic_wikitext_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_wordpiece_phonetic_wikitext_pipeline_en.md
new file mode 100644
index 00000000000000..55ce147d3f97fa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bert_wordpiece_phonetic_wikitext_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_wordpiece_phonetic_wikitext_pipeline pipeline BertSentenceEmbeddings from psktoure
+author: John Snow Labs
+name: sent_bert_wordpiece_phonetic_wikitext_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_wordpiece_phonetic_wikitext_pipeline` is a English model originally trained by psktoure.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_wordpiece_phonetic_wikitext_pipeline_en_5.5.1_3.0_1737684306287.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_wordpiece_phonetic_wikitext_pipeline_en_5.5.1_3.0_1737684306287.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_wordpiece_phonetic_wikitext_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_wordpiece_phonetic_wikitext_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_wordpiece_phonetic_wikitext_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|408.7 MB|
+
+## References
+
+https://huggingface.co/psktoure/BERT_WordPiece_phonetic_wikitext
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_berth4_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_berth4_en.md
new file mode 100644
index 00000000000000..b8672f5fef8807
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_berth4_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_berth4 BertSentenceEmbeddings from JeloH
+author: John Snow Labs
+name: sent_berth4
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_berth4` is a English model originally trained by JeloH.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_berth4_en_5.5.1_3.0_1737689548845.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_berth4_en_5.5.1_3.0_1737689548845.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_berth4","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_berth4","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_berth4|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/JeloH/BertH4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_berth4_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_berth4_pipeline_en.md
new file mode 100644
index 00000000000000..20e2fd1c3044aa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_berth4_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_berth4_pipeline pipeline BertSentenceEmbeddings from JeloH
+author: John Snow Labs
+name: sent_berth4_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_berth4_pipeline` is a English model originally trained by JeloH.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_berth4_pipeline_en_5.5.1_3.0_1737689570461.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_berth4_pipeline_en_5.5.1_3.0_1737689570461.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_berth4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_berth4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_berth4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.7 MB|
+
+## References
+
+https://huggingface.co/JeloH/BertH4
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bertskill_relative_key_query_modif_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bertskill_relative_key_query_modif_en.md
new file mode 100644
index 00000000000000..688372da15387f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bertskill_relative_key_query_modif_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bertskill_relative_key_query_modif BertSentenceEmbeddings from meilanynonsitentua
+author: John Snow Labs
+name: sent_bertskill_relative_key_query_modif
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bertskill_relative_key_query_modif` is a English model originally trained by meilanynonsitentua.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bertskill_relative_key_query_modif_en_5.5.1_3.0_1737745413564.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bertskill_relative_key_query_modif_en_5.5.1_3.0_1737745413564.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bertskill_relative_key_query_modif","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bertskill_relative_key_query_modif","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bertskill_relative_key_query_modif|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|414.1 MB|
+
+## References
+
+https://huggingface.co/meilanynonsitentua/bertskill-relative-key-query-modif
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bertskill_relative_key_query_modif_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bertskill_relative_key_query_modif_pipeline_en.md
new file mode 100644
index 00000000000000..cadc0574c1fdcb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bertskill_relative_key_query_modif_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bertskill_relative_key_query_modif_pipeline pipeline BertSentenceEmbeddings from meilanynonsitentua
+author: John Snow Labs
+name: sent_bertskill_relative_key_query_modif_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bertskill_relative_key_query_modif_pipeline` is a English model originally trained by meilanynonsitentua.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bertskill_relative_key_query_modif_pipeline_en_5.5.1_3.0_1737745434840.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bertskill_relative_key_query_modif_pipeline_en_5.5.1_3.0_1737745434840.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bertskill_relative_key_query_modif_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bertskill_relative_key_query_modif_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bertskill_relative_key_query_modif_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|414.6 MB|
+
+## References
+
+https://huggingface.co/meilanynonsitentua/bertskill-relative-key-query-modif
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bertturk_ner_ottoman_raw_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bertturk_ner_ottoman_raw_en.md
new file mode 100644
index 00000000000000..5387684e40653b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bertturk_ner_ottoman_raw_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bertturk_ner_ottoman_raw BertSentenceEmbeddings from onurkeles
+author: John Snow Labs
+name: sent_bertturk_ner_ottoman_raw
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bertturk_ner_ottoman_raw` is a English model originally trained by onurkeles.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bertturk_ner_ottoman_raw_en_5.5.1_3.0_1737688388447.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bertturk_ner_ottoman_raw_en_5.5.1_3.0_1737688388447.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bertturk_ner_ottoman_raw","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bertturk_ner_ottoman_raw","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bertturk_ner_ottoman_raw|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|412.0 MB|
+
+## References
+
+https://huggingface.co/onurkeles/bertturk-ner-ottoman-raw
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bertturk_ner_ottoman_raw_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bertturk_ner_ottoman_raw_pipeline_en.md
new file mode 100644
index 00000000000000..6b96b3262cb9da
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bertturk_ner_ottoman_raw_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bertturk_ner_ottoman_raw_pipeline pipeline BertSentenceEmbeddings from onurkeles
+author: John Snow Labs
+name: sent_bertturk_ner_ottoman_raw_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bertturk_ner_ottoman_raw_pipeline` is a English model originally trained by onurkeles.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bertturk_ner_ottoman_raw_pipeline_en_5.5.1_3.0_1737688418870.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bertturk_ner_ottoman_raw_pipeline_en_5.5.1_3.0_1737688418870.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bertturk_ner_ottoman_raw_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bertturk_ner_ottoman_raw_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bertturk_ner_ottoman_raw_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|412.5 MB|
+
+## References
+
+https://huggingface.co/onurkeles/bertturk-ner-ottoman-raw
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bio_clinicalbert_finetuned_imdb_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bio_clinicalbert_finetuned_imdb_en.md
new file mode 100644
index 00000000000000..2337959db3bcbf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bio_clinicalbert_finetuned_imdb_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bio_clinicalbert_finetuned_imdb BertSentenceEmbeddings from reza93v
+author: John Snow Labs
+name: sent_bio_clinicalbert_finetuned_imdb
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bio_clinicalbert_finetuned_imdb` is a English model originally trained by reza93v.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bio_clinicalbert_finetuned_imdb_en_5.5.1_3.0_1737689199636.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bio_clinicalbert_finetuned_imdb_en_5.5.1_3.0_1737689199636.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bio_clinicalbert_finetuned_imdb","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bio_clinicalbert_finetuned_imdb","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bio_clinicalbert_finetuned_imdb|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|403.3 MB|
+
+## References
+
+https://huggingface.co/reza93v/Bio_ClinicalBERT-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_bio_clinicalbert_finetuned_imdb_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_bio_clinicalbert_finetuned_imdb_pipeline_en.md
new file mode 100644
index 00000000000000..de6fb8abc202d7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_bio_clinicalbert_finetuned_imdb_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bio_clinicalbert_finetuned_imdb_pipeline pipeline BertSentenceEmbeddings from reza93v
+author: John Snow Labs
+name: sent_bio_clinicalbert_finetuned_imdb_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bio_clinicalbert_finetuned_imdb_pipeline` is a English model originally trained by reza93v.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bio_clinicalbert_finetuned_imdb_pipeline_en_5.5.1_3.0_1737689221489.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bio_clinicalbert_finetuned_imdb_pipeline_en_5.5.1_3.0_1737689221489.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bio_clinicalbert_finetuned_imdb_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bio_clinicalbert_finetuned_imdb_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bio_clinicalbert_finetuned_imdb_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.9 MB|
+
+## References
+
+https://huggingface.co/reza93v/Bio_ClinicalBERT-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_biobert_italian_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_biobert_italian_en.md
new file mode 100644
index 00000000000000..6fc8b1d67ab6f9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_biobert_italian_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_biobert_italian BertSentenceEmbeddings from marcopost-it
+author: John Snow Labs
+name: sent_biobert_italian
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_biobert_italian` is a English model originally trained by marcopost-it.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_biobert_italian_en_5.5.1_3.0_1737746369730.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_biobert_italian_en_5.5.1_3.0_1737746369730.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_biobert_italian","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_biobert_italian","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_biobert_italian|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|410.2 MB|
+
+## References
+
+https://huggingface.co/marcopost-it/biobert-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_biobert_italian_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_biobert_italian_pipeline_en.md
new file mode 100644
index 00000000000000..238cc1b25a3998
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_biobert_italian_pipeline_en.md
@@ -0,0 +1,73 @@
+---
+layout: model
+title: English sent_biobert_italian_pipeline pipeline BertSentenceEmbeddings from marcopost-it
+author: John Snow Labs
+name: sent_biobert_italian_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_biobert_italian_pipeline` is a English model originally trained by marcopost-it.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_biobert_italian_pipeline_en_5.5.1_3.0_1737746393339.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_biobert_italian_pipeline_en_5.5.1_3.0_1737746393339.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("sent_biobert_italian_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("sent_biobert_italian_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_biobert_italian_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.8 MB|
+
+## References
+
+References
+
+https://huggingface.co/marcopost-it/biobert-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_blade_english_chinese_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_blade_english_chinese_en.md
new file mode 100644
index 00000000000000..ec506260bcaf9e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_blade_english_chinese_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_blade_english_chinese BertSentenceEmbeddings from srnair
+author: John Snow Labs
+name: sent_blade_english_chinese
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_blade_english_chinese` is a English model originally trained by srnair.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_blade_english_chinese_en_5.5.1_3.0_1737749071417.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_blade_english_chinese_en_5.5.1_3.0_1737749071417.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_blade_english_chinese","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_blade_english_chinese","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_blade_english_chinese|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|421.8 MB|
+
+## References
+
+https://huggingface.co/srnair/blade-en-zh
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_blade_english_chinese_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_blade_english_chinese_pipeline_en.md
new file mode 100644
index 00000000000000..a457181ad3626a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_blade_english_chinese_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_blade_english_chinese_pipeline pipeline BertSentenceEmbeddings from srnair
+author: John Snow Labs
+name: sent_blade_english_chinese_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_blade_english_chinese_pipeline` is a English model originally trained by srnair.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_blade_english_chinese_pipeline_en_5.5.1_3.0_1737749093954.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_blade_english_chinese_pipeline_en_5.5.1_3.0_1737749093954.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_blade_english_chinese_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_blade_english_chinese_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_blade_english_chinese_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|422.3 MB|
+
+## References
+
+https://huggingface.co/srnair/blade-en-zh
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_blade_english_russian_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_blade_english_russian_en.md
new file mode 100644
index 00000000000000..a708d9a2a2ada3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_blade_english_russian_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_blade_english_russian BertSentenceEmbeddings from srnair
+author: John Snow Labs
+name: sent_blade_english_russian
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_blade_english_russian` is a English model originally trained by srnair.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_blade_english_russian_en_5.5.1_3.0_1737749341797.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_blade_english_russian_en_5.5.1_3.0_1737749341797.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_blade_english_russian","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_blade_english_russian","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_blade_english_russian|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|428.2 MB|
+
+## References
+
+https://huggingface.co/srnair/blade-en-ru
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_blade_english_russian_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_blade_english_russian_pipeline_en.md
new file mode 100644
index 00000000000000..eaafa110fc6b5d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_blade_english_russian_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_blade_english_russian_pipeline pipeline BertSentenceEmbeddings from srnair
+author: John Snow Labs
+name: sent_blade_english_russian_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_blade_english_russian_pipeline` is a English model originally trained by srnair.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_blade_english_russian_pipeline_en_5.5.1_3.0_1737749366545.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_blade_english_russian_pipeline_en_5.5.1_3.0_1737749366545.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_blade_english_russian_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_blade_english_russian_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_blade_english_russian_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|428.8 MB|
+
+## References
+
+https://huggingface.co/srnair/blade-en-ru
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_colbert_cocomae_220_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_colbert_cocomae_220_en.md
new file mode 100644
index 00000000000000..18784abf12514e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_colbert_cocomae_220_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_colbert_cocomae_220 BertSentenceEmbeddings from approach0
+author: John Snow Labs
+name: sent_colbert_cocomae_220
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_colbert_cocomae_220` is a English model originally trained by approach0.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_colbert_cocomae_220_en_5.5.1_3.0_1737749223867.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_colbert_cocomae_220_en_5.5.1_3.0_1737749223867.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_colbert_cocomae_220","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_colbert_cocomae_220","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_colbert_cocomae_220|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|409.9 MB|
+
+## References
+
+https://huggingface.co/approach0/colbert-cocomae-220
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_colbert_cocomae_220_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_colbert_cocomae_220_pipeline_en.md
new file mode 100644
index 00000000000000..4c082da1ef226c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_colbert_cocomae_220_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_colbert_cocomae_220_pipeline pipeline BertSentenceEmbeddings from approach0
+author: John Snow Labs
+name: sent_colbert_cocomae_220_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_colbert_cocomae_220_pipeline` is a English model originally trained by approach0.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_colbert_cocomae_220_pipeline_en_5.5.1_3.0_1737749248446.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_colbert_cocomae_220_pipeline_en_5.5.1_3.0_1737749248446.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_colbert_cocomae_220_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_colbert_cocomae_220_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_colbert_cocomae_220_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.4 MB|
+
+## References
+
+https://huggingface.co/approach0/colbert-cocomae-220
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_conflibert_scr_uncased_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_conflibert_scr_uncased_en.md
new file mode 100644
index 00000000000000..1e86db2256e29b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_conflibert_scr_uncased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_conflibert_scr_uncased BertSentenceEmbeddings from eventdata-utd
+author: John Snow Labs
+name: sent_conflibert_scr_uncased
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_conflibert_scr_uncased` is a English model originally trained by eventdata-utd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_conflibert_scr_uncased_en_5.5.1_3.0_1737688613766.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_conflibert_scr_uncased_en_5.5.1_3.0_1737688613766.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_conflibert_scr_uncased","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_conflibert_scr_uncased","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_conflibert_scr_uncased|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|406.0 MB|
+
+## References
+
+https://huggingface.co/eventdata-utd/ConfliBERT-scr-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_conflibert_scr_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_conflibert_scr_uncased_pipeline_en.md
new file mode 100644
index 00000000000000..4bf8b1ab06c58b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_conflibert_scr_uncased_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_conflibert_scr_uncased_pipeline pipeline BertSentenceEmbeddings from eventdata-utd
+author: John Snow Labs
+name: sent_conflibert_scr_uncased_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_conflibert_scr_uncased_pipeline` is a English model originally trained by eventdata-utd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_conflibert_scr_uncased_pipeline_en_5.5.1_3.0_1737688635466.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_conflibert_scr_uncased_pipeline_en_5.5.1_3.0_1737688635466.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_conflibert_scr_uncased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_conflibert_scr_uncased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_conflibert_scr_uncased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.5 MB|
+
+## References
+
+https://huggingface.co/eventdata-utd/ConfliBERT-scr-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_dictabert_large_he.md b/docs/_posts/ahmedlone127/2025-01-24-sent_dictabert_large_he.md
new file mode 100644
index 00000000000000..703a550c119e4a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_dictabert_large_he.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Hebrew sent_dictabert_large BertSentenceEmbeddings from dicta-il
+author: John Snow Labs
+name: sent_dictabert_large
+date: 2025-01-24
+tags: [he, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: he
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_dictabert_large` is a Hebrew model originally trained by dicta-il.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_dictabert_large_he_5.5.1_3.0_1737746221232.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_dictabert_large_he_5.5.1_3.0_1737746221232.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_dictabert_large","he") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_dictabert_large","he") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_dictabert_large|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|he|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/dicta-il/dictabert-large
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_dictabert_large_pipeline_he.md b/docs/_posts/ahmedlone127/2025-01-24-sent_dictabert_large_pipeline_he.md
new file mode 100644
index 00000000000000..5c44e19b34148c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_dictabert_large_pipeline_he.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Hebrew sent_dictabert_large_pipeline pipeline BertSentenceEmbeddings from dicta-il
+author: John Snow Labs
+name: sent_dictabert_large_pipeline
+date: 2025-01-24
+tags: [he, open_source, pipeline, onnx]
+task: Embeddings
+language: he
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_dictabert_large_pipeline` is a Hebrew model originally trained by dicta-il.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_dictabert_large_pipeline_he_5.5.1_3.0_1737746524332.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_dictabert_large_pipeline_he_5.5.1_3.0_1737746524332.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_dictabert_large_pipeline", lang = "he")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_dictabert_large_pipeline", lang = "he")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_dictabert_large_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|he|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/dicta-il/dictabert-large
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_dpr_cocomae_320_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_dpr_cocomae_320_en.md
new file mode 100644
index 00000000000000..0a2957afeb8336
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_dpr_cocomae_320_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_dpr_cocomae_320 BertSentenceEmbeddings from approach0
+author: John Snow Labs
+name: sent_dpr_cocomae_320
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_dpr_cocomae_320` is a English model originally trained by approach0.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_dpr_cocomae_320_en_5.5.1_3.0_1737748621825.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_dpr_cocomae_320_en_5.5.1_3.0_1737748621825.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_dpr_cocomae_320","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_dpr_cocomae_320","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_dpr_cocomae_320|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|409.9 MB|
+
+## References
+
+https://huggingface.co/approach0/dpr-cocomae-320
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_dpr_cocomae_320_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_dpr_cocomae_320_pipeline_en.md
new file mode 100644
index 00000000000000..2ff8f89d8c2beb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_dpr_cocomae_320_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_dpr_cocomae_320_pipeline pipeline BertSentenceEmbeddings from approach0
+author: John Snow Labs
+name: sent_dpr_cocomae_320_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_dpr_cocomae_320_pipeline` is a English model originally trained by approach0.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_dpr_cocomae_320_pipeline_en_5.5.1_3.0_1737748649783.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_dpr_cocomae_320_pipeline_en_5.5.1_3.0_1737748649783.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_dpr_cocomae_320_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_dpr_cocomae_320_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_dpr_cocomae_320_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.4 MB|
+
+## References
+
+https://huggingface.co/approach0/dpr-cocomae-320
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_dpr_cocomae_520_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_dpr_cocomae_520_en.md
new file mode 100644
index 00000000000000..7f6dacbf2be051
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_dpr_cocomae_520_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_dpr_cocomae_520 BertSentenceEmbeddings from approach0
+author: John Snow Labs
+name: sent_dpr_cocomae_520
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_dpr_cocomae_520` is a English model originally trained by approach0.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_dpr_cocomae_520_en_5.5.1_3.0_1737748571512.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_dpr_cocomae_520_en_5.5.1_3.0_1737748571512.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_dpr_cocomae_520","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_dpr_cocomae_520","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_dpr_cocomae_520|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|409.9 MB|
+
+## References
+
+https://huggingface.co/approach0/dpr-cocomae-520
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_dpr_cocomae_520_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_dpr_cocomae_520_pipeline_en.md
new file mode 100644
index 00000000000000..b1a328275e5962
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_dpr_cocomae_520_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_dpr_cocomae_520_pipeline pipeline BertSentenceEmbeddings from approach0
+author: John Snow Labs
+name: sent_dpr_cocomae_520_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_dpr_cocomae_520_pipeline` is a English model originally trained by approach0.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_dpr_cocomae_520_pipeline_en_5.5.1_3.0_1737748594013.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_dpr_cocomae_520_pipeline_en_5.5.1_3.0_1737748594013.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_dpr_cocomae_520_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_dpr_cocomae_520_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_dpr_cocomae_520_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.4 MB|
+
+## References
+
+https://huggingface.co/approach0/dpr-cocomae-520
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_dpr_cocondenser_320_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_dpr_cocondenser_320_en.md
new file mode 100644
index 00000000000000..02f0f171b40b4b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_dpr_cocondenser_320_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_dpr_cocondenser_320 BertSentenceEmbeddings from approach0
+author: John Snow Labs
+name: sent_dpr_cocondenser_320
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_dpr_cocondenser_320` is a English model originally trained by approach0.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_dpr_cocondenser_320_en_5.5.1_3.0_1737689613672.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_dpr_cocondenser_320_en_5.5.1_3.0_1737689613672.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_dpr_cocondenser_320","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_dpr_cocondenser_320","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_dpr_cocondenser_320|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|409.9 MB|
+
+## References
+
+https://huggingface.co/approach0/dpr-cocondenser-320
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_dpr_cocondenser_320_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_dpr_cocondenser_320_pipeline_en.md
new file mode 100644
index 00000000000000..b6e28027074618
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_dpr_cocondenser_320_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_dpr_cocondenser_320_pipeline pipeline BertSentenceEmbeddings from approach0
+author: John Snow Labs
+name: sent_dpr_cocondenser_320_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_dpr_cocondenser_320_pipeline` is a English model originally trained by approach0.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_dpr_cocondenser_320_pipeline_en_5.5.1_3.0_1737689636654.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_dpr_cocondenser_320_pipeline_en_5.5.1_3.0_1737689636654.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_dpr_cocondenser_320_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_dpr_cocondenser_320_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_dpr_cocondenser_320_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.4 MB|
+
+## References
+
+https://huggingface.co/approach0/dpr-cocondenser-320
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_dpr_cotbert_020_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_dpr_cotbert_020_en.md
new file mode 100644
index 00000000000000..c3da28c2197f8a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_dpr_cotbert_020_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_dpr_cotbert_020 BertSentenceEmbeddings from approach0
+author: John Snow Labs
+name: sent_dpr_cotbert_020
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_dpr_cotbert_020` is a English model originally trained by approach0.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_dpr_cotbert_020_en_5.5.1_3.0_1737748973124.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_dpr_cotbert_020_en_5.5.1_3.0_1737748973124.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_dpr_cotbert_020","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_dpr_cotbert_020","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_dpr_cotbert_020|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|409.8 MB|
+
+## References
+
+https://huggingface.co/approach0/dpr-cotbert-020
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_dpr_cotbert_020_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_dpr_cotbert_020_pipeline_en.md
new file mode 100644
index 00000000000000..a8b9507eebee19
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_dpr_cotbert_020_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_dpr_cotbert_020_pipeline pipeline BertSentenceEmbeddings from approach0
+author: John Snow Labs
+name: sent_dpr_cotbert_020_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_dpr_cotbert_020_pipeline` is a English model originally trained by approach0.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_dpr_cotbert_020_pipeline_en_5.5.1_3.0_1737748995047.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_dpr_cotbert_020_pipeline_en_5.5.1_3.0_1737748995047.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_dpr_cotbert_020_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_dpr_cotbert_020_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_dpr_cotbert_020_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.4 MB|
+
+## References
+
+https://huggingface.co/approach0/dpr-cotbert-020
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_dpr_vanilla_bert_320_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_dpr_vanilla_bert_320_en.md
new file mode 100644
index 00000000000000..ad31de3c6dbeb4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_dpr_vanilla_bert_320_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_dpr_vanilla_bert_320 BertSentenceEmbeddings from approach0
+author: John Snow Labs
+name: sent_dpr_vanilla_bert_320
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_dpr_vanilla_bert_320` is a English model originally trained by approach0.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_dpr_vanilla_bert_320_en_5.5.1_3.0_1737749320853.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_dpr_vanilla_bert_320_en_5.5.1_3.0_1737749320853.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_dpr_vanilla_bert_320","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_dpr_vanilla_bert_320","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_dpr_vanilla_bert_320|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|410.0 MB|
+
+## References
+
+https://huggingface.co/approach0/dpr-vanilla-bert-320
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_dpr_vanilla_bert_320_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_dpr_vanilla_bert_320_pipeline_en.md
new file mode 100644
index 00000000000000..3e1d84626e9691
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_dpr_vanilla_bert_320_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_dpr_vanilla_bert_320_pipeline pipeline BertSentenceEmbeddings from approach0
+author: John Snow Labs
+name: sent_dpr_vanilla_bert_320_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_dpr_vanilla_bert_320_pipeline` is a English model originally trained by approach0.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_dpr_vanilla_bert_320_pipeline_en_5.5.1_3.0_1737749344993.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_dpr_vanilla_bert_320_pipeline_en_5.5.1_3.0_1737749344993.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_dpr_vanilla_bert_320_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_dpr_vanilla_bert_320_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_dpr_vanilla_bert_320_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.6 MB|
+
+## References
+
+https://huggingface.co/approach0/dpr-vanilla-bert-320
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_dummy_model_bigbroo_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_dummy_model_bigbroo_en.md
new file mode 100644
index 00000000000000..33ff4049fc9812
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_dummy_model_bigbroo_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_dummy_model_bigbroo BertSentenceEmbeddings from BigBroo
+author: John Snow Labs
+name: sent_dummy_model_bigbroo
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_dummy_model_bigbroo` is a English model originally trained by BigBroo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_dummy_model_bigbroo_en_5.5.1_3.0_1737749525133.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_dummy_model_bigbroo_en_5.5.1_3.0_1737749525133.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_dummy_model_bigbroo","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_dummy_model_bigbroo","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_dummy_model_bigbroo|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/BigBroo/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_dummy_model_bigbroo_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_dummy_model_bigbroo_pipeline_en.md
new file mode 100644
index 00000000000000..b8e099cf145b4d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_dummy_model_bigbroo_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_dummy_model_bigbroo_pipeline pipeline BertSentenceEmbeddings from BigBroo
+author: John Snow Labs
+name: sent_dummy_model_bigbroo_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_dummy_model_bigbroo_pipeline` is a English model originally trained by BigBroo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_dummy_model_bigbroo_pipeline_en_5.5.1_3.0_1737749546696.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_dummy_model_bigbroo_pipeline_en_5.5.1_3.0_1737749546696.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_dummy_model_bigbroo_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_dummy_model_bigbroo_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_dummy_model_bigbroo_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|404.2 MB|
+
+## References
+
+https://huggingface.co/BigBroo/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_dummy_model_dimkkozhemyako_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_dummy_model_dimkkozhemyako_en.md
new file mode 100644
index 00000000000000..5b53be247ef022
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_dummy_model_dimkkozhemyako_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_dummy_model_dimkkozhemyako BertSentenceEmbeddings from DimkKozhemyako
+author: John Snow Labs
+name: sent_dummy_model_dimkkozhemyako
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_dummy_model_dimkkozhemyako` is a English model originally trained by DimkKozhemyako.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_dummy_model_dimkkozhemyako_en_5.5.1_3.0_1737745222550.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_dummy_model_dimkkozhemyako_en_5.5.1_3.0_1737745222550.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_dummy_model_dimkkozhemyako","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_dummy_model_dimkkozhemyako","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_dummy_model_dimkkozhemyako|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|108.6 MB|
+
+## References
+
+https://huggingface.co/DimkKozhemyako/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_dummy_model_dimkkozhemyako_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_dummy_model_dimkkozhemyako_pipeline_en.md
new file mode 100644
index 00000000000000..8ed27578cb7b9a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_dummy_model_dimkkozhemyako_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_dummy_model_dimkkozhemyako_pipeline pipeline BertSentenceEmbeddings from DimkKozhemyako
+author: John Snow Labs
+name: sent_dummy_model_dimkkozhemyako_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_dummy_model_dimkkozhemyako_pipeline` is a English model originally trained by DimkKozhemyako.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_dummy_model_dimkkozhemyako_pipeline_en_5.5.1_3.0_1737745239237.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_dummy_model_dimkkozhemyako_pipeline_en_5.5.1_3.0_1737745239237.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_dummy_model_dimkkozhemyako_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_dummy_model_dimkkozhemyako_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_dummy_model_dimkkozhemyako_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|109.2 MB|
+
+## References
+
+https://huggingface.co/DimkKozhemyako/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_fp_mbert_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_fp_mbert_en.md
new file mode 100644
index 00000000000000..29dfec098602e6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_fp_mbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_fp_mbert BertSentenceEmbeddings from Sadia2000
+author: John Snow Labs
+name: sent_fp_mbert
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_fp_mbert` is a English model originally trained by Sadia2000.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_fp_mbert_en_5.5.1_3.0_1737688431115.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_fp_mbert_en_5.5.1_3.0_1737688431115.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_fp_mbert","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_fp_mbert","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_fp_mbert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|664.1 MB|
+
+## References
+
+https://huggingface.co/Sadia2000/fp_mbert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_fp_mbert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_fp_mbert_pipeline_en.md
new file mode 100644
index 00000000000000..5b2e55fd255c5e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_fp_mbert_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_fp_mbert_pipeline pipeline BertSentenceEmbeddings from Sadia2000
+author: John Snow Labs
+name: sent_fp_mbert_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_fp_mbert_pipeline` is a English model originally trained by Sadia2000.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_fp_mbert_pipeline_en_5.5.1_3.0_1737688466045.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_fp_mbert_pipeline_en_5.5.1_3.0_1737688466045.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_fp_mbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_fp_mbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_fp_mbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|664.6 MB|
+
+## References
+
+https://huggingface.co/Sadia2000/fp_mbert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_gate_softmax_bert_base_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_gate_softmax_bert_base_en.md
new file mode 100644
index 00000000000000..a729fc1189ccea
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_gate_softmax_bert_base_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_gate_softmax_bert_base BertSentenceEmbeddings from magicslabnu
+author: John Snow Labs
+name: sent_gate_softmax_bert_base
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_gate_softmax_bert_base` is a English model originally trained by magicslabnu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_gate_softmax_bert_base_en_5.5.1_3.0_1737746056087.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_gate_softmax_bert_base_en_5.5.1_3.0_1737746056087.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_gate_softmax_bert_base","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_gate_softmax_bert_base","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_gate_softmax_bert_base|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|408.4 MB|
+
+## References
+
+https://huggingface.co/magicslabnu/gate_softmax_bert_base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_gate_softmax_bert_base_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_gate_softmax_bert_base_pipeline_en.md
new file mode 100644
index 00000000000000..f1f6cb76548f44
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_gate_softmax_bert_base_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_gate_softmax_bert_base_pipeline pipeline BertSentenceEmbeddings from magicslabnu
+author: John Snow Labs
+name: sent_gate_softmax_bert_base_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_gate_softmax_bert_base_pipeline` is a English model originally trained by magicslabnu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_gate_softmax_bert_base_pipeline_en_5.5.1_3.0_1737746077825.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_gate_softmax_bert_base_pipeline_en_5.5.1_3.0_1737746077825.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_gate_softmax_bert_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_gate_softmax_bert_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_gate_softmax_bert_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|408.9 MB|
+
+## References
+
+https://huggingface.co/magicslabnu/gate_softmax_bert_base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_gbert_large_autopart_de.md b/docs/_posts/ahmedlone127/2025-01-24-sent_gbert_large_autopart_de.md
new file mode 100644
index 00000000000000..1acbf00854733e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_gbert_large_autopart_de.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: German sent_gbert_large_autopart BertSentenceEmbeddings from luciore95
+author: John Snow Labs
+name: sent_gbert_large_autopart
+date: 2025-01-24
+tags: [de, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: de
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_gbert_large_autopart` is a German model originally trained by luciore95.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_gbert_large_autopart_de_5.5.1_3.0_1737688845795.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_gbert_large_autopart_de_5.5.1_3.0_1737688845795.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_gbert_large_autopart","de") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_gbert_large_autopart","de") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_gbert_large_autopart|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|de|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/luciore95/gbert-large-autopart
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_gbert_large_autopart_pipeline_de.md b/docs/_posts/ahmedlone127/2025-01-24-sent_gbert_large_autopart_pipeline_de.md
new file mode 100644
index 00000000000000..b7147616562d2b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_gbert_large_autopart_pipeline_de.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: German sent_gbert_large_autopart_pipeline pipeline BertSentenceEmbeddings from luciore95
+author: John Snow Labs
+name: sent_gbert_large_autopart_pipeline
+date: 2025-01-24
+tags: [de, open_source, pipeline, onnx]
+task: Embeddings
+language: de
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_gbert_large_autopart_pipeline` is a German model originally trained by luciore95.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_gbert_large_autopart_pipeline_de_5.5.1_3.0_1737688914571.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_gbert_large_autopart_pipeline_de_5.5.1_3.0_1737688914571.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_gbert_large_autopart_pipeline", lang = "de")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_gbert_large_autopart_pipeline", lang = "de")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_gbert_large_autopart_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|de|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/luciore95/gbert-large-autopart
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_indobert_nusa_id.md b/docs/_posts/ahmedlone127/2025-01-24-sent_indobert_nusa_id.md
new file mode 100644
index 00000000000000..3d953a67584de5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_indobert_nusa_id.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Indonesian sent_indobert_nusa BertSentenceEmbeddings from prosa-text
+author: John Snow Labs
+name: sent_indobert_nusa
+date: 2025-01-24
+tags: [id, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: id
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_indobert_nusa` is a Indonesian model originally trained by prosa-text.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_indobert_nusa_id_5.5.1_3.0_1737688832376.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_indobert_nusa_id_5.5.1_3.0_1737688832376.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_indobert_nusa","id") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_indobert_nusa","id") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_indobert_nusa|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|id|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/prosa-text/indobert-nusa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_indobert_nusa_pipeline_id.md b/docs/_posts/ahmedlone127/2025-01-24-sent_indobert_nusa_pipeline_id.md
new file mode 100644
index 00000000000000..bb84c73ffa4aa2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_indobert_nusa_pipeline_id.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Indonesian sent_indobert_nusa_pipeline pipeline BertSentenceEmbeddings from prosa-text
+author: John Snow Labs
+name: sent_indobert_nusa_pipeline
+date: 2025-01-24
+tags: [id, open_source, pipeline, onnx]
+task: Embeddings
+language: id
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_indobert_nusa_pipeline` is a Indonesian model originally trained by prosa-text.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_indobert_nusa_pipeline_id_5.5.1_3.0_1737688898533.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_indobert_nusa_pipeline_id_5.5.1_3.0_1737688898533.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_indobert_nusa_pipeline", lang = "id")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_indobert_nusa_pipeline", lang = "id")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_indobert_nusa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|id|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/prosa-text/indobert-nusa
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_japanese_bert_1_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_japanese_bert_1_en.md
new file mode 100644
index 00000000000000..c982aee1915bb2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_japanese_bert_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_japanese_bert_1 BertSentenceEmbeddings from neody
+author: John Snow Labs
+name: sent_japanese_bert_1
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_japanese_bert_1` is a English model originally trained by neody.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_japanese_bert_1_en_5.5.1_3.0_1737745313883.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_japanese_bert_1_en_5.5.1_3.0_1737745313883.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_japanese_bert_1","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_japanese_bert_1","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_japanese_bert_1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|253.4 MB|
+
+## References
+
+https://huggingface.co/neody/ja-bert-1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_japanese_bert_1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_japanese_bert_1_pipeline_en.md
new file mode 100644
index 00000000000000..8822f8f6b6db7c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_japanese_bert_1_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_japanese_bert_1_pipeline pipeline BertSentenceEmbeddings from neody
+author: John Snow Labs
+name: sent_japanese_bert_1_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_japanese_bert_1_pipeline` is a English model originally trained by neody.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_japanese_bert_1_pipeline_en_5.5.1_3.0_1737745327511.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_japanese_bert_1_pipeline_en_5.5.1_3.0_1737745327511.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_japanese_bert_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_japanese_bert_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_japanese_bert_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|254.0 MB|
+
+## References
+
+https://huggingface.co/neody/ja-bert-1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_kcbert_parent_09252023_mlm_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_kcbert_parent_09252023_mlm_en.md
new file mode 100644
index 00000000000000..0bdb33458ad9e6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_kcbert_parent_09252023_mlm_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_kcbert_parent_09252023_mlm BertSentenceEmbeddings from JuneKo
+author: John Snow Labs
+name: sent_kcbert_parent_09252023_mlm
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_kcbert_parent_09252023_mlm` is a English model originally trained by JuneKo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_kcbert_parent_09252023_mlm_en_5.5.1_3.0_1737748843698.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_kcbert_parent_09252023_mlm_en_5.5.1_3.0_1737748843698.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_kcbert_parent_09252023_mlm","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_kcbert_parent_09252023_mlm","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_kcbert_parent_09252023_mlm|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|406.2 MB|
+
+## References
+
+https://huggingface.co/JuneKo/kcBERT_parent_09252023_MLM
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_kcbert_parent_09252023_mlm_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_kcbert_parent_09252023_mlm_pipeline_en.md
new file mode 100644
index 00000000000000..27355eb1dc185e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_kcbert_parent_09252023_mlm_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_kcbert_parent_09252023_mlm_pipeline pipeline BertSentenceEmbeddings from JuneKo
+author: John Snow Labs
+name: sent_kcbert_parent_09252023_mlm_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_kcbert_parent_09252023_mlm_pipeline` is a English model originally trained by JuneKo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_kcbert_parent_09252023_mlm_pipeline_en_5.5.1_3.0_1737748865148.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_kcbert_parent_09252023_mlm_pipeline_en_5.5.1_3.0_1737748865148.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_kcbert_parent_09252023_mlm_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_kcbert_parent_09252023_mlm_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_kcbert_parent_09252023_mlm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/JuneKo/kcBERT_parent_09252023_MLM
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_kinyabert_large_finetuned_kintweets_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_kinyabert_large_finetuned_kintweets_en.md
new file mode 100644
index 00000000000000..a5606cb9919af5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_kinyabert_large_finetuned_kintweets_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_kinyabert_large_finetuned_kintweets BertSentenceEmbeddings from RogerB
+author: John Snow Labs
+name: sent_kinyabert_large_finetuned_kintweets
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_kinyabert_large_finetuned_kintweets` is a English model originally trained by RogerB.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_kinyabert_large_finetuned_kintweets_en_5.5.1_3.0_1737748400290.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_kinyabert_large_finetuned_kintweets_en_5.5.1_3.0_1737748400290.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_kinyabert_large_finetuned_kintweets","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_kinyabert_large_finetuned_kintweets","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_kinyabert_large_finetuned_kintweets|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|406.7 MB|
+
+## References
+
+https://huggingface.co/RogerB/KinyaBERT-large-finetuned-kintweets
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_kinyabert_large_finetuned_kintweets_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_kinyabert_large_finetuned_kintweets_pipeline_en.md
new file mode 100644
index 00000000000000..4a79271e676888
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_kinyabert_large_finetuned_kintweets_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_kinyabert_large_finetuned_kintweets_pipeline pipeline BertSentenceEmbeddings from RogerB
+author: John Snow Labs
+name: sent_kinyabert_large_finetuned_kintweets_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_kinyabert_large_finetuned_kintweets_pipeline` is a English model originally trained by RogerB.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_kinyabert_large_finetuned_kintweets_pipeline_en_5.5.1_3.0_1737748422723.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_kinyabert_large_finetuned_kintweets_pipeline_en_5.5.1_3.0_1737748422723.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_kinyabert_large_finetuned_kintweets_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_kinyabert_large_finetuned_kintweets_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_kinyabert_large_finetuned_kintweets_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.3 MB|
+
+## References
+
+https://huggingface.co/RogerB/KinyaBERT-large-finetuned-kintweets
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_kinyabert_small_finetuned_kintweets_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_kinyabert_small_finetuned_kintweets_en.md
new file mode 100644
index 00000000000000..b99832ddc6eadb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_kinyabert_small_finetuned_kintweets_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_kinyabert_small_finetuned_kintweets BertSentenceEmbeddings from RogerB
+author: John Snow Labs
+name: sent_kinyabert_small_finetuned_kintweets
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_kinyabert_small_finetuned_kintweets` is a English model originally trained by RogerB.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_kinyabert_small_finetuned_kintweets_en_5.5.1_3.0_1737749220975.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_kinyabert_small_finetuned_kintweets_en_5.5.1_3.0_1737749220975.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_kinyabert_small_finetuned_kintweets","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_kinyabert_small_finetuned_kintweets","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_kinyabert_small_finetuned_kintweets|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|247.4 MB|
+
+## References
+
+https://huggingface.co/RogerB/KinyaBERT-small-finetuned-kintweets
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_kinyabert_small_finetuned_kintweets_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_kinyabert_small_finetuned_kintweets_pipeline_en.md
new file mode 100644
index 00000000000000..c046be150d2a51
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_kinyabert_small_finetuned_kintweets_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_kinyabert_small_finetuned_kintweets_pipeline pipeline BertSentenceEmbeddings from RogerB
+author: John Snow Labs
+name: sent_kinyabert_small_finetuned_kintweets_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_kinyabert_small_finetuned_kintweets_pipeline` is a English model originally trained by RogerB.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_kinyabert_small_finetuned_kintweets_pipeline_en_5.5.1_3.0_1737749234466.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_kinyabert_small_finetuned_kintweets_pipeline_en_5.5.1_3.0_1737749234466.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_kinyabert_small_finetuned_kintweets_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_kinyabert_small_finetuned_kintweets_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_kinyabert_small_finetuned_kintweets_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|248.0 MB|
+
+## References
+
+https://huggingface.co/RogerB/KinyaBERT-small-finetuned-kintweets
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_labse_english_russian_finetuned_nlu_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_labse_english_russian_finetuned_nlu_en.md
new file mode 100644
index 00000000000000..19391f2b1507cb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_labse_english_russian_finetuned_nlu_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_labse_english_russian_finetuned_nlu BertSentenceEmbeddings from Maldopast
+author: John Snow Labs
+name: sent_labse_english_russian_finetuned_nlu
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_labse_english_russian_finetuned_nlu` is a English model originally trained by Maldopast.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_labse_english_russian_finetuned_nlu_en_5.5.1_3.0_1737684113070.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_labse_english_russian_finetuned_nlu_en_5.5.1_3.0_1737684113070.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_labse_english_russian_finetuned_nlu","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_labse_english_russian_finetuned_nlu","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_labse_english_russian_finetuned_nlu|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|480.3 MB|
+
+## References
+
+https://huggingface.co/Maldopast/LaBSE-en-ru-finetuned-nlu
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_labse_english_russian_finetuned_nlu_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_labse_english_russian_finetuned_nlu_pipeline_en.md
new file mode 100644
index 00000000000000..20e259dba2ca02
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_labse_english_russian_finetuned_nlu_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_labse_english_russian_finetuned_nlu_pipeline pipeline BertSentenceEmbeddings from Maldopast
+author: John Snow Labs
+name: sent_labse_english_russian_finetuned_nlu_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_labse_english_russian_finetuned_nlu_pipeline` is a English model originally trained by Maldopast.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_labse_english_russian_finetuned_nlu_pipeline_en_5.5.1_3.0_1737684138687.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_labse_english_russian_finetuned_nlu_pipeline_en_5.5.1_3.0_1737684138687.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_labse_english_russian_finetuned_nlu_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_labse_english_russian_finetuned_nlu_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_labse_english_russian_finetuned_nlu_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|480.9 MB|
+
+## References
+
+https://huggingface.co/Maldopast/LaBSE-en-ru-finetuned-nlu
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_lumbarradiologyreports_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_lumbarradiologyreports_en.md
new file mode 100644
index 00000000000000..50b5e733d93c19
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_lumbarradiologyreports_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_lumbarradiologyreports BertSentenceEmbeddings from YK96
+author: John Snow Labs
+name: sent_lumbarradiologyreports
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_lumbarradiologyreports` is a English model originally trained by YK96.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_lumbarradiologyreports_en_5.5.1_3.0_1737748489360.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_lumbarradiologyreports_en_5.5.1_3.0_1737748489360.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_lumbarradiologyreports","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_lumbarradiologyreports","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_lumbarradiologyreports|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/YK96/LumbarRadiologyReports
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_lumbarradiologyreports_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_lumbarradiologyreports_pipeline_en.md
new file mode 100644
index 00000000000000..11f414944e186d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_lumbarradiologyreports_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_lumbarradiologyreports_pipeline pipeline BertSentenceEmbeddings from YK96
+author: John Snow Labs
+name: sent_lumbarradiologyreports_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_lumbarradiologyreports_pipeline` is a English model originally trained by YK96.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_lumbarradiologyreports_pipeline_en_5.5.1_3.0_1737748510970.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_lumbarradiologyreports_pipeline_en_5.5.1_3.0_1737748510970.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_lumbarradiologyreports_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_lumbarradiologyreports_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_lumbarradiologyreports_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.7 MB|
+
+## References
+
+https://huggingface.co/YK96/LumbarRadiologyReports
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_malayalam_bert_scratch_ml.md b/docs/_posts/ahmedlone127/2025-01-24-sent_malayalam_bert_scratch_ml.md
new file mode 100644
index 00000000000000..edff2730dde897
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_malayalam_bert_scratch_ml.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Malayalam sent_malayalam_bert_scratch BertSentenceEmbeddings from l3cube-pune
+author: John Snow Labs
+name: sent_malayalam_bert_scratch
+date: 2025-01-24
+tags: [ml, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: ml
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_malayalam_bert_scratch` is a Malayalam model originally trained by l3cube-pune.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_malayalam_bert_scratch_ml_5.5.1_3.0_1737689214537.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_malayalam_bert_scratch_ml_5.5.1_3.0_1737689214537.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_malayalam_bert_scratch","ml") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_malayalam_bert_scratch","ml") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_malayalam_bert_scratch|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|ml|
+|Size:|470.7 MB|
+
+## References
+
+https://huggingface.co/l3cube-pune/malayalam-bert-scratch
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_malayalam_bert_scratch_pipeline_ml.md b/docs/_posts/ahmedlone127/2025-01-24-sent_malayalam_bert_scratch_pipeline_ml.md
new file mode 100644
index 00000000000000..d924ba9d85f5a3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_malayalam_bert_scratch_pipeline_ml.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Malayalam sent_malayalam_bert_scratch_pipeline pipeline BertSentenceEmbeddings from l3cube-pune
+author: John Snow Labs
+name: sent_malayalam_bert_scratch_pipeline
+date: 2025-01-24
+tags: [ml, open_source, pipeline, onnx]
+task: Embeddings
+language: ml
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_malayalam_bert_scratch_pipeline` is a Malayalam model originally trained by l3cube-pune.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_malayalam_bert_scratch_pipeline_ml_5.5.1_3.0_1737689242434.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_malayalam_bert_scratch_pipeline_ml_5.5.1_3.0_1737689242434.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_malayalam_bert_scratch_pipeline", lang = "ml")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_malayalam_bert_scratch_pipeline", lang = "ml")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_malayalam_bert_scratch_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ml|
+|Size:|471.3 MB|
+
+## References
+
+https://huggingface.co/l3cube-pune/malayalam-bert-scratch
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_mbert_finetuned_pytorch_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_mbert_finetuned_pytorch_en.md
new file mode 100644
index 00000000000000..4dda1dc24ccf9e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_mbert_finetuned_pytorch_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_mbert_finetuned_pytorch BertSentenceEmbeddings from fimu-docproc-research
+author: John Snow Labs
+name: sent_mbert_finetuned_pytorch
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_mbert_finetuned_pytorch` is a English model originally trained by fimu-docproc-research.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_mbert_finetuned_pytorch_en_5.5.1_3.0_1737745854882.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_mbert_finetuned_pytorch_en_5.5.1_3.0_1737745854882.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_mbert_finetuned_pytorch","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_mbert_finetuned_pytorch","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_mbert_finetuned_pytorch|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/fimu-docproc-research/mbert-finetuned-pytorch
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_mbert_finetuned_pytorch_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_mbert_finetuned_pytorch_pipeline_en.md
new file mode 100644
index 00000000000000..5d1146b591636b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_mbert_finetuned_pytorch_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_mbert_finetuned_pytorch_pipeline pipeline BertSentenceEmbeddings from fimu-docproc-research
+author: John Snow Labs
+name: sent_mbert_finetuned_pytorch_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_mbert_finetuned_pytorch_pipeline` is a English model originally trained by fimu-docproc-research.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_mbert_finetuned_pytorch_pipeline_en_5.5.1_3.0_1737745889661.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_mbert_finetuned_pytorch_pipeline_en_5.5.1_3.0_1737745889661.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_mbert_finetuned_pytorch_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_mbert_finetuned_pytorch_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_mbert_finetuned_pytorch_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|665.6 MB|
+
+## References
+
+https://huggingface.co/fimu-docproc-research/mbert-finetuned-pytorch
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_me_bert_mixed_mr.md b/docs/_posts/ahmedlone127/2025-01-24-sent_me_bert_mixed_mr.md
new file mode 100644
index 00000000000000..b11681d8dac56b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_me_bert_mixed_mr.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Marathi sent_me_bert_mixed BertSentenceEmbeddings from l3cube-pune
+author: John Snow Labs
+name: sent_me_bert_mixed
+date: 2025-01-24
+tags: [mr, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: mr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_me_bert_mixed` is a Marathi model originally trained by l3cube-pune.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_me_bert_mixed_mr_5.5.1_3.0_1737748639487.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_me_bert_mixed_mr_5.5.1_3.0_1737748639487.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_me_bert_mixed","mr") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_me_bert_mixed","mr") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_me_bert_mixed|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|mr|
+|Size:|665.0 MB|
+
+## References
+
+https://huggingface.co/l3cube-pune/me-bert-mixed
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_me_bert_mixed_pipeline_mr.md b/docs/_posts/ahmedlone127/2025-01-24-sent_me_bert_mixed_pipeline_mr.md
new file mode 100644
index 00000000000000..79daf3af7fab97
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_me_bert_mixed_pipeline_mr.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Marathi sent_me_bert_mixed_pipeline pipeline BertSentenceEmbeddings from l3cube-pune
+author: John Snow Labs
+name: sent_me_bert_mixed_pipeline
+date: 2025-01-24
+tags: [mr, open_source, pipeline, onnx]
+task: Embeddings
+language: mr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_me_bert_mixed_pipeline` is a Marathi model originally trained by l3cube-pune.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_me_bert_mixed_pipeline_mr_5.5.1_3.0_1737748679994.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_me_bert_mixed_pipeline_mr_5.5.1_3.0_1737748679994.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_me_bert_mixed_pipeline", lang = "mr")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_me_bert_mixed_pipeline", lang = "mr")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_me_bert_mixed_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|mr|
+|Size:|665.6 MB|
+
+## References
+
+https://huggingface.co/l3cube-pune/me-bert-mixed
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_meda_bert_indsigt_ai_da.md b/docs/_posts/ahmedlone127/2025-01-24-sent_meda_bert_indsigt_ai_da.md
new file mode 100644
index 00000000000000..decd389338d446
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_meda_bert_indsigt_ai_da.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Danish sent_meda_bert_indsigt_ai BertSentenceEmbeddings from indsigt-ai
+author: John Snow Labs
+name: sent_meda_bert_indsigt_ai
+date: 2025-01-24
+tags: [da, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: da
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_meda_bert_indsigt_ai` is a Danish model originally trained by indsigt-ai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_meda_bert_indsigt_ai_da_5.5.1_3.0_1737746047686.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_meda_bert_indsigt_ai_da_5.5.1_3.0_1737746047686.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_meda_bert_indsigt_ai","da") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_meda_bert_indsigt_ai","da") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_meda_bert_indsigt_ai|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|da|
+|Size:|412.3 MB|
+
+## References
+
+https://huggingface.co/indsigt-ai/MeDa-BERT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_meda_bert_indsigt_ai_pipeline_da.md b/docs/_posts/ahmedlone127/2025-01-24-sent_meda_bert_indsigt_ai_pipeline_da.md
new file mode 100644
index 00000000000000..170dacc3c7b002
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_meda_bert_indsigt_ai_pipeline_da.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Danish sent_meda_bert_indsigt_ai_pipeline pipeline BertSentenceEmbeddings from indsigt-ai
+author: John Snow Labs
+name: sent_meda_bert_indsigt_ai_pipeline
+date: 2025-01-24
+tags: [da, open_source, pipeline, onnx]
+task: Embeddings
+language: da
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_meda_bert_indsigt_ai_pipeline` is a Danish model originally trained by indsigt-ai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_meda_bert_indsigt_ai_pipeline_da_5.5.1_3.0_1737746069528.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_meda_bert_indsigt_ai_pipeline_da_5.5.1_3.0_1737746069528.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_meda_bert_indsigt_ai_pipeline", lang = "da")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_meda_bert_indsigt_ai_pipeline", lang = "da")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_meda_bert_indsigt_ai_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|da|
+|Size:|412.8 MB|
+
+## References
+
+https://huggingface.co/indsigt-ai/MeDa-BERT
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_medium_mlm_imdb_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_medium_mlm_imdb_en.md
new file mode 100644
index 00000000000000..36b05512cd8a12
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_medium_mlm_imdb_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_medium_mlm_imdb BertSentenceEmbeddings from muhtasham
+author: John Snow Labs
+name: sent_medium_mlm_imdb
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_medium_mlm_imdb` is a English model originally trained by muhtasham.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_medium_mlm_imdb_en_5.5.1_3.0_1737748389795.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_medium_mlm_imdb_en_5.5.1_3.0_1737748389795.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_medium_mlm_imdb","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_medium_mlm_imdb","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_medium_mlm_imdb|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|154.2 MB|
+
+## References
+
+https://huggingface.co/muhtasham/medium-mlm-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_medium_mlm_imdb_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_medium_mlm_imdb_pipeline_en.md
new file mode 100644
index 00000000000000..1990f18416408b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_medium_mlm_imdb_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_medium_mlm_imdb_pipeline pipeline BertSentenceEmbeddings from muhtasham
+author: John Snow Labs
+name: sent_medium_mlm_imdb_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_medium_mlm_imdb_pipeline` is a English model originally trained by muhtasham.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_medium_mlm_imdb_pipeline_en_5.5.1_3.0_1737748397589.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_medium_mlm_imdb_pipeline_en_5.5.1_3.0_1737748397589.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_medium_mlm_imdb_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_medium_mlm_imdb_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_medium_mlm_imdb_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|154.8 MB|
+
+## References
+
+https://huggingface.co/muhtasham/medium-mlm-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_mergedistill_maltese_128_norwegian_distill_v2_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_mergedistill_maltese_128_norwegian_distill_v2_en.md
new file mode 100644
index 00000000000000..5abecf566a0a53
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_mergedistill_maltese_128_norwegian_distill_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_mergedistill_maltese_128_norwegian_distill_v2 BertSentenceEmbeddings from amitness
+author: John Snow Labs
+name: sent_mergedistill_maltese_128_norwegian_distill_v2
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_mergedistill_maltese_128_norwegian_distill_v2` is a English model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_mergedistill_maltese_128_norwegian_distill_v2_en_5.5.1_3.0_1737749488305.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_mergedistill_maltese_128_norwegian_distill_v2_en_5.5.1_3.0_1737749488305.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_mergedistill_maltese_128_norwegian_distill_v2","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_mergedistill_maltese_128_norwegian_distill_v2","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_mergedistill_maltese_128_norwegian_distill_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|470.4 MB|
+
+## References
+
+https://huggingface.co/amitness/mergedistill-mt-128-no-distill-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_mergedistill_maltese_128_norwegian_distill_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_mergedistill_maltese_128_norwegian_distill_v2_pipeline_en.md
new file mode 100644
index 00000000000000..9e6f65d430d191
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_mergedistill_maltese_128_norwegian_distill_v2_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_mergedistill_maltese_128_norwegian_distill_v2_pipeline pipeline BertSentenceEmbeddings from amitness
+author: John Snow Labs
+name: sent_mergedistill_maltese_128_norwegian_distill_v2_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_mergedistill_maltese_128_norwegian_distill_v2_pipeline` is a English model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_mergedistill_maltese_128_norwegian_distill_v2_pipeline_en_5.5.1_3.0_1737749514478.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_mergedistill_maltese_128_norwegian_distill_v2_pipeline_en_5.5.1_3.0_1737749514478.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_mergedistill_maltese_128_norwegian_distill_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_mergedistill_maltese_128_norwegian_distill_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_mergedistill_maltese_128_norwegian_distill_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|471.0 MB|
+
+## References
+
+https://huggingface.co/amitness/mergedistill-mt-128-no-distill-v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_mergedistill_maltese_english_128_v2_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_mergedistill_maltese_english_128_v2_en.md
new file mode 100644
index 00000000000000..1302c388585361
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_mergedistill_maltese_english_128_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_mergedistill_maltese_english_128_v2 BertSentenceEmbeddings from amitness
+author: John Snow Labs
+name: sent_mergedistill_maltese_english_128_v2
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_mergedistill_maltese_english_128_v2` is a English model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_mergedistill_maltese_english_128_v2_en_5.5.1_3.0_1737749316971.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_mergedistill_maltese_english_128_v2_en_5.5.1_3.0_1737749316971.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_mergedistill_maltese_english_128_v2","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_mergedistill_maltese_english_128_v2","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_mergedistill_maltese_english_128_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|532.6 MB|
+
+## References
+
+https://huggingface.co/amitness/mergedistill-mt-en-128-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_mergedistill_maltese_english_128_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_mergedistill_maltese_english_128_v2_pipeline_en.md
new file mode 100644
index 00000000000000..bb310fe7071855
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_mergedistill_maltese_english_128_v2_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_mergedistill_maltese_english_128_v2_pipeline pipeline BertSentenceEmbeddings from amitness
+author: John Snow Labs
+name: sent_mergedistill_maltese_english_128_v2_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_mergedistill_maltese_english_128_v2_pipeline` is a English model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_mergedistill_maltese_english_128_v2_pipeline_en_5.5.1_3.0_1737749347013.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_mergedistill_maltese_english_128_v2_pipeline_en_5.5.1_3.0_1737749347013.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_mergedistill_maltese_english_128_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_mergedistill_maltese_english_128_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_mergedistill_maltese_english_128_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|533.1 MB|
+
+## References
+
+https://huggingface.co/amitness/mergedistill-mt-en-128-v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_mergedistill_maltese_english_512_v2_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_mergedistill_maltese_english_512_v2_en.md
new file mode 100644
index 00000000000000..aebcd8dd5e6078
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_mergedistill_maltese_english_512_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_mergedistill_maltese_english_512_v2 BertSentenceEmbeddings from amitness
+author: John Snow Labs
+name: sent_mergedistill_maltese_english_512_v2
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_mergedistill_maltese_english_512_v2` is a English model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_mergedistill_maltese_english_512_v2_en_5.5.1_3.0_1737748708589.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_mergedistill_maltese_english_512_v2_en_5.5.1_3.0_1737748708589.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_mergedistill_maltese_english_512_v2","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_mergedistill_maltese_english_512_v2","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_mergedistill_maltese_english_512_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|532.5 MB|
+
+## References
+
+https://huggingface.co/amitness/mergedistill-mt-en-512-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_mergedistill_maltese_english_512_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_mergedistill_maltese_english_512_v2_pipeline_en.md
new file mode 100644
index 00000000000000..eefdfa0da14330
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_mergedistill_maltese_english_512_v2_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_mergedistill_maltese_english_512_v2_pipeline pipeline BertSentenceEmbeddings from amitness
+author: John Snow Labs
+name: sent_mergedistill_maltese_english_512_v2_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_mergedistill_maltese_english_512_v2_pipeline` is a English model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_mergedistill_maltese_english_512_v2_pipeline_en_5.5.1_3.0_1737748736255.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_mergedistill_maltese_english_512_v2_pipeline_en_5.5.1_3.0_1737748736255.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_mergedistill_maltese_english_512_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_mergedistill_maltese_english_512_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_mergedistill_maltese_english_512_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|533.1 MB|
+
+## References
+
+https://huggingface.co/amitness/mergedistill-mt-en-512-v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_mergedistill_maltese_italian_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_mergedistill_maltese_italian_en.md
new file mode 100644
index 00000000000000..857359c289689b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_mergedistill_maltese_italian_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_mergedistill_maltese_italian BertSentenceEmbeddings from amitness
+author: John Snow Labs
+name: sent_mergedistill_maltese_italian
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_mergedistill_maltese_italian` is a English model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_mergedistill_maltese_italian_en_5.5.1_3.0_1737749112171.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_mergedistill_maltese_italian_en_5.5.1_3.0_1737749112171.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_mergedistill_maltese_italian","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_mergedistill_maltese_italian","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_mergedistill_maltese_italian|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|538.8 MB|
+
+## References
+
+https://huggingface.co/amitness/mergedistill-mt-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_mergedistill_maltese_italian_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_mergedistill_maltese_italian_pipeline_en.md
new file mode 100644
index 00000000000000..6eba86545eaef4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_mergedistill_maltese_italian_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_mergedistill_maltese_italian_pipeline pipeline BertSentenceEmbeddings from amitness
+author: John Snow Labs
+name: sent_mergedistill_maltese_italian_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_mergedistill_maltese_italian_pipeline` is a English model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_mergedistill_maltese_italian_pipeline_en_5.5.1_3.0_1737749140492.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_mergedistill_maltese_italian_pipeline_en_5.5.1_3.0_1737749140492.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_mergedistill_maltese_italian_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_mergedistill_maltese_italian_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_mergedistill_maltese_italian_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|539.3 MB|
+
+## References
+
+https://huggingface.co/amitness/mergedistill-mt-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_mlm_20230406_002_5_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_mlm_20230406_002_5_en.md
new file mode 100644
index 00000000000000..c05aa5a7b11708
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_mlm_20230406_002_5_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_mlm_20230406_002_5 BertSentenceEmbeddings from intanm
+author: John Snow Labs
+name: sent_mlm_20230406_002_5
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_mlm_20230406_002_5` is a English model originally trained by intanm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_mlm_20230406_002_5_en_5.5.1_3.0_1737748937697.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_mlm_20230406_002_5_en_5.5.1_3.0_1737748937697.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_mlm_20230406_002_5","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_mlm_20230406_002_5","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_mlm_20230406_002_5|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|464.3 MB|
+
+## References
+
+https://huggingface.co/intanm/mlm-20230406-002-5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_mlm_20230406_002_5_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_mlm_20230406_002_5_pipeline_en.md
new file mode 100644
index 00000000000000..12466febf75547
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_mlm_20230406_002_5_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_mlm_20230406_002_5_pipeline pipeline BertSentenceEmbeddings from intanm
+author: John Snow Labs
+name: sent_mlm_20230406_002_5_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_mlm_20230406_002_5_pipeline` is a English model originally trained by intanm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_mlm_20230406_002_5_pipeline_en_5.5.1_3.0_1737748963046.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_mlm_20230406_002_5_pipeline_en_5.5.1_3.0_1737748963046.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_mlm_20230406_002_5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_mlm_20230406_002_5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_mlm_20230406_002_5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|464.8 MB|
+
+## References
+
+https://huggingface.co/intanm/mlm-20230406-002-5
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_model_ak729_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_model_ak729_en.md
new file mode 100644
index 00000000000000..6513b96430f134
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_model_ak729_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_model_ak729 BertSentenceEmbeddings from Ak729
+author: John Snow Labs
+name: sent_model_ak729
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_model_ak729` is a English model originally trained by Ak729.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_model_ak729_en_5.5.1_3.0_1737745343526.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_model_ak729_en_5.5.1_3.0_1737745343526.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_model_ak729","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_model_ak729","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_model_ak729|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/Ak729/Model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_model_ak729_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_model_ak729_pipeline_en.md
new file mode 100644
index 00000000000000..83be38a537f635
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_model_ak729_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_model_ak729_pipeline pipeline BertSentenceEmbeddings from Ak729
+author: John Snow Labs
+name: sent_model_ak729_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_model_ak729_pipeline` is a English model originally trained by Ak729.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_model_ak729_pipeline_en_5.5.1_3.0_1737745365278.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_model_ak729_pipeline_en_5.5.1_3.0_1737745365278.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_model_ak729_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_model_ak729_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_model_ak729_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.7 MB|
+
+## References
+
+https://huggingface.co/Ak729/Model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_ottoman_berturk_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_ottoman_berturk_en.md
new file mode 100644
index 00000000000000..dbfac11c9f917d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_ottoman_berturk_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_ottoman_berturk BertSentenceEmbeddings from onurkeles
+author: John Snow Labs
+name: sent_ottoman_berturk
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_ottoman_berturk` is a English model originally trained by onurkeles.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_ottoman_berturk_en_5.5.1_3.0_1737689007546.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_ottoman_berturk_en_5.5.1_3.0_1737689007546.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_ottoman_berturk","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_ottoman_berturk","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_ottoman_berturk|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|412.3 MB|
+
+## References
+
+https://huggingface.co/onurkeles/ottoman_berturk
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_ottoman_berturk_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_ottoman_berturk_pipeline_en.md
new file mode 100644
index 00000000000000..eba7488a28867f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_ottoman_berturk_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_ottoman_berturk_pipeline pipeline BertSentenceEmbeddings from onurkeles
+author: John Snow Labs
+name: sent_ottoman_berturk_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_ottoman_berturk_pipeline` is a English model originally trained by onurkeles.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_ottoman_berturk_pipeline_en_5.5.1_3.0_1737689030003.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_ottoman_berturk_pipeline_en_5.5.1_3.0_1737689030003.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_ottoman_berturk_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_ottoman_berturk_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_ottoman_berturk_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|412.8 MB|
+
+## References
+
+https://huggingface.co/onurkeles/ottoman_berturk
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_pre_train_mbertv2_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_pre_train_mbertv2_en.md
new file mode 100644
index 00000000000000..5474047f63a01b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_pre_train_mbertv2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_pre_train_mbertv2 BertSentenceEmbeddings from morten-j
+author: John Snow Labs
+name: sent_pre_train_mbertv2
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_pre_train_mbertv2` is a English model originally trained by morten-j.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_pre_train_mbertv2_en_5.5.1_3.0_1737745512200.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_pre_train_mbertv2_en_5.5.1_3.0_1737745512200.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_pre_train_mbertv2","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_pre_train_mbertv2","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_pre_train_mbertv2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|658.6 MB|
+
+## References
+
+https://huggingface.co/morten-j/pre-train_mBERTv2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_pre_train_mbertv2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_pre_train_mbertv2_pipeline_en.md
new file mode 100644
index 00000000000000..09a2639713692d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_pre_train_mbertv2_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_pre_train_mbertv2_pipeline pipeline BertSentenceEmbeddings from morten-j
+author: John Snow Labs
+name: sent_pre_train_mbertv2_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_pre_train_mbertv2_pipeline` is a English model originally trained by morten-j.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_pre_train_mbertv2_pipeline_en_5.5.1_3.0_1737745549156.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_pre_train_mbertv2_pipeline_en_5.5.1_3.0_1737745549156.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_pre_train_mbertv2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_pre_train_mbertv2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_pre_train_mbertv2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|659.1 MB|
+
+## References
+
+https://huggingface.co/morten-j/pre-train_mBERTv2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_rubert_base_sakha_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_rubert_base_sakha_en.md
new file mode 100644
index 00000000000000..2579f811c1a078
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_rubert_base_sakha_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_rubert_base_sakha BertSentenceEmbeddings from bamaxi
+author: John Snow Labs
+name: sent_rubert_base_sakha
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_rubert_base_sakha` is a English model originally trained by bamaxi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_rubert_base_sakha_en_5.5.1_3.0_1737689646192.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_rubert_base_sakha_en_5.5.1_3.0_1737689646192.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_rubert_base_sakha","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_rubert_base_sakha","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_rubert_base_sakha|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|746.5 MB|
+
+## References
+
+https://huggingface.co/bamaxi/ruBert-base-sakha
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_rubert_base_sakha_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_rubert_base_sakha_pipeline_en.md
new file mode 100644
index 00000000000000..b276ed86d08f03
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_rubert_base_sakha_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_rubert_base_sakha_pipeline pipeline BertSentenceEmbeddings from bamaxi
+author: John Snow Labs
+name: sent_rubert_base_sakha_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_rubert_base_sakha_pipeline` is a English model originally trained by bamaxi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_rubert_base_sakha_pipeline_en_5.5.1_3.0_1737689686410.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_rubert_base_sakha_pipeline_en_5.5.1_3.0_1737689686410.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_rubert_base_sakha_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_rubert_base_sakha_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_rubert_base_sakha_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|747.0 MB|
+
+## References
+
+https://huggingface.co/bamaxi/ruBert-base-sakha
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_san_bert_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_san_bert_en.md
new file mode 100644
index 00000000000000..468c54cb3a48c0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_san_bert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_san_bert BertSentenceEmbeddings from sampathlonka
+author: John Snow Labs
+name: sent_san_bert
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_san_bert` is a English model originally trained by sampathlonka.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_san_bert_en_5.5.1_3.0_1737749462708.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_san_bert_en_5.5.1_3.0_1737749462708.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_san_bert","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_san_bert","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_san_bert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.9 MB|
+
+## References
+
+https://huggingface.co/sampathlonka/San-BERT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_san_bert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_san_bert_pipeline_en.md
new file mode 100644
index 00000000000000..52b9e3bf9e4fca
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_san_bert_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_san_bert_pipeline pipeline BertSentenceEmbeddings from sampathlonka
+author: John Snow Labs
+name: sent_san_bert_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_san_bert_pipeline` is a English model originally trained by sampathlonka.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_san_bert_pipeline_en_5.5.1_3.0_1737749484703.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_san_bert_pipeline_en_5.5.1_3.0_1737749484703.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_san_bert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_san_bert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_san_bert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|408.5 MB|
+
+## References
+
+https://huggingface.co/sampathlonka/San-BERT
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_smaller_albert_base_geo_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_smaller_albert_base_geo_en.md
new file mode 100644
index 00000000000000..c5f31403a875b4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_smaller_albert_base_geo_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_smaller_albert_base_geo BertSentenceEmbeddings from ZurabDz
+author: John Snow Labs
+name: sent_smaller_albert_base_geo
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_smaller_albert_base_geo` is a English model originally trained by ZurabDz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_smaller_albert_base_geo_en_5.5.1_3.0_1737689620404.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_smaller_albert_base_geo_en_5.5.1_3.0_1737689620404.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_smaller_albert_base_geo","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_smaller_albert_base_geo","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_smaller_albert_base_geo|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|41.6 MB|
+
+## References
+
+https://huggingface.co/ZurabDz/smaller_albert_base_geo
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_smaller_albert_base_geo_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_smaller_albert_base_geo_pipeline_en.md
new file mode 100644
index 00000000000000..33691c0288ceb2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_smaller_albert_base_geo_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_smaller_albert_base_geo_pipeline pipeline BertSentenceEmbeddings from ZurabDz
+author: John Snow Labs
+name: sent_smaller_albert_base_geo_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_smaller_albert_base_geo_pipeline` is a English model originally trained by ZurabDz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_smaller_albert_base_geo_pipeline_en_5.5.1_3.0_1737689623801.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_smaller_albert_base_geo_pipeline_en_5.5.1_3.0_1737689623801.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_smaller_albert_base_geo_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_smaller_albert_base_geo_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_smaller_albert_base_geo_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|42.1 MB|
+
+## References
+
+https://huggingface.co/ZurabDz/smaller_albert_base_geo
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_splade_nomath_bertnsp_220_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_splade_nomath_bertnsp_220_en.md
new file mode 100644
index 00000000000000..279982bc65caf9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_splade_nomath_bertnsp_220_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_splade_nomath_bertnsp_220 BertSentenceEmbeddings from approach0
+author: John Snow Labs
+name: sent_splade_nomath_bertnsp_220
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_splade_nomath_bertnsp_220` is a English model originally trained by approach0.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_splade_nomath_bertnsp_220_en_5.5.1_3.0_1737688502640.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_splade_nomath_bertnsp_220_en_5.5.1_3.0_1737688502640.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_splade_nomath_bertnsp_220","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_splade_nomath_bertnsp_220","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_splade_nomath_bertnsp_220|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|409.8 MB|
+
+## References
+
+https://huggingface.co/approach0/splade_nomath-bertnsp-220
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_splade_nomath_bertnsp_220_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_splade_nomath_bertnsp_220_pipeline_en.md
new file mode 100644
index 00000000000000..a546c9a6657b21
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_splade_nomath_bertnsp_220_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_splade_nomath_bertnsp_220_pipeline pipeline BertSentenceEmbeddings from approach0
+author: John Snow Labs
+name: sent_splade_nomath_bertnsp_220_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_splade_nomath_bertnsp_220_pipeline` is a English model originally trained by approach0.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_splade_nomath_bertnsp_220_pipeline_en_5.5.1_3.0_1737688524571.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_splade_nomath_bertnsp_220_pipeline_en_5.5.1_3.0_1737688524571.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_splade_nomath_bertnsp_220_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_splade_nomath_bertnsp_220_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_splade_nomath_bertnsp_220_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.4 MB|
+
+## References
+
+https://huggingface.co/approach0/splade_nomath-bertnsp-220
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_swahili_v1_pipeline_sw.md b/docs/_posts/ahmedlone127/2025-01-24-sent_swahili_v1_pipeline_sw.md
new file mode 100644
index 00000000000000..f3a5ed689e5833
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_swahili_v1_pipeline_sw.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Swahili (macrolanguage) sent_swahili_v1_pipeline pipeline BertSentenceEmbeddings from eolang
+author: John Snow Labs
+name: sent_swahili_v1_pipeline
+date: 2025-01-24
+tags: [sw, open_source, pipeline, onnx]
+task: Embeddings
+language: sw
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_swahili_v1_pipeline` is a Swahili (macrolanguage) model originally trained by eolang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_swahili_v1_pipeline_sw_5.5.1_3.0_1737689426981.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_swahili_v1_pipeline_sw_5.5.1_3.0_1737689426981.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_swahili_v1_pipeline", lang = "sw")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_swahili_v1_pipeline", lang = "sw")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_swahili_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|sw|
+|Size:|408.5 MB|
+
+## References
+
+https://huggingface.co/eolang/SW-v1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_swahili_v1_sw.md b/docs/_posts/ahmedlone127/2025-01-24-sent_swahili_v1_sw.md
new file mode 100644
index 00000000000000..756e5128bd232b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_swahili_v1_sw.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Swahili (macrolanguage) sent_swahili_v1 BertSentenceEmbeddings from eolang
+author: John Snow Labs
+name: sent_swahili_v1
+date: 2025-01-24
+tags: [sw, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: sw
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_swahili_v1` is a Swahili (macrolanguage) model originally trained by eolang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_swahili_v1_sw_5.5.1_3.0_1737689404994.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_swahili_v1_sw_5.5.1_3.0_1737689404994.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_swahili_v1","sw") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_swahili_v1","sw") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_swahili_v1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|sw|
+|Size:|408.0 MB|
+
+## References
+
+https://huggingface.co/eolang/SW-v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_telugu_bert_scratch_pipeline_te.md b/docs/_posts/ahmedlone127/2025-01-24-sent_telugu_bert_scratch_pipeline_te.md
new file mode 100644
index 00000000000000..2bd46b1bbec0e0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_telugu_bert_scratch_pipeline_te.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Telugu sent_telugu_bert_scratch_pipeline pipeline BertSentenceEmbeddings from l3cube-pune
+author: John Snow Labs
+name: sent_telugu_bert_scratch_pipeline
+date: 2025-01-24
+tags: [te, open_source, pipeline, onnx]
+task: Embeddings
+language: te
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_telugu_bert_scratch_pipeline` is a Telugu model originally trained by l3cube-pune.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_telugu_bert_scratch_pipeline_te_5.5.1_3.0_1737684343321.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_telugu_bert_scratch_pipeline_te_5.5.1_3.0_1737684343321.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_telugu_bert_scratch_pipeline", lang = "te")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_telugu_bert_scratch_pipeline", lang = "te")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_telugu_bert_scratch_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|te|
+|Size:|471.0 MB|
+
+## References
+
+https://huggingface.co/l3cube-pune/telugu-bert-scratch
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_telugu_bert_scratch_te.md b/docs/_posts/ahmedlone127/2025-01-24-sent_telugu_bert_scratch_te.md
new file mode 100644
index 00000000000000..5d20a2124e17d6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_telugu_bert_scratch_te.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Telugu sent_telugu_bert_scratch BertSentenceEmbeddings from l3cube-pune
+author: John Snow Labs
+name: sent_telugu_bert_scratch
+date: 2025-01-24
+tags: [te, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: te
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_telugu_bert_scratch` is a Telugu model originally trained by l3cube-pune.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_telugu_bert_scratch_te_5.5.1_3.0_1737684318459.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_telugu_bert_scratch_te_5.5.1_3.0_1737684318459.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_telugu_bert_scratch","te") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_telugu_bert_scratch","te") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_telugu_bert_scratch|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|te|
+|Size:|470.5 MB|
+
+## References
+
+https://huggingface.co/l3cube-pune/telugu-bert-scratch
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_tiny_mlm_glue_rte_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_tiny_mlm_glue_rte_en.md
new file mode 100644
index 00000000000000..a243dedd793339
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_tiny_mlm_glue_rte_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_tiny_mlm_glue_rte BertSentenceEmbeddings from muhtasham
+author: John Snow Labs
+name: sent_tiny_mlm_glue_rte
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_tiny_mlm_glue_rte` is a English model originally trained by muhtasham.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_tiny_mlm_glue_rte_en_5.5.1_3.0_1737689392100.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_tiny_mlm_glue_rte_en_5.5.1_3.0_1737689392100.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_tiny_mlm_glue_rte","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_tiny_mlm_glue_rte","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_tiny_mlm_glue_rte|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|16.7 MB|
+
+## References
+
+https://huggingface.co/muhtasham/tiny-mlm-glue-rte
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_tiny_mlm_glue_rte_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_tiny_mlm_glue_rte_pipeline_en.md
new file mode 100644
index 00000000000000..ff772ca603cef2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_tiny_mlm_glue_rte_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_tiny_mlm_glue_rte_pipeline pipeline BertSentenceEmbeddings from muhtasham
+author: John Snow Labs
+name: sent_tiny_mlm_glue_rte_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_tiny_mlm_glue_rte_pipeline` is a English model originally trained by muhtasham.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_tiny_mlm_glue_rte_pipeline_en_5.5.1_3.0_1737689393180.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_tiny_mlm_glue_rte_pipeline_en_5.5.1_3.0_1737689393180.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_tiny_mlm_glue_rte_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_tiny_mlm_glue_rte_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_tiny_mlm_glue_rte_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|17.2 MB|
+
+## References
+
+https://huggingface.co/muhtasham/tiny-mlm-glue-rte
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_vizwiz_bert_base_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_vizwiz_bert_base_en.md
new file mode 100644
index 00000000000000..678c36b6f87a45
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_vizwiz_bert_base_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_vizwiz_bert_base BertSentenceEmbeddings from nanom
+author: John Snow Labs
+name: sent_vizwiz_bert_base
+date: 2025-01-24
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_vizwiz_bert_base` is a English model originally trained by nanom.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_vizwiz_bert_base_en_5.5.1_3.0_1737748992445.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_vizwiz_bert_base_en_5.5.1_3.0_1737748992445.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_vizwiz_bert_base","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_vizwiz_bert_base","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_vizwiz_bert_base|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/nanom/vizwiz-bert-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-sent_vizwiz_bert_base_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-sent_vizwiz_bert_base_pipeline_en.md
new file mode 100644
index 00000000000000..4950141517c77c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-sent_vizwiz_bert_base_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_vizwiz_bert_base_pipeline pipeline BertSentenceEmbeddings from nanom
+author: John Snow Labs
+name: sent_vizwiz_bert_base_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_vizwiz_bert_base_pipeline` is a English model originally trained by nanom.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_vizwiz_bert_base_pipeline_en_5.5.1_3.0_1737749024391.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_vizwiz_bert_base_pipeline_en_5.5.1_3.0_1737749024391.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_vizwiz_bert_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_vizwiz_bert_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_vizwiz_bert_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.7 MB|
+
+## References
+
+https://huggingface.co/nanom/vizwiz-bert-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-skincancerclassifier_en.md b/docs/_posts/ahmedlone127/2025-01-24-skincancerclassifier_en.md
new file mode 100644
index 00000000000000..7b530e3a03d3f3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-skincancerclassifier_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English skincancerclassifier SwinForImageClassification from NeuronZero
+author: John Snow Labs
+name: skincancerclassifier
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`skincancerclassifier` is a English model originally trained by NeuronZero.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/skincancerclassifier_en_5.5.1_3.0_1737762429023.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/skincancerclassifier_en_5.5.1_3.0_1737762429023.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""skincancerclassifier","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("skincancerclassifier","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|skincancerclassifier|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|649.8 MB|
+
+## References
+
+https://huggingface.co/NeuronZero/SkinCancerClassifier
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-skincancerclassifier_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-skincancerclassifier_pipeline_en.md
new file mode 100644
index 00000000000000..a0959f5a4c65b3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-skincancerclassifier_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English skincancerclassifier_pipeline pipeline SwinForImageClassification from NeuronZero
+author: John Snow Labs
+name: skincancerclassifier_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`skincancerclassifier_pipeline` is a English model originally trained by NeuronZero.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/skincancerclassifier_pipeline_en_5.5.1_3.0_1737762466940.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/skincancerclassifier_pipeline_en_5.5.1_3.0_1737762466940.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("skincancerclassifier_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("skincancerclassifier_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|skincancerclassifier_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|649.8 MB|
+
+## References
+
+https://huggingface.co/NeuronZero/SkinCancerClassifier
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-spanbert_squad_finetuned_qa_tf32_en.md b/docs/_posts/ahmedlone127/2025-01-24-spanbert_squad_finetuned_qa_tf32_en.md
new file mode 100644
index 00000000000000..9d6cbe7df8d00d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-spanbert_squad_finetuned_qa_tf32_en.md
@@ -0,0 +1,92 @@
+---
+layout: model
+title: English spanbert_squad_finetuned_qa_tf32 BertForQuestionAnswering from botcon
+author: John Snow Labs
+name: spanbert_squad_finetuned_qa_tf32
+date: 2025-01-24
+tags: [bert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`spanbert_squad_finetuned_qa_tf32` is a English model originally trained by botcon.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/spanbert_squad_finetuned_qa_tf32_en_5.5.1_3.0_1737757683642.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/spanbert_squad_finetuned_qa_tf32_en_5.5.1_3.0_1737757683642.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = BertForQuestionAnswering.pretrained("spanbert_squad_finetuned_qa_tf32","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering  
+    .pretrained("spanbert_squad_finetuned_qa_tf32", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|spanbert_squad_finetuned_qa_tf32|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|377.6 MB|
+
+## References
+
+References
+
+https://huggingface.co/botcon/SpanBERT_squad_finetuned_qa_tf32
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-spanbert_squad_finetuned_qa_tf32_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-spanbert_squad_finetuned_qa_tf32_pipeline_en.md
new file mode 100644
index 00000000000000..7d79c4f207f43c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-spanbert_squad_finetuned_qa_tf32_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English spanbert_squad_finetuned_qa_tf32_pipeline pipeline BertForQuestionAnswering from Simsuk
+author: John Snow Labs
+name: spanbert_squad_finetuned_qa_tf32_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`spanbert_squad_finetuned_qa_tf32_pipeline` is a English model originally trained by Simsuk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/spanbert_squad_finetuned_qa_tf32_pipeline_en_5.5.1_3.0_1737757715469.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/spanbert_squad_finetuned_qa_tf32_pipeline_en_5.5.1_3.0_1737757715469.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("spanbert_squad_finetuned_qa_tf32_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("spanbert_squad_finetuned_qa_tf32_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|spanbert_squad_finetuned_qa_tf32_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|377.6 MB|
+
+## References
+
+https://huggingface.co/Simsuk/SpanBERT_squad_finetuned_qa_tf32
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-spanishroberta_italian_medprocner_en.md b/docs/_posts/ahmedlone127/2025-01-24-spanishroberta_italian_medprocner_en.md
new file mode 100644
index 00000000000000..47fbc5d6fd0a6d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-spanishroberta_italian_medprocner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English spanishroberta_italian_medprocner RoBertaForTokenClassification from aaaksenova
+author: John Snow Labs
+name: spanishroberta_italian_medprocner
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`spanishroberta_italian_medprocner` is a English model originally trained by aaaksenova.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/spanishroberta_italian_medprocner_en_5.5.1_3.0_1737685495827.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/spanishroberta_italian_medprocner_en_5.5.1_3.0_1737685495827.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("spanishroberta_italian_medprocner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("spanishroberta_italian_medprocner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|spanishroberta_italian_medprocner|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|463.7 MB|
+
+## References
+
+https://huggingface.co/aaaksenova/SpanishRoberta_it_medprocner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-spanishroberta_italian_medprocner_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-spanishroberta_italian_medprocner_pipeline_en.md
new file mode 100644
index 00000000000000..109c425c144ce7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-spanishroberta_italian_medprocner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English spanishroberta_italian_medprocner_pipeline pipeline RoBertaForTokenClassification from aaaksenova
+author: John Snow Labs
+name: spanishroberta_italian_medprocner_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`spanishroberta_italian_medprocner_pipeline` is a English model originally trained by aaaksenova.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/spanishroberta_italian_medprocner_pipeline_en_5.5.1_3.0_1737685520165.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/spanishroberta_italian_medprocner_pipeline_en_5.5.1_3.0_1737685520165.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("spanishroberta_italian_medprocner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("spanishroberta_italian_medprocner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|spanishroberta_italian_medprocner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|463.7 MB|
+
+## References
+
+https://huggingface.co/aaaksenova/SpanishRoberta_it_medprocner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-stanford_car_vit_patch16_en.md b/docs/_posts/ahmedlone127/2025-01-24-stanford_car_vit_patch16_en.md
new file mode 100644
index 00000000000000..24584a039e7854
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-stanford_car_vit_patch16_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English stanford_car_vit_patch16 ViTForImageClassification from therealcyberlord
+author: John Snow Labs
+name: stanford_car_vit_patch16
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`stanford_car_vit_patch16` is a English model originally trained by therealcyberlord.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/stanford_car_vit_patch16_en_5.5.1_3.0_1737744119622.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/stanford_car_vit_patch16_en_5.5.1_3.0_1737744119622.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""stanford_car_vit_patch16","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("stanford_car_vit_patch16","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|stanford_car_vit_patch16|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.9 MB|
+
+## References
+
+https://huggingface.co/therealcyberlord/stanford-car-vit-patch16
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-stanford_car_vit_patch16_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-stanford_car_vit_patch16_pipeline_en.md
new file mode 100644
index 00000000000000..cb35cfa2715d39
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-stanford_car_vit_patch16_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English stanford_car_vit_patch16_pipeline pipeline ViTForImageClassification from therealcyberlord
+author: John Snow Labs
+name: stanford_car_vit_patch16_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`stanford_car_vit_patch16_pipeline` is a English model originally trained by therealcyberlord.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/stanford_car_vit_patch16_pipeline_en_5.5.1_3.0_1737744137496.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/stanford_car_vit_patch16_pipeline_en_5.5.1_3.0_1737744137496.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("stanford_car_vit_patch16_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("stanford_car_vit_patch16_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|stanford_car_vit_patch16_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.9 MB|
+
+## References
+
+https://huggingface.co/therealcyberlord/stanford-car-vit-patch16
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-summarization_sft_reward_model_deberta_v3_large_v2_en.md b/docs/_posts/ahmedlone127/2025-01-24-summarization_sft_reward_model_deberta_v3_large_v2_en.md
new file mode 100644
index 00000000000000..5b70f75c12b3b2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-summarization_sft_reward_model_deberta_v3_large_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English summarization_sft_reward_model_deberta_v3_large_v2 DeBertaForSequenceClassification from weepcat
+author: John Snow Labs
+name: summarization_sft_reward_model_deberta_v3_large_v2
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`summarization_sft_reward_model_deberta_v3_large_v2` is a English model originally trained by weepcat.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/summarization_sft_reward_model_deberta_v3_large_v2_en_5.5.1_3.0_1737728871190.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/summarization_sft_reward_model_deberta_v3_large_v2_en_5.5.1_3.0_1737728871190.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("summarization_sft_reward_model_deberta_v3_large_v2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("summarization_sft_reward_model_deberta_v3_large_v2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|summarization_sft_reward_model_deberta_v3_large_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|832.5 MB|
+
+## References
+
+https://huggingface.co/weepcat/summarization_sft_reward-model-deberta-v3-large-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-summarization_sft_reward_model_deberta_v3_large_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-summarization_sft_reward_model_deberta_v3_large_v2_pipeline_en.md
new file mode 100644
index 00000000000000..288463a15f2600
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-summarization_sft_reward_model_deberta_v3_large_v2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English summarization_sft_reward_model_deberta_v3_large_v2_pipeline pipeline DeBertaForSequenceClassification from weepcat
+author: John Snow Labs
+name: summarization_sft_reward_model_deberta_v3_large_v2_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`summarization_sft_reward_model_deberta_v3_large_v2_pipeline` is a English model originally trained by weepcat.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/summarization_sft_reward_model_deberta_v3_large_v2_pipeline_en_5.5.1_3.0_1737729150174.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/summarization_sft_reward_model_deberta_v3_large_v2_pipeline_en_5.5.1_3.0_1737729150174.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("summarization_sft_reward_model_deberta_v3_large_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("summarization_sft_reward_model_deberta_v3_large_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|summarization_sft_reward_model_deberta_v3_large_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|832.6 MB|
+
+## References
+
+https://huggingface.co/weepcat/summarization_sft_reward-model-deberta-v3-large-v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-summarization_sft_reward_model_deberta_v3_large_v2_romansh_gemma_2b_mask_partial_romansh_random_length_en.md b/docs/_posts/ahmedlone127/2025-01-24-summarization_sft_reward_model_deberta_v3_large_v2_romansh_gemma_2b_mask_partial_romansh_random_length_en.md
new file mode 100644
index 00000000000000..1896ea92c2699f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-summarization_sft_reward_model_deberta_v3_large_v2_romansh_gemma_2b_mask_partial_romansh_random_length_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English summarization_sft_reward_model_deberta_v3_large_v2_romansh_gemma_2b_mask_partial_romansh_random_length DeBertaForSequenceClassification from weepcat
+author: John Snow Labs
+name: summarization_sft_reward_model_deberta_v3_large_v2_romansh_gemma_2b_mask_partial_romansh_random_length
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`summarization_sft_reward_model_deberta_v3_large_v2_romansh_gemma_2b_mask_partial_romansh_random_length` is a English model originally trained by weepcat.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/summarization_sft_reward_model_deberta_v3_large_v2_romansh_gemma_2b_mask_partial_romansh_random_length_en_5.5.1_3.0_1737728362783.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/summarization_sft_reward_model_deberta_v3_large_v2_romansh_gemma_2b_mask_partial_romansh_random_length_en_5.5.1_3.0_1737728362783.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("summarization_sft_reward_model_deberta_v3_large_v2_romansh_gemma_2b_mask_partial_romansh_random_length","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("summarization_sft_reward_model_deberta_v3_large_v2_romansh_gemma_2b_mask_partial_romansh_random_length", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|summarization_sft_reward_model_deberta_v3_large_v2_romansh_gemma_2b_mask_partial_romansh_random_length|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|832.5 MB|
+
+## References
+
+https://huggingface.co/weepcat/summarization_sft_reward-model-deberta-v3-large-v2_RM-Gemma-2B_mask_partial_rm_random_length
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-summarization_sft_reward_model_deberta_v3_large_v2_romansh_gemma_2b_mask_partial_romansh_random_length_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-summarization_sft_reward_model_deberta_v3_large_v2_romansh_gemma_2b_mask_partial_romansh_random_length_pipeline_en.md
new file mode 100644
index 00000000000000..0c0b638b14aba7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-summarization_sft_reward_model_deberta_v3_large_v2_romansh_gemma_2b_mask_partial_romansh_random_length_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English summarization_sft_reward_model_deberta_v3_large_v2_romansh_gemma_2b_mask_partial_romansh_random_length_pipeline pipeline DeBertaForSequenceClassification from weepcat
+author: John Snow Labs
+name: summarization_sft_reward_model_deberta_v3_large_v2_romansh_gemma_2b_mask_partial_romansh_random_length_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`summarization_sft_reward_model_deberta_v3_large_v2_romansh_gemma_2b_mask_partial_romansh_random_length_pipeline` is a English model originally trained by weepcat.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/summarization_sft_reward_model_deberta_v3_large_v2_romansh_gemma_2b_mask_partial_romansh_random_length_pipeline_en_5.5.1_3.0_1737728652073.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/summarization_sft_reward_model_deberta_v3_large_v2_romansh_gemma_2b_mask_partial_romansh_random_length_pipeline_en_5.5.1_3.0_1737728652073.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("summarization_sft_reward_model_deberta_v3_large_v2_romansh_gemma_2b_mask_partial_romansh_random_length_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("summarization_sft_reward_model_deberta_v3_large_v2_romansh_gemma_2b_mask_partial_romansh_random_length_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|summarization_sft_reward_model_deberta_v3_large_v2_romansh_gemma_2b_mask_partial_romansh_random_length_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|832.6 MB|
+
+## References
+
+https://huggingface.co/weepcat/summarization_sft_reward-model-deberta-v3-large-v2_RM-Gemma-2B_mask_partial_rm_random_length
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-summarizer_en.md b/docs/_posts/ahmedlone127/2025-01-24-summarizer_en.md
new file mode 100644
index 00000000000000..d3b1fa8fdc0829
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-summarizer_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English summarizer BartTransformer from hadifar
+author: John Snow Labs
+name: summarizer
+date: 2025-01-24
+tags: [en, open_source, onnx, text_generation, bart]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BartTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`summarizer` is a English model originally trained by hadifar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/summarizer_en_5.5.1_3.0_1737698238492.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/summarizer_en_5.5.1_3.0_1737698238492.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = BartTransformer.pretrained("summarizer","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = BartTransformer.pretrained("summarizer","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|summarizer|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|810.8 MB|
+
+## References
+
+https://huggingface.co/hadifar/summarizer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-summarizer_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-summarizer_pipeline_en.md
new file mode 100644
index 00000000000000..c8501825fb902c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-summarizer_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English summarizer_pipeline pipeline BartTransformer from hadifar
+author: John Snow Labs
+name: summarizer_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`summarizer_pipeline` is a English model originally trained by hadifar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/summarizer_pipeline_en_5.5.1_3.0_1737698283422.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/summarizer_pipeline_en_5.5.1_3.0_1737698283422.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("summarizer_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("summarizer_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|summarizer_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|810.9 MB|
+
+## References
+
+https://huggingface.co/hadifar/summarizer
+
+## Included Models
+
+- DocumentAssembler
+- BartTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-surface_grade_swin_tiny_patch4_window7_224_finetuned_v1_en.md b/docs/_posts/ahmedlone127/2025-01-24-surface_grade_swin_tiny_patch4_window7_224_finetuned_v1_en.md
new file mode 100644
index 00000000000000..d20dcf8d512ca9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-surface_grade_swin_tiny_patch4_window7_224_finetuned_v1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English surface_grade_swin_tiny_patch4_window7_224_finetuned_v1 SwinForImageClassification from ansilmbabl
+author: John Snow Labs
+name: surface_grade_swin_tiny_patch4_window7_224_finetuned_v1
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`surface_grade_swin_tiny_patch4_window7_224_finetuned_v1` is a English model originally trained by ansilmbabl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/surface_grade_swin_tiny_patch4_window7_224_finetuned_v1_en_5.5.1_3.0_1737762524041.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/surface_grade_swin_tiny_patch4_window7_224_finetuned_v1_en_5.5.1_3.0_1737762524041.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""surface_grade_swin_tiny_patch4_window7_224_finetuned_v1","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("surface_grade_swin_tiny_patch4_window7_224_finetuned_v1","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|surface_grade_swin_tiny_patch4_window7_224_finetuned_v1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/ansilmbabl/surface_grade-swin-tiny-patch4-window7-224-finetuned-v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-surface_grade_swin_tiny_patch4_window7_224_finetuned_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-surface_grade_swin_tiny_patch4_window7_224_finetuned_v1_pipeline_en.md
new file mode 100644
index 00000000000000..55005690ce0ad6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-surface_grade_swin_tiny_patch4_window7_224_finetuned_v1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English surface_grade_swin_tiny_patch4_window7_224_finetuned_v1_pipeline pipeline SwinForImageClassification from ansilmbabl
+author: John Snow Labs
+name: surface_grade_swin_tiny_patch4_window7_224_finetuned_v1_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`surface_grade_swin_tiny_patch4_window7_224_finetuned_v1_pipeline` is a English model originally trained by ansilmbabl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/surface_grade_swin_tiny_patch4_window7_224_finetuned_v1_pipeline_en_5.5.1_3.0_1737762534978.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/surface_grade_swin_tiny_patch4_window7_224_finetuned_v1_pipeline_en_5.5.1_3.0_1737762534978.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("surface_grade_swin_tiny_patch4_window7_224_finetuned_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("surface_grade_swin_tiny_patch4_window7_224_finetuned_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|surface_grade_swin_tiny_patch4_window7_224_finetuned_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/ansilmbabl/surface_grade-swin-tiny-patch4-window7-224-finetuned-v1
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-surface_motif_en.md b/docs/_posts/ahmedlone127/2025-01-24-surface_motif_en.md
new file mode 100644
index 00000000000000..fc18752d8cd72f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-surface_motif_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English surface_motif ViTForImageClassification from heartfish
+author: John Snow Labs
+name: surface_motif
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`surface_motif` is a English model originally trained by heartfish.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/surface_motif_en_5.5.1_3.0_1737744074881.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/surface_motif_en_5.5.1_3.0_1737744074881.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""surface_motif","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("surface_motif","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|surface_motif|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/heartfish/surface_motif
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-surface_motif_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-surface_motif_pipeline_en.md
new file mode 100644
index 00000000000000..61daf8de34e9bd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-surface_motif_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English surface_motif_pipeline pipeline ViTForImageClassification from heartfish
+author: John Snow Labs
+name: surface_motif_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`surface_motif_pipeline` is a English model originally trained by heartfish.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/surface_motif_pipeline_en_5.5.1_3.0_1737744092734.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/surface_motif_pipeline_en_5.5.1_3.0_1737744092734.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("surface_motif_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("surface_motif_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|surface_motif_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/heartfish/surface_motif
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swearwords_detection_model_en.md b/docs/_posts/ahmedlone127/2025-01-24-swearwords_detection_model_en.md
new file mode 100644
index 00000000000000..40cd5ed2f1a712
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swearwords_detection_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swearwords_detection_model BertForTokenClassification from keatrean
+author: John Snow Labs
+name: swearwords_detection_model
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swearwords_detection_model` is a English model originally trained by keatrean.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swearwords_detection_model_en_5.5.1_3.0_1737720307863.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swearwords_detection_model_en_5.5.1_3.0_1737720307863.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("swearwords_detection_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("swearwords_detection_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swearwords_detection_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|662.2 MB|
+
+## References
+
+https://huggingface.co/keatrean/swearwords-detection-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swearwords_detection_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swearwords_detection_model_pipeline_en.md
new file mode 100644
index 00000000000000..d726c3e18b2e4e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swearwords_detection_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English swearwords_detection_model_pipeline pipeline BertForTokenClassification from keatrean
+author: John Snow Labs
+name: swearwords_detection_model_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swearwords_detection_model_pipeline` is a English model originally trained by keatrean.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swearwords_detection_model_pipeline_en_5.5.1_3.0_1737720342839.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swearwords_detection_model_pipeline_en_5.5.1_3.0_1737720342839.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swearwords_detection_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swearwords_detection_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swearwords_detection_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|662.2 MB|
+
+## References
+
+https://huggingface.co/keatrean/swearwords-detection-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window12_384_in22k_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window12_384_in22k_en.md
new file mode 100644
index 00000000000000..203c0327688408
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window12_384_in22k_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_base_patch4_window12_384_in22k SwinForImageClassification from microsoft
+author: John Snow Labs
+name: swin_base_patch4_window12_384_in22k
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_base_patch4_window12_384_in22k` is a English model originally trained by microsoft.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window12_384_in22k_en_5.5.1_3.0_1737694652410.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window12_384_in22k_en_5.5.1_3.0_1737694652410.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_base_patch4_window12_384_in22k","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_base_patch4_window12_384_in22k","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_base_patch4_window12_384_in22k|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|820.3 MB|
+
+## References
+
+https://huggingface.co/microsoft/swin-base-patch4-window12-384-in22k
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window12_384_in22k_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window12_384_in22k_pipeline_en.md
new file mode 100644
index 00000000000000..a085ebcc7aa90d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window12_384_in22k_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_base_patch4_window12_384_in22k_pipeline pipeline SwinForImageClassification from microsoft
+author: John Snow Labs
+name: swin_base_patch4_window12_384_in22k_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_base_patch4_window12_384_in22k_pipeline` is a English model originally trained by microsoft.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window12_384_in22k_pipeline_en_5.5.1_3.0_1737694696092.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window12_384_in22k_pipeline_en_5.5.1_3.0_1737694696092.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_base_patch4_window12_384_in22k_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_base_patch4_window12_384_in22k_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_base_patch4_window12_384_in22k_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|820.3 MB|
+
+## References
+
+https://huggingface.co/microsoft/swin-base-patch4-window12-384-in22k
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_02_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_02_en.md
new file mode 100644
index 00000000000000..7ed538d93dfb97
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_02_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_02 SwinForImageClassification from amjadfqs
+author: John Snow Labs
+name: swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_02
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_02` is a English model originally trained by amjadfqs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_02_en_5.5.1_3.0_1737693933335.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_02_en_5.5.1_3.0_1737693933335.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_02","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_02","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_02|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|649.8 MB|
+
+## References
+
+https://huggingface.co/amjadfqs/swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-final_02
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_02_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_02_pipeline_en.md
new file mode 100644
index 00000000000000..00ecf814a8994b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_02_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_02_pipeline pipeline SwinForImageClassification from amjadfqs
+author: John Snow Labs
+name: swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_02_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_02_pipeline` is a English model originally trained by amjadfqs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_02_pipeline_en_5.5.1_3.0_1737693967577.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_02_pipeline_en_5.5.1_3.0_1737693967577.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_02_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_02_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_02_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|649.8 MB|
+
+## References
+
+https://huggingface.co/amjadfqs/swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-final_02
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_03_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_03_en.md
new file mode 100644
index 00000000000000..1fdf5686b22034
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_03_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_03 SwinForImageClassification from amjadfqs
+author: John Snow Labs
+name: swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_03
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_03` is a English model originally trained by amjadfqs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_03_en_5.5.1_3.0_1737715040327.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_03_en_5.5.1_3.0_1737715040327.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_03","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_03","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_03|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|649.8 MB|
+
+## References
+
+https://huggingface.co/amjadfqs/swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-final_03
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_03_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_03_pipeline_en.md
new file mode 100644
index 00000000000000..0f88837e7973e5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_03_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_03_pipeline pipeline SwinForImageClassification from amjadfqs
+author: John Snow Labs
+name: swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_03_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_03_pipeline` is a English model originally trained by amjadfqs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_03_pipeline_en_5.5.1_3.0_1737715076755.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_03_pipeline_en_5.5.1_3.0_1737715076755.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_03_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_03_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_03_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|649.8 MB|
+
+## References
+
+https://huggingface.co/amjadfqs/swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-final_03
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_07_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_07_en.md
new file mode 100644
index 00000000000000..6def7f9220efb6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_07_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_07 SwinForImageClassification from amjadfqs
+author: John Snow Labs
+name: swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_07
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_07` is a English model originally trained by amjadfqs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_07_en_5.5.1_3.0_1737694798665.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_07_en_5.5.1_3.0_1737694798665.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_07","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_07","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_07|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|649.8 MB|
+
+## References
+
+https://huggingface.co/amjadfqs/swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-final_07
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_07_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_07_pipeline_en.md
new file mode 100644
index 00000000000000..9caf6550839a37
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_07_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_07_pipeline pipeline SwinForImageClassification from amjadfqs
+author: John Snow Labs
+name: swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_07_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_07_pipeline` is a English model originally trained by amjadfqs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_07_pipeline_en_5.5.1_3.0_1737694833755.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_07_pipeline_en_5.5.1_3.0_1737694833755.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_07_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_07_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_07_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|649.8 MB|
+
+## References
+
+https://huggingface.co/amjadfqs/swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-final_07
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_08_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_08_en.md
new file mode 100644
index 00000000000000..c1fff317444502
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_08_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_08 SwinForImageClassification from amjadfqs
+author: John Snow Labs
+name: swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_08
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_08` is a English model originally trained by amjadfqs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_08_en_5.5.1_3.0_1737754767585.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_08_en_5.5.1_3.0_1737754767585.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_08","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_08","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_08|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|649.8 MB|
+
+## References
+
+https://huggingface.co/amjadfqs/swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-final_08
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_08_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_08_pipeline_en.md
new file mode 100644
index 00000000000000..042c74129833e4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_08_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_08_pipeline pipeline SwinForImageClassification from amjadfqs
+author: John Snow Labs
+name: swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_08_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_08_pipeline` is a English model originally trained by amjadfqs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_08_pipeline_en_5.5.1_3.0_1737754804054.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_08_pipeline_en_5.5.1_3.0_1737754804054.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_08_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_08_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_08_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|649.8 MB|
+
+## References
+
+https://huggingface.co/amjadfqs/swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-final_08
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_04_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_04_en.md
new file mode 100644
index 00000000000000..d5bcdd440a7509
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_04_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_04 SwinForImageClassification from amjadfqs
+author: John Snow Labs
+name: swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_04
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_04` is a English model originally trained by amjadfqs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_04_en_5.5.1_3.0_1737715192473.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_04_en_5.5.1_3.0_1737715192473.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_04","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_04","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_04|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|649.8 MB|
+
+## References
+
+https://huggingface.co/amjadfqs/swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-skullStrippded_04
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_04_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_04_pipeline_en.md
new file mode 100644
index 00000000000000..3b5a7c3db9b3c2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_04_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_04_pipeline pipeline SwinForImageClassification from amjadfqs
+author: John Snow Labs
+name: swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_04_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_04_pipeline` is a English model originally trained by amjadfqs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_04_pipeline_en_5.5.1_3.0_1737715227716.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_04_pipeline_en_5.5.1_3.0_1737715227716.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_04_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_04_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_04_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|649.8 MB|
+
+## References
+
+https://huggingface.co/amjadfqs/swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-skullStrippded_04
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window7_224_in22k_finetuned_ct_manuel_o_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window7_224_in22k_finetuned_ct_manuel_o_en.md
new file mode 100644
index 00000000000000..e1147aa4ac4689
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window7_224_in22k_finetuned_ct_manuel_o_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_base_patch4_window7_224_in22k_finetuned_ct_manuel_o SwinForImageClassification from Manuel-O
+author: John Snow Labs
+name: swin_base_patch4_window7_224_in22k_finetuned_ct_manuel_o
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_base_patch4_window7_224_in22k_finetuned_ct_manuel_o` is a English model originally trained by Manuel-O.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_in22k_finetuned_ct_manuel_o_en_5.5.1_3.0_1737754490946.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_in22k_finetuned_ct_manuel_o_en_5.5.1_3.0_1737754490946.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_base_patch4_window7_224_in22k_finetuned_ct_manuel_o","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_base_patch4_window7_224_in22k_finetuned_ct_manuel_o","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_base_patch4_window7_224_in22k_finetuned_ct_manuel_o|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|649.8 MB|
+
+## References
+
+https://huggingface.co/Manuel-O/swin-base-patch4-window7-224-in22k-finetuned-CT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window7_224_in22k_finetuned_ct_manuel_o_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window7_224_in22k_finetuned_ct_manuel_o_pipeline_en.md
new file mode 100644
index 00000000000000..4960db380f39f0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window7_224_in22k_finetuned_ct_manuel_o_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_base_patch4_window7_224_in22k_finetuned_ct_manuel_o_pipeline pipeline SwinForImageClassification from Manuel-O
+author: John Snow Labs
+name: swin_base_patch4_window7_224_in22k_finetuned_ct_manuel_o_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_base_patch4_window7_224_in22k_finetuned_ct_manuel_o_pipeline` is a English model originally trained by Manuel-O.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_in22k_finetuned_ct_manuel_o_pipeline_en_5.5.1_3.0_1737754528688.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_in22k_finetuned_ct_manuel_o_pipeline_en_5.5.1_3.0_1737754528688.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_base_patch4_window7_224_in22k_finetuned_ct_manuel_o_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_base_patch4_window7_224_in22k_finetuned_ct_manuel_o_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_base_patch4_window7_224_in22k_finetuned_ct_manuel_o_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|649.8 MB|
+
+## References
+
+https://huggingface.co/Manuel-O/swin-base-patch4-window7-224-in22k-finetuned-CT
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window7_224_in22k_finetuned_ct_v2_zen45_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window7_224_in22k_finetuned_ct_v2_zen45_en.md
new file mode 100644
index 00000000000000..487676ebd20bb8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window7_224_in22k_finetuned_ct_v2_zen45_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_base_patch4_window7_224_in22k_finetuned_ct_v2_zen45 SwinForImageClassification from zen45
+author: John Snow Labs
+name: swin_base_patch4_window7_224_in22k_finetuned_ct_v2_zen45
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_base_patch4_window7_224_in22k_finetuned_ct_v2_zen45` is a English model originally trained by zen45.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_in22k_finetuned_ct_v2_zen45_en_5.5.1_3.0_1737694636874.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_in22k_finetuned_ct_v2_zen45_en_5.5.1_3.0_1737694636874.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_base_patch4_window7_224_in22k_finetuned_ct_v2_zen45","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_base_patch4_window7_224_in22k_finetuned_ct_v2_zen45","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_base_patch4_window7_224_in22k_finetuned_ct_v2_zen45|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|649.8 MB|
+
+## References
+
+https://huggingface.co/zen45/swin-base-patch4-window7-224-in22k-finetuned-CT-V2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window7_224_in22k_finetuned_ct_v2_zen45_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window7_224_in22k_finetuned_ct_v2_zen45_pipeline_en.md
new file mode 100644
index 00000000000000..4600e247f9f1c6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window7_224_in22k_finetuned_ct_v2_zen45_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_base_patch4_window7_224_in22k_finetuned_ct_v2_zen45_pipeline pipeline SwinForImageClassification from zen45
+author: John Snow Labs
+name: swin_base_patch4_window7_224_in22k_finetuned_ct_v2_zen45_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_base_patch4_window7_224_in22k_finetuned_ct_v2_zen45_pipeline` is a English model originally trained by zen45.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_in22k_finetuned_ct_v2_zen45_pipeline_en_5.5.1_3.0_1737694674658.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_in22k_finetuned_ct_v2_zen45_pipeline_en_5.5.1_3.0_1737694674658.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_base_patch4_window7_224_in22k_finetuned_ct_v2_zen45_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_base_patch4_window7_224_in22k_finetuned_ct_v2_zen45_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_base_patch4_window7_224_in22k_finetuned_ct_v2_zen45_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|649.8 MB|
+
+## References
+
+https://huggingface.co/zen45/swin-base-patch4-window7-224-in22k-finetuned-CT-V2
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window7_224_venda_u13_b_80c_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window7_224_venda_u13_b_80c_en.md
new file mode 100644
index 00000000000000..bbe4dc942c4df0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window7_224_venda_u13_b_80c_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_base_patch4_window7_224_venda_u13_b_80c SwinForImageClassification from Augusto777
+author: John Snow Labs
+name: swin_base_patch4_window7_224_venda_u13_b_80c
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_base_patch4_window7_224_venda_u13_b_80c` is a English model originally trained by Augusto777.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_venda_u13_b_80c_en_5.5.1_3.0_1737715069087.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_venda_u13_b_80c_en_5.5.1_3.0_1737715069087.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_base_patch4_window7_224_venda_u13_b_80c","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_base_patch4_window7_224_venda_u13_b_80c","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_base_patch4_window7_224_venda_u13_b_80c|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|649.8 MB|
+
+## References
+
+https://huggingface.co/Augusto777/swin-base-patch4-window7-224-ve-U13-b-80c
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window7_224_venda_u13_b_80c_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window7_224_venda_u13_b_80c_pipeline_en.md
new file mode 100644
index 00000000000000..b470d75c027bdf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_base_patch4_window7_224_venda_u13_b_80c_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_base_patch4_window7_224_venda_u13_b_80c_pipeline pipeline SwinForImageClassification from Augusto777
+author: John Snow Labs
+name: swin_base_patch4_window7_224_venda_u13_b_80c_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_base_patch4_window7_224_venda_u13_b_80c_pipeline` is a English model originally trained by Augusto777.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_venda_u13_b_80c_pipeline_en_5.5.1_3.0_1737715116128.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_venda_u13_b_80c_pipeline_en_5.5.1_3.0_1737715116128.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_base_patch4_window7_224_venda_u13_b_80c_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_base_patch4_window7_224_venda_u13_b_80c_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_base_patch4_window7_224_venda_u13_b_80c_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|649.8 MB|
+
+## References
+
+https://huggingface.co/Augusto777/swin-base-patch4-window7-224-ve-U13-b-80c
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_finetuned_food101_alexeiskn_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_finetuned_food101_alexeiskn_en.md
new file mode 100644
index 00000000000000..bee855549dafa9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_finetuned_food101_alexeiskn_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_finetuned_food101_alexeiskn SwinForImageClassification from alexeiskn
+author: John Snow Labs
+name: swin_finetuned_food101_alexeiskn
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_finetuned_food101_alexeiskn` is a English model originally trained by alexeiskn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_finetuned_food101_alexeiskn_en_5.5.1_3.0_1737762820761.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_finetuned_food101_alexeiskn_en_5.5.1_3.0_1737762820761.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_finetuned_food101_alexeiskn","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_finetuned_food101_alexeiskn","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_finetuned_food101_alexeiskn|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|650.5 MB|
+
+## References
+
+https://huggingface.co/alexeiskn/swin-finetuned-food101
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_finetuned_food101_alexeiskn_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_finetuned_food101_alexeiskn_pipeline_en.md
new file mode 100644
index 00000000000000..cc10b4d321ffad
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_finetuned_food101_alexeiskn_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_finetuned_food101_alexeiskn_pipeline pipeline SwinForImageClassification from alexeiskn
+author: John Snow Labs
+name: swin_finetuned_food101_alexeiskn_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_finetuned_food101_alexeiskn_pipeline` is a English model originally trained by alexeiskn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_finetuned_food101_alexeiskn_pipeline_en_5.5.1_3.0_1737762856072.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_finetuned_food101_alexeiskn_pipeline_en_5.5.1_3.0_1737762856072.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_finetuned_food101_alexeiskn_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_finetuned_food101_alexeiskn_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_finetuned_food101_alexeiskn_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|650.5 MB|
+
+## References
+
+https://huggingface.co/alexeiskn/swin-finetuned-food101
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_large_patch4_window12_384_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_large_patch4_window12_384_en.md
new file mode 100644
index 00000000000000..92c12a0c812eee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_large_patch4_window12_384_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_large_patch4_window12_384 SwinForImageClassification from microsoft
+author: John Snow Labs
+name: swin_large_patch4_window12_384
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_large_patch4_window12_384` is a English model originally trained by microsoft.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_large_patch4_window12_384_en_5.5.1_3.0_1737715063677.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_large_patch4_window12_384_en_5.5.1_3.0_1737715063677.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_large_patch4_window12_384","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_large_patch4_window12_384","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_large_patch4_window12_384|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/microsoft/swin-large-patch4-window12-384
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_large_patch4_window12_384_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_large_patch4_window12_384_pipeline_en.md
new file mode 100644
index 00000000000000..b704ca9d9b033d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_large_patch4_window12_384_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_large_patch4_window12_384_pipeline pipeline SwinForImageClassification from microsoft
+author: John Snow Labs
+name: swin_large_patch4_window12_384_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_large_patch4_window12_384_pipeline` is a English model originally trained by microsoft.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_large_patch4_window12_384_pipeline_en_5.5.1_3.0_1737715147451.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_large_patch4_window12_384_pipeline_en_5.5.1_3.0_1737715147451.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_large_patch4_window12_384_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_large_patch4_window12_384_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_large_patch4_window12_384_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/microsoft/swin-large-patch4-window12-384
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_finetuned_lung_cancer_ct_scans_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_finetuned_lung_cancer_ct_scans_en.md
new file mode 100644
index 00000000000000..fcb1ae9c2e2dd4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_finetuned_lung_cancer_ct_scans_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_finetuned_lung_cancer_ct_scans SwinForImageClassification from oohtmeel
+author: John Snow Labs
+name: swin_tiny_patch4_finetuned_lung_cancer_ct_scans
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_finetuned_lung_cancer_ct_scans` is a English model originally trained by oohtmeel.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_finetuned_lung_cancer_ct_scans_en_5.5.1_3.0_1737694629068.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_finetuned_lung_cancer_ct_scans_en_5.5.1_3.0_1737694629068.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_finetuned_lung_cancer_ct_scans","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_finetuned_lung_cancer_ct_scans","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_finetuned_lung_cancer_ct_scans|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/oohtmeel/swin-tiny-patch4-finetuned-lung-cancer-ct-scans
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_finetuned_lung_cancer_ct_scans_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_finetuned_lung_cancer_ct_scans_pipeline_en.md
new file mode 100644
index 00000000000000..07b89d468c5f6e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_finetuned_lung_cancer_ct_scans_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_finetuned_lung_cancer_ct_scans_pipeline pipeline SwinForImageClassification from oohtmeel
+author: John Snow Labs
+name: swin_tiny_patch4_finetuned_lung_cancer_ct_scans_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_finetuned_lung_cancer_ct_scans_pipeline` is a English model originally trained by oohtmeel.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_finetuned_lung_cancer_ct_scans_pipeline_en_5.5.1_3.0_1737694639773.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_finetuned_lung_cancer_ct_scans_pipeline_en_5.5.1_3.0_1737694639773.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_finetuned_lung_cancer_ct_scans_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_finetuned_lung_cancer_ct_scans_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_finetuned_lung_cancer_ct_scans_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/oohtmeel/swin-tiny-patch4-finetuned-lung-cancer-ct-scans
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_bottomcleaneddata_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_bottomcleaneddata_en.md
new file mode 100644
index 00000000000000..0ba90afc2294d2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_bottomcleaneddata_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_bottomcleaneddata SwinForImageClassification from Soulaimen
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_bottomcleaneddata
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_bottomcleaneddata` is a English model originally trained by Soulaimen.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_bottomcleaneddata_en_5.5.1_3.0_1737715828625.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_bottomcleaneddata_en_5.5.1_3.0_1737715828625.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_bottomcleaneddata","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_bottomcleaneddata","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_bottomcleaneddata|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/Soulaimen/swin-tiny-patch4-window7-224-bottomCleanedData
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_bottomcleaneddata_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_bottomcleaneddata_pipeline_en.md
new file mode 100644
index 00000000000000..52492745b12537
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_bottomcleaneddata_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_bottomcleaneddata_pipeline pipeline SwinForImageClassification from Soulaimen
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_bottomcleaneddata_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_bottomcleaneddata_pipeline` is a English model originally trained by Soulaimen.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_bottomcleaneddata_pipeline_en_5.5.1_3.0_1737715839651.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_bottomcleaneddata_pipeline_en_5.5.1_3.0_1737715839651.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_bottomcleaneddata_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_bottomcleaneddata_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_bottomcleaneddata_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/Soulaimen/swin-tiny-patch4-window7-224-bottomCleanedData
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_classification_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_classification_en.md
new file mode 100644
index 00000000000000..75cedb7a23c251
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_classification_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_classification SwinForImageClassification from karoladelk
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_classification
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_classification` is a English model originally trained by karoladelk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_classification_en_5.5.1_3.0_1737754393392.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_classification_en_5.5.1_3.0_1737754393392.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_classification","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_classification","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_classification|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/karoladelk/swin-tiny-patch4-window7-224-classification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_classification_pipeline_en.md
new file mode 100644
index 00000000000000..99e6b6824a9e01
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_classification_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_classification_pipeline pipeline SwinForImageClassification from karoladelk
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_classification_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_classification_pipeline` is a English model originally trained by karoladelk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_classification_pipeline_en_5.5.1_3.0_1737754404428.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_classification_pipeline_en_5.5.1_3.0_1737754404428.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_classification_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_classification_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_classification_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/karoladelk/swin-tiny-patch4-window7-224-classification
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_eurosat_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_eurosat_en.md
new file mode 100644
index 00000000000000..34c9bfb03ec3f3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_eurosat_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_eurosat SwinForImageClassification from polejowska
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_eurosat
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_eurosat` is a English model originally trained by polejowska.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_eurosat_en_5.5.1_3.0_1737762756478.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_eurosat_en_5.5.1_3.0_1737762756478.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_eurosat","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_eurosat","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_eurosat|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/polejowska/swin-tiny-patch4-window7-224-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_eurosat_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_eurosat_pipeline_en.md
new file mode 100644
index 00000000000000..b2b7cc8888a194
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_eurosat_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_eurosat_pipeline pipeline SwinForImageClassification from polejowska
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_eurosat_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_eurosat_pipeline` is a English model originally trained by polejowska.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_eurosat_pipeline_en_5.5.1_3.0_1737762767863.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_eurosat_pipeline_en_5.5.1_3.0_1737762767863.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_eurosat_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_eurosat_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_eurosat_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/polejowska/swin-tiny-patch4-window7-224-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finalterm_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finalterm_en.md
new file mode 100644
index 00000000000000..f7cce94a44687c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finalterm_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finalterm SwinForImageClassification from vintage-lavender619
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finalterm
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finalterm` is a English model originally trained by vintage-lavender619.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finalterm_en_5.5.1_3.0_1737715032554.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finalterm_en_5.5.1_3.0_1737715032554.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finalterm","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finalterm","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finalterm|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/vintage-lavender619/swin-tiny-patch4-window7-224-finalterm
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finalterm_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finalterm_pipeline_en.md
new file mode 100644
index 00000000000000..e7cf2976342c3c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finalterm_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finalterm_pipeline pipeline SwinForImageClassification from vintage-lavender619
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finalterm_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finalterm_pipeline` is a English model originally trained by vintage-lavender619.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finalterm_pipeline_en_5.5.1_3.0_1737715044020.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finalterm_pipeline_en_5.5.1_3.0_1737715044020.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finalterm_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finalterm_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finalterm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/vintage-lavender619/swin-tiny-patch4-window7-224-finalterm
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_200k_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_200k_en.md
new file mode 100644
index 00000000000000..82c7744411e6dc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_200k_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_200k SwinForImageClassification from navradio
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_200k
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_200k` is a English model originally trained by navradio.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_200k_en_5.5.1_3.0_1737754473502.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_200k_en_5.5.1_3.0_1737754473502.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_200k","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_200k","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_200k|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/navradio/swin-tiny-patch4-window7-224-finetuned-200k
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_200k_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_200k_pipeline_en.md
new file mode 100644
index 00000000000000..07b9f3f9c31f67
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_200k_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_200k_pipeline pipeline SwinForImageClassification from navradio
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_200k_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_200k_pipeline` is a English model originally trained by navradio.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_200k_pipeline_en_5.5.1_3.0_1737754484862.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_200k_pipeline_en_5.5.1_3.0_1737754484862.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_200k_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_200k_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_200k_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/navradio/swin-tiny-patch4-window7-224-finetuned-200k
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_aiornot_step_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_aiornot_step_en.md
new file mode 100644
index 00000000000000..bfc739b2e61aa2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_aiornot_step_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_aiornot_step SwinForImageClassification from byc3230
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_aiornot_step
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_aiornot_step` is a English model originally trained by byc3230.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_aiornot_step_en_5.5.1_3.0_1737715202297.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_aiornot_step_en_5.5.1_3.0_1737715202297.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_aiornot_step","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_aiornot_step","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_aiornot_step|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/byc3230/swin-tiny-patch4-window7-224-finetuned-aiornot-step
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_aiornot_step_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_aiornot_step_pipeline_en.md
new file mode 100644
index 00000000000000..2d599adba52c13
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_aiornot_step_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_aiornot_step_pipeline pipeline SwinForImageClassification from byc3230
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_aiornot_step_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_aiornot_step_pipeline` is a English model originally trained by byc3230.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_aiornot_step_pipeline_en_5.5.1_3.0_1737715213553.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_aiornot_step_pipeline_en_5.5.1_3.0_1737715213553.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_aiornot_step_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_aiornot_step_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_aiornot_step_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/byc3230/swin-tiny-patch4-window7-224-finetuned-aiornot-step
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_angy309_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_angy309_en.md
new file mode 100644
index 00000000000000..9d39bde39aa63c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_angy309_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_angy309 SwinForImageClassification from Angy309
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_angy309
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_angy309` is a English model originally trained by Angy309.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_angy309_en_5.5.1_3.0_1737754491277.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_angy309_en_5.5.1_3.0_1737754491277.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_angy309","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_angy309","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_angy309|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/Angy309/swin-tiny-patch4-window7-224-finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_angy309_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_angy309_pipeline_en.md
new file mode 100644
index 00000000000000..02a7d1a19a0866
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_angy309_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_angy309_pipeline pipeline SwinForImageClassification from Angy309
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_angy309_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_angy309_pipeline` is a English model originally trained by Angy309.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_angy309_pipeline_en_5.5.1_3.0_1737754505628.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_angy309_pipeline_en_5.5.1_3.0_1737754505628.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_angy309_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_angy309_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_angy309_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/Angy309/swin-tiny-patch4-window7-224-finetuned
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_azure_poc_img_classification_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_azure_poc_img_classification_en.md
new file mode 100644
index 00000000000000..0e2670594da9ec
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_azure_poc_img_classification_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_azure_poc_img_classification SwinForImageClassification from DUCBUI
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_azure_poc_img_classification
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_azure_poc_img_classification` is a English model originally trained by DUCBUI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_azure_poc_img_classification_en_5.5.1_3.0_1737762950876.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_azure_poc_img_classification_en_5.5.1_3.0_1737762950876.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_azure_poc_img_classification","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_azure_poc_img_classification","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_azure_poc_img_classification|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/DUCBUI/swin-tiny-patch4-window7-224-finetuned-azure-poc-img-classification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_azure_poc_img_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_azure_poc_img_classification_pipeline_en.md
new file mode 100644
index 00000000000000..923b5517f4eb74
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_azure_poc_img_classification_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_azure_poc_img_classification_pipeline pipeline SwinForImageClassification from DUCBUI
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_azure_poc_img_classification_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_azure_poc_img_classification_pipeline` is a English model originally trained by DUCBUI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_azure_poc_img_classification_pipeline_en_5.5.1_3.0_1737762962121.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_azure_poc_img_classification_pipeline_en_5.5.1_3.0_1737762962121.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_azure_poc_img_classification_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_azure_poc_img_classification_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_azure_poc_img_classification_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/DUCBUI/swin-tiny-patch4-window7-224-finetuned-azure-poc-img-classification
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_black_widow_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_black_widow_en.md
new file mode 100644
index 00000000000000..22fc820d0a2b7c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_black_widow_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_black_widow SwinForImageClassification from zkdeng
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_black_widow
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_black_widow` is a English model originally trained by zkdeng.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_black_widow_en_5.5.1_3.0_1737694506140.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_black_widow_en_5.5.1_3.0_1737694506140.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_black_widow","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_black_widow","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_black_widow|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/zkdeng/swin-tiny-patch4-window7-224-finetuned-black_widow
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_black_widow_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_black_widow_pipeline_en.md
new file mode 100644
index 00000000000000..4ba2bab0ac14c7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_black_widow_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_black_widow_pipeline pipeline SwinForImageClassification from zkdeng
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_black_widow_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_black_widow_pipeline` is a English model originally trained by zkdeng.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_black_widow_pipeline_en_5.5.1_3.0_1737694516856.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_black_widow_pipeline_en_5.5.1_3.0_1737694516856.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_black_widow_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_black_widow_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_black_widow_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/zkdeng/swin-tiny-patch4-window7-224-finetuned-black_widow
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_cancer_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_cancer_en.md
new file mode 100644
index 00000000000000..d82c69cba86a5f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_cancer_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_cancer SwinForImageClassification from Zethearc
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_cancer
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_cancer` is a English model originally trained by Zethearc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_cancer_en_5.5.1_3.0_1737694229960.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_cancer_en_5.5.1_3.0_1737694229960.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_cancer","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_cancer","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_cancer|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/Zethearc/swin-tiny-patch4-window7-224-finetuned-cancer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_cancer_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_cancer_pipeline_en.md
new file mode 100644
index 00000000000000..31fcfe4339033a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_cancer_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_cancer_pipeline pipeline SwinForImageClassification from Zethearc
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_cancer_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_cancer_pipeline` is a English model originally trained by Zethearc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_cancer_pipeline_en_5.5.1_3.0_1737694241705.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_cancer_pipeline_en_5.5.1_3.0_1737694241705.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_cancer_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_cancer_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_cancer_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/Zethearc/swin-tiny-patch4-window7-224-finetuned-cancer
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_car0001_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_car0001_en.md
new file mode 100644
index 00000000000000..4f8f7311a881be
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_car0001_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_car0001 SwinForImageClassification from tsware
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_car0001
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_car0001` is a English model originally trained by tsware.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_car0001_en_5.5.1_3.0_1737715327504.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_car0001_en_5.5.1_3.0_1737715327504.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_car0001","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_car0001","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_car0001|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/tsware/swin-tiny-patch4-window7-224-finetuned-car0001
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_car0001_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_car0001_pipeline_en.md
new file mode 100644
index 00000000000000..acc84e695aa7ce
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_car0001_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_car0001_pipeline pipeline SwinForImageClassification from tsware
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_car0001_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_car0001_pipeline` is a English model originally trained by tsware.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_car0001_pipeline_en_5.5.1_3.0_1737715338845.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_car0001_pipeline_en_5.5.1_3.0_1737715338845.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_car0001_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_car0001_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_car0001_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/tsware/swin-tiny-patch4-window7-224-finetuned-car0001
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_car0004_addrealimg_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_car0004_addrealimg_en.md
new file mode 100644
index 00000000000000..5d69a0cb4be173
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_car0004_addrealimg_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_car0004_addrealimg SwinForImageClassification from tsware
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_car0004_addrealimg
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_car0004_addrealimg` is a English model originally trained by tsware.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_car0004_addrealimg_en_5.5.1_3.0_1737694352934.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_car0004_addrealimg_en_5.5.1_3.0_1737694352934.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_car0004_addrealimg","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_car0004_addrealimg","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_car0004_addrealimg|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/tsware/swin-tiny-patch4-window7-224-finetuned-car0004-addrealimg
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_car0004_addrealimg_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_car0004_addrealimg_pipeline_en.md
new file mode 100644
index 00000000000000..40d525c9b10dc3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_car0004_addrealimg_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_car0004_addrealimg_pipeline pipeline SwinForImageClassification from tsware
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_car0004_addrealimg_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_car0004_addrealimg_pipeline` is a English model originally trained by tsware.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_car0004_addrealimg_pipeline_en_5.5.1_3.0_1737694365735.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_car0004_addrealimg_pipeline_en_5.5.1_3.0_1737694365735.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_car0004_addrealimg_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_car0004_addrealimg_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_car0004_addrealimg_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/tsware/swin-tiny-patch4-window7-224-finetuned-car0004-addrealimg
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_car0005_realimg_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_car0005_realimg_en.md
new file mode 100644
index 00000000000000..59e250c06e8472
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_car0005_realimg_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_car0005_realimg SwinForImageClassification from tsware
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_car0005_realimg
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_car0005_realimg` is a English model originally trained by tsware.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_car0005_realimg_en_5.5.1_3.0_1737694124243.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_car0005_realimg_en_5.5.1_3.0_1737694124243.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_car0005_realimg","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_car0005_realimg","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_car0005_realimg|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/tsware/swin-tiny-patch4-window7-224-finetuned-car0005-realimg
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_car0005_realimg_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_car0005_realimg_pipeline_en.md
new file mode 100644
index 00000000000000..78550cf9f3f968
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_car0005_realimg_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_car0005_realimg_pipeline pipeline SwinForImageClassification from tsware
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_car0005_realimg_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_car0005_realimg_pipeline` is a English model originally trained by tsware.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_car0005_realimg_pipeline_en_5.5.1_3.0_1737694136304.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_car0005_realimg_pipeline_en_5.5.1_3.0_1737694136304.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_car0005_realimg_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_car0005_realimg_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_car0005_realimg_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/tsware/swin-tiny-patch4-window7-224-finetuned-car0005-realimg
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_cifar100_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_cifar100_en.md
new file mode 100644
index 00000000000000..4104f64cdcf21e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_cifar100_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_cifar100 SwinForImageClassification from jaycamper
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_cifar100
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_cifar100` is a English model originally trained by jaycamper.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_cifar100_en_5.5.1_3.0_1737715274390.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_cifar100_en_5.5.1_3.0_1737715274390.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_cifar100","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_cifar100","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_cifar100|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.9 MB|
+
+## References
+
+https://huggingface.co/jaycamper/swin-tiny-patch4-window7-224-finetuned-cifar100
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_cifar100_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_cifar100_pipeline_en.md
new file mode 100644
index 00000000000000..caf5192a7528cb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_cifar100_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_cifar100_pipeline pipeline SwinForImageClassification from jaycamper
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_cifar100_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_cifar100_pipeline` is a English model originally trained by jaycamper.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_cifar100_pipeline_en_5.5.1_3.0_1737715297121.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_cifar100_pipeline_en_5.5.1_3.0_1737715297121.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_cifar100_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_cifar100_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_cifar100_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.9 MB|
+
+## References
+
+https://huggingface.co/jaycamper/swin-tiny-patch4-window7-224-finetuned-cifar100
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_3_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_3_en.md
new file mode 100644
index 00000000000000..08de5aefc9abf7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_3 SwinForImageClassification from HITMYM
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_3
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_3` is a English model originally trained by HITMYM.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_3_en_5.5.1_3.0_1737694748238.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_3_en_5.5.1_3.0_1737694748238.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_3","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_3","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_3|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/HITMYM/swin-tiny-patch4-window7-224-finetuned-eurosat-3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_3_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_3_pipeline_en.md
new file mode 100644
index 00000000000000..37e2903c562d07
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_3_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_3_pipeline pipeline SwinForImageClassification from HITMYM
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_3_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_3_pipeline` is a English model originally trained by HITMYM.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_3_pipeline_en_5.5.1_3.0_1737694759595.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_3_pipeline_en_5.5.1_3.0_1737694759595.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/HITMYM/swin-tiny-patch4-window7-224-finetuned-eurosat-3
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_aichoux_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_aichoux_en.md
new file mode 100644
index 00000000000000..e2fc7b96f6293d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_aichoux_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_aichoux SwinForImageClassification from aichoux
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_aichoux
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_aichoux` is a English model originally trained by aichoux.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_aichoux_en_5.5.1_3.0_1737694144542.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_aichoux_en_5.5.1_3.0_1737694144542.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_aichoux","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_aichoux","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_aichoux|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/aichoux/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_aichoux_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_aichoux_pipeline_en.md
new file mode 100644
index 00000000000000..c54427c35d9686
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_aichoux_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_aichoux_pipeline pipeline SwinForImageClassification from aichoux
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_aichoux_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_aichoux_pipeline` is a English model originally trained by aichoux.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_aichoux_pipeline_en_5.5.1_3.0_1737694156259.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_aichoux_pipeline_en_5.5.1_3.0_1737694156259.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_aichoux_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_aichoux_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_aichoux_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/aichoux/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_anurag629_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_anurag629_en.md
new file mode 100644
index 00000000000000..eb16c639e6375f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_anurag629_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_anurag629 SwinForImageClassification from anurag629
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_anurag629
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_anurag629` is a English model originally trained by anurag629.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_anurag629_en_5.5.1_3.0_1737694350910.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_anurag629_en_5.5.1_3.0_1737694350910.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_anurag629","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_anurag629","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_anurag629|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.5 MB|
+
+## References
+
+https://huggingface.co/anurag629/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_anurag629_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_anurag629_pipeline_en.md
new file mode 100644
index 00000000000000..7141749feea4c4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_anurag629_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_anurag629_pipeline pipeline SwinForImageClassification from anurag629
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_anurag629_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_anurag629_pipeline` is a English model originally trained by anurag629.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_anurag629_pipeline_en_5.5.1_3.0_1737694362833.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_anurag629_pipeline_en_5.5.1_3.0_1737694362833.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_anurag629_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_anurag629_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_anurag629_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.5 MB|
+
+## References
+
+https://huggingface.co/anurag629/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_aullman_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_aullman_en.md
new file mode 100644
index 00000000000000..e8e035e1ae8595
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_aullman_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_aullman SwinForImageClassification from aullman
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_aullman
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_aullman` is a English model originally trained by aullman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_aullman_en_5.5.1_3.0_1737754581191.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_aullman_en_5.5.1_3.0_1737754581191.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_aullman","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_aullman","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_aullman|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/aullman/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_aullman_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_aullman_pipeline_en.md
new file mode 100644
index 00000000000000..94845a4c2f6ebd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_aullman_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_aullman_pipeline pipeline SwinForImageClassification from aullman
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_aullman_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_aullman_pipeline` is a English model originally trained by aullman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_aullman_pipeline_en_5.5.1_3.0_1737754592859.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_aullman_pipeline_en_5.5.1_3.0_1737754592859.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_aullman_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_aullman_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_aullman_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/aullman/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_aziiiiiiiiz_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_aziiiiiiiiz_en.md
new file mode 100644
index 00000000000000..99470e9de64137
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_aziiiiiiiiz_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_aziiiiiiiiz SwinForImageClassification from AZIIIIIIIIZ
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_aziiiiiiiiz
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_aziiiiiiiiz` is a English model originally trained by AZIIIIIIIIZ.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_aziiiiiiiiz_en_5.5.1_3.0_1737714826016.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_aziiiiiiiiz_en_5.5.1_3.0_1737714826016.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_aziiiiiiiiz","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_aziiiiiiiiz","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_aziiiiiiiiz|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/AZIIIIIIIIZ/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_aziiiiiiiiz_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_aziiiiiiiiz_pipeline_en.md
new file mode 100644
index 00000000000000..d8fb46af3e0970
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_aziiiiiiiiz_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_aziiiiiiiiz_pipeline pipeline SwinForImageClassification from AZIIIIIIIIZ
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_aziiiiiiiiz_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_aziiiiiiiiz_pipeline` is a English model originally trained by AZIIIIIIIIZ.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_aziiiiiiiiz_pipeline_en_5.5.1_3.0_1737714837481.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_aziiiiiiiiz_pipeline_en_5.5.1_3.0_1737714837481.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_aziiiiiiiiz_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_aziiiiiiiiz_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_aziiiiiiiiz_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/AZIIIIIIIIZ/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_bbrenes_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_bbrenes_en.md
new file mode 100644
index 00000000000000..3a572461e2c9d9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_bbrenes_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_bbrenes SwinForImageClassification from bbrenes
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_bbrenes
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_bbrenes` is a English model originally trained by bbrenes.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_bbrenes_en_5.5.1_3.0_1737694008185.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_bbrenes_en_5.5.1_3.0_1737694008185.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_bbrenes","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_bbrenes","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_bbrenes|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/bbrenes/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_bbrenes_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_bbrenes_pipeline_en.md
new file mode 100644
index 00000000000000..8f7acb8ef37b15
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_bbrenes_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_bbrenes_pipeline pipeline SwinForImageClassification from bbrenes
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_bbrenes_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_bbrenes_pipeline` is a English model originally trained by bbrenes.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_bbrenes_pipeline_en_5.5.1_3.0_1737694019072.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_bbrenes_pipeline_en_5.5.1_3.0_1737694019072.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_bbrenes_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_bbrenes_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_bbrenes_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/bbrenes/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_bmedeiros_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_bmedeiros_en.md
new file mode 100644
index 00000000000000..a367eb86409f4e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_bmedeiros_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_bmedeiros SwinForImageClassification from bmedeiros
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_bmedeiros
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_bmedeiros` is a English model originally trained by bmedeiros.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_bmedeiros_en_5.5.1_3.0_1737754273798.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_bmedeiros_en_5.5.1_3.0_1737754273798.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_bmedeiros","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_bmedeiros","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_bmedeiros|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/bmedeiros/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_bmedeiros_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_bmedeiros_pipeline_en.md
new file mode 100644
index 00000000000000..c8fcccd51bf8f9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_bmedeiros_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_bmedeiros_pipeline pipeline SwinForImageClassification from bmedeiros
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_bmedeiros_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_bmedeiros_pipeline` is a English model originally trained by bmedeiros.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_bmedeiros_pipeline_en_5.5.1_3.0_1737754285139.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_bmedeiros_pipeline_en_5.5.1_3.0_1737754285139.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_bmedeiros_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_bmedeiros_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_bmedeiros_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/bmedeiros/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_djoels_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_djoels_en.md
new file mode 100644
index 00000000000000..a8b6e7940d79c5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_djoels_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_djoels SwinForImageClassification from djoels
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_djoels
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_djoels` is a English model originally trained by djoels.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_djoels_en_5.5.1_3.0_1737762664547.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_djoels_en_5.5.1_3.0_1737762664547.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_djoels","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_djoels","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_djoels|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/djoels/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_djoels_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_djoels_pipeline_en.md
new file mode 100644
index 00000000000000..0649523db90dcf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_djoels_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_djoels_pipeline pipeline SwinForImageClassification from djoels
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_djoels_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_djoels_pipeline` is a English model originally trained by djoels.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_djoels_pipeline_en_5.5.1_3.0_1737762675494.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_djoels_pipeline_en_5.5.1_3.0_1737762675494.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_djoels_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_djoels_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_djoels_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/djoels/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_domasin_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_domasin_en.md
new file mode 100644
index 00000000000000..261649e83c3fcd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_domasin_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_domasin SwinForImageClassification from domasin
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_domasin
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_domasin` is a English model originally trained by domasin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_domasin_en_5.5.1_3.0_1737762310188.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_domasin_en_5.5.1_3.0_1737762310188.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_domasin","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_domasin","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_domasin|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/domasin/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_domasin_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_domasin_pipeline_en.md
new file mode 100644
index 00000000000000..fd1336d2372876
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_domasin_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_domasin_pipeline pipeline SwinForImageClassification from domasin
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_domasin_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_domasin_pipeline` is a English model originally trained by domasin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_domasin_pipeline_en_5.5.1_3.0_1737762321649.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_domasin_pipeline_en_5.5.1_3.0_1737762321649.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_domasin_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_domasin_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_domasin_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/domasin/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_erikejw_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_erikejw_en.md
new file mode 100644
index 00000000000000..56129b20f13a81
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_erikejw_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_erikejw SwinForImageClassification from erikejw
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_erikejw
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_erikejw` is a English model originally trained by erikejw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_erikejw_en_5.5.1_3.0_1737762237864.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_erikejw_en_5.5.1_3.0_1737762237864.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_erikejw","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_erikejw","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_erikejw|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/erikejw/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_erikejw_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_erikejw_pipeline_en.md
new file mode 100644
index 00000000000000..25dc8f56a80084
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_erikejw_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_erikejw_pipeline pipeline SwinForImageClassification from erikejw
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_erikejw_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_erikejw_pipeline` is a English model originally trained by erikejw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_erikejw_pipeline_en_5.5.1_3.0_1737762250977.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_erikejw_pipeline_en_5.5.1_3.0_1737762250977.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_erikejw_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_erikejw_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_erikejw_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/erikejw/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_firedfrog_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_firedfrog_en.md
new file mode 100644
index 00000000000000..2ad4e6872f11d4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_firedfrog_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_firedfrog SwinForImageClassification from firedfrog
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_firedfrog
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_firedfrog` is a English model originally trained by firedfrog.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_firedfrog_en_5.5.1_3.0_1737754692482.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_firedfrog_en_5.5.1_3.0_1737754692482.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_firedfrog","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_firedfrog","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_firedfrog|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/firedfrog/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_firedfrog_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_firedfrog_pipeline_en.md
new file mode 100644
index 00000000000000..f86395ce3c16b4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_firedfrog_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_firedfrog_pipeline pipeline SwinForImageClassification from firedfrog
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_firedfrog_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_firedfrog_pipeline` is a English model originally trained by firedfrog.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_firedfrog_pipeline_en_5.5.1_3.0_1737754703848.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_firedfrog_pipeline_en_5.5.1_3.0_1737754703848.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_firedfrog_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_firedfrog_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_firedfrog_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/firedfrog/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_frank0930_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_frank0930_en.md
new file mode 100644
index 00000000000000..70126f8ffa005e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_frank0930_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_frank0930 SwinForImageClassification from Frank0930
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_frank0930
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_frank0930` is a English model originally trained by Frank0930.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_frank0930_en_5.5.1_3.0_1737694483618.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_frank0930_en_5.5.1_3.0_1737694483618.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_frank0930","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_frank0930","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_frank0930|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/Frank0930/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_frank0930_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_frank0930_pipeline_en.md
new file mode 100644
index 00000000000000..781e18ff4c7c23
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_frank0930_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_frank0930_pipeline pipeline SwinForImageClassification from Frank0930
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_frank0930_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_frank0930_pipeline` is a English model originally trained by Frank0930.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_frank0930_pipeline_en_5.5.1_3.0_1737694494922.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_frank0930_pipeline_en_5.5.1_3.0_1737694494922.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_frank0930_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_frank0930_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_frank0930_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/Frank0930/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_hekmattaherinejad_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_hekmattaherinejad_en.md
new file mode 100644
index 00000000000000..4cc78bb7bb3a3d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_hekmattaherinejad_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_hekmattaherinejad SwinForImageClassification from HekmatTaherinejad
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_hekmattaherinejad
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_hekmattaherinejad` is a English model originally trained by HekmatTaherinejad.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_hekmattaherinejad_en_5.5.1_3.0_1737762237894.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_hekmattaherinejad_en_5.5.1_3.0_1737762237894.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_hekmattaherinejad","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_hekmattaherinejad","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_hekmattaherinejad|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/HekmatTaherinejad/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_hekmattaherinejad_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_hekmattaherinejad_pipeline_en.md
new file mode 100644
index 00000000000000..d78269f8d4bf23
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_hekmattaherinejad_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_hekmattaherinejad_pipeline pipeline SwinForImageClassification from HekmatTaherinejad
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_hekmattaherinejad_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_hekmattaherinejad_pipeline` is a English model originally trained by HekmatTaherinejad.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_hekmattaherinejad_pipeline_en_5.5.1_3.0_1737762249957.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_hekmattaherinejad_pipeline_en_5.5.1_3.0_1737762249957.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_hekmattaherinejad_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_hekmattaherinejad_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_hekmattaherinejad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/HekmatTaherinejad/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_heroza_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_heroza_en.md
new file mode 100644
index 00000000000000..2b1ff1903b6135
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_heroza_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_heroza SwinForImageClassification from heroza
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_heroza
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_heroza` is a English model originally trained by heroza.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_heroza_en_5.5.1_3.0_1737694110493.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_heroza_en_5.5.1_3.0_1737694110493.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_heroza","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_heroza","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_heroza|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/heroza/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_heroza_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_heroza_pipeline_en.md
new file mode 100644
index 00000000000000..69d55d0170bdd7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_heroza_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_heroza_pipeline pipeline SwinForImageClassification from heroza
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_heroza_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_heroza_pipeline` is a English model originally trained by heroza.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_heroza_pipeline_en_5.5.1_3.0_1737694122001.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_heroza_pipeline_en_5.5.1_3.0_1737694122001.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_heroza_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_heroza_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_heroza_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/heroza/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_jemole_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_jemole_en.md
new file mode 100644
index 00000000000000..d60713640aef31
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_jemole_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_jemole SwinForImageClassification from jemole
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_jemole
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_jemole` is a English model originally trained by jemole.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_jemole_en_5.5.1_3.0_1737762420865.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_jemole_en_5.5.1_3.0_1737762420865.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_jemole","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_jemole","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_jemole|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/jemole/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_jemole_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_jemole_pipeline_en.md
new file mode 100644
index 00000000000000..c2482b06e798cf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_jemole_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_jemole_pipeline pipeline SwinForImageClassification from jemole
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_jemole_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_jemole_pipeline` is a English model originally trained by jemole.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_jemole_pipeline_en_5.5.1_3.0_1737762432239.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_jemole_pipeline_en_5.5.1_3.0_1737762432239.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_jemole_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_jemole_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_jemole_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/jemole/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_jthetzel_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_jthetzel_en.md
new file mode 100644
index 00000000000000..fd7e234d787164
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_jthetzel_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_jthetzel SwinForImageClassification from jthetzel
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_jthetzel
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_jthetzel` is a English model originally trained by jthetzel.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_jthetzel_en_5.5.1_3.0_1737715437294.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_jthetzel_en_5.5.1_3.0_1737715437294.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_jthetzel","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_jthetzel","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_jthetzel|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/jthetzel/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_jthetzel_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_jthetzel_pipeline_en.md
new file mode 100644
index 00000000000000..a2778791caaaea
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_jthetzel_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_jthetzel_pipeline pipeline SwinForImageClassification from jthetzel
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_jthetzel_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_jthetzel_pipeline` is a English model originally trained by jthetzel.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_jthetzel_pipeline_en_5.5.1_3.0_1737715448565.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_jthetzel_pipeline_en_5.5.1_3.0_1737715448565.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_jthetzel_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_jthetzel_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_jthetzel_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/jthetzel/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_kclee111_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_kclee111_en.md
new file mode 100644
index 00000000000000..d2197685bc2b8a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_kclee111_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_kclee111 SwinForImageClassification from kclee111
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_kclee111
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_kclee111` is a English model originally trained by kclee111.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_kclee111_en_5.5.1_3.0_1737715342524.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_kclee111_en_5.5.1_3.0_1737715342524.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_kclee111","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_kclee111","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_kclee111|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/kclee111/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_kclee111_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_kclee111_pipeline_en.md
new file mode 100644
index 00000000000000..4c36c7ad399072
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_kclee111_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_kclee111_pipeline pipeline SwinForImageClassification from kclee111
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_kclee111_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_kclee111_pipeline` is a English model originally trained by kclee111.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_kclee111_pipeline_en_5.5.1_3.0_1737715353551.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_kclee111_pipeline_en_5.5.1_3.0_1737715353551.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_kclee111_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_kclee111_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_kclee111_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/kclee111/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_kornia_ani7772_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_kornia_ani7772_en.md
new file mode 100644
index 00000000000000..b46a04eb4ede17
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_kornia_ani7772_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_kornia_ani7772 SwinForImageClassification from Ani7772
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_kornia_ani7772
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_kornia_ani7772` is a English model originally trained by Ani7772.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_kornia_ani7772_en_5.5.1_3.0_1737715491196.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_kornia_ani7772_en_5.5.1_3.0_1737715491196.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_kornia_ani7772","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_kornia_ani7772","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_kornia_ani7772|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/Ani7772/swin-tiny-patch4-window7-224-finetuned-eurosat-kornia
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_kornia_ani7772_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_kornia_ani7772_pipeline_en.md
new file mode 100644
index 00000000000000..5e783e594886c0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_kornia_ani7772_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_kornia_ani7772_pipeline pipeline SwinForImageClassification from Ani7772
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_kornia_ani7772_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_kornia_ani7772_pipeline` is a English model originally trained by Ani7772.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_kornia_ani7772_pipeline_en_5.5.1_3.0_1737715502194.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_kornia_ani7772_pipeline_en_5.5.1_3.0_1737715502194.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_kornia_ani7772_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_kornia_ani7772_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_kornia_ani7772_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/Ani7772/swin-tiny-patch4-window7-224-finetuned-eurosat-kornia
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_lelel_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_lelel_en.md
new file mode 100644
index 00000000000000..fe238e4abdf2a3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_lelel_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_lelel SwinForImageClassification from LeLeL
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_lelel
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_lelel` is a English model originally trained by LeLeL.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_lelel_en_5.5.1_3.0_1737762345857.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_lelel_en_5.5.1_3.0_1737762345857.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_lelel","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_lelel","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_lelel|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/LeLeL/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_lelel_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_lelel_pipeline_en.md
new file mode 100644
index 00000000000000..df693e3ff272d4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_lelel_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_lelel_pipeline pipeline SwinForImageClassification from LeLeL
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_lelel_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_lelel_pipeline` is a English model originally trained by LeLeL.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_lelel_pipeline_en_5.5.1_3.0_1737762358232.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_lelel_pipeline_en_5.5.1_3.0_1737762358232.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_lelel_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_lelel_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_lelel_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/LeLeL/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_macanoso_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_macanoso_en.md
new file mode 100644
index 00000000000000..1debf4330c7a79
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_macanoso_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_macanoso SwinForImageClassification from macanoso
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_macanoso
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_macanoso` is a English model originally trained by macanoso.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_macanoso_en_5.5.1_3.0_1737763065405.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_macanoso_en_5.5.1_3.0_1737763065405.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_macanoso","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_macanoso","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_macanoso|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/macanoso/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_macanoso_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_macanoso_pipeline_en.md
new file mode 100644
index 00000000000000..4d224422042018
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_macanoso_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_macanoso_pipeline pipeline SwinForImageClassification from macanoso
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_macanoso_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_macanoso_pipeline` is a English model originally trained by macanoso.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_macanoso_pipeline_en_5.5.1_3.0_1737763076870.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_macanoso_pipeline_en_5.5.1_3.0_1737763076870.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_macanoso_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_macanoso_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_macanoso_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/macanoso/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_mansee_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_mansee_en.md
new file mode 100644
index 00000000000000..ec2f95e6e70064
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_mansee_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_mansee SwinForImageClassification from mansee
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_mansee
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_mansee` is a English model originally trained by mansee.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_mansee_en_5.5.1_3.0_1737715614909.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_mansee_en_5.5.1_3.0_1737715614909.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_mansee","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_mansee","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_mansee|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/mansee/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_mansee_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_mansee_pipeline_en.md
new file mode 100644
index 00000000000000..4c0a34ebc4ca77
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_mansee_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_mansee_pipeline pipeline SwinForImageClassification from mansee
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_mansee_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_mansee_pipeline` is a English model originally trained by mansee.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_mansee_pipeline_en_5.5.1_3.0_1737715625776.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_mansee_pipeline_en_5.5.1_3.0_1737715625776.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_mansee_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_mansee_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_mansee_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/mansee/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_minhhoque_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_minhhoque_en.md
new file mode 100644
index 00000000000000..5c9dc2d7b28680
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_minhhoque_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_minhhoque SwinForImageClassification from minhhoque
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_minhhoque
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_minhhoque` is a English model originally trained by minhhoque.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_minhhoque_en_5.5.1_3.0_1737762761588.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_minhhoque_en_5.5.1_3.0_1737762761588.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_minhhoque","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_minhhoque","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_minhhoque|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/minhhoque/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_minhhoque_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_minhhoque_pipeline_en.md
new file mode 100644
index 00000000000000..f863582da610d4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_minhhoque_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_minhhoque_pipeline pipeline SwinForImageClassification from minhhoque
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_minhhoque_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_minhhoque_pipeline` is a English model originally trained by minhhoque.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_minhhoque_pipeline_en_5.5.1_3.0_1737762772614.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_minhhoque_pipeline_en_5.5.1_3.0_1737762772614.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_minhhoque_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_minhhoque_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_minhhoque_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/minhhoque/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_obivine_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_obivine_en.md
new file mode 100644
index 00000000000000..8769cedb3b3563
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_obivine_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_obivine SwinForImageClassification from obivine
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_obivine
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_obivine` is a English model originally trained by obivine.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_obivine_en_5.5.1_3.0_1737714825750.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_obivine_en_5.5.1_3.0_1737714825750.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_obivine","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_obivine","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_obivine|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/obivine/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_obivine_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_obivine_pipeline_en.md
new file mode 100644
index 00000000000000..47ba5e6beb432b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_obivine_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_obivine_pipeline pipeline SwinForImageClassification from obivine
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_obivine_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_obivine_pipeline` is a English model originally trained by obivine.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_obivine_pipeline_en_5.5.1_3.0_1737714843386.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_obivine_pipeline_en_5.5.1_3.0_1737714843386.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_obivine_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_obivine_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_obivine_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/obivine/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_omidmns_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_omidmns_en.md
new file mode 100644
index 00000000000000..e3b9108d424a66
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_omidmns_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_omidmns SwinForImageClassification from omidmns
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_omidmns
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_omidmns` is a English model originally trained by omidmns.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_omidmns_en_5.5.1_3.0_1737715521637.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_omidmns_en_5.5.1_3.0_1737715521637.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_omidmns","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_omidmns","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_omidmns|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/omidmns/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_omidmns_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_omidmns_pipeline_en.md
new file mode 100644
index 00000000000000..9833e36124ccde
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_omidmns_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_omidmns_pipeline pipeline SwinForImageClassification from omidmns
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_omidmns_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_omidmns_pipeline` is a English model originally trained by omidmns.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_omidmns_pipeline_en_5.5.1_3.0_1737715532907.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_omidmns_pipeline_en_5.5.1_3.0_1737715532907.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_omidmns_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_omidmns_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_omidmns_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/omidmns/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_ravenonur_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_ravenonur_en.md
new file mode 100644
index 00000000000000..7217c40e8ea8a7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_ravenonur_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_ravenonur SwinForImageClassification from RavenOnur
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_ravenonur
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_ravenonur` is a English model originally trained by RavenOnur.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_ravenonur_en_5.5.1_3.0_1737762559114.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_ravenonur_en_5.5.1_3.0_1737762559114.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_ravenonur","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_ravenonur","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_ravenonur|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/RavenOnur/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_ravenonur_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_ravenonur_pipeline_en.md
new file mode 100644
index 00000000000000..d8b81747a5bccf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_ravenonur_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_ravenonur_pipeline pipeline SwinForImageClassification from RavenOnur
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_ravenonur_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_ravenonur_pipeline` is a English model originally trained by RavenOnur.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_ravenonur_pipeline_en_5.5.1_3.0_1737762570285.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_ravenonur_pipeline_en_5.5.1_3.0_1737762570285.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_ravenonur_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_ravenonur_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_ravenonur_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/RavenOnur/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_schoenml_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_schoenml_en.md
new file mode 100644
index 00000000000000..fe721756a70c3c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_schoenml_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_schoenml SwinForImageClassification from schoenml
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_schoenml
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_schoenml` is a English model originally trained by schoenml.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_schoenml_en_5.5.1_3.0_1737762537996.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_schoenml_en_5.5.1_3.0_1737762537996.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_schoenml","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_schoenml","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_schoenml|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/schoenml/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_schoenml_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_schoenml_pipeline_en.md
new file mode 100644
index 00000000000000..3db2a4091e3fc9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_schoenml_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_schoenml_pipeline pipeline SwinForImageClassification from schoenml
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_schoenml_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_schoenml_pipeline` is a English model originally trained by schoenml.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_schoenml_pipeline_en_5.5.1_3.0_1737762549670.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_schoenml_pipeline_en_5.5.1_3.0_1737762549670.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_schoenml_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_schoenml_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_schoenml_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/schoenml/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_sean83_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_sean83_en.md
new file mode 100644
index 00000000000000..333b3e040709ff
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_sean83_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_sean83 SwinForImageClassification from Sean83
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_sean83
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_sean83` is a English model originally trained by Sean83.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_sean83_en_5.5.1_3.0_1737694424113.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_sean83_en_5.5.1_3.0_1737694424113.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_sean83","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_sean83","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_sean83|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/Sean83/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_sean83_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_sean83_pipeline_en.md
new file mode 100644
index 00000000000000..a9ac09dba4fe38
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_sean83_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_sean83_pipeline pipeline SwinForImageClassification from Sean83
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_sean83_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_sean83_pipeline` is a English model originally trained by Sean83.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_sean83_pipeline_en_5.5.1_3.0_1737694435326.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_sean83_pipeline_en_5.5.1_3.0_1737694435326.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_sean83_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_sean83_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_sean83_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/Sean83/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_suredream_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_suredream_en.md
new file mode 100644
index 00000000000000..36284162697495
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_suredream_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_suredream SwinForImageClassification from suredream
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_suredream
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_suredream` is a English model originally trained by suredream.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_suredream_en_5.5.1_3.0_1737763189492.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_suredream_en_5.5.1_3.0_1737763189492.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_suredream","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_suredream","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_suredream|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/suredream/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_swayampragnya_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_swayampragnya_en.md
new file mode 100644
index 00000000000000..07fa119fe57e78
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_swayampragnya_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_swayampragnya SwinForImageClassification from swayampragnya
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_swayampragnya
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_swayampragnya` is a English model originally trained by swayampragnya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_swayampragnya_en_5.5.1_3.0_1737694342743.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_swayampragnya_en_5.5.1_3.0_1737694342743.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_swayampragnya","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_swayampragnya","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_swayampragnya|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/swayampragnya/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_swayampragnya_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_swayampragnya_pipeline_en.md
new file mode 100644
index 00000000000000..8ccb282f3afd5d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_swayampragnya_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_swayampragnya_pipeline pipeline SwinForImageClassification from swayampragnya
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_swayampragnya_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_swayampragnya_pipeline` is a English model originally trained by swayampragnya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_swayampragnya_pipeline_en_5.5.1_3.0_1737694354464.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_swayampragnya_pipeline_en_5.5.1_3.0_1737694354464.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_swayampragnya_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_swayampragnya_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_swayampragnya_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/swayampragnya/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_sybghat_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_sybghat_en.md
new file mode 100644
index 00000000000000..443b498331d489
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_sybghat_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_sybghat SwinForImageClassification from Sybghat
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_sybghat
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_sybghat` is a English model originally trained by Sybghat.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_sybghat_en_5.5.1_3.0_1737762699939.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_sybghat_en_5.5.1_3.0_1737762699939.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_sybghat","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_sybghat","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_sybghat|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/Sybghat/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_sybghat_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_sybghat_pipeline_en.md
new file mode 100644
index 00000000000000..99c6ccc2af2019
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_sybghat_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_sybghat_pipeline pipeline SwinForImageClassification from Sybghat
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_sybghat_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_sybghat_pipeline` is a English model originally trained by Sybghat.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_sybghat_pipeline_en_5.5.1_3.0_1737762710120.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_sybghat_pipeline_en_5.5.1_3.0_1737762710120.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_sybghat_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_sybghat_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_sybghat_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/Sybghat/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_t1msan_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_t1msan_en.md
new file mode 100644
index 00000000000000..a93066700f82cf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_t1msan_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_t1msan SwinForImageClassification from t1msan
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_t1msan
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_t1msan` is a English model originally trained by t1msan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_t1msan_en_5.5.1_3.0_1737714937496.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_t1msan_en_5.5.1_3.0_1737714937496.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_t1msan","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_t1msan","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_t1msan|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/t1msan/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_t1msan_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_t1msan_pipeline_en.md
new file mode 100644
index 00000000000000..03e7301a69d7af
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_t1msan_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_t1msan_pipeline pipeline SwinForImageClassification from t1msan
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_t1msan_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_t1msan_pipeline` is a English model originally trained by t1msan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_t1msan_pipeline_en_5.5.1_3.0_1737714949342.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_t1msan_pipeline_en_5.5.1_3.0_1737714949342.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_t1msan_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_t1msan_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_t1msan_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/t1msan/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_tastyos_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_tastyos_en.md
new file mode 100644
index 00000000000000..caa125aa9e1e23
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_tastyos_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_tastyos SwinForImageClassification from TastyOs
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_tastyos
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_tastyos` is a English model originally trained by TastyOs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_tastyos_en_5.5.1_3.0_1737762438416.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_tastyos_en_5.5.1_3.0_1737762438416.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_tastyos","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_tastyos","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_tastyos|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/TastyOs/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_tastyos_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_tastyos_pipeline_en.md
new file mode 100644
index 00000000000000..572e2370987401
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_tastyos_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_tastyos_pipeline pipeline SwinForImageClassification from TastyOs
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_tastyos_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_tastyos_pipeline` is a English model originally trained by TastyOs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_tastyos_pipeline_en_5.5.1_3.0_1737762455117.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_tastyos_pipeline_en_5.5.1_3.0_1737762455117.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_tastyos_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_tastyos_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_tastyos_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/TastyOs/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_tea_cup_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_tea_cup_en.md
new file mode 100644
index 00000000000000..33356a18c6fba3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_tea_cup_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_tea_cup SwinForImageClassification from tea-cup
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_tea_cup
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_tea_cup` is a English model originally trained by tea-cup.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_tea_cup_en_5.5.1_3.0_1737693898067.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_tea_cup_en_5.5.1_3.0_1737693898067.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_tea_cup","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_tea_cup","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_tea_cup|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/tea-cup/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_tea_cup_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_tea_cup_pipeline_en.md
new file mode 100644
index 00000000000000..cdb96f245ca75d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_tea_cup_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_tea_cup_pipeline pipeline SwinForImageClassification from tea-cup
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_tea_cup_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_tea_cup_pipeline` is a English model originally trained by tea-cup.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_tea_cup_pipeline_en_5.5.1_3.0_1737693911950.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_tea_cup_pipeline_en_5.5.1_3.0_1737693911950.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_tea_cup_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_tea_cup_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_tea_cup_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/tea-cup/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_vintage_lavender619_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_vintage_lavender619_en.md
new file mode 100644
index 00000000000000..c22f6350b9fad9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_vintage_lavender619_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_vintage_lavender619 SwinForImageClassification from vintage-lavender619
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_vintage_lavender619
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_vintage_lavender619` is a English model originally trained by vintage-lavender619.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_vintage_lavender619_en_5.5.1_3.0_1737754768414.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_vintage_lavender619_en_5.5.1_3.0_1737754768414.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_vintage_lavender619","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_vintage_lavender619","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_vintage_lavender619|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|212.1 MB|
+
+## References
+
+https://huggingface.co/vintage-lavender619/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_vintage_lavender619_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_vintage_lavender619_pipeline_en.md
new file mode 100644
index 00000000000000..a6b53900455366
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_vintage_lavender619_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_vintage_lavender619_pipeline pipeline SwinForImageClassification from vintage-lavender619
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_vintage_lavender619_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_vintage_lavender619_pipeline` is a English model originally trained by vintage-lavender619.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_vintage_lavender619_pipeline_en_5.5.1_3.0_1737754780561.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_vintage_lavender619_pipeline_en_5.5.1_3.0_1737754780561.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_vintage_lavender619_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_vintage_lavender619_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_vintage_lavender619_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|212.1 MB|
+
+## References
+
+https://huggingface.co/vintage-lavender619/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_weili_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_weili_en.md
new file mode 100644
index 00000000000000..48eeb20189d05d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_weili_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_weili SwinForImageClassification from Weili
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_weili
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_weili` is a English model originally trained by Weili.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_weili_en_5.5.1_3.0_1737762767795.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_weili_en_5.5.1_3.0_1737762767795.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_weili","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_weili","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_weili|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/Weili/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_weili_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_weili_pipeline_en.md
new file mode 100644
index 00000000000000..01f099b9ae6c83
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_weili_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_weili_pipeline pipeline SwinForImageClassification from Weili
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_weili_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_weili_pipeline` is a English model originally trained by Weili.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_weili_pipeline_en_5.5.1_3.0_1737762781448.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_weili_pipeline_en_5.5.1_3.0_1737762781448.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_weili_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_weili_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_weili_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/Weili/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_xihaad_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_xihaad_en.md
new file mode 100644
index 00000000000000..279d501dd6c474
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_xihaad_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_xihaad SwinForImageClassification from xihaad
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_xihaad
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_xihaad` is a English model originally trained by xihaad.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_xihaad_en_5.5.1_3.0_1737694571967.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_xihaad_en_5.5.1_3.0_1737694571967.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_xihaad","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_xihaad","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_xihaad|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/xihaad/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_xihaad_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_xihaad_pipeline_en.md
new file mode 100644
index 00000000000000..40b29925218b55
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_xihaad_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_xihaad_pipeline pipeline SwinForImageClassification from xihaad
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_xihaad_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_xihaad_pipeline` is a English model originally trained by xihaad.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_xihaad_pipeline_en_5.5.1_3.0_1737694583924.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_xihaad_pipeline_en_5.5.1_3.0_1737694583924.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_xihaad_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_xihaad_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_xihaad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/xihaad/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_yakirhasid_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_yakirhasid_en.md
new file mode 100644
index 00000000000000..b5f00d93c8a79d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_yakirhasid_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_yakirhasid SwinForImageClassification from YakirHasid
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_yakirhasid
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_yakirhasid` is a English model originally trained by YakirHasid.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_yakirhasid_en_5.5.1_3.0_1737754635619.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_yakirhasid_en_5.5.1_3.0_1737754635619.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_yakirhasid","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_yakirhasid","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_yakirhasid|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/YakirHasid/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_yakirhasid_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_yakirhasid_pipeline_en.md
new file mode 100644
index 00000000000000..5c23d189ba6023
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_yakirhasid_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_yakirhasid_pipeline pipeline SwinForImageClassification from YakirHasid
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_yakirhasid_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_yakirhasid_pipeline` is a English model originally trained by YakirHasid.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_yakirhasid_pipeline_en_5.5.1_3.0_1737754649595.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_yakirhasid_pipeline_en_5.5.1_3.0_1737754649595.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_yakirhasid_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_yakirhasid_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_yakirhasid_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/YakirHasid/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_zkdeng_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_zkdeng_en.md
new file mode 100644
index 00000000000000..65227310cad0bc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_zkdeng_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_zkdeng SwinForImageClassification from zkdeng
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_zkdeng
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_zkdeng` is a English model originally trained by zkdeng.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_zkdeng_en_5.5.1_3.0_1737694085798.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_zkdeng_en_5.5.1_3.0_1737694085798.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_zkdeng","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_zkdeng","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_zkdeng|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/zkdeng/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_zkdeng_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_zkdeng_pipeline_en.md
new file mode 100644
index 00000000000000..22772350b979f2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_zkdeng_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_zkdeng_pipeline pipeline SwinForImageClassification from zkdeng
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_zkdeng_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_zkdeng_pipeline` is a English model originally trained by zkdeng.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_zkdeng_pipeline_en_5.5.1_3.0_1737694096939.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_zkdeng_pipeline_en_5.5.1_3.0_1737694096939.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_zkdeng_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_zkdeng_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_zkdeng_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/zkdeng/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_zweehn_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_zweehn_en.md
new file mode 100644
index 00000000000000..0d3a0f8ea7da52
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_zweehn_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_zweehn SwinForImageClassification from Zweehn
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_zweehn
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_zweehn` is a English model originally trained by Zweehn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_zweehn_en_5.5.1_3.0_1737754423951.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_zweehn_en_5.5.1_3.0_1737754423951.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_zweehn","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_zweehn","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_zweehn|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/Zweehn/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_zweehn_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_zweehn_pipeline_en.md
new file mode 100644
index 00000000000000..089944bc509536
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_eurosat_zweehn_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_zweehn_pipeline pipeline SwinForImageClassification from Zweehn
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_zweehn_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_zweehn_pipeline` is a English model originally trained by Zweehn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_zweehn_pipeline_en_5.5.1_3.0_1737754435360.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_zweehn_pipeline_en_5.5.1_3.0_1737754435360.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_zweehn_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_zweehn_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_zweehn_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/Zweehn/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_fish_nandinilokeshreddy_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_fish_nandinilokeshreddy_en.md
new file mode 100644
index 00000000000000..9a347bab005530
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_fish_nandinilokeshreddy_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_fish_nandinilokeshreddy SwinForImageClassification from NandiniLokeshReddy
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_fish_nandinilokeshreddy
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_fish_nandinilokeshreddy` is a English model originally trained by NandiniLokeshReddy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_fish_nandinilokeshreddy_en_5.5.1_3.0_1737694237903.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_fish_nandinilokeshreddy_en_5.5.1_3.0_1737694237903.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_fish_nandinilokeshreddy","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_fish_nandinilokeshreddy","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_fish_nandinilokeshreddy|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/NandiniLokeshReddy/swin-tiny-patch4-window7-224-finetuned-fish
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_fish_nandinilokeshreddy_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_fish_nandinilokeshreddy_pipeline_en.md
new file mode 100644
index 00000000000000..5051a92ce033a1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_fish_nandinilokeshreddy_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_fish_nandinilokeshreddy_pipeline pipeline SwinForImageClassification from NandiniLokeshReddy
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_fish_nandinilokeshreddy_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_fish_nandinilokeshreddy_pipeline` is a English model originally trained by NandiniLokeshReddy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_fish_nandinilokeshreddy_pipeline_en_5.5.1_3.0_1737694248985.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_fish_nandinilokeshreddy_pipeline_en_5.5.1_3.0_1737694248985.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_fish_nandinilokeshreddy_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_fish_nandinilokeshreddy_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_fish_nandinilokeshreddy_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/NandiniLokeshReddy/swin-tiny-patch4-window7-224-finetuned-fish
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_herbify2_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_herbify2_en.md
new file mode 100644
index 00000000000000..a5aa23bcbbbd66
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_herbify2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_herbify2 SwinForImageClassification from purabp1249
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_herbify2
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_herbify2` is a English model originally trained by purabp1249.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_herbify2_en_5.5.1_3.0_1737714825453.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_herbify2_en_5.5.1_3.0_1737714825453.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_herbify2","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_herbify2","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_herbify2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/purabp1249/swin-tiny-patch4-window7-224-finetuned-herbify2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_herbify2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_herbify2_pipeline_en.md
new file mode 100644
index 00000000000000..f4e14f8e3995b0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_herbify2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_herbify2_pipeline pipeline SwinForImageClassification from purabp1249
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_herbify2_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_herbify2_pipeline` is a English model originally trained by purabp1249.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_herbify2_pipeline_en_5.5.1_3.0_1737714843349.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_herbify2_pipeline_en_5.5.1_3.0_1737714843349.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_herbify2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_herbify2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_herbify2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/purabp1249/swin-tiny-patch4-window7-224-finetuned-herbify2
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_homus_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_homus_en.md
new file mode 100644
index 00000000000000..c19b458975a214
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_homus_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_homus SwinForImageClassification from nadimkanazi
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_homus
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_homus` is a English model originally trained by nadimkanazi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_homus_en_5.5.1_3.0_1737694063633.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_homus_en_5.5.1_3.0_1737694063633.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_homus","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_homus","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_homus|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.5 MB|
+
+## References
+
+https://huggingface.co/nadimkanazi/swin-tiny-patch4-window7-224-finetuned-HOMUS
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_homus_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_homus_pipeline_en.md
new file mode 100644
index 00000000000000..fd7fde5e0e1446
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_homus_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_homus_pipeline pipeline SwinForImageClassification from nadimkanazi
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_homus_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_homus_pipeline` is a English model originally trained by nadimkanazi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_homus_pipeline_en_5.5.1_3.0_1737694075103.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_homus_pipeline_en_5.5.1_3.0_1737694075103.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_homus_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_homus_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_homus_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.5 MB|
+
+## References
+
+https://huggingface.co/nadimkanazi/swin-tiny-patch4-window7-224-finetuned-HOMUS
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_image_icelandic_plot_oriya_not_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_image_icelandic_plot_oriya_not_en.md
new file mode 100644
index 00000000000000..3e3bbf924804b5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_image_icelandic_plot_oriya_not_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_image_icelandic_plot_oriya_not SwinForImageClassification from qzheng75
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_image_icelandic_plot_oriya_not
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_image_icelandic_plot_oriya_not` is a English model originally trained by qzheng75.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_image_icelandic_plot_oriya_not_en_5.5.1_3.0_1737693943117.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_image_icelandic_plot_oriya_not_en_5.5.1_3.0_1737693943117.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_image_icelandic_plot_oriya_not","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_image_icelandic_plot_oriya_not","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_image_icelandic_plot_oriya_not|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/qzheng75/swin-tiny-patch4-window7-224-finetuned-image-is-plot-or-not
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_image_icelandic_plot_oriya_not_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_image_icelandic_plot_oriya_not_pipeline_en.md
new file mode 100644
index 00000000000000..4a2467a0100bb8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_image_icelandic_plot_oriya_not_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_image_icelandic_plot_oriya_not_pipeline pipeline SwinForImageClassification from qzheng75
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_image_icelandic_plot_oriya_not_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_image_icelandic_plot_oriya_not_pipeline` is a English model originally trained by qzheng75.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_image_icelandic_plot_oriya_not_pipeline_en_5.5.1_3.0_1737693954087.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_image_icelandic_plot_oriya_not_pipeline_en_5.5.1_3.0_1737693954087.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_image_icelandic_plot_oriya_not_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_image_icelandic_plot_oriya_not_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_image_icelandic_plot_oriya_not_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/qzheng75/swin-tiny-patch4-window7-224-finetuned-image-is-plot-or-not
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_mobile_eye_tracking_dataset_v2_asad_cse_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_mobile_eye_tracking_dataset_v2_asad_cse_en.md
new file mode 100644
index 00000000000000..d99b18ef305b7d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_mobile_eye_tracking_dataset_v2_asad_cse_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_mobile_eye_tracking_dataset_v2_asad_cse SwinForImageClassification from asad-cse
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_mobile_eye_tracking_dataset_v2_asad_cse
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_mobile_eye_tracking_dataset_v2_asad_cse` is a English model originally trained by asad-cse.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_mobile_eye_tracking_dataset_v2_asad_cse_en_5.5.1_3.0_1737754174455.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_mobile_eye_tracking_dataset_v2_asad_cse_en_5.5.1_3.0_1737754174455.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_mobile_eye_tracking_dataset_v2_asad_cse","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_mobile_eye_tracking_dataset_v2_asad_cse","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_mobile_eye_tracking_dataset_v2_asad_cse|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/asad-cse/swin-tiny-patch4-window7-224-finetuned-mobile-eye-tracking-dataset-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_mobile_eye_tracking_dataset_v2_asad_cse_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_mobile_eye_tracking_dataset_v2_asad_cse_pipeline_en.md
new file mode 100644
index 00000000000000..d51f77834c70d8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_mobile_eye_tracking_dataset_v2_asad_cse_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_mobile_eye_tracking_dataset_v2_asad_cse_pipeline pipeline SwinForImageClassification from asad-cse
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_mobile_eye_tracking_dataset_v2_asad_cse_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_mobile_eye_tracking_dataset_v2_asad_cse_pipeline` is a English model originally trained by asad-cse.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_mobile_eye_tracking_dataset_v2_asad_cse_pipeline_en_5.5.1_3.0_1737754187843.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_mobile_eye_tracking_dataset_v2_asad_cse_pipeline_en_5.5.1_3.0_1737754187843.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_mobile_eye_tracking_dataset_v2_asad_cse_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_mobile_eye_tracking_dataset_v2_asad_cse_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_mobile_eye_tracking_dataset_v2_asad_cse_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/asad-cse/swin-tiny-patch4-window7-224-finetuned-mobile-eye-tracking-dataset-v2
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_mri_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_mri_en.md
new file mode 100644
index 00000000000000..050e816c3c1896
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_mri_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_mri SwinForImageClassification from raedinkhaled
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_mri
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_mri` is a English model originally trained by raedinkhaled.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_mri_en_5.5.1_3.0_1737762344385.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_mri_en_5.5.1_3.0_1737762344385.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_mri","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_mri","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_mri|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/raedinkhaled/swin-tiny-patch4-window7-224-finetuned-mri
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_mri_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_mri_pipeline_en.md
new file mode 100644
index 00000000000000..280a844f6b1f34
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_mri_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_mri_pipeline pipeline SwinForImageClassification from raedinkhaled
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_mri_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_mri_pipeline` is a English model originally trained by raedinkhaled.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_mri_pipeline_en_5.5.1_3.0_1737762355235.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_mri_pipeline_en_5.5.1_3.0_1737762355235.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_mri_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_mri_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_mri_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/raedinkhaled/swin-tiny-patch4-window7-224-finetuned-mri
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_noh_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_noh_en.md
new file mode 100644
index 00000000000000..391b02c174f2c3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_noh_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_noh SwinForImageClassification from hoanbklucky
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_noh
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_noh` is a English model originally trained by hoanbklucky.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_noh_en_5.5.1_3.0_1737754081266.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_noh_en_5.5.1_3.0_1737754081266.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_noh","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_noh","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_noh|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/hoanbklucky/swin-tiny-patch4-window7-224-finetuned-noh
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_noh_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_noh_pipeline_en.md
new file mode 100644
index 00000000000000..921a855ef8c3e0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_noh_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_noh_pipeline pipeline SwinForImageClassification from hoanbklucky
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_noh_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_noh_pipeline` is a English model originally trained by hoanbklucky.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_noh_pipeline_en_5.5.1_3.0_1737754099264.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_noh_pipeline_en_5.5.1_3.0_1737754099264.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_noh_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_noh_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_noh_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/hoanbklucky/swin-tiny-patch4-window7-224-finetuned-noh
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_pe_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_pe_en.md
new file mode 100644
index 00000000000000..a028dddba2476d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_pe_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_pe SwinForImageClassification from navradio
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_pe
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_pe` is a English model originally trained by navradio.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_pe_en_5.5.1_3.0_1737763095841.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_pe_en_5.5.1_3.0_1737763095841.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_pe","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_pe","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_pe|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/navradio/swin-tiny-patch4-window7-224-finetuned-PE
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_pe_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_pe_pipeline_en.md
new file mode 100644
index 00000000000000..5a7d2b72682884
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_pe_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_pe_pipeline pipeline SwinForImageClassification from navradio
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_pe_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_pe_pipeline` is a English model originally trained by navradio.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_pe_pipeline_en_5.5.1_3.0_1737763106562.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_pe_pipeline_en_5.5.1_3.0_1737763106562.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_pe_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_pe_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_pe_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/navradio/swin-tiny-patch4-window7-224-finetuned-PE
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_shotclass_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_shotclass_en.md
new file mode 100644
index 00000000000000..9316581abe0877
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_shotclass_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_shotclass SwinForImageClassification from Manixtox
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_shotclass
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_shotclass` is a English model originally trained by Manixtox.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_shotclass_en_5.5.1_3.0_1737715494342.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_shotclass_en_5.5.1_3.0_1737715494342.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_shotclass","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_shotclass","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_shotclass|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/Manixtox/swin-tiny-patch4-window7-224-finetuned-shotclass
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_shotclass_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_shotclass_pipeline_en.md
new file mode 100644
index 00000000000000..c3d47aad01d514
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_shotclass_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_shotclass_pipeline pipeline SwinForImageClassification from Manixtox
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_shotclass_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_shotclass_pipeline` is a English model originally trained by Manixtox.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_shotclass_pipeline_en_5.5.1_3.0_1737715505619.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_shotclass_pipeline_en_5.5.1_3.0_1737715505619.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_shotclass_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_shotclass_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_shotclass_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/Manixtox/swin-tiny-patch4-window7-224-finetuned-shotclass
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_skin_cancer_isarali_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_skin_cancer_isarali_en.md
new file mode 100644
index 00000000000000..d3087cdd39e69f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_skin_cancer_isarali_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_skin_cancer_isarali SwinForImageClassification from IsaraLi
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_skin_cancer_isarali
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_skin_cancer_isarali` is a English model originally trained by IsaraLi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_skin_cancer_isarali_en_5.5.1_3.0_1737762866087.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_skin_cancer_isarali_en_5.5.1_3.0_1737762866087.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_skin_cancer_isarali","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_skin_cancer_isarali","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_skin_cancer_isarali|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/IsaraLi/swin-tiny-patch4-window7-224-finetuned-skin-cancer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_skin_cancer_isarali_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_skin_cancer_isarali_pipeline_en.md
new file mode 100644
index 00000000000000..decd2970c0187b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_skin_cancer_isarali_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_skin_cancer_isarali_pipeline pipeline SwinForImageClassification from IsaraLi
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_skin_cancer_isarali_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_skin_cancer_isarali_pipeline` is a English model originally trained by IsaraLi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_skin_cancer_isarali_pipeline_en_5.5.1_3.0_1737762877120.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_skin_cancer_isarali_pipeline_en_5.5.1_3.0_1737762877120.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_skin_cancer_isarali_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_skin_cancer_isarali_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_skin_cancer_isarali_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/IsaraLi/swin-tiny-patch4-window7-224-finetuned-skin-cancer
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_southern_sotho_wsdmhar_stacked_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_southern_sotho_wsdmhar_stacked_en.md
new file mode 100644
index 00000000000000..c2309e1dd757ac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_southern_sotho_wsdmhar_stacked_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_southern_sotho_wsdmhar_stacked SwinForImageClassification from ayubkfupm
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_southern_sotho_wsdmhar_stacked
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_southern_sotho_wsdmhar_stacked` is a English model originally trained by ayubkfupm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_southern_sotho_wsdmhar_stacked_en_5.5.1_3.0_1737762508156.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_southern_sotho_wsdmhar_stacked_en_5.5.1_3.0_1737762508156.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_southern_sotho_wsdmhar_stacked","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_southern_sotho_wsdmhar_stacked","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_southern_sotho_wsdmhar_stacked|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/ayubkfupm/swin-tiny-patch4-window7-224-finetuned-st-wsdmhar-stacked
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_southern_sotho_wsdmhar_stacked_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_southern_sotho_wsdmhar_stacked_pipeline_en.md
new file mode 100644
index 00000000000000..d9971f26485304
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_southern_sotho_wsdmhar_stacked_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_southern_sotho_wsdmhar_stacked_pipeline pipeline SwinForImageClassification from ayubkfupm
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_southern_sotho_wsdmhar_stacked_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_southern_sotho_wsdmhar_stacked_pipeline` is a English model originally trained by ayubkfupm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_southern_sotho_wsdmhar_stacked_pipeline_en_5.5.1_3.0_1737762519420.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_southern_sotho_wsdmhar_stacked_pipeline_en_5.5.1_3.0_1737762519420.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_southern_sotho_wsdmhar_stacked_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_southern_sotho_wsdmhar_stacked_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_southern_sotho_wsdmhar_stacked_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/ayubkfupm/swin-tiny-patch4-window7-224-finetuned-st-wsdmhar-stacked
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_woody_140epochs_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_woody_140epochs_en.md
new file mode 100644
index 00000000000000..53638dafe0ca51
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_woody_140epochs_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_woody_140epochs SwinForImageClassification from Alex-VisTas
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_woody_140epochs
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_woody_140epochs` is a English model originally trained by Alex-VisTas.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_woody_140epochs_en_5.5.1_3.0_1737762988041.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_woody_140epochs_en_5.5.1_3.0_1737762988041.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_woody_140epochs","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_woody_140epochs","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_woody_140epochs|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/Alex-VisTas/swin-tiny-patch4-window7-224-finetuned-woody_140epochs
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_woody_140epochs_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_woody_140epochs_pipeline_en.md
new file mode 100644
index 00000000000000..d7f92f5fd0e0b1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_woody_140epochs_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_woody_140epochs_pipeline pipeline SwinForImageClassification from Alex-VisTas
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_woody_140epochs_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_woody_140epochs_pipeline` is a English model originally trained by Alex-VisTas.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_woody_140epochs_pipeline_en_5.5.1_3.0_1737762999298.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_woody_140epochs_pipeline_en_5.5.1_3.0_1737762999298.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_woody_140epochs_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_woody_140epochs_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_woody_140epochs_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/Alex-VisTas/swin-tiny-patch4-window7-224-finetuned-woody_140epochs
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_woody_180epochs_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_woody_180epochs_en.md
new file mode 100644
index 00000000000000..edac5debe1a910
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_woody_180epochs_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_woody_180epochs SwinForImageClassification from Alex-VisTas
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_woody_180epochs
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_woody_180epochs` is a English model originally trained by Alex-VisTas.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_woody_180epochs_en_5.5.1_3.0_1737762895636.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_woody_180epochs_en_5.5.1_3.0_1737762895636.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_woody_180epochs","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_woody_180epochs","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_woody_180epochs|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/Alex-VisTas/swin-tiny-patch4-window7-224-finetuned-woody_180epochs
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_woody_180epochs_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_woody_180epochs_pipeline_en.md
new file mode 100644
index 00000000000000..64aff7e03f0cd1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_finetuned_woody_180epochs_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_woody_180epochs_pipeline pipeline SwinForImageClassification from Alex-VisTas
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_woody_180epochs_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_woody_180epochs_pipeline` is a English model originally trained by Alex-VisTas.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_woody_180epochs_pipeline_en_5.5.1_3.0_1737762906727.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_woody_180epochs_pipeline_en_5.5.1_3.0_1737762906727.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_woody_180epochs_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_woody_180epochs_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_woody_180epochs_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/Alex-VisTas/swin-tiny-patch4-window7-224-finetuned-woody_180epochs
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_ft_mango_leaf_disease_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_ft_mango_leaf_disease_en.md
new file mode 100644
index 00000000000000..992bc282124d3b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_ft_mango_leaf_disease_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_ft_mango_leaf_disease SwinForImageClassification from juniorjukeko
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_ft_mango_leaf_disease
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_ft_mango_leaf_disease` is a English model originally trained by juniorjukeko.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_ft_mango_leaf_disease_en_5.5.1_3.0_1737754251032.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_ft_mango_leaf_disease_en_5.5.1_3.0_1737754251032.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_ft_mango_leaf_disease","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_ft_mango_leaf_disease","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_ft_mango_leaf_disease|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/juniorjukeko/swin-tiny-patch4-window7-224_ft_mango_leaf_disease
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_ft_mango_leaf_disease_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_ft_mango_leaf_disease_pipeline_en.md
new file mode 100644
index 00000000000000..6319d4b5fc0b9a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_ft_mango_leaf_disease_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_ft_mango_leaf_disease_pipeline pipeline SwinForImageClassification from juniorjukeko
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_ft_mango_leaf_disease_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_ft_mango_leaf_disease_pipeline` is a English model originally trained by juniorjukeko.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_ft_mango_leaf_disease_pipeline_en_5.5.1_3.0_1737754262705.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_ft_mango_leaf_disease_pipeline_en_5.5.1_3.0_1737754262705.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_ft_mango_leaf_disease_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_ft_mango_leaf_disease_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_ft_mango_leaf_disease_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/juniorjukeko/swin-tiny-patch4-window7-224_ft_mango_leaf_disease
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_image_classifier_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_image_classifier_en.md
new file mode 100644
index 00000000000000..6ca288a0fca128
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_image_classifier_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_image_classifier SwinForImageClassification from LynnKukunda
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_image_classifier
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_image_classifier` is a English model originally trained by LynnKukunda.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_image_classifier_en_5.5.1_3.0_1737694572518.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_image_classifier_en_5.5.1_3.0_1737694572518.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_image_classifier","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_image_classifier","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_image_classifier|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/LynnKukunda/swin-tiny-patch4-window7-224-image-classifier
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_image_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_image_classifier_pipeline_en.md
new file mode 100644
index 00000000000000..5228099b899b3a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_image_classifier_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_image_classifier_pipeline pipeline SwinForImageClassification from LynnKukunda
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_image_classifier_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_image_classifier_pipeline` is a English model originally trained by LynnKukunda.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_image_classifier_pipeline_en_5.5.1_3.0_1737694585456.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_image_classifier_pipeline_en_5.5.1_3.0_1737694585456.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_image_classifier_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_image_classifier_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_image_classifier_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/LynnKukunda/swin-tiny-patch4-window7-224-image-classifier
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_kontur_competition_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_kontur_competition_en.md
new file mode 100644
index 00000000000000..41f723bff616cc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_kontur_competition_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_kontur_competition SwinForImageClassification from t1msan
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_kontur_competition
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_kontur_competition` is a English model originally trained by t1msan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_kontur_competition_en_5.5.1_3.0_1737714825374.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_kontur_competition_en_5.5.1_3.0_1737714825374.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_kontur_competition","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_kontur_competition","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_kontur_competition|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/t1msan/swin-tiny-patch4-window7-224-Kontur-competition
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_kontur_competition_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_kontur_competition_pipeline_en.md
new file mode 100644
index 00000000000000..b041f37651c52b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_kontur_competition_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_kontur_competition_pipeline pipeline SwinForImageClassification from t1msan
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_kontur_competition_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_kontur_competition_pipeline` is a English model originally trained by t1msan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_kontur_competition_pipeline_en_5.5.1_3.0_1737714843355.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_kontur_competition_pipeline_en_5.5.1_3.0_1737714843355.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_kontur_competition_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_kontur_competition_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_kontur_competition_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/t1msan/swin-tiny-patch4-window7-224-Kontur-competition
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_lego_v1_3ep_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_lego_v1_3ep_en.md
new file mode 100644
index 00000000000000..539c42e03bcf6c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_lego_v1_3ep_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_lego_v1_3ep SwinForImageClassification from Angy309
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_lego_v1_3ep
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_lego_v1_3ep` is a English model originally trained by Angy309.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_lego_v1_3ep_en_5.5.1_3.0_1737694700849.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_lego_v1_3ep_en_5.5.1_3.0_1737694700849.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_lego_v1_3ep","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_lego_v1_3ep","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_lego_v1_3ep|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/Angy309/swin-tiny-patch4-window7-224-Lego-v1-3ep
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_lego_v1_3ep_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_lego_v1_3ep_pipeline_en.md
new file mode 100644
index 00000000000000..ab48cdc93fcb9a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_lego_v1_3ep_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_lego_v1_3ep_pipeline pipeline SwinForImageClassification from Angy309
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_lego_v1_3ep_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_lego_v1_3ep_pipeline` is a English model originally trained by Angy309.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_lego_v1_3ep_pipeline_en_5.5.1_3.0_1737694713765.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_lego_v1_3ep_pipeline_en_5.5.1_3.0_1737694713765.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_lego_v1_3ep_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_lego_v1_3ep_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_lego_v1_3ep_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/Angy309/swin-tiny-patch4-window7-224-Lego-v1-3ep
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_pruned_0_1_finetuned_eurosat_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_pruned_0_1_finetuned_eurosat_en.md
new file mode 100644
index 00000000000000..b904430d0e99c0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_pruned_0_1_finetuned_eurosat_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_pruned_0_1_finetuned_eurosat SwinForImageClassification from 2022happy
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_pruned_0_1_finetuned_eurosat
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_pruned_0_1_finetuned_eurosat` is a English model originally trained by 2022happy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_pruned_0_1_finetuned_eurosat_en_5.5.1_3.0_1737754780320.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_pruned_0_1_finetuned_eurosat_en_5.5.1_3.0_1737754780320.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_pruned_0_1_finetuned_eurosat","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_pruned_0_1_finetuned_eurosat","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_pruned_0_1_finetuned_eurosat|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.1 MB|
+
+## References
+
+https://huggingface.co/2022happy/swin-tiny-patch4-window7-224-pruned-0.1-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_pruned_0_1_finetuned_eurosat_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_pruned_0_1_finetuned_eurosat_pipeline_en.md
new file mode 100644
index 00000000000000..2b2d7e4231b4f8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_pruned_0_1_finetuned_eurosat_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_pruned_0_1_finetuned_eurosat_pipeline pipeline SwinForImageClassification from 2022happy
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_pruned_0_1_finetuned_eurosat_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_pruned_0_1_finetuned_eurosat_pipeline` is a English model originally trained by 2022happy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_pruned_0_1_finetuned_eurosat_pipeline_en_5.5.1_3.0_1737754794289.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_pruned_0_1_finetuned_eurosat_pipeline_en_5.5.1_3.0_1737754794289.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_pruned_0_1_finetuned_eurosat_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_pruned_0_1_finetuned_eurosat_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_pruned_0_1_finetuned_eurosat_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.1 MB|
+
+## References
+
+https://huggingface.co/2022happy/swin-tiny-patch4-window7-224-pruned-0.1-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_pruned_0_5_finetuned_eurosat_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_pruned_0_5_finetuned_eurosat_en.md
new file mode 100644
index 00000000000000..56680cd7b1a863
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_pruned_0_5_finetuned_eurosat_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_pruned_0_5_finetuned_eurosat SwinForImageClassification from 2022happy
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_pruned_0_5_finetuned_eurosat
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_pruned_0_5_finetuned_eurosat` is a English model originally trained by 2022happy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_pruned_0_5_finetuned_eurosat_en_5.5.1_3.0_1737715404682.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_pruned_0_5_finetuned_eurosat_en_5.5.1_3.0_1737715404682.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_pruned_0_5_finetuned_eurosat","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_pruned_0_5_finetuned_eurosat","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_pruned_0_5_finetuned_eurosat|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.1 MB|
+
+## References
+
+https://huggingface.co/2022happy/swin-tiny-patch4-window7-224-pruned-0.5-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_pruned_0_5_finetuned_eurosat_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_pruned_0_5_finetuned_eurosat_pipeline_en.md
new file mode 100644
index 00000000000000..b6f24e1dea3be9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_pruned_0_5_finetuned_eurosat_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_pruned_0_5_finetuned_eurosat_pipeline pipeline SwinForImageClassification from 2022happy
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_pruned_0_5_finetuned_eurosat_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_pruned_0_5_finetuned_eurosat_pipeline` is a English model originally trained by 2022happy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_pruned_0_5_finetuned_eurosat_pipeline_en_5.5.1_3.0_1737715415807.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_pruned_0_5_finetuned_eurosat_pipeline_en_5.5.1_3.0_1737715415807.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_pruned_0_5_finetuned_eurosat_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_pruned_0_5_finetuned_eurosat_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_pruned_0_5_finetuned_eurosat_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.1 MB|
+
+## References
+
+https://huggingface.co/2022happy/swin-tiny-patch4-window7-224-pruned-0.5-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_pruned_0_6_finetuned_eurosat_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_pruned_0_6_finetuned_eurosat_en.md
new file mode 100644
index 00000000000000..d7f34c90214f93
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_pruned_0_6_finetuned_eurosat_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_pruned_0_6_finetuned_eurosat SwinForImageClassification from 2022happy
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_pruned_0_6_finetuned_eurosat
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_pruned_0_6_finetuned_eurosat` is a English model originally trained by 2022happy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_pruned_0_6_finetuned_eurosat_en_5.5.1_3.0_1737754081494.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_pruned_0_6_finetuned_eurosat_en_5.5.1_3.0_1737754081494.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_pruned_0_6_finetuned_eurosat","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_pruned_0_6_finetuned_eurosat","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_pruned_0_6_finetuned_eurosat|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.1 MB|
+
+## References
+
+https://huggingface.co/2022happy/swin-tiny-patch4-window7-224-pruned-0.6-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_pruned_0_6_finetuned_eurosat_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_pruned_0_6_finetuned_eurosat_pipeline_en.md
new file mode 100644
index 00000000000000..cbbead0c4047b2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_pruned_0_6_finetuned_eurosat_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_pruned_0_6_finetuned_eurosat_pipeline pipeline SwinForImageClassification from 2022happy
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_pruned_0_6_finetuned_eurosat_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_pruned_0_6_finetuned_eurosat_pipeline` is a English model originally trained by 2022happy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_pruned_0_6_finetuned_eurosat_pipeline_en_5.5.1_3.0_1737754093630.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_pruned_0_6_finetuned_eurosat_pipeline_en_5.5.1_3.0_1737754093630.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_pruned_0_6_finetuned_eurosat_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_pruned_0_6_finetuned_eurosat_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_pruned_0_6_finetuned_eurosat_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.1 MB|
+
+## References
+
+https://huggingface.co/2022happy/swin-tiny-patch4-window7-224-pruned-0.6-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_shortsleevecleaneddata_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_shortsleevecleaneddata_en.md
new file mode 100644
index 00000000000000..bb03f5a0fbd27f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_shortsleevecleaneddata_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_shortsleevecleaneddata SwinForImageClassification from Soulaimen
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_shortsleevecleaneddata
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_shortsleevecleaneddata` is a English model originally trained by Soulaimen.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_shortsleevecleaneddata_en_5.5.1_3.0_1737715455710.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_shortsleevecleaneddata_en_5.5.1_3.0_1737715455710.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_shortsleevecleaneddata","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_shortsleevecleaneddata","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_shortsleevecleaneddata|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/Soulaimen/swin-tiny-patch4-window7-224-shortSleeveCleanedData
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_shortsleevecleaneddata_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_shortsleevecleaneddata_pipeline_en.md
new file mode 100644
index 00000000000000..f7126c7d05fd4e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_shortsleevecleaneddata_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_shortsleevecleaneddata_pipeline pipeline SwinForImageClassification from Soulaimen
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_shortsleevecleaneddata_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_shortsleevecleaneddata_pipeline` is a English model originally trained by Soulaimen.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_shortsleevecleaneddata_pipeline_en_5.5.1_3.0_1737715466849.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_shortsleevecleaneddata_pipeline_en_5.5.1_3.0_1737715466849.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_shortsleevecleaneddata_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_shortsleevecleaneddata_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_shortsleevecleaneddata_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/Soulaimen/swin-tiny-patch4-window7-224-shortSleeveCleanedData
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_uploads_classifier_v2_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_uploads_classifier_v2_en.md
new file mode 100644
index 00000000000000..05ba6c6e5b99c8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_uploads_classifier_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_uploads_classifier_v2 SwinForImageClassification from dvs
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_uploads_classifier_v2
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_uploads_classifier_v2` is a English model originally trained by dvs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_uploads_classifier_v2_en_5.5.1_3.0_1737694394174.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_uploads_classifier_v2_en_5.5.1_3.0_1737694394174.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_uploads_classifier_v2","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_uploads_classifier_v2","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_uploads_classifier_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/dvs/swin-tiny-patch4-window7-224-uploads-classifier-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_uploads_classifier_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_uploads_classifier_v2_pipeline_en.md
new file mode 100644
index 00000000000000..bfe6ae8ffa05ff
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_uploads_classifier_v2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_uploads_classifier_v2_pipeline pipeline SwinForImageClassification from dvs
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_uploads_classifier_v2_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_uploads_classifier_v2_pipeline` is a English model originally trained by dvs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_uploads_classifier_v2_pipeline_en_5.5.1_3.0_1737694405489.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_uploads_classifier_v2_pipeline_en_5.5.1_3.0_1737694405489.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_uploads_classifier_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_uploads_classifier_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_uploads_classifier_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/dvs/swin-tiny-patch4-window7-224-uploads-classifier-v2
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_venda_u11_b_80_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_venda_u11_b_80_en.md
new file mode 100644
index 00000000000000..2c01d45c2a7bf2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_venda_u11_b_80_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_venda_u11_b_80 SwinForImageClassification from Augusto777
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_venda_u11_b_80
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_venda_u11_b_80` is a English model originally trained by Augusto777.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_venda_u11_b_80_en_5.5.1_3.0_1737754609645.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_venda_u11_b_80_en_5.5.1_3.0_1737754609645.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_venda_u11_b_80","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_venda_u11_b_80","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_venda_u11_b_80|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/Augusto777/swin-tiny-patch4-window7-224-ve-U11-b-80
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_venda_u11_b_80_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_venda_u11_b_80_pipeline_en.md
new file mode 100644
index 00000000000000..40282e29765306
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_venda_u11_b_80_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_venda_u11_b_80_pipeline pipeline SwinForImageClassification from Augusto777
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_venda_u11_b_80_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_venda_u11_b_80_pipeline` is a English model originally trained by Augusto777.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_venda_u11_b_80_pipeline_en_5.5.1_3.0_1737754621376.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_venda_u11_b_80_pipeline_en_5.5.1_3.0_1737754621376.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_venda_u11_b_80_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_venda_u11_b_80_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_venda_u11_b_80_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/Augusto777/swin-tiny-patch4-window7-224-ve-U11-b-80
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_venda_u13_b_12_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_venda_u13_b_12_en.md
new file mode 100644
index 00000000000000..4f6a19d3873b62
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_venda_u13_b_12_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_venda_u13_b_12 SwinForImageClassification from Augusto777
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_venda_u13_b_12
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_venda_u13_b_12` is a English model originally trained by Augusto777.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_venda_u13_b_12_en_5.5.1_3.0_1737754481134.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_venda_u13_b_12_en_5.5.1_3.0_1737754481134.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_venda_u13_b_12","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_venda_u13_b_12","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_venda_u13_b_12|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/Augusto777/swin-tiny-patch4-window7-224-ve-U13-b-12
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_venda_u13_b_12_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_venda_u13_b_12_pipeline_en.md
new file mode 100644
index 00000000000000..70f3f41613f475
--- /dev/null
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@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_venda_u13_b_12_pipeline pipeline SwinForImageClassification from Augusto777
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_venda_u13_b_12_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_venda_u13_b_12_pipeline` is a English model originally trained by Augusto777.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_venda_u13_b_12_pipeline_en_5.5.1_3.0_1737754492507.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_venda_u13_b_12_pipeline_en_5.5.1_3.0_1737754492507.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_venda_u13_b_12_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_venda_u13_b_12_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_venda_u13_b_12_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/Augusto777/swin-tiny-patch4-window7-224-ve-U13-b-12
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_venda_u13_b_80_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_venda_u13_b_80_en.md
new file mode 100644
index 00000000000000..79c63e176d7b0c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_venda_u13_b_80_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_venda_u13_b_80 SwinForImageClassification from Augusto777
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_venda_u13_b_80
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_venda_u13_b_80` is a English model originally trained by Augusto777.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_venda_u13_b_80_en_5.5.1_3.0_1737715655288.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_venda_u13_b_80_en_5.5.1_3.0_1737715655288.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_venda_u13_b_80","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_venda_u13_b_80","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_venda_u13_b_80|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/Augusto777/swin-tiny-patch4-window7-224-ve-U13-b-80
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_venda_u13_b_80_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_venda_u13_b_80_pipeline_en.md
new file mode 100644
index 00000000000000..631e05d35a4c6c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_venda_u13_b_80_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_venda_u13_b_80_pipeline pipeline SwinForImageClassification from Augusto777
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_venda_u13_b_80_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_venda_u13_b_80_pipeline` is a English model originally trained by Augusto777.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_venda_u13_b_80_pipeline_en_5.5.1_3.0_1737715666752.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_venda_u13_b_80_pipeline_en_5.5.1_3.0_1737715666752.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_venda_u13_b_80_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_venda_u13_b_80_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_venda_u13_b_80_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/Augusto777/swin-tiny-patch4-window7-224-ve-U13-b-80
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_venda_u13_b_80b_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_venda_u13_b_80b_en.md
new file mode 100644
index 00000000000000..b0c64e4cd88f05
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_venda_u13_b_80b_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_venda_u13_b_80b SwinForImageClassification from Augusto777
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_venda_u13_b_80b
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_venda_u13_b_80b` is a English model originally trained by Augusto777.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_venda_u13_b_80b_en_5.5.1_3.0_1737715389603.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_venda_u13_b_80b_en_5.5.1_3.0_1737715389603.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_venda_u13_b_80b","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_venda_u13_b_80b","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_venda_u13_b_80b|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/Augusto777/swin-tiny-patch4-window7-224-ve-U13-b-80b
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_venda_u13_b_80b_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_venda_u13_b_80b_pipeline_en.md
new file mode 100644
index 00000000000000..5d123b4ea3ad6b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-swin_tiny_patch4_window7_224_venda_u13_b_80b_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_venda_u13_b_80b_pipeline pipeline SwinForImageClassification from Augusto777
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_venda_u13_b_80b_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_venda_u13_b_80b_pipeline` is a English model originally trained by Augusto777.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_venda_u13_b_80b_pipeline_en_5.5.1_3.0_1737715400839.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_venda_u13_b_80b_pipeline_en_5.5.1_3.0_1737715400839.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_venda_u13_b_80b_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_venda_u13_b_80b_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_venda_u13_b_80b_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/Augusto777/swin-tiny-patch4-window7-224-ve-U13-b-80b
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-t2_arabic_2_en.md b/docs/_posts/ahmedlone127/2025-01-24-t2_arabic_2_en.md
new file mode 100644
index 00000000000000..ce4109d119fb2c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-t2_arabic_2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English t2_arabic_2 XlmRoBertaForSequenceClassification from keles
+author: John Snow Labs
+name: t2_arabic_2
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t2_arabic_2` is a English model originally trained by keles.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t2_arabic_2_en_5.5.1_3.0_1737713860437.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t2_arabic_2_en_5.5.1_3.0_1737713860437.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("t2_arabic_2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("t2_arabic_2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t2_arabic_2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|821.7 MB|
+
+## References
+
+https://huggingface.co/keles/t2_ar_2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-t2_arabic_2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-t2_arabic_2_pipeline_en.md
new file mode 100644
index 00000000000000..2d5332476b355e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-t2_arabic_2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English t2_arabic_2_pipeline pipeline XlmRoBertaForSequenceClassification from keles
+author: John Snow Labs
+name: t2_arabic_2_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t2_arabic_2_pipeline` is a English model originally trained by keles.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t2_arabic_2_pipeline_en_5.5.1_3.0_1737713961756.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t2_arabic_2_pipeline_en_5.5.1_3.0_1737713961756.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t2_arabic_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t2_arabic_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t2_arabic_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|821.8 MB|
+
+## References
+
+https://huggingface.co/keles/t2_ar_2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-tacl_bert_squad_trained_en.md b/docs/_posts/ahmedlone127/2025-01-24-tacl_bert_squad_trained_en.md
new file mode 100644
index 00000000000000..12ca875d27d9c2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-tacl_bert_squad_trained_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English tacl_bert_squad_trained BertForQuestionAnswering from sandeepvarma99
+author: John Snow Labs
+name: tacl_bert_squad_trained
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tacl_bert_squad_trained` is a English model originally trained by sandeepvarma99.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tacl_bert_squad_trained_en_5.5.1_3.0_1737750959259.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tacl_bert_squad_trained_en_5.5.1_3.0_1737750959259.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("tacl_bert_squad_trained","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("tacl_bert_squad_trained", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tacl_bert_squad_trained|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/sandeepvarma99/tacl-bert-squad-trained
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-tacl_bert_squad_trained_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-tacl_bert_squad_trained_pipeline_en.md
new file mode 100644
index 00000000000000..f538eaedf5fc7f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-tacl_bert_squad_trained_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English tacl_bert_squad_trained_pipeline pipeline BertForQuestionAnswering from sandeepvarma99
+author: John Snow Labs
+name: tacl_bert_squad_trained_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tacl_bert_squad_trained_pipeline` is a English model originally trained by sandeepvarma99.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tacl_bert_squad_trained_pipeline_en_5.5.1_3.0_1737751026537.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tacl_bert_squad_trained_pipeline_en_5.5.1_3.0_1737751026537.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("tacl_bert_squad_trained_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("tacl_bert_squad_trained_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tacl_bert_squad_trained_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/sandeepvarma99/tacl-bert-squad-trained
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-test_bert_en.md b/docs/_posts/ahmedlone127/2025-01-24-test_bert_en.md
new file mode 100644
index 00000000000000..42110da8e38651
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-test_bert_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English test_bert BertForQuestionAnswering from Devishri1
+author: John Snow Labs
+name: test_bert
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_bert` is a English model originally trained by Devishri1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_bert_en_5.5.1_3.0_1737747674605.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_bert_en_5.5.1_3.0_1737747674605.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("test_bert","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("test_bert", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_bert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/Devishri1/test_bert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-test_bert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-test_bert_pipeline_en.md
new file mode 100644
index 00000000000000..4bd5a2b394f4f5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-test_bert_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English test_bert_pipeline pipeline BertForQuestionAnswering from Devishri1
+author: John Snow Labs
+name: test_bert_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_bert_pipeline` is a English model originally trained by Devishri1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_bert_pipeline_en_5.5.1_3.0_1737747713886.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_bert_pipeline_en_5.5.1_3.0_1737747713886.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("test_bert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("test_bert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_bert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/Devishri1/test_bert
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-test_chinese_trained2_en.md b/docs/_posts/ahmedlone127/2025-01-24-test_chinese_trained2_en.md
new file mode 100644
index 00000000000000..03e81ad97e9b72
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-test_chinese_trained2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English test_chinese_trained2 BertForQuestionAnswering from sunnyHong
+author: John Snow Labs
+name: test_chinese_trained2
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_chinese_trained2` is a English model originally trained by sunnyHong.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_chinese_trained2_en_5.5.1_3.0_1737751946740.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_chinese_trained2_en_5.5.1_3.0_1737751946740.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("test_chinese_trained2","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("test_chinese_trained2", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_chinese_trained2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/sunnyHong/test-chinese-trained2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-test_chinese_trained2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-test_chinese_trained2_pipeline_en.md
new file mode 100644
index 00000000000000..70e8344965a004
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-test_chinese_trained2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English test_chinese_trained2_pipeline pipeline BertForQuestionAnswering from sunnyHong
+author: John Snow Labs
+name: test_chinese_trained2_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_chinese_trained2_pipeline` is a English model originally trained by sunnyHong.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_chinese_trained2_pipeline_en_5.5.1_3.0_1737751981853.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_chinese_trained2_pipeline_en_5.5.1_3.0_1737751981853.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("test_chinese_trained2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("test_chinese_trained2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_chinese_trained2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/sunnyHong/test-chinese-trained2
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-test_model_najma_nur_en.md b/docs/_posts/ahmedlone127/2025-01-24-test_model_najma_nur_en.md
new file mode 100644
index 00000000000000..228875081a088c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-test_model_najma_nur_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English test_model_najma_nur CamemBertEmbeddings from Najma-Nur
+author: John Snow Labs
+name: test_model_najma_nur
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_model_najma_nur` is a English model originally trained by Najma-Nur.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_model_najma_nur_en_5.5.1_3.0_1737696172902.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_model_najma_nur_en_5.5.1_3.0_1737696172902.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("test_model_najma_nur","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("test_model_najma_nur","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_model_najma_nur|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/Najma-Nur/test_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-test_model_najma_nur_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-test_model_najma_nur_pipeline_en.md
new file mode 100644
index 00000000000000..0ae0a62840ddf8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-test_model_najma_nur_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English test_model_najma_nur_pipeline pipeline CamemBertEmbeddings from Najma-Nur
+author: John Snow Labs
+name: test_model_najma_nur_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_model_najma_nur_pipeline` is a English model originally trained by Najma-Nur.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_model_najma_nur_pipeline_en_5.5.1_3.0_1737696252026.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_model_najma_nur_pipeline_en_5.5.1_3.0_1737696252026.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("test_model_najma_nur_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("test_model_najma_nur_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_model_najma_nur_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/Najma-Nur/test_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-testmod_en.md b/docs/_posts/ahmedlone127/2025-01-24-testmod_en.md
new file mode 100644
index 00000000000000..bae4fc9b064cb6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-testmod_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English testmod GPT2Transformer from dierce
+author: John Snow Labs
+name: testmod
+date: 2025-01-24
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`testmod` is a English model originally trained by dierce.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/testmod_en_5.5.1_3.0_1737731981620.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/testmod_en_5.5.1_3.0_1737731981620.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("testmod","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("testmod","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|testmod|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|466.9 MB|
+
+## References
+
+https://huggingface.co/dierce/testmod
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-testmod_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-testmod_pipeline_en.md
new file mode 100644
index 00000000000000..4352258c2f05d5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-testmod_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English testmod_pipeline pipeline GPT2Transformer from dierce
+author: John Snow Labs
+name: testmod_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`testmod_pipeline` is a English model originally trained by dierce.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/testmod_pipeline_en_5.5.1_3.0_1737732006667.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/testmod_pipeline_en_5.5.1_3.0_1737732006667.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("testmod_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("testmod_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|testmod_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.9 MB|
+
+## References
+
+https://huggingface.co/dierce/testmod
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-testza_en.md b/docs/_posts/ahmedlone127/2025-01-24-testza_en.md
new file mode 100644
index 00000000000000..9e7ba3bef3c780
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-testza_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English testza CamemBertForQuestionAnswering from GETTOz
+author: John Snow Labs
+name: testza
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, camembert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`testza` is a English model originally trained by GETTOz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/testza_en_5.5.1_3.0_1737685000247.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/testza_en_5.5.1_3.0_1737685000247.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = CamemBertForQuestionAnswering.pretrained("testza","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = CamemBertForQuestionAnswering.pretrained("testza", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|testza|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|392.1 MB|
+
+## References
+
+https://huggingface.co/GETTOz/Testza
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-testza_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-testza_pipeline_en.md
new file mode 100644
index 00000000000000..bdc744457a471e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-testza_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English testza_pipeline pipeline CamemBertForQuestionAnswering from GETTOz
+author: John Snow Labs
+name: testza_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`testza_pipeline` is a English model originally trained by GETTOz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/testza_pipeline_en_5.5.1_3.0_1737685021117.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/testza_pipeline_en_5.5.1_3.0_1737685021117.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("testza_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("testza_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|testza_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|392.1 MB|
+
+## References
+
+https://huggingface.co/GETTOz/Testza
+
+## Included Models
+
+- MultiDocumentAssembler
+- CamemBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-text2image_prompt_generator_en.md b/docs/_posts/ahmedlone127/2025-01-24-text2image_prompt_generator_en.md
new file mode 100644
index 00000000000000..a0d03f46343f6c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-text2image_prompt_generator_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English text2image_prompt_generator GPT2Transformer from succinctly
+author: John Snow Labs
+name: text2image_prompt_generator
+date: 2025-01-24
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`text2image_prompt_generator` is a English model originally trained by succinctly.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/text2image_prompt_generator_en_5.5.1_3.0_1737717335628.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/text2image_prompt_generator_en_5.5.1_3.0_1737717335628.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("text2image_prompt_generator","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("text2image_prompt_generator","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|text2image_prompt_generator|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.9 MB|
+
+## References
+
+https://huggingface.co/succinctly/text2image-prompt-generator
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-text2image_prompt_generator_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-text2image_prompt_generator_pipeline_en.md
new file mode 100644
index 00000000000000..0dec7075beb3d9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-text2image_prompt_generator_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English text2image_prompt_generator_pipeline pipeline GPT2Transformer from succinctly
+author: John Snow Labs
+name: text2image_prompt_generator_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`text2image_prompt_generator_pipeline` is a English model originally trained by succinctly.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/text2image_prompt_generator_pipeline_en_5.5.1_3.0_1737717359427.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/text2image_prompt_generator_pipeline_en_5.5.1_3.0_1737717359427.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("text2image_prompt_generator_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("text2image_prompt_generator_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|text2image_prompt_generator_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.9 MB|
+
+## References
+
+https://huggingface.co/succinctly/text2image-prompt-generator
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-tiny_gpt2_sshleifer_en.md b/docs/_posts/ahmedlone127/2025-01-24-tiny_gpt2_sshleifer_en.md
new file mode 100644
index 00000000000000..27cbdc0826c28d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-tiny_gpt2_sshleifer_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English tiny_gpt2_sshleifer GPT2Transformer from sshleifer
+author: John Snow Labs
+name: tiny_gpt2_sshleifer
+date: 2025-01-24
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_gpt2_sshleifer` is a English model originally trained by sshleifer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_gpt2_sshleifer_en_5.5.1_3.0_1737717210476.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_gpt2_sshleifer_en_5.5.1_3.0_1737717210476.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("tiny_gpt2_sshleifer","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("tiny_gpt2_sshleifer","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tiny_gpt2_sshleifer|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|1.5 MB|
+
+## References
+
+https://huggingface.co/sshleifer/tiny-gpt2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-tiny_gpt2_sshleifer_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-tiny_gpt2_sshleifer_pipeline_en.md
new file mode 100644
index 00000000000000..957201b796605a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-tiny_gpt2_sshleifer_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English tiny_gpt2_sshleifer_pipeline pipeline GPT2Transformer from sshleifer
+author: John Snow Labs
+name: tiny_gpt2_sshleifer_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_gpt2_sshleifer_pipeline` is a English model originally trained by sshleifer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_gpt2_sshleifer_pipeline_en_5.5.1_3.0_1737717210941.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_gpt2_sshleifer_pipeline_en_5.5.1_3.0_1737717210941.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("tiny_gpt2_sshleifer_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("tiny_gpt2_sshleifer_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tiny_gpt2_sshleifer_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 MB|
+
+## References
+
+https://huggingface.co/sshleifer/tiny-gpt2
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-topk_10epoch_nepal_bhasa_60_pruned_en.md b/docs/_posts/ahmedlone127/2025-01-24-topk_10epoch_nepal_bhasa_60_pruned_en.md
new file mode 100644
index 00000000000000..943d57485c9d12
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-topk_10epoch_nepal_bhasa_60_pruned_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English topk_10epoch_nepal_bhasa_60_pruned BertForQuestionAnswering from xihajun
+author: John Snow Labs
+name: topk_10epoch_nepal_bhasa_60_pruned
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`topk_10epoch_nepal_bhasa_60_pruned` is a English model originally trained by xihajun.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/topk_10epoch_nepal_bhasa_60_pruned_en_5.5.1_3.0_1737752098560.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/topk_10epoch_nepal_bhasa_60_pruned_en_5.5.1_3.0_1737752098560.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("topk_10epoch_nepal_bhasa_60_pruned","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("topk_10epoch_nepal_bhasa_60_pruned", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|topk_10epoch_nepal_bhasa_60_pruned|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/xihajun/topK_10epoch_new_60_pruned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-topk_10epoch_nepal_bhasa_60_pruned_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-topk_10epoch_nepal_bhasa_60_pruned_pipeline_en.md
new file mode 100644
index 00000000000000..10436a6fc1776a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-topk_10epoch_nepal_bhasa_60_pruned_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English topk_10epoch_nepal_bhasa_60_pruned_pipeline pipeline BertForQuestionAnswering from xihajun
+author: John Snow Labs
+name: topk_10epoch_nepal_bhasa_60_pruned_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`topk_10epoch_nepal_bhasa_60_pruned_pipeline` is a English model originally trained by xihajun.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/topk_10epoch_nepal_bhasa_60_pruned_pipeline_en_5.5.1_3.0_1737752172061.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/topk_10epoch_nepal_bhasa_60_pruned_pipeline_en_5.5.1_3.0_1737752172061.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("topk_10epoch_nepal_bhasa_60_pruned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("topk_10epoch_nepal_bhasa_60_pruned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|topk_10epoch_nepal_bhasa_60_pruned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/xihajun/topK_10epoch_new_60_pruned
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-toy_en.md b/docs/_posts/ahmedlone127/2025-01-24-toy_en.md
new file mode 100644
index 00000000000000..ede2a141b22b32
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-toy_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English toy DistilBertForQuestionAnswering from datarpit
+author: John Snow Labs
+name: toy
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`toy` is a English model originally trained by datarpit.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/toy_en_5.5.1_3.0_1737741254739.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/toy_en_5.5.1_3.0_1737741254739.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("toy","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("toy", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|toy|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/datarpit/toy
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-toy_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-toy_pipeline_en.md
new file mode 100644
index 00000000000000..bc5baec442d595
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-toy_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English toy_pipeline pipeline DistilBertForQuestionAnswering from datarpit
+author: John Snow Labs
+name: toy_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`toy_pipeline` is a English model originally trained by datarpit.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/toy_pipeline_en_5.5.1_3.0_1737741268120.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/toy_pipeline_en_5.5.1_3.0_1737741268120.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("toy_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("toy_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|toy_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/datarpit/toy
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-turkish_sentiment_analysis_en.md b/docs/_posts/ahmedlone127/2025-01-24-turkish_sentiment_analysis_en.md
new file mode 100644
index 00000000000000..55c25a6f860799
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-turkish_sentiment_analysis_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English turkish_sentiment_analysis BertForSequenceClassification from altan01
+author: John Snow Labs
+name: turkish_sentiment_analysis
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`turkish_sentiment_analysis` is a English model originally trained by altan01.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/turkish_sentiment_analysis_en_5.5.1_3.0_1737710471202.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/turkish_sentiment_analysis_en_5.5.1_3.0_1737710471202.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("turkish_sentiment_analysis","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("turkish_sentiment_analysis", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|turkish_sentiment_analysis|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|414.7 MB|
+
+## References
+
+https://huggingface.co/altan01/turkish_sentiment_analysis
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-turkish_sentiment_analysis_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-turkish_sentiment_analysis_pipeline_en.md
new file mode 100644
index 00000000000000..ad8fcd101d12c8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-turkish_sentiment_analysis_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English turkish_sentiment_analysis_pipeline pipeline BertForSequenceClassification from altan01
+author: John Snow Labs
+name: turkish_sentiment_analysis_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`turkish_sentiment_analysis_pipeline` is a English model originally trained by altan01.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/turkish_sentiment_analysis_pipeline_en_5.5.1_3.0_1737710493201.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/turkish_sentiment_analysis_pipeline_en_5.5.1_3.0_1737710493201.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("turkish_sentiment_analysis_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("turkish_sentiment_analysis_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|turkish_sentiment_analysis_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|414.7 MB|
+
+## References
+
+https://huggingface.co/altan01/turkish_sentiment_analysis
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-turkish_zeroshot_distilbert_en.md b/docs/_posts/ahmedlone127/2025-01-24-turkish_zeroshot_distilbert_en.md
new file mode 100644
index 00000000000000..2a09dfc4591889
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-turkish_zeroshot_distilbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English turkish_zeroshot_distilbert DistilBertForZeroShotClassification from kaixkhazaki
+author: John Snow Labs
+name: turkish_zeroshot_distilbert
+date: 2025-01-24
+tags: [en, open_source, onnx, zero_shot, distilbert]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`turkish_zeroshot_distilbert` is a English model originally trained by kaixkhazaki.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/turkish_zeroshot_distilbert_en_5.5.1_3.0_1737699980127.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/turkish_zeroshot_distilbert_en_5.5.1_3.0_1737699980127.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+zeroShotClassifier  = DistilBertForZeroShotClassification.pretrained("turkish_zeroshot_distilbert","en") \
+     .setInputCols(["document","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, zeroShotClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val zeroShotClassifier  = DistilBertForZeroShotClassification.pretrained("turkish_zeroshot_distilbert", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, zeroShotClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|turkish_zeroshot_distilbert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|254.1 MB|
+
+## References
+
+https://huggingface.co/kaixkhazaki/turkish-zeroshot-distilbert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-turkish_zeroshot_distilbert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-turkish_zeroshot_distilbert_pipeline_en.md
new file mode 100644
index 00000000000000..0d5fdd79182f6f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-turkish_zeroshot_distilbert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English turkish_zeroshot_distilbert_pipeline pipeline DistilBertForZeroShotClassification from kaixkhazaki
+author: John Snow Labs
+name: turkish_zeroshot_distilbert_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`turkish_zeroshot_distilbert_pipeline` is a English model originally trained by kaixkhazaki.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/turkish_zeroshot_distilbert_pipeline_en_5.5.1_3.0_1737699993590.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/turkish_zeroshot_distilbert_pipeline_en_5.5.1_3.0_1737699993590.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("turkish_zeroshot_distilbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("turkish_zeroshot_distilbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|turkish_zeroshot_distilbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|254.1 MB|
+
+## References
+
+https://huggingface.co/kaixkhazaki/turkish-zeroshot-distilbert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-twitter_xlm_roberta_base_sentiment_deletion_multiclass_spanish_en.md b/docs/_posts/ahmedlone127/2025-01-24-twitter_xlm_roberta_base_sentiment_deletion_multiclass_spanish_en.md
new file mode 100644
index 00000000000000..570750e6ad53e6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-twitter_xlm_roberta_base_sentiment_deletion_multiclass_spanish_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English twitter_xlm_roberta_base_sentiment_deletion_multiclass_spanish XlmRoBertaForSequenceClassification from research-dump
+author: John Snow Labs
+name: twitter_xlm_roberta_base_sentiment_deletion_multiclass_spanish
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_xlm_roberta_base_sentiment_deletion_multiclass_spanish` is a English model originally trained by research-dump.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twitter_xlm_roberta_base_sentiment_deletion_multiclass_spanish_en_5.5.1_3.0_1737712315096.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_xlm_roberta_base_sentiment_deletion_multiclass_spanish_en_5.5.1_3.0_1737712315096.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("twitter_xlm_roberta_base_sentiment_deletion_multiclass_spanish","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("twitter_xlm_roberta_base_sentiment_deletion_multiclass_spanish", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|twitter_xlm_roberta_base_sentiment_deletion_multiclass_spanish|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/research-dump/twitter-xlm-roberta-base-sentiment_deletion_multiclass_es
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-twitter_xlm_roberta_base_sentiment_deletion_multiclass_spanish_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-twitter_xlm_roberta_base_sentiment_deletion_multiclass_spanish_pipeline_en.md
new file mode 100644
index 00000000000000..52170628a00387
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-twitter_xlm_roberta_base_sentiment_deletion_multiclass_spanish_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English twitter_xlm_roberta_base_sentiment_deletion_multiclass_spanish_pipeline pipeline XlmRoBertaForSequenceClassification from research-dump
+author: John Snow Labs
+name: twitter_xlm_roberta_base_sentiment_deletion_multiclass_spanish_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_xlm_roberta_base_sentiment_deletion_multiclass_spanish_pipeline` is a English model originally trained by research-dump.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twitter_xlm_roberta_base_sentiment_deletion_multiclass_spanish_pipeline_en_5.5.1_3.0_1737712377126.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_xlm_roberta_base_sentiment_deletion_multiclass_spanish_pipeline_en_5.5.1_3.0_1737712377126.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("twitter_xlm_roberta_base_sentiment_deletion_multiclass_spanish_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("twitter_xlm_roberta_base_sentiment_deletion_multiclass_spanish_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|twitter_xlm_roberta_base_sentiment_deletion_multiclass_spanish_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/research-dump/twitter-xlm-roberta-base-sentiment_deletion_multiclass_es
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-uit_deberta_v3_large_finetuned_en.md b/docs/_posts/ahmedlone127/2025-01-24-uit_deberta_v3_large_finetuned_en.md
new file mode 100644
index 00000000000000..c853585a5c8cbb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-uit_deberta_v3_large_finetuned_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English uit_deberta_v3_large_finetuned DeBertaForSequenceClassification from sercetexam9
+author: John Snow Labs
+name: uit_deberta_v3_large_finetuned
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`uit_deberta_v3_large_finetuned` is a English model originally trained by sercetexam9.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/uit_deberta_v3_large_finetuned_en_5.5.1_3.0_1737728195674.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/uit_deberta_v3_large_finetuned_en_5.5.1_3.0_1737728195674.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("uit_deberta_v3_large_finetuned","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("uit_deberta_v3_large_finetuned", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|uit_deberta_v3_large_finetuned|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/sercetexam9/UIT-deberta-v3-large-finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-uit_deberta_v3_large_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-uit_deberta_v3_large_finetuned_pipeline_en.md
new file mode 100644
index 00000000000000..ae8e37a0290fcd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-uit_deberta_v3_large_finetuned_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English uit_deberta_v3_large_finetuned_pipeline pipeline DeBertaForSequenceClassification from sercetexam9
+author: John Snow Labs
+name: uit_deberta_v3_large_finetuned_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`uit_deberta_v3_large_finetuned_pipeline` is a English model originally trained by sercetexam9.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/uit_deberta_v3_large_finetuned_pipeline_en_5.5.1_3.0_1737728322910.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/uit_deberta_v3_large_finetuned_pipeline_en_5.5.1_3.0_1737728322910.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("uit_deberta_v3_large_finetuned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("uit_deberta_v3_large_finetuned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|uit_deberta_v3_large_finetuned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/sercetexam9/UIT-deberta-v3-large-finetuned
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-uit_norwegian_predeberta_v3_large_finetuned_en.md b/docs/_posts/ahmedlone127/2025-01-24-uit_norwegian_predeberta_v3_large_finetuned_en.md
new file mode 100644
index 00000000000000..ad31772b24f159
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-uit_norwegian_predeberta_v3_large_finetuned_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English uit_norwegian_predeberta_v3_large_finetuned DeBertaForSequenceClassification from sercetexam9
+author: John Snow Labs
+name: uit_norwegian_predeberta_v3_large_finetuned
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`uit_norwegian_predeberta_v3_large_finetuned` is a English model originally trained by sercetexam9.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/uit_norwegian_predeberta_v3_large_finetuned_en_5.5.1_3.0_1737728287423.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/uit_norwegian_predeberta_v3_large_finetuned_en_5.5.1_3.0_1737728287423.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("uit_norwegian_predeberta_v3_large_finetuned","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("uit_norwegian_predeberta_v3_large_finetuned", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|uit_norwegian_predeberta_v3_large_finetuned|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/sercetexam9/UIT-NO-PREdeberta-v3-large-finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-uit_norwegian_predeberta_v3_large_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-uit_norwegian_predeberta_v3_large_finetuned_pipeline_en.md
new file mode 100644
index 00000000000000..e9ba1c21c3f17c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-uit_norwegian_predeberta_v3_large_finetuned_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English uit_norwegian_predeberta_v3_large_finetuned_pipeline pipeline DeBertaForSequenceClassification from sercetexam9
+author: John Snow Labs
+name: uit_norwegian_predeberta_v3_large_finetuned_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`uit_norwegian_predeberta_v3_large_finetuned_pipeline` is a English model originally trained by sercetexam9.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/uit_norwegian_predeberta_v3_large_finetuned_pipeline_en_5.5.1_3.0_1737728412998.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/uit_norwegian_predeberta_v3_large_finetuned_pipeline_en_5.5.1_3.0_1737728412998.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("uit_norwegian_predeberta_v3_large_finetuned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("uit_norwegian_predeberta_v3_large_finetuned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|uit_norwegian_predeberta_v3_large_finetuned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/sercetexam9/UIT-NO-PREdeberta-v3-large-finetuned
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-uyghur_test_en.md b/docs/_posts/ahmedlone127/2025-01-24-uyghur_test_en.md
new file mode 100644
index 00000000000000..47d44dee532bf2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-uyghur_test_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English uyghur_test CamemBertEmbeddings from ohumma
+author: John Snow Labs
+name: uyghur_test
+date: 2025-01-24
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`uyghur_test` is a English model originally trained by ohumma.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/uyghur_test_en_5.5.1_3.0_1737696615739.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/uyghur_test_en_5.5.1_3.0_1737696615739.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("uyghur_test","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("uyghur_test","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|uyghur_test|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/ohumma/ug-test
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-uyghur_test_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-uyghur_test_pipeline_en.md
new file mode 100644
index 00000000000000..d344b61b7c36c4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-uyghur_test_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English uyghur_test_pipeline pipeline CamemBertEmbeddings from ohumma
+author: John Snow Labs
+name: uyghur_test_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`uyghur_test_pipeline` is a English model originally trained by ohumma.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/uyghur_test_pipeline_en_5.5.1_3.0_1737696694879.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/uyghur_test_pipeline_en_5.5.1_3.0_1737696694879.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("uyghur_test_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("uyghur_test_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|uyghur_test_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/ohumma/ug-test
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-vit_ana_0_89_en.md b/docs/_posts/ahmedlone127/2025-01-24-vit_ana_0_89_en.md
new file mode 100644
index 00000000000000..e035b70c4f4f89
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-vit_ana_0_89_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_ana_0_89 SwinForImageClassification from Shk4
+author: John Snow Labs
+name: vit_ana_0_89
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_ana_0_89` is a English model originally trained by Shk4.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_ana_0_89_en_5.5.1_3.0_1737715547837.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_ana_0_89_en_5.5.1_3.0_1737715547837.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""vit_ana_0_89","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("vit_ana_0_89","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_ana_0_89|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/Shk4/vit_ana_0.89
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-vit_ana_0_89_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-vit_ana_0_89_pipeline_en.md
new file mode 100644
index 00000000000000..f9da2aeb0cde9b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-vit_ana_0_89_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_ana_0_89_pipeline pipeline SwinForImageClassification from Shk4
+author: John Snow Labs
+name: vit_ana_0_89_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_ana_0_89_pipeline` is a English model originally trained by Shk4.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_ana_0_89_pipeline_en_5.5.1_3.0_1737715558956.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_ana_0_89_pipeline_en_5.5.1_3.0_1737715558956.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_ana_0_89_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_ana_0_89_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_ana_0_89_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/Shk4/vit_ana_0.89
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-vit_base_age_classification_en.md b/docs/_posts/ahmedlone127/2025-01-24-vit_base_age_classification_en.md
new file mode 100644
index 00000000000000..281095b6dd7151
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-vit_base_age_classification_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_base_age_classification ViTForImageClassification from akashmaggon
+author: John Snow Labs
+name: vit_base_age_classification
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_age_classification` is a English model originally trained by akashmaggon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_age_classification_en_5.5.1_3.0_1737744289580.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_age_classification_en_5.5.1_3.0_1737744289580.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vit_base_age_classification","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vit_base_age_classification","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_age_classification|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/akashmaggon/vit-base-age-classification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-vit_base_age_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-vit_base_age_classification_pipeline_en.md
new file mode 100644
index 00000000000000..2021b084df2da8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-vit_base_age_classification_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_base_age_classification_pipeline pipeline ViTForImageClassification from akashmaggon
+author: John Snow Labs
+name: vit_base_age_classification_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_age_classification_pipeline` is a English model originally trained by akashmaggon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_age_classification_pipeline_en_5.5.1_3.0_1737744307150.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_age_classification_pipeline_en_5.5.1_3.0_1737744307150.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_base_age_classification_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_base_age_classification_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_age_classification_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/akashmaggon/vit-base-age-classification
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-vit_base_patch16_224_in21k_weather_images_classification_en.md b/docs/_posts/ahmedlone127/2025-01-24-vit_base_patch16_224_in21k_weather_images_classification_en.md
new file mode 100644
index 00000000000000..38c14e901cff0a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-vit_base_patch16_224_in21k_weather_images_classification_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_base_patch16_224_in21k_weather_images_classification ViTForImageClassification from DunnBC22
+author: John Snow Labs
+name: vit_base_patch16_224_in21k_weather_images_classification
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_patch16_224_in21k_weather_images_classification` is a English model originally trained by DunnBC22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_in21k_weather_images_classification_en_5.5.1_3.0_1737744059110.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_in21k_weather_images_classification_en_5.5.1_3.0_1737744059110.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vit_base_patch16_224_in21k_weather_images_classification","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vit_base_patch16_224_in21k_weather_images_classification","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_patch16_224_in21k_weather_images_classification|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/DunnBC22/vit-base-patch16-224-in21k-weather-images-classification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-vit_base_patch16_224_in21k_weather_images_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-vit_base_patch16_224_in21k_weather_images_classification_pipeline_en.md
new file mode 100644
index 00000000000000..e2299e71a9fa3e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-vit_base_patch16_224_in21k_weather_images_classification_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_base_patch16_224_in21k_weather_images_classification_pipeline pipeline ViTForImageClassification from DunnBC22
+author: John Snow Labs
+name: vit_base_patch16_224_in21k_weather_images_classification_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_patch16_224_in21k_weather_images_classification_pipeline` is a English model originally trained by DunnBC22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_in21k_weather_images_classification_pipeline_en_5.5.1_3.0_1737744076523.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_in21k_weather_images_classification_pipeline_en_5.5.1_3.0_1737744076523.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_base_patch16_224_in21k_weather_images_classification_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_base_patch16_224_in21k_weather_images_classification_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_patch16_224_in21k_weather_images_classification_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.4 MB|
+
+## References
+
+https://huggingface.co/DunnBC22/vit-base-patch16-224-in21k-weather-images-classification
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-vit_deepfake_detection_en.md b/docs/_posts/ahmedlone127/2025-01-24-vit_deepfake_detection_en.md
new file mode 100644
index 00000000000000..4e2dd4d60996ba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-vit_deepfake_detection_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_deepfake_detection ViTForImageClassification from Wvolf
+author: John Snow Labs
+name: vit_deepfake_detection
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_deepfake_detection` is a English model originally trained by Wvolf.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_deepfake_detection_en_5.5.1_3.0_1737744019146.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_deepfake_detection_en_5.5.1_3.0_1737744019146.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vit_deepfake_detection","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vit_deepfake_detection","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_deepfake_detection|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/Wvolf/ViT_Deepfake_Detection
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-vit_deepfake_detection_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-vit_deepfake_detection_pipeline_en.md
new file mode 100644
index 00000000000000..9cf475fa2ff424
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-vit_deepfake_detection_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_deepfake_detection_pipeline pipeline ViTForImageClassification from Wvolf
+author: John Snow Labs
+name: vit_deepfake_detection_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_deepfake_detection_pipeline` is a English model originally trained by Wvolf.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_deepfake_detection_pipeline_en_5.5.1_3.0_1737744036185.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_deepfake_detection_pipeline_en_5.5.1_3.0_1737744036185.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_deepfake_detection_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_deepfake_detection_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_deepfake_detection_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/Wvolf/ViT_Deepfake_Detection
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-vit_with_attentions_en.md b/docs/_posts/ahmedlone127/2025-01-24-vit_with_attentions_en.md
new file mode 100644
index 00000000000000..640fd35cb9d31c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-vit_with_attentions_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_with_attentions ViTForImageClassification from IlyasMoutawwakil
+author: John Snow Labs
+name: vit_with_attentions
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_with_attentions` is a English model originally trained by IlyasMoutawwakil.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_with_attentions_en_5.5.1_3.0_1737744393759.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_with_attentions_en_5.5.1_3.0_1737744393759.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vit_with_attentions","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vit_with_attentions","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_with_attentions|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|324.2 MB|
+
+## References
+
+https://huggingface.co/IlyasMoutawwakil/vit-with-attentions
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-vit_with_attentions_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-vit_with_attentions_pipeline_en.md
new file mode 100644
index 00000000000000..c93abaddb96d7a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-vit_with_attentions_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_with_attentions_pipeline pipeline ViTForImageClassification from IlyasMoutawwakil
+author: John Snow Labs
+name: vit_with_attentions_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_with_attentions_pipeline` is a English model originally trained by IlyasMoutawwakil.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_with_attentions_pipeline_en_5.5.1_3.0_1737744410727.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_with_attentions_pipeline_en_5.5.1_3.0_1737744410727.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_with_attentions_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_with_attentions_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_with_attentions_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|324.2 MB|
+
+## References
+
+https://huggingface.co/IlyasMoutawwakil/vit-with-attentions
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-wikineural_multilingual_ner_heedoooch_pipeline_xx.md b/docs/_posts/ahmedlone127/2025-01-24-wikineural_multilingual_ner_heedoooch_pipeline_xx.md
new file mode 100644
index 00000000000000..f4e7aacf04c8a1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-wikineural_multilingual_ner_heedoooch_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual wikineural_multilingual_ner_heedoooch_pipeline pipeline BertForTokenClassification from heedoooch
+author: John Snow Labs
+name: wikineural_multilingual_ner_heedoooch_pipeline
+date: 2025-01-24
+tags: [xx, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`wikineural_multilingual_ner_heedoooch_pipeline` is a Multilingual model originally trained by heedoooch.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/wikineural_multilingual_ner_heedoooch_pipeline_xx_5.5.1_3.0_1737720358461.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/wikineural_multilingual_ner_heedoooch_pipeline_xx_5.5.1_3.0_1737720358461.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("wikineural_multilingual_ner_heedoooch_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("wikineural_multilingual_ner_heedoooch_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|wikineural_multilingual_ner_heedoooch_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/heedoooch/wikineural-multilingual-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-wikineural_multilingual_ner_heedoooch_xx.md b/docs/_posts/ahmedlone127/2025-01-24-wikineural_multilingual_ner_heedoooch_xx.md
new file mode 100644
index 00000000000000..6acd9b7f30a561
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-wikineural_multilingual_ner_heedoooch_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual wikineural_multilingual_ner_heedoooch BertForTokenClassification from heedoooch
+author: John Snow Labs
+name: wikineural_multilingual_ner_heedoooch
+date: 2025-01-24
+tags: [xx, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`wikineural_multilingual_ner_heedoooch` is a Multilingual model originally trained by heedoooch.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/wikineural_multilingual_ner_heedoooch_xx_5.5.1_3.0_1737720323713.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/wikineural_multilingual_ner_heedoooch_xx_5.5.1_3.0_1737720323713.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("wikineural_multilingual_ner_heedoooch","xx") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("wikineural_multilingual_ner_heedoooch", "xx")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|wikineural_multilingual_ner_heedoooch|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|xx|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/heedoooch/wikineural-multilingual-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-win_eurosat_en.md b/docs/_posts/ahmedlone127/2025-01-24-win_eurosat_en.md
new file mode 100644
index 00000000000000..52cb48e3cf53b1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-win_eurosat_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English win_eurosat SwinForImageClassification from MiroJ
+author: John Snow Labs
+name: win_eurosat
+date: 2025-01-24
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`win_eurosat` is a English model originally trained by MiroJ.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/win_eurosat_en_5.5.1_3.0_1737754267709.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/win_eurosat_en_5.5.1_3.0_1737754267709.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""win_eurosat","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("win_eurosat","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|win_eurosat|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/MiroJ/win_eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-win_eurosat_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-win_eurosat_pipeline_en.md
new file mode 100644
index 00000000000000..60776c2968df5d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-win_eurosat_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English win_eurosat_pipeline pipeline SwinForImageClassification from MiroJ
+author: John Snow Labs
+name: win_eurosat_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`win_eurosat_pipeline` is a English model originally trained by MiroJ.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/win_eurosat_pipeline_en_5.5.1_3.0_1737754278553.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/win_eurosat_pipeline_en_5.5.1_3.0_1737754278553.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("win_eurosat_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("win_eurosat_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|win_eurosat_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/MiroJ/win_eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-wnut_17_model_en.md b/docs/_posts/ahmedlone127/2025-01-24-wnut_17_model_en.md
new file mode 100644
index 00000000000000..520bca53dbfe95
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-wnut_17_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English wnut_17_model DistilBertForTokenClassification from nstrn-mo
+author: John Snow Labs
+name: wnut_17_model
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`wnut_17_model` is a English model originally trained by nstrn-mo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/wnut_17_model_en_5.5.1_3.0_1737692497729.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/wnut_17_model_en_5.5.1_3.0_1737692497729.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("wnut_17_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("wnut_17_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|wnut_17_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/nstrn-mo/wnut_17_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-wnut_17_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-wnut_17_model_pipeline_en.md
new file mode 100644
index 00000000000000..22c3a3969194e6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-wnut_17_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English wnut_17_model_pipeline pipeline DistilBertForTokenClassification from nstrn-mo
+author: John Snow Labs
+name: wnut_17_model_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`wnut_17_model_pipeline` is a English model originally trained by nstrn-mo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/wnut_17_model_pipeline_en_5.5.1_3.0_1737692517227.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/wnut_17_model_pipeline_en_5.5.1_3.0_1737692517227.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("wnut_17_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("wnut_17_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|wnut_17_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/nstrn-mo/wnut_17_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_r_base_finetuned_after_mrp_v2_royal_lake_9_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_r_base_finetuned_after_mrp_v2_royal_lake_9_en.md
new file mode 100644
index 00000000000000..da0f641afb3704
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_r_base_finetuned_after_mrp_v2_royal_lake_9_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_r_base_finetuned_after_mrp_v2_royal_lake_9 XlmRoBertaForSequenceClassification from haturusinghe
+author: John Snow Labs
+name: xlm_r_base_finetuned_after_mrp_v2_royal_lake_9
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_r_base_finetuned_after_mrp_v2_royal_lake_9` is a English model originally trained by haturusinghe.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_r_base_finetuned_after_mrp_v2_royal_lake_9_en_5.5.1_3.0_1737714300221.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_r_base_finetuned_after_mrp_v2_royal_lake_9_en_5.5.1_3.0_1737714300221.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_r_base_finetuned_after_mrp_v2_royal_lake_9","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_r_base_finetuned_after_mrp_v2_royal_lake_9", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_r_base_finetuned_after_mrp_v2_royal_lake_9|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|782.7 MB|
+
+## References
+
+https://huggingface.co/haturusinghe/xlm_r_base-finetuned_after_mrp-v2-royal-lake-9
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_r_base_finetuned_after_mrp_v2_royal_lake_9_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_r_base_finetuned_after_mrp_v2_royal_lake_9_pipeline_en.md
new file mode 100644
index 00000000000000..921e990a3d3be4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_r_base_finetuned_after_mrp_v2_royal_lake_9_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_r_base_finetuned_after_mrp_v2_royal_lake_9_pipeline pipeline XlmRoBertaForSequenceClassification from haturusinghe
+author: John Snow Labs
+name: xlm_r_base_finetuned_after_mrp_v2_royal_lake_9_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_r_base_finetuned_after_mrp_v2_royal_lake_9_pipeline` is a English model originally trained by haturusinghe.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_r_base_finetuned_after_mrp_v2_royal_lake_9_pipeline_en_5.5.1_3.0_1737714441319.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_r_base_finetuned_after_mrp_v2_royal_lake_9_pipeline_en_5.5.1_3.0_1737714441319.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_r_base_finetuned_after_mrp_v2_royal_lake_9_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_r_base_finetuned_after_mrp_v2_royal_lake_9_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_r_base_finetuned_after_mrp_v2_royal_lake_9_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|782.7 MB|
+
+## References
+
+https://huggingface.co/haturusinghe/xlm_r_base-finetuned_after_mrp-v2-royal-lake-9
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_r_tydiqa_gs224_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_r_tydiqa_gs224_en.md
new file mode 100644
index 00000000000000..de9b7ae1fef5cf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_r_tydiqa_gs224_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English xlm_r_tydiqa_gs224 XlmRoBertaForQuestionAnswering from gs224
+author: John Snow Labs
+name: xlm_r_tydiqa_gs224
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, xlm_roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_r_tydiqa_gs224` is a English model originally trained by gs224.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_r_tydiqa_gs224_en_5.5.1_3.0_1737753011143.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_r_tydiqa_gs224_en_5.5.1_3.0_1737753011143.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_r_tydiqa_gs224","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_r_tydiqa_gs224", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_r_tydiqa_gs224|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|904.1 MB|
+
+## References
+
+https://huggingface.co/gs224/xlm-r-tydiqa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_r_tydiqa_gs224_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_r_tydiqa_gs224_pipeline_en.md
new file mode 100644
index 00000000000000..efc68c2ed49153
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_r_tydiqa_gs224_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English xlm_r_tydiqa_gs224_pipeline pipeline XlmRoBertaForQuestionAnswering from gs224
+author: John Snow Labs
+name: xlm_r_tydiqa_gs224_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_r_tydiqa_gs224_pipeline` is a English model originally trained by gs224.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_r_tydiqa_gs224_pipeline_en_5.5.1_3.0_1737753105833.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_r_tydiqa_gs224_pipeline_en_5.5.1_3.0_1737753105833.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_r_tydiqa_gs224_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_r_tydiqa_gs224_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_r_tydiqa_gs224_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|904.1 MB|
+
+## References
+
+https://huggingface.co/gs224/xlm-r-tydiqa
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_autext2024_80train_attribution_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_autext2024_80train_attribution_en.md
new file mode 100644
index 00000000000000..46fa9b92b02203
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_autext2024_80train_attribution_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_autext2024_80train_attribution XlmRoBertaForSequenceClassification from ISEGURA
+author: John Snow Labs
+name: xlm_roberta_base_autext2024_80train_attribution
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_autext2024_80train_attribution` is a English model originally trained by ISEGURA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_autext2024_80train_attribution_en_5.5.1_3.0_1737713604641.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_autext2024_80train_attribution_en_5.5.1_3.0_1737713604641.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_autext2024_80train_attribution","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_autext2024_80train_attribution", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_autext2024_80train_attribution|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|825.8 MB|
+
+## References
+
+https://huggingface.co/ISEGURA/xlm-roberta-base-autext2024_80train_attribution
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_autext2024_80train_attribution_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_autext2024_80train_attribution_pipeline_en.md
new file mode 100644
index 00000000000000..b182afe6d75313
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_autext2024_80train_attribution_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_autext2024_80train_attribution_pipeline pipeline XlmRoBertaForSequenceClassification from ISEGURA
+author: John Snow Labs
+name: xlm_roberta_base_autext2024_80train_attribution_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_autext2024_80train_attribution_pipeline` is a English model originally trained by ISEGURA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_autext2024_80train_attribution_pipeline_en_5.5.1_3.0_1737713733487.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_autext2024_80train_attribution_pipeline_en_5.5.1_3.0_1737713733487.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_autext2024_80train_attribution_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_autext2024_80train_attribution_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_autext2024_80train_attribution_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|825.8 MB|
+
+## References
+
+https://huggingface.co/ISEGURA/xlm-roberta-base-autext2024_80train_attribution
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_deletion_multiclass_gr_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_deletion_multiclass_gr_en.md
new file mode 100644
index 00000000000000..28719e43f1ee91
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_deletion_multiclass_gr_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_deletion_multiclass_gr XlmRoBertaForSequenceClassification from research-dump
+author: John Snow Labs
+name: xlm_roberta_base_deletion_multiclass_gr
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_deletion_multiclass_gr` is a English model originally trained by research-dump.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_deletion_multiclass_gr_en_5.5.1_3.0_1737712917646.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_deletion_multiclass_gr_en_5.5.1_3.0_1737712917646.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_deletion_multiclass_gr","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_deletion_multiclass_gr", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_deletion_multiclass_gr|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|778.5 MB|
+
+## References
+
+https://huggingface.co/research-dump/xlm-roberta-base_deletion_multiclass_gr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_deletion_multiclass_gr_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_deletion_multiclass_gr_pipeline_en.md
new file mode 100644
index 00000000000000..0e2ffd0068f2e8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_deletion_multiclass_gr_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_deletion_multiclass_gr_pipeline pipeline XlmRoBertaForSequenceClassification from research-dump
+author: John Snow Labs
+name: xlm_roberta_base_deletion_multiclass_gr_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_deletion_multiclass_gr_pipeline` is a English model originally trained by research-dump.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_deletion_multiclass_gr_pipeline_en_5.5.1_3.0_1737713071731.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_deletion_multiclass_gr_pipeline_en_5.5.1_3.0_1737713071731.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_deletion_multiclass_gr_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_deletion_multiclass_gr_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_deletion_multiclass_gr_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|778.5 MB|
+
+## References
+
+https://huggingface.co/research-dump/xlm-roberta-base_deletion_multiclass_gr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_final_vietnam_train_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_final_vietnam_train_en.md
new file mode 100644
index 00000000000000..2e14fd8d78442e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_final_vietnam_train_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_final_vietnam_train XlmRoBertaForSequenceClassification from ThuyNT03
+author: John Snow Labs
+name: xlm_roberta_base_final_vietnam_train
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_final_vietnam_train` is a English model originally trained by ThuyNT03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_final_vietnam_train_en_5.5.1_3.0_1737712759405.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_final_vietnam_train_en_5.5.1_3.0_1737712759405.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_final_vietnam_train","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_final_vietnam_train", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_final_vietnam_train|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|794.2 MB|
+
+## References
+
+https://huggingface.co/ThuyNT03/xlm-roberta-base-Final_VietNam-train
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_final_vietnam_train_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_final_vietnam_train_pipeline_en.md
new file mode 100644
index 00000000000000..5f4b82c29043ad
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_final_vietnam_train_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_final_vietnam_train_pipeline pipeline XlmRoBertaForSequenceClassification from ThuyNT03
+author: John Snow Labs
+name: xlm_roberta_base_final_vietnam_train_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_final_vietnam_train_pipeline` is a English model originally trained by ThuyNT03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_final_vietnam_train_pipeline_en_5.5.1_3.0_1737712894626.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_final_vietnam_train_pipeline_en_5.5.1_3.0_1737712894626.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_final_vietnam_train_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_final_vietnam_train_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_final_vietnam_train_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|794.3 MB|
+
+## References
+
+https://huggingface.co/ThuyNT03/xlm-roberta-base-Final_VietNam-train
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_all_cotysong113_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_all_cotysong113_en.md
new file mode 100644
index 00000000000000..2640485020fe90
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_all_cotysong113_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_cotysong113 XlmRoBertaForTokenClassification from cotysong113
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_cotysong113
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_cotysong113` is a English model originally trained by cotysong113.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_cotysong113_en_5.5.1_3.0_1737681955406.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_cotysong113_en_5.5.1_3.0_1737681955406.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_cotysong113","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_cotysong113", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_cotysong113|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|856.7 MB|
+
+## References
+
+https://huggingface.co/cotysong113/xlm-roberta-base-finetuned-panx-all
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_all_cotysong113_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_all_cotysong113_pipeline_en.md
new file mode 100644
index 00000000000000..371b6496baaec8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_all_cotysong113_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_cotysong113_pipeline pipeline XlmRoBertaForTokenClassification from cotysong113
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_cotysong113_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_cotysong113_pipeline` is a English model originally trained by cotysong113.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_cotysong113_pipeline_en_5.5.1_3.0_1737682040918.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_cotysong113_pipeline_en_5.5.1_3.0_1737682040918.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_cotysong113_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_cotysong113_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_cotysong113_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|856.7 MB|
+
+## References
+
+https://huggingface.co/cotysong113/xlm-roberta-base-finetuned-panx-all
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_all_nik135_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_all_nik135_en.md
new file mode 100644
index 00000000000000..a1755e48b1a2c0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_all_nik135_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_nik135 XlmRoBertaForTokenClassification from nik135
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_nik135
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_nik135` is a English model originally trained by nik135.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_nik135_en_5.5.1_3.0_1737677139509.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_nik135_en_5.5.1_3.0_1737677139509.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_nik135","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_nik135", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_nik135|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/nik135/xlm-roberta-base-finetuned-panx-all
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_all_nik135_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_all_nik135_pipeline_en.md
new file mode 100644
index 00000000000000..56df6a8d417695
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_all_nik135_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_nik135_pipeline pipeline XlmRoBertaForTokenClassification from nik135
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_nik135_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_nik135_pipeline` is a English model originally trained by nik135.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_nik135_pipeline_en_5.5.1_3.0_1737677226324.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_nik135_pipeline_en_5.5.1_3.0_1737677226324.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_nik135_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_nik135_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_nik135_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/nik135/xlm-roberta-base-finetuned-panx-all
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_arabic_alhamaideh_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_arabic_alhamaideh_en.md
new file mode 100644
index 00000000000000..778f9e58f0ab8b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_arabic_alhamaideh_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_arabic_alhamaideh XlmRoBertaForTokenClassification from alhamaideh
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_arabic_alhamaideh
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_arabic_alhamaideh` is a English model originally trained by alhamaideh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_arabic_alhamaideh_en_5.5.1_3.0_1737681937887.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_arabic_alhamaideh_en_5.5.1_3.0_1737681937887.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_arabic_alhamaideh","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_arabic_alhamaideh", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_arabic_alhamaideh|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|817.9 MB|
+
+## References
+
+https://huggingface.co/alhamaideh/xlm-roberta-base-finetuned-panx-ar
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_arabic_alhamaideh_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_arabic_alhamaideh_pipeline_en.md
new file mode 100644
index 00000000000000..bf316b28f241bf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_arabic_alhamaideh_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_arabic_alhamaideh_pipeline pipeline XlmRoBertaForTokenClassification from alhamaideh
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_arabic_alhamaideh_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_arabic_alhamaideh_pipeline` is a English model originally trained by alhamaideh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_arabic_alhamaideh_pipeline_en_5.5.1_3.0_1737682046151.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_arabic_alhamaideh_pipeline_en_5.5.1_3.0_1737682046151.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_arabic_alhamaideh_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_arabic_alhamaideh_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_arabic_alhamaideh_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|817.9 MB|
+
+## References
+
+https://huggingface.co/alhamaideh/xlm-roberta-base-finetuned-panx-ar
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_english_ashkanero_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_english_ashkanero_en.md
new file mode 100644
index 00000000000000..9776095fc541a8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_english_ashkanero_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_ashkanero XlmRoBertaForTokenClassification from Ashkanero
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_ashkanero
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_ashkanero` is a English model originally trained by Ashkanero.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_ashkanero_en_5.5.1_3.0_1737677882751.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_ashkanero_en_5.5.1_3.0_1737677882751.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_ashkanero","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_ashkanero", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_ashkanero|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/Ashkanero/xlm-roberta-base-finetuned-panx-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_english_ashkanero_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_english_ashkanero_pipeline_en.md
new file mode 100644
index 00000000000000..8043c87c4b1fe1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_english_ashkanero_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_ashkanero_pipeline pipeline XlmRoBertaForTokenClassification from Ashkanero
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_ashkanero_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_ashkanero_pipeline` is a English model originally trained by Ashkanero.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_ashkanero_pipeline_en_5.5.1_3.0_1737677992973.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_ashkanero_pipeline_en_5.5.1_3.0_1737677992973.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_ashkanero_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_ashkanero_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_ashkanero_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/Ashkanero/xlm-roberta-base-finetuned-panx-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_english_m_rezaei_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_english_m_rezaei_en.md
new file mode 100644
index 00000000000000..8e416d472f1f01
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_english_m_rezaei_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_m_rezaei XlmRoBertaForTokenClassification from M-Rezaei
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_m_rezaei
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_m_rezaei` is a English model originally trained by M-Rezaei.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_m_rezaei_en_5.5.1_3.0_1737680837847.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_m_rezaei_en_5.5.1_3.0_1737680837847.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_m_rezaei","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_m_rezaei", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_m_rezaei|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|817.2 MB|
+
+## References
+
+https://huggingface.co/M-Rezaei/xlm-roberta-base-finetuned-panx-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_english_m_rezaei_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_english_m_rezaei_pipeline_en.md
new file mode 100644
index 00000000000000..395e3b39e4f121
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_english_m_rezaei_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_m_rezaei_pipeline pipeline XlmRoBertaForTokenClassification from M-Rezaei
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_m_rezaei_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_m_rezaei_pipeline` is a English model originally trained by M-Rezaei.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_m_rezaei_pipeline_en_5.5.1_3.0_1737680940720.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_m_rezaei_pipeline_en_5.5.1_3.0_1737680940720.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_m_rezaei_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_m_rezaei_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_m_rezaei_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|817.2 MB|
+
+## References
+
+https://huggingface.co/M-Rezaei/xlm-roberta-base-finetuned-panx-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_english_shawki11_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_english_shawki11_en.md
new file mode 100644
index 00000000000000..96722968ef5b3c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_english_shawki11_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_shawki11 XlmRoBertaForTokenClassification from Shawki11
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_shawki11
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_shawki11` is a English model originally trained by Shawki11.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_shawki11_en_5.5.1_3.0_1737679290531.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_shawki11_en_5.5.1_3.0_1737679290531.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_shawki11","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_shawki11", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_shawki11|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|845.2 MB|
+
+## References
+
+https://huggingface.co/Shawki11/xlm-roberta-base-finetuned-panx-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_english_shawki11_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_english_shawki11_pipeline_en.md
new file mode 100644
index 00000000000000..5b801fa32e70ee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_english_shawki11_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_shawki11_pipeline pipeline XlmRoBertaForTokenClassification from Shawki11
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_shawki11_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_shawki11_pipeline` is a English model originally trained by Shawki11.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_shawki11_pipeline_en_5.5.1_3.0_1737679384129.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_shawki11_pipeline_en_5.5.1_3.0_1737679384129.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_shawki11_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_shawki11_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_shawki11_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|845.2 MB|
+
+## References
+
+https://huggingface.co/Shawki11/xlm-roberta-base-finetuned-panx-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_english_thundergod_zenitsu_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_english_thundergod_zenitsu_en.md
new file mode 100644
index 00000000000000..c8dfa15c106b71
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_english_thundergod_zenitsu_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_thundergod_zenitsu XlmRoBertaForTokenClassification from thundergod-zenitsu
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_thundergod_zenitsu
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_thundergod_zenitsu` is a English model originally trained by thundergod-zenitsu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_thundergod_zenitsu_en_5.5.1_3.0_1737682516871.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_thundergod_zenitsu_en_5.5.1_3.0_1737682516871.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_thundergod_zenitsu","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_thundergod_zenitsu", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_thundergod_zenitsu|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/thundergod-zenitsu/xlm-roberta-base-finetuned-panx-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_english_thundergod_zenitsu_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_english_thundergod_zenitsu_pipeline_en.md
new file mode 100644
index 00000000000000..a26fa91685a394
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_english_thundergod_zenitsu_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_thundergod_zenitsu_pipeline pipeline XlmRoBertaForTokenClassification from thundergod-zenitsu
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_thundergod_zenitsu_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_thundergod_zenitsu_pipeline` is a English model originally trained by thundergod-zenitsu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_thundergod_zenitsu_pipeline_en_5.5.1_3.0_1737682631323.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_thundergod_zenitsu_pipeline_en_5.5.1_3.0_1737682631323.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_thundergod_zenitsu_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_thundergod_zenitsu_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_thundergod_zenitsu_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/thundergod-zenitsu/xlm-roberta-base-finetuned-panx-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_finnish_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_finnish_en.md
new file mode 100644
index 00000000000000..7bda4ee99bd1db
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_finnish_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_finnish XlmRoBertaForTokenClassification from zuhayr
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_finnish
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_finnish` is a English model originally trained by zuhayr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_finnish_en_5.5.1_3.0_1737682963105.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_finnish_en_5.5.1_3.0_1737682963105.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_finnish","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_finnish", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_finnish|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|836.7 MB|
+
+## References
+
+https://huggingface.co/zuhayr/xlm-roberta-base-finetuned-panx-fi
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_finnish_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_finnish_pipeline_en.md
new file mode 100644
index 00000000000000..4f1d9e2e3cbd5e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_finnish_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_finnish_pipeline pipeline XlmRoBertaForTokenClassification from zuhayr
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_finnish_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_finnish_pipeline` is a English model originally trained by zuhayr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_finnish_pipeline_en_5.5.1_3.0_1737683055505.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_finnish_pipeline_en_5.5.1_3.0_1737683055505.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_finnish_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_finnish_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_finnish_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|836.7 MB|
+
+## References
+
+https://huggingface.co/zuhayr/xlm-roberta-base-finetuned-panx-fi
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_french_ameko_dev_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_french_ameko_dev_en.md
new file mode 100644
index 00000000000000..02d54ef0325eed
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_french_ameko_dev_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_ameko_dev XlmRoBertaForTokenClassification from ameko-dev
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_ameko_dev
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_ameko_dev` is a English model originally trained by ameko-dev.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_ameko_dev_en_5.5.1_3.0_1737681553812.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_ameko_dev_en_5.5.1_3.0_1737681553812.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_ameko_dev","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_ameko_dev", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_ameko_dev|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/ameko-dev/xlm-roberta-base-finetuned-panx-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_french_ameko_dev_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_french_ameko_dev_pipeline_en.md
new file mode 100644
index 00000000000000..52cae63cd71333
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_french_ameko_dev_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_ameko_dev_pipeline pipeline XlmRoBertaForTokenClassification from ameko-dev
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_ameko_dev_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_ameko_dev_pipeline` is a English model originally trained by ameko-dev.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_ameko_dev_pipeline_en_5.5.1_3.0_1737681647071.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_ameko_dev_pipeline_en_5.5.1_3.0_1737681647071.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_ameko_dev_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_ameko_dev_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_ameko_dev_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/ameko-dev/xlm-roberta-base-finetuned-panx-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_french_cotysong113_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_french_cotysong113_en.md
new file mode 100644
index 00000000000000..e39a2979a6fd50
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_french_cotysong113_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_cotysong113 XlmRoBertaForTokenClassification from cotysong113
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_cotysong113
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_cotysong113` is a English model originally trained by cotysong113.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_cotysong113_en_5.5.1_3.0_1737678877730.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_cotysong113_en_5.5.1_3.0_1737678877730.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_cotysong113","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_cotysong113", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_cotysong113|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|838.3 MB|
+
+## References
+
+https://huggingface.co/cotysong113/xlm-roberta-base-finetuned-panx-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_french_cotysong113_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_french_cotysong113_pipeline_en.md
new file mode 100644
index 00000000000000..27b675525d3b63
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_french_cotysong113_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_cotysong113_pipeline pipeline XlmRoBertaForTokenClassification from cotysong113
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_cotysong113_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_cotysong113_pipeline` is a English model originally trained by cotysong113.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_cotysong113_pipeline_en_5.5.1_3.0_1737678971436.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_cotysong113_pipeline_en_5.5.1_3.0_1737678971436.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_cotysong113_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_cotysong113_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_cotysong113_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|838.3 MB|
+
+## References
+
+https://huggingface.co/cotysong113/xlm-roberta-base-finetuned-panx-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_french_do1232_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_french_do1232_en.md
new file mode 100644
index 00000000000000..5e734825866bb2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_french_do1232_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_do1232 XlmRoBertaForTokenClassification from do1232
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_do1232
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_do1232` is a English model originally trained by do1232.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_do1232_en_5.5.1_3.0_1737683127785.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_do1232_en_5.5.1_3.0_1737683127785.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_do1232","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_do1232", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_do1232|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/do1232/xlm-roberta-base-finetuned-panx-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_french_do1232_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_french_do1232_pipeline_en.md
new file mode 100644
index 00000000000000..e81da424ff01fb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_french_do1232_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_do1232_pipeline pipeline XlmRoBertaForTokenClassification from do1232
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_do1232_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_do1232_pipeline` is a English model originally trained by do1232.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_do1232_pipeline_en_5.5.1_3.0_1737683222643.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_do1232_pipeline_en_5.5.1_3.0_1737683222643.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_do1232_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_do1232_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_do1232_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/do1232/xlm-roberta-base-finetuned-panx-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_french_fr.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_french_fr.md
new file mode 100644
index 00000000000000..d05adc16130aad
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_french_fr.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: French xlm_roberta_base_finetuned_panx_french XlmRoBertaForTokenClassification from Adriana213
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french
+date: 2025-01-24
+tags: [fr, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: fr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french` is a French model originally trained by Adriana213.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_fr_5.5.1_3.0_1737679573122.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_fr_5.5.1_3.0_1737679573122.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french","fr") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french", "fr")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|fr|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/Adriana213/xlm-roberta-base-finetuned-panx-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_french_m_rezaei_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_french_m_rezaei_en.md
new file mode 100644
index 00000000000000..db2bf4138f1851
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_french_m_rezaei_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_m_rezaei XlmRoBertaForTokenClassification from M-Rezaei
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_m_rezaei
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_m_rezaei` is a English model originally trained by M-Rezaei.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_m_rezaei_en_5.5.1_3.0_1737680367845.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_m_rezaei_en_5.5.1_3.0_1737680367845.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_m_rezaei","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_m_rezaei", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_m_rezaei|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|831.8 MB|
+
+## References
+
+https://huggingface.co/M-Rezaei/xlm-roberta-base-finetuned-panx-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_french_m_rezaei_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_french_m_rezaei_pipeline_en.md
new file mode 100644
index 00000000000000..9a2788f4dd5adf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_french_m_rezaei_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_m_rezaei_pipeline pipeline XlmRoBertaForTokenClassification from M-Rezaei
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_m_rezaei_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_m_rezaei_pipeline` is a English model originally trained by M-Rezaei.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_m_rezaei_pipeline_en_5.5.1_3.0_1737680460627.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_m_rezaei_pipeline_en_5.5.1_3.0_1737680460627.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_m_rezaei_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_m_rezaei_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_m_rezaei_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|831.8 MB|
+
+## References
+
+https://huggingface.co/M-Rezaei/xlm-roberta-base-finetuned-panx-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_french_pipeline_fr.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_french_pipeline_fr.md
new file mode 100644
index 00000000000000..b8bca0866c4c94
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_french_pipeline_fr.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: French xlm_roberta_base_finetuned_panx_french_pipeline pipeline XlmRoBertaForTokenClassification from Adriana213
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_pipeline
+date: 2025-01-24
+tags: [fr, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: fr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_pipeline` is a French model originally trained by Adriana213.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_pipeline_fr_5.5.1_3.0_1737679668242.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_pipeline_fr_5.5.1_3.0_1737679668242.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_pipeline", lang = "fr")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_pipeline", lang = "fr")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|fr|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/Adriana213/xlm-roberta-base-finetuned-panx-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_french_qkdaf_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_french_qkdaf_en.md
new file mode 100644
index 00000000000000..6acbcb3c3b56b0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_french_qkdaf_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_qkdaf XlmRoBertaForTokenClassification from qkdaf
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_qkdaf
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_qkdaf` is a English model originally trained by qkdaf.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_qkdaf_en_5.5.1_3.0_1737680033314.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_qkdaf_en_5.5.1_3.0_1737680033314.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_qkdaf","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_qkdaf", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_qkdaf|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/qkdaf/xlm-roberta-base-finetuned-panx-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_french_qkdaf_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_french_qkdaf_pipeline_en.md
new file mode 100644
index 00000000000000..d4ec953c4981eb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_french_qkdaf_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_qkdaf_pipeline pipeline XlmRoBertaForTokenClassification from qkdaf
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_qkdaf_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_qkdaf_pipeline` is a English model originally trained by qkdaf.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_qkdaf_pipeline_en_5.5.1_3.0_1737680129036.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_qkdaf_pipeline_en_5.5.1_3.0_1737680129036.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_qkdaf_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_qkdaf_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_qkdaf_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/qkdaf/xlm-roberta-base-finetuned-panx-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_french_shawki11_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_french_shawki11_en.md
new file mode 100644
index 00000000000000..3fff4010f2f962
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_french_shawki11_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_shawki11 XlmRoBertaForTokenClassification from Shawki11
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_shawki11
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_shawki11` is a English model originally trained by Shawki11.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_shawki11_en_5.5.1_3.0_1737681754810.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_shawki11_en_5.5.1_3.0_1737681754810.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_shawki11","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_shawki11", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_shawki11|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|842.9 MB|
+
+## References
+
+https://huggingface.co/Shawki11/xlm-roberta-base-finetuned-panx-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_french_shawki11_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_french_shawki11_pipeline_en.md
new file mode 100644
index 00000000000000..89c34c402f26e0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_french_shawki11_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_shawki11_pipeline pipeline XlmRoBertaForTokenClassification from Shawki11
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_shawki11_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_shawki11_pipeline` is a English model originally trained by Shawki11.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_shawki11_pipeline_en_5.5.1_3.0_1737681842789.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_shawki11_pipeline_en_5.5.1_3.0_1737681842789.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_shawki11_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_shawki11_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_shawki11_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|842.9 MB|
+
+## References
+
+https://huggingface.co/Shawki11/xlm-roberta-base-finetuned-panx-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_french_vaibhavdlights_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_french_vaibhavdlights_en.md
new file mode 100644
index 00000000000000..043d8f07af84de
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_french_vaibhavdlights_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_vaibhavdlights XlmRoBertaForTokenClassification from VaibhavdLights
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_vaibhavdlights
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_vaibhavdlights` is a English model originally trained by VaibhavdLights.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_vaibhavdlights_en_5.5.1_3.0_1737682169827.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_vaibhavdlights_en_5.5.1_3.0_1737682169827.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_vaibhavdlights","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_vaibhavdlights", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_vaibhavdlights|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/VaibhavdLights/xlm-roberta-base-finetuned-panx-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_french_vaibhavdlights_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_french_vaibhavdlights_pipeline_en.md
new file mode 100644
index 00000000000000..c876e3375a16db
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_french_vaibhavdlights_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_vaibhavdlights_pipeline pipeline XlmRoBertaForTokenClassification from VaibhavdLights
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_vaibhavdlights_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_vaibhavdlights_pipeline` is a English model originally trained by VaibhavdLights.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_vaibhavdlights_pipeline_en_5.5.1_3.0_1737682265166.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_vaibhavdlights_pipeline_en_5.5.1_3.0_1737682265166.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_vaibhavdlights_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_vaibhavdlights_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_vaibhavdlights_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/VaibhavdLights/xlm-roberta-base-finetuned-panx-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_ajit_transformer_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_ajit_transformer_en.md
new file mode 100644
index 00000000000000..b313bb9355e593
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_ajit_transformer_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_ajit_transformer XlmRoBertaForTokenClassification from ajit-transformer
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_ajit_transformer
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_ajit_transformer` is a English model originally trained by ajit-transformer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_ajit_transformer_en_5.5.1_3.0_1737678701686.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_ajit_transformer_en_5.5.1_3.0_1737678701686.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_ajit_transformer","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_ajit_transformer", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_ajit_transformer|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|851.7 MB|
+
+## References
+
+https://huggingface.co/ajit-transformer/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_ajit_transformer_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_ajit_transformer_pipeline_en.md
new file mode 100644
index 00000000000000..f063c5ae5c91a3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_ajit_transformer_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_ajit_transformer_pipeline pipeline XlmRoBertaForTokenClassification from ajit-transformer
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_ajit_transformer_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_ajit_transformer_pipeline` is a English model originally trained by ajit-transformer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_ajit_transformer_pipeline_en_5.5.1_3.0_1737678778031.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_ajit_transformer_pipeline_en_5.5.1_3.0_1737678778031.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_ajit_transformer_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_ajit_transformer_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_ajit_transformer_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|851.8 MB|
+
+## References
+
+https://huggingface.co/ajit-transformer/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_cogsci13_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_cogsci13_en.md
new file mode 100644
index 00000000000000..f470df2eae4fe7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_cogsci13_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_cogsci13 XlmRoBertaForTokenClassification from cogsci13
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_cogsci13
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_cogsci13` is a English model originally trained by cogsci13.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_cogsci13_en_5.5.1_3.0_1737679054452.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_cogsci13_en_5.5.1_3.0_1737679054452.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_cogsci13","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_cogsci13", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_cogsci13|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/cogsci13/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_cogsci13_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_cogsci13_pipeline_en.md
new file mode 100644
index 00000000000000..7944ff82dba043
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_cogsci13_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_cogsci13_pipeline pipeline XlmRoBertaForTokenClassification from cogsci13
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_cogsci13_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_cogsci13_pipeline` is a English model originally trained by cogsci13.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_cogsci13_pipeline_en_5.5.1_3.0_1737679142340.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_cogsci13_pipeline_en_5.5.1_3.0_1737679142340.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_cogsci13_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_cogsci13_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_cogsci13_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/cogsci13/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_dhruvaray_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_dhruvaray_en.md
new file mode 100644
index 00000000000000..569f01423c3873
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_dhruvaray_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_dhruvaray XlmRoBertaForTokenClassification from dhruvaray
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_dhruvaray
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_dhruvaray` is a English model originally trained by dhruvaray.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_dhruvaray_en_5.5.1_3.0_1737677235579.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_dhruvaray_en_5.5.1_3.0_1737677235579.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_dhruvaray","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_dhruvaray", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_dhruvaray|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/dhruvaray/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_dhruvaray_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_dhruvaray_pipeline_en.md
new file mode 100644
index 00000000000000..08bb153da204ec
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_dhruvaray_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_dhruvaray_pipeline pipeline XlmRoBertaForTokenClassification from dhruvaray
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_dhruvaray_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_dhruvaray_pipeline` is a English model originally trained by dhruvaray.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_dhruvaray_pipeline_en_5.5.1_3.0_1737677322975.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_dhruvaray_pipeline_en_5.5.1_3.0_1737677322975.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_dhruvaray_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_dhruvaray_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_dhruvaray_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/dhruvaray/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_dksm_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_dksm_en.md
new file mode 100644
index 00000000000000..2335c1029c069f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_dksm_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_dksm XlmRoBertaForTokenClassification from dimmyk
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_dksm
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_dksm` is a English model originally trained by dimmyk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_dksm_en_5.5.1_3.0_1737680206313.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_dksm_en_5.5.1_3.0_1737680206313.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_dksm","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_dksm", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_dksm|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|816.8 MB|
+
+## References
+
+https://huggingface.co/dimmyk/xlm-roberta-base-finetuned-panx-de-dksm
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_dksm_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_dksm_pipeline_en.md
new file mode 100644
index 00000000000000..810ef185f24275
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_dksm_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_dksm_pipeline pipeline XlmRoBertaForTokenClassification from dimmyk
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_dksm_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_dksm_pipeline` is a English model originally trained by dimmyk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_dksm_pipeline_en_5.5.1_3.0_1737680325101.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_dksm_pipeline_en_5.5.1_3.0_1737680325101.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_dksm_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_dksm_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_dksm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|816.8 MB|
+
+## References
+
+https://huggingface.co/dimmyk/xlm-roberta-base-finetuned-panx-de-dksm
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_french_do1232_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_french_do1232_en.md
new file mode 100644
index 00000000000000..190e32e70c59d3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_french_do1232_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_do1232 XlmRoBertaForTokenClassification from do1232
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_do1232
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_do1232` is a English model originally trained by do1232.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_do1232_en_5.5.1_3.0_1737678873182.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_do1232_en_5.5.1_3.0_1737678873182.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_do1232","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_do1232", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_do1232|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/do1232/xlm-roberta-base-finetuned-panx-de-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_french_do1232_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_french_do1232_pipeline_en.md
new file mode 100644
index 00000000000000..6ef37cf02b68e3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_french_do1232_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_do1232_pipeline pipeline XlmRoBertaForTokenClassification from do1232
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_do1232_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_do1232_pipeline` is a English model originally trained by do1232.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_do1232_pipeline_en_5.5.1_3.0_1737678968827.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_do1232_pipeline_en_5.5.1_3.0_1737678968827.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_do1232_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_do1232_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_do1232_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/do1232/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_french_dro14_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_french_dro14_en.md
new file mode 100644
index 00000000000000..609959a88d9f3c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_french_dro14_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_dro14 XlmRoBertaForTokenClassification from dro14
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_dro14
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_dro14` is a English model originally trained by dro14.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_dro14_en_5.5.1_3.0_1737683247810.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_dro14_en_5.5.1_3.0_1737683247810.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_dro14","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_dro14", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_dro14|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/dro14/xlm-roberta-base-finetuned-panx-de-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_french_dro14_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_french_dro14_pipeline_en.md
new file mode 100644
index 00000000000000..74abe0855bb820
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_french_dro14_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_dro14_pipeline pipeline XlmRoBertaForTokenClassification from dro14
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_dro14_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_dro14_pipeline` is a English model originally trained by dro14.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_dro14_pipeline_en_5.5.1_3.0_1737683336420.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_dro14_pipeline_en_5.5.1_3.0_1737683336420.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_dro14_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_dro14_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_dro14_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/dro14/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_french_jonghwanbaek1_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_french_jonghwanbaek1_en.md
new file mode 100644
index 00000000000000..944c48a9865f44
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_french_jonghwanbaek1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_jonghwanbaek1 XlmRoBertaForTokenClassification from jonghwanbaek1
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_jonghwanbaek1
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_jonghwanbaek1` is a English model originally trained by jonghwanbaek1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_jonghwanbaek1_en_5.5.1_3.0_1737682577094.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_jonghwanbaek1_en_5.5.1_3.0_1737682577094.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_jonghwanbaek1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_jonghwanbaek1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_jonghwanbaek1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/jonghwanbaek1/xlm-roberta-base-finetuned-panx-de-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_french_jonghwanbaek1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_french_jonghwanbaek1_pipeline_en.md
new file mode 100644
index 00000000000000..4774a514c14637
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_french_jonghwanbaek1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_jonghwanbaek1_pipeline pipeline XlmRoBertaForTokenClassification from jonghwanbaek1
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_jonghwanbaek1_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_jonghwanbaek1_pipeline` is a English model originally trained by jonghwanbaek1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_jonghwanbaek1_pipeline_en_5.5.1_3.0_1737682668440.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_jonghwanbaek1_pipeline_en_5.5.1_3.0_1737682668440.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_jonghwanbaek1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_jonghwanbaek1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_jonghwanbaek1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/jonghwanbaek1/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_french_mohamedalaa00_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_french_mohamedalaa00_en.md
new file mode 100644
index 00000000000000..3ce2112842cdce
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_french_mohamedalaa00_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_mohamedalaa00 XlmRoBertaForTokenClassification from MohamedAlaa00
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_mohamedalaa00
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_mohamedalaa00` is a English model originally trained by MohamedAlaa00.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_mohamedalaa00_en_5.5.1_3.0_1737682306771.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_mohamedalaa00_en_5.5.1_3.0_1737682306771.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_mohamedalaa00","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_mohamedalaa00", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_mohamedalaa00|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|853.0 MB|
+
+## References
+
+https://huggingface.co/MohamedAlaa00/xlm-roberta-base-finetuned-panx-de-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_french_mohamedalaa00_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_french_mohamedalaa00_pipeline_en.md
new file mode 100644
index 00000000000000..0dfa45b33c2a06
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_french_mohamedalaa00_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_mohamedalaa00_pipeline pipeline XlmRoBertaForTokenClassification from MohamedAlaa00
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_mohamedalaa00_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_mohamedalaa00_pipeline` is a English model originally trained by MohamedAlaa00.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_mohamedalaa00_pipeline_en_5.5.1_3.0_1737682391030.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_mohamedalaa00_pipeline_en_5.5.1_3.0_1737682391030.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_mohamedalaa00_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_mohamedalaa00_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_mohamedalaa00_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|853.0 MB|
+
+## References
+
+https://huggingface.co/MohamedAlaa00/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_french_nik135_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_french_nik135_en.md
new file mode 100644
index 00000000000000..e943a7da93ebca
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_french_nik135_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_nik135 XlmRoBertaForTokenClassification from nik135
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_nik135
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_nik135` is a English model originally trained by nik135.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_nik135_en_5.5.1_3.0_1737681827062.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_nik135_en_5.5.1_3.0_1737681827062.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_nik135","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_nik135", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_nik135|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/nik135/xlm-roberta-base-finetuned-panx-de-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_french_nik135_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_french_nik135_pipeline_en.md
new file mode 100644
index 00000000000000..60d164eb0742e0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_french_nik135_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_nik135_pipeline pipeline XlmRoBertaForTokenClassification from nik135
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_nik135_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_nik135_pipeline` is a English model originally trained by nik135.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_nik135_pipeline_en_5.5.1_3.0_1737681917366.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_nik135_pipeline_en_5.5.1_3.0_1737681917366.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_nik135_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_nik135_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_nik135_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/nik135/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_french_yashcfc_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_french_yashcfc_en.md
new file mode 100644
index 00000000000000..9a9679c072df8e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_french_yashcfc_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_yashcfc XlmRoBertaForTokenClassification from yashcfc
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_yashcfc
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_yashcfc` is a English model originally trained by yashcfc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_yashcfc_en_5.5.1_3.0_1737677922904.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_yashcfc_en_5.5.1_3.0_1737677922904.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_yashcfc","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_yashcfc", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_yashcfc|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/yashcfc/xlm-roberta-base-finetuned-panx-de-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_french_yashcfc_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_french_yashcfc_pipeline_en.md
new file mode 100644
index 00000000000000..fd6ef2048b6016
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_french_yashcfc_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_yashcfc_pipeline pipeline XlmRoBertaForTokenClassification from yashcfc
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_yashcfc_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_yashcfc_pipeline` is a English model originally trained by yashcfc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_yashcfc_pipeline_en_5.5.1_3.0_1737678012968.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_yashcfc_pipeline_en_5.5.1_3.0_1737678012968.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_yashcfc_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_yashcfc_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_yashcfc_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/yashcfc/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_kajetanfrackowiak_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_kajetanfrackowiak_en.md
new file mode 100644
index 00000000000000..fe97ab0561acbc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_kajetanfrackowiak_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_kajetanfrackowiak XlmRoBertaForTokenClassification from KajetanFrackowiak
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_kajetanfrackowiak
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_kajetanfrackowiak` is a English model originally trained by KajetanFrackowiak.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_kajetanfrackowiak_en_5.5.1_3.0_1737682939612.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_kajetanfrackowiak_en_5.5.1_3.0_1737682939612.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_kajetanfrackowiak","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_kajetanfrackowiak", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_kajetanfrackowiak|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/KajetanFrackowiak/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_kajetanfrackowiak_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_kajetanfrackowiak_pipeline_en.md
new file mode 100644
index 00000000000000..3f57167cbad3e1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_kajetanfrackowiak_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_kajetanfrackowiak_pipeline pipeline XlmRoBertaForTokenClassification from KajetanFrackowiak
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_kajetanfrackowiak_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_kajetanfrackowiak_pipeline` is a English model originally trained by KajetanFrackowiak.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_kajetanfrackowiak_pipeline_en_5.5.1_3.0_1737683028812.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_kajetanfrackowiak_pipeline_en_5.5.1_3.0_1737683028812.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_kajetanfrackowiak_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_kajetanfrackowiak_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_kajetanfrackowiak_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/KajetanFrackowiak/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_kiptets_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_kiptets_en.md
new file mode 100644
index 00000000000000..90453372aebc13
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_kiptets_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_kiptets XlmRoBertaForTokenClassification from kiptets
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_kiptets
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_kiptets` is a English model originally trained by kiptets.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_kiptets_en_5.5.1_3.0_1737679080409.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_kiptets_en_5.5.1_3.0_1737679080409.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_kiptets","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_kiptets", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_kiptets|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/kiptets/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_kiptets_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_kiptets_pipeline_en.md
new file mode 100644
index 00000000000000..b9c947179695f0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_kiptets_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_kiptets_pipeline pipeline XlmRoBertaForTokenClassification from kiptets
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_kiptets_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_kiptets_pipeline` is a English model originally trained by kiptets.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_kiptets_pipeline_en_5.5.1_3.0_1737679169183.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_kiptets_pipeline_en_5.5.1_3.0_1737679169183.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_kiptets_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_kiptets_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_kiptets_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/kiptets/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_loki47_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_loki47_en.md
new file mode 100644
index 00000000000000..c27c81645a6da0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_loki47_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_loki47 XlmRoBertaForTokenClassification from loki47
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_loki47
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_loki47` is a English model originally trained by loki47.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_loki47_en_5.5.1_3.0_1737682729559.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_loki47_en_5.5.1_3.0_1737682729559.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_loki47","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_loki47", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_loki47|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/loki47/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_loki47_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_loki47_pipeline_en.md
new file mode 100644
index 00000000000000..569e25dfc67487
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_loki47_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_loki47_pipeline pipeline XlmRoBertaForTokenClassification from loki47
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_loki47_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_loki47_pipeline` is a English model originally trained by loki47.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_loki47_pipeline_en_5.5.1_3.0_1737682817184.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_loki47_pipeline_en_5.5.1_3.0_1737682817184.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_loki47_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_loki47_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_loki47_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/loki47/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_m_rezaei_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_m_rezaei_en.md
new file mode 100644
index 00000000000000..1962be0d5c2247
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_m_rezaei_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_m_rezaei XlmRoBertaForTokenClassification from M-Rezaei
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_m_rezaei
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_m_rezaei` is a English model originally trained by M-Rezaei.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_m_rezaei_en_5.5.1_3.0_1737682259455.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_m_rezaei_en_5.5.1_3.0_1737682259455.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_m_rezaei","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_m_rezaei", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_m_rezaei|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|830.1 MB|
+
+## References
+
+https://huggingface.co/M-Rezaei/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_m_rezaei_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_m_rezaei_pipeline_en.md
new file mode 100644
index 00000000000000..2fd78becbd05fd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_m_rezaei_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_m_rezaei_pipeline pipeline XlmRoBertaForTokenClassification from M-Rezaei
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_m_rezaei_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_m_rezaei_pipeline` is a English model originally trained by M-Rezaei.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_m_rezaei_pipeline_en_5.5.1_3.0_1737682355260.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_m_rezaei_pipeline_en_5.5.1_3.0_1737682355260.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_m_rezaei_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_m_rezaei_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_m_rezaei_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|830.1 MB|
+
+## References
+
+https://huggingface.co/M-Rezaei/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_robercg33_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_robercg33_en.md
new file mode 100644
index 00000000000000..2eb091651ea7bf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_robercg33_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_robercg33 XlmRoBertaForTokenClassification from robercg33
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_robercg33
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_robercg33` is a English model originally trained by robercg33.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_robercg33_en_5.5.1_3.0_1737680362879.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_robercg33_en_5.5.1_3.0_1737680362879.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_robercg33","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_robercg33", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_robercg33|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/robercg33/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_robercg33_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_robercg33_pipeline_en.md
new file mode 100644
index 00000000000000..08da223a97ffb0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_robercg33_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_robercg33_pipeline pipeline XlmRoBertaForTokenClassification from robercg33
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_robercg33_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_robercg33_pipeline` is a English model originally trained by robercg33.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_robercg33_pipeline_en_5.5.1_3.0_1737680454695.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_robercg33_pipeline_en_5.5.1_3.0_1737680454695.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_robercg33_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_robercg33_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_robercg33_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/robercg33/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_snagmin_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_snagmin_en.md
new file mode 100644
index 00000000000000..03fd3b8517e5f3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_snagmin_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_snagmin XlmRoBertaForTokenClassification from snagmin
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_snagmin
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_snagmin` is a English model originally trained by snagmin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_snagmin_en_5.5.1_3.0_1737682053287.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_snagmin_en_5.5.1_3.0_1737682053287.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_snagmin","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_snagmin", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_snagmin|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/snagmin/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_snagmin_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_snagmin_pipeline_en.md
new file mode 100644
index 00000000000000..23bf7ff36a6b87
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_snagmin_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_snagmin_pipeline pipeline XlmRoBertaForTokenClassification from snagmin
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_snagmin_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_snagmin_pipeline` is a English model originally trained by snagmin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_snagmin_pipeline_en_5.5.1_3.0_1737682153999.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_snagmin_pipeline_en_5.5.1_3.0_1737682153999.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_snagmin_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_snagmin_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_snagmin_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/snagmin/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_vantaa32_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_vantaa32_en.md
new file mode 100644
index 00000000000000..df8426a23a794a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_vantaa32_en.md
@@ -0,0 +1,96 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_vantaa32 XlmRoBertaForTokenClassification from vantaa32
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_vantaa32
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_vantaa32` is a English model originally trained by vantaa32.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_vantaa32_en_5.5.1_3.0_1737682458963.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_vantaa32_en_5.5.1_3.0_1737682458963.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_vantaa32","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_vantaa32", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_vantaa32|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+References
+
+https://huggingface.co/vantaa32/xlm-roberta-base-finetuned_panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_vantaa32_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_vantaa32_pipeline_en.md
new file mode 100644
index 00000000000000..0832047c7bd69a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_german_vantaa32_pipeline_en.md
@@ -0,0 +1,72 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_vantaa32_pipeline pipeline XlmRoBertaForTokenClassification from vantaa32
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_vantaa32_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_vantaa32_pipeline` is a English model originally trained by vantaa32.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_vantaa32_pipeline_en_5.5.1_3.0_1737682548036.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_vantaa32_pipeline_en_5.5.1_3.0_1737682548036.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_vantaa32_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_vantaa32_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_vantaa32_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+References
+
+https://huggingface.co/vantaa32/xlm-roberta-base-finetuned_panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_italian_btown2_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_italian_btown2_en.md
new file mode 100644
index 00000000000000..24e3e617296b9b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_italian_btown2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_btown2 XlmRoBertaForTokenClassification from btown2
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_btown2
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_btown2` is a English model originally trained by btown2.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_btown2_en_5.5.1_3.0_1737683136480.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_btown2_en_5.5.1_3.0_1737683136480.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_btown2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_btown2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_btown2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|816.7 MB|
+
+## References
+
+https://huggingface.co/btown2/xlm-roberta-base-finetuned-panx-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_italian_btown2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_italian_btown2_pipeline_en.md
new file mode 100644
index 00000000000000..cf7363820fd8e1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_italian_btown2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_btown2_pipeline pipeline XlmRoBertaForTokenClassification from btown2
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_btown2_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_btown2_pipeline` is a English model originally trained by btown2.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_btown2_pipeline_en_5.5.1_3.0_1737683238774.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_btown2_pipeline_en_5.5.1_3.0_1737683238774.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_btown2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_btown2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_btown2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|816.8 MB|
+
+## References
+
+https://huggingface.co/btown2/xlm-roberta-base-finetuned-panx-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_italian_jongbaly_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_italian_jongbaly_en.md
new file mode 100644
index 00000000000000..417ad49094d7cf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_italian_jongbaly_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_jongbaly XlmRoBertaForTokenClassification from jongbaly
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_jongbaly
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_jongbaly` is a English model originally trained by jongbaly.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_jongbaly_en_5.5.1_3.0_1737679291801.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_jongbaly_en_5.5.1_3.0_1737679291801.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_jongbaly","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_jongbaly", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_jongbaly|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|816.7 MB|
+
+## References
+
+https://huggingface.co/jongbaly/xlm-roberta-base-finetuned-panx-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_italian_jongbaly_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_italian_jongbaly_pipeline_en.md
new file mode 100644
index 00000000000000..767c32e28068c1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_italian_jongbaly_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_jongbaly_pipeline pipeline XlmRoBertaForTokenClassification from jongbaly
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_jongbaly_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_jongbaly_pipeline` is a English model originally trained by jongbaly.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_jongbaly_pipeline_en_5.5.1_3.0_1737679399775.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_jongbaly_pipeline_en_5.5.1_3.0_1737679399775.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_jongbaly_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_jongbaly_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_jongbaly_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|816.8 MB|
+
+## References
+
+https://huggingface.co/jongbaly/xlm-roberta-base-finetuned-panx-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_italian_m_rezaei_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_italian_m_rezaei_en.md
new file mode 100644
index 00000000000000..d5e47b5c4a5c10
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_italian_m_rezaei_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_m_rezaei XlmRoBertaForTokenClassification from M-Rezaei
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_m_rezaei
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_m_rezaei` is a English model originally trained by M-Rezaei.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_m_rezaei_en_5.5.1_3.0_1737682679224.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_m_rezaei_en_5.5.1_3.0_1737682679224.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_m_rezaei","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_m_rezaei", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_m_rezaei|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|820.7 MB|
+
+## References
+
+https://huggingface.co/M-Rezaei/xlm-roberta-base-finetuned-panx-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_italian_m_rezaei_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_italian_m_rezaei_pipeline_en.md
new file mode 100644
index 00000000000000..065003644c4a32
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_italian_m_rezaei_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_m_rezaei_pipeline pipeline XlmRoBertaForTokenClassification from M-Rezaei
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_m_rezaei_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_m_rezaei_pipeline` is a English model originally trained by M-Rezaei.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_m_rezaei_pipeline_en_5.5.1_3.0_1737682780896.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_m_rezaei_pipeline_en_5.5.1_3.0_1737682780896.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_m_rezaei_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_m_rezaei_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_m_rezaei_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|820.7 MB|
+
+## References
+
+https://huggingface.co/M-Rezaei/xlm-roberta-base-finetuned-panx-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_italian_shawki11_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_italian_shawki11_en.md
new file mode 100644
index 00000000000000..619de54f18d8fc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_italian_shawki11_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_shawki11 XlmRoBertaForTokenClassification from Shawki11
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_shawki11
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_shawki11` is a English model originally trained by Shawki11.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_shawki11_en_5.5.1_3.0_1737679653844.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_shawki11_en_5.5.1_3.0_1737679653844.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_shawki11","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_shawki11", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_shawki11|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|843.8 MB|
+
+## References
+
+https://huggingface.co/Shawki11/xlm-roberta-base-finetuned-panx-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_italian_shawki11_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_italian_shawki11_pipeline_en.md
new file mode 100644
index 00000000000000..eb53b670c60258
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_panx_italian_shawki11_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_shawki11_pipeline pipeline XlmRoBertaForTokenClassification from Shawki11
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_shawki11_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_shawki11_pipeline` is a English model originally trained by Shawki11.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_shawki11_pipeline_en_5.5.1_3.0_1737679741584.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_shawki11_pipeline_en_5.5.1_3.0_1737679741584.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_shawki11_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_shawki11_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_shawki11_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|843.8 MB|
+
+## References
+
+https://huggingface.co/Shawki11/xlm-roberta-base-finetuned-panx-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_t_product_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_t_product_en.md
new file mode 100644
index 00000000000000..4b4a2ebb368a73
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_t_product_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_t_product XlmRoBertaForSequenceClassification from Gregorig
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_t_product
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_t_product` is a English model originally trained by Gregorig.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_t_product_en_5.5.1_3.0_1737712988950.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_t_product_en_5.5.1_3.0_1737712988950.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_finetuned_t_product","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_finetuned_t_product", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_t_product|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|796.4 MB|
+
+## References
+
+https://huggingface.co/Gregorig/xlm-roberta-base-finetuned-t_product
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_t_product_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_t_product_pipeline_en.md
new file mode 100644
index 00000000000000..9001e4dc00bbb8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_finetuned_t_product_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_t_product_pipeline pipeline XlmRoBertaForSequenceClassification from Gregorig
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_t_product_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_t_product_pipeline` is a English model originally trained by Gregorig.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_t_product_pipeline_en_5.5.1_3.0_1737713118441.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_t_product_pipeline_en_5.5.1_3.0_1737713118441.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_t_product_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_t_product_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_t_product_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|796.4 MB|
+
+## References
+
+https://huggingface.co/Gregorig/xlm-roberta-base-finetuned-t_product
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_ner_coin_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_ner_coin_en.md
new file mode 100644
index 00000000000000..2b00bdf1f5ca18
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_ner_coin_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_ner_coin XlmRoBertaForTokenClassification from thanhdath
+author: John Snow Labs
+name: xlm_roberta_base_ner_coin
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_ner_coin` is a English model originally trained by thanhdath.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_ner_coin_en_5.5.1_3.0_1737677079188.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_ner_coin_en_5.5.1_3.0_1737677079188.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_ner_coin","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_ner_coin", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_ner_coin|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|816.4 MB|
+
+## References
+
+https://huggingface.co/thanhdath/xlm-roberta-base-ner-coin
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_ner_coin_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_ner_coin_pipeline_en.md
new file mode 100644
index 00000000000000..a51b4f3ed0b5ac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_ner_coin_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_ner_coin_pipeline pipeline XlmRoBertaForTokenClassification from thanhdath
+author: John Snow Labs
+name: xlm_roberta_base_ner_coin_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_ner_coin_pipeline` is a English model originally trained by thanhdath.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_ner_coin_pipeline_en_5.5.1_3.0_1737677182621.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_ner_coin_pipeline_en_5.5.1_3.0_1737677182621.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_ner_coin_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_ner_coin_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_ner_coin_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|816.4 MB|
+
+## References
+
+https://huggingface.co/thanhdath/xlm-roberta-base-ner-coin
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_qa_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_qa_en.md
new file mode 100644
index 00000000000000..3d854857c5062a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_qa_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English xlm_roberta_base_qa XlmRoBertaForQuestionAnswering from alynakbaba
+author: John Snow Labs
+name: xlm_roberta_base_qa
+date: 2025-01-24
+tags: [en, open_source, onnx, question_answering, xlm_roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_qa` is a English model originally trained by alynakbaba.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_qa_en_5.5.1_3.0_1737753304155.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_qa_en_5.5.1_3.0_1737753304155.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_base_qa","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_base_qa", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_qa|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|799.4 MB|
+
+## References
+
+https://huggingface.co/alynakbaba/xlm-roberta-base-qa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_qa_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_qa_pipeline_en.md
new file mode 100644
index 00000000000000..9e3e32c49808c4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_qa_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English xlm_roberta_base_qa_pipeline pipeline XlmRoBertaForQuestionAnswering from alynakbaba
+author: John Snow Labs
+name: xlm_roberta_base_qa_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_qa_pipeline` is a English model originally trained by alynakbaba.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_qa_pipeline_en_5.5.1_3.0_1737753433638.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_qa_pipeline_en_5.5.1_3.0_1737753433638.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_qa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_qa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_qa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|799.4 MB|
+
+## References
+
+https://huggingface.co/alynakbaba/xlm-roberta-base-qa
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_slovene_200_reranker_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_slovene_200_reranker_en.md
new file mode 100644
index 00000000000000..bc4ae88d5c7e26
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_slovene_200_reranker_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_slovene_200_reranker XlmRoBertaForSequenceClassification from PMJAi
+author: John Snow Labs
+name: xlm_roberta_base_slovene_200_reranker
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_slovene_200_reranker` is a English model originally trained by PMJAi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_slovene_200_reranker_en_5.5.1_3.0_1737712813272.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_slovene_200_reranker_en_5.5.1_3.0_1737712813272.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_slovene_200_reranker","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_slovene_200_reranker", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_slovene_200_reranker|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|871.2 MB|
+
+## References
+
+https://huggingface.co/PMJAi/xlm-roberta-base-sl_200-reranker
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_slovene_200_reranker_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_slovene_200_reranker_pipeline_en.md
new file mode 100644
index 00000000000000..0fafc287800988
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_base_slovene_200_reranker_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_slovene_200_reranker_pipeline pipeline XlmRoBertaForSequenceClassification from PMJAi
+author: John Snow Labs
+name: xlm_roberta_base_slovene_200_reranker_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_slovene_200_reranker_pipeline` is a English model originally trained by PMJAi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_slovene_200_reranker_pipeline_en_5.5.1_3.0_1737712915693.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_slovene_200_reranker_pipeline_en_5.5.1_3.0_1737712915693.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_slovene_200_reranker_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_slovene_200_reranker_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_slovene_200_reranker_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|871.2 MB|
+
+## References
+
+https://huggingface.co/PMJAi/xlm-roberta-base-sl_200-reranker
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_checkpoints_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_checkpoints_en.md
new file mode 100644
index 00000000000000..f896a3187492f6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_checkpoints_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_checkpoints XlmRoBertaForSequenceClassification from Lareb00
+author: John Snow Labs
+name: xlm_roberta_checkpoints
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_checkpoints` is a English model originally trained by Lareb00.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_checkpoints_en_5.5.1_3.0_1737713512013.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_checkpoints_en_5.5.1_3.0_1737713512013.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_checkpoints","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_checkpoints", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_checkpoints|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|818.2 MB|
+
+## References
+
+https://huggingface.co/Lareb00/xlm-roberta-checkpoints
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_checkpoints_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_checkpoints_pipeline_en.md
new file mode 100644
index 00000000000000..91ddc77dab2cd7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_checkpoints_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_checkpoints_pipeline pipeline XlmRoBertaForSequenceClassification from Lareb00
+author: John Snow Labs
+name: xlm_roberta_checkpoints_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_checkpoints_pipeline` is a English model originally trained by Lareb00.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_checkpoints_pipeline_en_5.5.1_3.0_1737713633825.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_checkpoints_pipeline_en_5.5.1_3.0_1737713633825.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_checkpoints_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_checkpoints_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_checkpoints_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|818.2 MB|
+
+## References
+
+https://huggingface.co/Lareb00/xlm-roberta-checkpoints
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_finetuned_emojis_cen_1_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_finetuned_emojis_cen_1_en.md
new file mode 100644
index 00000000000000..278ea9e673cf33
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_finetuned_emojis_cen_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_finetuned_emojis_cen_1 XlmRoBertaForSequenceClassification from Karim-Gamal
+author: John Snow Labs
+name: xlm_roberta_finetuned_emojis_cen_1
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_finetuned_emojis_cen_1` is a English model originally trained by Karim-Gamal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_finetuned_emojis_cen_1_en_5.5.1_3.0_1737712321723.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_finetuned_emojis_cen_1_en_5.5.1_3.0_1737712321723.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_finetuned_emojis_cen_1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_finetuned_emojis_cen_1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_finetuned_emojis_cen_1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Karim-Gamal/XLM-Roberta-finetuned-emojis-cen-1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_finetuned_emojis_cen_1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_finetuned_emojis_cen_1_pipeline_en.md
new file mode 100644
index 00000000000000..6ad46ace73bb9d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlm_roberta_finetuned_emojis_cen_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_finetuned_emojis_cen_1_pipeline pipeline XlmRoBertaForSequenceClassification from Karim-Gamal
+author: John Snow Labs
+name: xlm_roberta_finetuned_emojis_cen_1_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_finetuned_emojis_cen_1_pipeline` is a English model originally trained by Karim-Gamal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_finetuned_emojis_cen_1_pipeline_en_5.5.1_3.0_1737712383287.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_finetuned_emojis_cen_1_pipeline_en_5.5.1_3.0_1737712383287.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_finetuned_emojis_cen_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_finetuned_emojis_cen_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_finetuned_emojis_cen_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Karim-Gamal/XLM-Roberta-finetuned-emojis-cen-1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlmr_base_finetuned_hausa_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlmr_base_finetuned_hausa_en.md
new file mode 100644
index 00000000000000..c60a09076fafb8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlmr_base_finetuned_hausa_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlmr_base_finetuned_hausa XlmRoBertaForTokenClassification from grace-pro
+author: John Snow Labs
+name: xlmr_base_finetuned_hausa
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmr_base_finetuned_hausa` is a English model originally trained by grace-pro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmr_base_finetuned_hausa_en_5.5.1_3.0_1737681202949.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmr_base_finetuned_hausa_en_5.5.1_3.0_1737681202949.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlmr_base_finetuned_hausa","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlmr_base_finetuned_hausa", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmr_base_finetuned_hausa|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|869.4 MB|
+
+## References
+
+https://huggingface.co/grace-pro/xlmr-base-finetuned-hausa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlmr_base_finetuned_hausa_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlmr_base_finetuned_hausa_pipeline_en.md
new file mode 100644
index 00000000000000..3aa7c45736edd2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlmr_base_finetuned_hausa_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlmr_base_finetuned_hausa_pipeline pipeline XlmRoBertaForTokenClassification from grace-pro
+author: John Snow Labs
+name: xlmr_base_finetuned_hausa_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmr_base_finetuned_hausa_pipeline` is a English model originally trained by grace-pro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmr_base_finetuned_hausa_pipeline_en_5.5.1_3.0_1737681268200.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmr_base_finetuned_hausa_pipeline_en_5.5.1_3.0_1737681268200.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlmr_base_finetuned_hausa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmr_base_finetuned_hausa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmr_base_finetuned_hausa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|869.4 MB|
+
+## References
+
+https://huggingface.co/grace-pro/xlmr-base-finetuned-hausa
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlmroberta_sst2_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlmroberta_sst2_en.md
new file mode 100644
index 00000000000000..af2b04b0ecc058
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlmroberta_sst2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlmroberta_sst2 XlmRoBertaForSequenceClassification from Areepatw
+author: John Snow Labs
+name: xlmroberta_sst2
+date: 2025-01-24
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_sst2` is a English model originally trained by Areepatw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_sst2_en_5.5.1_3.0_1737714129316.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_sst2_en_5.5.1_3.0_1737714129316.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlmroberta_sst2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlmroberta_sst2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_sst2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|803.2 MB|
+
+## References
+
+https://huggingface.co/Areepatw/xlmroberta-sst2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xlmroberta_sst2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-xlmroberta_sst2_pipeline_en.md
new file mode 100644
index 00000000000000..e2f2aed7523e04
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xlmroberta_sst2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlmroberta_sst2_pipeline pipeline XlmRoBertaForSequenceClassification from Areepatw
+author: John Snow Labs
+name: xlmroberta_sst2_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_sst2_pipeline` is a English model originally trained by Areepatw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmroberta_sst2_pipeline_en_5.5.1_3.0_1737714263715.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_sst2_pipeline_en_5.5.1_3.0_1737714263715.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlmroberta_sst2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmroberta_sst2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_sst2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|803.3 MB|
+
+## References
+
+https://huggingface.co/Areepatw/xlmroberta-sst2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xmlner_biobert_en.md b/docs/_posts/ahmedlone127/2025-01-24-xmlner_biobert_en.md
new file mode 100644
index 00000000000000..0dc87e466a3ccf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xmlner_biobert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xmlner_biobert XlmRoBertaForTokenClassification from Vantwoth
+author: John Snow Labs
+name: xmlner_biobert
+date: 2025-01-24
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xmlner_biobert` is a English model originally trained by Vantwoth.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xmlner_biobert_en_5.5.1_3.0_1737680106146.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xmlner_biobert_en_5.5.1_3.0_1737680106146.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xmlner_biobert","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xmlner_biobert", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xmlner_biobert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|653.3 MB|
+
+## References
+
+https://huggingface.co/Vantwoth/xmlNer-biobert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-xmlner_biobert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-xmlner_biobert_pipeline_en.md
new file mode 100644
index 00000000000000..c240ee594d716d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-xmlner_biobert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xmlner_biobert_pipeline pipeline XlmRoBertaForTokenClassification from Vantwoth
+author: John Snow Labs
+name: xmlner_biobert_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xmlner_biobert_pipeline` is a English model originally trained by Vantwoth.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xmlner_biobert_pipeline_en_5.5.1_3.0_1737680299696.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xmlner_biobert_pipeline_en_5.5.1_3.0_1737680299696.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xmlner_biobert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xmlner_biobert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xmlner_biobert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|653.3 MB|
+
+## References
+
+https://huggingface.co/Vantwoth/xmlNer-biobert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-your_repo_name_mrbean01_en.md b/docs/_posts/ahmedlone127/2025-01-24-your_repo_name_mrbean01_en.md
new file mode 100644
index 00000000000000..45b259bdf23e30
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-your_repo_name_mrbean01_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English your_repo_name_mrbean01 GPT2Transformer from Mrbean01
+author: John Snow Labs
+name: your_repo_name_mrbean01
+date: 2025-01-24
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`your_repo_name_mrbean01` is a English model originally trained by Mrbean01.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/your_repo_name_mrbean01_en_5.5.1_3.0_1737733310210.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/your_repo_name_mrbean01_en_5.5.1_3.0_1737733310210.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("your_repo_name_mrbean01","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("your_repo_name_mrbean01","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|your_repo_name_mrbean01|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/Mrbean01/your-repo-name
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-24-your_repo_name_mrbean01_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-24-your_repo_name_mrbean01_pipeline_en.md
new file mode 100644
index 00000000000000..5f1ff97d6a45e9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-24-your_repo_name_mrbean01_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English your_repo_name_mrbean01_pipeline pipeline GPT2Transformer from Mrbean01
+author: John Snow Labs
+name: your_repo_name_mrbean01_pipeline
+date: 2025-01-24
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`your_repo_name_mrbean01_pipeline` is a English model originally trained by Mrbean01.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/your_repo_name_mrbean01_pipeline_en_5.5.1_3.0_1737733340107.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/your_repo_name_mrbean01_pipeline_en_5.5.1_3.0_1737733340107.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("your_repo_name_mrbean01_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("your_repo_name_mrbean01_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|your_repo_name_mrbean01_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/Mrbean01/your-repo-name
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-063165e4_8904_42bd_9b41_c71649d3ef9d_en.md b/docs/_posts/ahmedlone127/2025-01-25-063165e4_8904_42bd_9b41_c71649d3ef9d_en.md
new file mode 100644
index 00000000000000..ab560d7776fe8d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-063165e4_8904_42bd_9b41_c71649d3ef9d_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English 063165e4_8904_42bd_9b41_c71649d3ef9d BertEmbeddings from ismailpolas
+author: John Snow Labs
+name: 063165e4_8904_42bd_9b41_c71649d3ef9d
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`063165e4_8904_42bd_9b41_c71649d3ef9d` is a English model originally trained by ismailpolas.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/063165e4_8904_42bd_9b41_c71649d3ef9d_en_5.5.1_3.0_1737774880427.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/063165e4_8904_42bd_9b41_c71649d3ef9d_en_5.5.1_3.0_1737774880427.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("063165e4_8904_42bd_9b41_c71649d3ef9d","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("063165e4_8904_42bd_9b41_c71649d3ef9d","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|063165e4_8904_42bd_9b41_c71649d3ef9d|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/ismailpolas/063165e4-8904-42bd-9b41-c71649d3ef9d
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-063165e4_8904_42bd_9b41_c71649d3ef9d_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-063165e4_8904_42bd_9b41_c71649d3ef9d_pipeline_en.md
new file mode 100644
index 00000000000000..8f4c478e802b48
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-063165e4_8904_42bd_9b41_c71649d3ef9d_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English 063165e4_8904_42bd_9b41_c71649d3ef9d_pipeline pipeline BertEmbeddings from ismailpolas
+author: John Snow Labs
+name: 063165e4_8904_42bd_9b41_c71649d3ef9d_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`063165e4_8904_42bd_9b41_c71649d3ef9d_pipeline` is a English model originally trained by ismailpolas.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/063165e4_8904_42bd_9b41_c71649d3ef9d_pipeline_en_5.5.1_3.0_1737774904329.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/063165e4_8904_42bd_9b41_c71649d3ef9d_pipeline_en_5.5.1_3.0_1737774904329.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("063165e4_8904_42bd_9b41_c71649d3ef9d_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("063165e4_8904_42bd_9b41_c71649d3ef9d_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|063165e4_8904_42bd_9b41_c71649d3ef9d_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/ismailpolas/063165e4-8904-42bd-9b41-c71649d3ef9d
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-10dimensions_power_en.md b/docs/_posts/ahmedlone127/2025-01-25-10dimensions_power_en.md
new file mode 100644
index 00000000000000..eb8e92107a1a1a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-10dimensions_power_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English 10dimensions_power BertForSequenceClassification from Blablablab
+author: John Snow Labs
+name: 10dimensions_power
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`10dimensions_power` is a English model originally trained by Blablablab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/10dimensions_power_en_5.5.1_3.0_1737839852541.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/10dimensions_power_en_5.5.1_3.0_1737839852541.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("10dimensions_power","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("10dimensions_power", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|10dimensions_power|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|405.9 MB|
+
+## References
+
+https://huggingface.co/Blablablab/10dimensions-power
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-10dimensions_power_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-10dimensions_power_pipeline_en.md
new file mode 100644
index 00000000000000..781218a1ac652a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-10dimensions_power_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English 10dimensions_power_pipeline pipeline BertForSequenceClassification from Blablablab
+author: John Snow Labs
+name: 10dimensions_power_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`10dimensions_power_pipeline` is a English model originally trained by Blablablab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/10dimensions_power_pipeline_en_5.5.1_3.0_1737839873525.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/10dimensions_power_pipeline_en_5.5.1_3.0_1737839873525.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("10dimensions_power_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("10dimensions_power_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|10dimensions_power_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|405.9 MB|
+
+## References
+
+https://huggingface.co/Blablablab/10dimensions-power
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-20240712152243_en.md b/docs/_posts/ahmedlone127/2025-01-25-20240712152243_en.md
new file mode 100644
index 00000000000000..8e9a953934493c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-20240712152243_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English 20240712152243 XlmRoBertaForTokenClassification from nttaii
+author: John Snow Labs
+name: 20240712152243
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`20240712152243` is a English model originally trained by nttaii.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/20240712152243_en_5.5.1_3.0_1737778624266.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/20240712152243_en_5.5.1_3.0_1737778624266.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("20240712152243","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("20240712152243", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|20240712152243|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|833.5 MB|
+
+## References
+
+https://huggingface.co/nttaii/20240712152243
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-20240712152243_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-20240712152243_pipeline_en.md
new file mode 100644
index 00000000000000..fdfd4b94f987e5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-20240712152243_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English 20240712152243_pipeline pipeline XlmRoBertaForTokenClassification from nttaii
+author: John Snow Labs
+name: 20240712152243_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`20240712152243_pipeline` is a English model originally trained by nttaii.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/20240712152243_pipeline_en_5.5.1_3.0_1737778738189.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/20240712152243_pipeline_en_5.5.1_3.0_1737778738189.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("20240712152243_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("20240712152243_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|20240712152243_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|833.5 MB|
+
+## References
+
+https://huggingface.co/nttaii/20240712152243
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-208k_marianmt_nepali_tonga_tonga_islands_english_en.md b/docs/_posts/ahmedlone127/2025-01-25-208k_marianmt_nepali_tonga_tonga_islands_english_en.md
new file mode 100644
index 00000000000000..d2d0dee3d619cf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-208k_marianmt_nepali_tonga_tonga_islands_english_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English 208k_marianmt_nepali_tonga_tonga_islands_english MarianTransformer from iamTangsang
+author: John Snow Labs
+name: 208k_marianmt_nepali_tonga_tonga_islands_english
+date: 2025-01-25
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`208k_marianmt_nepali_tonga_tonga_islands_english` is a English model originally trained by iamTangsang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/208k_marianmt_nepali_tonga_tonga_islands_english_en_5.5.1_3.0_1737782796406.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/208k_marianmt_nepali_tonga_tonga_islands_english_en_5.5.1_3.0_1737782796406.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("208k_marianmt_nepali_tonga_tonga_islands_english","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("208k_marianmt_nepali_tonga_tonga_islands_english","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|208k_marianmt_nepali_tonga_tonga_islands_english|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|414.5 MB|
+
+## References
+
+https://huggingface.co/iamTangsang/208k-MarianMT-Nepali-to-English
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-208k_marianmt_nepali_tonga_tonga_islands_english_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-208k_marianmt_nepali_tonga_tonga_islands_english_pipeline_en.md
new file mode 100644
index 00000000000000..87fe56d4f49e35
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-208k_marianmt_nepali_tonga_tonga_islands_english_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English 208k_marianmt_nepali_tonga_tonga_islands_english_pipeline pipeline MarianTransformer from iamTangsang
+author: John Snow Labs
+name: 208k_marianmt_nepali_tonga_tonga_islands_english_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`208k_marianmt_nepali_tonga_tonga_islands_english_pipeline` is a English model originally trained by iamTangsang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/208k_marianmt_nepali_tonga_tonga_islands_english_pipeline_en_5.5.1_3.0_1737782819976.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/208k_marianmt_nepali_tonga_tonga_islands_english_pipeline_en_5.5.1_3.0_1737782819976.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("208k_marianmt_nepali_tonga_tonga_islands_english_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("208k_marianmt_nepali_tonga_tonga_islands_english_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|208k_marianmt_nepali_tonga_tonga_islands_english_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|415.1 MB|
+
+## References
+
+https://huggingface.co/iamTangsang/208k-MarianMT-Nepali-to-English
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-9000samples_en.md b/docs/_posts/ahmedlone127/2025-01-25-9000samples_en.md
new file mode 100644
index 00000000000000..f28052ea491a19
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-9000samples_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English 9000samples MarianTransformer from vania2911
+author: John Snow Labs
+name: 9000samples
+date: 2025-01-25
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`9000samples` is a English model originally trained by vania2911.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/9000samples_en_5.5.1_3.0_1737841717207.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/9000samples_en_5.5.1_3.0_1737841717207.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("9000samples","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("9000samples","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|9000samples|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|295.5 MB|
+
+## References
+
+https://huggingface.co/vania2911/9000samples
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-9000samples_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-9000samples_pipeline_en.md
new file mode 100644
index 00000000000000..7189c4bd3c3f77
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-9000samples_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English 9000samples_pipeline pipeline MarianTransformer from vania2911
+author: John Snow Labs
+name: 9000samples_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`9000samples_pipeline` is a English model originally trained by vania2911.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/9000samples_pipeline_en_5.5.1_3.0_1737841732785.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/9000samples_pipeline_en_5.5.1_3.0_1737841732785.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("9000samples_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("9000samples_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|9000samples_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|296.0 MB|
+
+## References
+
+https://huggingface.co/vania2911/9000samples
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-a_nepal_bhasa_repo_en.md b/docs/_posts/ahmedlone127/2025-01-25-a_nepal_bhasa_repo_en.md
new file mode 100644
index 00000000000000..b7acddda27dd97
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-a_nepal_bhasa_repo_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English a_nepal_bhasa_repo DistilBertForSequenceClassification from AliMokh
+author: John Snow Labs
+name: a_nepal_bhasa_repo
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`a_nepal_bhasa_repo` is a English model originally trained by AliMokh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/a_nepal_bhasa_repo_en_5.5.1_3.0_1737821792735.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/a_nepal_bhasa_repo_en_5.5.1_3.0_1737821792735.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("a_nepal_bhasa_repo","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("a_nepal_bhasa_repo", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|a_nepal_bhasa_repo|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/AliMokh/A-new-repo
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-a_nepal_bhasa_repo_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-a_nepal_bhasa_repo_pipeline_en.md
new file mode 100644
index 00000000000000..bb4126cf8eb186
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-a_nepal_bhasa_repo_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English a_nepal_bhasa_repo_pipeline pipeline DistilBertForSequenceClassification from AliMokh
+author: John Snow Labs
+name: a_nepal_bhasa_repo_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`a_nepal_bhasa_repo_pipeline` is a English model originally trained by AliMokh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/a_nepal_bhasa_repo_pipeline_en_5.5.1_3.0_1737821816127.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/a_nepal_bhasa_repo_pipeline_en_5.5.1_3.0_1737821816127.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("a_nepal_bhasa_repo_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("a_nepal_bhasa_repo_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|a_nepal_bhasa_repo_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/AliMokh/A-new-repo
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-abstractokenizer_en.md b/docs/_posts/ahmedlone127/2025-01-25-abstractokenizer_en.md
new file mode 100644
index 00000000000000..699fb4952b0bef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-abstractokenizer_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English abstractokenizer DistilBertForSequenceClassification from abehandlerorg
+author: John Snow Labs
+name: abstractokenizer
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`abstractokenizer` is a English model originally trained by abehandlerorg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/abstractokenizer_en_5.5.1_3.0_1737822041905.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/abstractokenizer_en_5.5.1_3.0_1737822041905.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("abstractokenizer","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("abstractokenizer", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|abstractokenizer|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/abehandlerorg/abstractokenizer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-abstractokenizer_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-abstractokenizer_pipeline_en.md
new file mode 100644
index 00000000000000..cd3a0fbbf3c4c2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-abstractokenizer_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English abstractokenizer_pipeline pipeline DistilBertForSequenceClassification from abehandlerorg
+author: John Snow Labs
+name: abstractokenizer_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`abstractokenizer_pipeline` is a English model originally trained by abehandlerorg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/abstractokenizer_pipeline_en_5.5.1_3.0_1737822056372.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/abstractokenizer_pipeline_en_5.5.1_3.0_1737822056372.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("abstractokenizer_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("abstractokenizer_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|abstractokenizer_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/abehandlerorg/abstractokenizer
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-afriberta_base_finetuned_hausa_en.md b/docs/_posts/ahmedlone127/2025-01-25-afriberta_base_finetuned_hausa_en.md
new file mode 100644
index 00000000000000..627b13d84a0b6b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-afriberta_base_finetuned_hausa_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English afriberta_base_finetuned_hausa XlmRoBertaForTokenClassification from grace-pro
+author: John Snow Labs
+name: afriberta_base_finetuned_hausa
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`afriberta_base_finetuned_hausa` is a English model originally trained by grace-pro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/afriberta_base_finetuned_hausa_en_5.5.1_3.0_1737832530741.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/afriberta_base_finetuned_hausa_en_5.5.1_3.0_1737832530741.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("afriberta_base_finetuned_hausa","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("afriberta_base_finetuned_hausa", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|afriberta_base_finetuned_hausa|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|415.2 MB|
+
+## References
+
+https://huggingface.co/grace-pro/afriberta-base-finetuned-hausa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-afriberta_base_finetuned_hausa_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-afriberta_base_finetuned_hausa_pipeline_en.md
new file mode 100644
index 00000000000000..9838817b251a92
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-afriberta_base_finetuned_hausa_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English afriberta_base_finetuned_hausa_pipeline pipeline XlmRoBertaForTokenClassification from grace-pro
+author: John Snow Labs
+name: afriberta_base_finetuned_hausa_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`afriberta_base_finetuned_hausa_pipeline` is a English model originally trained by grace-pro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/afriberta_base_finetuned_hausa_pipeline_en_5.5.1_3.0_1737832552835.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/afriberta_base_finetuned_hausa_pipeline_en_5.5.1_3.0_1737832552835.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("afriberta_base_finetuned_hausa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("afriberta_base_finetuned_hausa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|afriberta_base_finetuned_hausa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|415.3 MB|
+
+## References
+
+https://huggingface.co/grace-pro/afriberta-base-finetuned-hausa
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-afriberta_finetuned_hausa_en.md b/docs/_posts/ahmedlone127/2025-01-25-afriberta_finetuned_hausa_en.md
new file mode 100644
index 00000000000000..efedb9a70a495b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-afriberta_finetuned_hausa_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English afriberta_finetuned_hausa XlmRoBertaForTokenClassification from grace-pro
+author: John Snow Labs
+name: afriberta_finetuned_hausa
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`afriberta_finetuned_hausa` is a English model originally trained by grace-pro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/afriberta_finetuned_hausa_en_5.5.1_3.0_1737832405803.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/afriberta_finetuned_hausa_en_5.5.1_3.0_1737832405803.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("afriberta_finetuned_hausa","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("afriberta_finetuned_hausa", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|afriberta_finetuned_hausa|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|468.3 MB|
+
+## References
+
+https://huggingface.co/grace-pro/afriberta-finetuned-hausa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-afriberta_finetuned_hausa_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-afriberta_finetuned_hausa_pipeline_en.md
new file mode 100644
index 00000000000000..45a3d61b1404fe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-afriberta_finetuned_hausa_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English afriberta_finetuned_hausa_pipeline pipeline XlmRoBertaForTokenClassification from grace-pro
+author: John Snow Labs
+name: afriberta_finetuned_hausa_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`afriberta_finetuned_hausa_pipeline` is a English model originally trained by grace-pro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/afriberta_finetuned_hausa_pipeline_en_5.5.1_3.0_1737832436479.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/afriberta_finetuned_hausa_pipeline_en_5.5.1_3.0_1737832436479.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("afriberta_finetuned_hausa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("afriberta_finetuned_hausa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|afriberta_finetuned_hausa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|468.3 MB|
+
+## References
+
+https://huggingface.co/grace-pro/afriberta-finetuned-hausa
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-afriberta_large_finetuned_hausa_en.md b/docs/_posts/ahmedlone127/2025-01-25-afriberta_large_finetuned_hausa_en.md
new file mode 100644
index 00000000000000..b9516852e3e9c6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-afriberta_large_finetuned_hausa_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English afriberta_large_finetuned_hausa XlmRoBertaForTokenClassification from grace-pro
+author: John Snow Labs
+name: afriberta_large_finetuned_hausa
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`afriberta_large_finetuned_hausa` is a English model originally trained by grace-pro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/afriberta_large_finetuned_hausa_en_5.5.1_3.0_1737791758583.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/afriberta_large_finetuned_hausa_en_5.5.1_3.0_1737791758583.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("afriberta_large_finetuned_hausa","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("afriberta_large_finetuned_hausa", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|afriberta_large_finetuned_hausa|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|468.3 MB|
+
+## References
+
+https://huggingface.co/grace-pro/afriberta-large-finetuned-hausa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-afriberta_large_finetuned_hausa_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-afriberta_large_finetuned_hausa_pipeline_en.md
new file mode 100644
index 00000000000000..29abe74ac5ac8d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-afriberta_large_finetuned_hausa_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English afriberta_large_finetuned_hausa_pipeline pipeline XlmRoBertaForTokenClassification from grace-pro
+author: John Snow Labs
+name: afriberta_large_finetuned_hausa_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`afriberta_large_finetuned_hausa_pipeline` is a English model originally trained by grace-pro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/afriberta_large_finetuned_hausa_pipeline_en_5.5.1_3.0_1737791783210.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/afriberta_large_finetuned_hausa_pipeline_en_5.5.1_3.0_1737791783210.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("afriberta_large_finetuned_hausa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("afriberta_large_finetuned_hausa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|afriberta_large_finetuned_hausa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|468.3 MB|
+
+## References
+
+https://huggingface.co/grace-pro/afriberta-large-finetuned-hausa
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-afrikalm_multilang_en.md b/docs/_posts/ahmedlone127/2025-01-25-afrikalm_multilang_en.md
new file mode 100644
index 00000000000000..c4d2ed65615eb2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-afrikalm_multilang_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English afrikalm_multilang BertEmbeddings from frankl1
+author: John Snow Labs
+name: afrikalm_multilang
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`afrikalm_multilang` is a English model originally trained by frankl1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/afrikalm_multilang_en_5.5.1_3.0_1737821359260.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/afrikalm_multilang_en_5.5.1_3.0_1737821359260.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("afrikalm_multilang","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("afrikalm_multilang","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|afrikalm_multilang|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|138.3 MB|
+
+## References
+
+https://huggingface.co/frankl1/afrikalm-multilang
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-afrikalm_multilang_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-afrikalm_multilang_pipeline_en.md
new file mode 100644
index 00000000000000..14ccc0fae19c4a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-afrikalm_multilang_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English afrikalm_multilang_pipeline pipeline BertEmbeddings from frankl1
+author: John Snow Labs
+name: afrikalm_multilang_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`afrikalm_multilang_pipeline` is a English model originally trained by frankl1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/afrikalm_multilang_pipeline_en_5.5.1_3.0_1737821365731.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/afrikalm_multilang_pipeline_en_5.5.1_3.0_1737821365731.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("afrikalm_multilang_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("afrikalm_multilang_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|afrikalm_multilang_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|138.3 MB|
+
+## References
+
+https://huggingface.co/frankl1/afrikalm-multilang
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-agriculture_bert_finetuned_en.md b/docs/_posts/ahmedlone127/2025-01-25-agriculture_bert_finetuned_en.md
new file mode 100644
index 00000000000000..60c4b62c9cbef9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-agriculture_bert_finetuned_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English agriculture_bert_finetuned BertEmbeddings from YMEA
+author: John Snow Labs
+name: agriculture_bert_finetuned
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`agriculture_bert_finetuned` is a English model originally trained by YMEA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/agriculture_bert_finetuned_en_5.5.1_3.0_1737806398909.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/agriculture_bert_finetuned_en_5.5.1_3.0_1737806398909.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("agriculture_bert_finetuned","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("agriculture_bert_finetuned","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|agriculture_bert_finetuned|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|409.9 MB|
+
+## References
+
+https://huggingface.co/YMEA/agriculture-bert-finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-agriculture_bert_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-agriculture_bert_finetuned_pipeline_en.md
new file mode 100644
index 00000000000000..f2e779cafbdca5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-agriculture_bert_finetuned_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English agriculture_bert_finetuned_pipeline pipeline BertEmbeddings from YMEA
+author: John Snow Labs
+name: agriculture_bert_finetuned_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`agriculture_bert_finetuned_pipeline` is a English model originally trained by YMEA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/agriculture_bert_finetuned_pipeline_en_5.5.1_3.0_1737806421163.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/agriculture_bert_finetuned_pipeline_en_5.5.1_3.0_1737806421163.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("agriculture_bert_finetuned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("agriculture_bert_finetuned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|agriculture_bert_finetuned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.9 MB|
+
+## References
+
+https://huggingface.co/YMEA/agriculture-bert-finetuned
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-albert_base_v2_ecom_qa_en.md b/docs/_posts/ahmedlone127/2025-01-25-albert_base_v2_ecom_qa_en.md
new file mode 100644
index 00000000000000..297553405a1b23
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-albert_base_v2_ecom_qa_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English albert_base_v2_ecom_qa AlbertForQuestionAnswering from Vinayak1699
+author: John Snow Labs
+name: albert_base_v2_ecom_qa
+date: 2025-01-25
+tags: [en, open_source, onnx, question_answering, albert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_v2_ecom_qa` is a English model originally trained by Vinayak1699.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_v2_ecom_qa_en_5.5.1_3.0_1737796275564.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_v2_ecom_qa_en_5.5.1_3.0_1737796275564.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = AlbertForQuestionAnswering.pretrained("albert_base_v2_ecom_qa","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = AlbertForQuestionAnswering.pretrained("albert_base_v2_ecom_qa", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_base_v2_ecom_qa|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|42.0 MB|
+
+## References
+
+https://huggingface.co/Vinayak1699/albert-base-v2-ecom-qa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-albert_base_v2_ecom_qa_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-albert_base_v2_ecom_qa_pipeline_en.md
new file mode 100644
index 00000000000000..a3ed94d82e10eb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-albert_base_v2_ecom_qa_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English albert_base_v2_ecom_qa_pipeline pipeline AlbertForQuestionAnswering from Vinayak1699
+author: John Snow Labs
+name: albert_base_v2_ecom_qa_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_v2_ecom_qa_pipeline` is a English model originally trained by Vinayak1699.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_v2_ecom_qa_pipeline_en_5.5.1_3.0_1737796277784.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_v2_ecom_qa_pipeline_en_5.5.1_3.0_1737796277784.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("albert_base_v2_ecom_qa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("albert_base_v2_ecom_qa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_base_v2_ecom_qa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|42.0 MB|
+
+## References
+
+https://huggingface.co/Vinayak1699/albert-base-v2-ecom-qa
+
+## Included Models
+
+- MultiDocumentAssembler
+- AlbertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-all_minilm_l6_v2_personal_project_default_2024_05_17_en.md b/docs/_posts/ahmedlone127/2025-01-25-all_minilm_l6_v2_personal_project_default_2024_05_17_en.md
new file mode 100644
index 00000000000000..c159896db75a6b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-all_minilm_l6_v2_personal_project_default_2024_05_17_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English all_minilm_l6_v2_personal_project_default_2024_05_17 BertEmbeddings from brugmark
+author: John Snow Labs
+name: all_minilm_l6_v2_personal_project_default_2024_05_17
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_minilm_l6_v2_personal_project_default_2024_05_17` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_default_2024_05_17_en_5.5.1_3.0_1737807183493.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_default_2024_05_17_en_5.5.1_3.0_1737807183493.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("all_minilm_l6_v2_personal_project_default_2024_05_17","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("all_minilm_l6_v2_personal_project_default_2024_05_17","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_minilm_l6_v2_personal_project_default_2024_05_17|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|83.9 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-default-2024-05-17
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-all_minilm_l6_v2_personal_project_default_2024_05_17_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-all_minilm_l6_v2_personal_project_default_2024_05_17_pipeline_en.md
new file mode 100644
index 00000000000000..d358ad11f7d43c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-all_minilm_l6_v2_personal_project_default_2024_05_17_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English all_minilm_l6_v2_personal_project_default_2024_05_17_pipeline pipeline BertEmbeddings from brugmark
+author: John Snow Labs
+name: all_minilm_l6_v2_personal_project_default_2024_05_17_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_minilm_l6_v2_personal_project_default_2024_05_17_pipeline` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_default_2024_05_17_pipeline_en_5.5.1_3.0_1737807187988.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_default_2024_05_17_pipeline_en_5.5.1_3.0_1737807187988.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("all_minilm_l6_v2_personal_project_default_2024_05_17_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("all_minilm_l6_v2_personal_project_default_2024_05_17_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_minilm_l6_v2_personal_project_default_2024_05_17_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|83.9 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-default-2024-05-17
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-all_minilm_l6_v2_personal_project_default_2024_05_31_en.md b/docs/_posts/ahmedlone127/2025-01-25-all_minilm_l6_v2_personal_project_default_2024_05_31_en.md
new file mode 100644
index 00000000000000..77f2251f5302ab
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-all_minilm_l6_v2_personal_project_default_2024_05_31_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English all_minilm_l6_v2_personal_project_default_2024_05_31 BertEmbeddings from brugmark
+author: John Snow Labs
+name: all_minilm_l6_v2_personal_project_default_2024_05_31
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_minilm_l6_v2_personal_project_default_2024_05_31` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_default_2024_05_31_en_5.5.1_3.0_1737846088783.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_default_2024_05_31_en_5.5.1_3.0_1737846088783.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("all_minilm_l6_v2_personal_project_default_2024_05_31","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("all_minilm_l6_v2_personal_project_default_2024_05_31","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_minilm_l6_v2_personal_project_default_2024_05_31|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|83.9 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-default-2024-05-31
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-all_minilm_l6_v2_personal_project_default_2024_05_31_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-all_minilm_l6_v2_personal_project_default_2024_05_31_pipeline_en.md
new file mode 100644
index 00000000000000..86dd1aaa83703a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-all_minilm_l6_v2_personal_project_default_2024_05_31_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English all_minilm_l6_v2_personal_project_default_2024_05_31_pipeline pipeline BertEmbeddings from brugmark
+author: John Snow Labs
+name: all_minilm_l6_v2_personal_project_default_2024_05_31_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_minilm_l6_v2_personal_project_default_2024_05_31_pipeline` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_default_2024_05_31_pipeline_en_5.5.1_3.0_1737846094507.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_default_2024_05_31_pipeline_en_5.5.1_3.0_1737846094507.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("all_minilm_l6_v2_personal_project_default_2024_05_31_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("all_minilm_l6_v2_personal_project_default_2024_05_31_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_minilm_l6_v2_personal_project_default_2024_05_31_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|83.9 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-default-2024-05-31
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-all_minilm_l6_v2_personal_project_default_2024_06_03_en.md b/docs/_posts/ahmedlone127/2025-01-25-all_minilm_l6_v2_personal_project_default_2024_06_03_en.md
new file mode 100644
index 00000000000000..d18299b912d187
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-all_minilm_l6_v2_personal_project_default_2024_06_03_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English all_minilm_l6_v2_personal_project_default_2024_06_03 BertEmbeddings from brugmark
+author: John Snow Labs
+name: all_minilm_l6_v2_personal_project_default_2024_06_03
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_minilm_l6_v2_personal_project_default_2024_06_03` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_default_2024_06_03_en_5.5.1_3.0_1737807029063.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_default_2024_06_03_en_5.5.1_3.0_1737807029063.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("all_minilm_l6_v2_personal_project_default_2024_06_03","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("all_minilm_l6_v2_personal_project_default_2024_06_03","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_minilm_l6_v2_personal_project_default_2024_06_03|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|83.9 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-default-2024-06-03
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-all_minilm_l6_v2_personal_project_default_2024_06_03_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-all_minilm_l6_v2_personal_project_default_2024_06_03_pipeline_en.md
new file mode 100644
index 00000000000000..e3e38c3fe70a43
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-all_minilm_l6_v2_personal_project_default_2024_06_03_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English all_minilm_l6_v2_personal_project_default_2024_06_03_pipeline pipeline BertEmbeddings from brugmark
+author: John Snow Labs
+name: all_minilm_l6_v2_personal_project_default_2024_06_03_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_minilm_l6_v2_personal_project_default_2024_06_03_pipeline` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_default_2024_06_03_pipeline_en_5.5.1_3.0_1737807033677.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_default_2024_06_03_pipeline_en_5.5.1_3.0_1737807033677.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("all_minilm_l6_v2_personal_project_default_2024_06_03_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("all_minilm_l6_v2_personal_project_default_2024_06_03_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_minilm_l6_v2_personal_project_default_2024_06_03_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|83.9 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-default-2024-06-03
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-all_minilm_l6_v2_personal_project_default_2024_06_12_en.md b/docs/_posts/ahmedlone127/2025-01-25-all_minilm_l6_v2_personal_project_default_2024_06_12_en.md
new file mode 100644
index 00000000000000..b352ad5110840a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-all_minilm_l6_v2_personal_project_default_2024_06_12_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English all_minilm_l6_v2_personal_project_default_2024_06_12 BertEmbeddings from brugmark
+author: John Snow Labs
+name: all_minilm_l6_v2_personal_project_default_2024_06_12
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_minilm_l6_v2_personal_project_default_2024_06_12` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_default_2024_06_12_en_5.5.1_3.0_1737846343954.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_default_2024_06_12_en_5.5.1_3.0_1737846343954.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("all_minilm_l6_v2_personal_project_default_2024_06_12","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("all_minilm_l6_v2_personal_project_default_2024_06_12","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_minilm_l6_v2_personal_project_default_2024_06_12|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|83.9 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-default-2024-06-12
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-all_minilm_l6_v2_personal_project_default_2024_06_12_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-all_minilm_l6_v2_personal_project_default_2024_06_12_pipeline_en.md
new file mode 100644
index 00000000000000..b5673bdaa678a7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-all_minilm_l6_v2_personal_project_default_2024_06_12_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English all_minilm_l6_v2_personal_project_default_2024_06_12_pipeline pipeline BertEmbeddings from brugmark
+author: John Snow Labs
+name: all_minilm_l6_v2_personal_project_default_2024_06_12_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_minilm_l6_v2_personal_project_default_2024_06_12_pipeline` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_default_2024_06_12_pipeline_en_5.5.1_3.0_1737846348435.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_default_2024_06_12_pipeline_en_5.5.1_3.0_1737846348435.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("all_minilm_l6_v2_personal_project_default_2024_06_12_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("all_minilm_l6_v2_personal_project_default_2024_06_12_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_minilm_l6_v2_personal_project_default_2024_06_12_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|83.9 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-default-2024-06-12
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-all_minilm_l6_v2_personal_project_finetuned_2024_06_12_en.md b/docs/_posts/ahmedlone127/2025-01-25-all_minilm_l6_v2_personal_project_finetuned_2024_06_12_en.md
new file mode 100644
index 00000000000000..c27c99997fcc09
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-all_minilm_l6_v2_personal_project_finetuned_2024_06_12_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English all_minilm_l6_v2_personal_project_finetuned_2024_06_12 BertEmbeddings from brugmark
+author: John Snow Labs
+name: all_minilm_l6_v2_personal_project_finetuned_2024_06_12
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_minilm_l6_v2_personal_project_finetuned_2024_06_12` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_finetuned_2024_06_12_en_5.5.1_3.0_1737775004846.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_finetuned_2024_06_12_en_5.5.1_3.0_1737775004846.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("all_minilm_l6_v2_personal_project_finetuned_2024_06_12","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("all_minilm_l6_v2_personal_project_finetuned_2024_06_12","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_minilm_l6_v2_personal_project_finetuned_2024_06_12|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|84.8 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-finetuned-2024-06-12
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-all_minilm_l6_v2_personal_project_finetuned_2024_06_12_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-all_minilm_l6_v2_personal_project_finetuned_2024_06_12_pipeline_en.md
new file mode 100644
index 00000000000000..b049b64a390b99
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-all_minilm_l6_v2_personal_project_finetuned_2024_06_12_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English all_minilm_l6_v2_personal_project_finetuned_2024_06_12_pipeline pipeline BertEmbeddings from brugmark
+author: John Snow Labs
+name: all_minilm_l6_v2_personal_project_finetuned_2024_06_12_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_minilm_l6_v2_personal_project_finetuned_2024_06_12_pipeline` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_finetuned_2024_06_12_pipeline_en_5.5.1_3.0_1737775009183.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_finetuned_2024_06_12_pipeline_en_5.5.1_3.0_1737775009183.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("all_minilm_l6_v2_personal_project_finetuned_2024_06_12_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("all_minilm_l6_v2_personal_project_finetuned_2024_06_12_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_minilm_l6_v2_personal_project_finetuned_2024_06_12_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|84.8 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-finetuned-2024-06-12
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-all_minilm_l6_v2_personal_project_finetuned_2024_06_14_en.md b/docs/_posts/ahmedlone127/2025-01-25-all_minilm_l6_v2_personal_project_finetuned_2024_06_14_en.md
new file mode 100644
index 00000000000000..4f15f297c2d4ea
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-all_minilm_l6_v2_personal_project_finetuned_2024_06_14_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English all_minilm_l6_v2_personal_project_finetuned_2024_06_14 BertEmbeddings from brugmark
+author: John Snow Labs
+name: all_minilm_l6_v2_personal_project_finetuned_2024_06_14
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_minilm_l6_v2_personal_project_finetuned_2024_06_14` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_finetuned_2024_06_14_en_5.5.1_3.0_1737846226318.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_finetuned_2024_06_14_en_5.5.1_3.0_1737846226318.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("all_minilm_l6_v2_personal_project_finetuned_2024_06_14","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("all_minilm_l6_v2_personal_project_finetuned_2024_06_14","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_minilm_l6_v2_personal_project_finetuned_2024_06_14|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|84.6 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-finetuned-2024-06-14
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-all_minilm_l6_v2_personal_project_finetuned_2024_06_14_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-all_minilm_l6_v2_personal_project_finetuned_2024_06_14_pipeline_en.md
new file mode 100644
index 00000000000000..caf7b8b6c6969c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-all_minilm_l6_v2_personal_project_finetuned_2024_06_14_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English all_minilm_l6_v2_personal_project_finetuned_2024_06_14_pipeline pipeline BertEmbeddings from brugmark
+author: John Snow Labs
+name: all_minilm_l6_v2_personal_project_finetuned_2024_06_14_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_minilm_l6_v2_personal_project_finetuned_2024_06_14_pipeline` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_finetuned_2024_06_14_pipeline_en_5.5.1_3.0_1737846230638.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_finetuned_2024_06_14_pipeline_en_5.5.1_3.0_1737846230638.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("all_minilm_l6_v2_personal_project_finetuned_2024_06_14_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("all_minilm_l6_v2_personal_project_finetuned_2024_06_14_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_minilm_l6_v2_personal_project_finetuned_2024_06_14_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|84.6 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-finetuned-2024-06-14
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-all_minilm_l6_v2_personal_project_finetuned_2024_06_17_en.md b/docs/_posts/ahmedlone127/2025-01-25-all_minilm_l6_v2_personal_project_finetuned_2024_06_17_en.md
new file mode 100644
index 00000000000000..4ec372815463a7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-all_minilm_l6_v2_personal_project_finetuned_2024_06_17_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English all_minilm_l6_v2_personal_project_finetuned_2024_06_17 BertEmbeddings from brugmark
+author: John Snow Labs
+name: all_minilm_l6_v2_personal_project_finetuned_2024_06_17
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_minilm_l6_v2_personal_project_finetuned_2024_06_17` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_finetuned_2024_06_17_en_5.5.1_3.0_1737774442655.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_finetuned_2024_06_17_en_5.5.1_3.0_1737774442655.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("all_minilm_l6_v2_personal_project_finetuned_2024_06_17","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("all_minilm_l6_v2_personal_project_finetuned_2024_06_17","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_minilm_l6_v2_personal_project_finetuned_2024_06_17|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|84.7 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-finetuned-2024-06-17
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-all_minilm_l6_v2_personal_project_finetuned_2024_06_17_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-all_minilm_l6_v2_personal_project_finetuned_2024_06_17_pipeline_en.md
new file mode 100644
index 00000000000000..4ea3db8d673e6e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-all_minilm_l6_v2_personal_project_finetuned_2024_06_17_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English all_minilm_l6_v2_personal_project_finetuned_2024_06_17_pipeline pipeline BertEmbeddings from brugmark
+author: John Snow Labs
+name: all_minilm_l6_v2_personal_project_finetuned_2024_06_17_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_minilm_l6_v2_personal_project_finetuned_2024_06_17_pipeline` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_finetuned_2024_06_17_pipeline_en_5.5.1_3.0_1737774446805.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_finetuned_2024_06_17_pipeline_en_5.5.1_3.0_1737774446805.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("all_minilm_l6_v2_personal_project_finetuned_2024_06_17_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("all_minilm_l6_v2_personal_project_finetuned_2024_06_17_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_minilm_l6_v2_personal_project_finetuned_2024_06_17_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|84.7 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-finetuned-2024-06-17
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-augmented_model_final_en.md b/docs/_posts/ahmedlone127/2025-01-25-augmented_model_final_en.md
new file mode 100644
index 00000000000000..9ae75718f094af
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-augmented_model_final_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English augmented_model_final DistilBertForSequenceClassification from LeonardoFettucciari
+author: John Snow Labs
+name: augmented_model_final
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`augmented_model_final` is a English model originally trained by LeonardoFettucciari.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/augmented_model_final_en_5.5.1_3.0_1737821927375.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/augmented_model_final_en_5.5.1_3.0_1737821927375.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("augmented_model_final","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("augmented_model_final", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|augmented_model_final|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/LeonardoFettucciari/augmented_model_final
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-augmented_model_final_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-augmented_model_final_pipeline_en.md
new file mode 100644
index 00000000000000..2fb0ed3d3df93c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-augmented_model_final_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English augmented_model_final_pipeline pipeline DistilBertForSequenceClassification from LeonardoFettucciari
+author: John Snow Labs
+name: augmented_model_final_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`augmented_model_final_pipeline` is a English model originally trained by LeonardoFettucciari.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/augmented_model_final_pipeline_en_5.5.1_3.0_1737821940921.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/augmented_model_final_pipeline_en_5.5.1_3.0_1737821940921.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("augmented_model_final_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("augmented_model_final_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|augmented_model_final_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/LeonardoFettucciari/augmented_model_final
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-autotrain_pmmxv_0342h_en.md b/docs/_posts/ahmedlone127/2025-01-25-autotrain_pmmxv_0342h_en.md
new file mode 100644
index 00000000000000..ee16a3be35d7cc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-autotrain_pmmxv_0342h_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English autotrain_pmmxv_0342h DistilBertForSequenceClassification from ben-yu
+author: John Snow Labs
+name: autotrain_pmmxv_0342h
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_pmmxv_0342h` is a English model originally trained by ben-yu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_pmmxv_0342h_en_5.5.1_3.0_1737837073333.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_pmmxv_0342h_en_5.5.1_3.0_1737837073333.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("autotrain_pmmxv_0342h","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("autotrain_pmmxv_0342h", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_pmmxv_0342h|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/ben-yu/autotrain-pmmxv-0342h
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-autotrain_pmmxv_0342h_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-autotrain_pmmxv_0342h_pipeline_en.md
new file mode 100644
index 00000000000000..4536fe2a3ef1f9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-autotrain_pmmxv_0342h_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English autotrain_pmmxv_0342h_pipeline pipeline DistilBertForSequenceClassification from ben-yu
+author: John Snow Labs
+name: autotrain_pmmxv_0342h_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_pmmxv_0342h_pipeline` is a English model originally trained by ben-yu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_pmmxv_0342h_pipeline_en_5.5.1_3.0_1737837086866.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_pmmxv_0342h_pipeline_en_5.5.1_3.0_1737837086866.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("autotrain_pmmxv_0342h_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("autotrain_pmmxv_0342h_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_pmmxv_0342h_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/ben-yu/autotrain-pmmxv-0342h
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-babylm_student_gpt2_0_en.md b/docs/_posts/ahmedlone127/2025-01-25-babylm_student_gpt2_0_en.md
new file mode 100644
index 00000000000000..a88abda1454deb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-babylm_student_gpt2_0_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English babylm_student_gpt2_0 GPT2Transformer from momergul
+author: John Snow Labs
+name: babylm_student_gpt2_0
+date: 2025-01-25
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`babylm_student_gpt2_0` is a English model originally trained by momergul.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/babylm_student_gpt2_0_en_5.5.1_3.0_1737825843761.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/babylm_student_gpt2_0_en_5.5.1_3.0_1737825843761.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("babylm_student_gpt2_0","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("babylm_student_gpt2_0","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|babylm_student_gpt2_0|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.4 MB|
+
+## References
+
+https://huggingface.co/momergul/babylm-student-gpt2-0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-babylm_student_gpt2_0_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-babylm_student_gpt2_0_pipeline_en.md
new file mode 100644
index 00000000000000..a9b21fe6affd6b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-babylm_student_gpt2_0_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English babylm_student_gpt2_0_pipeline pipeline GPT2Transformer from momergul
+author: John Snow Labs
+name: babylm_student_gpt2_0_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`babylm_student_gpt2_0_pipeline` is a English model originally trained by momergul.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/babylm_student_gpt2_0_pipeline_en_5.5.1_3.0_1737825870882.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/babylm_student_gpt2_0_pipeline_en_5.5.1_3.0_1737825870882.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("babylm_student_gpt2_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("babylm_student_gpt2_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|babylm_student_gpt2_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.4 MB|
+
+## References
+
+https://huggingface.co/momergul/babylm-student-gpt2-0
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-babylm_student_gpt2_1_en.md b/docs/_posts/ahmedlone127/2025-01-25-babylm_student_gpt2_1_en.md
new file mode 100644
index 00000000000000..ccc24cdedec057
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-babylm_student_gpt2_1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English babylm_student_gpt2_1 GPT2Transformer from momergul
+author: John Snow Labs
+name: babylm_student_gpt2_1
+date: 2025-01-25
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`babylm_student_gpt2_1` is a English model originally trained by momergul.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/babylm_student_gpt2_1_en_5.5.1_3.0_1737766331544.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/babylm_student_gpt2_1_en_5.5.1_3.0_1737766331544.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("babylm_student_gpt2_1","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("babylm_student_gpt2_1","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|babylm_student_gpt2_1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.4 MB|
+
+## References
+
+https://huggingface.co/momergul/babylm-student-gpt2-1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-babylm_student_gpt2_1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-babylm_student_gpt2_1_pipeline_en.md
new file mode 100644
index 00000000000000..1af212004758d7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-babylm_student_gpt2_1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English babylm_student_gpt2_1_pipeline pipeline GPT2Transformer from momergul
+author: John Snow Labs
+name: babylm_student_gpt2_1_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`babylm_student_gpt2_1_pipeline` is a English model originally trained by momergul.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/babylm_student_gpt2_1_pipeline_en_5.5.1_3.0_1737766356156.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/babylm_student_gpt2_1_pipeline_en_5.5.1_3.0_1737766356156.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("babylm_student_gpt2_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("babylm_student_gpt2_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|babylm_student_gpt2_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.4 MB|
+
+## References
+
+https://huggingface.co/momergul/babylm-student-gpt2-1
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-babylm_student_gpt2_2_en.md b/docs/_posts/ahmedlone127/2025-01-25-babylm_student_gpt2_2_en.md
new file mode 100644
index 00000000000000..6e2cdbccda1a68
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-babylm_student_gpt2_2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English babylm_student_gpt2_2 GPT2Transformer from momergul
+author: John Snow Labs
+name: babylm_student_gpt2_2
+date: 2025-01-25
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`babylm_student_gpt2_2` is a English model originally trained by momergul.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/babylm_student_gpt2_2_en_5.5.1_3.0_1737765427189.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/babylm_student_gpt2_2_en_5.5.1_3.0_1737765427189.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("babylm_student_gpt2_2","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("babylm_student_gpt2_2","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|babylm_student_gpt2_2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.6 MB|
+
+## References
+
+https://huggingface.co/momergul/babylm-student-gpt2-2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-babylm_student_gpt2_2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-babylm_student_gpt2_2_pipeline_en.md
new file mode 100644
index 00000000000000..f77b5c3674c86d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-babylm_student_gpt2_2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English babylm_student_gpt2_2_pipeline pipeline GPT2Transformer from momergul
+author: John Snow Labs
+name: babylm_student_gpt2_2_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`babylm_student_gpt2_2_pipeline` is a English model originally trained by momergul.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/babylm_student_gpt2_2_pipeline_en_5.5.1_3.0_1737765451417.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/babylm_student_gpt2_2_pipeline_en_5.5.1_3.0_1737765451417.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("babylm_student_gpt2_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("babylm_student_gpt2_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|babylm_student_gpt2_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.6 MB|
+
+## References
+
+https://huggingface.co/momergul/babylm-student-gpt2-2
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-banglabert_generator_finetuned_fill_in_the_blanks_kaggle_en.md b/docs/_posts/ahmedlone127/2025-01-25-banglabert_generator_finetuned_fill_in_the_blanks_kaggle_en.md
new file mode 100644
index 00000000000000..d2f51cb5d8336c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-banglabert_generator_finetuned_fill_in_the_blanks_kaggle_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English banglabert_generator_finetuned_fill_in_the_blanks_kaggle BertEmbeddings from mahsharyahan
+author: John Snow Labs
+name: banglabert_generator_finetuned_fill_in_the_blanks_kaggle
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`banglabert_generator_finetuned_fill_in_the_blanks_kaggle` is a English model originally trained by mahsharyahan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/banglabert_generator_finetuned_fill_in_the_blanks_kaggle_en_5.5.1_3.0_1737775007704.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/banglabert_generator_finetuned_fill_in_the_blanks_kaggle_en_5.5.1_3.0_1737775007704.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("banglabert_generator_finetuned_fill_in_the_blanks_kaggle","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("banglabert_generator_finetuned_fill_in_the_blanks_kaggle","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|banglabert_generator_finetuned_fill_in_the_blanks_kaggle|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|130.0 MB|
+
+## References
+
+https://huggingface.co/mahsharyahan/banglabert_generator-finetuned-fill-in-the-blanks-kaggle
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-banglabert_generator_finetuned_fill_in_the_blanks_kaggle_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-banglabert_generator_finetuned_fill_in_the_blanks_kaggle_pipeline_en.md
new file mode 100644
index 00000000000000..68bf7d89dfd7cf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-banglabert_generator_finetuned_fill_in_the_blanks_kaggle_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English banglabert_generator_finetuned_fill_in_the_blanks_kaggle_pipeline pipeline BertEmbeddings from mahsharyahan
+author: John Snow Labs
+name: banglabert_generator_finetuned_fill_in_the_blanks_kaggle_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`banglabert_generator_finetuned_fill_in_the_blanks_kaggle_pipeline` is a English model originally trained by mahsharyahan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/banglabert_generator_finetuned_fill_in_the_blanks_kaggle_pipeline_en_5.5.1_3.0_1737775014202.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/banglabert_generator_finetuned_fill_in_the_blanks_kaggle_pipeline_en_5.5.1_3.0_1737775014202.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("banglabert_generator_finetuned_fill_in_the_blanks_kaggle_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("banglabert_generator_finetuned_fill_in_the_blanks_kaggle_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|banglabert_generator_finetuned_fill_in_the_blanks_kaggle_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|130.0 MB|
+
+## References
+
+https://huggingface.co/mahsharyahan/banglabert_generator-finetuned-fill-in-the-blanks-kaggle
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bank_complaint_intent_classifier_v2_en.md b/docs/_posts/ahmedlone127/2025-01-25-bank_complaint_intent_classifier_v2_en.md
new file mode 100644
index 00000000000000..6c92fb73ab20fc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bank_complaint_intent_classifier_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bank_complaint_intent_classifier_v2 DistilBertForSequenceClassification from KunalEsM
+author: John Snow Labs
+name: bank_complaint_intent_classifier_v2
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bank_complaint_intent_classifier_v2` is a English model originally trained by KunalEsM.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bank_complaint_intent_classifier_v2_en_5.5.1_3.0_1737838086079.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bank_complaint_intent_classifier_v2_en_5.5.1_3.0_1737838086079.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("bank_complaint_intent_classifier_v2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("bank_complaint_intent_classifier_v2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bank_complaint_intent_classifier_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/KunalEsM/bank_complaint_intent_classifier_v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bank_complaint_intent_classifier_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bank_complaint_intent_classifier_v2_pipeline_en.md
new file mode 100644
index 00000000000000..c0074e0c94a53e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bank_complaint_intent_classifier_v2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bank_complaint_intent_classifier_v2_pipeline pipeline DistilBertForSequenceClassification from KunalEsM
+author: John Snow Labs
+name: bank_complaint_intent_classifier_v2_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bank_complaint_intent_classifier_v2_pipeline` is a English model originally trained by KunalEsM.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bank_complaint_intent_classifier_v2_pipeline_en_5.5.1_3.0_1737838099537.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bank_complaint_intent_classifier_v2_pipeline_en_5.5.1_3.0_1737838099537.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bank_complaint_intent_classifier_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bank_complaint_intent_classifier_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bank_complaint_intent_classifier_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/KunalEsM/bank_complaint_intent_classifier_v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-battlestar_gpt2_small_x49_en.md b/docs/_posts/ahmedlone127/2025-01-25-battlestar_gpt2_small_x49_en.md
new file mode 100644
index 00000000000000..903971d4d9738d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-battlestar_gpt2_small_x49_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English battlestar_gpt2_small_x49 GPT2Transformer from stanford-crfm
+author: John Snow Labs
+name: battlestar_gpt2_small_x49
+date: 2025-01-25
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`battlestar_gpt2_small_x49` is a English model originally trained by stanford-crfm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/battlestar_gpt2_small_x49_en_5.5.1_3.0_1737770923871.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/battlestar_gpt2_small_x49_en_5.5.1_3.0_1737770923871.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("battlestar_gpt2_small_x49","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("battlestar_gpt2_small_x49","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|battlestar_gpt2_small_x49|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|299.3 MB|
+
+## References
+
+https://huggingface.co/stanford-crfm/battlestar-gpt2-small-x49
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-battlestar_gpt2_small_x49_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-battlestar_gpt2_small_x49_pipeline_en.md
new file mode 100644
index 00000000000000..b1c7f0623b8c86
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-battlestar_gpt2_small_x49_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English battlestar_gpt2_small_x49_pipeline pipeline GPT2Transformer from stanford-crfm
+author: John Snow Labs
+name: battlestar_gpt2_small_x49_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`battlestar_gpt2_small_x49_pipeline` is a English model originally trained by stanford-crfm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/battlestar_gpt2_small_x49_pipeline_en_5.5.1_3.0_1737771011231.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/battlestar_gpt2_small_x49_pipeline_en_5.5.1_3.0_1737771011231.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("battlestar_gpt2_small_x49_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("battlestar_gpt2_small_x49_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|battlestar_gpt2_small_x49_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|299.3 MB|
+
+## References
+
+https://huggingface.co/stanford-crfm/battlestar-gpt2-small-x49
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bde_cner_batteryonlybert_uncased_base_en.md b/docs/_posts/ahmedlone127/2025-01-25-bde_cner_batteryonlybert_uncased_base_en.md
new file mode 100644
index 00000000000000..ae37ab4c3459a7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bde_cner_batteryonlybert_uncased_base_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bde_cner_batteryonlybert_uncased_base BertForTokenClassification from batterydata
+author: John Snow Labs
+name: bde_cner_batteryonlybert_uncased_base
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bde_cner_batteryonlybert_uncased_base` is a English model originally trained by batterydata.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bde_cner_batteryonlybert_uncased_base_en_5.5.1_3.0_1737835636368.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bde_cner_batteryonlybert_uncased_base_en_5.5.1_3.0_1737835636368.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bde_cner_batteryonlybert_uncased_base","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bde_cner_batteryonlybert_uncased_base", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bde_cner_batteryonlybert_uncased_base|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|408.1 MB|
+
+## References
+
+https://huggingface.co/batterydata/bde-cner-batteryonlybert-uncased-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bde_cner_batteryonlybert_uncased_base_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bde_cner_batteryonlybert_uncased_base_pipeline_en.md
new file mode 100644
index 00000000000000..6b70f243d67b12
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bde_cner_batteryonlybert_uncased_base_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bde_cner_batteryonlybert_uncased_base_pipeline pipeline BertForTokenClassification from batterydata
+author: John Snow Labs
+name: bde_cner_batteryonlybert_uncased_base_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bde_cner_batteryonlybert_uncased_base_pipeline` is a English model originally trained by batterydata.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bde_cner_batteryonlybert_uncased_base_pipeline_en_5.5.1_3.0_1737835657638.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bde_cner_batteryonlybert_uncased_base_pipeline_en_5.5.1_3.0_1737835657638.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bde_cner_batteryonlybert_uncased_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bde_cner_batteryonlybert_uncased_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bde_cner_batteryonlybert_uncased_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|408.2 MB|
+
+## References
+
+https://huggingface.co/batterydata/bde-cner-batteryonlybert-uncased-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-behpouyan_sentiment_fa.md b/docs/_posts/ahmedlone127/2025-01-25-behpouyan_sentiment_fa.md
new file mode 100644
index 00000000000000..6c4fbfdf28ac25
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-behpouyan_sentiment_fa.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Persian behpouyan_sentiment BertForSequenceClassification from Behpouyan
+author: John Snow Labs
+name: behpouyan_sentiment
+date: 2025-01-25
+tags: [fa, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: fa
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`behpouyan_sentiment` is a Persian model originally trained by Behpouyan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/behpouyan_sentiment_fa_5.5.1_3.0_1737801412881.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/behpouyan_sentiment_fa_5.5.1_3.0_1737801412881.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("behpouyan_sentiment","fa") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("behpouyan_sentiment", "fa")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|behpouyan_sentiment|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|fa|
+|Size:|608.7 MB|
+
+## References
+
+https://huggingface.co/Behpouyan/Behpouyan-Sentiment
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-behpouyan_sentiment_pipeline_fa.md b/docs/_posts/ahmedlone127/2025-01-25-behpouyan_sentiment_pipeline_fa.md
new file mode 100644
index 00000000000000..cc0193a396e8a7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-behpouyan_sentiment_pipeline_fa.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Persian behpouyan_sentiment_pipeline pipeline BertForSequenceClassification from Behpouyan
+author: John Snow Labs
+name: behpouyan_sentiment_pipeline
+date: 2025-01-25
+tags: [fa, open_source, pipeline, onnx]
+task: Text Classification
+language: fa
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`behpouyan_sentiment_pipeline` is a Persian model originally trained by Behpouyan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/behpouyan_sentiment_pipeline_fa_5.5.1_3.0_1737801444151.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/behpouyan_sentiment_pipeline_fa_5.5.1_3.0_1737801444151.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("behpouyan_sentiment_pipeline", lang = "fa")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("behpouyan_sentiment_pipeline", lang = "fa")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|behpouyan_sentiment_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|fa|
+|Size:|608.8 MB|
+
+## References
+
+https://huggingface.co/Behpouyan/Behpouyan-Sentiment
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert1distilbert_base_uncased_finetuned_cola_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert1distilbert_base_uncased_finetuned_cola_en.md
new file mode 100644
index 00000000000000..b332480f5f71ec
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert1distilbert_base_uncased_finetuned_cola_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert1distilbert_base_uncased_finetuned_cola DistilBertForSequenceClassification from NereuS28
+author: John Snow Labs
+name: bert1distilbert_base_uncased_finetuned_cola
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert1distilbert_base_uncased_finetuned_cola` is a English model originally trained by NereuS28.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert1distilbert_base_uncased_finetuned_cola_en_5.5.1_3.0_1737822592867.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert1distilbert_base_uncased_finetuned_cola_en_5.5.1_3.0_1737822592867.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("bert1distilbert_base_uncased_finetuned_cola","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("bert1distilbert_base_uncased_finetuned_cola", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert1distilbert_base_uncased_finetuned_cola|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/NereuS28/BERT1distilbert-base-uncased-finetuned-cola
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert1distilbert_base_uncased_finetuned_cola_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert1distilbert_base_uncased_finetuned_cola_pipeline_en.md
new file mode 100644
index 00000000000000..c0d22a03dee452
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert1distilbert_base_uncased_finetuned_cola_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert1distilbert_base_uncased_finetuned_cola_pipeline pipeline DistilBertForSequenceClassification from NereuS28
+author: John Snow Labs
+name: bert1distilbert_base_uncased_finetuned_cola_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert1distilbert_base_uncased_finetuned_cola_pipeline` is a English model originally trained by NereuS28.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert1distilbert_base_uncased_finetuned_cola_pipeline_en_5.5.1_3.0_1737822606657.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert1distilbert_base_uncased_finetuned_cola_pipeline_en_5.5.1_3.0_1737822606657.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert1distilbert_base_uncased_finetuned_cola_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert1distilbert_base_uncased_finetuned_cola_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert1distilbert_base_uncased_finetuned_cola_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/NereuS28/BERT1distilbert-base-uncased-finetuned-cola
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_1ds_domain_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_1ds_domain_en.md
new file mode 100644
index 00000000000000..11292295f64e74
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_1ds_domain_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_1ds_domain BertEmbeddings from Vishal24
+author: John Snow Labs
+name: bert_1ds_domain
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_1ds_domain` is a English model originally trained by Vishal24.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_1ds_domain_en_5.5.1_3.0_1737806872849.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_1ds_domain_en_5.5.1_3.0_1737806872849.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_1ds_domain","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_1ds_domain","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_1ds_domain|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/Vishal24/bert-1ds-domain
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_1ds_domain_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_1ds_domain_pipeline_en.md
new file mode 100644
index 00000000000000..616f5c3c852982
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_1ds_domain_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_1ds_domain_pipeline pipeline BertEmbeddings from Vishal24
+author: John Snow Labs
+name: bert_1ds_domain_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_1ds_domain_pipeline` is a English model originally trained by Vishal24.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_1ds_domain_pipeline_en_5.5.1_3.0_1737806893886.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_1ds_domain_pipeline_en_5.5.1_3.0_1737806893886.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_1ds_domain_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_1ds_domain_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_1ds_domain_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/Vishal24/bert-1ds-domain
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_martin_fierro_dbarsotti_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_martin_fierro_dbarsotti_en.md
new file mode 100644
index 00000000000000..25e804a700d741
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_martin_fierro_dbarsotti_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_adaptation_martin_fierro_dbarsotti BertEmbeddings from dbarsotti
+author: John Snow Labs
+name: bert_adaptation_martin_fierro_dbarsotti
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_martin_fierro_dbarsotti` is a English model originally trained by dbarsotti.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_martin_fierro_dbarsotti_en_5.5.1_3.0_1737807449314.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_martin_fierro_dbarsotti_en_5.5.1_3.0_1737807449314.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_adaptation_martin_fierro_dbarsotti","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_adaptation_martin_fierro_dbarsotti","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_martin_fierro_dbarsotti|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/dbarsotti/bert_adaptation_martin_fierro
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_martin_fierro_dbarsotti_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_martin_fierro_dbarsotti_pipeline_en.md
new file mode 100644
index 00000000000000..7af5a124cb3a4b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_martin_fierro_dbarsotti_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_adaptation_martin_fierro_dbarsotti_pipeline pipeline BertEmbeddings from dbarsotti
+author: John Snow Labs
+name: bert_adaptation_martin_fierro_dbarsotti_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_martin_fierro_dbarsotti_pipeline` is a English model originally trained by dbarsotti.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_martin_fierro_dbarsotti_pipeline_en_5.5.1_3.0_1737807470143.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_martin_fierro_dbarsotti_pipeline_en_5.5.1_3.0_1737807470143.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_adaptation_martin_fierro_dbarsotti_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_adaptation_martin_fierro_dbarsotti_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_martin_fierro_dbarsotti_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/dbarsotti/bert_adaptation_martin_fierro
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_martin_fierro_guntherfrager_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_martin_fierro_guntherfrager_en.md
new file mode 100644
index 00000000000000..06c554546cfdc5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_martin_fierro_guntherfrager_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_adaptation_martin_fierro_guntherfrager BertEmbeddings from GuntherFrager
+author: John Snow Labs
+name: bert_adaptation_martin_fierro_guntherfrager
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_martin_fierro_guntherfrager` is a English model originally trained by GuntherFrager.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_martin_fierro_guntherfrager_en_5.5.1_3.0_1737774287374.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_martin_fierro_guntherfrager_en_5.5.1_3.0_1737774287374.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_adaptation_martin_fierro_guntherfrager","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_adaptation_martin_fierro_guntherfrager","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_martin_fierro_guntherfrager|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/GuntherFrager/bert_adaptation_martin_fierro
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_martin_fierro_guntherfrager_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_martin_fierro_guntherfrager_pipeline_en.md
new file mode 100644
index 00000000000000..5d605b74df4ceb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_martin_fierro_guntherfrager_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_adaptation_martin_fierro_guntherfrager_pipeline pipeline BertEmbeddings from GuntherFrager
+author: John Snow Labs
+name: bert_adaptation_martin_fierro_guntherfrager_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_martin_fierro_guntherfrager_pipeline` is a English model originally trained by GuntherFrager.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_martin_fierro_guntherfrager_pipeline_en_5.5.1_3.0_1737774309517.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_martin_fierro_guntherfrager_pipeline_en_5.5.1_3.0_1737774309517.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_adaptation_martin_fierro_guntherfrager_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_adaptation_martin_fierro_guntherfrager_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_martin_fierro_guntherfrager_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/GuntherFrager/bert_adaptation_martin_fierro
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_martin_fierro_martinrobins_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_martin_fierro_martinrobins_en.md
new file mode 100644
index 00000000000000..f740b56f0bb974
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_martin_fierro_martinrobins_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_adaptation_martin_fierro_martinrobins BertEmbeddings from MartinRobins
+author: John Snow Labs
+name: bert_adaptation_martin_fierro_martinrobins
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_martin_fierro_martinrobins` is a English model originally trained by MartinRobins.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_martin_fierro_martinrobins_en_5.5.1_3.0_1737807379158.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_martin_fierro_martinrobins_en_5.5.1_3.0_1737807379158.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_adaptation_martin_fierro_martinrobins","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_adaptation_martin_fierro_martinrobins","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_martin_fierro_martinrobins|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/MartinRobins/bert_adaptation_martin_fierro
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_martin_fierro_martinrobins_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_martin_fierro_martinrobins_pipeline_en.md
new file mode 100644
index 00000000000000..2a2facfbddf809
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_martin_fierro_martinrobins_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_adaptation_martin_fierro_martinrobins_pipeline pipeline BertEmbeddings from MartinRobins
+author: John Snow Labs
+name: bert_adaptation_martin_fierro_martinrobins_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_martin_fierro_martinrobins_pipeline` is a English model originally trained by MartinRobins.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_martin_fierro_martinrobins_pipeline_en_5.5.1_3.0_1737807400349.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_martin_fierro_martinrobins_pipeline_en_5.5.1_3.0_1737807400349.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_adaptation_martin_fierro_martinrobins_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_adaptation_martin_fierro_martinrobins_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_martin_fierro_martinrobins_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/MartinRobins/bert_adaptation_martin_fierro
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_peppa_pig_juanph_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_peppa_pig_juanph_en.md
new file mode 100644
index 00000000000000..656337d0af5f21
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_peppa_pig_juanph_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_adaptation_peppa_pig_juanph BertEmbeddings from JuanPH
+author: John Snow Labs
+name: bert_adaptation_peppa_pig_juanph
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_peppa_pig_juanph` is a English model originally trained by JuanPH.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_peppa_pig_juanph_en_5.5.1_3.0_1737774442770.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_peppa_pig_juanph_en_5.5.1_3.0_1737774442770.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_adaptation_peppa_pig_juanph","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_adaptation_peppa_pig_juanph","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_peppa_pig_juanph|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/JuanPH/bert_adaptation_peppa_pig
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_peppa_pig_juanph_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_peppa_pig_juanph_pipeline_en.md
new file mode 100644
index 00000000000000..77af8c79c35b23
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_peppa_pig_juanph_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_adaptation_peppa_pig_juanph_pipeline pipeline BertEmbeddings from JuanPH
+author: John Snow Labs
+name: bert_adaptation_peppa_pig_juanph_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_peppa_pig_juanph_pipeline` is a English model originally trained by JuanPH.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_peppa_pig_juanph_pipeline_en_5.5.1_3.0_1737774464905.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_peppa_pig_juanph_pipeline_en_5.5.1_3.0_1737774464905.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_adaptation_peppa_pig_juanph_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_adaptation_peppa_pig_juanph_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_peppa_pig_juanph_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/JuanPH/bert_adaptation_peppa_pig
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_peppa_pig_valelisciani_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_peppa_pig_valelisciani_en.md
new file mode 100644
index 00000000000000..24be9d31934864
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_peppa_pig_valelisciani_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_adaptation_peppa_pig_valelisciani BertEmbeddings from ValeLisciani
+author: John Snow Labs
+name: bert_adaptation_peppa_pig_valelisciani
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_peppa_pig_valelisciani` is a English model originally trained by ValeLisciani.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_peppa_pig_valelisciani_en_5.5.1_3.0_1737820963459.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_peppa_pig_valelisciani_en_5.5.1_3.0_1737820963459.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_adaptation_peppa_pig_valelisciani","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_adaptation_peppa_pig_valelisciani","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_peppa_pig_valelisciani|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/ValeLisciani/bert_adaptation_peppa_pig
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_peppa_pig_valelisciani_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_peppa_pig_valelisciani_pipeline_en.md
new file mode 100644
index 00000000000000..c2c605cef37c32
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_peppa_pig_valelisciani_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_adaptation_peppa_pig_valelisciani_pipeline pipeline BertEmbeddings from ValeLisciani
+author: John Snow Labs
+name: bert_adaptation_peppa_pig_valelisciani_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_peppa_pig_valelisciani_pipeline` is a English model originally trained by ValeLisciani.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_peppa_pig_valelisciani_pipeline_en_5.5.1_3.0_1737820985486.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_peppa_pig_valelisciani_pipeline_en_5.5.1_3.0_1737820985486.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_adaptation_peppa_pig_valelisciani_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_adaptation_peppa_pig_valelisciani_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_peppa_pig_valelisciani_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/ValeLisciani/bert_adaptation_peppa_pig
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_preguntas_german_norwegian_videntes_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_preguntas_german_norwegian_videntes_en.md
new file mode 100644
index 00000000000000..6e80c203662953
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_preguntas_german_norwegian_videntes_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_adaptation_preguntas_german_norwegian_videntes BertEmbeddings from FAyrolo
+author: John Snow Labs
+name: bert_adaptation_preguntas_german_norwegian_videntes
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_preguntas_german_norwegian_videntes` is a English model originally trained by FAyrolo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_preguntas_german_norwegian_videntes_en_5.5.1_3.0_1737774069011.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_preguntas_german_norwegian_videntes_en_5.5.1_3.0_1737774069011.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_adaptation_preguntas_german_norwegian_videntes","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_adaptation_preguntas_german_norwegian_videntes","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_preguntas_german_norwegian_videntes|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/FAyrolo/bert_adaptation_preguntas_de_no_videntes
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_preguntas_german_norwegian_videntes_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_preguntas_german_norwegian_videntes_pipeline_en.md
new file mode 100644
index 00000000000000..fa1aaf887e189f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_preguntas_german_norwegian_videntes_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_adaptation_preguntas_german_norwegian_videntes_pipeline pipeline BertEmbeddings from FAyrolo
+author: John Snow Labs
+name: bert_adaptation_preguntas_german_norwegian_videntes_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_preguntas_german_norwegian_videntes_pipeline` is a English model originally trained by FAyrolo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_preguntas_german_norwegian_videntes_pipeline_en_5.5.1_3.0_1737774090707.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_preguntas_german_norwegian_videntes_pipeline_en_5.5.1_3.0_1737774090707.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_adaptation_preguntas_german_norwegian_videntes_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_adaptation_preguntas_german_norwegian_videntes_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_preguntas_german_norwegian_videntes_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/FAyrolo/bert_adaptation_preguntas_de_no_videntes
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_referencias_german_vinos_gongoody_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_referencias_german_vinos_gongoody_en.md
new file mode 100644
index 00000000000000..35eb34c66c52f6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_referencias_german_vinos_gongoody_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_adaptation_referencias_german_vinos_gongoody BertEmbeddings from gongoody
+author: John Snow Labs
+name: bert_adaptation_referencias_german_vinos_gongoody
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_referencias_german_vinos_gongoody` is a English model originally trained by gongoody.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_referencias_german_vinos_gongoody_en_5.5.1_3.0_1737806789024.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_referencias_german_vinos_gongoody_en_5.5.1_3.0_1737806789024.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_adaptation_referencias_german_vinos_gongoody","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_adaptation_referencias_german_vinos_gongoody","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_referencias_german_vinos_gongoody|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/gongoody/bert_adaptation_referencias_de_vinos
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_referencias_german_vinos_gongoody_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_referencias_german_vinos_gongoody_pipeline_en.md
new file mode 100644
index 00000000000000..32554591fc5045
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_referencias_german_vinos_gongoody_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_adaptation_referencias_german_vinos_gongoody_pipeline pipeline BertEmbeddings from gongoody
+author: John Snow Labs
+name: bert_adaptation_referencias_german_vinos_gongoody_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_referencias_german_vinos_gongoody_pipeline` is a English model originally trained by gongoody.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_referencias_german_vinos_gongoody_pipeline_en_5.5.1_3.0_1737806810745.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_referencias_german_vinos_gongoody_pipeline_en_5.5.1_3.0_1737806810745.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_adaptation_referencias_german_vinos_gongoody_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_adaptation_referencias_german_vinos_gongoody_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_referencias_german_vinos_gongoody_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/gongoody/bert_adaptation_referencias_de_vinos
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_referencias_german_vinos_naevier_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_referencias_german_vinos_naevier_en.md
new file mode 100644
index 00000000000000..08ebbe00792bbf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_referencias_german_vinos_naevier_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_adaptation_referencias_german_vinos_naevier BertEmbeddings from Naevier
+author: John Snow Labs
+name: bert_adaptation_referencias_german_vinos_naevier
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_referencias_german_vinos_naevier` is a English model originally trained by Naevier.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_referencias_german_vinos_naevier_en_5.5.1_3.0_1737774559313.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_referencias_german_vinos_naevier_en_5.5.1_3.0_1737774559313.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_adaptation_referencias_german_vinos_naevier","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_adaptation_referencias_german_vinos_naevier","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_referencias_german_vinos_naevier|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/Naevier/bert_adaptation_referencias_de_vinos
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_referencias_german_vinos_naevier_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_referencias_german_vinos_naevier_pipeline_en.md
new file mode 100644
index 00000000000000..7bb626853bc96c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_referencias_german_vinos_naevier_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_adaptation_referencias_german_vinos_naevier_pipeline pipeline BertEmbeddings from Naevier
+author: John Snow Labs
+name: bert_adaptation_referencias_german_vinos_naevier_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_referencias_german_vinos_naevier_pipeline` is a English model originally trained by Naevier.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_referencias_german_vinos_naevier_pipeline_en_5.5.1_3.0_1737774582015.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_referencias_german_vinos_naevier_pipeline_en_5.5.1_3.0_1737774582015.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_adaptation_referencias_german_vinos_naevier_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_adaptation_referencias_german_vinos_naevier_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_referencias_german_vinos_naevier_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/Naevier/bert_adaptation_referencias_de_vinos
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_referencias_german_vinos_sofiabobbiesi_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_referencias_german_vinos_sofiabobbiesi_en.md
new file mode 100644
index 00000000000000..0950414e2719ac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_referencias_german_vinos_sofiabobbiesi_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_adaptation_referencias_german_vinos_sofiabobbiesi BertEmbeddings from sofiabobbiesi
+author: John Snow Labs
+name: bert_adaptation_referencias_german_vinos_sofiabobbiesi
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_referencias_german_vinos_sofiabobbiesi` is a English model originally trained by sofiabobbiesi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_referencias_german_vinos_sofiabobbiesi_en_5.5.1_3.0_1737774906930.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_referencias_german_vinos_sofiabobbiesi_en_5.5.1_3.0_1737774906930.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_adaptation_referencias_german_vinos_sofiabobbiesi","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_adaptation_referencias_german_vinos_sofiabobbiesi","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_referencias_german_vinos_sofiabobbiesi|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/sofiabobbiesi/bert_adaptation_referencias_de_vinos
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_referencias_german_vinos_sofiabobbiesi_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_referencias_german_vinos_sofiabobbiesi_pipeline_en.md
new file mode 100644
index 00000000000000..78ce5d38a2663f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_referencias_german_vinos_sofiabobbiesi_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_adaptation_referencias_german_vinos_sofiabobbiesi_pipeline pipeline BertEmbeddings from sofiabobbiesi
+author: John Snow Labs
+name: bert_adaptation_referencias_german_vinos_sofiabobbiesi_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_referencias_german_vinos_sofiabobbiesi_pipeline` is a English model originally trained by sofiabobbiesi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_referencias_german_vinos_sofiabobbiesi_pipeline_en_5.5.1_3.0_1737774931170.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_referencias_german_vinos_sofiabobbiesi_pipeline_en_5.5.1_3.0_1737774931170.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_adaptation_referencias_german_vinos_sofiabobbiesi_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_adaptation_referencias_german_vinos_sofiabobbiesi_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_referencias_german_vinos_sofiabobbiesi_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/sofiabobbiesi/bert_adaptation_referencias_de_vinos
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_referencias_german_vinos_steffstaurini_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_referencias_german_vinos_steffstaurini_en.md
new file mode 100644
index 00000000000000..ce03b3daf9c043
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_referencias_german_vinos_steffstaurini_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_adaptation_referencias_german_vinos_steffstaurini BertEmbeddings from steffstaurini
+author: John Snow Labs
+name: bert_adaptation_referencias_german_vinos_steffstaurini
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_referencias_german_vinos_steffstaurini` is a English model originally trained by steffstaurini.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_referencias_german_vinos_steffstaurini_en_5.5.1_3.0_1737784687258.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_referencias_german_vinos_steffstaurini_en_5.5.1_3.0_1737784687258.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_adaptation_referencias_german_vinos_steffstaurini","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_adaptation_referencias_german_vinos_steffstaurini","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_referencias_german_vinos_steffstaurini|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/steffstaurini/bert_adaptation_referencias_de_vinos
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_referencias_german_vinos_steffstaurini_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_referencias_german_vinos_steffstaurini_pipeline_en.md
new file mode 100644
index 00000000000000..41a0f2818424b1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_adaptation_referencias_german_vinos_steffstaurini_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_adaptation_referencias_german_vinos_steffstaurini_pipeline pipeline BertEmbeddings from steffstaurini
+author: John Snow Labs
+name: bert_adaptation_referencias_german_vinos_steffstaurini_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_referencias_german_vinos_steffstaurini_pipeline` is a English model originally trained by steffstaurini.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_referencias_german_vinos_steffstaurini_pipeline_en_5.5.1_3.0_1737784713331.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_referencias_german_vinos_steffstaurini_pipeline_en_5.5.1_3.0_1737784713331.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_adaptation_referencias_german_vinos_steffstaurini_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_adaptation_referencias_german_vinos_steffstaurini_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_referencias_german_vinos_steffstaurini_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/steffstaurini/bert_adaptation_referencias_de_vinos
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_after_pcgu_finetuned_imdb_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_after_pcgu_finetuned_imdb_en.md
new file mode 100644
index 00000000000000..ae5856aedc05ca
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_after_pcgu_finetuned_imdb_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_after_pcgu_finetuned_imdb BertEmbeddings from cmzheng
+author: John Snow Labs
+name: bert_after_pcgu_finetuned_imdb
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_after_pcgu_finetuned_imdb` is a English model originally trained by cmzheng.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_after_pcgu_finetuned_imdb_en_5.5.1_3.0_1737821369796.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_after_pcgu_finetuned_imdb_en_5.5.1_3.0_1737821369796.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_after_pcgu_finetuned_imdb","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_after_pcgu_finetuned_imdb","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_after_pcgu_finetuned_imdb|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/cmzheng/bert_after_PCGU-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_after_pcgu_finetuned_imdb_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_after_pcgu_finetuned_imdb_pipeline_en.md
new file mode 100644
index 00000000000000..22503788791229
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_after_pcgu_finetuned_imdb_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_after_pcgu_finetuned_imdb_pipeline pipeline BertEmbeddings from cmzheng
+author: John Snow Labs
+name: bert_after_pcgu_finetuned_imdb_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_after_pcgu_finetuned_imdb_pipeline` is a English model originally trained by cmzheng.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_after_pcgu_finetuned_imdb_pipeline_en_5.5.1_3.0_1737821392780.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_after_pcgu_finetuned_imdb_pipeline_en_5.5.1_3.0_1737821392780.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_after_pcgu_finetuned_imdb_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_after_pcgu_finetuned_imdb_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_after_pcgu_finetuned_imdb_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/cmzheng/bert_after_PCGU-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_arabertv2_finetuned_squad_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_arabertv2_finetuned_squad_en.md
new file mode 100644
index 00000000000000..3913f139b04735
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_arabertv2_finetuned_squad_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_arabertv2_finetuned_squad BertForQuestionAnswering from RaghadDS
+author: John Snow Labs
+name: bert_base_arabertv2_finetuned_squad
+date: 2025-01-25
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_arabertv2_finetuned_squad` is a English model originally trained by RaghadDS.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_arabertv2_finetuned_squad_en_5.5.1_3.0_1737812973661.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_arabertv2_finetuned_squad_en_5.5.1_3.0_1737812973661.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_arabertv2_finetuned_squad","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_arabertv2_finetuned_squad", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_arabertv2_finetuned_squad|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|504.8 MB|
+
+## References
+
+https://huggingface.co/RaghadDS/bert-base-arabertv2-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_arabertv2_finetuned_squad_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_arabertv2_finetuned_squad_pipeline_en.md
new file mode 100644
index 00000000000000..22b9d4923f85cb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_arabertv2_finetuned_squad_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_arabertv2_finetuned_squad_pipeline pipeline BertForQuestionAnswering from RaghadDS
+author: John Snow Labs
+name: bert_base_arabertv2_finetuned_squad_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_arabertv2_finetuned_squad_pipeline` is a English model originally trained by RaghadDS.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_arabertv2_finetuned_squad_pipeline_en_5.5.1_3.0_1737813004387.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_arabertv2_finetuned_squad_pipeline_en_5.5.1_3.0_1737813004387.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_arabertv2_finetuned_squad_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_arabertv2_finetuned_squad_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_arabertv2_finetuned_squad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|504.8 MB|
+
+## References
+
+https://huggingface.co/RaghadDS/bert-base-arabertv2-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_buddhist_sanskrit_v2_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_buddhist_sanskrit_v2_en.md
new file mode 100644
index 00000000000000..69cab45b817d31
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_buddhist_sanskrit_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_buddhist_sanskrit_v2 BertEmbeddings from Matej
+author: John Snow Labs
+name: bert_base_buddhist_sanskrit_v2
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_buddhist_sanskrit_v2` is a English model originally trained by Matej.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_buddhist_sanskrit_v2_en_5.5.1_3.0_1737820861862.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_buddhist_sanskrit_v2_en_5.5.1_3.0_1737820861862.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_base_buddhist_sanskrit_v2","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_base_buddhist_sanskrit_v2","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_buddhist_sanskrit_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|408.3 MB|
+
+## References
+
+https://huggingface.co/Matej/bert-base-buddhist-sanskrit-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_buddhist_sanskrit_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_buddhist_sanskrit_v2_pipeline_en.md
new file mode 100644
index 00000000000000..50231dfb7ed548
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_buddhist_sanskrit_v2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_buddhist_sanskrit_v2_pipeline pipeline BertEmbeddings from Matej
+author: John Snow Labs
+name: bert_base_buddhist_sanskrit_v2_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_buddhist_sanskrit_v2_pipeline` is a English model originally trained by Matej.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_buddhist_sanskrit_v2_pipeline_en_5.5.1_3.0_1737820882869.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_buddhist_sanskrit_v2_pipeline_en_5.5.1_3.0_1737820882869.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_buddhist_sanskrit_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_buddhist_sanskrit_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_buddhist_sanskrit_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|408.3 MB|
+
+## References
+
+https://huggingface.co/Matej/bert-base-buddhist-sanskrit-v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_cased_finetuned_ades_sonatafyai_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_cased_finetuned_ades_sonatafyai_en.md
new file mode 100644
index 00000000000000..72434de2e2dd55
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_cased_finetuned_ades_sonatafyai_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_cased_finetuned_ades_sonatafyai BertForTokenClassification from Sonatafyai
+author: John Snow Labs
+name: bert_base_cased_finetuned_ades_sonatafyai
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_finetuned_ades_sonatafyai` is a English model originally trained by Sonatafyai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_finetuned_ades_sonatafyai_en_5.5.1_3.0_1737843913891.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_finetuned_ades_sonatafyai_en_5.5.1_3.0_1737843913891.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_base_cased_finetuned_ades_sonatafyai","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_base_cased_finetuned_ades_sonatafyai", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_cased_finetuned_ades_sonatafyai|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/Sonatafyai/bert-base-cased-finetuned_ADEs_SonatafyAI
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_cased_finetuned_ades_sonatafyai_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_cased_finetuned_ades_sonatafyai_pipeline_en.md
new file mode 100644
index 00000000000000..65db65e0cfeccb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_cased_finetuned_ades_sonatafyai_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_cased_finetuned_ades_sonatafyai_pipeline pipeline BertForTokenClassification from Sonatafyai
+author: John Snow Labs
+name: bert_base_cased_finetuned_ades_sonatafyai_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_finetuned_ades_sonatafyai_pipeline` is a English model originally trained by Sonatafyai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_finetuned_ades_sonatafyai_pipeline_en_5.5.1_3.0_1737843942823.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_finetuned_ades_sonatafyai_pipeline_en_5.5.1_3.0_1737843942823.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_cased_finetuned_ades_sonatafyai_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_cased_finetuned_ades_sonatafyai_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_cased_finetuned_ades_sonatafyai_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/Sonatafyai/bert-base-cased-finetuned_ADEs_SonatafyAI
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_cased_ner_rfb_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_cased_ner_rfb_en.md
new file mode 100644
index 00000000000000..7b85881a2ae739
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_cased_ner_rfb_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_cased_ner_rfb BertForTokenClassification from clamsproject
+author: John Snow Labs
+name: bert_base_cased_ner_rfb
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_ner_rfb` is a English model originally trained by clamsproject.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_ner_rfb_en_5.5.1_3.0_1737845186612.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_ner_rfb_en_5.5.1_3.0_1737845186612.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_base_cased_ner_rfb","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_base_cased_ner_rfb", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_cased_ner_rfb|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/clamsproject/bert-base-cased-ner-rfb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_cased_ner_rfb_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_cased_ner_rfb_pipeline_en.md
new file mode 100644
index 00000000000000..1b67f8666cfa1f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_cased_ner_rfb_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_cased_ner_rfb_pipeline pipeline BertForTokenClassification from clamsproject
+author: John Snow Labs
+name: bert_base_cased_ner_rfb_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_ner_rfb_pipeline` is a English model originally trained by clamsproject.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_ner_rfb_pipeline_en_5.5.1_3.0_1737845207585.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_ner_rfb_pipeline_en_5.5.1_3.0_1737845207585.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_cased_ner_rfb_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_cased_ner_rfb_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_cased_ner_rfb_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/clamsproject/bert-base-cased-ner-rfb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_cased_wikitext2_agkelly_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_cased_wikitext2_agkelly_en.md
new file mode 100644
index 00000000000000..f6b79beb1254ef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_cased_wikitext2_agkelly_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_cased_wikitext2_agkelly BertEmbeddings from agkelly
+author: John Snow Labs
+name: bert_base_cased_wikitext2_agkelly
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_wikitext2_agkelly` is a English model originally trained by agkelly.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_wikitext2_agkelly_en_5.5.1_3.0_1737774721053.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_wikitext2_agkelly_en_5.5.1_3.0_1737774721053.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_base_cased_wikitext2_agkelly","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_base_cased_wikitext2_agkelly","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_cased_wikitext2_agkelly|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|403.4 MB|
+
+## References
+
+https://huggingface.co/agkelly/bert-base-cased-wikitext2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_cased_wikitext2_agkelly_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_cased_wikitext2_agkelly_pipeline_en.md
new file mode 100644
index 00000000000000..ca148c175c4b59
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_cased_wikitext2_agkelly_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_cased_wikitext2_agkelly_pipeline pipeline BertEmbeddings from agkelly
+author: John Snow Labs
+name: bert_base_cased_wikitext2_agkelly_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_wikitext2_agkelly_pipeline` is a English model originally trained by agkelly.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_wikitext2_agkelly_pipeline_en_5.5.1_3.0_1737774742794.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_wikitext2_agkelly_pipeline_en_5.5.1_3.0_1737774742794.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_cased_wikitext2_agkelly_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_cased_wikitext2_agkelly_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_cased_wikitext2_agkelly_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.5 MB|
+
+## References
+
+https://huggingface.co/agkelly/bert-base-cased-wikitext2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_german_uncased_de.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_german_uncased_de.md
new file mode 100644
index 00000000000000..46f45ad42a34db
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_german_uncased_de.md
@@ -0,0 +1,80 @@
+---
+layout: model
+title: German BERT Base Uncased Model
+author: John Snow Labs
+name: bert_base_german_uncased
+date: 2025-01-25
+tags: [open_source, embeddings, german, de, bert, onnx]
+task: Embeddings
+language: de
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+The source data for the model consists of a recent Wikipedia dump, EU Bookshop corpus, Open Subtitles, CommonCrawl, ParaCrawl and News Crawl. This results in a dataset with a size of 16GB and 2,350,234,427 tokens. The model is trained with an initial sequence length of 512 subwords and was performed for 1.5M steps.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_german_uncased_de_5.5.1_3.0_1737846714781.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_german_uncased_de_5.5.1_3.0_1737846714781.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+embeddings = BertEmbeddings.pretrained("bert_base_german_uncased", "de") \
+.setInputCols("sentence", "token") \
+.setOutputCol("embeddings")
+nlp_pipeline = Pipeline(stages=[document_assembler, sentence_detector, tokenizer, embeddings])
+```
+```scala
+val embeddings = BertEmbeddings.pretrained("bert_base_german_uncased", "de")
+.setInputCols("sentence", "token")
+.setOutputCol("embeddings")
+val pipeline = new Pipeline().setStages(Array(document_assembler, sentence_detector, tokenizer, embeddings))
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("de.embed.bert.uncased").predict("""Put your text here.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_german_uncased|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|de|
+|Size:|409.9 MB|
+
+## Benchmarking
+
+```bash
+
+For results on downstream tasks like NER or PoS tagging, please refer to
+[this repository](https://github.com/stefan-it/fine-tuned-berts-seq).
+```
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_german_uncased_pipeline_de.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_german_uncased_pipeline_de.md
new file mode 100644
index 00000000000000..44fa93612ed6db
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_german_uncased_pipeline_de.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: German bert_base_german_uncased_pipeline pipeline BertEmbeddings from voize
+author: John Snow Labs
+name: bert_base_german_uncased_pipeline
+date: 2025-01-25
+tags: [de, open_source, pipeline, onnx]
+task: Embeddings
+language: de
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_german_uncased_pipeline` is a German model originally trained by voize.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_german_uncased_pipeline_de_5.5.1_3.0_1737846734613.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_german_uncased_pipeline_de_5.5.1_3.0_1737846734613.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_german_uncased_pipeline", lang = "de")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_german_uncased_pipeline", lang = "de")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_german_uncased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|de|
+|Size:|409.9 MB|
+
+## References
+
+https://huggingface.co/voize/bert-base-german-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_gpt_review_classification_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_gpt_review_classification_en.md
new file mode 100644
index 00000000000000..2c6cced3b46283
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_gpt_review_classification_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_gpt_review_classification BertForSequenceClassification from djangodevloper
+author: John Snow Labs
+name: bert_base_gpt_review_classification
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_gpt_review_classification` is a English model originally trained by djangodevloper.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_gpt_review_classification_en_5.5.1_3.0_1737800666782.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_gpt_review_classification_en_5.5.1_3.0_1737800666782.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("bert_base_gpt_review_classification","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_gpt_review_classification", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_gpt_review_classification|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/djangodevloper/bert-base-gpt-review-classification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_gpt_review_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_gpt_review_classification_pipeline_en.md
new file mode 100644
index 00000000000000..12e296349ea6f6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_gpt_review_classification_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_gpt_review_classification_pipeline pipeline BertForSequenceClassification from djangodevloper
+author: John Snow Labs
+name: bert_base_gpt_review_classification_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_gpt_review_classification_pipeline` is a English model originally trained by djangodevloper.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_gpt_review_classification_pipeline_en_5.5.1_3.0_1737800688428.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_gpt_review_classification_pipeline_en_5.5.1_3.0_1737800688428.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_gpt_review_classification_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_gpt_review_classification_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_gpt_review_classification_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/djangodevloper/bert-base-gpt-review-classification
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_lda_20_v1_book_sst2_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_lda_20_v1_book_sst2_en.md
new file mode 100644
index 00000000000000..32b5bd2d279fbc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_lda_20_v1_book_sst2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_lda_20_v1_book_sst2 DistilBertForSequenceClassification from gokulsrinivasagan
+author: John Snow Labs
+name: bert_base_lda_20_v1_book_sst2
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_lda_20_v1_book_sst2` is a English model originally trained by gokulsrinivasagan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_lda_20_v1_book_sst2_en_5.5.1_3.0_1737837885413.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_lda_20_v1_book_sst2_en_5.5.1_3.0_1737837885413.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("bert_base_lda_20_v1_book_sst2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("bert_base_lda_20_v1_book_sst2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_lda_20_v1_book_sst2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|410.2 MB|
+
+## References
+
+https://huggingface.co/gokulsrinivasagan/bert_base_lda_20_v1_book_sst2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_lda_20_v1_book_sst2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_lda_20_v1_book_sst2_pipeline_en.md
new file mode 100644
index 00000000000000..5794b3f9e1c0bb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_lda_20_v1_book_sst2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_lda_20_v1_book_sst2_pipeline pipeline DistilBertForSequenceClassification from gokulsrinivasagan
+author: John Snow Labs
+name: bert_base_lda_20_v1_book_sst2_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_lda_20_v1_book_sst2_pipeline` is a English model originally trained by gokulsrinivasagan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_lda_20_v1_book_sst2_pipeline_en_5.5.1_3.0_1737837906981.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_lda_20_v1_book_sst2_pipeline_en_5.5.1_3.0_1737837906981.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_lda_20_v1_book_sst2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_lda_20_v1_book_sst2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_lda_20_v1_book_sst2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.2 MB|
+
+## References
+
+https://huggingface.co/gokulsrinivasagan/bert_base_lda_20_v1_book_sst2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_lda_5_v1_book_cola_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_lda_5_v1_book_cola_en.md
new file mode 100644
index 00000000000000..e7767a8b10f41d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_lda_5_v1_book_cola_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_lda_5_v1_book_cola DistilBertForSequenceClassification from gokulsrinivasagan
+author: John Snow Labs
+name: bert_base_lda_5_v1_book_cola
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_lda_5_v1_book_cola` is a English model originally trained by gokulsrinivasagan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_lda_5_v1_book_cola_en_5.5.1_3.0_1737837977498.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_lda_5_v1_book_cola_en_5.5.1_3.0_1737837977498.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("bert_base_lda_5_v1_book_cola","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("bert_base_lda_5_v1_book_cola", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_lda_5_v1_book_cola|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|410.2 MB|
+
+## References
+
+https://huggingface.co/gokulsrinivasagan/bert_base_lda_5_v1_book_cola
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_lda_5_v1_book_cola_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_lda_5_v1_book_cola_pipeline_en.md
new file mode 100644
index 00000000000000..d40aa7a94488c9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_lda_5_v1_book_cola_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_lda_5_v1_book_cola_pipeline pipeline DistilBertForSequenceClassification from gokulsrinivasagan
+author: John Snow Labs
+name: bert_base_lda_5_v1_book_cola_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_lda_5_v1_book_cola_pipeline` is a English model originally trained by gokulsrinivasagan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_lda_5_v1_book_cola_pipeline_en_5.5.1_3.0_1737837999402.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_lda_5_v1_book_cola_pipeline_en_5.5.1_3.0_1737837999402.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_lda_5_v1_book_cola_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_lda_5_v1_book_cola_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_lda_5_v1_book_cola_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.2 MB|
+
+## References
+
+https://huggingface.co/gokulsrinivasagan/bert_base_lda_5_v1_book_cola
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_lda_rte_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_lda_rte_en.md
new file mode 100644
index 00000000000000..eacec0a9755910
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_lda_rte_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_lda_rte DistilBertForSequenceClassification from gokulsrinivasagan
+author: John Snow Labs
+name: bert_base_lda_rte
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_lda_rte` is a English model originally trained by gokulsrinivasagan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_lda_rte_en_5.5.1_3.0_1737838121813.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_lda_rte_en_5.5.1_3.0_1737838121813.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("bert_base_lda_rte","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("bert_base_lda_rte", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_lda_rte|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|410.4 MB|
+
+## References
+
+https://huggingface.co/gokulsrinivasagan/bert_base_lda_rte
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_lda_rte_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_lda_rte_pipeline_en.md
new file mode 100644
index 00000000000000..8fd736dd86b033
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_lda_rte_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_lda_rte_pipeline pipeline DistilBertForSequenceClassification from gokulsrinivasagan
+author: John Snow Labs
+name: bert_base_lda_rte_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_lda_rte_pipeline` is a English model originally trained by gokulsrinivasagan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_lda_rte_pipeline_en_5.5.1_3.0_1737838144819.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_lda_rte_pipeline_en_5.5.1_3.0_1737838144819.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_lda_rte_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_lda_rte_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_lda_rte_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.4 MB|
+
+## References
+
+https://huggingface.co/gokulsrinivasagan/bert_base_lda_rte
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_mm_awesomealignindic_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_mm_awesomealignindic_en.md
new file mode 100644
index 00000000000000..8f1691a738f7e4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_mm_awesomealignindic_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_mm_awesomealignindic BertEmbeddings from ABHIiiii1
+author: John Snow Labs
+name: bert_base_mm_awesomealignindic
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_mm_awesomealignindic` is a English model originally trained by ABHIiiii1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_mm_awesomealignindic_en_5.5.1_3.0_1737784711378.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_mm_awesomealignindic_en_5.5.1_3.0_1737784711378.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_base_mm_awesomealignindic","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_base_mm_awesomealignindic","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_mm_awesomealignindic|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/ABHIiiii1/bert-base-mm-awesomeAlignIndic
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_mm_awesomealignindic_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_mm_awesomealignindic_pipeline_en.md
new file mode 100644
index 00000000000000..1ca315ad526f85
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_mm_awesomealignindic_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_mm_awesomealignindic_pipeline pipeline BertEmbeddings from ABHIiiii1
+author: John Snow Labs
+name: bert_base_mm_awesomealignindic_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_mm_awesomealignindic_pipeline` is a English model originally trained by ABHIiiii1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_mm_awesomealignindic_pipeline_en_5.5.1_3.0_1737784755579.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_mm_awesomealignindic_pipeline_en_5.5.1_3.0_1737784755579.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_mm_awesomealignindic_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_mm_awesomealignindic_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_mm_awesomealignindic_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/ABHIiiii1/bert-base-mm-awesomeAlignIndic
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_multilingual_cased_finetuned_pipeline_xx.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_multilingual_cased_finetuned_pipeline_xx.md
new file mode 100644
index 00000000000000..6df697eae50551
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_multilingual_cased_finetuned_pipeline_xx.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Multilingual bert_base_multilingual_cased_finetuned_pipeline pipeline BertForQuestionAnswering from badokorach
+author: John Snow Labs
+name: bert_base_multilingual_cased_finetuned_pipeline
+date: 2025-01-25
+tags: [xx, open_source, pipeline, onnx]
+task: Question Answering
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_cased_finetuned_pipeline` is a Multilingual model originally trained by badokorach.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_pipeline_xx_5.5.1_3.0_1737813831376.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_pipeline_xx_5.5.1_3.0_1737813831376.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_multilingual_cased_finetuned_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_multilingual_cased_finetuned_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_multilingual_cased_finetuned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/badokorach/bert-base-multilingual-cased-finetuned
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_multilingual_cased_finetuned_xx.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_multilingual_cased_finetuned_xx.md
new file mode 100644
index 00000000000000..7e6a24d9cf8733
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_multilingual_cased_finetuned_xx.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Multilingual bert_base_multilingual_cased_finetuned BertForQuestionAnswering from badokorach
+author: John Snow Labs
+name: bert_base_multilingual_cased_finetuned
+date: 2025-01-25
+tags: [xx, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_cased_finetuned` is a Multilingual model originally trained by badokorach.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_xx_5.5.1_3.0_1737813792658.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_xx_5.5.1_3.0_1737813792658.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_multilingual_cased_finetuned","xx") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_multilingual_cased_finetuned", "xx")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_multilingual_cased_finetuned|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|xx|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/badokorach/bert-base-multilingual-cased-finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_multilingual_cased_mongolian_ner_pipeline_xx.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_multilingual_cased_mongolian_ner_pipeline_xx.md
new file mode 100644
index 00000000000000..d5eab7c358d381
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_multilingual_cased_mongolian_ner_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual bert_base_multilingual_cased_mongolian_ner_pipeline pipeline BertForTokenClassification from nemuwn
+author: John Snow Labs
+name: bert_base_multilingual_cased_mongolian_ner_pipeline
+date: 2025-01-25
+tags: [xx, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_cased_mongolian_ner_pipeline` is a Multilingual model originally trained by nemuwn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_mongolian_ner_pipeline_xx_5.5.1_3.0_1737835225196.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_mongolian_ner_pipeline_xx_5.5.1_3.0_1737835225196.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_multilingual_cased_mongolian_ner_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_multilingual_cased_mongolian_ner_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_multilingual_cased_mongolian_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/nemuwn/bert-base-multilingual-cased-mongolian-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_multilingual_cased_mongolian_ner_xx.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_multilingual_cased_mongolian_ner_xx.md
new file mode 100644
index 00000000000000..b67a9af1abc4c7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_multilingual_cased_mongolian_ner_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual bert_base_multilingual_cased_mongolian_ner BertForTokenClassification from nemuwn
+author: John Snow Labs
+name: bert_base_multilingual_cased_mongolian_ner
+date: 2025-01-25
+tags: [xx, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_cased_mongolian_ner` is a Multilingual model originally trained by nemuwn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_mongolian_ner_xx_5.5.1_3.0_1737835191235.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_mongolian_ner_xx_5.5.1_3.0_1737835191235.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_base_multilingual_cased_mongolian_ner","xx") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_base_multilingual_cased_mongolian_ner", "xx")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_multilingual_cased_mongolian_ner|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|xx|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/nemuwn/bert-base-multilingual-cased-mongolian-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_sanskrit_saskta_mental_uncased_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_sanskrit_saskta_mental_uncased_en.md
new file mode 100644
index 00000000000000..a3cb07ec382368
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_sanskrit_saskta_mental_uncased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_sanskrit_saskta_mental_uncased BertForSequenceClassification from djangodevloper
+author: John Snow Labs
+name: bert_base_sanskrit_saskta_mental_uncased
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_sanskrit_saskta_mental_uncased` is a English model originally trained by djangodevloper.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_sanskrit_saskta_mental_uncased_en_5.5.1_3.0_1737800510330.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_sanskrit_saskta_mental_uncased_en_5.5.1_3.0_1737800510330.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("bert_base_sanskrit_saskta_mental_uncased","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_sanskrit_saskta_mental_uncased", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_sanskrit_saskta_mental_uncased|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/djangodevloper/bert-base-sa-mental-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_sanskrit_saskta_mental_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_sanskrit_saskta_mental_uncased_pipeline_en.md
new file mode 100644
index 00000000000000..1e8d1ab01cff55
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_sanskrit_saskta_mental_uncased_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_sanskrit_saskta_mental_uncased_pipeline pipeline BertForSequenceClassification from djangodevloper
+author: John Snow Labs
+name: bert_base_sanskrit_saskta_mental_uncased_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_sanskrit_saskta_mental_uncased_pipeline` is a English model originally trained by djangodevloper.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_sanskrit_saskta_mental_uncased_pipeline_en_5.5.1_3.0_1737800531882.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_sanskrit_saskta_mental_uncased_pipeline_en_5.5.1_3.0_1737800531882.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_sanskrit_saskta_mental_uncased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_sanskrit_saskta_mental_uncased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_sanskrit_saskta_mental_uncased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/djangodevloper/bert-base-sa-mental-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_train_book_qqp_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_train_book_qqp_en.md
new file mode 100644
index 00000000000000..9a682ca4a1b996
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_train_book_qqp_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_train_book_qqp DistilBertForSequenceClassification from gokulsrinivasagan
+author: John Snow Labs
+name: bert_base_train_book_qqp
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_train_book_qqp` is a English model originally trained by gokulsrinivasagan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_train_book_qqp_en_5.5.1_3.0_1737836873808.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_train_book_qqp_en_5.5.1_3.0_1737836873808.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("bert_base_train_book_qqp","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("bert_base_train_book_qqp", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_train_book_qqp|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|410.2 MB|
+
+## References
+
+https://huggingface.co/gokulsrinivasagan/bert_base_train_book_qqp
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_train_book_qqp_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_train_book_qqp_pipeline_en.md
new file mode 100644
index 00000000000000..e02a11d52526fc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_train_book_qqp_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_train_book_qqp_pipeline pipeline DistilBertForSequenceClassification from gokulsrinivasagan
+author: John Snow Labs
+name: bert_base_train_book_qqp_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_train_book_qqp_pipeline` is a English model originally trained by gokulsrinivasagan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_train_book_qqp_pipeline_en_5.5.1_3.0_1737836896956.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_train_book_qqp_pipeline_en_5.5.1_3.0_1737836896956.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_train_book_qqp_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_train_book_qqp_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_train_book_qqp_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.3 MB|
+
+## References
+
+https://huggingface.co/gokulsrinivasagan/bert_base_train_book_qqp
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_train_book_rte_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_train_book_rte_en.md
new file mode 100644
index 00000000000000..d1ab2300136bff
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_train_book_rte_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_train_book_rte DistilBertForSequenceClassification from gokulsrinivasagan
+author: John Snow Labs
+name: bert_base_train_book_rte
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_train_book_rte` is a English model originally trained by gokulsrinivasagan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_train_book_rte_en_5.5.1_3.0_1737836772981.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_train_book_rte_en_5.5.1_3.0_1737836772981.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("bert_base_train_book_rte","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("bert_base_train_book_rte", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_train_book_rte|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|410.2 MB|
+
+## References
+
+https://huggingface.co/gokulsrinivasagan/bert_base_train_book_rte
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_train_book_rte_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_train_book_rte_pipeline_en.md
new file mode 100644
index 00000000000000..bd64eb59e4da9a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_train_book_rte_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_train_book_rte_pipeline pipeline DistilBertForSequenceClassification from gokulsrinivasagan
+author: John Snow Labs
+name: bert_base_train_book_rte_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_train_book_rte_pipeline` is a English model originally trained by gokulsrinivasagan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_train_book_rte_pipeline_en_5.5.1_3.0_1737836793608.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_train_book_rte_pipeline_en_5.5.1_3.0_1737836793608.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_train_book_rte_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_train_book_rte_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_train_book_rte_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.3 MB|
+
+## References
+
+https://huggingface.co/gokulsrinivasagan/bert_base_train_book_rte
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_turkish_cased2_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_turkish_cased2_en.md
new file mode 100644
index 00000000000000..60e7f67378eb55
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_turkish_cased2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_turkish_cased2 BertForTokenClassification from hks1444
+author: John Snow Labs
+name: bert_base_turkish_cased2
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_turkish_cased2` is a English model originally trained by hks1444.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_turkish_cased2_en_5.5.1_3.0_1737835139593.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_turkish_cased2_en_5.5.1_3.0_1737835139593.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_base_turkish_cased2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_base_turkish_cased2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_turkish_cased2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|412.3 MB|
+
+## References
+
+https://huggingface.co/hks1444/bert-base-turkish-cased2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_turkish_cased2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_turkish_cased2_pipeline_en.md
new file mode 100644
index 00000000000000..006b6a36186a2b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_turkish_cased2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_turkish_cased2_pipeline pipeline BertForTokenClassification from hks1444
+author: John Snow Labs
+name: bert_base_turkish_cased2_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_turkish_cased2_pipeline` is a English model originally trained by hks1444.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_turkish_cased2_pipeline_en_5.5.1_3.0_1737835161253.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_turkish_cased2_pipeline_en_5.5.1_3.0_1737835161253.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_turkish_cased2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_turkish_cased2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_turkish_cased2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|412.3 MB|
+
+## References
+
+https://huggingface.co/hks1444/bert-base-turkish-cased2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_ep_10_0_b_8_lr_4e_07_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_1000_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_ep_10_0_b_8_lr_4e_07_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_1000_en.md
new file mode 100644
index 00000000000000..c93f314ef58077
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_ep_10_0_b_8_lr_4e_07_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_1000_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_ep_10_0_b_8_lr_4e_07_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_1000 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_10_0_b_8_lr_4e_07_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_1000
+date: 2025-01-25
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_10_0_b_8_lr_4e_07_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_1000` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_10_0_b_8_lr_4e_07_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_1000_en_5.5.1_3.0_1737812851803.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_10_0_b_8_lr_4e_07_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_1000_en_5.5.1_3.0_1737812851803.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_10_0_b_8_lr_4e_07_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_1000","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_10_0_b_8_lr_4e_07_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_1000", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_10_0_b_8_lr_4e_07_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_1000|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-10.0-b-8-lr-4e-07-dp-1.0-ss-0-st-False-fh-False-hs-1000
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_ep_10_0_b_8_lr_4e_07_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_1000_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_ep_10_0_b_8_lr_4e_07_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_1000_pipeline_en.md
new file mode 100644
index 00000000000000..a454534a850f6f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_ep_10_0_b_8_lr_4e_07_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_1000_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_ep_10_0_b_8_lr_4e_07_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_1000_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_10_0_b_8_lr_4e_07_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_1000_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_10_0_b_8_lr_4e_07_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_1000_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_10_0_b_8_lr_4e_07_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_1000_pipeline_en_5.5.1_3.0_1737812873730.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_10_0_b_8_lr_4e_07_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_1000_pipeline_en_5.5.1_3.0_1737812873730.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_ep_10_0_b_8_lr_4e_07_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_1000_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_ep_10_0_b_8_lr_4e_07_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_1000_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_10_0_b_8_lr_4e_07_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_1000_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-10.0-b-8-lr-4e-07-dp-1.0-ss-0-st-False-fh-False-hs-1000
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_ep_1_29_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_ep_1_29_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en.md
new file mode 100644
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--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_ep_1_29_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_ep_1_29_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_1_29_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0
+date: 2025-01-25
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_1_29_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_29_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en_5.5.1_3.0_1737812944188.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_29_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en_5.5.1_3.0_1737812944188.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_1_29_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_1_29_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_1_29_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-1.29-b-32-lr-4e-07-dp-0.5-ss-0-st-True-fh-False-hs-0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_ep_1_29_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_ep_1_29_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en.md
new file mode 100644
index 00000000000000..50bcbe29b708c4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_ep_1_29_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_ep_1_29_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_1_29_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_1_29_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_29_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en_5.5.1_3.0_1737812965992.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_29_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en_5.5.1_3.0_1737812965992.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_ep_1_29_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_ep_1_29_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_1_29_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-1.29-b-32-lr-4e-07-dp-0.5-ss-0-st-True-fh-False-hs-0
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_ep_2_69_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_ep_2_69_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en.md
new file mode 100644
index 00000000000000..29c5d25324a739
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_ep_2_69_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_ep_2_69_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_2_69_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0
+date: 2025-01-25
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_2_69_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_2_69_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en_5.5.1_3.0_1737812975204.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_2_69_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_en_5.5.1_3.0_1737812975204.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_2_69_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_2_69_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_2_69_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-2.69-b-32-lr-4e-07-dp-0.5-ss-0-st-True-fh-False-hs-0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_ep_2_69_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_ep_2_69_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en.md
new file mode 100644
index 00000000000000..ac153c5899bb83
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_ep_2_69_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_ep_2_69_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_2_69_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_2_69_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_2_69_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en_5.5.1_3.0_1737813000969.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_2_69_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en_5.5.1_3.0_1737813000969.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_ep_2_69_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_ep_2_69_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_2_69_b_32_lr_4e_07_dp_0_5_swati_0_southern_sotho_true_fh_false_hs_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-2.69-b-32-lr-4e-07-dp-0.5-ss-0-st-True-fh-False-hs-0
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_ep_3_11_b_32_lr_4e_07_dp_1_0_swati_700_southern_sotho_false_fh_true_hs_0_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_ep_3_11_b_32_lr_4e_07_dp_1_0_swati_700_southern_sotho_false_fh_true_hs_0_en.md
new file mode 100644
index 00000000000000..89ddd30c81622e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_ep_3_11_b_32_lr_4e_07_dp_1_0_swati_700_southern_sotho_false_fh_true_hs_0_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_ep_3_11_b_32_lr_4e_07_dp_1_0_swati_700_southern_sotho_false_fh_true_hs_0 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_3_11_b_32_lr_4e_07_dp_1_0_swati_700_southern_sotho_false_fh_true_hs_0
+date: 2025-01-25
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_3_11_b_32_lr_4e_07_dp_1_0_swati_700_southern_sotho_false_fh_true_hs_0` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_3_11_b_32_lr_4e_07_dp_1_0_swati_700_southern_sotho_false_fh_true_hs_0_en_5.5.1_3.0_1737813511804.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_3_11_b_32_lr_4e_07_dp_1_0_swati_700_southern_sotho_false_fh_true_hs_0_en_5.5.1_3.0_1737813511804.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_3_11_b_32_lr_4e_07_dp_1_0_swati_700_southern_sotho_false_fh_true_hs_0","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_3_11_b_32_lr_4e_07_dp_1_0_swati_700_southern_sotho_false_fh_true_hs_0", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_3_11_b_32_lr_4e_07_dp_1_0_swati_700_southern_sotho_false_fh_true_hs_0|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-3.11-b-32-lr-4e-07-dp-1.0-ss-700-st-False-fh-True-hs-0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_ep_3_11_b_32_lr_4e_07_dp_1_0_swati_700_southern_sotho_false_fh_true_hs_0_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_ep_3_11_b_32_lr_4e_07_dp_1_0_swati_700_southern_sotho_false_fh_true_hs_0_pipeline_en.md
new file mode 100644
index 00000000000000..9d1ce09dad6cbe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_ep_3_11_b_32_lr_4e_07_dp_1_0_swati_700_southern_sotho_false_fh_true_hs_0_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_ep_3_11_b_32_lr_4e_07_dp_1_0_swati_700_southern_sotho_false_fh_true_hs_0_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_3_11_b_32_lr_4e_07_dp_1_0_swati_700_southern_sotho_false_fh_true_hs_0_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_3_11_b_32_lr_4e_07_dp_1_0_swati_700_southern_sotho_false_fh_true_hs_0_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_3_11_b_32_lr_4e_07_dp_1_0_swati_700_southern_sotho_false_fh_true_hs_0_pipeline_en_5.5.1_3.0_1737813533087.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_3_11_b_32_lr_4e_07_dp_1_0_swati_700_southern_sotho_false_fh_true_hs_0_pipeline_en_5.5.1_3.0_1737813533087.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_ep_3_11_b_32_lr_4e_07_dp_1_0_swati_700_southern_sotho_false_fh_true_hs_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_ep_3_11_b_32_lr_4e_07_dp_1_0_swati_700_southern_sotho_false_fh_true_hs_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_3_11_b_32_lr_4e_07_dp_1_0_swati_700_southern_sotho_false_fh_true_hs_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-3.11-b-32-lr-4e-07-dp-1.0-ss-700-st-False-fh-True-hs-0
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_ep_3_74_b_32_lr_4e_07_dp_1_0_swati_800_southern_sotho_false_fh_true_hs_0_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_ep_3_74_b_32_lr_4e_07_dp_1_0_swati_800_southern_sotho_false_fh_true_hs_0_en.md
new file mode 100644
index 00000000000000..0080b8847b9001
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_ep_3_74_b_32_lr_4e_07_dp_1_0_swati_800_southern_sotho_false_fh_true_hs_0_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_ep_3_74_b_32_lr_4e_07_dp_1_0_swati_800_southern_sotho_false_fh_true_hs_0 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_3_74_b_32_lr_4e_07_dp_1_0_swati_800_southern_sotho_false_fh_true_hs_0
+date: 2025-01-25
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_3_74_b_32_lr_4e_07_dp_1_0_swati_800_southern_sotho_false_fh_true_hs_0` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_3_74_b_32_lr_4e_07_dp_1_0_swati_800_southern_sotho_false_fh_true_hs_0_en_5.5.1_3.0_1737813365181.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_3_74_b_32_lr_4e_07_dp_1_0_swati_800_southern_sotho_false_fh_true_hs_0_en_5.5.1_3.0_1737813365181.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_3_74_b_32_lr_4e_07_dp_1_0_swati_800_southern_sotho_false_fh_true_hs_0","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_3_74_b_32_lr_4e_07_dp_1_0_swati_800_southern_sotho_false_fh_true_hs_0", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_3_74_b_32_lr_4e_07_dp_1_0_swati_800_southern_sotho_false_fh_true_hs_0|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-3.74-b-32-lr-4e-07-dp-1.0-ss-800-st-False-fh-True-hs-0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_ep_3_74_b_32_lr_4e_07_dp_1_0_swati_800_southern_sotho_false_fh_true_hs_0_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_ep_3_74_b_32_lr_4e_07_dp_1_0_swati_800_southern_sotho_false_fh_true_hs_0_pipeline_en.md
new file mode 100644
index 00000000000000..013bdfcb382bca
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_ep_3_74_b_32_lr_4e_07_dp_1_0_swati_800_southern_sotho_false_fh_true_hs_0_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_ep_3_74_b_32_lr_4e_07_dp_1_0_swati_800_southern_sotho_false_fh_true_hs_0_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_3_74_b_32_lr_4e_07_dp_1_0_swati_800_southern_sotho_false_fh_true_hs_0_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_3_74_b_32_lr_4e_07_dp_1_0_swati_800_southern_sotho_false_fh_true_hs_0_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_3_74_b_32_lr_4e_07_dp_1_0_swati_800_southern_sotho_false_fh_true_hs_0_pipeline_en_5.5.1_3.0_1737813386316.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_3_74_b_32_lr_4e_07_dp_1_0_swati_800_southern_sotho_false_fh_true_hs_0_pipeline_en_5.5.1_3.0_1737813386316.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_ep_3_74_b_32_lr_4e_07_dp_1_0_swati_800_southern_sotho_false_fh_true_hs_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_ep_3_74_b_32_lr_4e_07_dp_1_0_swati_800_southern_sotho_false_fh_true_hs_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_3_74_b_32_lr_4e_07_dp_1_0_swati_800_southern_sotho_false_fh_true_hs_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-3.74-b-32-lr-4e-07-dp-1.0-ss-800-st-False-fh-True-hs-0
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_99999_swati_10000_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_99999_swati_10000_en.md
new file mode 100644
index 00000000000000..c23f369ed3d87c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_99999_swati_10000_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_99999_swati_10000 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_99999_swati_10000
+date: 2025-01-25
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_99999_swati_10000` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_99999_swati_10000_en_5.5.1_3.0_1737814106747.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_99999_swati_10000_en_5.5.1_3.0_1737814106747.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_99999_swati_10000","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_99999_swati_10000", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_99999_swati_10000|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.0-lr-1e-05-wd-0.001-dp-0.99999-ss-10000
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_99999_swati_10000_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_99999_swati_10000_pipeline_en.md
new file mode 100644
index 00000000000000..e36601127a6f59
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_99999_swati_10000_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_99999_swati_10000_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_99999_swati_10000_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_99999_swati_10000_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_99999_swati_10000_pipeline_en_5.5.1_3.0_1737814127685.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_99999_swati_10000_pipeline_en_5.5.1_3.0_1737814127685.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_99999_swati_10000_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_99999_swati_10000_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_99999_swati_10000_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.0-lr-1e-05-wd-0.001-dp-0.99999-ss-10000
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_1_0_lr_2e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_1_0_lr_2e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true_en.md
new file mode 100644
index 00000000000000..86d28450bec94f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_1_0_lr_2e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_0_lr_2e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_0_lr_2e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true
+date: 2025-01-25
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_0_lr_2e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_2e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true_en_5.5.1_3.0_1737813949929.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_2e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true_en_5.5.1_3.0_1737813949929.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_0_lr_2e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_0_lr_2e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_0_lr_2e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.0-lr-2e-06-wd-0.001-dp-0.2-ss-0-st-True-fh-True
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_1_0_lr_2e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_1_0_lr_2e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true_pipeline_en.md
new file mode 100644
index 00000000000000..5fe573770d7b1a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_1_0_lr_2e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_0_lr_2e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_0_lr_2e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_0_lr_2e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_2e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true_pipeline_en_5.5.1_3.0_1737813971314.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_2e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true_pipeline_en_5.5.1_3.0_1737813971314.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_0_lr_2e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_0_lr_2e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_0_lr_2e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.0-lr-2e-06-wd-0.001-dp-0.2-ss-0-st-True-fh-True
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_2882_southern_sotho_false_fh_true_hs_666_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_2882_southern_sotho_false_fh_true_hs_666_en.md
new file mode 100644
index 00000000000000..244b4c4fdff760
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_2882_southern_sotho_false_fh_true_hs_666_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_2882_southern_sotho_false_fh_true_hs_666 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_2882_southern_sotho_false_fh_true_hs_666
+date: 2025-01-25
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_2882_southern_sotho_false_fh_true_hs_666` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_2882_southern_sotho_false_fh_true_hs_666_en_5.5.1_3.0_1737814014242.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_2882_southern_sotho_false_fh_true_hs_666_en_5.5.1_3.0_1737814014242.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_2882_southern_sotho_false_fh_true_hs_666","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_2882_southern_sotho_false_fh_true_hs_666", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_2882_southern_sotho_false_fh_true_hs_666|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-2.0-lr-1e-05-wd-0.001-dp-0.2-ss-2882-st-False-fh-True-hs-666
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_2882_southern_sotho_false_fh_true_hs_666_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_2882_southern_sotho_false_fh_true_hs_666_pipeline_en.md
new file mode 100644
index 00000000000000..cb0a3f7b10d91a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_2882_southern_sotho_false_fh_true_hs_666_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_2882_southern_sotho_false_fh_true_hs_666_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_2882_southern_sotho_false_fh_true_hs_666_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_2882_southern_sotho_false_fh_true_hs_666_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_2882_southern_sotho_false_fh_true_hs_666_pipeline_en_5.5.1_3.0_1737814037184.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_2882_southern_sotho_false_fh_true_hs_666_pipeline_en_5.5.1_3.0_1737814037184.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_2882_southern_sotho_false_fh_true_hs_666_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_2882_southern_sotho_false_fh_true_hs_666_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_2_0_lr_1e_05_wd_0_001_dp_0_2_swati_2882_southern_sotho_false_fh_true_hs_666_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-2.0-lr-1e-05-wd-0.001-dp-0.2-ss-2882-st-False-fh-True-hs-666
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true_en.md
new file mode 100644
index 00000000000000..6ee475b5deb91e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true
+date: 2025-01-25
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true_en_5.5.1_3.0_1737813281374.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true_en_5.5.1_3.0_1737813281374.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-2.0-lr-1e-06-wd-0.001-dp-0.2-ss-0-st-True-fh-True
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true_pipeline_en.md
new file mode 100644
index 00000000000000..20b7c79b354423
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true_pipeline_en_5.5.1_3.0_1737813302595.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true_pipeline_en_5.5.1_3.0_1737813302595.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_true_fh_true_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-2.0-lr-1e-06-wd-0.001-dp-0.2-ss-0-st-True-fh-True
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_2_swati_1000_southern_sotho_true_fh_true_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_2_swati_1000_southern_sotho_true_fh_true_en.md
new file mode 100644
index 00000000000000..f2ceb3dd7e4d26
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_2_swati_1000_southern_sotho_true_fh_true_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_2_swati_1000_southern_sotho_true_fh_true BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_2_swati_1000_southern_sotho_true_fh_true
+date: 2025-01-25
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_2_swati_1000_southern_sotho_true_fh_true` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_2_swati_1000_southern_sotho_true_fh_true_en_5.5.1_3.0_1737813773969.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_2_swati_1000_southern_sotho_true_fh_true_en_5.5.1_3.0_1737813773969.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_2_swati_1000_southern_sotho_true_fh_true","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_2_swati_1000_southern_sotho_true_fh_true", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_2_swati_1000_southern_sotho_true_fh_true|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-2.0-lr-1e-06-wd-0.001-dp-0.2-ss-1000-st-True-fh-True
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_2_swati_1000_southern_sotho_true_fh_true_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_2_swati_1000_southern_sotho_true_fh_true_pipeline_en.md
new file mode 100644
index 00000000000000..eedd235f94379e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_2_swati_1000_southern_sotho_true_fh_true_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_2_swati_1000_southern_sotho_true_fh_true_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_2_swati_1000_southern_sotho_true_fh_true_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_2_swati_1000_southern_sotho_true_fh_true_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_2_swati_1000_southern_sotho_true_fh_true_pipeline_en_5.5.1_3.0_1737813795084.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_2_swati_1000_southern_sotho_true_fh_true_pipeline_en_5.5.1_3.0_1737813795084.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_2_swati_1000_southern_sotho_true_fh_true_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_2_swati_1000_southern_sotho_true_fh_true_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_2_0_lr_1e_06_wd_0_001_dp_0_2_swati_1000_southern_sotho_true_fh_true_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-2.0-lr-1e-06-wd-0.001-dp-0.2-ss-1000-st-True-fh-True
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_1_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_1_en.md
new file mode 100644
index 00000000000000..00e1d7f11c3d5b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_1 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_1
+date: 2025-01-25
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_1` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_1_en_5.5.1_3.0_1737813412300.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_1_en_5.5.1_3.0_1737813412300.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_1","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_1", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-2.0-lr-5e-05-wd-0.001-dp-0.1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_1_pipeline_en.md
new file mode 100644
index 00000000000000..ceba610f2e7ed1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_1_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_1_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_1_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_1_pipeline_en_5.5.1_3.0_1737813433580.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_1_pipeline_en_5.5.1_3.0_1737813433580.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-2.0-lr-5e-05-wd-0.001-dp-0.1
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_300_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_300_en.md
new file mode 100644
index 00000000000000..3b607054b37706
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_300_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_300 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_300
+date: 2025-01-25
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_300` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_300_en_5.5.1_3.0_1737813153186.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_300_en_5.5.1_3.0_1737813153186.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_300","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_300", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_300|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-3.0-lr-1e-05-wd-0.001-dp-0.2-ss-0-st-False-fh-False-hs-300
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_300_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_300_pipeline_en.md
new file mode 100644
index 00000000000000..a8a1867d43e4c0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_300_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_300_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_300_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_300_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_300_pipeline_en_5.5.1_3.0_1737813176988.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_300_pipeline_en_5.5.1_3.0_1737813176988.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_300_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_300_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_300_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-3.0-lr-1e-05-wd-0.001-dp-0.2-ss-0-st-False-fh-False-hs-300
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500_en.md
new file mode 100644
index 00000000000000..a53a66f47f681e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500
+date: 2025-01-25
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500_en_5.5.1_3.0_1737813895197.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500_en_5.5.1_3.0_1737813895197.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-3.0-lr-1e-06-wd-0.001-dp-0.2-ss-0-st-False-fh-False-hs-500
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500_pipeline_en.md
new file mode 100644
index 00000000000000..462ccf01c9ca6e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500_pipeline_en_5.5.1_3.0_1737813916987.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500_pipeline_en_5.5.1_3.0_1737813916987.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-3.0-lr-1e-06-wd-0.001-dp-0.2-ss-0-st-False-fh-False-hs-500
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_600_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_600_en.md
new file mode 100644
index 00000000000000..b0f0c4e9a5d63f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_600_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_600 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_600
+date: 2025-01-25
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_600` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_600_en_5.5.1_3.0_1737813250120.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_600_en_5.5.1_3.0_1737813250120.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_600","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_600", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_600|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-4.0-lr-1e-06-wd-0.001-dp-0.2-ss-0-st-False-fh-False-hs-600
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_600_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_600_pipeline_en.md
new file mode 100644
index 00000000000000..8adfbec88af500
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_600_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_600_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_600_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_600_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_600_pipeline_en_5.5.1_3.0_1737813272788.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_600_pipeline_en_5.5.1_3.0_1737813272788.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_600_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_600_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_600_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-4.0-lr-1e-06-wd-0.001-dp-0.2-ss-0-st-False-fh-False-hs-600
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_5_0_lr_1e_05_wd_0_001_dp_0_004_swati_0_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_5_0_lr_1e_05_wd_0_001_dp_0_004_swati_0_en.md
new file mode 100644
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--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_5_0_lr_1e_05_wd_0_001_dp_0_004_swati_0_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_5_0_lr_1e_05_wd_0_001_dp_0_004_swati_0 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_5_0_lr_1e_05_wd_0_001_dp_0_004_swati_0
+date: 2025-01-25
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_5_0_lr_1e_05_wd_0_001_dp_0_004_swati_0` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_5_0_lr_1e_05_wd_0_001_dp_0_004_swati_0_en_5.5.1_3.0_1737813823127.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_5_0_lr_1e_05_wd_0_001_dp_0_004_swati_0_en_5.5.1_3.0_1737813823127.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_5_0_lr_1e_05_wd_0_001_dp_0_004_swati_0","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_5_0_lr_1e_05_wd_0_001_dp_0_004_swati_0", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_5_0_lr_1e_05_wd_0_001_dp_0_004_swati_0|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-5.0-lr-1e-05-wd-0.001-dp-0.004-ss-0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_5_0_lr_1e_05_wd_0_001_dp_0_004_swati_0_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_5_0_lr_1e_05_wd_0_001_dp_0_004_swati_0_pipeline_en.md
new file mode 100644
index 00000000000000..a1a034da5e251f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetune_squad_ep_5_0_lr_1e_05_wd_0_001_dp_0_004_swati_0_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_5_0_lr_1e_05_wd_0_001_dp_0_004_swati_0_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_5_0_lr_1e_05_wd_0_001_dp_0_004_swati_0_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_5_0_lr_1e_05_wd_0_001_dp_0_004_swati_0_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_5_0_lr_1e_05_wd_0_001_dp_0_004_swati_0_pipeline_en_5.5.1_3.0_1737813844137.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_5_0_lr_1e_05_wd_0_001_dp_0_004_swati_0_pipeline_en_5.5.1_3.0_1737813844137.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_5_0_lr_1e_05_wd_0_001_dp_0_004_swati_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_5_0_lr_1e_05_wd_0_001_dp_0_004_swati_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_5_0_lr_1e_05_wd_0_001_dp_0_004_swati_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-5.0-lr-1e-05-wd-0.001-dp-0.004-ss-0
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetuned_fin_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetuned_fin_en.md
new file mode 100644
index 00000000000000..8ed192b0d2a20f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetuned_fin_en.md
@@ -0,0 +1,96 @@
+---
+layout: model
+title: English bert_base_uncased_finetuned_fin BertForSequenceClassification from Venkatesh4342
+author: John Snow Labs
+name: bert_base_uncased_finetuned_fin
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_fin` is a English model originally trained by Venkatesh4342.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_fin_en_5.5.1_3.0_1737821325688.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_fin_en_5.5.1_3.0_1737821325688.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_fin","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_fin", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetuned_fin|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+References
+
+https://huggingface.co/Venkatesh4342/bert-base-uncased-finetuned-fin
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetuned_fin_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetuned_fin_pipeline_en.md
new file mode 100644
index 00000000000000..94a840b8e100d8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetuned_fin_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_uncased_finetuned_fin_pipeline pipeline BertEmbeddings from fhzh123
+author: John Snow Labs
+name: bert_base_uncased_finetuned_fin_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_fin_pipeline` is a English model originally trained by fhzh123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_fin_pipeline_en_5.5.1_3.0_1737821347036.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_fin_pipeline_en_5.5.1_3.0_1737821347036.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetuned_fin_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_fin_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetuned_fin_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/fhzh123/bert-base-uncased-finetuned-fin
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetuned_news_1977_1981_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetuned_news_1977_1981_en.md
new file mode 100644
index 00000000000000..80e0e143b45b55
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetuned_news_1977_1981_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_uncased_finetuned_news_1977_1981 BertEmbeddings from sally9805
+author: John Snow Labs
+name: bert_base_uncased_finetuned_news_1977_1981
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_news_1977_1981` is a English model originally trained by sally9805.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_news_1977_1981_en_5.5.1_3.0_1737785204048.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_news_1977_1981_en_5.5.1_3.0_1737785204048.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_base_uncased_finetuned_news_1977_1981","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_base_uncased_finetuned_news_1977_1981","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetuned_news_1977_1981|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/sally9805/bert-base-uncased-finetuned-news-1977-1981
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetuned_news_1977_1981_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetuned_news_1977_1981_pipeline_en.md
new file mode 100644
index 00000000000000..539d84289a4a1d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_finetuned_news_1977_1981_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_uncased_finetuned_news_1977_1981_pipeline pipeline BertEmbeddings from sally9805
+author: John Snow Labs
+name: bert_base_uncased_finetuned_news_1977_1981_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_news_1977_1981_pipeline` is a English model originally trained by sally9805.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_news_1977_1981_pipeline_en_5.5.1_3.0_1737785225229.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_news_1977_1981_pipeline_en_5.5.1_3.0_1737785225229.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetuned_news_1977_1981_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_news_1977_1981_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetuned_news_1977_1981_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/sally9805/bert-base-uncased-finetuned-news-1977-1981
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_issues_128_athlonxpgzw_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_issues_128_athlonxpgzw_en.md
new file mode 100644
index 00000000000000..1d10ca4258e123
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_issues_128_athlonxpgzw_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_uncased_issues_128_athlonxpgzw BertEmbeddings from athlonxpgzw
+author: John Snow Labs
+name: bert_base_uncased_issues_128_athlonxpgzw
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_issues_128_athlonxpgzw` is a English model originally trained by athlonxpgzw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_issues_128_athlonxpgzw_en_5.5.1_3.0_1737784868825.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_issues_128_athlonxpgzw_en_5.5.1_3.0_1737784868825.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_base_uncased_issues_128_athlonxpgzw","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_base_uncased_issues_128_athlonxpgzw","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_issues_128_athlonxpgzw|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/athlonxpgzw/bert-base-uncased-issues-128
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_issues_128_athlonxpgzw_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_issues_128_athlonxpgzw_pipeline_en.md
new file mode 100644
index 00000000000000..e494066e379159
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_issues_128_athlonxpgzw_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_uncased_issues_128_athlonxpgzw_pipeline pipeline BertEmbeddings from athlonxpgzw
+author: John Snow Labs
+name: bert_base_uncased_issues_128_athlonxpgzw_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_issues_128_athlonxpgzw_pipeline` is a English model originally trained by athlonxpgzw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_issues_128_athlonxpgzw_pipeline_en_5.5.1_3.0_1737784897521.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_issues_128_athlonxpgzw_pipeline_en_5.5.1_3.0_1737784897521.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_issues_128_athlonxpgzw_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_issues_128_athlonxpgzw_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_issues_128_athlonxpgzw_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/athlonxpgzw/bert-base-uncased-issues-128
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_issues_128_feng_2052_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_issues_128_feng_2052_en.md
new file mode 100644
index 00000000000000..dfc99006ce7c75
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_issues_128_feng_2052_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_uncased_issues_128_feng_2052 BertEmbeddings from feng-2052
+author: John Snow Labs
+name: bert_base_uncased_issues_128_feng_2052
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_issues_128_feng_2052` is a English model originally trained by feng-2052.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_issues_128_feng_2052_en_5.5.1_3.0_1737784688526.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_issues_128_feng_2052_en_5.5.1_3.0_1737784688526.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_base_uncased_issues_128_feng_2052","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_base_uncased_issues_128_feng_2052","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_issues_128_feng_2052|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/feng-2052/bert-base-uncased-issues-128
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_issues_128_feng_2052_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_issues_128_feng_2052_pipeline_en.md
new file mode 100644
index 00000000000000..d8218e45cc6ad2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_issues_128_feng_2052_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_uncased_issues_128_feng_2052_pipeline pipeline BertEmbeddings from feng-2052
+author: John Snow Labs
+name: bert_base_uncased_issues_128_feng_2052_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_issues_128_feng_2052_pipeline` is a English model originally trained by feng-2052.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_issues_128_feng_2052_pipeline_en_5.5.1_3.0_1737784713473.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_issues_128_feng_2052_pipeline_en_5.5.1_3.0_1737784713473.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_issues_128_feng_2052_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_issues_128_feng_2052_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_issues_128_feng_2052_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/feng-2052/bert-base-uncased-issues-128
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_issues_128_pradeepiisc_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_issues_128_pradeepiisc_en.md
new file mode 100644
index 00000000000000..a0c137ba2c6bce
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_issues_128_pradeepiisc_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_uncased_issues_128_pradeepiisc BertEmbeddings from pradeepiisc
+author: John Snow Labs
+name: bert_base_uncased_issues_128_pradeepiisc
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_issues_128_pradeepiisc` is a English model originally trained by pradeepiisc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_issues_128_pradeepiisc_en_5.5.1_3.0_1737785518071.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_issues_128_pradeepiisc_en_5.5.1_3.0_1737785518071.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_base_uncased_issues_128_pradeepiisc","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_base_uncased_issues_128_pradeepiisc","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_issues_128_pradeepiisc|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/pradeepiisc/bert-base-uncased-issues-128
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_issues_128_pradeepiisc_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_issues_128_pradeepiisc_pipeline_en.md
new file mode 100644
index 00000000000000..20fa1b4d6af12d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_issues_128_pradeepiisc_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_uncased_issues_128_pradeepiisc_pipeline pipeline BertEmbeddings from pradeepiisc
+author: John Snow Labs
+name: bert_base_uncased_issues_128_pradeepiisc_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_issues_128_pradeepiisc_pipeline` is a English model originally trained by pradeepiisc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_issues_128_pradeepiisc_pipeline_en_5.5.1_3.0_1737785540056.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_issues_128_pradeepiisc_pipeline_en_5.5.1_3.0_1737785540056.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_issues_128_pradeepiisc_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_issues_128_pradeepiisc_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_issues_128_pradeepiisc_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/pradeepiisc/bert-base-uncased-issues-128
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_winowhy_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_winowhy_en.md
new file mode 100644
index 00000000000000..abc57744c7031e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_winowhy_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_winowhy BertForQuestionAnswering from DunnBC22
+author: John Snow Labs
+name: bert_base_uncased_winowhy
+date: 2025-01-25
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_winowhy` is a English model originally trained by DunnBC22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_winowhy_en_5.5.1_3.0_1737814167031.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_winowhy_en_5.5.1_3.0_1737814167031.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_winowhy","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_winowhy", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_winowhy|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/DunnBC22/bert-base-uncased-Winowhy
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_winowhy_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_winowhy_pipeline_en.md
new file mode 100644
index 00000000000000..0cf80798577dba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_base_uncased_winowhy_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_winowhy_pipeline pipeline BertForQuestionAnswering from DunnBC22
+author: John Snow Labs
+name: bert_base_uncased_winowhy_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_winowhy_pipeline` is a English model originally trained by DunnBC22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_winowhy_pipeline_en_5.5.1_3.0_1737814187585.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_winowhy_pipeline_en_5.5.1_3.0_1737814187585.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_winowhy_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_winowhy_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_winowhy_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/DunnBC22/bert-base-uncased-Winowhy
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_chat_moderation_x_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_chat_moderation_x_en.md
new file mode 100644
index 00000000000000..7db73f81f49578
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_chat_moderation_x_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_chat_moderation_x DistilBertForSequenceClassification from andriadze
+author: John Snow Labs
+name: bert_chat_moderation_x
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_chat_moderation_x` is a English model originally trained by andriadze.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_chat_moderation_x_en_5.5.1_3.0_1737822062013.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_chat_moderation_x_en_5.5.1_3.0_1737822062013.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("bert_chat_moderation_x","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("bert_chat_moderation_x", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_chat_moderation_x|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/andriadze/bert-chat-moderation-X
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_chat_moderation_x_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_chat_moderation_x_pipeline_en.md
new file mode 100644
index 00000000000000..a1116d55dc08f7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_chat_moderation_x_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_chat_moderation_x_pipeline pipeline DistilBertForSequenceClassification from andriadze
+author: John Snow Labs
+name: bert_chat_moderation_x_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_chat_moderation_x_pipeline` is a English model originally trained by andriadze.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_chat_moderation_x_pipeline_en_5.5.1_3.0_1737822077102.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_chat_moderation_x_pipeline_en_5.5.1_3.0_1737822077102.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_chat_moderation_x_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_chat_moderation_x_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_chat_moderation_x_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/andriadze/bert-chat-moderation-X
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_english_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_english_en.md
new file mode 100644
index 00000000000000..831055a4e27bd6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_english_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_english BertEmbeddings from lzhang472
+author: John Snow Labs
+name: bert_english
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_english` is a English model originally trained by lzhang472.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_english_en_5.5.1_3.0_1737807042292.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_english_en_5.5.1_3.0_1737807042292.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_english","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_english","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_english|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|406.5 MB|
+
+## References
+
+https://huggingface.co/lzhang472/bert-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_english_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_english_pipeline_en.md
new file mode 100644
index 00000000000000..42843da9c48b8e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_english_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_english_pipeline pipeline BertEmbeddings from lzhang472
+author: John Snow Labs
+name: bert_english_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_english_pipeline` is a English model originally trained by lzhang472.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_english_pipeline_en_5.5.1_3.0_1737807064116.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_english_pipeline_en_5.5.1_3.0_1737807064116.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_english_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_english_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_english_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.5 MB|
+
+## References
+
+https://huggingface.co/lzhang472/bert-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_10_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_10_en.md
new file mode 100644
index 00000000000000..88f72d15cd320f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_10_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_finetuned_ner_10 BertForTokenClassification from jdavit
+author: John Snow Labs
+name: bert_finetuned_ner_10
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_10` is a English model originally trained by jdavit.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_10_en_5.5.1_3.0_1737845063371.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_10_en_5.5.1_3.0_1737845063371.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_finetuned_ner_10","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner_10", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_10|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/jdavit/bert-finetuned-ner-10
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_10_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_10_pipeline_en.md
new file mode 100644
index 00000000000000..6d1bec80849508
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_10_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_finetuned_ner_10_pipeline pipeline BertForTokenClassification from jdavit
+author: John Snow Labs
+name: bert_finetuned_ner_10_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_10_pipeline` is a English model originally trained by jdavit.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_10_pipeline_en_5.5.1_3.0_1737845085161.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_10_pipeline_en_5.5.1_3.0_1737845085161.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_ner_10_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_ner_10_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_10_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/jdavit/bert-finetuned-ner-10
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_12_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_12_en.md
new file mode 100644
index 00000000000000..c578185083538e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_12_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_finetuned_ner_12 BertForTokenClassification from jdavit
+author: John Snow Labs
+name: bert_finetuned_ner_12
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_12` is a English model originally trained by jdavit.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_12_en_5.5.1_3.0_1737844673202.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_12_en_5.5.1_3.0_1737844673202.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_finetuned_ner_12","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner_12", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_12|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/jdavit/bert-finetuned-ner-12
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_12_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_12_pipeline_en.md
new file mode 100644
index 00000000000000..1d2c6f2005100f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_12_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_finetuned_ner_12_pipeline pipeline BertForTokenClassification from jdavit
+author: John Snow Labs
+name: bert_finetuned_ner_12_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_12_pipeline` is a English model originally trained by jdavit.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_12_pipeline_en_5.5.1_3.0_1737844693151.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_12_pipeline_en_5.5.1_3.0_1737844693151.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_ner_12_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_ner_12_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_12_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/jdavit/bert-finetuned-ner-12
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_17_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_17_en.md
new file mode 100644
index 00000000000000..ea7e25e1dce5cf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_17_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_finetuned_ner_17 BertForTokenClassification from jdavit
+author: John Snow Labs
+name: bert_finetuned_ner_17
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_17` is a English model originally trained by jdavit.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_17_en_5.5.1_3.0_1737843913903.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_17_en_5.5.1_3.0_1737843913903.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_finetuned_ner_17","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner_17", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_17|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/jdavit/bert-finetuned-ner-17
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_17_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_17_pipeline_en.md
new file mode 100644
index 00000000000000..a6d3b8763728b9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_17_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_finetuned_ner_17_pipeline pipeline BertForTokenClassification from jdavit
+author: John Snow Labs
+name: bert_finetuned_ner_17_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_17_pipeline` is a English model originally trained by jdavit.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_17_pipeline_en_5.5.1_3.0_1737843942915.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_17_pipeline_en_5.5.1_3.0_1737843942915.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_ner_17_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_ner_17_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_17_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/jdavit/bert-finetuned-ner-17
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_1_willilamvel_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_1_willilamvel_en.md
new file mode 100644
index 00000000000000..e7b018cb62bafa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_1_willilamvel_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_finetuned_ner_1_willilamvel BertForTokenClassification from Willilamvel
+author: John Snow Labs
+name: bert_finetuned_ner_1_willilamvel
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_1_willilamvel` is a English model originally trained by Willilamvel.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_1_willilamvel_en_5.5.1_3.0_1737844292898.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_1_willilamvel_en_5.5.1_3.0_1737844292898.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_finetuned_ner_1_willilamvel","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner_1_willilamvel", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_1_willilamvel|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/Willilamvel/bert-finetuned-ner-1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_1_willilamvel_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_1_willilamvel_pipeline_en.md
new file mode 100644
index 00000000000000..e8677ab6ece44f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_1_willilamvel_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_finetuned_ner_1_willilamvel_pipeline pipeline BertForTokenClassification from Willilamvel
+author: John Snow Labs
+name: bert_finetuned_ner_1_willilamvel_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_1_willilamvel_pipeline` is a English model originally trained by Willilamvel.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_1_willilamvel_pipeline_en_5.5.1_3.0_1737844313336.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_1_willilamvel_pipeline_en_5.5.1_3.0_1737844313336.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_ner_1_willilamvel_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_ner_1_willilamvel_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_1_willilamvel_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/Willilamvel/bert-finetuned-ner-1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_20_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_20_en.md
new file mode 100644
index 00000000000000..8c9bb6205379e8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_20_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_finetuned_ner_20 BertForTokenClassification from jdavit
+author: John Snow Labs
+name: bert_finetuned_ner_20
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_20` is a English model originally trained by jdavit.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_20_en_5.5.1_3.0_1737843913791.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_20_en_5.5.1_3.0_1737843913791.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_finetuned_ner_20","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner_20", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_20|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/jdavit/bert-finetuned-ner-20
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_20_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_20_pipeline_en.md
new file mode 100644
index 00000000000000..3a723e71901a65
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_20_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_finetuned_ner_20_pipeline pipeline BertForTokenClassification from jdavit
+author: John Snow Labs
+name: bert_finetuned_ner_20_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_20_pipeline` is a English model originally trained by jdavit.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_20_pipeline_en_5.5.1_3.0_1737843942965.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_20_pipeline_en_5.5.1_3.0_1737843942965.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_ner_20_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_ner_20_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_20_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/jdavit/bert-finetuned-ner-20
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_aniruddh10124_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_aniruddh10124_en.md
new file mode 100644
index 00000000000000..e25a9f4c6d6e11
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_aniruddh10124_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_finetuned_ner_aniruddh10124 BertForTokenClassification from aniruddh10124
+author: John Snow Labs
+name: bert_finetuned_ner_aniruddh10124
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_aniruddh10124` is a English model originally trained by aniruddh10124.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_aniruddh10124_en_5.5.1_3.0_1737844572264.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_aniruddh10124_en_5.5.1_3.0_1737844572264.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_finetuned_ner_aniruddh10124","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner_aniruddh10124", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_aniruddh10124|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/aniruddh10124/bert-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_aniruddh10124_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_aniruddh10124_pipeline_en.md
new file mode 100644
index 00000000000000..8a16108ac49142
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_aniruddh10124_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_finetuned_ner_aniruddh10124_pipeline pipeline BertForTokenClassification from aniruddh10124
+author: John Snow Labs
+name: bert_finetuned_ner_aniruddh10124_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_aniruddh10124_pipeline` is a English model originally trained by aniruddh10124.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_aniruddh10124_pipeline_en_5.5.1_3.0_1737844592254.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_aniruddh10124_pipeline_en_5.5.1_3.0_1737844592254.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_ner_aniruddh10124_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_ner_aniruddh10124_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_aniruddh10124_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/aniruddh10124/bert-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_ashed00_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_ashed00_en.md
new file mode 100644
index 00000000000000..137a4fb88fba75
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_ashed00_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_finetuned_ner_ashed00 BertForTokenClassification from Ashed00
+author: John Snow Labs
+name: bert_finetuned_ner_ashed00
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_ashed00` is a English model originally trained by Ashed00.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_ashed00_en_5.5.1_3.0_1737834864068.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_ashed00_en_5.5.1_3.0_1737834864068.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_finetuned_ner_ashed00","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner_ashed00", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_ashed00|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/Ashed00/bert-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_ashed00_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_ashed00_pipeline_en.md
new file mode 100644
index 00000000000000..d63f459525ec21
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_ashed00_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_finetuned_ner_ashed00_pipeline pipeline BertForTokenClassification from Ashed00
+author: John Snow Labs
+name: bert_finetuned_ner_ashed00_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_ashed00_pipeline` is a English model originally trained by Ashed00.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_ashed00_pipeline_en_5.5.1_3.0_1737834884598.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_ashed00_pipeline_en_5.5.1_3.0_1737834884598.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_ner_ashed00_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_ner_ashed00_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_ashed00_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/Ashed00/bert-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_brianchu26_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_brianchu26_en.md
new file mode 100644
index 00000000000000..0be764ea297d5c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_brianchu26_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_finetuned_ner_brianchu26 BertForTokenClassification from brianchu26
+author: John Snow Labs
+name: bert_finetuned_ner_brianchu26
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_brianchu26` is a English model originally trained by brianchu26.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_brianchu26_en_5.5.1_3.0_1737844416916.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_brianchu26_en_5.5.1_3.0_1737844416916.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_finetuned_ner_brianchu26","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner_brianchu26", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_brianchu26|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/brianchu26/bert-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_brianchu26_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_brianchu26_pipeline_en.md
new file mode 100644
index 00000000000000..a37eca91428ab4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_brianchu26_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_finetuned_ner_brianchu26_pipeline pipeline BertForTokenClassification from brianchu26
+author: John Snow Labs
+name: bert_finetuned_ner_brianchu26_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_brianchu26_pipeline` is a English model originally trained by brianchu26.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_brianchu26_pipeline_en_5.5.1_3.0_1737844436921.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_brianchu26_pipeline_en_5.5.1_3.0_1737844436921.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_ner_brianchu26_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_ner_brianchu26_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_brianchu26_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/brianchu26/bert-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_chasche_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_chasche_en.md
new file mode 100644
index 00000000000000..95590241754703
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_chasche_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_finetuned_ner_chasche BertForTokenClassification from chasche
+author: John Snow Labs
+name: bert_finetuned_ner_chasche
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_chasche` is a English model originally trained by chasche.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_chasche_en_5.5.1_3.0_1737835670313.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_chasche_en_5.5.1_3.0_1737835670313.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_finetuned_ner_chasche","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner_chasche", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_chasche|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/chasche/bert-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_chasche_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_chasche_pipeline_en.md
new file mode 100644
index 00000000000000..498b8274bd8e52
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_chasche_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_finetuned_ner_chasche_pipeline pipeline BertForTokenClassification from chasche
+author: John Snow Labs
+name: bert_finetuned_ner_chasche_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_chasche_pipeline` is a English model originally trained by chasche.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_chasche_pipeline_en_5.5.1_3.0_1737835690216.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_chasche_pipeline_en_5.5.1_3.0_1737835690216.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_ner_chasche_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_ner_chasche_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_chasche_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/chasche/bert-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_daga2001_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_daga2001_en.md
new file mode 100644
index 00000000000000..e024e14e75d5b1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_daga2001_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_finetuned_ner_daga2001 BertForTokenClassification from Daga2001
+author: John Snow Labs
+name: bert_finetuned_ner_daga2001
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_daga2001` is a English model originally trained by Daga2001.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_daga2001_en_5.5.1_3.0_1737835031330.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_daga2001_en_5.5.1_3.0_1737835031330.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_finetuned_ner_daga2001","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner_daga2001", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_daga2001|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/Daga2001/bert-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_daga2001_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_daga2001_pipeline_en.md
new file mode 100644
index 00000000000000..6e86eb123cee72
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_daga2001_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_finetuned_ner_daga2001_pipeline pipeline BertForTokenClassification from Daga2001
+author: John Snow Labs
+name: bert_finetuned_ner_daga2001_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_daga2001_pipeline` is a English model originally trained by Daga2001.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_daga2001_pipeline_en_5.5.1_3.0_1737835051926.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_daga2001_pipeline_en_5.5.1_3.0_1737835051926.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_ner_daga2001_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_ner_daga2001_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_daga2001_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/Daga2001/bert-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_for_deployment_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_for_deployment_en.md
new file mode 100644
index 00000000000000..70c5abac4489a9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_for_deployment_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_finetuned_ner_for_deployment BertForTokenClassification from Nirmal-re
+author: John Snow Labs
+name: bert_finetuned_ner_for_deployment
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_for_deployment` is a English model originally trained by Nirmal-re.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_for_deployment_en_5.5.1_3.0_1737835240813.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_for_deployment_en_5.5.1_3.0_1737835240813.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_finetuned_ner_for_deployment","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner_for_deployment", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_for_deployment|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/Nirmal-re/bert-finetuned-ner-for-deployment
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_for_deployment_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_for_deployment_pipeline_en.md
new file mode 100644
index 00000000000000..accce25dec0a11
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_for_deployment_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_finetuned_ner_for_deployment_pipeline pipeline BertForTokenClassification from Nirmal-re
+author: John Snow Labs
+name: bert_finetuned_ner_for_deployment_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_for_deployment_pipeline` is a English model originally trained by Nirmal-re.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_for_deployment_pipeline_en_5.5.1_3.0_1737835262014.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_for_deployment_pipeline_en_5.5.1_3.0_1737835262014.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_ner_for_deployment_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_ner_for_deployment_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_for_deployment_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/Nirmal-re/bert-finetuned-ner-for-deployment
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_hzsss_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_hzsss_en.md
new file mode 100644
index 00000000000000..8ef56dfadd42fd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_hzsss_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_finetuned_ner_hzsss BertForTokenClassification from hzSSS
+author: John Snow Labs
+name: bert_finetuned_ner_hzsss
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_hzsss` is a English model originally trained by hzSSS.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_hzsss_en_5.5.1_3.0_1737844265704.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_hzsss_en_5.5.1_3.0_1737844265704.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_finetuned_ner_hzsss","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner_hzsss", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_hzsss|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/hzSSS/bert-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_hzsss_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_hzsss_pipeline_en.md
new file mode 100644
index 00000000000000..95ef6ad0c0ef17
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_hzsss_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_finetuned_ner_hzsss_pipeline pipeline BertForTokenClassification from hzSSS
+author: John Snow Labs
+name: bert_finetuned_ner_hzsss_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_hzsss_pipeline` is a English model originally trained by hzSSS.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_hzsss_pipeline_en_5.5.1_3.0_1737844289783.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_hzsss_pipeline_en_5.5.1_3.0_1737844289783.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_ner_hzsss_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_ner_hzsss_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_hzsss_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/hzSSS/bert-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_jasonwenhuan_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_jasonwenhuan_en.md
new file mode 100644
index 00000000000000..a2f2762b920459
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_jasonwenhuan_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_finetuned_ner_jasonwenhuan BertForTokenClassification from jasonwenhuan
+author: John Snow Labs
+name: bert_finetuned_ner_jasonwenhuan
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_jasonwenhuan` is a English model originally trained by jasonwenhuan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_jasonwenhuan_en_5.5.1_3.0_1737834876231.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_jasonwenhuan_en_5.5.1_3.0_1737834876231.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_finetuned_ner_jasonwenhuan","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner_jasonwenhuan", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_jasonwenhuan|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/jasonwenhuan/bert-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_jasonwenhuan_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_jasonwenhuan_pipeline_en.md
new file mode 100644
index 00000000000000..a699a2d871c0be
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_jasonwenhuan_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_finetuned_ner_jasonwenhuan_pipeline pipeline BertForTokenClassification from jasonwenhuan
+author: John Snow Labs
+name: bert_finetuned_ner_jasonwenhuan_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_jasonwenhuan_pipeline` is a English model originally trained by jasonwenhuan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_jasonwenhuan_pipeline_en_5.5.1_3.0_1737834903178.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_jasonwenhuan_pipeline_en_5.5.1_3.0_1737834903178.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_ner_jasonwenhuan_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_ner_jasonwenhuan_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_jasonwenhuan_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/jasonwenhuan/bert-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_pascaly_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_pascaly_en.md
new file mode 100644
index 00000000000000..77edb44f950c3b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_pascaly_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_finetuned_ner_pascaly BertForTokenClassification from PascalY
+author: John Snow Labs
+name: bert_finetuned_ner_pascaly
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_pascaly` is a English model originally trained by PascalY.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_pascaly_en_5.5.1_3.0_1737844350263.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_pascaly_en_5.5.1_3.0_1737844350263.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_finetuned_ner_pascaly","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner_pascaly", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_pascaly|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/PascalY/bert-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_pascaly_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_pascaly_pipeline_en.md
new file mode 100644
index 00000000000000..84a4a3287eba23
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_pascaly_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_finetuned_ner_pascaly_pipeline pipeline BertForTokenClassification from PascalY
+author: John Snow Labs
+name: bert_finetuned_ner_pascaly_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_pascaly_pipeline` is a English model originally trained by PascalY.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_pascaly_pipeline_en_5.5.1_3.0_1737844370961.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_pascaly_pipeline_en_5.5.1_3.0_1737844370961.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_ner_pascaly_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_ner_pascaly_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_pascaly_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/PascalY/bert-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_sapana1234_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_sapana1234_en.md
new file mode 100644
index 00000000000000..165efb97610489
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_sapana1234_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_finetuned_ner_sapana1234 BertForTokenClassification from sapana1234
+author: John Snow Labs
+name: bert_finetuned_ner_sapana1234
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_sapana1234` is a English model originally trained by sapana1234.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_sapana1234_en_5.5.1_3.0_1737844972392.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_sapana1234_en_5.5.1_3.0_1737844972392.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_finetuned_ner_sapana1234","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner_sapana1234", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_sapana1234|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/sapana1234/bert-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_sapana1234_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_sapana1234_pipeline_en.md
new file mode 100644
index 00000000000000..66b86229862d98
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_sapana1234_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_finetuned_ner_sapana1234_pipeline pipeline BertForTokenClassification from sapana1234
+author: John Snow Labs
+name: bert_finetuned_ner_sapana1234_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_sapana1234_pipeline` is a English model originally trained by sapana1234.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_sapana1234_pipeline_en_5.5.1_3.0_1737844992803.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_sapana1234_pipeline_en_5.5.1_3.0_1737844992803.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_ner_sapana1234_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_ner_sapana1234_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_sapana1234_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/sapana1234/bert-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_toyohama_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_toyohama_en.md
new file mode 100644
index 00000000000000..a374a8c49377f0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_toyohama_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_finetuned_ner_toyohama BertForTokenClassification from toyohama
+author: John Snow Labs
+name: bert_finetuned_ner_toyohama
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_toyohama` is a English model originally trained by toyohama.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_toyohama_en_5.5.1_3.0_1737844507661.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_toyohama_en_5.5.1_3.0_1737844507661.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_finetuned_ner_toyohama","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner_toyohama", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_toyohama|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/toyohama/bert-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_toyohama_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_toyohama_pipeline_en.md
new file mode 100644
index 00000000000000..e7cf43da05ce77
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_toyohama_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_finetuned_ner_toyohama_pipeline pipeline BertForTokenClassification from toyohama
+author: John Snow Labs
+name: bert_finetuned_ner_toyohama_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_toyohama_pipeline` is a English model originally trained by toyohama.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_toyohama_pipeline_en_5.5.1_3.0_1737844528209.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_toyohama_pipeline_en_5.5.1_3.0_1737844528209.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_ner_toyohama_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_ner_toyohama_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_toyohama_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/toyohama/bert-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_victoriacolmenares_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_victoriacolmenares_en.md
new file mode 100644
index 00000000000000..4bb03ab13698cf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_victoriacolmenares_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_finetuned_ner_victoriacolmenares BertForTokenClassification from victoriacolmenares
+author: John Snow Labs
+name: bert_finetuned_ner_victoriacolmenares
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_victoriacolmenares` is a English model originally trained by victoriacolmenares.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_victoriacolmenares_en_5.5.1_3.0_1737844246252.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_victoriacolmenares_en_5.5.1_3.0_1737844246252.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_finetuned_ner_victoriacolmenares","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner_victoriacolmenares", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_victoriacolmenares|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/victoriacolmenares/bert-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_victoriacolmenares_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_victoriacolmenares_pipeline_en.md
new file mode 100644
index 00000000000000..95013e00312127
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_victoriacolmenares_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_finetuned_ner_victoriacolmenares_pipeline pipeline BertForTokenClassification from victoriacolmenares
+author: John Snow Labs
+name: bert_finetuned_ner_victoriacolmenares_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_victoriacolmenares_pipeline` is a English model originally trained by victoriacolmenares.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_victoriacolmenares_pipeline_en_5.5.1_3.0_1737844266497.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_victoriacolmenares_pipeline_en_5.5.1_3.0_1737844266497.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_ner_victoriacolmenares_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_ner_victoriacolmenares_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_victoriacolmenares_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/victoriacolmenares/bert-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_waystar_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_waystar_en.md
new file mode 100644
index 00000000000000..5cb1cf2600f1e9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_waystar_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_finetuned_ner_waystar BertForTokenClassification from WAYSTAR
+author: John Snow Labs
+name: bert_finetuned_ner_waystar
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_waystar` is a English model originally trained by WAYSTAR.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_waystar_en_5.5.1_3.0_1737844805822.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_waystar_en_5.5.1_3.0_1737844805822.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_finetuned_ner_waystar","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner_waystar", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_waystar|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/WAYSTAR/bert-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_waystar_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_waystar_pipeline_en.md
new file mode 100644
index 00000000000000..7a623a7078258c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_ner_waystar_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_finetuned_ner_waystar_pipeline pipeline BertForTokenClassification from WAYSTAR
+author: John Snow Labs
+name: bert_finetuned_ner_waystar_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_waystar_pipeline` is a English model originally trained by WAYSTAR.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_waystar_pipeline_en_5.5.1_3.0_1737844826316.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_waystar_pipeline_en_5.5.1_3.0_1737844826316.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_ner_waystar_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_ner_waystar_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_waystar_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/WAYSTAR/bert-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_squad_abelvs_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_squad_abelvs_en.md
new file mode 100644
index 00000000000000..3eb8b206f2b010
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_squad_abelvs_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_finetuned_squad_abelvs BertForQuestionAnswering from abelvs
+author: John Snow Labs
+name: bert_finetuned_squad_abelvs
+date: 2025-01-25
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_abelvs` is a English model originally trained by abelvs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_abelvs_en_5.5.1_3.0_1737813285362.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_abelvs_en_5.5.1_3.0_1737813285362.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_abelvs","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_abelvs", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_abelvs|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/abelvs/bert-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_squad_abelvs_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_squad_abelvs_pipeline_en.md
new file mode 100644
index 00000000000000..d0873b38f4973b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_squad_abelvs_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_finetuned_squad_abelvs_pipeline pipeline BertForQuestionAnswering from abelvs
+author: John Snow Labs
+name: bert_finetuned_squad_abelvs_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_abelvs_pipeline` is a English model originally trained by abelvs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_abelvs_pipeline_en_5.5.1_3.0_1737813306803.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_abelvs_pipeline_en_5.5.1_3.0_1737813306803.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_squad_abelvs_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_squad_abelvs_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_abelvs_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/abelvs/bert-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_squad_alicexiaolin_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_squad_alicexiaolin_en.md
new file mode 100644
index 00000000000000..3b7e540abe47c7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_squad_alicexiaolin_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_finetuned_squad_alicexiaolin BertForQuestionAnswering from Alicexiaolin
+author: John Snow Labs
+name: bert_finetuned_squad_alicexiaolin
+date: 2025-01-25
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_alicexiaolin` is a English model originally trained by Alicexiaolin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_alicexiaolin_en_5.5.1_3.0_1737813580970.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_alicexiaolin_en_5.5.1_3.0_1737813580970.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_alicexiaolin","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_alicexiaolin", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_alicexiaolin|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/Alicexiaolin/bert-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_squad_alicexiaolin_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_squad_alicexiaolin_pipeline_en.md
new file mode 100644
index 00000000000000..1c9d4dba7e31b4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_squad_alicexiaolin_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_finetuned_squad_alicexiaolin_pipeline pipeline BertForQuestionAnswering from Alicexiaolin
+author: John Snow Labs
+name: bert_finetuned_squad_alicexiaolin_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_alicexiaolin_pipeline` is a English model originally trained by Alicexiaolin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_alicexiaolin_pipeline_en_5.5.1_3.0_1737813601955.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_alicexiaolin_pipeline_en_5.5.1_3.0_1737813601955.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_squad_alicexiaolin_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_squad_alicexiaolin_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_alicexiaolin_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/Alicexiaolin/bert-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_squad_alynakbaba_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_squad_alynakbaba_en.md
new file mode 100644
index 00000000000000..8100431d29413d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_squad_alynakbaba_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_finetuned_squad_alynakbaba BertForQuestionAnswering from alynakbaba
+author: John Snow Labs
+name: bert_finetuned_squad_alynakbaba
+date: 2025-01-25
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_alynakbaba` is a English model originally trained by alynakbaba.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_alynakbaba_en_5.5.1_3.0_1737813523610.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_alynakbaba_en_5.5.1_3.0_1737813523610.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_alynakbaba","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_alynakbaba", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_alynakbaba|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/alynakbaba/bert-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_squad_alynakbaba_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_squad_alynakbaba_pipeline_en.md
new file mode 100644
index 00000000000000..e780e04bf570ab
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_finetuned_squad_alynakbaba_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_finetuned_squad_alynakbaba_pipeline pipeline BertForQuestionAnswering from alynakbaba
+author: John Snow Labs
+name: bert_finetuned_squad_alynakbaba_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_alynakbaba_pipeline` is a English model originally trained by alynakbaba.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_alynakbaba_pipeline_en_5.5.1_3.0_1737813550116.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_alynakbaba_pipeline_en_5.5.1_3.0_1737813550116.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_squad_alynakbaba_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_squad_alynakbaba_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_alynakbaba_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/alynakbaba/bert-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_gest_pred_seqeval_partialmatch_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_gest_pred_seqeval_partialmatch_en.md
new file mode 100644
index 00000000000000..efb0ca37cfbeb8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_gest_pred_seqeval_partialmatch_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_gest_pred_seqeval_partialmatch BertForTokenClassification from Jsevisal
+author: John Snow Labs
+name: bert_gest_pred_seqeval_partialmatch
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_gest_pred_seqeval_partialmatch` is a English model originally trained by Jsevisal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_gest_pred_seqeval_partialmatch_en_5.5.1_3.0_1737844920223.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_gest_pred_seqeval_partialmatch_en_5.5.1_3.0_1737844920223.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_gest_pred_seqeval_partialmatch","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_gest_pred_seqeval_partialmatch", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_gest_pred_seqeval_partialmatch|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.8 MB|
+
+## References
+
+https://huggingface.co/Jsevisal/bert-gest-pred-seqeval-partialmatch
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_gest_pred_seqeval_partialmatch_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_gest_pred_seqeval_partialmatch_pipeline_en.md
new file mode 100644
index 00000000000000..d31a726c3a396e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_gest_pred_seqeval_partialmatch_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_gest_pred_seqeval_partialmatch_pipeline pipeline BertForTokenClassification from Jsevisal
+author: John Snow Labs
+name: bert_gest_pred_seqeval_partialmatch_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_gest_pred_seqeval_partialmatch_pipeline` is a English model originally trained by Jsevisal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_gest_pred_seqeval_partialmatch_pipeline_en_5.5.1_3.0_1737844940681.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_gest_pred_seqeval_partialmatch_pipeline_en_5.5.1_3.0_1737844940681.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_gest_pred_seqeval_partialmatch_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_gest_pred_seqeval_partialmatch_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_gest_pred_seqeval_partialmatch_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.8 MB|
+
+## References
+
+https://huggingface.co/Jsevisal/bert-gest-pred-seqeval-partialmatch
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_job_german_extended_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_job_german_extended_en.md
new file mode 100644
index 00000000000000..a3456aae01d963
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_job_german_extended_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_job_german_extended BertEmbeddings from dathi103
+author: John Snow Labs
+name: bert_job_german_extended
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_job_german_extended` is a English model originally trained by dathi103.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_job_german_extended_en_5.5.1_3.0_1737846298836.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_job_german_extended_en_5.5.1_3.0_1737846298836.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_job_german_extended","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_job_german_extended","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_job_german_extended|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|418.3 MB|
+
+## References
+
+https://huggingface.co/dathi103/bert-job-german-extended
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_job_german_extended_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_job_german_extended_pipeline_en.md
new file mode 100644
index 00000000000000..6d3fab0ba2a8b0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_job_german_extended_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_job_german_extended_pipeline pipeline BertEmbeddings from dathi103
+author: John Snow Labs
+name: bert_job_german_extended_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_job_german_extended_pipeline` is a English model originally trained by dathi103.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_job_german_extended_pipeline_en_5.5.1_3.0_1737846319396.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_job_german_extended_pipeline_en_5.5.1_3.0_1737846319396.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_job_german_extended_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_job_german_extended_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_job_german_extended_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|418.3 MB|
+
+## References
+
+https://huggingface.co/dathi103/bert-job-german-extended
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_journal_classifier_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_journal_classifier_en.md
new file mode 100644
index 00000000000000..deb6a411ecc77e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_journal_classifier_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_journal_classifier BertForSequenceClassification from amalsalilanhuggingface
+author: John Snow Labs
+name: bert_journal_classifier
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_journal_classifier` is a English model originally trained by amalsalilanhuggingface.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_journal_classifier_en_5.5.1_3.0_1737801022980.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_journal_classifier_en_5.5.1_3.0_1737801022980.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("bert_journal_classifier","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("bert_journal_classifier", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_journal_classifier|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/amalsalilanhuggingface/bert-journal-classifier
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_journal_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_journal_classifier_pipeline_en.md
new file mode 100644
index 00000000000000..f1926527d399ce
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_journal_classifier_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_journal_classifier_pipeline pipeline BertForSequenceClassification from amalsalilanhuggingface
+author: John Snow Labs
+name: bert_journal_classifier_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_journal_classifier_pipeline` is a English model originally trained by amalsalilanhuggingface.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_journal_classifier_pipeline_en_5.5.1_3.0_1737801044604.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_journal_classifier_pipeline_en_5.5.1_3.0_1737801044604.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_journal_classifier_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_journal_classifier_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_journal_classifier_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/amalsalilanhuggingface/bert-journal-classifier
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_l2_h768_uncased_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_l2_h768_uncased_en.md
new file mode 100644
index 00000000000000..0225113f57efa6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_l2_h768_uncased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_l2_h768_uncased BertEmbeddings from gaunernst
+author: John Snow Labs
+name: bert_l2_h768_uncased
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_l2_h768_uncased` is a English model originally trained by gaunernst.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_l2_h768_uncased_en_5.5.1_3.0_1737846197173.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_l2_h768_uncased_en_5.5.1_3.0_1737846197173.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_l2_h768_uncased","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_l2_h768_uncased","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_l2_h768_uncased|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|141.9 MB|
+
+## References
+
+https://huggingface.co/gaunernst/bert-L2-H768-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_l2_h768_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_l2_h768_uncased_pipeline_en.md
new file mode 100644
index 00000000000000..4a1911b3ce903d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_l2_h768_uncased_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_l2_h768_uncased_pipeline pipeline BertEmbeddings from gaunernst
+author: John Snow Labs
+name: bert_l2_h768_uncased_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_l2_h768_uncased_pipeline` is a English model originally trained by gaunernst.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_l2_h768_uncased_pipeline_en_5.5.1_3.0_1737846204122.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_l2_h768_uncased_pipeline_en_5.5.1_3.0_1737846204122.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_l2_h768_uncased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_l2_h768_uncased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_l2_h768_uncased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|141.9 MB|
+
+## References
+
+https://huggingface.co/gaunernst/bert-L2-H768-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_large_cased_whole_word_masking_finetuned_squad_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_large_cased_whole_word_masking_finetuned_squad_en.md
new file mode 100644
index 00000000000000..8d991ac240db70
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_large_cased_whole_word_masking_finetuned_squad_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_large_cased_whole_word_masking_finetuned_squad BertForQuestionAnswering from Arup-Dutta-Bappy
+author: John Snow Labs
+name: bert_large_cased_whole_word_masking_finetuned_squad
+date: 2025-01-25
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_cased_whole_word_masking_finetuned_squad` is a English model originally trained by Arup-Dutta-Bappy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_cased_whole_word_masking_finetuned_squad_en_5.5.1_3.0_1737813456465.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_cased_whole_word_masking_finetuned_squad_en_5.5.1_3.0_1737813456465.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_large_cased_whole_word_masking_finetuned_squad","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_large_cased_whole_word_masking_finetuned_squad", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_large_cased_whole_word_masking_finetuned_squad|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/Arup-Dutta-Bappy/bert-large-cased-whole-word-masking-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_large_cased_whole_word_masking_finetuned_squad_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_large_cased_whole_word_masking_finetuned_squad_pipeline_en.md
new file mode 100644
index 00000000000000..7fc24ec9c0dca9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_large_cased_whole_word_masking_finetuned_squad_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_large_cased_whole_word_masking_finetuned_squad_pipeline pipeline BertForQuestionAnswering from Arup-Dutta-Bappy
+author: John Snow Labs
+name: bert_large_cased_whole_word_masking_finetuned_squad_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_cased_whole_word_masking_finetuned_squad_pipeline` is a English model originally trained by Arup-Dutta-Bappy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_cased_whole_word_masking_finetuned_squad_pipeline_en_5.5.1_3.0_1737813520795.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_cased_whole_word_masking_finetuned_squad_pipeline_en_5.5.1_3.0_1737813520795.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_large_cased_whole_word_masking_finetuned_squad_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_large_cased_whole_word_masking_finetuned_squad_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_large_cased_whole_word_masking_finetuned_squad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/Arup-Dutta-Bappy/bert-large-cased-whole-word-masking-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_large_mnr_mlm_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_large_mnr_mlm_en.md
new file mode 100644
index 00000000000000..091ef39129cf74
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_large_mnr_mlm_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_large_mnr_mlm BertEmbeddings from omarelsayeed
+author: John Snow Labs
+name: bert_large_mnr_mlm
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_mnr_mlm` is a English model originally trained by omarelsayeed.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_mnr_mlm_en_5.5.1_3.0_1737785616668.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_mnr_mlm_en_5.5.1_3.0_1737785616668.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_large_mnr_mlm","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_large_mnr_mlm","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_large_mnr_mlm|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|1.4 GB|
+
+## References
+
+https://huggingface.co/omarelsayeed/bert_large_mnr_mlm
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_large_mnr_mlm_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_large_mnr_mlm_pipeline_en.md
new file mode 100644
index 00000000000000..8a054d46a204a1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_large_mnr_mlm_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_large_mnr_mlm_pipeline pipeline BertEmbeddings from omarelsayeed
+author: John Snow Labs
+name: bert_large_mnr_mlm_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_mnr_mlm_pipeline` is a English model originally trained by omarelsayeed.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_mnr_mlm_pipeline_en_5.5.1_3.0_1737785691763.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_mnr_mlm_pipeline_en_5.5.1_3.0_1737785691763.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_large_mnr_mlm_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_large_mnr_mlm_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_large_mnr_mlm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.4 GB|
+
+## References
+
+https://huggingface.co/omarelsayeed/bert_large_mnr_mlm
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_model_chaligula_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_model_chaligula_en.md
new file mode 100644
index 00000000000000..2c465b0a354991
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_model_chaligula_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_model_chaligula BertForSequenceClassification from Chaligula
+author: John Snow Labs
+name: bert_model_chaligula
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_model_chaligula` is a English model originally trained by Chaligula.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_model_chaligula_en_5.5.1_3.0_1737801009822.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_model_chaligula_en_5.5.1_3.0_1737801009822.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("bert_model_chaligula","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("bert_model_chaligula", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_model_chaligula|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/Chaligula/BERT-Model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_model_chaligula_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_model_chaligula_pipeline_en.md
new file mode 100644
index 00000000000000..a403af6306f9fb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_model_chaligula_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_model_chaligula_pipeline pipeline BertForSequenceClassification from Chaligula
+author: John Snow Labs
+name: bert_model_chaligula_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_model_chaligula_pipeline` is a English model originally trained by Chaligula.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_model_chaligula_pipeline_en_5.5.1_3.0_1737801033234.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_model_chaligula_pipeline_en_5.5.1_3.0_1737801033234.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_model_chaligula_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_model_chaligula_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_model_chaligula_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/Chaligula/BERT-Model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_multi_base_uncased_finetuned_sayula_popoluca_kyrgyz_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_multi_base_uncased_finetuned_sayula_popoluca_kyrgyz_en.md
new file mode 100644
index 00000000000000..7391c780dca57e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_multi_base_uncased_finetuned_sayula_popoluca_kyrgyz_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_multi_base_uncased_finetuned_sayula_popoluca_kyrgyz BertForTokenClassification from Justice0893
+author: John Snow Labs
+name: bert_multi_base_uncased_finetuned_sayula_popoluca_kyrgyz
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_multi_base_uncased_finetuned_sayula_popoluca_kyrgyz` is a English model originally trained by Justice0893.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_multi_base_uncased_finetuned_sayula_popoluca_kyrgyz_en_5.5.1_3.0_1737834873728.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_multi_base_uncased_finetuned_sayula_popoluca_kyrgyz_en_5.5.1_3.0_1737834873728.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_multi_base_uncased_finetuned_sayula_popoluca_kyrgyz","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_multi_base_uncased_finetuned_sayula_popoluca_kyrgyz", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_multi_base_uncased_finetuned_sayula_popoluca_kyrgyz|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|625.6 MB|
+
+## References
+
+https://huggingface.co/Justice0893/bert-multi-base-uncased-finetuned-pos-ky
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_multi_base_uncased_finetuned_sayula_popoluca_kyrgyz_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_multi_base_uncased_finetuned_sayula_popoluca_kyrgyz_pipeline_en.md
new file mode 100644
index 00000000000000..7c60bbac1d75c9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_multi_base_uncased_finetuned_sayula_popoluca_kyrgyz_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_multi_base_uncased_finetuned_sayula_popoluca_kyrgyz_pipeline pipeline BertForTokenClassification from Justice0893
+author: John Snow Labs
+name: bert_multi_base_uncased_finetuned_sayula_popoluca_kyrgyz_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_multi_base_uncased_finetuned_sayula_popoluca_kyrgyz_pipeline` is a English model originally trained by Justice0893.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_multi_base_uncased_finetuned_sayula_popoluca_kyrgyz_pipeline_en_5.5.1_3.0_1737834911862.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_multi_base_uncased_finetuned_sayula_popoluca_kyrgyz_pipeline_en_5.5.1_3.0_1737834911862.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_multi_base_uncased_finetuned_sayula_popoluca_kyrgyz_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_multi_base_uncased_finetuned_sayula_popoluca_kyrgyz_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_multi_base_uncased_finetuned_sayula_popoluca_kyrgyz_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|625.6 MB|
+
+## References
+
+https://huggingface.co/Justice0893/bert-multi-base-uncased-finetuned-pos-ky
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_multi_uncased_finetuned_sayula_popoluca_turkish_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_multi_uncased_finetuned_sayula_popoluca_turkish_en.md
new file mode 100644
index 00000000000000..c6b6ec2daa93a9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_multi_uncased_finetuned_sayula_popoluca_turkish_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_multi_uncased_finetuned_sayula_popoluca_turkish BertForTokenClassification from Justice0893
+author: John Snow Labs
+name: bert_multi_uncased_finetuned_sayula_popoluca_turkish
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_multi_uncased_finetuned_sayula_popoluca_turkish` is a English model originally trained by Justice0893.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_multi_uncased_finetuned_sayula_popoluca_turkish_en_5.5.1_3.0_1737844807109.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_multi_uncased_finetuned_sayula_popoluca_turkish_en_5.5.1_3.0_1737844807109.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_multi_uncased_finetuned_sayula_popoluca_turkish","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_multi_uncased_finetuned_sayula_popoluca_turkish", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_multi_uncased_finetuned_sayula_popoluca_turkish|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|625.6 MB|
+
+## References
+
+https://huggingface.co/Justice0893/bert_multi-uncased-finetuned-pos-tr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_multi_uncased_finetuned_sayula_popoluca_turkish_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_multi_uncased_finetuned_sayula_popoluca_turkish_pipeline_en.md
new file mode 100644
index 00000000000000..7379ef22bdc145
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_multi_uncased_finetuned_sayula_popoluca_turkish_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_multi_uncased_finetuned_sayula_popoluca_turkish_pipeline pipeline BertForTokenClassification from Justice0893
+author: John Snow Labs
+name: bert_multi_uncased_finetuned_sayula_popoluca_turkish_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_multi_uncased_finetuned_sayula_popoluca_turkish_pipeline` is a English model originally trained by Justice0893.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_multi_uncased_finetuned_sayula_popoluca_turkish_pipeline_en_5.5.1_3.0_1737844839359.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_multi_uncased_finetuned_sayula_popoluca_turkish_pipeline_en_5.5.1_3.0_1737844839359.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_multi_uncased_finetuned_sayula_popoluca_turkish_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_multi_uncased_finetuned_sayula_popoluca_turkish_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_multi_uncased_finetuned_sayula_popoluca_turkish_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|625.6 MB|
+
+## References
+
+https://huggingface.co/Justice0893/bert_multi-uncased-finetuned-pos-tr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_pretrained_litcov10k_paraphrased_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_pretrained_litcov10k_paraphrased_en.md
new file mode 100644
index 00000000000000..457682bd11e567
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_pretrained_litcov10k_paraphrased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_pretrained_litcov10k_paraphrased BertEmbeddings from IneG
+author: John Snow Labs
+name: bert_pretrained_litcov10k_paraphrased
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_pretrained_litcov10k_paraphrased` is a English model originally trained by IneG.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_pretrained_litcov10k_paraphrased_en_5.5.1_3.0_1737806827919.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_pretrained_litcov10k_paraphrased_en_5.5.1_3.0_1737806827919.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_pretrained_litcov10k_paraphrased","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_pretrained_litcov10k_paraphrased","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_pretrained_litcov10k_paraphrased|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/IneG/BERT_pretrained_litcov10K_paraphrased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_pretrained_litcov10k_paraphrased_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_pretrained_litcov10k_paraphrased_pipeline_en.md
new file mode 100644
index 00000000000000..a4998378d4e20d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_pretrained_litcov10k_paraphrased_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_pretrained_litcov10k_paraphrased_pipeline pipeline BertEmbeddings from IneG
+author: John Snow Labs
+name: bert_pretrained_litcov10k_paraphrased_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_pretrained_litcov10k_paraphrased_pipeline` is a English model originally trained by IneG.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_pretrained_litcov10k_paraphrased_pipeline_en_5.5.1_3.0_1737806849063.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_pretrained_litcov10k_paraphrased_pipeline_en_5.5.1_3.0_1737806849063.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_pretrained_litcov10k_paraphrased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_pretrained_litcov10k_paraphrased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_pretrained_litcov10k_paraphrased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/IneG/BERT_pretrained_litcov10K_paraphrased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_qa_vidarn_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_qa_vidarn_en.md
new file mode 100644
index 00000000000000..670ef7c1f2a075
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_qa_vidarn_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_qa_vidarn BertForQuestionAnswering from vidarn
+author: John Snow Labs
+name: bert_qa_vidarn
+date: 2025-01-25
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_qa_vidarn` is a English model originally trained by vidarn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_vidarn_en_5.5.1_3.0_1737813190760.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_vidarn_en_5.5.1_3.0_1737813190760.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_vidarn","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_vidarn", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_vidarn|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|606.5 MB|
+
+## References
+
+https://huggingface.co/vidarn/bert-qa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_qa_vidarn_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_qa_vidarn_pipeline_en.md
new file mode 100644
index 00000000000000..5a0e7bd4777622
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_qa_vidarn_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_qa_vidarn_pipeline pipeline BertForQuestionAnswering from vidarn
+author: John Snow Labs
+name: bert_qa_vidarn_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_qa_vidarn_pipeline` is a English model originally trained by vidarn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_vidarn_pipeline_en_5.5.1_3.0_1737813222795.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_vidarn_pipeline_en_5.5.1_3.0_1737813222795.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_qa_vidarn_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_qa_vidarn_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_vidarn_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|606.5 MB|
+
+## References
+
+https://huggingface.co/vidarn/bert-qa
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_squad_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_squad_en.md
new file mode 100644
index 00000000000000..6688dc9b5b499f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_squad_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_squad BertForQuestionAnswering from Sadat07
+author: John Snow Labs
+name: bert_squad
+date: 2025-01-25
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_squad` is a English model originally trained by Sadat07.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_squad_en_5.5.1_3.0_1737813153678.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_squad_en_5.5.1_3.0_1737813153678.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_squad","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_squad", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_squad|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/Sadat07/bert-SQuAD
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_squad_finetuned_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_squad_finetuned_en.md
new file mode 100644
index 00000000000000..fa97fb0afac917
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_squad_finetuned_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_squad_finetuned DistilBertForQuestionAnswering from Salmamoori
+author: John Snow Labs
+name: bert_squad_finetuned
+date: 2025-01-25
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_squad_finetuned` is a English model originally trained by Salmamoori.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_squad_finetuned_en_5.5.1_3.0_1737823839431.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_squad_finetuned_en_5.5.1_3.0_1737823839431.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("bert_squad_finetuned","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("bert_squad_finetuned", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_squad_finetuned|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Salmamoori/BERT-SQuAD-finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_squad_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_squad_finetuned_pipeline_en.md
new file mode 100644
index 00000000000000..bfc333527049d3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_squad_finetuned_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_squad_finetuned_pipeline pipeline DistilBertForQuestionAnswering from Salmamoori
+author: John Snow Labs
+name: bert_squad_finetuned_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_squad_finetuned_pipeline` is a English model originally trained by Salmamoori.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_squad_finetuned_pipeline_en_5.5.1_3.0_1737823852697.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_squad_finetuned_pipeline_en_5.5.1_3.0_1737823852697.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_squad_finetuned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_squad_finetuned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_squad_finetuned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Salmamoori/BERT-SQuAD-finetuned
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_squad_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_squad_pipeline_en.md
new file mode 100644
index 00000000000000..d3f4141ff3c474
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_squad_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_squad_pipeline pipeline BertForQuestionAnswering from Sadat07
+author: John Snow Labs
+name: bert_squad_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_squad_pipeline` is a English model originally trained by Sadat07.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_squad_pipeline_en_5.5.1_3.0_1737813178746.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_squad_pipeline_en_5.5.1_3.0_1737813178746.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_squad_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_squad_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_squad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/Sadat07/bert-SQuAD
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_test_orangecheers_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_test_orangecheers_en.md
new file mode 100644
index 00000000000000..43d275bfd9d4d8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_test_orangecheers_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_test_orangecheers BertForSequenceClassification from OrangeCheers
+author: John Snow Labs
+name: bert_test_orangecheers
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_test_orangecheers` is a English model originally trained by OrangeCheers.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_test_orangecheers_en_5.5.1_3.0_1737840128613.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_test_orangecheers_en_5.5.1_3.0_1737840128613.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("bert_test_orangecheers","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("bert_test_orangecheers", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_test_orangecheers|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/OrangeCheers/bert_test
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_test_orangecheers_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_test_orangecheers_pipeline_en.md
new file mode 100644
index 00000000000000..bae6cd857502a8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_test_orangecheers_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_test_orangecheers_pipeline pipeline BertForSequenceClassification from OrangeCheers
+author: John Snow Labs
+name: bert_test_orangecheers_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_test_orangecheers_pipeline` is a English model originally trained by OrangeCheers.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_test_orangecheers_pipeline_en_5.5.1_3.0_1737840187709.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_test_orangecheers_pipeline_en_5.5.1_3.0_1737840187709.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_test_orangecheers_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_test_orangecheers_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_test_orangecheers_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/OrangeCheers/bert_test
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_tiny_lda_100_v1_book_mrpc_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_tiny_lda_100_v1_book_mrpc_en.md
new file mode 100644
index 00000000000000..f2740742a47e83
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_tiny_lda_100_v1_book_mrpc_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_tiny_lda_100_v1_book_mrpc DistilBertForSequenceClassification from gokulsrinivasagan
+author: John Snow Labs
+name: bert_tiny_lda_100_v1_book_mrpc
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_tiny_lda_100_v1_book_mrpc` is a English model originally trained by gokulsrinivasagan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_tiny_lda_100_v1_book_mrpc_en_5.5.1_3.0_1737838510952.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_tiny_lda_100_v1_book_mrpc_en_5.5.1_3.0_1737838510952.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("bert_tiny_lda_100_v1_book_mrpc","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("bert_tiny_lda_100_v1_book_mrpc", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_tiny_lda_100_v1_book_mrpc|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|123.7 MB|
+
+## References
+
+https://huggingface.co/gokulsrinivasagan/bert_tiny_lda_100_v1_book_mrpc
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_tiny_lda_100_v1_book_mrpc_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_tiny_lda_100_v1_book_mrpc_pipeline_en.md
new file mode 100644
index 00000000000000..772627619bb646
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_tiny_lda_100_v1_book_mrpc_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_tiny_lda_100_v1_book_mrpc_pipeline pipeline DistilBertForSequenceClassification from gokulsrinivasagan
+author: John Snow Labs
+name: bert_tiny_lda_100_v1_book_mrpc_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_tiny_lda_100_v1_book_mrpc_pipeline` is a English model originally trained by gokulsrinivasagan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_tiny_lda_100_v1_book_mrpc_pipeline_en_5.5.1_3.0_1737838519529.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_tiny_lda_100_v1_book_mrpc_pipeline_en_5.5.1_3.0_1737838519529.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_tiny_lda_100_v1_book_mrpc_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_tiny_lda_100_v1_book_mrpc_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_tiny_lda_100_v1_book_mrpc_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|123.7 MB|
+
+## References
+
+https://huggingface.co/gokulsrinivasagan/bert_tiny_lda_100_v1_book_mrpc
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_tiny_lda_100_v1_sst2_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_tiny_lda_100_v1_sst2_en.md
new file mode 100644
index 00000000000000..167bad03d2f675
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_tiny_lda_100_v1_sst2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_tiny_lda_100_v1_sst2 DistilBertForSequenceClassification from gokulsrinivasagan
+author: John Snow Labs
+name: bert_tiny_lda_100_v1_sst2
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_tiny_lda_100_v1_sst2` is a English model originally trained by gokulsrinivasagan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_tiny_lda_100_v1_sst2_en_5.5.1_3.0_1737838357263.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_tiny_lda_100_v1_sst2_en_5.5.1_3.0_1737838357263.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("bert_tiny_lda_100_v1_sst2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("bert_tiny_lda_100_v1_sst2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_tiny_lda_100_v1_sst2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|123.9 MB|
+
+## References
+
+https://huggingface.co/gokulsrinivasagan/bert_tiny_lda_100_v1_sst2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_tiny_lda_100_v1_sst2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_tiny_lda_100_v1_sst2_pipeline_en.md
new file mode 100644
index 00000000000000..10f6b9dfa0eed2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_tiny_lda_100_v1_sst2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_tiny_lda_100_v1_sst2_pipeline pipeline DistilBertForSequenceClassification from gokulsrinivasagan
+author: John Snow Labs
+name: bert_tiny_lda_100_v1_sst2_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_tiny_lda_100_v1_sst2_pipeline` is a English model originally trained by gokulsrinivasagan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_tiny_lda_100_v1_sst2_pipeline_en_5.5.1_3.0_1737838363327.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_tiny_lda_100_v1_sst2_pipeline_en_5.5.1_3.0_1737838363327.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_tiny_lda_100_v1_sst2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_tiny_lda_100_v1_sst2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_tiny_lda_100_v1_sst2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|123.9 MB|
+
+## References
+
+https://huggingface.co/gokulsrinivasagan/bert_tiny_lda_100_v1_sst2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_tiny_lda_qnli_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_tiny_lda_qnli_en.md
new file mode 100644
index 00000000000000..b6d2a238f51394
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_tiny_lda_qnli_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_tiny_lda_qnli DistilBertForSequenceClassification from gokulsrinivasagan
+author: John Snow Labs
+name: bert_tiny_lda_qnli
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_tiny_lda_qnli` is a English model originally trained by gokulsrinivasagan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_tiny_lda_qnli_en_5.5.1_3.0_1737836565748.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_tiny_lda_qnli_en_5.5.1_3.0_1737836565748.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("bert_tiny_lda_qnli","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("bert_tiny_lda_qnli", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_tiny_lda_qnli|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|123.9 MB|
+
+## References
+
+https://huggingface.co/gokulsrinivasagan/bert_tiny_lda_qnli
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_tiny_lda_qnli_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_tiny_lda_qnli_pipeline_en.md
new file mode 100644
index 00000000000000..ad228622cc361e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_tiny_lda_qnli_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_tiny_lda_qnli_pipeline pipeline DistilBertForSequenceClassification from gokulsrinivasagan
+author: John Snow Labs
+name: bert_tiny_lda_qnli_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_tiny_lda_qnli_pipeline` is a English model originally trained by gokulsrinivasagan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_tiny_lda_qnli_pipeline_en_5.5.1_3.0_1737836571899.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_tiny_lda_qnli_pipeline_en_5.5.1_3.0_1737836571899.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_tiny_lda_qnli_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_tiny_lda_qnli_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_tiny_lda_qnli_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|123.9 MB|
+
+## References
+
+https://huggingface.co/gokulsrinivasagan/bert_tiny_lda_qnli
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_tsonga_wordpiece_phonetic_wikitext_0_1_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_tsonga_wordpiece_phonetic_wikitext_0_1_en.md
new file mode 100644
index 00000000000000..96ba71f9865384
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_tsonga_wordpiece_phonetic_wikitext_0_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_tsonga_wordpiece_phonetic_wikitext_0_1 BertEmbeddings from psktoure
+author: John Snow Labs
+name: bert_tsonga_wordpiece_phonetic_wikitext_0_1
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_tsonga_wordpiece_phonetic_wikitext_0_1` is a English model originally trained by psktoure.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_tsonga_wordpiece_phonetic_wikitext_0_1_en_5.5.1_3.0_1737784842732.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_tsonga_wordpiece_phonetic_wikitext_0_1_en_5.5.1_3.0_1737784842732.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_tsonga_wordpiece_phonetic_wikitext_0_1","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_tsonga_wordpiece_phonetic_wikitext_0_1","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_tsonga_wordpiece_phonetic_wikitext_0_1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|408.0 MB|
+
+## References
+
+https://huggingface.co/psktoure/BERT_TS_WordPiece_phonetic_wikitext_0.1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_tsonga_wordpiece_phonetic_wikitext_0_1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_tsonga_wordpiece_phonetic_wikitext_0_1_pipeline_en.md
new file mode 100644
index 00000000000000..e3afef6eb5a237
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_tsonga_wordpiece_phonetic_wikitext_0_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_tsonga_wordpiece_phonetic_wikitext_0_1_pipeline pipeline BertEmbeddings from psktoure
+author: John Snow Labs
+name: bert_tsonga_wordpiece_phonetic_wikitext_0_1_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_tsonga_wordpiece_phonetic_wikitext_0_1_pipeline` is a English model originally trained by psktoure.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_tsonga_wordpiece_phonetic_wikitext_0_1_pipeline_en_5.5.1_3.0_1737784864064.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_tsonga_wordpiece_phonetic_wikitext_0_1_pipeline_en_5.5.1_3.0_1737784864064.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_tsonga_wordpiece_phonetic_wikitext_0_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_tsonga_wordpiece_phonetic_wikitext_0_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_tsonga_wordpiece_phonetic_wikitext_0_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|408.1 MB|
+
+## References
+
+https://huggingface.co/psktoure/BERT_TS_WordPiece_phonetic_wikitext_0.1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_tsonga_wordpiece_phonetic_wikitext_0_9_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_tsonga_wordpiece_phonetic_wikitext_0_9_en.md
new file mode 100644
index 00000000000000..52de267ae59347
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_tsonga_wordpiece_phonetic_wikitext_0_9_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_tsonga_wordpiece_phonetic_wikitext_0_9 BertEmbeddings from psktoure
+author: John Snow Labs
+name: bert_tsonga_wordpiece_phonetic_wikitext_0_9
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_tsonga_wordpiece_phonetic_wikitext_0_9` is a English model originally trained by psktoure.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_tsonga_wordpiece_phonetic_wikitext_0_9_en_5.5.1_3.0_1737785630934.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_tsonga_wordpiece_phonetic_wikitext_0_9_en_5.5.1_3.0_1737785630934.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_tsonga_wordpiece_phonetic_wikitext_0_9","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_tsonga_wordpiece_phonetic_wikitext_0_9","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_tsonga_wordpiece_phonetic_wikitext_0_9|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|408.4 MB|
+
+## References
+
+https://huggingface.co/psktoure/BERT_TS_WordPiece_phonetic_wikitext_0.9
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_tsonga_wordpiece_phonetic_wikitext_0_9_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_tsonga_wordpiece_phonetic_wikitext_0_9_pipeline_en.md
new file mode 100644
index 00000000000000..b8ff067e393a43
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_tsonga_wordpiece_phonetic_wikitext_0_9_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_tsonga_wordpiece_phonetic_wikitext_0_9_pipeline pipeline BertEmbeddings from psktoure
+author: John Snow Labs
+name: bert_tsonga_wordpiece_phonetic_wikitext_0_9_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_tsonga_wordpiece_phonetic_wikitext_0_9_pipeline` is a English model originally trained by psktoure.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_tsonga_wordpiece_phonetic_wikitext_0_9_pipeline_en_5.5.1_3.0_1737785654996.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_tsonga_wordpiece_phonetic_wikitext_0_9_pipeline_en_5.5.1_3.0_1737785654996.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_tsonga_wordpiece_phonetic_wikitext_0_9_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_tsonga_wordpiece_phonetic_wikitext_0_9_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_tsonga_wordpiece_phonetic_wikitext_0_9_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|408.4 MB|
+
+## References
+
+https://huggingface.co/psktoure/BERT_TS_WordPiece_phonetic_wikitext_0.9
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_wordpiece_wikitext_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_wordpiece_wikitext_en.md
new file mode 100644
index 00000000000000..d5106fad83645e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_wordpiece_wikitext_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_wordpiece_wikitext BertEmbeddings from psktoure
+author: John Snow Labs
+name: bert_wordpiece_wikitext
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_wordpiece_wikitext` is a English model originally trained by psktoure.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_wordpiece_wikitext_en_5.5.1_3.0_1737806676754.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_wordpiece_wikitext_en_5.5.1_3.0_1737806676754.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_wordpiece_wikitext","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_wordpiece_wikitext","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_wordpiece_wikitext|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|408.1 MB|
+
+## References
+
+https://huggingface.co/psktoure/BERT_WordPiece_wikitext
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bert_wordpiece_wikitext_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bert_wordpiece_wikitext_pipeline_en.md
new file mode 100644
index 00000000000000..f1ed5d3f329d42
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bert_wordpiece_wikitext_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_wordpiece_wikitext_pipeline pipeline BertEmbeddings from psktoure
+author: John Snow Labs
+name: bert_wordpiece_wikitext_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_wordpiece_wikitext_pipeline` is a English model originally trained by psktoure.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_wordpiece_wikitext_pipeline_en_5.5.1_3.0_1737806698234.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_wordpiece_wikitext_pipeline_en_5.5.1_3.0_1737806698234.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_wordpiece_wikitext_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_wordpiece_wikitext_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_wordpiece_wikitext_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|408.1 MB|
+
+## References
+
+https://huggingface.co/psktoure/BERT_WordPiece_wikitext
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-berth5_en.md b/docs/_posts/ahmedlone127/2025-01-25-berth5_en.md
new file mode 100644
index 00000000000000..85d099315463a1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-berth5_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English berth5 BertEmbeddings from JeloH
+author: John Snow Labs
+name: berth5
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`berth5` is a English model originally trained by JeloH.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/berth5_en_5.5.1_3.0_1737821187223.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/berth5_en_5.5.1_3.0_1737821187223.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("berth5","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("berth5","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|berth5|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/JeloH/BertH5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-berth5_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-berth5_pipeline_en.md
new file mode 100644
index 00000000000000..5c8a29689820d1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-berth5_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English berth5_pipeline pipeline BertEmbeddings from JeloH
+author: John Snow Labs
+name: berth5_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`berth5_pipeline` is a English model originally trained by JeloH.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/berth5_pipeline_en_5.5.1_3.0_1737821209635.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/berth5_pipeline_en_5.5.1_3.0_1737821209635.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("berth5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("berth5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|berth5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/JeloH/BertH5
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bertmodel_petrichoro7_en.md b/docs/_posts/ahmedlone127/2025-01-25-bertmodel_petrichoro7_en.md
new file mode 100644
index 00000000000000..2450ec423bd80e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bertmodel_petrichoro7_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bertmodel_petrichoro7 BertForQuestionAnswering from petrichoro7
+author: John Snow Labs
+name: bertmodel_petrichoro7
+date: 2025-01-25
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bertmodel_petrichoro7` is a English model originally trained by petrichoro7.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bertmodel_petrichoro7_en_5.5.1_3.0_1737813647419.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bertmodel_petrichoro7_en_5.5.1_3.0_1737813647419.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bertmodel_petrichoro7","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bertmodel_petrichoro7", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bertmodel_petrichoro7|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/petrichoro7/BERTModel
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bertmodel_petrichoro7_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bertmodel_petrichoro7_pipeline_en.md
new file mode 100644
index 00000000000000..8a077e3c668f5c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bertmodel_petrichoro7_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bertmodel_petrichoro7_pipeline pipeline BertForQuestionAnswering from petrichoro7
+author: John Snow Labs
+name: bertmodel_petrichoro7_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bertmodel_petrichoro7_pipeline` is a English model originally trained by petrichoro7.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bertmodel_petrichoro7_pipeline_en_5.5.1_3.0_1737813668595.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bertmodel_petrichoro7_pipeline_en_5.5.1_3.0_1737813668595.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bertmodel_petrichoro7_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bertmodel_petrichoro7_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bertmodel_petrichoro7_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/petrichoro7/BERTModel
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-berto_los_muchachos_1_matomaral_en.md b/docs/_posts/ahmedlone127/2025-01-25-berto_los_muchachos_1_matomaral_en.md
new file mode 100644
index 00000000000000..e589d35152dd00
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-berto_los_muchachos_1_matomaral_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English berto_los_muchachos_1_matomaral BertForTokenClassification from MatoMaral
+author: John Snow Labs
+name: berto_los_muchachos_1_matomaral
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`berto_los_muchachos_1_matomaral` is a English model originally trained by MatoMaral.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/berto_los_muchachos_1_matomaral_en_5.5.1_3.0_1737845040081.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/berto_los_muchachos_1_matomaral_en_5.5.1_3.0_1737845040081.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("berto_los_muchachos_1_matomaral","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("berto_los_muchachos_1_matomaral", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|berto_los_muchachos_1_matomaral|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|409.6 MB|
+
+## References
+
+https://huggingface.co/MatoMaral/BERTO-LOS-MUCHACHOS-1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-berto_los_muchachos_1_matomaral_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-berto_los_muchachos_1_matomaral_pipeline_en.md
new file mode 100644
index 00000000000000..2dff0313658872
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-berto_los_muchachos_1_matomaral_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English berto_los_muchachos_1_matomaral_pipeline pipeline BertForTokenClassification from MatoMaral
+author: John Snow Labs
+name: berto_los_muchachos_1_matomaral_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`berto_los_muchachos_1_matomaral_pipeline` is a English model originally trained by MatoMaral.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/berto_los_muchachos_1_matomaral_pipeline_en_5.5.1_3.0_1737845060846.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/berto_los_muchachos_1_matomaral_pipeline_en_5.5.1_3.0_1737845060846.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("berto_los_muchachos_1_matomaral_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("berto_los_muchachos_1_matomaral_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|berto_los_muchachos_1_matomaral_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.6 MB|
+
+## References
+
+https://huggingface.co/MatoMaral/BERTO-LOS-MUCHACHOS-1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-beto_finetuned_ner_22_en.md b/docs/_posts/ahmedlone127/2025-01-25-beto_finetuned_ner_22_en.md
new file mode 100644
index 00000000000000..0a31f19bd5fcf4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-beto_finetuned_ner_22_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English beto_finetuned_ner_22 BertForTokenClassification from saos200
+author: John Snow Labs
+name: beto_finetuned_ner_22
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`beto_finetuned_ner_22` is a English model originally trained by saos200.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/beto_finetuned_ner_22_en_5.5.1_3.0_1737835532635.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/beto_finetuned_ner_22_en_5.5.1_3.0_1737835532635.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("beto_finetuned_ner_22","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("beto_finetuned_ner_22", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|beto_finetuned_ner_22|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|409.5 MB|
+
+## References
+
+https://huggingface.co/saos200/BETO-finetuned-ner-22
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-beto_finetuned_ner_22_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-beto_finetuned_ner_22_pipeline_en.md
new file mode 100644
index 00000000000000..0b12ca7ec17be3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-beto_finetuned_ner_22_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English beto_finetuned_ner_22_pipeline pipeline BertForTokenClassification from saos200
+author: John Snow Labs
+name: beto_finetuned_ner_22_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`beto_finetuned_ner_22_pipeline` is a English model originally trained by saos200.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/beto_finetuned_ner_22_pipeline_en_5.5.1_3.0_1737835553392.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/beto_finetuned_ner_22_pipeline_en_5.5.1_3.0_1737835553392.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("beto_finetuned_ner_22_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("beto_finetuned_ner_22_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|beto_finetuned_ner_22_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.5 MB|
+
+## References
+
+https://huggingface.co/saos200/BETO-finetuned-ner-22
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bge_base_custom_matryoshka_en.md b/docs/_posts/ahmedlone127/2025-01-25-bge_base_custom_matryoshka_en.md
new file mode 100644
index 00000000000000..c625842747b13d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bge_base_custom_matryoshka_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_base_custom_matryoshka BGEEmbeddings from mahsaBa76
+author: John Snow Labs
+name: bge_base_custom_matryoshka
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_custom_matryoshka` is a English model originally trained by mahsaBa76.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_custom_matryoshka_en_5.5.1_3.0_1737783968099.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_custom_matryoshka_en_5.5.1_3.0_1737783968099.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_base_custom_matryoshka","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_base_custom_matryoshka","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_custom_matryoshka|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|382.6 MB|
+
+## References
+
+https://huggingface.co/mahsaBa76/bge-base-custom-matryoshka
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bge_base_custom_matryoshka_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bge_base_custom_matryoshka_pipeline_en.md
new file mode 100644
index 00000000000000..cb11407bb19e41
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bge_base_custom_matryoshka_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_base_custom_matryoshka_pipeline pipeline BGEEmbeddings from mahsaBa76
+author: John Snow Labs
+name: bge_base_custom_matryoshka_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_custom_matryoshka_pipeline` is a English model originally trained by mahsaBa76.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_custom_matryoshka_pipeline_en_5.5.1_3.0_1737784001307.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_custom_matryoshka_pipeline_en_5.5.1_3.0_1737784001307.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_base_custom_matryoshka_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_base_custom_matryoshka_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_custom_matryoshka_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|382.6 MB|
+
+## References
+
+https://huggingface.co/mahsaBa76/bge-base-custom-matryoshka
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bge_base_english_v1_5_course_recommender_v5_en.md b/docs/_posts/ahmedlone127/2025-01-25-bge_base_english_v1_5_course_recommender_v5_en.md
new file mode 100644
index 00000000000000..7a0a4afa3ceaf4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bge_base_english_v1_5_course_recommender_v5_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_base_english_v1_5_course_recommender_v5 BGEEmbeddings from datasocietyco
+author: John Snow Labs
+name: bge_base_english_v1_5_course_recommender_v5
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_english_v1_5_course_recommender_v5` is a English model originally trained by datasocietyco.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_course_recommender_v5_en_5.5.1_3.0_1737784110789.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_course_recommender_v5_en_5.5.1_3.0_1737784110789.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_base_english_v1_5_course_recommender_v5","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_base_english_v1_5_course_recommender_v5","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_english_v1_5_course_recommender_v5|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|375.7 MB|
+
+## References
+
+https://huggingface.co/datasocietyco/bge-base-en-v1.5-course-recommender-v5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bge_base_english_v1_5_course_recommender_v5_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bge_base_english_v1_5_course_recommender_v5_pipeline_en.md
new file mode 100644
index 00000000000000..9460e0ad466d57
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bge_base_english_v1_5_course_recommender_v5_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_base_english_v1_5_course_recommender_v5_pipeline pipeline BGEEmbeddings from datasocietyco
+author: John Snow Labs
+name: bge_base_english_v1_5_course_recommender_v5_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_english_v1_5_course_recommender_v5_pipeline` is a English model originally trained by datasocietyco.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_course_recommender_v5_pipeline_en_5.5.1_3.0_1737784143244.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_course_recommender_v5_pipeline_en_5.5.1_3.0_1737784143244.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_base_english_v1_5_course_recommender_v5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_base_english_v1_5_course_recommender_v5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_english_v1_5_course_recommender_v5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|375.7 MB|
+
+## References
+
+https://huggingface.co/datasocietyco/bge-base-en-v1.5-course-recommender-v5
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bge_base_english_v1_5_finetuned_en.md b/docs/_posts/ahmedlone127/2025-01-25-bge_base_english_v1_5_finetuned_en.md
new file mode 100644
index 00000000000000..28dc2a4da30228
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bge_base_english_v1_5_finetuned_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_base_english_v1_5_finetuned BGEEmbeddings from rezarahim
+author: John Snow Labs
+name: bge_base_english_v1_5_finetuned
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_english_v1_5_finetuned` is a English model originally trained by rezarahim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_finetuned_en_5.5.1_3.0_1737783824299.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_finetuned_en_5.5.1_3.0_1737783824299.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_base_english_v1_5_finetuned","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_base_english_v1_5_finetuned","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_english_v1_5_finetuned|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|377.6 MB|
+
+## References
+
+https://huggingface.co/rezarahim/bge-base-en-v1.5-finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bge_base_english_v1_5_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bge_base_english_v1_5_finetuned_pipeline_en.md
new file mode 100644
index 00000000000000..7b540f3f50ea6a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bge_base_english_v1_5_finetuned_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_base_english_v1_5_finetuned_pipeline pipeline BGEEmbeddings from rezarahim
+author: John Snow Labs
+name: bge_base_english_v1_5_finetuned_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_english_v1_5_finetuned_pipeline` is a English model originally trained by rezarahim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_finetuned_pipeline_en_5.5.1_3.0_1737783861213.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_finetuned_pipeline_en_5.5.1_3.0_1737783861213.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_base_english_v1_5_finetuned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_base_english_v1_5_finetuned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_english_v1_5_finetuned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|377.6 MB|
+
+## References
+
+https://huggingface.co/rezarahim/bge-base-en-v1.5-finetuned
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bge_base_financial_matryoshka_fe2x_en.md b/docs/_posts/ahmedlone127/2025-01-25-bge_base_financial_matryoshka_fe2x_en.md
new file mode 100644
index 00000000000000..c338fa20175504
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bge_base_financial_matryoshka_fe2x_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_base_financial_matryoshka_fe2x BGEEmbeddings from Fe2x
+author: John Snow Labs
+name: bge_base_financial_matryoshka_fe2x
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_fe2x` is a English model originally trained by Fe2x.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_fe2x_en_5.5.1_3.0_1737784369538.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_fe2x_en_5.5.1_3.0_1737784369538.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_fe2x","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_fe2x","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_financial_matryoshka_fe2x|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|387.1 MB|
+
+## References
+
+https://huggingface.co/Fe2x/bge-base-financial-matryoshka
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bge_base_financial_matryoshka_fe2x_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bge_base_financial_matryoshka_fe2x_pipeline_en.md
new file mode 100644
index 00000000000000..52ed5be289b536
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bge_base_financial_matryoshka_fe2x_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_base_financial_matryoshka_fe2x_pipeline pipeline BGEEmbeddings from Fe2x
+author: John Snow Labs
+name: bge_base_financial_matryoshka_fe2x_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_fe2x_pipeline` is a English model originally trained by Fe2x.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_fe2x_pipeline_en_5.5.1_3.0_1737784397017.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_fe2x_pipeline_en_5.5.1_3.0_1737784397017.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_base_financial_matryoshka_fe2x_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_base_financial_matryoshka_fe2x_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_financial_matryoshka_fe2x_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|387.1 MB|
+
+## References
+
+https://huggingface.co/Fe2x/bge-base-financial-matryoshka
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bge_base_financial_matryoshka_kenoc_en.md b/docs/_posts/ahmedlone127/2025-01-25-bge_base_financial_matryoshka_kenoc_en.md
new file mode 100644
index 00000000000000..ccc5aa4db8ea91
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bge_base_financial_matryoshka_kenoc_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_base_financial_matryoshka_kenoc BGEEmbeddings from kenoc
+author: John Snow Labs
+name: bge_base_financial_matryoshka_kenoc
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_kenoc` is a English model originally trained by kenoc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_kenoc_en_5.5.1_3.0_1737783965097.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_kenoc_en_5.5.1_3.0_1737783965097.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_kenoc","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_base_financial_matryoshka_kenoc","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_financial_matryoshka_kenoc|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|387.1 MB|
+
+## References
+
+https://huggingface.co/kenoc/bge-base-financial-matryoshka
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bge_base_financial_matryoshka_kenoc_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bge_base_financial_matryoshka_kenoc_pipeline_en.md
new file mode 100644
index 00000000000000..a9e76a23be699a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bge_base_financial_matryoshka_kenoc_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_base_financial_matryoshka_kenoc_pipeline pipeline BGEEmbeddings from kenoc
+author: John Snow Labs
+name: bge_base_financial_matryoshka_kenoc_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_financial_matryoshka_kenoc_pipeline` is a English model originally trained by kenoc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_kenoc_pipeline_en_5.5.1_3.0_1737783993555.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_financial_matryoshka_kenoc_pipeline_en_5.5.1_3.0_1737783993555.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_base_financial_matryoshka_kenoc_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_base_financial_matryoshka_kenoc_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_financial_matryoshka_kenoc_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|387.1 MB|
+
+## References
+
+https://huggingface.co/kenoc/bge-base-financial-matryoshka
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bge_base_movie_matryoshka_en.md b/docs/_posts/ahmedlone127/2025-01-25-bge_base_movie_matryoshka_en.md
new file mode 100644
index 00000000000000..ec07f10d6b9dab
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bge_base_movie_matryoshka_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_base_movie_matryoshka BGEEmbeddings from YxBxRyXJx
+author: John Snow Labs
+name: bge_base_movie_matryoshka
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_movie_matryoshka` is a English model originally trained by YxBxRyXJx.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_movie_matryoshka_en_5.5.1_3.0_1737783821557.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_movie_matryoshka_en_5.5.1_3.0_1737783821557.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_base_movie_matryoshka","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_base_movie_matryoshka","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_movie_matryoshka|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|385.4 MB|
+
+## References
+
+https://huggingface.co/YxBxRyXJx/bge-base-movie-matryoshka
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bge_base_movie_matryoshka_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bge_base_movie_matryoshka_pipeline_en.md
new file mode 100644
index 00000000000000..225361cc60aa2f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bge_base_movie_matryoshka_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_base_movie_matryoshka_pipeline pipeline BGEEmbeddings from YxBxRyXJx
+author: John Snow Labs
+name: bge_base_movie_matryoshka_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_movie_matryoshka_pipeline` is a English model originally trained by YxBxRyXJx.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_movie_matryoshka_pipeline_en_5.5.1_3.0_1737783852331.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_movie_matryoshka_pipeline_en_5.5.1_3.0_1737783852331.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_base_movie_matryoshka_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_base_movie_matryoshka_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_movie_matryoshka_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|385.4 MB|
+
+## References
+
+https://huggingface.co/YxBxRyXJx/bge-base-movie-matryoshka
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bge_finetuned_detail_en.md b/docs/_posts/ahmedlone127/2025-01-25-bge_finetuned_detail_en.md
new file mode 100644
index 00000000000000..7d9e237e3a2894
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bge_finetuned_detail_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_finetuned_detail BGEEmbeddings from rezarahim
+author: John Snow Labs
+name: bge_finetuned_detail
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_finetuned_detail` is a English model originally trained by rezarahim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_finetuned_detail_en_5.5.1_3.0_1737783824389.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_finetuned_detail_en_5.5.1_3.0_1737783824389.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_finetuned_detail","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_finetuned_detail","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_finetuned_detail|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|377.6 MB|
+
+## References
+
+https://huggingface.co/rezarahim/bge-finetuned-detail
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bge_finetuned_detail_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bge_finetuned_detail_pipeline_en.md
new file mode 100644
index 00000000000000..ea61535397fb98
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bge_finetuned_detail_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_finetuned_detail_pipeline pipeline BGEEmbeddings from rezarahim
+author: John Snow Labs
+name: bge_finetuned_detail_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_finetuned_detail_pipeline` is a English model originally trained by rezarahim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_finetuned_detail_pipeline_en_5.5.1_3.0_1737783857492.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_finetuned_detail_pipeline_en_5.5.1_3.0_1737783857492.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_finetuned_detail_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_finetuned_detail_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_finetuned_detail_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|377.6 MB|
+
+## References
+
+https://huggingface.co/rezarahim/bge-finetuned-detail
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bge_small_english_v1_5_2025_01_01_21_55_17_en.md b/docs/_posts/ahmedlone127/2025-01-25-bge_small_english_v1_5_2025_01_01_21_55_17_en.md
new file mode 100644
index 00000000000000..2f8d22931cf094
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bge_small_english_v1_5_2025_01_01_21_55_17_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_small_english_v1_5_2025_01_01_21_55_17 BGEEmbeddings from gutsartificial
+author: John Snow Labs
+name: bge_small_english_v1_5_2025_01_01_21_55_17
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_small_english_v1_5_2025_01_01_21_55_17` is a English model originally trained by gutsartificial.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_small_english_v1_5_2025_01_01_21_55_17_en_5.5.1_3.0_1737784226354.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_small_english_v1_5_2025_01_01_21_55_17_en_5.5.1_3.0_1737784226354.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_small_english_v1_5_2025_01_01_21_55_17","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_small_english_v1_5_2025_01_01_21_55_17","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_small_english_v1_5_2025_01_01_21_55_17|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|123.3 MB|
+
+## References
+
+https://huggingface.co/gutsartificial/bge-small-en-v1.5-2025-01-01_21-55-17
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bge_small_english_v1_5_2025_01_01_21_55_17_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bge_small_english_v1_5_2025_01_01_21_55_17_pipeline_en.md
new file mode 100644
index 00000000000000..8a4ae786d7b705
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bge_small_english_v1_5_2025_01_01_21_55_17_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_small_english_v1_5_2025_01_01_21_55_17_pipeline pipeline BGEEmbeddings from gutsartificial
+author: John Snow Labs
+name: bge_small_english_v1_5_2025_01_01_21_55_17_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_small_english_v1_5_2025_01_01_21_55_17_pipeline` is a English model originally trained by gutsartificial.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_small_english_v1_5_2025_01_01_21_55_17_pipeline_en_5.5.1_3.0_1737784232986.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_small_english_v1_5_2025_01_01_21_55_17_pipeline_en_5.5.1_3.0_1737784232986.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_small_english_v1_5_2025_01_01_21_55_17_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_small_english_v1_5_2025_01_01_21_55_17_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_small_english_v1_5_2025_01_01_21_55_17_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|123.3 MB|
+
+## References
+
+https://huggingface.co/gutsartificial/bge-small-en-v1.5-2025-01-01_21-55-17
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bge_small_qa_telecom_ft_en.md b/docs/_posts/ahmedlone127/2025-01-25-bge_small_qa_telecom_ft_en.md
new file mode 100644
index 00000000000000..dca3648834eec0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bge_small_qa_telecom_ft_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_small_qa_telecom_ft BGEEmbeddings from dinho1597
+author: John Snow Labs
+name: bge_small_qa_telecom_ft
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_small_qa_telecom_ft` is a English model originally trained by dinho1597.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_small_qa_telecom_ft_en_5.5.1_3.0_1737783944663.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_small_qa_telecom_ft_en_5.5.1_3.0_1737783944663.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_small_qa_telecom_ft","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_small_qa_telecom_ft","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_small_qa_telecom_ft|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|115.5 MB|
+
+## References
+
+https://huggingface.co/dinho1597/bge-small-qa-telecom-ft
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bge_small_qa_telecom_ft_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bge_small_qa_telecom_ft_pipeline_en.md
new file mode 100644
index 00000000000000..cb35cddbacca6f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bge_small_qa_telecom_ft_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_small_qa_telecom_ft_pipeline pipeline BGEEmbeddings from dinho1597
+author: John Snow Labs
+name: bge_small_qa_telecom_ft_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_small_qa_telecom_ft_pipeline` is a English model originally trained by dinho1597.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_small_qa_telecom_ft_pipeline_en_5.5.1_3.0_1737783952562.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_small_qa_telecom_ft_pipeline_en_5.5.1_3.0_1737783952562.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_small_qa_telecom_ft_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_small_qa_telecom_ft_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_small_qa_telecom_ft_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|115.5 MB|
+
+## References
+
+https://huggingface.co/dinho1597/bge-small-qa-telecom-ft
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bgeembeddingsretailedft_en.md b/docs/_posts/ahmedlone127/2025-01-25-bgeembeddingsretailedft_en.md
new file mode 100644
index 00000000000000..b1260f875c3364
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bgeembeddingsretailedft_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bgeembeddingsretailedft BGEEmbeddings from mavihsrr
+author: John Snow Labs
+name: bgeembeddingsretailedft
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bgeembeddingsretailedft` is a English model originally trained by mavihsrr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bgeembeddingsretailedft_en_5.5.1_3.0_1737784307958.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bgeembeddingsretailedft_en_5.5.1_3.0_1737784307958.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bgeembeddingsretailedft","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bgeembeddingsretailedft","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bgeembeddingsretailedft|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|118.6 MB|
+
+## References
+
+https://huggingface.co/mavihsrr/bgeEmbeddingsRetailedFT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bgeembeddingsretailedft_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bgeembeddingsretailedft_pipeline_en.md
new file mode 100644
index 00000000000000..3017396ba46386
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bgeembeddingsretailedft_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bgeembeddingsretailedft_pipeline pipeline BGEEmbeddings from mavihsrr
+author: John Snow Labs
+name: bgeembeddingsretailedft_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bgeembeddingsretailedft_pipeline` is a English model originally trained by mavihsrr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bgeembeddingsretailedft_pipeline_en_5.5.1_3.0_1737784315612.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bgeembeddingsretailedft_pipeline_en_5.5.1_3.0_1737784315612.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bgeembeddingsretailedft_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bgeembeddingsretailedft_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bgeembeddingsretailedft_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|118.6 MB|
+
+## References
+
+https://huggingface.co/mavihsrr/bgeEmbeddingsRetailedFT
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bilingualchildrenemo_en.md b/docs/_posts/ahmedlone127/2025-01-25-bilingualchildrenemo_en.md
new file mode 100644
index 00000000000000..2ee8e605de355b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bilingualchildrenemo_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bilingualchildrenemo XlmRoBertaForSequenceClassification from nanaaaa
+author: John Snow Labs
+name: bilingualchildrenemo
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bilingualchildrenemo` is a English model originally trained by nanaaaa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bilingualchildrenemo_en_5.5.1_3.0_1737815812025.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bilingualchildrenemo_en_5.5.1_3.0_1737815812025.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("bilingualchildrenemo","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("bilingualchildrenemo", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bilingualchildrenemo|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|837.5 MB|
+
+## References
+
+https://huggingface.co/nanaaaa/BilingualChildrenEmo
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bilingualchildrenemo_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bilingualchildrenemo_pipeline_en.md
new file mode 100644
index 00000000000000..5ac1d41b994be5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bilingualchildrenemo_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bilingualchildrenemo_pipeline pipeline XlmRoBertaForSequenceClassification from nanaaaa
+author: John Snow Labs
+name: bilingualchildrenemo_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bilingualchildrenemo_pipeline` is a English model originally trained by nanaaaa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bilingualchildrenemo_pipeline_en_5.5.1_3.0_1737815889443.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bilingualchildrenemo_pipeline_en_5.5.1_3.0_1737815889443.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bilingualchildrenemo_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bilingualchildrenemo_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bilingualchildrenemo_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|837.5 MB|
+
+## References
+
+https://huggingface.co/nanaaaa/BilingualChildrenEmo
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-biobert_biomedical_ner_en.md b/docs/_posts/ahmedlone127/2025-01-25-biobert_biomedical_ner_en.md
new file mode 100644
index 00000000000000..b8a2a8fcbe69ef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-biobert_biomedical_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English biobert_biomedical_ner BertForTokenClassification from henrymark
+author: John Snow Labs
+name: biobert_biomedical_ner
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biobert_biomedical_ner` is a English model originally trained by henrymark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biobert_biomedical_ner_en_5.5.1_3.0_1737835454412.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biobert_biomedical_ner_en_5.5.1_3.0_1737835454412.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("biobert_biomedical_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("biobert_biomedical_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|biobert_biomedical_ner|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.1 MB|
+
+## References
+
+https://huggingface.co/henrymark/biobert-biomedical-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-biobert_biomedical_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-biobert_biomedical_ner_pipeline_en.md
new file mode 100644
index 00000000000000..e3b8a0c7c46eaa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-biobert_biomedical_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English biobert_biomedical_ner_pipeline pipeline BertForTokenClassification from henrymark
+author: John Snow Labs
+name: biobert_biomedical_ner_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biobert_biomedical_ner_pipeline` is a English model originally trained by henrymark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biobert_biomedical_ner_pipeline_en_5.5.1_3.0_1737835474413.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biobert_biomedical_ner_pipeline_en_5.5.1_3.0_1737835474413.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("biobert_biomedical_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("biobert_biomedical_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|biobert_biomedical_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.1 MB|
+
+## References
+
+https://huggingface.co/henrymark/biobert-biomedical-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-blade_english_persian_farsi_en.md b/docs/_posts/ahmedlone127/2025-01-25-blade_english_persian_farsi_en.md
new file mode 100644
index 00000000000000..7707ca0c54af53
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-blade_english_persian_farsi_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English blade_english_persian_farsi BertEmbeddings from srnair
+author: John Snow Labs
+name: blade_english_persian_farsi
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`blade_english_persian_farsi` is a English model originally trained by srnair.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/blade_english_persian_farsi_en_5.5.1_3.0_1737806364017.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/blade_english_persian_farsi_en_5.5.1_3.0_1737806364017.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("blade_english_persian_farsi","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("blade_english_persian_farsi","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|blade_english_persian_farsi|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|410.6 MB|
+
+## References
+
+https://huggingface.co/srnair/blade-en-fa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-blade_english_persian_farsi_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-blade_english_persian_farsi_pipeline_en.md
new file mode 100644
index 00000000000000..939f5968d77f8b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-blade_english_persian_farsi_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English blade_english_persian_farsi_pipeline pipeline BertEmbeddings from srnair
+author: John Snow Labs
+name: blade_english_persian_farsi_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`blade_english_persian_farsi_pipeline` is a English model originally trained by srnair.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/blade_english_persian_farsi_pipeline_en_5.5.1_3.0_1737806386188.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/blade_english_persian_farsi_pipeline_en_5.5.1_3.0_1737806386188.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("blade_english_persian_farsi_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("blade_english_persian_farsi_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|blade_english_persian_farsi_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.6 MB|
+
+## References
+
+https://huggingface.co/srnair/blade-en-fa
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bpeo_classifier_en.md b/docs/_posts/ahmedlone127/2025-01-25-bpeo_classifier_en.md
new file mode 100644
index 00000000000000..85687603d44896
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bpeo_classifier_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bpeo_classifier DistilBertForSequenceClassification from jpbywater
+author: John Snow Labs
+name: bpeo_classifier
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bpeo_classifier` is a English model originally trained by jpbywater.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bpeo_classifier_en_5.5.1_3.0_1737822278705.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bpeo_classifier_en_5.5.1_3.0_1737822278705.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("bpeo_classifier","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("bpeo_classifier", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bpeo_classifier|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/jpbywater/bpeo_classifier
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bpeo_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-bpeo_classifier_pipeline_en.md
new file mode 100644
index 00000000000000..b7850850f773df
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bpeo_classifier_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bpeo_classifier_pipeline pipeline DistilBertForSequenceClassification from jpbywater
+author: John Snow Labs
+name: bpeo_classifier_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bpeo_classifier_pipeline` is a English model originally trained by jpbywater.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bpeo_classifier_pipeline_en_5.5.1_3.0_1737822292316.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bpeo_classifier_pipeline_en_5.5.1_3.0_1737822292316.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bpeo_classifier_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bpeo_classifier_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bpeo_classifier_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/jpbywater/bpeo_classifier
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-brwac_large_v1_2__checkpoint_6_en.md b/docs/_posts/ahmedlone127/2025-01-25-brwac_large_v1_2__checkpoint_6_en.md
new file mode 100644
index 00000000000000..aca21de180170c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-brwac_large_v1_2__checkpoint_6_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English brwac_large_v1_2__checkpoint_6 RoBertaEmbeddings from eduagarcia-temp
+author: John Snow Labs
+name: brwac_large_v1_2__checkpoint_6
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`brwac_large_v1_2__checkpoint_6` is a English model originally trained by eduagarcia-temp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/brwac_large_v1_2__checkpoint_6_en_5.5.1_3.0_1737797704504.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/brwac_large_v1_2__checkpoint_6_en_5.5.1_3.0_1737797704504.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("brwac_large_v1_2__checkpoint_6","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("brwac_large_v1_2__checkpoint_6","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|brwac_large_v1_2__checkpoint_6|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|845.3 MB|
+
+## References
+
+https://huggingface.co/eduagarcia-temp/brwac_large_v1_2__checkpoint_6
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-brwac_large_v1_2__checkpoint_6_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-brwac_large_v1_2__checkpoint_6_pipeline_en.md
new file mode 100644
index 00000000000000..33479851991636
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-brwac_large_v1_2__checkpoint_6_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English brwac_large_v1_2__checkpoint_6_pipeline pipeline RoBertaEmbeddings from eduagarcia-temp
+author: John Snow Labs
+name: brwac_large_v1_2__checkpoint_6_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`brwac_large_v1_2__checkpoint_6_pipeline` is a English model originally trained by eduagarcia-temp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/brwac_large_v1_2__checkpoint_6_pipeline_en_5.5.1_3.0_1737797957236.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/brwac_large_v1_2__checkpoint_6_pipeline_en_5.5.1_3.0_1737797957236.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("brwac_large_v1_2__checkpoint_6_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("brwac_large_v1_2__checkpoint_6_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|brwac_large_v1_2__checkpoint_6_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|845.3 MB|
+
+## References
+
+https://huggingface.co/eduagarcia-temp/brwac_large_v1_2__checkpoint_6
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-brwac_v1_1__checkpoint_last_en.md b/docs/_posts/ahmedlone127/2025-01-25-brwac_v1_1__checkpoint_last_en.md
new file mode 100644
index 00000000000000..7a52319014d34a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-brwac_v1_1__checkpoint_last_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English brwac_v1_1__checkpoint_last RoBertaEmbeddings from eduagarcia-temp
+author: John Snow Labs
+name: brwac_v1_1__checkpoint_last
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`brwac_v1_1__checkpoint_last` is a English model originally trained by eduagarcia-temp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/brwac_v1_1__checkpoint_last_en_5.5.1_3.0_1737797234245.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/brwac_v1_1__checkpoint_last_en_5.5.1_3.0_1737797234245.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("brwac_v1_1__checkpoint_last","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("brwac_v1_1__checkpoint_last","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|brwac_v1_1__checkpoint_last|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|298.5 MB|
+
+## References
+
+https://huggingface.co/eduagarcia-temp/brwac_v1_1__checkpoint_last
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-brwac_v1_1__checkpoint_last_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-brwac_v1_1__checkpoint_last_pipeline_en.md
new file mode 100644
index 00000000000000..0aa59fc79b5f22
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-brwac_v1_1__checkpoint_last_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English brwac_v1_1__checkpoint_last_pipeline pipeline RoBertaEmbeddings from eduagarcia-temp
+author: John Snow Labs
+name: brwac_v1_1__checkpoint_last_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`brwac_v1_1__checkpoint_last_pipeline` is a English model originally trained by eduagarcia-temp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/brwac_v1_1__checkpoint_last_pipeline_en_5.5.1_3.0_1737797322793.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/brwac_v1_1__checkpoint_last_pipeline_en_5.5.1_3.0_1737797322793.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("brwac_v1_1__checkpoint_last_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("brwac_v1_1__checkpoint_last_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|brwac_v1_1__checkpoint_last_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|298.5 MB|
+
+## References
+
+https://huggingface.co/eduagarcia-temp/brwac_v1_1__checkpoint_last
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bsc_bio_ehr_spanish_carmen_enfermedad_es.md b/docs/_posts/ahmedlone127/2025-01-25-bsc_bio_ehr_spanish_carmen_enfermedad_es.md
new file mode 100644
index 00000000000000..fa1a4bdf8aee83
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bsc_bio_ehr_spanish_carmen_enfermedad_es.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Castilian, Spanish bsc_bio_ehr_spanish_carmen_enfermedad RoBertaForTokenClassification from BSC-NLP4BIA
+author: John Snow Labs
+name: bsc_bio_ehr_spanish_carmen_enfermedad
+date: 2025-01-25
+tags: [es, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: es
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bsc_bio_ehr_spanish_carmen_enfermedad` is a Castilian, Spanish model originally trained by BSC-NLP4BIA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bsc_bio_ehr_spanish_carmen_enfermedad_es_5.5.1_3.0_1737809531343.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bsc_bio_ehr_spanish_carmen_enfermedad_es_5.5.1_3.0_1737809531343.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("bsc_bio_ehr_spanish_carmen_enfermedad","es") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("bsc_bio_ehr_spanish_carmen_enfermedad", "es")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bsc_bio_ehr_spanish_carmen_enfermedad|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|es|
+|Size:|438.1 MB|
+
+## References
+
+https://huggingface.co/BSC-NLP4BIA/bsc-bio-ehr-es-carmen-enfermedad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-bsc_bio_ehr_spanish_carmen_enfermedad_pipeline_es.md b/docs/_posts/ahmedlone127/2025-01-25-bsc_bio_ehr_spanish_carmen_enfermedad_pipeline_es.md
new file mode 100644
index 00000000000000..21775a9849d915
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-bsc_bio_ehr_spanish_carmen_enfermedad_pipeline_es.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Castilian, Spanish bsc_bio_ehr_spanish_carmen_enfermedad_pipeline pipeline RoBertaForTokenClassification from BSC-NLP4BIA
+author: John Snow Labs
+name: bsc_bio_ehr_spanish_carmen_enfermedad_pipeline
+date: 2025-01-25
+tags: [es, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: es
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bsc_bio_ehr_spanish_carmen_enfermedad_pipeline` is a Castilian, Spanish model originally trained by BSC-NLP4BIA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bsc_bio_ehr_spanish_carmen_enfermedad_pipeline_es_5.5.1_3.0_1737809556913.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bsc_bio_ehr_spanish_carmen_enfermedad_pipeline_es_5.5.1_3.0_1737809556913.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bsc_bio_ehr_spanish_carmen_enfermedad_pipeline", lang = "es")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bsc_bio_ehr_spanish_carmen_enfermedad_pipeline", lang = "es")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bsc_bio_ehr_spanish_carmen_enfermedad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|es|
+|Size:|438.1 MB|
+
+## References
+
+https://huggingface.co/BSC-NLP4BIA/bsc-bio-ehr-es-carmen-enfermedad
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_billsum_model_cotysong113_en.md b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_billsum_model_cotysong113_en.md
new file mode 100644
index 00000000000000..292dee965eada7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_billsum_model_cotysong113_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_billsum_model_cotysong113 T5Transformer from cotysong113
+author: John Snow Labs
+name: burmese_awesome_billsum_model_cotysong113
+date: 2025-01-25
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_billsum_model_cotysong113` is a English model originally trained by cotysong113.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_billsum_model_cotysong113_en_5.5.1_3.0_1737849059597.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_billsum_model_cotysong113_en_5.5.1_3.0_1737849059597.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("burmese_awesome_billsum_model_cotysong113","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("burmese_awesome_billsum_model_cotysong113", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_billsum_model_cotysong113|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|266.0 MB|
+
+## References
+
+https://huggingface.co/cotysong113/my_awesome_billsum_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_billsum_model_cotysong113_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_billsum_model_cotysong113_pipeline_en.md
new file mode 100644
index 00000000000000..4ded5ace7d85c4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_billsum_model_cotysong113_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_billsum_model_cotysong113_pipeline pipeline T5Transformer from cotysong113
+author: John Snow Labs
+name: burmese_awesome_billsum_model_cotysong113_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_billsum_model_cotysong113_pipeline` is a English model originally trained by cotysong113.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_billsum_model_cotysong113_pipeline_en_5.5.1_3.0_1737849078350.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_billsum_model_cotysong113_pipeline_en_5.5.1_3.0_1737849078350.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_billsum_model_cotysong113_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_billsum_model_cotysong113_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_billsum_model_cotysong113_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|266.0 MB|
+
+## References
+
+https://huggingface.co/cotysong113/my_awesome_billsum_model
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_billsum_model_ddexterr_en.md b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_billsum_model_ddexterr_en.md
new file mode 100644
index 00000000000000..ed291628f35961
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_billsum_model_ddexterr_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_billsum_model_ddexterr T5Transformer from ddexterr
+author: John Snow Labs
+name: burmese_awesome_billsum_model_ddexterr
+date: 2025-01-25
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_billsum_model_ddexterr` is a English model originally trained by ddexterr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_billsum_model_ddexterr_en_5.5.1_3.0_1737848958761.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_billsum_model_ddexterr_en_5.5.1_3.0_1737848958761.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("burmese_awesome_billsum_model_ddexterr","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("burmese_awesome_billsum_model_ddexterr", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_billsum_model_ddexterr|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|266.0 MB|
+
+## References
+
+https://huggingface.co/ddexterr/my_awesome_billsum_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_billsum_model_ddexterr_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_billsum_model_ddexterr_pipeline_en.md
new file mode 100644
index 00000000000000..af36e7dd55cf20
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_billsum_model_ddexterr_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_billsum_model_ddexterr_pipeline pipeline T5Transformer from ddexterr
+author: John Snow Labs
+name: burmese_awesome_billsum_model_ddexterr_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_billsum_model_ddexterr_pipeline` is a English model originally trained by ddexterr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_billsum_model_ddexterr_pipeline_en_5.5.1_3.0_1737848978180.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_billsum_model_ddexterr_pipeline_en_5.5.1_3.0_1737848978180.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_billsum_model_ddexterr_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_billsum_model_ddexterr_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_billsum_model_ddexterr_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|266.0 MB|
+
+## References
+
+https://huggingface.co/ddexterr/my_awesome_billsum_model
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_eli5_mlm_model_stephenimm_en.md b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_eli5_mlm_model_stephenimm_en.md
new file mode 100644
index 00000000000000..06896e6f6df6d8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_eli5_mlm_model_stephenimm_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_eli5_mlm_model_stephenimm RoBertaEmbeddings from stephenimm
+author: John Snow Labs
+name: burmese_awesome_eli5_mlm_model_stephenimm
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_eli5_mlm_model_stephenimm` is a English model originally trained by stephenimm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_stephenimm_en_5.5.1_3.0_1737797422843.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_stephenimm_en_5.5.1_3.0_1737797422843.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("burmese_awesome_eli5_mlm_model_stephenimm","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("burmese_awesome_eli5_mlm_model_stephenimm","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_eli5_mlm_model_stephenimm|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/stephenimm/my_awesome_eli5_mlm_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_eli5_mlm_model_stephenimm_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_eli5_mlm_model_stephenimm_pipeline_en.md
new file mode 100644
index 00000000000000..998cd4f2dffa4f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_eli5_mlm_model_stephenimm_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_eli5_mlm_model_stephenimm_pipeline pipeline RoBertaEmbeddings from stephenimm
+author: John Snow Labs
+name: burmese_awesome_eli5_mlm_model_stephenimm_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_eli5_mlm_model_stephenimm_pipeline` is a English model originally trained by stephenimm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_stephenimm_pipeline_en_5.5.1_3.0_1737797441956.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_stephenimm_pipeline_en_5.5.1_3.0_1737797441956.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_eli5_mlm_model_stephenimm_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_eli5_mlm_model_stephenimm_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_eli5_mlm_model_stephenimm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/stephenimm/my_awesome_eli5_mlm_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model2_dstankovskii_en.md b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model2_dstankovskii_en.md
new file mode 100644
index 00000000000000..21a925e70e875c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model2_dstankovskii_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model2_dstankovskii DistilBertForSequenceClassification from dstankovskii
+author: John Snow Labs
+name: burmese_awesome_model2_dstankovskii
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model2_dstankovskii` is a English model originally trained by dstankovskii.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model2_dstankovskii_en_5.5.1_3.0_1737822626530.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model2_dstankovskii_en_5.5.1_3.0_1737822626530.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_model2_dstankovskii","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model2_dstankovskii", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model2_dstankovskii|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/dstankovskii/my_awesome_model2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model2_dstankovskii_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model2_dstankovskii_pipeline_en.md
new file mode 100644
index 00000000000000..659eb5f7ba3ee5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model2_dstankovskii_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model2_dstankovskii_pipeline pipeline DistilBertForSequenceClassification from dstankovskii
+author: John Snow Labs
+name: burmese_awesome_model2_dstankovskii_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model2_dstankovskii_pipeline` is a English model originally trained by dstankovskii.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model2_dstankovskii_pipeline_en_5.5.1_3.0_1737822642014.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model2_dstankovskii_pipeline_en_5.5.1_3.0_1737822642014.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model2_dstankovskii_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model2_dstankovskii_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model2_dstankovskii_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/dstankovskii/my_awesome_model2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_3_en.md b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_3_en.md
new file mode 100644
index 00000000000000..faf282212b6a5a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_3 DistilBertForSequenceClassification from gavinqiangli
+author: John Snow Labs
+name: burmese_awesome_model_3
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_3` is a English model originally trained by gavinqiangli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_3_en_5.5.1_3.0_1737837646859.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_3_en_5.5.1_3.0_1737837646859.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_3","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_3", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_3|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/gavinqiangli/my_awesome_model_3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_3_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_3_pipeline_en.md
new file mode 100644
index 00000000000000..2c4bfdaccbd16e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_3_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_3_pipeline pipeline DistilBertForSequenceClassification from gavinqiangli
+author: John Snow Labs
+name: burmese_awesome_model_3_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_3_pipeline` is a English model originally trained by gavinqiangli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_3_pipeline_en_5.5.1_3.0_1737837663157.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_3_pipeline_en_5.5.1_3.0_1737837663157.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/gavinqiangli/my_awesome_model_3
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_boisalai_en.md b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_boisalai_en.md
new file mode 100644
index 00000000000000..57e84d2bb36ae3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_boisalai_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_boisalai DistilBertForSequenceClassification from boisalai
+author: John Snow Labs
+name: burmese_awesome_model_boisalai
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_boisalai` is a English model originally trained by boisalai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_boisalai_en_5.5.1_3.0_1737837525214.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_boisalai_en_5.5.1_3.0_1737837525214.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_boisalai","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_boisalai", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_boisalai|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/boisalai/my_awesome_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_boisalai_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_boisalai_pipeline_en.md
new file mode 100644
index 00000000000000..8dfd593619e73d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_boisalai_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_boisalai_pipeline pipeline DistilBertForSequenceClassification from boisalai
+author: John Snow Labs
+name: burmese_awesome_model_boisalai_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_boisalai_pipeline` is a English model originally trained by boisalai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_boisalai_pipeline_en_5.5.1_3.0_1737837541349.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_boisalai_pipeline_en_5.5.1_3.0_1737837541349.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_boisalai_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_boisalai_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_boisalai_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/boisalai/my_awesome_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_gimhansandeeptha_en.md b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_gimhansandeeptha_en.md
new file mode 100644
index 00000000000000..9a4a02d6a5037b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_gimhansandeeptha_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_gimhansandeeptha DistilBertForSequenceClassification from gimhanSandeeptha
+author: John Snow Labs
+name: burmese_awesome_model_gimhansandeeptha
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_gimhansandeeptha` is a English model originally trained by gimhanSandeeptha.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_gimhansandeeptha_en_5.5.1_3.0_1737822505318.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_gimhansandeeptha_en_5.5.1_3.0_1737822505318.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_gimhansandeeptha","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_gimhansandeeptha", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_gimhansandeeptha|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/gimhanSandeeptha/my_awesome_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_gimhansandeeptha_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_gimhansandeeptha_pipeline_en.md
new file mode 100644
index 00000000000000..7058d313c2354f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_gimhansandeeptha_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_gimhansandeeptha_pipeline pipeline DistilBertForSequenceClassification from gimhanSandeeptha
+author: John Snow Labs
+name: burmese_awesome_model_gimhansandeeptha_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_gimhansandeeptha_pipeline` is a English model originally trained by gimhanSandeeptha.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_gimhansandeeptha_pipeline_en_5.5.1_3.0_1737822518576.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_gimhansandeeptha_pipeline_en_5.5.1_3.0_1737822518576.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_gimhansandeeptha_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_gimhansandeeptha_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_gimhansandeeptha_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/gimhanSandeeptha/my_awesome_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_jacqueslenormand_en.md b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_jacqueslenormand_en.md
new file mode 100644
index 00000000000000..bf129d16a13e13
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_jacqueslenormand_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_jacqueslenormand DistilBertForSequenceClassification from jacqueslenormand
+author: John Snow Labs
+name: burmese_awesome_model_jacqueslenormand
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_jacqueslenormand` is a English model originally trained by jacqueslenormand.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_jacqueslenormand_en_5.5.1_3.0_1737821792741.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_jacqueslenormand_en_5.5.1_3.0_1737821792741.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_jacqueslenormand","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_jacqueslenormand", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_jacqueslenormand|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/jacqueslenormand/my_awesome_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_jacqueslenormand_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_jacqueslenormand_pipeline_en.md
new file mode 100644
index 00000000000000..79cec547b3e2c4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_jacqueslenormand_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_jacqueslenormand_pipeline pipeline DistilBertForSequenceClassification from jacqueslenormand
+author: John Snow Labs
+name: burmese_awesome_model_jacqueslenormand_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_jacqueslenormand_pipeline` is a English model originally trained by jacqueslenormand.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_jacqueslenormand_pipeline_en_5.5.1_3.0_1737821816095.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_jacqueslenormand_pipeline_en_5.5.1_3.0_1737821816095.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_jacqueslenormand_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_jacqueslenormand_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_jacqueslenormand_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/jacqueslenormand/my_awesome_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_lilyyellow_en.md b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_lilyyellow_en.md
new file mode 100644
index 00000000000000..377cc53f826ccd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_lilyyellow_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_lilyyellow DistilBertForSequenceClassification from lilyyellow
+author: John Snow Labs
+name: burmese_awesome_model_lilyyellow
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_lilyyellow` is a English model originally trained by lilyyellow.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_lilyyellow_en_5.5.1_3.0_1737836267988.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_lilyyellow_en_5.5.1_3.0_1737836267988.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_lilyyellow","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_lilyyellow", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_lilyyellow|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/lilyyellow/my_awesome_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_lilyyellow_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_lilyyellow_pipeline_en.md
new file mode 100644
index 00000000000000..c052e5d754f029
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_lilyyellow_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_lilyyellow_pipeline pipeline DistilBertForSequenceClassification from lilyyellow
+author: John Snow Labs
+name: burmese_awesome_model_lilyyellow_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_lilyyellow_pipeline` is a English model originally trained by lilyyellow.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_lilyyellow_pipeline_en_5.5.1_3.0_1737836284495.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_lilyyellow_pipeline_en_5.5.1_3.0_1737836284495.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_lilyyellow_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_lilyyellow_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_lilyyellow_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/lilyyellow/my_awesome_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_lqs2427_en.md b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_lqs2427_en.md
new file mode 100644
index 00000000000000..7cd157df6ac5c4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_lqs2427_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_lqs2427 DistilBertForSequenceClassification from lqs2427
+author: John Snow Labs
+name: burmese_awesome_model_lqs2427
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_lqs2427` is a English model originally trained by lqs2427.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_lqs2427_en_5.5.1_3.0_1737837754213.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_lqs2427_en_5.5.1_3.0_1737837754213.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_lqs2427","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_lqs2427", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_lqs2427|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/lqs2427/my_awesome_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_lqs2427_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_lqs2427_pipeline_en.md
new file mode 100644
index 00000000000000..6e00ad5b4f3431
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_lqs2427_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_lqs2427_pipeline pipeline DistilBertForSequenceClassification from lqs2427
+author: John Snow Labs
+name: burmese_awesome_model_lqs2427_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_lqs2427_pipeline` is a English model originally trained by lqs2427.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_lqs2427_pipeline_en_5.5.1_3.0_1737837766980.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_lqs2427_pipeline_en_5.5.1_3.0_1737837766980.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_lqs2427_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_lqs2427_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_lqs2427_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/lqs2427/my_awesome_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_massimoambrosini_en.md b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_massimoambrosini_en.md
new file mode 100644
index 00000000000000..85b4a8ab097b1c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_massimoambrosini_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_massimoambrosini DistilBertForSequenceClassification from massimoambrosini
+author: John Snow Labs
+name: burmese_awesome_model_massimoambrosini
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_massimoambrosini` is a English model originally trained by massimoambrosini.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_massimoambrosini_en_5.5.1_3.0_1737822373447.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_massimoambrosini_en_5.5.1_3.0_1737822373447.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_massimoambrosini","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_massimoambrosini", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_massimoambrosini|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/massimoambrosini/my_awesome_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_massimoambrosini_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_massimoambrosini_pipeline_en.md
new file mode 100644
index 00000000000000..8be42548d3ac74
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_massimoambrosini_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_massimoambrosini_pipeline pipeline DistilBertForSequenceClassification from massimoambrosini
+author: John Snow Labs
+name: burmese_awesome_model_massimoambrosini_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_massimoambrosini_pipeline` is a English model originally trained by massimoambrosini.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_massimoambrosini_pipeline_en_5.5.1_3.0_1737822386409.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_massimoambrosini_pipeline_en_5.5.1_3.0_1737822386409.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_massimoambrosini_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_massimoambrosini_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_massimoambrosini_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/massimoambrosini/my_awesome_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_r_en.md b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_r_en.md
new file mode 100644
index 00000000000000..a8f11a80101686
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_r_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_r DistilBertForSequenceClassification from oltenu
+author: John Snow Labs
+name: burmese_awesome_model_r
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_r` is a English model originally trained by oltenu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_r_en_5.5.1_3.0_1737822064666.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_r_en_5.5.1_3.0_1737822064666.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_r","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_r", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_r|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/oltenu/my_awesome_model_r
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_r_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_r_pipeline_en.md
new file mode 100644
index 00000000000000..bf2a8b948b6a7e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_r_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_r_pipeline pipeline DistilBertForSequenceClassification from oltenu
+author: John Snow Labs
+name: burmese_awesome_model_r_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_r_pipeline` is a English model originally trained by oltenu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_r_pipeline_en_5.5.1_3.0_1737822080525.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_r_pipeline_en_5.5.1_3.0_1737822080525.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_r_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_r_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_r_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/oltenu/my_awesome_model_r
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_thony08_en.md b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_thony08_en.md
new file mode 100644
index 00000000000000..5d8e21e4baa949
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_thony08_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_thony08 DistilBertForSequenceClassification from thony08
+author: John Snow Labs
+name: burmese_awesome_model_thony08
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_thony08` is a English model originally trained by thony08.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_thony08_en_5.5.1_3.0_1737822649210.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_thony08_en_5.5.1_3.0_1737822649210.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_thony08","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_thony08", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_thony08|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/thony08/my_awesome_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_thony08_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_thony08_pipeline_en.md
new file mode 100644
index 00000000000000..03ba177e3f3bb5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_thony08_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_thony08_pipeline pipeline DistilBertForSequenceClassification from thony08
+author: John Snow Labs
+name: burmese_awesome_model_thony08_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_thony08_pipeline` is a English model originally trained by thony08.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_thony08_pipeline_en_5.5.1_3.0_1737822662121.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_thony08_pipeline_en_5.5.1_3.0_1737822662121.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_thony08_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_thony08_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_thony08_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/thony08/my_awesome_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_williamywy_en.md b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_williamywy_en.md
new file mode 100644
index 00000000000000..40e868661214f5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_williamywy_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_williamywy DistilBertForSequenceClassification from WilliamYWY
+author: John Snow Labs
+name: burmese_awesome_model_williamywy
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_williamywy` is a English model originally trained by WilliamYWY.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_williamywy_en_5.5.1_3.0_1737837525267.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_williamywy_en_5.5.1_3.0_1737837525267.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_williamywy","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_williamywy", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_williamywy|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/WilliamYWY/my_awesome_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_williamywy_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_williamywy_pipeline_en.md
new file mode 100644
index 00000000000000..747a5afd633624
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_williamywy_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_williamywy_pipeline pipeline DistilBertForSequenceClassification from WilliamYWY
+author: John Snow Labs
+name: burmese_awesome_model_williamywy_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_williamywy_pipeline` is a English model originally trained by WilliamYWY.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_williamywy_pipeline_en_5.5.1_3.0_1737837545101.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_williamywy_pipeline_en_5.5.1_3.0_1737837545101.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_williamywy_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_williamywy_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_williamywy_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/WilliamYWY/my_awesome_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_wyxwangmed_en.md b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_wyxwangmed_en.md
new file mode 100644
index 00000000000000..029008a5c90d25
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_wyxwangmed_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_wyxwangmed DistilBertForSequenceClassification from wyxwangmed
+author: John Snow Labs
+name: burmese_awesome_model_wyxwangmed
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_wyxwangmed` is a English model originally trained by wyxwangmed.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_wyxwangmed_en_5.5.1_3.0_1737821792723.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_wyxwangmed_en_5.5.1_3.0_1737821792723.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_wyxwangmed","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_wyxwangmed", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_wyxwangmed|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/wyxwangmed/my_awesome_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_wyxwangmed_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_wyxwangmed_pipeline_en.md
new file mode 100644
index 00000000000000..e3c89bd6eff5ce
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_wyxwangmed_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_wyxwangmed_pipeline pipeline DistilBertForSequenceClassification from wyxwangmed
+author: John Snow Labs
+name: burmese_awesome_model_wyxwangmed_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_wyxwangmed_pipeline` is a English model originally trained by wyxwangmed.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_wyxwangmed_pipeline_en_5.5.1_3.0_1737821816202.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_wyxwangmed_pipeline_en_5.5.1_3.0_1737821816202.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_wyxwangmed_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_wyxwangmed_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_wyxwangmed_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/wyxwangmed/my_awesome_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_yonho67_en.md b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_yonho67_en.md
new file mode 100644
index 00000000000000..82cd27e644c337
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_yonho67_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_yonho67 DistilBertForSequenceClassification from yonho67
+author: John Snow Labs
+name: burmese_awesome_model_yonho67
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_yonho67` is a English model originally trained by yonho67.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_yonho67_en_5.5.1_3.0_1737812063707.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_yonho67_en_5.5.1_3.0_1737812063707.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_yonho67","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_yonho67", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_yonho67|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/yonho67/my_awesome_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_yonho67_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_yonho67_pipeline_en.md
new file mode 100644
index 00000000000000..a52f97dd2c377c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_yonho67_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_yonho67_pipeline pipeline DistilBertForSequenceClassification from yonho67
+author: John Snow Labs
+name: burmese_awesome_model_yonho67_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_yonho67_pipeline` is a English model originally trained by yonho67.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_yonho67_pipeline_en_5.5.1_3.0_1737812077565.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_yonho67_pipeline_en_5.5.1_3.0_1737812077565.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_yonho67_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_yonho67_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_yonho67_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/yonho67/my_awesome_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_zhengyu_su_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_zhengyu_su_pipeline_en.md
new file mode 100644
index 00000000000000..b69b12a210ec98
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_model_zhengyu_su_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_zhengyu_su_pipeline pipeline DistilBertForSequenceClassification from zhengyu-su
+author: John Snow Labs
+name: burmese_awesome_model_zhengyu_su_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_zhengyu_su_pipeline` is a English model originally trained by zhengyu-su.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_zhengyu_su_pipeline_en_5.5.1_3.0_1737836759133.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_zhengyu_su_pipeline_en_5.5.1_3.0_1737836759133.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_zhengyu_su_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_zhengyu_su_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_zhengyu_su_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/zhengyu-su/my_awesome_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_opus_books_model_clui_en.md b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_opus_books_model_clui_en.md
new file mode 100644
index 00000000000000..b8ed8074cbc19b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_opus_books_model_clui_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_opus_books_model_clui MarianTransformer from clui
+author: John Snow Labs
+name: burmese_awesome_opus_books_model_clui
+date: 2025-01-25
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_opus_books_model_clui` is a English model originally trained by clui.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_clui_en_5.5.1_3.0_1737782025757.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_clui_en_5.5.1_3.0_1737782025757.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("burmese_awesome_opus_books_model_clui","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("burmese_awesome_opus_books_model_clui","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_opus_books_model_clui|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|477.1 MB|
+
+## References
+
+https://huggingface.co/clui/my_awesome_opus_books_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_opus_books_model_clui_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_opus_books_model_clui_pipeline_en.md
new file mode 100644
index 00000000000000..492133a0567355
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_opus_books_model_clui_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_opus_books_model_clui_pipeline pipeline MarianTransformer from clui
+author: John Snow Labs
+name: burmese_awesome_opus_books_model_clui_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_opus_books_model_clui_pipeline` is a English model originally trained by clui.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_clui_pipeline_en_5.5.1_3.0_1737782051196.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_clui_pipeline_en_5.5.1_3.0_1737782051196.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_opus_books_model_clui_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_opus_books_model_clui_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_opus_books_model_clui_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|477.6 MB|
+
+## References
+
+https://huggingface.co/clui/my_awesome_opus_books_model
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_qa_model_salmamoori_en.md b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_qa_model_salmamoori_en.md
new file mode 100644
index 00000000000000..8a2910d846e842
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_qa_model_salmamoori_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_salmamoori DistilBertForQuestionAnswering from Salmamoori
+author: John Snow Labs
+name: burmese_awesome_qa_model_salmamoori
+date: 2025-01-25
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_salmamoori` is a English model originally trained by Salmamoori.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_salmamoori_en_5.5.1_3.0_1737823845541.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_salmamoori_en_5.5.1_3.0_1737823845541.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_salmamoori","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_salmamoori", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_salmamoori|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Salmamoori/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_qa_model_salmamoori_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_qa_model_salmamoori_pipeline_en.md
new file mode 100644
index 00000000000000..53ee0764695c37
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_qa_model_salmamoori_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_salmamoori_pipeline pipeline DistilBertForQuestionAnswering from Salmamoori
+author: John Snow Labs
+name: burmese_awesome_qa_model_salmamoori_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_salmamoori_pipeline` is a English model originally trained by Salmamoori.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_salmamoori_pipeline_en_5.5.1_3.0_1737823859903.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_salmamoori_pipeline_en_5.5.1_3.0_1737823859903.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_salmamoori_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_salmamoori_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_salmamoori_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Salmamoori/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_transformer_model_qualiamachine_en.md b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_transformer_model_qualiamachine_en.md
new file mode 100644
index 00000000000000..b34095b7bd1f65
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_transformer_model_qualiamachine_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_transformer_model_qualiamachine DistilBertForSequenceClassification from qualiaMachine
+author: John Snow Labs
+name: burmese_awesome_transformer_model_qualiamachine
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_transformer_model_qualiamachine` is a English model originally trained by qualiaMachine.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_transformer_model_qualiamachine_en_5.5.1_3.0_1737836439240.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_transformer_model_qualiamachine_en_5.5.1_3.0_1737836439240.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_transformer_model_qualiamachine","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_transformer_model_qualiamachine", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_transformer_model_qualiamachine|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/qualiaMachine/my-awesome-transformer-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_transformer_model_qualiamachine_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_transformer_model_qualiamachine_pipeline_en.md
new file mode 100644
index 00000000000000..453ff26b56e2ca
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-burmese_awesome_transformer_model_qualiamachine_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_transformer_model_qualiamachine_pipeline pipeline DistilBertForSequenceClassification from qualiaMachine
+author: John Snow Labs
+name: burmese_awesome_transformer_model_qualiamachine_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_transformer_model_qualiamachine_pipeline` is a English model originally trained by qualiaMachine.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_transformer_model_qualiamachine_pipeline_en_5.5.1_3.0_1737836452059.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_transformer_model_qualiamachine_pipeline_en_5.5.1_3.0_1737836452059.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_transformer_model_qualiamachine_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_transformer_model_qualiamachine_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_transformer_model_qualiamachine_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/qualiaMachine/my-awesome-transformer-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-burmese_model_paoloant_en.md b/docs/_posts/ahmedlone127/2025-01-25-burmese_model_paoloant_en.md
new file mode 100644
index 00000000000000..93c0fcb2e3af09
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-burmese_model_paoloant_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_model_paoloant BertEmbeddings from Paoloant
+author: John Snow Labs
+name: burmese_model_paoloant
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_model_paoloant` is a English model originally trained by Paoloant.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_model_paoloant_en_5.5.1_3.0_1737821348181.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_model_paoloant_en_5.5.1_3.0_1737821348181.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("burmese_model_paoloant","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("burmese_model_paoloant","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_model_paoloant|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/Paoloant/my-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-burmese_model_paoloant_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-burmese_model_paoloant_pipeline_en.md
new file mode 100644
index 00000000000000..263e54ee266385
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-burmese_model_paoloant_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_model_paoloant_pipeline pipeline BertEmbeddings from Paoloant
+author: John Snow Labs
+name: burmese_model_paoloant_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_model_paoloant_pipeline` is a English model originally trained by Paoloant.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_model_paoloant_pipeline_en_5.5.1_3.0_1737821371406.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_model_paoloant_pipeline_en_5.5.1_3.0_1737821371406.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_model_paoloant_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_model_paoloant_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_model_paoloant_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/Paoloant/my-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-burmese_qa_model_amine101_en.md b/docs/_posts/ahmedlone127/2025-01-25-burmese_qa_model_amine101_en.md
new file mode 100644
index 00000000000000..1709885af7973a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-burmese_qa_model_amine101_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_qa_model_amine101 BertForQuestionAnswering from Amine101
+author: John Snow Labs
+name: burmese_qa_model_amine101
+date: 2025-01-25
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_qa_model_amine101` is a English model originally trained by Amine101.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_qa_model_amine101_en_5.5.1_3.0_1737813701779.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_qa_model_amine101_en_5.5.1_3.0_1737813701779.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("burmese_qa_model_amine101","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("burmese_qa_model_amine101", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_qa_model_amine101|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|551.5 MB|
+
+## References
+
+https://huggingface.co/Amine101/my_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-burmese_qa_model_amine101_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-burmese_qa_model_amine101_pipeline_en.md
new file mode 100644
index 00000000000000..52f84e9794fcdf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-burmese_qa_model_amine101_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_qa_model_amine101_pipeline pipeline BertForQuestionAnswering from Amine101
+author: John Snow Labs
+name: burmese_qa_model_amine101_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_qa_model_amine101_pipeline` is a English model originally trained by Amine101.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_qa_model_amine101_pipeline_en_5.5.1_3.0_1737813730702.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_qa_model_amine101_pipeline_en_5.5.1_3.0_1737813730702.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_qa_model_amine101_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_qa_model_amine101_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_qa_model_amine101_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|551.5 MB|
+
+## References
+
+https://huggingface.co/Amine101/my_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-burmese_sentiment_analysis_model_chawki17_en.md b/docs/_posts/ahmedlone127/2025-01-25-burmese_sentiment_analysis_model_chawki17_en.md
new file mode 100644
index 00000000000000..8d53836a9be7b7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-burmese_sentiment_analysis_model_chawki17_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_sentiment_analysis_model_chawki17 DistilBertForSequenceClassification from chawki17
+author: John Snow Labs
+name: burmese_sentiment_analysis_model_chawki17
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_sentiment_analysis_model_chawki17` is a English model originally trained by chawki17.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_sentiment_analysis_model_chawki17_en_5.5.1_3.0_1737837858143.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_sentiment_analysis_model_chawki17_en_5.5.1_3.0_1737837858143.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_sentiment_analysis_model_chawki17","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_sentiment_analysis_model_chawki17", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_sentiment_analysis_model_chawki17|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/chawki17/My_Sentiment_Analysis_Model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-burmese_sentiment_analysis_model_chawki17_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-burmese_sentiment_analysis_model_chawki17_pipeline_en.md
new file mode 100644
index 00000000000000..c0c3f656d27a7c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-burmese_sentiment_analysis_model_chawki17_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_sentiment_analysis_model_chawki17_pipeline pipeline DistilBertForSequenceClassification from chawki17
+author: John Snow Labs
+name: burmese_sentiment_analysis_model_chawki17_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_sentiment_analysis_model_chawki17_pipeline` is a English model originally trained by chawki17.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_sentiment_analysis_model_chawki17_pipeline_en_5.5.1_3.0_1737837871985.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_sentiment_analysis_model_chawki17_pipeline_en_5.5.1_3.0_1737837871985.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_sentiment_analysis_model_chawki17_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_sentiment_analysis_model_chawki17_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_sentiment_analysis_model_chawki17_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/chawki17/My_Sentiment_Analysis_Model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-burmese_sms_model_en.md b/docs/_posts/ahmedlone127/2025-01-25-burmese_sms_model_en.md
new file mode 100644
index 00000000000000..637fb579f9f6e2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-burmese_sms_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_sms_model DistilBertForSequenceClassification from icy123
+author: John Snow Labs
+name: burmese_sms_model
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_sms_model` is a English model originally trained by icy123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_sms_model_en_5.5.1_3.0_1737822796267.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_sms_model_en_5.5.1_3.0_1737822796267.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_sms_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_sms_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_sms_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|507.6 MB|
+
+## References
+
+https://huggingface.co/icy123/my_sms_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-burmese_sms_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-burmese_sms_model_pipeline_en.md
new file mode 100644
index 00000000000000..6b6e803a4e8b1c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-burmese_sms_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_sms_model_pipeline pipeline DistilBertForSequenceClassification from icy123
+author: John Snow Labs
+name: burmese_sms_model_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_sms_model_pipeline` is a English model originally trained by icy123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_sms_model_pipeline_en_5.5.1_3.0_1737822822448.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_sms_model_pipeline_en_5.5.1_3.0_1737822822448.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_sms_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_sms_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_sms_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|507.6 MB|
+
+## References
+
+https://huggingface.co/icy123/my_sms_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-burmese_yoruba_translator_new1_en.md b/docs/_posts/ahmedlone127/2025-01-25-burmese_yoruba_translator_new1_en.md
new file mode 100644
index 00000000000000..02fc285519600c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-burmese_yoruba_translator_new1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_yoruba_translator_new1 MarianTransformer from Harcuracy
+author: John Snow Labs
+name: burmese_yoruba_translator_new1
+date: 2025-01-25
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_yoruba_translator_new1` is a English model originally trained by Harcuracy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_yoruba_translator_new1_en_5.5.1_3.0_1737827808524.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_yoruba_translator_new1_en_5.5.1_3.0_1737827808524.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("burmese_yoruba_translator_new1","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("burmese_yoruba_translator_new1","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_yoruba_translator_new1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|414.5 MB|
+
+## References
+
+https://huggingface.co/Harcuracy/my_yoruba_translator_new1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-burmese_yoruba_translator_new1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-burmese_yoruba_translator_new1_pipeline_en.md
new file mode 100644
index 00000000000000..766f0ad880dfd4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-burmese_yoruba_translator_new1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_yoruba_translator_new1_pipeline pipeline MarianTransformer from Harcuracy
+author: John Snow Labs
+name: burmese_yoruba_translator_new1_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_yoruba_translator_new1_pipeline` is a English model originally trained by Harcuracy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_yoruba_translator_new1_pipeline_en_5.5.1_3.0_1737827829493.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_yoruba_translator_new1_pipeline_en_5.5.1_3.0_1737827829493.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_yoruba_translator_new1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_yoruba_translator_new1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_yoruba_translator_new1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|415.1 MB|
+
+## References
+
+https://huggingface.co/Harcuracy/my_yoruba_translator_new1
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-canadian_address_checker_on_en.md b/docs/_posts/ahmedlone127/2025-01-25-canadian_address_checker_on_en.md
new file mode 100644
index 00000000000000..7218ecb6cfd9ca
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-canadian_address_checker_on_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English canadian_address_checker_on BertEmbeddings from Hythcliff
+author: John Snow Labs
+name: canadian_address_checker_on
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`canadian_address_checker_on` is a English model originally trained by Hythcliff.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/canadian_address_checker_on_en_5.5.1_3.0_1737846657188.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/canadian_address_checker_on_en_5.5.1_3.0_1737846657188.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("canadian_address_checker_on","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("canadian_address_checker_on","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|canadian_address_checker_on|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|406.2 MB|
+
+## References
+
+https://huggingface.co/Hythcliff/canadian-address-checker-on
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-canadian_address_checker_on_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-canadian_address_checker_on_pipeline_en.md
new file mode 100644
index 00000000000000..33fa3daedd0211
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-canadian_address_checker_on_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English canadian_address_checker_on_pipeline pipeline BertEmbeddings from Hythcliff
+author: John Snow Labs
+name: canadian_address_checker_on_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`canadian_address_checker_on_pipeline` is a English model originally trained by Hythcliff.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/canadian_address_checker_on_pipeline_en_5.5.1_3.0_1737846677127.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/canadian_address_checker_on_pipeline_en_5.5.1_3.0_1737846677127.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("canadian_address_checker_on_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("canadian_address_checker_on_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|canadian_address_checker_on_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.2 MB|
+
+## References
+
+https://huggingface.co/Hythcliff/canadian-address-checker-on
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-caprica_gpt2_small_x81_en.md b/docs/_posts/ahmedlone127/2025-01-25-caprica_gpt2_small_x81_en.md
new file mode 100644
index 00000000000000..aaae97d8a5147b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-caprica_gpt2_small_x81_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English caprica_gpt2_small_x81 GPT2Transformer from stanford-crfm
+author: John Snow Labs
+name: caprica_gpt2_small_x81
+date: 2025-01-25
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`caprica_gpt2_small_x81` is a English model originally trained by stanford-crfm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/caprica_gpt2_small_x81_en_5.5.1_3.0_1737766208526.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/caprica_gpt2_small_x81_en_5.5.1_3.0_1737766208526.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("caprica_gpt2_small_x81","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("caprica_gpt2_small_x81","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|caprica_gpt2_small_x81|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|299.3 MB|
+
+## References
+
+https://huggingface.co/stanford-crfm/caprica-gpt2-small-x81
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-caprica_gpt2_small_x81_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-caprica_gpt2_small_x81_pipeline_en.md
new file mode 100644
index 00000000000000..4c55dc96453893
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-caprica_gpt2_small_x81_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English caprica_gpt2_small_x81_pipeline pipeline GPT2Transformer from stanford-crfm
+author: John Snow Labs
+name: caprica_gpt2_small_x81_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`caprica_gpt2_small_x81_pipeline` is a English model originally trained by stanford-crfm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/caprica_gpt2_small_x81_pipeline_en_5.5.1_3.0_1737766295507.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/caprica_gpt2_small_x81_pipeline_en_5.5.1_3.0_1737766295507.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("caprica_gpt2_small_x81_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("caprica_gpt2_small_x81_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|caprica_gpt2_small_x81_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|299.3 MB|
+
+## References
+
+https://huggingface.co/stanford-crfm/caprica-gpt2-small-x81
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-car_vs_rest_en.md b/docs/_posts/ahmedlone127/2025-01-25-car_vs_rest_en.md
new file mode 100644
index 00000000000000..9ad95e986df17a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-car_vs_rest_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English car_vs_rest SwinForImageClassification from Nekshay
+author: John Snow Labs
+name: car_vs_rest
+date: 2025-01-25
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`car_vs_rest` is a English model originally trained by Nekshay.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/car_vs_rest_en_5.5.1_3.0_1737763263988.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/car_vs_rest_en_5.5.1_3.0_1737763263988.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""car_vs_rest","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("car_vs_rest","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|car_vs_rest|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|649.8 MB|
+
+## References
+
+https://huggingface.co/Nekshay/Car_VS_Rest
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-car_vs_rest_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-car_vs_rest_pipeline_en.md
new file mode 100644
index 00000000000000..8fb13484784691
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-car_vs_rest_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English car_vs_rest_pipeline pipeline SwinForImageClassification from Nekshay
+author: John Snow Labs
+name: car_vs_rest_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`car_vs_rest_pipeline` is a English model originally trained by Nekshay.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/car_vs_rest_pipeline_en_5.5.1_3.0_1737763301712.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/car_vs_rest_pipeline_en_5.5.1_3.0_1737763301712.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("car_vs_rest_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("car_vs_rest_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|car_vs_rest_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|649.8 MB|
+
+## References
+
+https://huggingface.co/Nekshay/Car_VS_Rest
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-cardinal_news_classifier_en.md b/docs/_posts/ahmedlone127/2025-01-25-cardinal_news_classifier_en.md
new file mode 100644
index 00000000000000..514c2b1103522a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-cardinal_news_classifier_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English cardinal_news_classifier DistilBertForSequenceClassification from rehmatsg
+author: John Snow Labs
+name: cardinal_news_classifier
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cardinal_news_classifier` is a English model originally trained by rehmatsg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cardinal_news_classifier_en_5.5.1_3.0_1737811676472.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cardinal_news_classifier_en_5.5.1_3.0_1737811676472.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("cardinal_news_classifier","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("cardinal_news_classifier", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cardinal_news_classifier|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/rehmatsg/cardinal-news-classifier
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-cardinal_news_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-cardinal_news_classifier_pipeline_en.md
new file mode 100644
index 00000000000000..1380e81121cb12
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-cardinal_news_classifier_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English cardinal_news_classifier_pipeline pipeline DistilBertForSequenceClassification from rehmatsg
+author: John Snow Labs
+name: cardinal_news_classifier_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cardinal_news_classifier_pipeline` is a English model originally trained by rehmatsg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cardinal_news_classifier_pipeline_en_5.5.1_3.0_1737811689659.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cardinal_news_classifier_pipeline_en_5.5.1_3.0_1737811689659.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("cardinal_news_classifier_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cardinal_news_classifier_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cardinal_news_classifier_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.6 MB|
+
+## References
+
+https://huggingface.co/rehmatsg/cardinal-news-classifier
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-celebrimbor_gpt2_medium_x81_en.md b/docs/_posts/ahmedlone127/2025-01-25-celebrimbor_gpt2_medium_x81_en.md
new file mode 100644
index 00000000000000..5427ffcbbf6e6e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-celebrimbor_gpt2_medium_x81_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English celebrimbor_gpt2_medium_x81 GPT2Transformer from stanford-crfm
+author: John Snow Labs
+name: celebrimbor_gpt2_medium_x81
+date: 2025-01-25
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`celebrimbor_gpt2_medium_x81` is a English model originally trained by stanford-crfm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/celebrimbor_gpt2_medium_x81_en_5.5.1_3.0_1737765942267.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/celebrimbor_gpt2_medium_x81_en_5.5.1_3.0_1737765942267.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("celebrimbor_gpt2_medium_x81","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("celebrimbor_gpt2_medium_x81","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|celebrimbor_gpt2_medium_x81|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|852.2 MB|
+
+## References
+
+https://huggingface.co/stanford-crfm/celebrimbor-gpt2-medium-x81
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-celebrimbor_gpt2_medium_x81_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-celebrimbor_gpt2_medium_x81_pipeline_en.md
new file mode 100644
index 00000000000000..3a0ca2c107de69
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-celebrimbor_gpt2_medium_x81_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English celebrimbor_gpt2_medium_x81_pipeline pipeline GPT2Transformer from stanford-crfm
+author: John Snow Labs
+name: celebrimbor_gpt2_medium_x81_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`celebrimbor_gpt2_medium_x81_pipeline` is a English model originally trained by stanford-crfm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/celebrimbor_gpt2_medium_x81_pipeline_en_5.5.1_3.0_1737766185745.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/celebrimbor_gpt2_medium_x81_pipeline_en_5.5.1_3.0_1737766185745.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("celebrimbor_gpt2_medium_x81_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("celebrimbor_gpt2_medium_x81_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|celebrimbor_gpt2_medium_x81_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|852.2 MB|
+
+## References
+
+https://huggingface.co/stanford-crfm/celebrimbor-gpt2-medium-x81
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-cerebras_gpt_111m_en.md b/docs/_posts/ahmedlone127/2025-01-25-cerebras_gpt_111m_en.md
new file mode 100644
index 00000000000000..5fc8990d1d7337
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-cerebras_gpt_111m_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English cerebras_gpt_111m GPT2Transformer from cerebras
+author: John Snow Labs
+name: cerebras_gpt_111m
+date: 2025-01-25
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cerebras_gpt_111m` is a English model originally trained by cerebras.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cerebras_gpt_111m_en_5.5.1_3.0_1737826578681.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cerebras_gpt_111m_en_5.5.1_3.0_1737826578681.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("cerebras_gpt_111m","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("cerebras_gpt_111m","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cerebras_gpt_111m|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|417.4 MB|
+
+## References
+
+https://huggingface.co/cerebras/Cerebras-GPT-111M
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-cerebras_gpt_111m_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-cerebras_gpt_111m_pipeline_en.md
new file mode 100644
index 00000000000000..e90ff1b9e76470
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-cerebras_gpt_111m_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English cerebras_gpt_111m_pipeline pipeline GPT2Transformer from cerebras
+author: John Snow Labs
+name: cerebras_gpt_111m_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cerebras_gpt_111m_pipeline` is a English model originally trained by cerebras.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cerebras_gpt_111m_pipeline_en_5.5.1_3.0_1737826599683.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cerebras_gpt_111m_pipeline_en_5.5.1_3.0_1737826599683.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("cerebras_gpt_111m_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cerebras_gpt_111m_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cerebras_gpt_111m_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|417.4 MB|
+
+## References
+
+https://huggingface.co/cerebras/Cerebras-GPT-111M
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-clasificadormotivomoradistilespanol10_05_en.md b/docs/_posts/ahmedlone127/2025-01-25-clasificadormotivomoradistilespanol10_05_en.md
new file mode 100644
index 00000000000000..b8775208ba0661
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-clasificadormotivomoradistilespanol10_05_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English clasificadormotivomoradistilespanol10_05 DistilBertForSequenceClassification from Arodrigo
+author: John Snow Labs
+name: clasificadormotivomoradistilespanol10_05
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clasificadormotivomoradistilespanol10_05` is a English model originally trained by Arodrigo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clasificadormotivomoradistilespanol10_05_en_5.5.1_3.0_1737822333361.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clasificadormotivomoradistilespanol10_05_en_5.5.1_3.0_1737822333361.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("clasificadormotivomoradistilespanol10_05","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("clasificadormotivomoradistilespanol10_05", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clasificadormotivomoradistilespanol10_05|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|252.4 MB|
+
+## References
+
+https://huggingface.co/Arodrigo/ClasificadorMotivoMoraDistilEspanol10-05
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-clasificadormotivomoradistilespanol10_05_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-clasificadormotivomoradistilespanol10_05_pipeline_en.md
new file mode 100644
index 00000000000000..54d03beff0081e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-clasificadormotivomoradistilespanol10_05_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English clasificadormotivomoradistilespanol10_05_pipeline pipeline DistilBertForSequenceClassification from Arodrigo
+author: John Snow Labs
+name: clasificadormotivomoradistilespanol10_05_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clasificadormotivomoradistilespanol10_05_pipeline` is a English model originally trained by Arodrigo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clasificadormotivomoradistilespanol10_05_pipeline_en_5.5.1_3.0_1737822346743.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clasificadormotivomoradistilespanol10_05_pipeline_en_5.5.1_3.0_1737822346743.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("clasificadormotivomoradistilespanol10_05_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("clasificadormotivomoradistilespanol10_05_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clasificadormotivomoradistilespanol10_05_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|252.5 MB|
+
+## References
+
+https://huggingface.co/Arodrigo/ClasificadorMotivoMoraDistilEspanol10-05
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-classification_model_albert_en.md b/docs/_posts/ahmedlone127/2025-01-25-classification_model_albert_en.md
new file mode 100644
index 00000000000000..619a3809cb02d8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-classification_model_albert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English classification_model_albert AlbertForSequenceClassification from zxdexpo
+author: John Snow Labs
+name: classification_model_albert
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, albert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`classification_model_albert` is a English model originally trained by zxdexpo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/classification_model_albert_en_5.5.1_3.0_1737847092766.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/classification_model_albert_en_5.5.1_3.0_1737847092766.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = AlbertForSequenceClassification.pretrained("classification_model_albert","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = AlbertForSequenceClassification.pretrained("classification_model_albert", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|classification_model_albert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/zxdexpo/classification_model_albert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-classification_model_albert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-classification_model_albert_pipeline_en.md
new file mode 100644
index 00000000000000..d565001c9a085f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-classification_model_albert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English classification_model_albert_pipeline pipeline AlbertForSequenceClassification from zxdexpo
+author: John Snow Labs
+name: classification_model_albert_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`classification_model_albert_pipeline` is a English model originally trained by zxdexpo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/classification_model_albert_pipeline_en_5.5.1_3.0_1737847095202.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/classification_model_albert_pipeline_en_5.5.1_3.0_1737847095202.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("classification_model_albert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("classification_model_albert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|classification_model_albert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/zxdexpo/classification_model_albert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-companyx_customer_support_ticket_routing_distilbert_en.md b/docs/_posts/ahmedlone127/2025-01-25-companyx_customer_support_ticket_routing_distilbert_en.md
new file mode 100644
index 00000000000000..3c7518ebb2caf1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-companyx_customer_support_ticket_routing_distilbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English companyx_customer_support_ticket_routing_distilbert DistilBertForSequenceClassification from interneuronai
+author: John Snow Labs
+name: companyx_customer_support_ticket_routing_distilbert
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`companyx_customer_support_ticket_routing_distilbert` is a English model originally trained by interneuronai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/companyx_customer_support_ticket_routing_distilbert_en_5.5.1_3.0_1737822213112.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/companyx_customer_support_ticket_routing_distilbert_en_5.5.1_3.0_1737822213112.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("companyx_customer_support_ticket_routing_distilbert","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("companyx_customer_support_ticket_routing_distilbert", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|companyx_customer_support_ticket_routing_distilbert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|507.7 MB|
+
+## References
+
+https://huggingface.co/interneuronai/companyx_customer_support_ticket_routing_distilbert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-companyx_customer_support_ticket_routing_distilbert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-companyx_customer_support_ticket_routing_distilbert_pipeline_en.md
new file mode 100644
index 00000000000000..1e7570b46b28d6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-companyx_customer_support_ticket_routing_distilbert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English companyx_customer_support_ticket_routing_distilbert_pipeline pipeline DistilBertForSequenceClassification from interneuronai
+author: John Snow Labs
+name: companyx_customer_support_ticket_routing_distilbert_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`companyx_customer_support_ticket_routing_distilbert_pipeline` is a English model originally trained by interneuronai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/companyx_customer_support_ticket_routing_distilbert_pipeline_en_5.5.1_3.0_1737822239541.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/companyx_customer_support_ticket_routing_distilbert_pipeline_en_5.5.1_3.0_1737822239541.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("companyx_customer_support_ticket_routing_distilbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("companyx_customer_support_ticket_routing_distilbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|companyx_customer_support_ticket_routing_distilbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|507.7 MB|
+
+## References
+
+https://huggingface.co/interneuronai/companyx_customer_support_ticket_routing_distilbert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-concretegpt_124m_128ctx_strict_small_seq_bins_en.md b/docs/_posts/ahmedlone127/2025-01-25-concretegpt_124m_128ctx_strict_small_seq_bins_en.md
new file mode 100644
index 00000000000000..ab14d97f9a1dfc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-concretegpt_124m_128ctx_strict_small_seq_bins_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English concretegpt_124m_128ctx_strict_small_seq_bins GPT2Transformer from colinglab
+author: John Snow Labs
+name: concretegpt_124m_128ctx_strict_small_seq_bins
+date: 2025-01-25
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`concretegpt_124m_128ctx_strict_small_seq_bins` is a English model originally trained by colinglab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/concretegpt_124m_128ctx_strict_small_seq_bins_en_5.5.1_3.0_1737764888916.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/concretegpt_124m_128ctx_strict_small_seq_bins_en_5.5.1_3.0_1737764888916.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("concretegpt_124m_128ctx_strict_small_seq_bins","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("concretegpt_124m_128ctx_strict_small_seq_bins","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|concretegpt_124m_128ctx_strict_small_seq_bins|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.2 MB|
+
+## References
+
+https://huggingface.co/colinglab/ConcreteGPT-124M-128ctx-Strict-Small-seq_bins
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-concretegpt_124m_128ctx_strict_small_seq_bins_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-concretegpt_124m_128ctx_strict_small_seq_bins_pipeline_en.md
new file mode 100644
index 00000000000000..f3e0e5fdeb0242
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-concretegpt_124m_128ctx_strict_small_seq_bins_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English concretegpt_124m_128ctx_strict_small_seq_bins_pipeline pipeline GPT2Transformer from colinglab
+author: John Snow Labs
+name: concretegpt_124m_128ctx_strict_small_seq_bins_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`concretegpt_124m_128ctx_strict_small_seq_bins_pipeline` is a English model originally trained by colinglab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/concretegpt_124m_128ctx_strict_small_seq_bins_pipeline_en_5.5.1_3.0_1737764913508.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/concretegpt_124m_128ctx_strict_small_seq_bins_pipeline_en_5.5.1_3.0_1737764913508.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("concretegpt_124m_128ctx_strict_small_seq_bins_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("concretegpt_124m_128ctx_strict_small_seq_bins_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|concretegpt_124m_128ctx_strict_small_seq_bins_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.2 MB|
+
+## References
+
+https://huggingface.co/colinglab/ConcreteGPT-124M-128ctx-Strict-Small-seq_bins
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-convbert_base_turkish_cased_offensive_mlm_pipeline_tr.md b/docs/_posts/ahmedlone127/2025-01-25-convbert_base_turkish_cased_offensive_mlm_pipeline_tr.md
new file mode 100644
index 00000000000000..516558763d803c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-convbert_base_turkish_cased_offensive_mlm_pipeline_tr.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Turkish convbert_base_turkish_cased_offensive_mlm_pipeline pipeline BertEmbeddings from Overfit-GM
+author: John Snow Labs
+name: convbert_base_turkish_cased_offensive_mlm_pipeline
+date: 2025-01-25
+tags: [tr, open_source, pipeline, onnx]
+task: Embeddings
+language: tr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`convbert_base_turkish_cased_offensive_mlm_pipeline` is a Turkish model originally trained by Overfit-GM.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/convbert_base_turkish_cased_offensive_mlm_pipeline_tr_5.5.1_3.0_1737785429439.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/convbert_base_turkish_cased_offensive_mlm_pipeline_tr_5.5.1_3.0_1737785429439.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("convbert_base_turkish_cased_offensive_mlm_pipeline", lang = "tr")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("convbert_base_turkish_cased_offensive_mlm_pipeline", lang = "tr")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|convbert_base_turkish_cased_offensive_mlm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|tr|
+|Size:|400.1 MB|
+
+## References
+
+https://huggingface.co/Overfit-GM/convbert-base-turkish-cased-offensive-mlm
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-convbert_base_turkish_cased_offensive_mlm_tr.md b/docs/_posts/ahmedlone127/2025-01-25-convbert_base_turkish_cased_offensive_mlm_tr.md
new file mode 100644
index 00000000000000..db663334c55cef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-convbert_base_turkish_cased_offensive_mlm_tr.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Turkish convbert_base_turkish_cased_offensive_mlm BertEmbeddings from Overfit-GM
+author: John Snow Labs
+name: convbert_base_turkish_cased_offensive_mlm
+date: 2025-01-25
+tags: [tr, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: tr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`convbert_base_turkish_cased_offensive_mlm` is a Turkish model originally trained by Overfit-GM.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/convbert_base_turkish_cased_offensive_mlm_tr_5.5.1_3.0_1737785407955.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/convbert_base_turkish_cased_offensive_mlm_tr_5.5.1_3.0_1737785407955.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("convbert_base_turkish_cased_offensive_mlm","tr") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("convbert_base_turkish_cased_offensive_mlm","tr") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|convbert_base_turkish_cased_offensive_mlm|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|tr|
+|Size:|400.1 MB|
+
+## References
+
+https://huggingface.co/Overfit-GM/convbert-base-turkish-cased-offensive-mlm
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-covid_roberta_80_en.md b/docs/_posts/ahmedlone127/2025-01-25-covid_roberta_80_en.md
new file mode 100644
index 00000000000000..04404e717d57c0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-covid_roberta_80_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English covid_roberta_80 RoBertaEmbeddings from timoneda
+author: John Snow Labs
+name: covid_roberta_80
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`covid_roberta_80` is a English model originally trained by timoneda.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/covid_roberta_80_en_5.5.1_3.0_1737797679237.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/covid_roberta_80_en_5.5.1_3.0_1737797679237.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("covid_roberta_80","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("covid_roberta_80","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|covid_roberta_80|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/timoneda/covid_roberta_80
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-covid_roberta_80_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-covid_roberta_80_pipeline_en.md
new file mode 100644
index 00000000000000..a1c806fd8df4cd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-covid_roberta_80_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English covid_roberta_80_pipeline pipeline RoBertaEmbeddings from timoneda
+author: John Snow Labs
+name: covid_roberta_80_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`covid_roberta_80_pipeline` is a English model originally trained by timoneda.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/covid_roberta_80_pipeline_en_5.5.1_3.0_1737797750138.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/covid_roberta_80_pipeline_en_5.5.1_3.0_1737797750138.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("covid_roberta_80_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("covid_roberta_80_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|covid_roberta_80_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/timoneda/covid_roberta_80
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-cs221_deberta_v3_large_finetuned_en.md b/docs/_posts/ahmedlone127/2025-01-25-cs221_deberta_v3_large_finetuned_en.md
new file mode 100644
index 00000000000000..25543ca858eae5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-cs221_deberta_v3_large_finetuned_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English cs221_deberta_v3_large_finetuned DeBertaForSequenceClassification from Kuongan
+author: John Snow Labs
+name: cs221_deberta_v3_large_finetuned
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cs221_deberta_v3_large_finetuned` is a English model originally trained by Kuongan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cs221_deberta_v3_large_finetuned_en_5.5.1_3.0_1737820244204.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cs221_deberta_v3_large_finetuned_en_5.5.1_3.0_1737820244204.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("cs221_deberta_v3_large_finetuned","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("cs221_deberta_v3_large_finetuned", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cs221_deberta_v3_large_finetuned|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/Kuongan/CS221-deberta-v3-large-finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-cs221_deberta_v3_large_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-cs221_deberta_v3_large_finetuned_pipeline_en.md
new file mode 100644
index 00000000000000..5b117fca838405
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-cs221_deberta_v3_large_finetuned_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English cs221_deberta_v3_large_finetuned_pipeline pipeline DeBertaForSequenceClassification from Kuongan
+author: John Snow Labs
+name: cs221_deberta_v3_large_finetuned_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cs221_deberta_v3_large_finetuned_pipeline` is a English model originally trained by Kuongan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cs221_deberta_v3_large_finetuned_pipeline_en_5.5.1_3.0_1737820367120.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cs221_deberta_v3_large_finetuned_pipeline_en_5.5.1_3.0_1737820367120.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("cs221_deberta_v3_large_finetuned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cs221_deberta_v3_large_finetuned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cs221_deberta_v3_large_finetuned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/Kuongan/CS221-deberta-v3-large-finetuned
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-csv_with_des_en.md b/docs/_posts/ahmedlone127/2025-01-25-csv_with_des_en.md
new file mode 100644
index 00000000000000..439ed50f912be1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-csv_with_des_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English csv_with_des DistilBertForSequenceClassification from i-dhilip
+author: John Snow Labs
+name: csv_with_des
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`csv_with_des` is a English model originally trained by i-dhilip.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/csv_with_des_en_5.5.1_3.0_1737811798753.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/csv_with_des_en_5.5.1_3.0_1737811798753.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("csv_with_des","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("csv_with_des", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|csv_with_des|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/i-dhilip/csv_with_des
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-csv_with_des_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-csv_with_des_pipeline_en.md
new file mode 100644
index 00000000000000..f3288b2d3fc07d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-csv_with_des_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English csv_with_des_pipeline pipeline DistilBertForSequenceClassification from i-dhilip
+author: John Snow Labs
+name: csv_with_des_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`csv_with_des_pipeline` is a English model originally trained by i-dhilip.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/csv_with_des_pipeline_en_5.5.1_3.0_1737811812152.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/csv_with_des_pipeline_en_5.5.1_3.0_1737811812152.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("csv_with_des_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("csv_with_des_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|csv_with_des_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/i-dhilip/csv_with_des
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-custom_model_tweets_sentiment_3000_samples_en.md b/docs/_posts/ahmedlone127/2025-01-25-custom_model_tweets_sentiment_3000_samples_en.md
new file mode 100644
index 00000000000000..c4811346a7df56
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-custom_model_tweets_sentiment_3000_samples_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English custom_model_tweets_sentiment_3000_samples DistilBertForSequenceClassification from vipboyhp2208
+author: John Snow Labs
+name: custom_model_tweets_sentiment_3000_samples
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`custom_model_tweets_sentiment_3000_samples` is a English model originally trained by vipboyhp2208.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/custom_model_tweets_sentiment_3000_samples_en_5.5.1_3.0_1737836144442.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/custom_model_tweets_sentiment_3000_samples_en_5.5.1_3.0_1737836144442.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("custom_model_tweets_sentiment_3000_samples","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("custom_model_tweets_sentiment_3000_samples", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|custom_model_tweets_sentiment_3000_samples|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/vipboyhp2208/custom-model-tweets-sentiment-3000-samples
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-custom_model_tweets_sentiment_3000_samples_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-custom_model_tweets_sentiment_3000_samples_pipeline_en.md
new file mode 100644
index 00000000000000..a2d9ea1adf6797
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-custom_model_tweets_sentiment_3000_samples_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English custom_model_tweets_sentiment_3000_samples_pipeline pipeline DistilBertForSequenceClassification from vipboyhp2208
+author: John Snow Labs
+name: custom_model_tweets_sentiment_3000_samples_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`custom_model_tweets_sentiment_3000_samples_pipeline` is a English model originally trained by vipboyhp2208.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/custom_model_tweets_sentiment_3000_samples_pipeline_en_5.5.1_3.0_1737836156966.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/custom_model_tweets_sentiment_3000_samples_pipeline_en_5.5.1_3.0_1737836156966.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("custom_model_tweets_sentiment_3000_samples_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("custom_model_tweets_sentiment_3000_samples_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|custom_model_tweets_sentiment_3000_samples_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/vipboyhp2208/custom-model-tweets-sentiment-3000-samples
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-custom_qa_model_en.md b/docs/_posts/ahmedlone127/2025-01-25-custom_qa_model_en.md
new file mode 100644
index 00000000000000..99f91d194dd986
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-custom_qa_model_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English custom_qa_model T5Transformer from rsurigi
+author: John Snow Labs
+name: custom_qa_model
+date: 2025-01-25
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`custom_qa_model` is a English model originally trained by rsurigi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/custom_qa_model_en_5.5.1_3.0_1737849216064.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/custom_qa_model_en_5.5.1_3.0_1737849216064.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("custom_qa_model","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("custom_qa_model", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|custom_qa_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|213.1 MB|
+
+## References
+
+https://huggingface.co/rsurigi/custom-qa-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-custom_qa_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-custom_qa_model_pipeline_en.md
new file mode 100644
index 00000000000000..b273caa26b89c8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-custom_qa_model_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English custom_qa_model_pipeline pipeline T5Transformer from rsurigi
+author: John Snow Labs
+name: custom_qa_model_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`custom_qa_model_pipeline` is a English model originally trained by rsurigi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/custom_qa_model_pipeline_en_5.5.1_3.0_1737849244102.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/custom_qa_model_pipeline_en_5.5.1_3.0_1737849244102.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("custom_qa_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("custom_qa_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|custom_qa_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|213.1 MB|
+
+## References
+
+https://huggingface.co/rsurigi/custom-qa-model
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-custommodel_yelp_snoopy47_en.md b/docs/_posts/ahmedlone127/2025-01-25-custommodel_yelp_snoopy47_en.md
new file mode 100644
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--- /dev/null
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@@ -0,0 +1,94 @@
+---
+layout: model
+title: English custommodel_yelp_snoopy47 DistilBertForSequenceClassification from Snoopy47
+author: John Snow Labs
+name: custommodel_yelp_snoopy47
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`custommodel_yelp_snoopy47` is a English model originally trained by Snoopy47.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/custommodel_yelp_snoopy47_en_5.5.1_3.0_1737821921752.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/custommodel_yelp_snoopy47_en_5.5.1_3.0_1737821921752.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("custommodel_yelp_snoopy47","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("custommodel_yelp_snoopy47", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|custommodel_yelp_snoopy47|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Snoopy47/CustomModel_yelp
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-custommodel_yelp_snoopy47_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-custommodel_yelp_snoopy47_pipeline_en.md
new file mode 100644
index 00000000000000..1f06ba8dcc0a86
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-custommodel_yelp_snoopy47_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English custommodel_yelp_snoopy47_pipeline pipeline DistilBertForSequenceClassification from Snoopy47
+author: John Snow Labs
+name: custommodel_yelp_snoopy47_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`custommodel_yelp_snoopy47_pipeline` is a English model originally trained by Snoopy47.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/custommodel_yelp_snoopy47_pipeline_en_5.5.1_3.0_1737821935274.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/custommodel_yelp_snoopy47_pipeline_en_5.5.1_3.0_1737821935274.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("custommodel_yelp_snoopy47_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("custommodel_yelp_snoopy47_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|custommodel_yelp_snoopy47_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Snoopy47/CustomModel_yelp
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-cybert_dnrti_en.md b/docs/_posts/ahmedlone127/2025-01-25-cybert_dnrti_en.md
new file mode 100644
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--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-cybert_dnrti_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English cybert_dnrti RoBertaForTokenClassification from anonymouspd
+author: John Snow Labs
+name: cybert_dnrti
+date: 2025-01-25
+tags: [roberta, en, open_source, token_classification, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cybert_dnrti` is a English model originally trained by anonymouspd.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cybert_dnrti_en_5.5.1_3.0_1737808117700.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cybert_dnrti_en_5.5.1_3.0_1737808117700.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+    
+tokenizer = Tokenizer() \
+        .setInputCols(["document"]) \
+        .setOutputCol("token")
+        
+    
+tokenClassifier = RoBertaForTokenClassification.pretrained("cybert_dnrti","en") \
+            .setInputCols(["document","token"]) \
+            .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val tokenizer = Tokenizer() \
+        .setInputCols(Array("document")) \
+        .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification  
+    .pretrained("cybert_dnrti", "en")
+    .setInputCols(Array("document","token")) 
+    .setOutputCol("ner") 
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cybert_dnrti|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|311.3 MB|
+
+## References
+
+References
+
+https://huggingface.co/anonymouspd/CyBERT-DNRTI
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-cybert_dnrti_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-cybert_dnrti_pipeline_en.md
new file mode 100644
index 00000000000000..abb38e2983f3c0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-cybert_dnrti_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English cybert_dnrti_pipeline pipeline RoBertaForTokenClassification from Cyber-ThreaD
+author: John Snow Labs
+name: cybert_dnrti_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cybert_dnrti_pipeline` is a English model originally trained by Cyber-ThreaD.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cybert_dnrti_pipeline_en_5.5.1_3.0_1737808134027.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cybert_dnrti_pipeline_en_5.5.1_3.0_1737808134027.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("cybert_dnrti_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cybert_dnrti_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cybert_dnrti_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|311.4 MB|
+
+## References
+
+https://huggingface.co/Cyber-ThreaD/CyBERT-DNRTI
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-d4data_on_babe_en.md b/docs/_posts/ahmedlone127/2025-01-25-d4data_on_babe_en.md
new file mode 100644
index 00000000000000..50ef63c02aec99
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-d4data_on_babe_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English d4data_on_babe DistilBertForSequenceClassification from Onunes
+author: John Snow Labs
+name: d4data_on_babe
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`d4data_on_babe` is a English model originally trained by Onunes.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/d4data_on_babe_en_5.5.1_3.0_1737821792779.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/d4data_on_babe_en_5.5.1_3.0_1737821792779.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("d4data_on_babe","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("d4data_on_babe", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|d4data_on_babe|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.4 MB|
+
+## References
+
+https://huggingface.co/Onunes/D4DATA-on-BABE
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-d4data_on_babe_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-d4data_on_babe_pipeline_en.md
new file mode 100644
index 00000000000000..57325ceb6b1305
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-d4data_on_babe_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English d4data_on_babe_pipeline pipeline DistilBertForSequenceClassification from Onunes
+author: John Snow Labs
+name: d4data_on_babe_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`d4data_on_babe_pipeline` is a English model originally trained by Onunes.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/d4data_on_babe_pipeline_en_5.5.1_3.0_1737821816182.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/d4data_on_babe_pipeline_en_5.5.1_3.0_1737821816182.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("d4data_on_babe_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("d4data_on_babe_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|d4data_on_babe_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Onunes/D4DATA-on-BABE
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-darbert_en.md b/docs/_posts/ahmedlone127/2025-01-25-darbert_en.md
new file mode 100644
index 00000000000000..7c8366f0efece3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-darbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English darbert RoBertaEmbeddings from ahmedJaafari
+author: John Snow Labs
+name: darbert
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`darbert` is a English model originally trained by ahmedJaafari.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/darbert_en_5.5.1_3.0_1737797402636.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/darbert_en_5.5.1_3.0_1737797402636.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("darbert","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("darbert","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|darbert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|319.4 MB|
+
+## References
+
+https://huggingface.co/ahmedJaafari/DarBert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-darbert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-darbert_pipeline_en.md
new file mode 100644
index 00000000000000..82415289d4cf67
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-darbert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English darbert_pipeline pipeline RoBertaEmbeddings from ahmedJaafari
+author: John Snow Labs
+name: darbert_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`darbert_pipeline` is a English model originally trained by ahmedJaafari.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/darbert_pipeline_en_5.5.1_3.0_1737797420844.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/darbert_pipeline_en_5.5.1_3.0_1737797420844.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("darbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("darbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|darbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|319.4 MB|
+
+## References
+
+https://huggingface.co/ahmedJaafari/DarBert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-darijatranslation_en.md b/docs/_posts/ahmedlone127/2025-01-25-darijatranslation_en.md
new file mode 100644
index 00000000000000..2d1650a1d60134
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-darijatranslation_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English darijatranslation MarianTransformer from wiamChair2
+author: John Snow Labs
+name: darijatranslation
+date: 2025-01-25
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`darijatranslation` is a English model originally trained by wiamChair2.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/darijatranslation_en_5.5.1_3.0_1737780847112.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/darijatranslation_en_5.5.1_3.0_1737780847112.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("darijatranslation","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("darijatranslation","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|darijatranslation|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|409.6 MB|
+
+## References
+
+https://huggingface.co/wiamChair2/DarijaTranslation
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-darijatranslation_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-darijatranslation_pipeline_en.md
new file mode 100644
index 00000000000000..0441fd53b9e8f2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-darijatranslation_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English darijatranslation_pipeline pipeline MarianTransformer from wiamChair2
+author: John Snow Labs
+name: darijatranslation_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`darijatranslation_pipeline` is a English model originally trained by wiamChair2.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/darijatranslation_pipeline_en_5.5.1_3.0_1737780868648.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/darijatranslation_pipeline_en_5.5.1_3.0_1737780868648.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("darijatranslation_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("darijatranslation_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|darijatranslation_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.2 MB|
+
+## References
+
+https://huggingface.co/wiamChair2/DarijaTranslation
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-db_aca2_4_2_en.md b/docs/_posts/ahmedlone127/2025-01-25-db_aca2_4_2_en.md
new file mode 100644
index 00000000000000..2750cca4905506
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-db_aca2_4_2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English db_aca2_4_2 DistilBertForSequenceClassification from exala
+author: John Snow Labs
+name: db_aca2_4_2
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`db_aca2_4_2` is a English model originally trained by exala.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/db_aca2_4_2_en_5.5.1_3.0_1737836989296.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/db_aca2_4_2_en_5.5.1_3.0_1737836989296.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("db_aca2_4_2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("db_aca2_4_2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|db_aca2_4_2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.6 MB|
+
+## References
+
+https://huggingface.co/exala/db_aca2_4.2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-db_aca2_4_2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-db_aca2_4_2_pipeline_en.md
new file mode 100644
index 00000000000000..0ff985f29ecd41
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-db_aca2_4_2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English db_aca2_4_2_pipeline pipeline DistilBertForSequenceClassification from exala
+author: John Snow Labs
+name: db_aca2_4_2_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`db_aca2_4_2_pipeline` is a English model originally trained by exala.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/db_aca2_4_2_pipeline_en_5.5.1_3.0_1737837002554.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/db_aca2_4_2_pipeline_en_5.5.1_3.0_1737837002554.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("db_aca2_4_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("db_aca2_4_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|db_aca2_4_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.6 MB|
+
+## References
+
+https://huggingface.co/exala/db_aca2_4.2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-ddi_pubmedbert_abstract_en.md b/docs/_posts/ahmedlone127/2025-01-25-ddi_pubmedbert_abstract_en.md
new file mode 100644
index 00000000000000..639bc61b8410f8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-ddi_pubmedbert_abstract_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ddi_pubmedbert_abstract BertForSequenceClassification from jialicheng
+author: John Snow Labs
+name: ddi_pubmedbert_abstract
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ddi_pubmedbert_abstract` is a English model originally trained by jialicheng.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ddi_pubmedbert_abstract_en_5.5.1_3.0_1737800818828.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ddi_pubmedbert_abstract_en_5.5.1_3.0_1737800818828.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("ddi_pubmedbert_abstract","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("ddi_pubmedbert_abstract", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ddi_pubmedbert_abstract|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|410.3 MB|
+
+## References
+
+https://huggingface.co/jialicheng/ddi-pubmedbert-abstract
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-ddi_pubmedbert_abstract_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-ddi_pubmedbert_abstract_pipeline_en.md
new file mode 100644
index 00000000000000..2023eb333e2477
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-ddi_pubmedbert_abstract_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ddi_pubmedbert_abstract_pipeline pipeline BertForSequenceClassification from jialicheng
+author: John Snow Labs
+name: ddi_pubmedbert_abstract_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ddi_pubmedbert_abstract_pipeline` is a English model originally trained by jialicheng.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ddi_pubmedbert_abstract_pipeline_en_5.5.1_3.0_1737800840825.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ddi_pubmedbert_abstract_pipeline_en_5.5.1_3.0_1737800840825.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ddi_pubmedbert_abstract_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ddi_pubmedbert_abstract_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ddi_pubmedbert_abstract_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.3 MB|
+
+## References
+
+https://huggingface.co/jialicheng/ddi-pubmedbert-abstract
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-deberta_v3_xsmall_cola_en.md b/docs/_posts/ahmedlone127/2025-01-25-deberta_v3_xsmall_cola_en.md
new file mode 100644
index 00000000000000..e55f407652ccb6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-deberta_v3_xsmall_cola_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_xsmall_cola DeBertaForSequenceClassification from cliang1453
+author: John Snow Labs
+name: deberta_v3_xsmall_cola
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_xsmall_cola` is a English model originally trained by cliang1453.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_cola_en_5.5.1_3.0_1737820123569.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_cola_en_5.5.1_3.0_1737820123569.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_xsmall_cola","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_xsmall_cola", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_xsmall_cola|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|201.8 MB|
+
+## References
+
+https://huggingface.co/cliang1453/deberta-v3-xsmall-cola
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-deberta_v3_xsmall_cola_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-deberta_v3_xsmall_cola_pipeline_en.md
new file mode 100644
index 00000000000000..2a454b89cbd870
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-deberta_v3_xsmall_cola_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_xsmall_cola_pipeline pipeline DeBertaForSequenceClassification from cliang1453
+author: John Snow Labs
+name: deberta_v3_xsmall_cola_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_xsmall_cola_pipeline` is a English model originally trained by cliang1453.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_cola_pipeline_en_5.5.1_3.0_1737820161444.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_cola_pipeline_en_5.5.1_3.0_1737820161444.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_xsmall_cola_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_xsmall_cola_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_xsmall_cola_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|201.8 MB|
+
+## References
+
+https://huggingface.co/cliang1453/deberta-v3-xsmall-cola
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-dgpt22_en.md b/docs/_posts/ahmedlone127/2025-01-25-dgpt22_en.md
new file mode 100644
index 00000000000000..52cc2ef5d42e04
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-dgpt22_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English dgpt22 GPT2Transformer from umar-naveed
+author: John Snow Labs
+name: dgpt22
+date: 2025-01-25
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dgpt22` is a English model originally trained by umar-naveed.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dgpt22_en_5.5.1_3.0_1737824267701.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dgpt22_en_5.5.1_3.0_1737824267701.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("dgpt22","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("dgpt22","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dgpt22|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|308.4 MB|
+
+## References
+
+https://huggingface.co/umar-naveed/dgpt22
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-dgpt22_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-dgpt22_pipeline_en.md
new file mode 100644
index 00000000000000..34090be60f2b8b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-dgpt22_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English dgpt22_pipeline pipeline GPT2Transformer from umar-naveed
+author: John Snow Labs
+name: dgpt22_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dgpt22_pipeline` is a English model originally trained by umar-naveed.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dgpt22_pipeline_en_5.5.1_3.0_1737824283181.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dgpt22_pipeline_en_5.5.1_3.0_1737824283181.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dgpt22_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dgpt22_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dgpt22_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|308.4 MB|
+
+## References
+
+https://huggingface.co/umar-naveed/dgpt22
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-dgpt2_2_en.md b/docs/_posts/ahmedlone127/2025-01-25-dgpt2_2_en.md
new file mode 100644
index 00000000000000..09ce3d7404cba0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-dgpt2_2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English dgpt2_2 GPT2Transformer from umar-naveed
+author: John Snow Labs
+name: dgpt2_2
+date: 2025-01-25
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dgpt2_2` is a English model originally trained by umar-naveed.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dgpt2_2_en_5.5.1_3.0_1737825586127.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dgpt2_2_en_5.5.1_3.0_1737825586127.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("dgpt2_2","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("dgpt2_2","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dgpt2_2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.2 MB|
+
+## References
+
+https://huggingface.co/umar-naveed/dgpt2.2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-dgpt2_2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-dgpt2_2_pipeline_en.md
new file mode 100644
index 00000000000000..dc42f03541f39d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-dgpt2_2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English dgpt2_2_pipeline pipeline GPT2Transformer from umar-naveed
+author: John Snow Labs
+name: dgpt2_2_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dgpt2_2_pipeline` is a English model originally trained by umar-naveed.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dgpt2_2_pipeline_en_5.5.1_3.0_1737825609959.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dgpt2_2_pipeline_en_5.5.1_3.0_1737825609959.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dgpt2_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dgpt2_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dgpt2_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.2 MB|
+
+## References
+
+https://huggingface.co/umar-naveed/dgpt2.2
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-dgpt_en.md b/docs/_posts/ahmedlone127/2025-01-25-dgpt_en.md
new file mode 100644
index 00000000000000..c83abc7acc4712
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-dgpt_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English dgpt GPT2Transformer from umar-naveed
+author: John Snow Labs
+name: dgpt
+date: 2025-01-25
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dgpt` is a English model originally trained by umar-naveed.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dgpt_en_5.5.1_3.0_1737764949566.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dgpt_en_5.5.1_3.0_1737764949566.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("dgpt","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("dgpt","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dgpt|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|308.4 MB|
+
+## References
+
+https://huggingface.co/umar-naveed/dgpt
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-dgpt_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-dgpt_pipeline_en.md
new file mode 100644
index 00000000000000..235e280bf70878
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-dgpt_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English dgpt_pipeline pipeline GPT2Transformer from umar-naveed
+author: John Snow Labs
+name: dgpt_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dgpt_pipeline` is a English model originally trained by umar-naveed.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dgpt_pipeline_en_5.5.1_3.0_1737764965803.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dgpt_pipeline_en_5.5.1_3.0_1737764965803.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dgpt_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dgpt_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dgpt_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|308.4 MB|
+
+## References
+
+https://huggingface.co/umar-naveed/dgpt
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-dialogpt_medium_nova_en.md b/docs/_posts/ahmedlone127/2025-01-25-dialogpt_medium_nova_en.md
new file mode 100644
index 00000000000000..a05ab490c16e85
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-dialogpt_medium_nova_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English dialogpt_medium_nova GPT2Transformer from Serpxn
+author: John Snow Labs
+name: dialogpt_medium_nova
+date: 2025-01-25
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dialogpt_medium_nova` is a English model originally trained by Serpxn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dialogpt_medium_nova_en_5.5.1_3.0_1737824491188.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dialogpt_medium_nova_en_5.5.1_3.0_1737824491188.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("dialogpt_medium_nova","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("dialogpt_medium_nova","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dialogpt_medium_nova|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/Serpxn/DialoGPT-medium-Nova
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-dialogpt_medium_nova_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-dialogpt_medium_nova_pipeline_en.md
new file mode 100644
index 00000000000000..eec3c9fcd9f8a3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-dialogpt_medium_nova_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English dialogpt_medium_nova_pipeline pipeline GPT2Transformer from Serpxn
+author: John Snow Labs
+name: dialogpt_medium_nova_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dialogpt_medium_nova_pipeline` is a English model originally trained by Serpxn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dialogpt_medium_nova_pipeline_en_5.5.1_3.0_1737824557422.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dialogpt_medium_nova_pipeline_en_5.5.1_3.0_1737824557422.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dialogpt_medium_nova_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dialogpt_medium_nova_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dialogpt_medium_nova_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/Serpxn/DialoGPT-medium-Nova
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-disease_ner_cat_v1_ca.md b/docs/_posts/ahmedlone127/2025-01-25-disease_ner_cat_v1_ca.md
new file mode 100644
index 00000000000000..7d1343a3558afd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-disease_ner_cat_v1_ca.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Catalan, Valencian disease_ner_cat_v1 RoBertaForTokenClassification from BSC-NLP4BIA
+author: John Snow Labs
+name: disease_ner_cat_v1
+date: 2025-01-25
+tags: [ca, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: ca
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`disease_ner_cat_v1` is a Catalan, Valencian model originally trained by BSC-NLP4BIA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/disease_ner_cat_v1_ca_5.5.1_3.0_1737809525976.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/disease_ner_cat_v1_ca_5.5.1_3.0_1737809525976.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("disease_ner_cat_v1","ca") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("disease_ner_cat_v1", "ca")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|disease_ner_cat_v1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|ca|
+|Size:|435.9 MB|
+
+## References
+
+https://huggingface.co/BSC-NLP4BIA/disease-ner-cat-v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-disease_ner_cat_v1_pipeline_ca.md b/docs/_posts/ahmedlone127/2025-01-25-disease_ner_cat_v1_pipeline_ca.md
new file mode 100644
index 00000000000000..b0f6469c9460a5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-disease_ner_cat_v1_pipeline_ca.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Catalan, Valencian disease_ner_cat_v1_pipeline pipeline RoBertaForTokenClassification from BSC-NLP4BIA
+author: John Snow Labs
+name: disease_ner_cat_v1_pipeline
+date: 2025-01-25
+tags: [ca, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: ca
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`disease_ner_cat_v1_pipeline` is a Catalan, Valencian model originally trained by BSC-NLP4BIA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/disease_ner_cat_v1_pipeline_ca_5.5.1_3.0_1737809550541.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/disease_ner_cat_v1_pipeline_ca_5.5.1_3.0_1737809550541.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("disease_ner_cat_v1_pipeline", lang = "ca")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("disease_ner_cat_v1_pipeline", lang = "ca")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|disease_ner_cat_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ca|
+|Size:|436.0 MB|
+
+## References
+
+https://huggingface.co/BSC-NLP4BIA/disease-ner-cat-v1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distil_bert_ft_qa_model_7up_v2_en.md b/docs/_posts/ahmedlone127/2025-01-25-distil_bert_ft_qa_model_7up_v2_en.md
new file mode 100644
index 00000000000000..eb5a173e91c889
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distil_bert_ft_qa_model_7up_v2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distil_bert_ft_qa_model_7up_v2 BertForQuestionAnswering from cadzchua
+author: John Snow Labs
+name: distil_bert_ft_qa_model_7up_v2
+date: 2025-01-25
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distil_bert_ft_qa_model_7up_v2` is a English model originally trained by cadzchua.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distil_bert_ft_qa_model_7up_v2_en_5.5.1_3.0_1737813745929.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distil_bert_ft_qa_model_7up_v2_en_5.5.1_3.0_1737813745929.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("distil_bert_ft_qa_model_7up_v2","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("distil_bert_ft_qa_model_7up_v2", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distil_bert_ft_qa_model_7up_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/cadzchua/distil-bert-ft-qa-model-7up-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distil_bert_ft_qa_model_7up_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distil_bert_ft_qa_model_7up_v2_pipeline_en.md
new file mode 100644
index 00000000000000..481adc65d8630e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distil_bert_ft_qa_model_7up_v2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distil_bert_ft_qa_model_7up_v2_pipeline pipeline BertForQuestionAnswering from cadzchua
+author: John Snow Labs
+name: distil_bert_ft_qa_model_7up_v2_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distil_bert_ft_qa_model_7up_v2_pipeline` is a English model originally trained by cadzchua.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distil_bert_ft_qa_model_7up_v2_pipeline_en_5.5.1_3.0_1737813767739.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distil_bert_ft_qa_model_7up_v2_pipeline_en_5.5.1_3.0_1737813767739.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distil_bert_ft_qa_model_7up_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distil_bert_ft_qa_model_7up_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distil_bert_ft_qa_model_7up_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/cadzchua/distil-bert-ft-qa-model-7up-v2
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distil_bert_ft_qa_model_7up_v7_en.md b/docs/_posts/ahmedlone127/2025-01-25-distil_bert_ft_qa_model_7up_v7_en.md
new file mode 100644
index 00000000000000..440ed915a15d8c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distil_bert_ft_qa_model_7up_v7_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distil_bert_ft_qa_model_7up_v7 BertForQuestionAnswering from cadzchua
+author: John Snow Labs
+name: distil_bert_ft_qa_model_7up_v7
+date: 2025-01-25
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distil_bert_ft_qa_model_7up_v7` is a English model originally trained by cadzchua.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distil_bert_ft_qa_model_7up_v7_en_5.5.1_3.0_1737813971330.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distil_bert_ft_qa_model_7up_v7_en_5.5.1_3.0_1737813971330.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("distil_bert_ft_qa_model_7up_v7","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("distil_bert_ft_qa_model_7up_v7", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distil_bert_ft_qa_model_7up_v7|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/cadzchua/distil-bert-ft-qa-model-7up-v7
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distil_bert_ft_qa_model_7up_v7_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distil_bert_ft_qa_model_7up_v7_pipeline_en.md
new file mode 100644
index 00000000000000..a7e4064e528235
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distil_bert_ft_qa_model_7up_v7_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distil_bert_ft_qa_model_7up_v7_pipeline pipeline BertForQuestionAnswering from cadzchua
+author: John Snow Labs
+name: distil_bert_ft_qa_model_7up_v7_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distil_bert_ft_qa_model_7up_v7_pipeline` is a English model originally trained by cadzchua.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distil_bert_ft_qa_model_7up_v7_pipeline_en_5.5.1_3.0_1737814005881.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distil_bert_ft_qa_model_7up_v7_pipeline_en_5.5.1_3.0_1737814005881.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distil_bert_ft_qa_model_7up_v7_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distil_bert_ft_qa_model_7up_v7_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distil_bert_ft_qa_model_7up_v7_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/cadzchua/distil-bert-ft-qa-model-7up-v7
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distil_bert_imeoocap_en.md b/docs/_posts/ahmedlone127/2025-01-25-distil_bert_imeoocap_en.md
new file mode 100644
index 00000000000000..b94c8f9c0a6485
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distil_bert_imeoocap_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distil_bert_imeoocap DistilBertForSequenceClassification from sakren
+author: John Snow Labs
+name: distil_bert_imeoocap
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distil_bert_imeoocap` is a English model originally trained by sakren.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distil_bert_imeoocap_en_5.5.1_3.0_1737836752484.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distil_bert_imeoocap_en_5.5.1_3.0_1737836752484.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distil_bert_imeoocap","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distil_bert_imeoocap", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distil_bert_imeoocap|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/sakren/distil-bert-imeoocap
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distil_bert_imeoocap_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distil_bert_imeoocap_pipeline_en.md
new file mode 100644
index 00000000000000..f892d56c6436eb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distil_bert_imeoocap_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distil_bert_imeoocap_pipeline pipeline DistilBertForSequenceClassification from sakren
+author: John Snow Labs
+name: distil_bert_imeoocap_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distil_bert_imeoocap_pipeline` is a English model originally trained by sakren.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distil_bert_imeoocap_pipeline_en_5.5.1_3.0_1737836765964.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distil_bert_imeoocap_pipeline_en_5.5.1_3.0_1737836765964.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distil_bert_imeoocap_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distil_bert_imeoocap_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distil_bert_imeoocap_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/sakren/distil-bert-imeoocap
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_ag_news_2024_12_11_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_ag_news_2024_12_11_en.md
new file mode 100644
index 00000000000000..482a572fcb0738
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_ag_news_2024_12_11_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_ag_news_2024_12_11 DistilBertForSequenceClassification from chicagoillinoiswork
+author: John Snow Labs
+name: distilbert_ag_news_2024_12_11
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_ag_news_2024_12_11` is a English model originally trained by chicagoillinoiswork.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_ag_news_2024_12_11_en_5.5.1_3.0_1737837640330.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_ag_news_2024_12_11_en_5.5.1_3.0_1737837640330.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_ag_news_2024_12_11","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_ag_news_2024_12_11", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_ag_news_2024_12_11|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/chicagoillinoiswork/distilbert-ag-news-2024-12-11
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_ag_news_2024_12_11_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_ag_news_2024_12_11_pipeline_en.md
new file mode 100644
index 00000000000000..8db9df9095625a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_ag_news_2024_12_11_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_ag_news_2024_12_11_pipeline pipeline DistilBertForSequenceClassification from chicagoillinoiswork
+author: John Snow Labs
+name: distilbert_ag_news_2024_12_11_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_ag_news_2024_12_11_pipeline` is a English model originally trained by chicagoillinoiswork.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_ag_news_2024_12_11_pipeline_en_5.5.1_3.0_1737837655437.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_ag_news_2024_12_11_pipeline_en_5.5.1_3.0_1737837655437.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_ag_news_2024_12_11_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_ag_news_2024_12_11_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_ag_news_2024_12_11_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/chicagoillinoiswork/distilbert-ag-news-2024-12-11
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_lda_qnli_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_lda_qnli_en.md
new file mode 100644
index 00000000000000..1ee8d7142f5ffb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_lda_qnli_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_lda_qnli DistilBertForSequenceClassification from gokulsrinivasagan
+author: John Snow Labs
+name: distilbert_base_lda_qnli
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_lda_qnli` is a English model originally trained by gokulsrinivasagan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_lda_qnli_en_5.5.1_3.0_1737837645964.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_lda_qnli_en_5.5.1_3.0_1737837645964.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_lda_qnli","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_lda_qnli", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_lda_qnli|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|251.2 MB|
+
+## References
+
+https://huggingface.co/gokulsrinivasagan/distilbert_base_lda_qnli
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_lda_qnli_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_lda_qnli_pipeline_en.md
new file mode 100644
index 00000000000000..629dfd2fe15b6a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_lda_qnli_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_lda_qnli_pipeline pipeline DistilBertForSequenceClassification from gokulsrinivasagan
+author: John Snow Labs
+name: distilbert_base_lda_qnli_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_lda_qnli_pipeline` is a English model originally trained by gokulsrinivasagan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_lda_qnli_pipeline_en_5.5.1_3.0_1737837662915.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_lda_qnli_pipeline_en_5.5.1_3.0_1737837662915.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_lda_qnli_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_lda_qnli_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_lda_qnli_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|251.3 MB|
+
+## References
+
+https://huggingface.co/gokulsrinivasagan/distilbert_base_lda_qnli
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_lda_qqp_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_lda_qqp_en.md
new file mode 100644
index 00000000000000..5bc8c5a4d5ef2b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_lda_qqp_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_lda_qqp DistilBertForSequenceClassification from gokulsrinivasagan
+author: John Snow Labs
+name: distilbert_base_lda_qqp
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_lda_qqp` is a English model originally trained by gokulsrinivasagan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_lda_qqp_en_5.5.1_3.0_1737836858181.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_lda_qqp_en_5.5.1_3.0_1737836858181.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_lda_qqp","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_lda_qqp", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_lda_qqp|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|251.2 MB|
+
+## References
+
+https://huggingface.co/gokulsrinivasagan/distilbert_base_lda_qqp
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_lda_qqp_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_lda_qqp_pipeline_en.md
new file mode 100644
index 00000000000000..ffe2735c6c478d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_lda_qqp_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_lda_qqp_pipeline pipeline DistilBertForSequenceClassification from gokulsrinivasagan
+author: John Snow Labs
+name: distilbert_base_lda_qqp_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_lda_qqp_pipeline` is a English model originally trained by gokulsrinivasagan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_lda_qqp_pipeline_en_5.5.1_3.0_1737836871248.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_lda_qqp_pipeline_en_5.5.1_3.0_1737836871248.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_lda_qqp_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_lda_qqp_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_lda_qqp_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|251.3 MB|
+
+## References
+
+https://huggingface.co/gokulsrinivasagan/distilbert_base_lda_qqp
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_multilingual_cased_aoe_test12_pipeline_xx.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_multilingual_cased_aoe_test12_pipeline_xx.md
new file mode 100644
index 00000000000000..fe62527b2001a6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_multilingual_cased_aoe_test12_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual distilbert_base_multilingual_cased_aoe_test12_pipeline pipeline DistilBertForSequenceClassification from cvapict
+author: John Snow Labs
+name: distilbert_base_multilingual_cased_aoe_test12_pipeline
+date: 2025-01-25
+tags: [xx, open_source, pipeline, onnx]
+task: Text Classification
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_multilingual_cased_aoe_test12_pipeline` is a Multilingual model originally trained by cvapict.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_multilingual_cased_aoe_test12_pipeline_xx_5.5.1_3.0_1737838365594.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_multilingual_cased_aoe_test12_pipeline_xx_5.5.1_3.0_1737838365594.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_multilingual_cased_aoe_test12_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_multilingual_cased_aoe_test12_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_multilingual_cased_aoe_test12_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|507.6 MB|
+
+## References
+
+https://huggingface.co/cvapict/distilbert-base-multilingual-cased-aoe-test12
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_multilingual_cased_aoe_test12_xx.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_multilingual_cased_aoe_test12_xx.md
new file mode 100644
index 00000000000000..3ca849a1bec454
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_multilingual_cased_aoe_test12_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual distilbert_base_multilingual_cased_aoe_test12 DistilBertForSequenceClassification from cvapict
+author: John Snow Labs
+name: distilbert_base_multilingual_cased_aoe_test12
+date: 2025-01-25
+tags: [xx, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_multilingual_cased_aoe_test12` is a Multilingual model originally trained by cvapict.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_multilingual_cased_aoe_test12_xx_5.5.1_3.0_1737838338422.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_multilingual_cased_aoe_test12_xx_5.5.1_3.0_1737838338422.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_multilingual_cased_aoe_test12","xx") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_multilingual_cased_aoe_test12", "xx")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_multilingual_cased_aoe_test12|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|xx|
+|Size:|507.6 MB|
+
+## References
+
+https://huggingface.co/cvapict/distilbert-base-multilingual-cased-aoe-test12
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_3epoch_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_3epoch_en.md
new file mode 100644
index 00000000000000..218e8ac257bd30
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_3epoch_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_3epoch DistilBertForSequenceClassification from dianamihalache27
+author: John Snow Labs
+name: distilbert_base_uncased_3epoch
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_3epoch` is a English model originally trained by dianamihalache27.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_3epoch_en_5.5.1_3.0_1737822551262.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_3epoch_en_5.5.1_3.0_1737822551262.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_3epoch","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_3epoch", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_3epoch|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/dianamihalache27/distilbert-base-uncased_3epoch
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_3epoch_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_3epoch_pipeline_en.md
new file mode 100644
index 00000000000000..9f2067b055aa5b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_3epoch_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_3epoch_pipeline pipeline DistilBertForSequenceClassification from dianamihalache27
+author: John Snow Labs
+name: distilbert_base_uncased_3epoch_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_3epoch_pipeline` is a English model originally trained by dianamihalache27.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_3epoch_pipeline_en_5.5.1_3.0_1737822564304.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_3epoch_pipeline_en_5.5.1_3.0_1737822564304.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_3epoch_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_3epoch_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_3epoch_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/dianamihalache27/distilbert-base-uncased_3epoch
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_distilled_clinc_imaditya123_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_distilled_clinc_imaditya123_en.md
new file mode 100644
index 00000000000000..6d84fddc9470cb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_distilled_clinc_imaditya123_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_distilled_clinc_imaditya123 DistilBertForSequenceClassification from imaditya123
+author: John Snow Labs
+name: distilbert_base_uncased_distilled_clinc_imaditya123
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_distilled_clinc_imaditya123` is a English model originally trained by imaditya123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_distilled_clinc_imaditya123_en_5.5.1_3.0_1737838200683.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_distilled_clinc_imaditya123_en_5.5.1_3.0_1737838200683.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_distilled_clinc_imaditya123","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_distilled_clinc_imaditya123", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_distilled_clinc_imaditya123|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.9 MB|
+
+## References
+
+https://huggingface.co/imaditya123/distilbert-base-uncased-distilled-clinc
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_distilled_clinc_imaditya123_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_distilled_clinc_imaditya123_pipeline_en.md
new file mode 100644
index 00000000000000..d6ba09716e5e25
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_distilled_clinc_imaditya123_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_distilled_clinc_imaditya123_pipeline pipeline DistilBertForSequenceClassification from imaditya123
+author: John Snow Labs
+name: distilbert_base_uncased_distilled_clinc_imaditya123_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_distilled_clinc_imaditya123_pipeline` is a English model originally trained by imaditya123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_distilled_clinc_imaditya123_pipeline_en_5.5.1_3.0_1737838214029.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_distilled_clinc_imaditya123_pipeline_en_5.5.1_3.0_1737838214029.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_distilled_clinc_imaditya123_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_distilled_clinc_imaditya123_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_distilled_clinc_imaditya123_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.9 MB|
+
+## References
+
+https://huggingface.co/imaditya123/distilbert-base-uncased-distilled-clinc
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_distilled_clinc_oscarnav_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_distilled_clinc_oscarnav_en.md
new file mode 100644
index 00000000000000..4e0005e7770b55
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_distilled_clinc_oscarnav_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_distilled_clinc_oscarnav DistilBertForSequenceClassification from OscarNav
+author: John Snow Labs
+name: distilbert_base_uncased_distilled_clinc_oscarnav
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_distilled_clinc_oscarnav` is a English model originally trained by OscarNav.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_distilled_clinc_oscarnav_en_5.5.1_3.0_1737821792754.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_distilled_clinc_oscarnav_en_5.5.1_3.0_1737821792754.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_distilled_clinc_oscarnav","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_distilled_clinc_oscarnav", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_distilled_clinc_oscarnav|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.9 MB|
+
+## References
+
+https://huggingface.co/OscarNav/distilbert-base-uncased-distilled-clinc
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_distilled_clinc_oscarnav_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_distilled_clinc_oscarnav_pipeline_en.md
new file mode 100644
index 00000000000000..51786e34f33d0a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_distilled_clinc_oscarnav_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_distilled_clinc_oscarnav_pipeline pipeline DistilBertForSequenceClassification from OscarNav
+author: John Snow Labs
+name: distilbert_base_uncased_distilled_clinc_oscarnav_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_distilled_clinc_oscarnav_pipeline` is a English model originally trained by OscarNav.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_distilled_clinc_oscarnav_pipeline_en_5.5.1_3.0_1737821806071.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_distilled_clinc_oscarnav_pipeline_en_5.5.1_3.0_1737821806071.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_distilled_clinc_oscarnav_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_distilled_clinc_oscarnav_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_distilled_clinc_oscarnav_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.9 MB|
+
+## References
+
+https://huggingface.co/OscarNav/distilbert-base-uncased-distilled-clinc
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_distilled_clinc_taoyoung_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_distilled_clinc_taoyoung_en.md
new file mode 100644
index 00000000000000..ee4bcd044095a1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_distilled_clinc_taoyoung_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_distilled_clinc_taoyoung DistilBertForSequenceClassification from taoyoung
+author: John Snow Labs
+name: distilbert_base_uncased_distilled_clinc_taoyoung
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_distilled_clinc_taoyoung` is a English model originally trained by taoyoung.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_distilled_clinc_taoyoung_en_5.5.1_3.0_1737838208966.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_distilled_clinc_taoyoung_en_5.5.1_3.0_1737838208966.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_distilled_clinc_taoyoung","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_distilled_clinc_taoyoung", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_distilled_clinc_taoyoung|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.9 MB|
+
+## References
+
+https://huggingface.co/taoyoung/distilbert-base-uncased-distilled-clinc
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_distilled_clinc_taoyoung_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_distilled_clinc_taoyoung_pipeline_en.md
new file mode 100644
index 00000000000000..08b2d42d72ba43
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_distilled_clinc_taoyoung_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_distilled_clinc_taoyoung_pipeline pipeline DistilBertForSequenceClassification from taoyoung
+author: John Snow Labs
+name: distilbert_base_uncased_distilled_clinc_taoyoung_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_distilled_clinc_taoyoung_pipeline` is a English model originally trained by taoyoung.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_distilled_clinc_taoyoung_pipeline_en_5.5.1_3.0_1737838224490.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_distilled_clinc_taoyoung_pipeline_en_5.5.1_3.0_1737838224490.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_distilled_clinc_taoyoung_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_distilled_clinc_taoyoung_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_distilled_clinc_taoyoung_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.9 MB|
+
+## References
+
+https://huggingface.co/taoyoung/distilbert-base-uncased-distilled-clinc
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_ecom_qa_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_ecom_qa_en.md
new file mode 100644
index 00000000000000..b3177d6f123dcc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_ecom_qa_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilbert_base_uncased_ecom_qa DistilBertForQuestionAnswering from Vinayak1699
+author: John Snow Labs
+name: distilbert_base_uncased_ecom_qa
+date: 2025-01-25
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_ecom_qa` is a English model originally trained by Vinayak1699.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_ecom_qa_en_5.5.1_3.0_1737823872557.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_ecom_qa_en_5.5.1_3.0_1737823872557.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_ecom_qa","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_ecom_qa", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_ecom_qa|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Vinayak1699/distilbert-base-uncased-ecom-qa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_ecom_qa_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_ecom_qa_pipeline_en.md
new file mode 100644
index 00000000000000..8cc577bf18bb83
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_ecom_qa_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbert_base_uncased_ecom_qa_pipeline pipeline DistilBertForQuestionAnswering from Vinayak1699
+author: John Snow Labs
+name: distilbert_base_uncased_ecom_qa_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_ecom_qa_pipeline` is a English model originally trained by Vinayak1699.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_ecom_qa_pipeline_en_5.5.1_3.0_1737823885146.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_ecom_qa_pipeline_en_5.5.1_3.0_1737823885146.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_ecom_qa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_ecom_qa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_ecom_qa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Vinayak1699/distilbert-base-uncased-ecom-qa
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_emotion_ft_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_emotion_ft_en.md
new file mode 100644
index 00000000000000..7799c078fc4e2b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_emotion_ft_en.md
@@ -0,0 +1,98 @@
+---
+layout: model
+title: English distilbert_base_uncased_emotion_ft DistilBertForSequenceClassification from lanchunhui
+author: John Snow Labs
+name: distilbert_base_uncased_emotion_ft
+date: 2025-01-25
+tags: [bert, en, open_source, sequence_classification, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_emotion_ft` is a English model originally trained by lanchunhui.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_emotion_ft_en_5.5.1_3.0_1737821936990.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_emotion_ft_en_5.5.1_3.0_1737821936990.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = DocumentAssembler()\
+    .setInputCol("text")\
+    .setOutputCol("document")
+
+tokenizer = Tokenizer()\
+    .setInputCols("document")\
+    .setOutputCol("token")  
+    
+sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_emotion_ft","en")\
+            .setInputCols(["document","token"])\
+            .setOutputCol("class")
+
+pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val document_assembler = new DocumentAssembler()
+    .setInputCol("text")
+    .setOutputCol("document")
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document") 
+    .setOutputCol("token")  
+    
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_emotion_ft","en")
+            .setInputCols(Array("document","token"))
+            .setOutputCol("class")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_emotion_ft|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+References
+
+https://huggingface.co/lanchunhui/distilbert-base-uncased_emotion_ft
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_emotion_ft_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_emotion_ft_pipeline_en.md
new file mode 100644
index 00000000000000..c3f9a55a6b4aa0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_emotion_ft_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_emotion_ft_pipeline pipeline DistilBertForSequenceClassification from yakusou2333
+author: John Snow Labs
+name: distilbert_base_uncased_emotion_ft_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_emotion_ft_pipeline` is a English model originally trained by yakusou2333.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_emotion_ft_pipeline_en_5.5.1_3.0_1737821952065.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_emotion_ft_pipeline_en_5.5.1_3.0_1737821952065.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_emotion_ft_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_emotion_ft_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_emotion_ft_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/yakusou2333/distilbert-base-uncased_emotion_ft_
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_financial_news_sentiment_analysis_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_financial_news_sentiment_analysis_en.md
new file mode 100644
index 00000000000000..b0f65de33591d1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_financial_news_sentiment_analysis_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_financial_news_sentiment_analysis DistilBertForSequenceClassification from AnkitAI
+author: John Snow Labs
+name: distilbert_base_uncased_financial_news_sentiment_analysis
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_financial_news_sentiment_analysis` is a English model originally trained by AnkitAI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_financial_news_sentiment_analysis_en_5.5.1_3.0_1737836652049.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_financial_news_sentiment_analysis_en_5.5.1_3.0_1737836652049.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_financial_news_sentiment_analysis","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_financial_news_sentiment_analysis", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_financial_news_sentiment_analysis|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/AnkitAI/distilbert-base-uncased-financial-news-sentiment-analysis
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_financial_news_sentiment_analysis_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_financial_news_sentiment_analysis_pipeline_en.md
new file mode 100644
index 00000000000000..4dcdd904c76021
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_financial_news_sentiment_analysis_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_financial_news_sentiment_analysis_pipeline pipeline DistilBertForSequenceClassification from AnkitAI
+author: John Snow Labs
+name: distilbert_base_uncased_financial_news_sentiment_analysis_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_financial_news_sentiment_analysis_pipeline` is a English model originally trained by AnkitAI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_financial_news_sentiment_analysis_pipeline_en_5.5.1_3.0_1737836665240.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_financial_news_sentiment_analysis_pipeline_en_5.5.1_3.0_1737836665240.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_financial_news_sentiment_analysis_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_financial_news_sentiment_analysis_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_financial_news_sentiment_analysis_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/AnkitAI/distilbert-base-uncased-financial-news-sentiment-analysis
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_code_text_classifier_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_code_text_classifier_en.md
new file mode 100644
index 00000000000000..96f9001b8a49ad
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_code_text_classifier_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_code_text_classifier DistilBertForSequenceClassification from AZIIIIIIIIZ
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_code_text_classifier
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_code_text_classifier` is a English model originally trained by AZIIIIIIIIZ.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_code_text_classifier_en_5.5.1_3.0_1737837523249.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_code_text_classifier_en_5.5.1_3.0_1737837523249.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_code_text_classifier","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_code_text_classifier", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_code_text_classifier|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/AZIIIIIIIIZ/distilbert-base-uncased_finetuned_code_text_classifier
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_code_text_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_code_text_classifier_pipeline_en.md
new file mode 100644
index 00000000000000..6e3d6361313d8a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_code_text_classifier_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_code_text_classifier_pipeline pipeline DistilBertForSequenceClassification from AZIIIIIIIIZ
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_code_text_classifier_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_code_text_classifier_pipeline` is a English model originally trained by AZIIIIIIIIZ.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_code_text_classifier_pipeline_en_5.5.1_3.0_1737837537460.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_code_text_classifier_pipeline_en_5.5.1_3.0_1737837537460.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_code_text_classifier_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_code_text_classifier_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_code_text_classifier_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/AZIIIIIIIIZ/distilbert-base-uncased_finetuned_code_text_classifier
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_cola_nxbisgin_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_cola_nxbisgin_en.md
new file mode 100644
index 00000000000000..c6874de4cde0eb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_cola_nxbisgin_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_cola_nxbisgin DistilBertForSequenceClassification from nxbisgin
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_cola_nxbisgin
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_cola_nxbisgin` is a English model originally trained by nxbisgin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_cola_nxbisgin_en_5.5.1_3.0_1737836531934.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_cola_nxbisgin_en_5.5.1_3.0_1737836531934.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_cola_nxbisgin","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_cola_nxbisgin", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_cola_nxbisgin|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/nxbisgin/distilbert-base-uncased-finetuned-cola
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_cola_nxbisgin_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_cola_nxbisgin_pipeline_en.md
new file mode 100644
index 00000000000000..629ba932c2660a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_cola_nxbisgin_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_cola_nxbisgin_pipeline pipeline DistilBertForSequenceClassification from nxbisgin
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_cola_nxbisgin_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_cola_nxbisgin_pipeline` is a English model originally trained by nxbisgin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_cola_nxbisgin_pipeline_en_5.5.1_3.0_1737836551614.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_cola_nxbisgin_pipeline_en_5.5.1_3.0_1737836551614.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_cola_nxbisgin_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_cola_nxbisgin_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_cola_nxbisgin_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/nxbisgin/distilbert-base-uncased-finetuned-cola
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_cola_werywjw_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_cola_werywjw_en.md
new file mode 100644
index 00000000000000..4910a4329bc396
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_cola_werywjw_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_cola_werywjw DistilBertForSequenceClassification from werywjw
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_cola_werywjw
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_cola_werywjw` is a English model originally trained by werywjw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_cola_werywjw_en_5.5.1_3.0_1737836241531.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_cola_werywjw_en_5.5.1_3.0_1737836241531.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_cola_werywjw","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_cola_werywjw", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_cola_werywjw|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/werywjw/distilbert-base-uncased-finetuned-cola
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_cola_werywjw_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_cola_werywjw_pipeline_en.md
new file mode 100644
index 00000000000000..87e32c4397f8a8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_cola_werywjw_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_cola_werywjw_pipeline pipeline DistilBertForSequenceClassification from werywjw
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_cola_werywjw_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_cola_werywjw_pipeline` is a English model originally trained by werywjw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_cola_werywjw_pipeline_en_5.5.1_3.0_1737836255565.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_cola_werywjw_pipeline_en_5.5.1_3.0_1737836255565.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_cola_werywjw_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_cola_werywjw_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_cola_werywjw_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/werywjw/distilbert-base-uncased-finetuned-cola
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_01_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_01_en.md
new file mode 100644
index 00000000000000..d40d7f7225228d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_01_en.md
@@ -0,0 +1,98 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_01 DistilBertForSequenceClassification from Hardeep
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_01
+date: 2025-01-25
+tags: [bert, en, open_source, sequence_classification, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_01` is a English model originally trained by Hardeep.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_01_en_5.5.1_3.0_1737822298653.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_01_en_5.5.1_3.0_1737822298653.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = DocumentAssembler()\
+    .setInputCol("text")\
+    .setOutputCol("document")
+
+tokenizer = Tokenizer()\
+    .setInputCols("document")\
+    .setOutputCol("token")  
+    
+sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_01","en")\
+            .setInputCols(["document","token"])\
+            .setOutputCol("class")
+
+pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val document_assembler = new DocumentAssembler()
+    .setInputCol("text")
+    .setOutputCol("document")
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document") 
+    .setOutputCol("token")  
+    
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_01","en")
+            .setInputCols(Array("document","token"))
+            .setOutputCol("class")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_01|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+References
+
+https://huggingface.co/Hardeep/distilbert-base-uncased-finetuned-emotion-01
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_01_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_01_pipeline_en.md
new file mode 100644
index 00000000000000..44bb880c450a4d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_01_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_01_pipeline pipeline DistilBertForSequenceClassification from Kumarajiva
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_01_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_01_pipeline` is a English model originally trained by Kumarajiva.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_01_pipeline_en_5.5.1_3.0_1737822315038.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_01_pipeline_en_5.5.1_3.0_1737822315038.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_01_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_01_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_01_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Kumarajiva/distilbert-base-uncased-finetuned-emotion-01
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_5imp5on_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_5imp5on_en.md
new file mode 100644
index 00000000000000..32ee4b373bbf54
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_5imp5on_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_5imp5on DistilBertForSequenceClassification from 5imp5on
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_5imp5on
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_5imp5on` is a English model originally trained by 5imp5on.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_5imp5on_en_5.5.1_3.0_1737822983655.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_5imp5on_en_5.5.1_3.0_1737822983655.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_5imp5on","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_5imp5on", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_5imp5on|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/5imp5on/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_5imp5on_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_5imp5on_pipeline_en.md
new file mode 100644
index 00000000000000..70e31f3ad5817b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_5imp5on_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_5imp5on_pipeline pipeline DistilBertForSequenceClassification from 5imp5on
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_5imp5on_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_5imp5on_pipeline` is a English model originally trained by 5imp5on.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_5imp5on_pipeline_en_5.5.1_3.0_1737822996326.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_5imp5on_pipeline_en_5.5.1_3.0_1737822996326.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_5imp5on_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_5imp5on_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_5imp5on_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/5imp5on/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_abdelrahman_hassan66_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_abdelrahman_hassan66_en.md
new file mode 100644
index 00000000000000..24f52e6f26c9ed
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_abdelrahman_hassan66_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_abdelrahman_hassan66 DistilBertForSequenceClassification from Abdelrahman-hassan66
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_abdelrahman_hassan66
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_abdelrahman_hassan66` is a English model originally trained by Abdelrahman-hassan66.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_abdelrahman_hassan66_en_5.5.1_3.0_1737838469550.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_abdelrahman_hassan66_en_5.5.1_3.0_1737838469550.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_abdelrahman_hassan66","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_abdelrahman_hassan66", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_abdelrahman_hassan66|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Abdelrahman-hassan66/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_abdelrahman_hassan66_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_abdelrahman_hassan66_pipeline_en.md
new file mode 100644
index 00000000000000..27e9d7ff4f526b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_abdelrahman_hassan66_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_abdelrahman_hassan66_pipeline pipeline DistilBertForSequenceClassification from Abdelrahman-hassan66
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_abdelrahman_hassan66_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_abdelrahman_hassan66_pipeline` is a English model originally trained by Abdelrahman-hassan66.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_abdelrahman_hassan66_pipeline_en_5.5.1_3.0_1737838484215.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_abdelrahman_hassan66_pipeline_en_5.5.1_3.0_1737838484215.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_abdelrahman_hassan66_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_abdelrahman_hassan66_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_abdelrahman_hassan66_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Abdelrahman-hassan66/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_activeyixiao_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_activeyixiao_en.md
new file mode 100644
index 00000000000000..06312ef1795445
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_activeyixiao_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_activeyixiao DistilBertForSequenceClassification from ActiveYixiao
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_activeyixiao
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_activeyixiao` is a English model originally trained by ActiveYixiao.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_activeyixiao_en_5.5.1_3.0_1737822766849.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_activeyixiao_en_5.5.1_3.0_1737822766849.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_activeyixiao","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_activeyixiao", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_activeyixiao|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/ActiveYixiao/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_activeyixiao_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_activeyixiao_pipeline_en.md
new file mode 100644
index 00000000000000..7424519d12263d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_activeyixiao_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_activeyixiao_pipeline pipeline DistilBertForSequenceClassification from ActiveYixiao
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_activeyixiao_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_activeyixiao_pipeline` is a English model originally trained by ActiveYixiao.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_activeyixiao_pipeline_en_5.5.1_3.0_1737822780017.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_activeyixiao_pipeline_en_5.5.1_3.0_1737822780017.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_activeyixiao_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_activeyixiao_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_activeyixiao_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/ActiveYixiao/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_andrewmwells_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_andrewmwells_en.md
new file mode 100644
index 00000000000000..512f4f54d38a54
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_andrewmwells_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_andrewmwells DistilBertForSequenceClassification from andrewmwells
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_andrewmwells
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_andrewmwells` is a English model originally trained by andrewmwells.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_andrewmwells_en_5.5.1_3.0_1737836504183.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_andrewmwells_en_5.5.1_3.0_1737836504183.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_andrewmwells","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_andrewmwells", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_andrewmwells|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/andrewmwells/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_andrewmwells_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_andrewmwells_pipeline_en.md
new file mode 100644
index 00000000000000..f50e34b7cb2717
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_andrewmwells_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_andrewmwells_pipeline pipeline DistilBertForSequenceClassification from andrewmwells
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_andrewmwells_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_andrewmwells_pipeline` is a English model originally trained by andrewmwells.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_andrewmwells_pipeline_en_5.5.1_3.0_1737836517813.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_andrewmwells_pipeline_en_5.5.1_3.0_1737836517813.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_andrewmwells_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_andrewmwells_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_andrewmwells_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/andrewmwells/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_bevilacquaj_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_bevilacquaj_en.md
new file mode 100644
index 00000000000000..8ef29282dc8ddc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_bevilacquaj_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_bevilacquaj DistilBertForSequenceClassification from bevilacquaj
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_bevilacquaj
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_bevilacquaj` is a English model originally trained by bevilacquaj.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_bevilacquaj_en_5.5.1_3.0_1737811508332.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_bevilacquaj_en_5.5.1_3.0_1737811508332.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_bevilacquaj","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_bevilacquaj", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_bevilacquaj|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/bevilacquaj/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_bevilacquaj_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_bevilacquaj_pipeline_en.md
new file mode 100644
index 00000000000000..ba0771f49ce526
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_bevilacquaj_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_bevilacquaj_pipeline pipeline DistilBertForSequenceClassification from bevilacquaj
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_bevilacquaj_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_bevilacquaj_pipeline` is a English model originally trained by bevilacquaj.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_bevilacquaj_pipeline_en_5.5.1_3.0_1737811521515.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_bevilacquaj_pipeline_en_5.5.1_3.0_1737811521515.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_bevilacquaj_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_bevilacquaj_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_bevilacquaj_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/bevilacquaj/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_dukuni_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_dukuni_en.md
new file mode 100644
index 00000000000000..16b12f7e9160a8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_dukuni_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_dukuni DistilBertForSequenceClassification from dukuni
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_dukuni
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_dukuni` is a English model originally trained by dukuni.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_dukuni_en_5.5.1_3.0_1737822616280.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_dukuni_en_5.5.1_3.0_1737822616280.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_dukuni","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_dukuni", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_dukuni|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/dukuni/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_dukuni_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_dukuni_pipeline_en.md
new file mode 100644
index 00000000000000..468d02a6096f62
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_dukuni_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_dukuni_pipeline pipeline DistilBertForSequenceClassification from dukuni
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_dukuni_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_dukuni_pipeline` is a English model originally trained by dukuni.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_dukuni_pipeline_en_5.5.1_3.0_1737822629433.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_dukuni_pipeline_en_5.5.1_3.0_1737822629433.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_dukuni_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_dukuni_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_dukuni_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/dukuni/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_duoduoba2020_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_duoduoba2020_en.md
new file mode 100644
index 00000000000000..a6e71c0a36296e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_duoduoba2020_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_duoduoba2020 DistilBertForSequenceClassification from duoduoba2020
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_duoduoba2020
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_duoduoba2020` is a English model originally trained by duoduoba2020.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_duoduoba2020_en_5.5.1_3.0_1737838306726.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_duoduoba2020_en_5.5.1_3.0_1737838306726.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_duoduoba2020","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_duoduoba2020", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_duoduoba2020|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/duoduoba2020/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_duoduoba2020_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_duoduoba2020_pipeline_en.md
new file mode 100644
index 00000000000000..fd120f08e97765
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_duoduoba2020_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_duoduoba2020_pipeline pipeline DistilBertForSequenceClassification from duoduoba2020
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_duoduoba2020_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_duoduoba2020_pipeline` is a English model originally trained by duoduoba2020.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_duoduoba2020_pipeline_en_5.5.1_3.0_1737838320175.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_duoduoba2020_pipeline_en_5.5.1_3.0_1737838320175.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_duoduoba2020_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_duoduoba2020_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_duoduoba2020_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/duoduoba2020/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_english_5_0_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_english_5_0_en.md
new file mode 100644
index 00000000000000..247ca96a525c3a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_english_5_0_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_english_5_0 DistilBertForSequenceClassification from LeBruse
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_english_5_0
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_english_5_0` is a English model originally trained by LeBruse.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_english_5_0_en_5.5.1_3.0_1737837880757.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_english_5_0_en_5.5.1_3.0_1737837880757.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_english_5_0","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_english_5_0", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_english_5_0|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/LeBruse/distilbert-base-uncased-finetuned-emotion-english-5.0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_english_5_0_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_english_5_0_pipeline_en.md
new file mode 100644
index 00000000000000..01af4345ab0b54
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_english_5_0_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_english_5_0_pipeline pipeline DistilBertForSequenceClassification from LeBruse
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_english_5_0_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_english_5_0_pipeline` is a English model originally trained by LeBruse.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_english_5_0_pipeline_en_5.5.1_3.0_1737837893464.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_english_5_0_pipeline_en_5.5.1_3.0_1737837893464.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_english_5_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_english_5_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_english_5_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/LeBruse/distilbert-base-uncased-finetuned-emotion-english-5.0
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_full_sets_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_full_sets_en.md
new file mode 100644
index 00000000000000..82f4bd90eb21eb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_full_sets_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_full_sets DistilBertForSequenceClassification from A01794620
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_full_sets
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_full_sets` is a English model originally trained by A01794620.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_full_sets_en_5.5.1_3.0_1737836488936.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_full_sets_en_5.5.1_3.0_1737836488936.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_full_sets","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_full_sets", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_full_sets|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/A01794620/distilbert-base-uncased-finetuned-emotion-full-sets
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_full_sets_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_full_sets_pipeline_en.md
new file mode 100644
index 00000000000000..b570fa40bd9895
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_full_sets_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_full_sets_pipeline pipeline DistilBertForSequenceClassification from A01794620
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_full_sets_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_full_sets_pipeline` is a English model originally trained by A01794620.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_full_sets_pipeline_en_5.5.1_3.0_1737836501867.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_full_sets_pipeline_en_5.5.1_3.0_1737836501867.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_full_sets_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_full_sets_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_full_sets_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/A01794620/distilbert-base-uncased-finetuned-emotion-full-sets
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_hegdesiddesh_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_hegdesiddesh_en.md
new file mode 100644
index 00000000000000..dd040ed2082f62
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_hegdesiddesh_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_hegdesiddesh DistilBertForSequenceClassification from HegdeSiddesh
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_hegdesiddesh
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_hegdesiddesh` is a English model originally trained by HegdeSiddesh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_hegdesiddesh_en_5.5.1_3.0_1737822411167.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_hegdesiddesh_en_5.5.1_3.0_1737822411167.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_hegdesiddesh","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_hegdesiddesh", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_hegdesiddesh|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/HegdeSiddesh/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_hegdesiddesh_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_hegdesiddesh_pipeline_en.md
new file mode 100644
index 00000000000000..3da6a6b7feb87b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_hegdesiddesh_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_hegdesiddesh_pipeline pipeline DistilBertForSequenceClassification from HegdeSiddesh
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_hegdesiddesh_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_hegdesiddesh_pipeline` is a English model originally trained by HegdeSiddesh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_hegdesiddesh_pipeline_en_5.5.1_3.0_1737822424504.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_hegdesiddesh_pipeline_en_5.5.1_3.0_1737822424504.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_hegdesiddesh_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_hegdesiddesh_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_hegdesiddesh_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/HegdeSiddesh/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_hyeming00_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_hyeming00_en.md
new file mode 100644
index 00000000000000..e1c92ba63c3985
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_hyeming00_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_hyeming00 DistilBertForSequenceClassification from hyeming00
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_hyeming00
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_hyeming00` is a English model originally trained by hyeming00.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_hyeming00_en_5.5.1_3.0_1737836739687.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_hyeming00_en_5.5.1_3.0_1737836739687.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_hyeming00","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_hyeming00", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_hyeming00|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/hyeming00/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_hyeming00_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_hyeming00_pipeline_en.md
new file mode 100644
index 00000000000000..7fc607560c83c9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_hyeming00_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_hyeming00_pipeline pipeline DistilBertForSequenceClassification from hyeming00
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_hyeming00_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_hyeming00_pipeline` is a English model originally trained by hyeming00.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_hyeming00_pipeline_en_5.5.1_3.0_1737836753025.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_hyeming00_pipeline_en_5.5.1_3.0_1737836753025.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_hyeming00_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_hyeming00_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_hyeming00_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/hyeming00/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_jnwulff_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_jnwulff_en.md
new file mode 100644
index 00000000000000..b797c3e1552869
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_jnwulff_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_jnwulff DistilBertForSequenceClassification from jnwulff
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_jnwulff
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_jnwulff` is a English model originally trained by jnwulff.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_jnwulff_en_5.5.1_3.0_1737822708694.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_jnwulff_en_5.5.1_3.0_1737822708694.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_jnwulff","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_jnwulff", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_jnwulff|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/jnwulff/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_jnwulff_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_jnwulff_pipeline_en.md
new file mode 100644
index 00000000000000..a5b267722bb159
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_jnwulff_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_jnwulff_pipeline pipeline DistilBertForSequenceClassification from jnwulff
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_jnwulff_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_jnwulff_pipeline` is a English model originally trained by jnwulff.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_jnwulff_pipeline_en_5.5.1_3.0_1737822721607.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_jnwulff_pipeline_en_5.5.1_3.0_1737822721607.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_jnwulff_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_jnwulff_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_jnwulff_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/jnwulff/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_juanimusso_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_juanimusso_en.md
new file mode 100644
index 00000000000000..0acae4b334bb50
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_juanimusso_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_juanimusso DistilBertForSequenceClassification from juanimusso
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_juanimusso
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_juanimusso` is a English model originally trained by juanimusso.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_juanimusso_en_5.5.1_3.0_1737838591133.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_juanimusso_en_5.5.1_3.0_1737838591133.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_juanimusso","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_juanimusso", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_juanimusso|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/juanimusso/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_juanimusso_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_juanimusso_pipeline_en.md
new file mode 100644
index 00000000000000..e2925dbbc0f5e6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_juanimusso_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_juanimusso_pipeline pipeline DistilBertForSequenceClassification from juanimusso
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_juanimusso_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_juanimusso_pipeline` is a English model originally trained by juanimusso.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_juanimusso_pipeline_en_5.5.1_3.0_1737838603468.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_juanimusso_pipeline_en_5.5.1_3.0_1737838603468.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_juanimusso_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_juanimusso_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_juanimusso_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/juanimusso/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_kyrylopanin_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_kyrylopanin_en.md
new file mode 100644
index 00000000000000..bc23755a41044f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_kyrylopanin_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_kyrylopanin DistilBertForSequenceClassification from kyrylopanin
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_kyrylopanin
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_kyrylopanin` is a English model originally trained by kyrylopanin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_kyrylopanin_en_5.5.1_3.0_1737821941065.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_kyrylopanin_en_5.5.1_3.0_1737821941065.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_kyrylopanin","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_kyrylopanin", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_kyrylopanin|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/kyrylopanin/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_kyrylopanin_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_kyrylopanin_pipeline_en.md
new file mode 100644
index 00000000000000..d5fbec7adcf78e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_kyrylopanin_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_kyrylopanin_pipeline pipeline DistilBertForSequenceClassification from kyrylopanin
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_kyrylopanin_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_kyrylopanin_pipeline` is a English model originally trained by kyrylopanin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_kyrylopanin_pipeline_en_5.5.1_3.0_1737821957793.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_kyrylopanin_pipeline_en_5.5.1_3.0_1737821957793.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_kyrylopanin_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_kyrylopanin_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_kyrylopanin_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/kyrylopanin/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_malay_sarcasm_1_0_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_malay_sarcasm_1_0_en.md
new file mode 100644
index 00000000000000..6d6400082b72c7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_malay_sarcasm_1_0_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_malay_sarcasm_1_0 DistilBertForSequenceClassification from LeBruse
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_malay_sarcasm_1_0
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_malay_sarcasm_1_0` is a English model originally trained by LeBruse.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_malay_sarcasm_1_0_en_5.5.1_3.0_1737837994781.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_malay_sarcasm_1_0_en_5.5.1_3.0_1737837994781.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_malay_sarcasm_1_0","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_malay_sarcasm_1_0", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_malay_sarcasm_1_0|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/LeBruse/distilbert-base-uncased-finetuned-emotion-malay-sarcasm-1.0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_malay_sarcasm_1_0_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_malay_sarcasm_1_0_pipeline_en.md
new file mode 100644
index 00000000000000..0ffd7c475d025e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_malay_sarcasm_1_0_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_malay_sarcasm_1_0_pipeline pipeline DistilBertForSequenceClassification from LeBruse
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_malay_sarcasm_1_0_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_malay_sarcasm_1_0_pipeline` is a English model originally trained by LeBruse.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_malay_sarcasm_1_0_pipeline_en_5.5.1_3.0_1737838008303.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_malay_sarcasm_1_0_pipeline_en_5.5.1_3.0_1737838008303.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_malay_sarcasm_1_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_malay_sarcasm_1_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_malay_sarcasm_1_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/LeBruse/distilbert-base-uncased-finetuned-emotion-malay-sarcasm-1.0
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_mikechen_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_mikechen_en.md
new file mode 100644
index 00000000000000..2381f641af26fb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_mikechen_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_mikechen DistilBertForSequenceClassification from mikechen
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_mikechen
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_mikechen` is a English model originally trained by mikechen.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_mikechen_en_5.5.1_3.0_1737838223225.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_mikechen_en_5.5.1_3.0_1737838223225.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_mikechen","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_mikechen", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_mikechen|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/mikechen/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_mikechen_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_mikechen_pipeline_en.md
new file mode 100644
index 00000000000000..617cc6ca246395
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_mikechen_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_mikechen_pipeline pipeline DistilBertForSequenceClassification from mikechen
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_mikechen_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_mikechen_pipeline` is a English model originally trained by mikechen.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_mikechen_pipeline_en_5.5.1_3.0_1737838237073.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_mikechen_pipeline_en_5.5.1_3.0_1737838237073.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_mikechen_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_mikechen_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_mikechen_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/mikechen/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_orangejun_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_orangejun_en.md
new file mode 100644
index 00000000000000..54b7f6f8c22c7d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_orangejun_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_orangejun DistilBertForSequenceClassification from OrangeJun
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_orangejun
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_orangejun` is a English model originally trained by OrangeJun.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_orangejun_en_5.5.1_3.0_1737837193710.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_orangejun_en_5.5.1_3.0_1737837193710.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_orangejun","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_orangejun", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_orangejun|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/OrangeJun/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_orangejun_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_orangejun_pipeline_en.md
new file mode 100644
index 00000000000000..6d65d409fe97d5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_orangejun_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_orangejun_pipeline pipeline DistilBertForSequenceClassification from OrangeJun
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_orangejun_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_orangejun_pipeline` is a English model originally trained by OrangeJun.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_orangejun_pipeline_en_5.5.1_3.0_1737837206452.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_orangejun_pipeline_en_5.5.1_3.0_1737837206452.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_orangejun_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_orangejun_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_orangejun_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/OrangeJun/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_orenot_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_orenot_en.md
new file mode 100644
index 00000000000000..40de24edc0627e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_orenot_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_orenot DistilBertForSequenceClassification from orenot
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_orenot
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_orenot` is a English model originally trained by orenot.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_orenot_en_5.5.1_3.0_1737836977743.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_orenot_en_5.5.1_3.0_1737836977743.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_orenot","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_orenot", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_orenot|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/orenot/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_orenot_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_orenot_pipeline_en.md
new file mode 100644
index 00000000000000..cdba1a1c010635
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_orenot_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_orenot_pipeline pipeline DistilBertForSequenceClassification from orenot
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_orenot_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_orenot_pipeline` is a English model originally trained by orenot.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_orenot_pipeline_en_5.5.1_3.0_1737836991077.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_orenot_pipeline_en_5.5.1_3.0_1737836991077.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_orenot_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_orenot_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_orenot_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/orenot/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_rbxo0128_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_rbxo0128_en.md
new file mode 100644
index 00000000000000..5d8d4e33e36728
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_rbxo0128_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_rbxo0128 DistilBertForSequenceClassification from rbxo0128
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_rbxo0128
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_rbxo0128` is a English model originally trained by rbxo0128.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_rbxo0128_en_5.5.1_3.0_1737836642847.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_rbxo0128_en_5.5.1_3.0_1737836642847.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_rbxo0128","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_rbxo0128", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_rbxo0128|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/rbxo0128/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_rbxo0128_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_rbxo0128_pipeline_en.md
new file mode 100644
index 00000000000000..43bf9098cfe34b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_rbxo0128_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_rbxo0128_pipeline pipeline DistilBertForSequenceClassification from rbxo0128
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_rbxo0128_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_rbxo0128_pipeline` is a English model originally trained by rbxo0128.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_rbxo0128_pipeline_en_5.5.1_3.0_1737836655687.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_rbxo0128_pipeline_en_5.5.1_3.0_1737836655687.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_rbxo0128_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_rbxo0128_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_rbxo0128_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/rbxo0128/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_reynaldhavard_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_reynaldhavard_en.md
new file mode 100644
index 00000000000000..e9ecffea6b61f1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_reynaldhavard_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_reynaldhavard DistilBertForSequenceClassification from reynaldhavard
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_reynaldhavard
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_reynaldhavard` is a English model originally trained by reynaldhavard.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_reynaldhavard_en_5.5.1_3.0_1737836632215.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_reynaldhavard_en_5.5.1_3.0_1737836632215.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_reynaldhavard","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_reynaldhavard", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_reynaldhavard|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/reynaldhavard/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_reynaldhavard_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_reynaldhavard_pipeline_en.md
new file mode 100644
index 00000000000000..c0f3b52a4b3c2a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_reynaldhavard_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_reynaldhavard_pipeline pipeline DistilBertForSequenceClassification from reynaldhavard
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_reynaldhavard_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_reynaldhavard_pipeline` is a English model originally trained by reynaldhavard.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_reynaldhavard_pipeline_en_5.5.1_3.0_1737836645362.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_reynaldhavard_pipeline_en_5.5.1_3.0_1737836645362.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_reynaldhavard_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_reynaldhavard_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_reynaldhavard_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/reynaldhavard/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_stevenxxzg_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_stevenxxzg_en.md
new file mode 100644
index 00000000000000..a388f5b72f515e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_stevenxxzg_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_stevenxxzg DistilBertForSequenceClassification from stevenxxzg
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_stevenxxzg
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_stevenxxzg` is a English model originally trained by stevenxxzg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_stevenxxzg_en_5.5.1_3.0_1737837991591.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_stevenxxzg_en_5.5.1_3.0_1737837991591.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_stevenxxzg","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_stevenxxzg", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_stevenxxzg|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/stevenxxzg/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_stevenxxzg_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_stevenxxzg_pipeline_en.md
new file mode 100644
index 00000000000000..09c6ab444d8652
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_stevenxxzg_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_stevenxxzg_pipeline pipeline DistilBertForSequenceClassification from stevenxxzg
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_stevenxxzg_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_stevenxxzg_pipeline` is a English model originally trained by stevenxxzg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_stevenxxzg_pipeline_en_5.5.1_3.0_1737838004826.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_stevenxxzg_pipeline_en_5.5.1_3.0_1737838004826.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_stevenxxzg_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_stevenxxzg_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_stevenxxzg_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/stevenxxzg/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_tajshvra_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_tajshvra_en.md
new file mode 100644
index 00000000000000..5561e84b1c5c4e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_tajshvra_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_tajshvra DistilBertForSequenceClassification from tajshvra
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_tajshvra
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_tajshvra` is a English model originally trained by tajshvra.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_tajshvra_en_5.5.1_3.0_1737837864897.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_tajshvra_en_5.5.1_3.0_1737837864897.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_tajshvra","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_tajshvra", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_tajshvra|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/tajshvra/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_tajshvra_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_tajshvra_pipeline_en.md
new file mode 100644
index 00000000000000..112801afe09225
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_tajshvra_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_tajshvra_pipeline pipeline DistilBertForSequenceClassification from tajshvra
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_tajshvra_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_tajshvra_pipeline` is a English model originally trained by tajshvra.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_tajshvra_pipeline_en_5.5.1_3.0_1737837878451.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_tajshvra_pipeline_en_5.5.1_3.0_1737837878451.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_tajshvra_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_tajshvra_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_tajshvra_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/tajshvra/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_vanderlist_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_vanderlist_en.md
new file mode 100644
index 00000000000000..0610bafe285e59
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_vanderlist_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_vanderlist DistilBertForSequenceClassification from vanderlist
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_vanderlist
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_vanderlist` is a English model originally trained by vanderlist.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_vanderlist_en_5.5.1_3.0_1737836868218.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_vanderlist_en_5.5.1_3.0_1737836868218.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_vanderlist","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_vanderlist", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_vanderlist|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/vanderlist/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_vanderlist_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_vanderlist_pipeline_en.md
new file mode 100644
index 00000000000000..14d643c0bf16db
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotion_vanderlist_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_vanderlist_pipeline pipeline DistilBertForSequenceClassification from vanderlist
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_vanderlist_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_vanderlist_pipeline` is a English model originally trained by vanderlist.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_vanderlist_pipeline_en_5.5.1_3.0_1737836881109.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_vanderlist_pipeline_en_5.5.1_3.0_1737836881109.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_vanderlist_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_vanderlist_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_vanderlist_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/vanderlist/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotions_1mind_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotions_1mind_en.md
new file mode 100644
index 00000000000000..56196a9bb4d124
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotions_1mind_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotions_1mind DistilBertForSequenceClassification from 1mind
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotions_1mind
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotions_1mind` is a English model originally trained by 1mind.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotions_1mind_en_5.5.1_3.0_1737822495093.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotions_1mind_en_5.5.1_3.0_1737822495093.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotions_1mind","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotions_1mind", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotions_1mind|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/1mind/distilbert-base-uncased-finetuned-emotions
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotions_1mind_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotions_1mind_pipeline_en.md
new file mode 100644
index 00000000000000..6fbb21cc4a1ac2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotions_1mind_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotions_1mind_pipeline pipeline DistilBertForSequenceClassification from 1mind
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotions_1mind_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotions_1mind_pipeline` is a English model originally trained by 1mind.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotions_1mind_pipeline_en_5.5.1_3.0_1737822508553.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotions_1mind_pipeline_en_5.5.1_3.0_1737822508553.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotions_1mind_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotions_1mind_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotions_1mind_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/1mind/distilbert-base-uncased-finetuned-emotions
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotions_cindyangelira_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotions_cindyangelira_en.md
new file mode 100644
index 00000000000000..4502f5b0445b43
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotions_cindyangelira_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotions_cindyangelira DistilBertForSequenceClassification from cindyangelira
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotions_cindyangelira
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotions_cindyangelira` is a English model originally trained by cindyangelira.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotions_cindyangelira_en_5.5.1_3.0_1737837105855.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotions_cindyangelira_en_5.5.1_3.0_1737837105855.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotions_cindyangelira","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotions_cindyangelira", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotions_cindyangelira|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/cindyangelira/distilbert-base-uncased-finetuned-emotions
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotions_cindyangelira_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotions_cindyangelira_pipeline_en.md
new file mode 100644
index 00000000000000..b7a159403089b1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_emotions_cindyangelira_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotions_cindyangelira_pipeline pipeline DistilBertForSequenceClassification from cindyangelira
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotions_cindyangelira_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotions_cindyangelira_pipeline` is a English model originally trained by cindyangelira.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotions_cindyangelira_pipeline_en_5.5.1_3.0_1737837121206.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotions_cindyangelira_pipeline_en_5.5.1_3.0_1737837121206.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotions_cindyangelira_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotions_cindyangelira_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotions_cindyangelira_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/cindyangelira/distilbert-base-uncased-finetuned-emotions
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_intro_verizon_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_intro_verizon_en.md
new file mode 100644
index 00000000000000..052f9bee2b612f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_intro_verizon_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_intro_verizon DistilBertForSequenceClassification from TieIncred
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_intro_verizon
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_intro_verizon` is a English model originally trained by TieIncred.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_intro_verizon_en_5.5.1_3.0_1737836529895.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_intro_verizon_en_5.5.1_3.0_1737836529895.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_intro_verizon","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_intro_verizon", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_intro_verizon|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/TieIncred/distilbert-base-uncased-finetuned-intro-verizon
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_intro_verizon_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_intro_verizon_pipeline_en.md
new file mode 100644
index 00000000000000..79fd666e8a6721
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_intro_verizon_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_intro_verizon_pipeline pipeline DistilBertForSequenceClassification from TieIncred
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_intro_verizon_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_intro_verizon_pipeline` is a English model originally trained by TieIncred.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_intro_verizon_pipeline_en_5.5.1_3.0_1737836548483.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_intro_verizon_pipeline_en_5.5.1_3.0_1737836548483.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_intro_verizon_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_intro_verizon_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_intro_verizon_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/TieIncred/distilbert-base-uncased-finetuned-intro-verizon
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_on_emotions_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_on_emotions_en.md
new file mode 100644
index 00000000000000..9879a6331a9f5c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_on_emotions_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_on_emotions DistilBertForSequenceClassification from hange
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_on_emotions
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_on_emotions` is a English model originally trained by hange.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_on_emotions_en_5.5.1_3.0_1737837755900.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_on_emotions_en_5.5.1_3.0_1737837755900.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_on_emotions","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_on_emotions", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_on_emotions|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/hange/distilbert-base-uncased-finetuned-on-emotions
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_on_emotions_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_on_emotions_pipeline_en.md
new file mode 100644
index 00000000000000..d209951d67dba8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_on_emotions_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_on_emotions_pipeline pipeline DistilBertForSequenceClassification from hange
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_on_emotions_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_on_emotions_pipeline` is a English model originally trained by hange.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_on_emotions_pipeline_en_5.5.1_3.0_1737837769147.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_on_emotions_pipeline_en_5.5.1_3.0_1737837769147.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_on_emotions_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_on_emotions_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_on_emotions_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/hange/distilbert-base-uncased-finetuned-on-emotions
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_t_overall_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_t_overall_en.md
new file mode 100644
index 00000000000000..bcd74bfb786a24
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_t_overall_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_t_overall DistilBertForSequenceClassification from Gregorig
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_t_overall
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_t_overall` is a English model originally trained by Gregorig.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_t_overall_en_5.5.1_3.0_1737822171038.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_t_overall_en_5.5.1_3.0_1737822171038.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_t_overall","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_t_overall", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_t_overall|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Gregorig/distilbert-base-uncased-finetuned-t_overall
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_t_overall_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_t_overall_pipeline_en.md
new file mode 100644
index 00000000000000..9b522626eb2e57
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_finetuned_t_overall_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_t_overall_pipeline pipeline DistilBertForSequenceClassification from Gregorig
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_t_overall_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_t_overall_pipeline` is a English model originally trained by Gregorig.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_t_overall_pipeline_en_5.5.1_3.0_1737822184358.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_t_overall_pipeline_en_5.5.1_3.0_1737822184358.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_t_overall_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_t_overall_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_t_overall_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Gregorig/distilbert-base-uncased-finetuned-t_overall
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_sentiment_finetuned_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_sentiment_finetuned_en.md
new file mode 100644
index 00000000000000..fc641f850d5da4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_sentiment_finetuned_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_sentiment_finetuned DistilBertForSequenceClassification from Suhana-37
+author: John Snow Labs
+name: distilbert_base_uncased_sentiment_finetuned
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_sentiment_finetuned` is a English model originally trained by Suhana-37.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_sentiment_finetuned_en_5.5.1_3.0_1737822142701.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_sentiment_finetuned_en_5.5.1_3.0_1737822142701.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_sentiment_finetuned","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_sentiment_finetuned", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_sentiment_finetuned|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Suhana-37/distilbert-base-uncased-sentiment-finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_sentiment_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_sentiment_finetuned_pipeline_en.md
new file mode 100644
index 00000000000000..0aa00067080444
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_sentiment_finetuned_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_sentiment_finetuned_pipeline pipeline DistilBertForSequenceClassification from Suhana-37
+author: John Snow Labs
+name: distilbert_base_uncased_sentiment_finetuned_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_sentiment_finetuned_pipeline` is a English model originally trained by Suhana-37.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_sentiment_finetuned_pipeline_en_5.5.1_3.0_1737822156133.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_sentiment_finetuned_pipeline_en_5.5.1_3.0_1737822156133.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_sentiment_finetuned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_sentiment_finetuned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_sentiment_finetuned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Suhana-37/distilbert-base-uncased-sentiment-finetuned
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_steam_sentiment_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_steam_sentiment_en.md
new file mode 100644
index 00000000000000..dfb8b966100d64
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_steam_sentiment_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_steam_sentiment DistilBertForSequenceClassification from ericsonwillians
+author: John Snow Labs
+name: distilbert_base_uncased_steam_sentiment
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_steam_sentiment` is a English model originally trained by ericsonwillians.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_steam_sentiment_en_5.5.1_3.0_1737837634482.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_steam_sentiment_en_5.5.1_3.0_1737837634482.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_steam_sentiment","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_steam_sentiment", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_steam_sentiment|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/ericsonwillians/distilbert-base-uncased-steam-sentiment
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_steam_sentiment_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_steam_sentiment_pipeline_en.md
new file mode 100644
index 00000000000000..67384e2f0c0017
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_steam_sentiment_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_steam_sentiment_pipeline pipeline DistilBertForSequenceClassification from ericsonwillians
+author: John Snow Labs
+name: distilbert_base_uncased_steam_sentiment_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_steam_sentiment_pipeline` is a English model originally trained by ericsonwillians.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_steam_sentiment_pipeline_en_5.5.1_3.0_1737837648960.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_steam_sentiment_pipeline_en_5.5.1_3.0_1737837648960.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_steam_sentiment_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_steam_sentiment_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_steam_sentiment_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/ericsonwillians/distilbert-base-uncased-steam-sentiment
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_survey_category_0_0_2_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_survey_category_0_0_2_en.md
new file mode 100644
index 00000000000000..9280579beeb536
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_survey_category_0_0_2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_survey_category_0_0_2 DistilBertForSequenceClassification from ansilmbabl
+author: John Snow Labs
+name: distilbert_base_uncased_survey_category_0_0_2
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_survey_category_0_0_2` is a English model originally trained by ansilmbabl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_survey_category_0_0_2_en_5.5.1_3.0_1737811682636.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_survey_category_0_0_2_en_5.5.1_3.0_1737811682636.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_survey_category_0_0_2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_survey_category_0_0_2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_survey_category_0_0_2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/ansilmbabl/distilbert-base-uncased-survey-category-0.0.2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_survey_category_0_0_2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_survey_category_0_0_2_pipeline_en.md
new file mode 100644
index 00000000000000..b0f7b66226a3ca
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_base_uncased_survey_category_0_0_2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_survey_category_0_0_2_pipeline pipeline DistilBertForSequenceClassification from ansilmbabl
+author: John Snow Labs
+name: distilbert_base_uncased_survey_category_0_0_2_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_survey_category_0_0_2_pipeline` is a English model originally trained by ansilmbabl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_survey_category_0_0_2_pipeline_en_5.5.1_3.0_1737811696178.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_survey_category_0_0_2_pipeline_en_5.5.1_3.0_1737811696178.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_survey_category_0_0_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_survey_category_0_0_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_survey_category_0_0_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/ansilmbabl/distilbert-base-uncased-survey-category-0.0.2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_classifier_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_classifier_en.md
new file mode 100644
index 00000000000000..34597c8be8364e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_classifier_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_classifier DistilBertForSequenceClassification from evelynkol
+author: John Snow Labs
+name: distilbert_classifier
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_classifier` is a English model originally trained by evelynkol.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_classifier_en_5.5.1_3.0_1737838421304.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_classifier_en_5.5.1_3.0_1737838421304.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_classifier","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_classifier", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_classifier|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/evelynkol/distilbert-classifier
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_classifier_pipeline_en.md
new file mode 100644
index 00000000000000..73ac2859be2082
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_classifier_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_classifier_pipeline pipeline DistilBertForSequenceClassification from evelynkol
+author: John Snow Labs
+name: distilbert_classifier_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_classifier_pipeline` is a English model originally trained by evelynkol.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_classifier_pipeline_en_5.5.1_3.0_1737838435118.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_classifier_pipeline_en_5.5.1_3.0_1737838435118.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_classifier_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_classifier_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_classifier_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/evelynkol/distilbert-classifier
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_coping_replies_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_coping_replies_en.md
new file mode 100644
index 00000000000000..ff2f6f63c598bb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_coping_replies_en.md
@@ -0,0 +1,96 @@
+---
+layout: model
+title: English distilbert_coping_replies DistilBertForSequenceClassification from coping-appraisal
+author: John Snow Labs
+name: distilbert_coping_replies
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_coping_replies` is a English model originally trained by coping-appraisal.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_coping_replies_en_5.5.1_3.0_1737837101500.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_coping_replies_en_5.5.1_3.0_1737837101500.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_coping_replies","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_coping_replies", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_coping_replies|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+References
+
+https://huggingface.co/coping-appraisal/distilbert-coping-replies
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_coping_replies_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_coping_replies_pipeline_en.md
new file mode 100644
index 00000000000000..5e776c493e1c72
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_coping_replies_pipeline_en.md
@@ -0,0 +1,72 @@
+---
+layout: model
+title: English distilbert_coping_replies_pipeline pipeline DistilBertForSequenceClassification from coping-appraisal
+author: John Snow Labs
+name: distilbert_coping_replies_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_coping_replies_pipeline` is a English model originally trained by coping-appraisal.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_coping_replies_pipeline_en_5.5.1_3.0_1737837115358.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_coping_replies_pipeline_en_5.5.1_3.0_1737837115358.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("distilbert_coping_replies_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("distilbert_coping_replies_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_coping_replies_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+References
+
+https://huggingface.co/coping-appraisal/distilbert-coping-replies
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_epu_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_epu_en.md
new file mode 100644
index 00000000000000..ef0753a13f00d1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_epu_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_epu DistilBertForSequenceClassification from Drshafi
+author: John Snow Labs
+name: distilbert_epu
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_epu` is a English model originally trained by Drshafi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_epu_en_5.5.1_3.0_1737811379803.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_epu_en_5.5.1_3.0_1737811379803.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_epu","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_epu", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_epu|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Drshafi/distilbert_EPU
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_epu_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_epu_pipeline_en.md
new file mode 100644
index 00000000000000..1dcd6f119a365c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_epu_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_epu_pipeline pipeline DistilBertForSequenceClassification from Drshafi
+author: John Snow Labs
+name: distilbert_epu_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_epu_pipeline` is a English model originally trained by Drshafi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_epu_pipeline_en_5.5.1_3.0_1737811396473.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_epu_pipeline_en_5.5.1_3.0_1737811396473.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_epu_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_epu_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_epu_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Drshafi/distilbert_EPU
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_finetune_araproje_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_finetune_araproje_en.md
new file mode 100644
index 00000000000000..6907638c534689
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_finetune_araproje_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_finetune_araproje DistilBertForSequenceClassification from rmysysv
+author: John Snow Labs
+name: distilbert_finetune_araproje
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetune_araproje` is a English model originally trained by rmysysv.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_finetune_araproje_en_5.5.1_3.0_1737812091871.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetune_araproje_en_5.5.1_3.0_1737812091871.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_finetune_araproje","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_finetune_araproje", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_finetune_araproje|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|254.1 MB|
+
+## References
+
+https://huggingface.co/rmysysv/distilbert-finetune-araproje
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_finetune_araproje_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_finetune_araproje_pipeline_en.md
new file mode 100644
index 00000000000000..33c61035ac8ae8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_finetune_araproje_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_finetune_araproje_pipeline pipeline DistilBertForSequenceClassification from rmysysv
+author: John Snow Labs
+name: distilbert_finetune_araproje_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetune_araproje_pipeline` is a English model originally trained by rmysysv.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_finetune_araproje_pipeline_en_5.5.1_3.0_1737812105154.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetune_araproje_pipeline_en_5.5.1_3.0_1737812105154.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_finetune_araproje_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_finetune_araproje_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_finetune_araproje_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|254.1 MB|
+
+## References
+
+https://huggingface.co/rmysysv/distilbert-finetune-araproje
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_finetuned_karthik_sriram_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_finetuned_karthik_sriram_en.md
new file mode 100644
index 00000000000000..0ec4522b1a9346
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_finetuned_karthik_sriram_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_finetuned_karthik_sriram DistilBertForSequenceClassification from Karthik-Sriram
+author: John Snow Labs
+name: distilbert_finetuned_karthik_sriram
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetuned_karthik_sriram` is a English model originally trained by Karthik-Sriram.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_karthik_sriram_en_5.5.1_3.0_1737822510226.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_karthik_sriram_en_5.5.1_3.0_1737822510226.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_finetuned_karthik_sriram","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_finetuned_karthik_sriram", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_finetuned_karthik_sriram|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Karthik-Sriram/distilbert-finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_finetuned_karthik_sriram_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_finetuned_karthik_sriram_pipeline_en.md
new file mode 100644
index 00000000000000..a65a73b0ead66a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_finetuned_karthik_sriram_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_finetuned_karthik_sriram_pipeline pipeline DistilBertForSequenceClassification from Karthik-Sriram
+author: John Snow Labs
+name: distilbert_finetuned_karthik_sriram_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetuned_karthik_sriram_pipeline` is a English model originally trained by Karthik-Sriram.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_karthik_sriram_pipeline_en_5.5.1_3.0_1737822524487.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_karthik_sriram_pipeline_en_5.5.1_3.0_1737822524487.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_finetuned_karthik_sriram_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_finetuned_karthik_sriram_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_finetuned_karthik_sriram_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Karthik-Sriram/distilbert-finetuned
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_lda_100_v1_wnli_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_lda_100_v1_wnli_en.md
new file mode 100644
index 00000000000000..d57355b79755b2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_lda_100_v1_wnli_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_lda_100_v1_wnli DistilBertForSequenceClassification from gokulsrinivasagan
+author: John Snow Labs
+name: distilbert_lda_100_v1_wnli
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_lda_100_v1_wnli` is a English model originally trained by gokulsrinivasagan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_lda_100_v1_wnli_en_5.5.1_3.0_1737838458072.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_lda_100_v1_wnli_en_5.5.1_3.0_1737838458072.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_lda_100_v1_wnli","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_lda_100_v1_wnli", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_lda_100_v1_wnli|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|251.2 MB|
+
+## References
+
+https://huggingface.co/gokulsrinivasagan/distilbert_lda_100_v1_wnli
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_lda_100_v1_wnli_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_lda_100_v1_wnli_pipeline_en.md
new file mode 100644
index 00000000000000..c33465941826c6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_lda_100_v1_wnli_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_lda_100_v1_wnli_pipeline pipeline DistilBertForSequenceClassification from gokulsrinivasagan
+author: John Snow Labs
+name: distilbert_lda_100_v1_wnli_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_lda_100_v1_wnli_pipeline` is a English model originally trained by gokulsrinivasagan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_lda_100_v1_wnli_pipeline_en_5.5.1_3.0_1737838470541.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_lda_100_v1_wnli_pipeline_en_5.5.1_3.0_1737838470541.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_lda_100_v1_wnli_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_lda_100_v1_wnli_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_lda_100_v1_wnli_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|251.3 MB|
+
+## References
+
+https://huggingface.co/gokulsrinivasagan/distilbert_lda_100_v1_wnli
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_lda_50_v1_mnli_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_lda_50_v1_mnli_en.md
new file mode 100644
index 00000000000000..e4681a1b28b345
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_lda_50_v1_mnli_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_lda_50_v1_mnli DistilBertForSequenceClassification from gokulsrinivasagan
+author: John Snow Labs
+name: distilbert_lda_50_v1_mnli
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_lda_50_v1_mnli` is a English model originally trained by gokulsrinivasagan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_lda_50_v1_mnli_en_5.5.1_3.0_1737837804602.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_lda_50_v1_mnli_en_5.5.1_3.0_1737837804602.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_lda_50_v1_mnli","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_lda_50_v1_mnli", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_lda_50_v1_mnli|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|251.2 MB|
+
+## References
+
+https://huggingface.co/gokulsrinivasagan/distilbert_lda_50_v1_mnli
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_lda_50_v1_mnli_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_lda_50_v1_mnli_pipeline_en.md
new file mode 100644
index 00000000000000..fa4904df3c8bf4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_lda_50_v1_mnli_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_lda_50_v1_mnli_pipeline pipeline DistilBertForSequenceClassification from gokulsrinivasagan
+author: John Snow Labs
+name: distilbert_lda_50_v1_mnli_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_lda_50_v1_mnli_pipeline` is a English model originally trained by gokulsrinivasagan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_lda_50_v1_mnli_pipeline_en_5.5.1_3.0_1737837816935.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_lda_50_v1_mnli_pipeline_en_5.5.1_3.0_1737837816935.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_lda_50_v1_mnli_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_lda_50_v1_mnli_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_lda_50_v1_mnli_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|251.3 MB|
+
+## References
+
+https://huggingface.co/gokulsrinivasagan/distilbert_lda_50_v1_mnli
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_lda_5_v1_rte_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_lda_5_v1_rte_en.md
new file mode 100644
index 00000000000000..26aee784794e93
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_lda_5_v1_rte_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_lda_5_v1_rte DistilBertForSequenceClassification from gokulsrinivasagan
+author: John Snow Labs
+name: distilbert_lda_5_v1_rte
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_lda_5_v1_rte` is a English model originally trained by gokulsrinivasagan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_lda_5_v1_rte_en_5.5.1_3.0_1737838197506.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_lda_5_v1_rte_en_5.5.1_3.0_1737838197506.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_lda_5_v1_rte","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_lda_5_v1_rte", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_lda_5_v1_rte|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|251.2 MB|
+
+## References
+
+https://huggingface.co/gokulsrinivasagan/distilbert_lda_5_v1_rte
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_lda_5_v1_rte_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_lda_5_v1_rte_pipeline_en.md
new file mode 100644
index 00000000000000..3145a87ea47ea3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_lda_5_v1_rte_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_lda_5_v1_rte_pipeline pipeline DistilBertForSequenceClassification from gokulsrinivasagan
+author: John Snow Labs
+name: distilbert_lda_5_v1_rte_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_lda_5_v1_rte_pipeline` is a English model originally trained by gokulsrinivasagan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_lda_5_v1_rte_pipeline_en_5.5.1_3.0_1737838210392.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_lda_5_v1_rte_pipeline_en_5.5.1_3.0_1737838210392.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_lda_5_v1_rte_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_lda_5_v1_rte_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_lda_5_v1_rte_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|251.3 MB|
+
+## References
+
+https://huggingface.co/gokulsrinivasagan/distilbert_lda_5_v1_rte
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_ndd_html_content_tags_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_ndd_html_content_tags_en.md
new file mode 100644
index 00000000000000..1b2201babc53d4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_ndd_html_content_tags_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_ndd_html_content_tags DistilBertForSequenceClassification from lgk03
+author: John Snow Labs
+name: distilbert_ndd_html_content_tags
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_ndd_html_content_tags` is a English model originally trained by lgk03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_ndd_html_content_tags_en_5.5.1_3.0_1737837249414.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_ndd_html_content_tags_en_5.5.1_3.0_1737837249414.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_ndd_html_content_tags","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_ndd_html_content_tags", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_ndd_html_content_tags|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/lgk03/distilBERT-NDD.html.content_tags
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_ndd_html_content_tags_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_ndd_html_content_tags_pipeline_en.md
new file mode 100644
index 00000000000000..20123fa0ee29c4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_ndd_html_content_tags_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_ndd_html_content_tags_pipeline pipeline DistilBertForSequenceClassification from lgk03
+author: John Snow Labs
+name: distilbert_ndd_html_content_tags_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_ndd_html_content_tags_pipeline` is a English model originally trained by lgk03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_ndd_html_content_tags_pipeline_en_5.5.1_3.0_1737837262072.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_ndd_html_content_tags_pipeline_en_5.5.1_3.0_1737837262072.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_ndd_html_content_tags_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_ndd_html_content_tags_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_ndd_html_content_tags_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/lgk03/distilBERT-NDD.html.content_tags
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_rotten_tomatoes_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_rotten_tomatoes_en.md
new file mode 100644
index 00000000000000..14f7be32d281a7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_rotten_tomatoes_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_rotten_tomatoes DistilBertForSequenceClassification from huiang
+author: John Snow Labs
+name: distilbert_rotten_tomatoes
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_rotten_tomatoes` is a English model originally trained by huiang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_rotten_tomatoes_en_5.5.1_3.0_1737837763526.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_rotten_tomatoes_en_5.5.1_3.0_1737837763526.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_rotten_tomatoes","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_rotten_tomatoes", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_rotten_tomatoes|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/huiang/distilbert-rotten_tomatoes
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_rotten_tomatoes_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_rotten_tomatoes_pipeline_en.md
new file mode 100644
index 00000000000000..5a6d04edab8a0d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_rotten_tomatoes_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_rotten_tomatoes_pipeline pipeline DistilBertForSequenceClassification from huiang
+author: John Snow Labs
+name: distilbert_rotten_tomatoes_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_rotten_tomatoes_pipeline` is a English model originally trained by huiang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_rotten_tomatoes_pipeline_en_5.5.1_3.0_1737837778935.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_rotten_tomatoes_pipeline_en_5.5.1_3.0_1737837778935.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_rotten_tomatoes_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_rotten_tomatoes_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_rotten_tomatoes_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/huiang/distilbert-rotten_tomatoes
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_scam_classification_v1_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_scam_classification_v1_en.md
new file mode 100644
index 00000000000000..53624aa99e5e8a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_scam_classification_v1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_scam_classification_v1 DistilBertForSequenceClassification from BothBosu
+author: John Snow Labs
+name: distilbert_scam_classification_v1
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_scam_classification_v1` is a English model originally trained by BothBosu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_scam_classification_v1_en_5.5.1_3.0_1737838568419.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_scam_classification_v1_en_5.5.1_3.0_1737838568419.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_scam_classification_v1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_scam_classification_v1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_scam_classification_v1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/BothBosu/distilbert-scam-classification-v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_scam_classification_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_scam_classification_v1_pipeline_en.md
new file mode 100644
index 00000000000000..4e2286a874d2c7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_scam_classification_v1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_scam_classification_v1_pipeline pipeline DistilBertForSequenceClassification from BothBosu
+author: John Snow Labs
+name: distilbert_scam_classification_v1_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_scam_classification_v1_pipeline` is a English model originally trained by BothBosu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_scam_classification_v1_pipeline_en_5.5.1_3.0_1737838581667.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_scam_classification_v1_pipeline_en_5.5.1_3.0_1737838581667.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_scam_classification_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_scam_classification_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_scam_classification_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/BothBosu/distilbert-scam-classification-v1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_small_offensive_classification_test_af2024ma_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_small_offensive_classification_test_af2024ma_en.md
new file mode 100644
index 00000000000000..4a179042d51e57
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_small_offensive_classification_test_af2024ma_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_small_offensive_classification_test_af2024ma DistilBertForSequenceClassification from Af2024ma
+author: John Snow Labs
+name: distilbert_small_offensive_classification_test_af2024ma
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_small_offensive_classification_test_af2024ma` is a English model originally trained by Af2024ma.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_small_offensive_classification_test_af2024ma_en_5.5.1_3.0_1737836404239.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_small_offensive_classification_test_af2024ma_en_5.5.1_3.0_1737836404239.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_small_offensive_classification_test_af2024ma","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_small_offensive_classification_test_af2024ma", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_small_offensive_classification_test_af2024ma|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|813.2 MB|
+
+## References
+
+https://huggingface.co/Af2024ma/distilbert-small-offensive-classification-test
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_small_offensive_classification_test_af2024ma_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_small_offensive_classification_test_af2024ma_pipeline_en.md
new file mode 100644
index 00000000000000..8ea5a91cee1f79
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_small_offensive_classification_test_af2024ma_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_small_offensive_classification_test_af2024ma_pipeline pipeline DistilBertForSequenceClassification from Af2024ma
+author: John Snow Labs
+name: distilbert_small_offensive_classification_test_af2024ma_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_small_offensive_classification_test_af2024ma_pipeline` is a English model originally trained by Af2024ma.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_small_offensive_classification_test_af2024ma_pipeline_en_5.5.1_3.0_1737836526522.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_small_offensive_classification_test_af2024ma_pipeline_en_5.5.1_3.0_1737836526522.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_small_offensive_classification_test_af2024ma_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_small_offensive_classification_test_af2024ma_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_small_offensive_classification_test_af2024ma_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|813.2 MB|
+
+## References
+
+https://huggingface.co/Af2024ma/distilbert-small-offensive-classification-test
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_small_offensive_classification_test_vastoxlordes_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_small_offensive_classification_test_vastoxlordes_en.md
new file mode 100644
index 00000000000000..cf41f9c8e63dbb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_small_offensive_classification_test_vastoxlordes_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_small_offensive_classification_test_vastoxlordes DistilBertForSequenceClassification from VastoXlordes
+author: John Snow Labs
+name: distilbert_small_offensive_classification_test_vastoxlordes
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_small_offensive_classification_test_vastoxlordes` is a English model originally trained by VastoXlordes.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_small_offensive_classification_test_vastoxlordes_en_5.5.1_3.0_1737837228894.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_small_offensive_classification_test_vastoxlordes_en_5.5.1_3.0_1737837228894.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_small_offensive_classification_test_vastoxlordes","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_small_offensive_classification_test_vastoxlordes", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_small_offensive_classification_test_vastoxlordes|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|809.1 MB|
+
+## References
+
+https://huggingface.co/VastoXlordes/distilbert-small-offensive-classification-test
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_small_offensive_classification_test_vastoxlordes_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_small_offensive_classification_test_vastoxlordes_pipeline_en.md
new file mode 100644
index 00000000000000..f4a64bbbdd5966
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_small_offensive_classification_test_vastoxlordes_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_small_offensive_classification_test_vastoxlordes_pipeline pipeline DistilBertForSequenceClassification from VastoXlordes
+author: John Snow Labs
+name: distilbert_small_offensive_classification_test_vastoxlordes_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_small_offensive_classification_test_vastoxlordes_pipeline` is a English model originally trained by VastoXlordes.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_small_offensive_classification_test_vastoxlordes_pipeline_en_5.5.1_3.0_1737837344465.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_small_offensive_classification_test_vastoxlordes_pipeline_en_5.5.1_3.0_1737837344465.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_small_offensive_classification_test_vastoxlordes_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_small_offensive_classification_test_vastoxlordes_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_small_offensive_classification_test_vastoxlordes_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|809.1 MB|
+
+## References
+
+https://huggingface.co/VastoXlordes/distilbert-small-offensive-classification-test
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_uncased_assamese_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_uncased_assamese_en.md
new file mode 100644
index 00000000000000..8c0cea78200f28
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_uncased_assamese_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_uncased_assamese DistilBertForSequenceClassification from raulgdp
+author: John Snow Labs
+name: distilbert_uncased_assamese
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_uncased_assamese` is a English model originally trained by raulgdp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_uncased_assamese_en_5.5.1_3.0_1737822232899.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_uncased_assamese_en_5.5.1_3.0_1737822232899.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_uncased_assamese","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_uncased_assamese", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_uncased_assamese|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/raulgdp/Distilbert-uncased-AS
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_uncased_assamese_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_uncased_assamese_pipeline_en.md
new file mode 100644
index 00000000000000..c98aee0e30bf61
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_uncased_assamese_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_uncased_assamese_pipeline pipeline DistilBertForSequenceClassification from raulgdp
+author: John Snow Labs
+name: distilbert_uncased_assamese_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_uncased_assamese_pipeline` is a English model originally trained by raulgdp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_uncased_assamese_pipeline_en_5.5.1_3.0_1737822245987.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_uncased_assamese_pipeline_en_5.5.1_3.0_1737822245987.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_uncased_assamese_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_uncased_assamese_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_uncased_assamese_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/raulgdp/Distilbert-uncased-AS
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_vietnamese_sentiment_analyst_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_vietnamese_sentiment_analyst_en.md
new file mode 100644
index 00000000000000..f09e522a4cfe7d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_vietnamese_sentiment_analyst_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_vietnamese_sentiment_analyst DistilBertForSequenceClassification from Kawaiibuta
+author: John Snow Labs
+name: distilbert_vietnamese_sentiment_analyst
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_vietnamese_sentiment_analyst` is a English model originally trained by Kawaiibuta.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_vietnamese_sentiment_analyst_en_5.5.1_3.0_1737836394578.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_vietnamese_sentiment_analyst_en_5.5.1_3.0_1737836394578.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_vietnamese_sentiment_analyst","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_vietnamese_sentiment_analyst", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_vietnamese_sentiment_analyst|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|507.6 MB|
+
+## References
+
+https://huggingface.co/Kawaiibuta/distilBERT_vietnamese_sentiment_analyst
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_vietnamese_sentiment_analyst_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_vietnamese_sentiment_analyst_pipeline_en.md
new file mode 100644
index 00000000000000..2cec4512f163ff
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_vietnamese_sentiment_analyst_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_vietnamese_sentiment_analyst_pipeline pipeline DistilBertForSequenceClassification from Kawaiibuta
+author: John Snow Labs
+name: distilbert_vietnamese_sentiment_analyst_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_vietnamese_sentiment_analyst_pipeline` is a English model originally trained by Kawaiibuta.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_vietnamese_sentiment_analyst_pipeline_en_5.5.1_3.0_1737836421564.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_vietnamese_sentiment_analyst_pipeline_en_5.5.1_3.0_1737836421564.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_vietnamese_sentiment_analyst_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_vietnamese_sentiment_analyst_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_vietnamese_sentiment_analyst_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|507.6 MB|
+
+## References
+
+https://huggingface.co/Kawaiibuta/distilBERT_vietnamese_sentiment_analyst
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_yelp_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_yelp_en.md
new file mode 100644
index 00000000000000..72b565cae468f2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_yelp_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_yelp DistilBertForSequenceClassification from huiang
+author: John Snow Labs
+name: distilbert_yelp
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_yelp` is a English model originally trained by huiang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_yelp_en_5.5.1_3.0_1737837975973.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_yelp_en_5.5.1_3.0_1737837975973.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_yelp","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_yelp", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_yelp|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/huiang/distilbert-yelp
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilbert_yelp_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilbert_yelp_pipeline_en.md
new file mode 100644
index 00000000000000..e4088c650fff16
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilbert_yelp_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_yelp_pipeline pipeline DistilBertForSequenceClassification from huiang
+author: John Snow Labs
+name: distilbert_yelp_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_yelp_pipeline` is a English model originally trained by huiang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_yelp_pipeline_en_5.5.1_3.0_1737837989335.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_yelp_pipeline_en_5.5.1_3.0_1737837989335.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_yelp_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_yelp_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_yelp_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/huiang/distilbert-yelp
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distillbert_base_drug_effectiveness_classification_model_en.md b/docs/_posts/ahmedlone127/2025-01-25-distillbert_base_drug_effectiveness_classification_model_en.md
new file mode 100644
index 00000000000000..4d896e4011191f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distillbert_base_drug_effectiveness_classification_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distillbert_base_drug_effectiveness_classification_model DistilBertForSequenceClassification from jvbjkbjkbfjis
+author: John Snow Labs
+name: distillbert_base_drug_effectiveness_classification_model
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distillbert_base_drug_effectiveness_classification_model` is a English model originally trained by jvbjkbjkbfjis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distillbert_base_drug_effectiveness_classification_model_en_5.5.1_3.0_1737822061425.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distillbert_base_drug_effectiveness_classification_model_en_5.5.1_3.0_1737822061425.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distillbert_base_drug_effectiveness_classification_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distillbert_base_drug_effectiveness_classification_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distillbert_base_drug_effectiveness_classification_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/jvbjkbjkbfjis/distillbert-base-drug-effectiveness-classification-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distillbert_base_drug_effectiveness_classification_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distillbert_base_drug_effectiveness_classification_model_pipeline_en.md
new file mode 100644
index 00000000000000..8a1bb05fb22e66
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distillbert_base_drug_effectiveness_classification_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distillbert_base_drug_effectiveness_classification_model_pipeline pipeline DistilBertForSequenceClassification from jvbjkbjkbfjis
+author: John Snow Labs
+name: distillbert_base_drug_effectiveness_classification_model_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distillbert_base_drug_effectiveness_classification_model_pipeline` is a English model originally trained by jvbjkbjkbfjis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distillbert_base_drug_effectiveness_classification_model_pipeline_en_5.5.1_3.0_1737822075450.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distillbert_base_drug_effectiveness_classification_model_pipeline_en_5.5.1_3.0_1737822075450.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distillbert_base_drug_effectiveness_classification_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distillbert_base_drug_effectiveness_classification_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distillbert_base_drug_effectiveness_classification_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/jvbjkbjkbfjis/distillbert-base-drug-effectiveness-classification-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilroberta_base_climate_d_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilroberta_base_climate_d_en.md
new file mode 100644
index 00000000000000..8ff02b73b2f746
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilroberta_base_climate_d_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilroberta_base_climate_d RoBertaEmbeddings from climatebert
+author: John Snow Labs
+name: distilroberta_base_climate_d
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_climate_d` is a English model originally trained by climatebert.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_base_climate_d_en_5.5.1_3.0_1737796652763.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_climate_d_en_5.5.1_3.0_1737796652763.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("distilroberta_base_climate_d","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("distilroberta_base_climate_d","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_base_climate_d|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|307.4 MB|
+
+## References
+
+https://huggingface.co/climatebert/distilroberta-base-climate-d
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilroberta_base_climate_d_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilroberta_base_climate_d_pipeline_en.md
new file mode 100644
index 00000000000000..0284380b4d60c5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilroberta_base_climate_d_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilroberta_base_climate_d_pipeline pipeline RoBertaEmbeddings from climatebert
+author: John Snow Labs
+name: distilroberta_base_climate_d_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_climate_d_pipeline` is a English model originally trained by climatebert.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_base_climate_d_pipeline_en_5.5.1_3.0_1737796672397.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_climate_d_pipeline_en_5.5.1_3.0_1737796672397.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilroberta_base_climate_d_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilroberta_base_climate_d_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_base_climate_d_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|307.4 MB|
+
+## References
+
+https://huggingface.co/climatebert/distilroberta-base-climate-d
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilroberta_base_colombian_sign_language_python_unimodal_bimodal_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilroberta_base_colombian_sign_language_python_unimodal_bimodal_en.md
new file mode 100644
index 00000000000000..0144c73ff6e3a2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilroberta_base_colombian_sign_language_python_unimodal_bimodal_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilroberta_base_colombian_sign_language_python_unimodal_bimodal RoBertaEmbeddings from antolin
+author: John Snow Labs
+name: distilroberta_base_colombian_sign_language_python_unimodal_bimodal
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_colombian_sign_language_python_unimodal_bimodal` is a English model originally trained by antolin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_base_colombian_sign_language_python_unimodal_bimodal_en_5.5.1_3.0_1737797373740.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_colombian_sign_language_python_unimodal_bimodal_en_5.5.1_3.0_1737797373740.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("distilroberta_base_colombian_sign_language_python_unimodal_bimodal","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("distilroberta_base_colombian_sign_language_python_unimodal_bimodal","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_base_colombian_sign_language_python_unimodal_bimodal|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|306.6 MB|
+
+## References
+
+https://huggingface.co/antolin/distilroberta-base-csn-python-unimodal-bimodal
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilroberta_base_colombian_sign_language_python_unimodal_bimodal_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilroberta_base_colombian_sign_language_python_unimodal_bimodal_pipeline_en.md
new file mode 100644
index 00000000000000..5203bf7efc3e04
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilroberta_base_colombian_sign_language_python_unimodal_bimodal_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilroberta_base_colombian_sign_language_python_unimodal_bimodal_pipeline pipeline RoBertaEmbeddings from antolin
+author: John Snow Labs
+name: distilroberta_base_colombian_sign_language_python_unimodal_bimodal_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_colombian_sign_language_python_unimodal_bimodal_pipeline` is a English model originally trained by antolin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_base_colombian_sign_language_python_unimodal_bimodal_pipeline_en_5.5.1_3.0_1737797390320.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_colombian_sign_language_python_unimodal_bimodal_pipeline_en_5.5.1_3.0_1737797390320.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilroberta_base_colombian_sign_language_python_unimodal_bimodal_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilroberta_base_colombian_sign_language_python_unimodal_bimodal_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_base_colombian_sign_language_python_unimodal_bimodal_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|306.6 MB|
+
+## References
+
+https://huggingface.co/antolin/distilroberta-base-csn-python-unimodal-bimodal
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilroberta_base_ft_technology_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilroberta_base_ft_technology_en.md
new file mode 100644
index 00000000000000..34c47b7410a1ee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilroberta_base_ft_technology_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilroberta_base_ft_technology RoBertaEmbeddings from jkruk
+author: John Snow Labs
+name: distilroberta_base_ft_technology
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_ft_technology` is a English model originally trained by jkruk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_base_ft_technology_en_5.5.1_3.0_1737797787409.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_ft_technology_en_5.5.1_3.0_1737797787409.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("distilroberta_base_ft_technology","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("distilroberta_base_ft_technology","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_base_ft_technology|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/jkruk/distilroberta-base-ft-technology
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilroberta_base_ft_technology_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilroberta_base_ft_technology_pipeline_en.md
new file mode 100644
index 00000000000000..2b00511b6a4334
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilroberta_base_ft_technology_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilroberta_base_ft_technology_pipeline pipeline RoBertaEmbeddings from jkruk
+author: John Snow Labs
+name: distilroberta_base_ft_technology_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_ft_technology_pipeline` is a English model originally trained by jkruk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_base_ft_technology_pipeline_en_5.5.1_3.0_1737797803754.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_ft_technology_pipeline_en_5.5.1_3.0_1737797803754.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilroberta_base_ft_technology_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilroberta_base_ft_technology_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_base_ft_technology_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/jkruk/distilroberta-base-ft-technology
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilroberta_base_ft_twoxchromosomes_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilroberta_base_ft_twoxchromosomes_en.md
new file mode 100644
index 00000000000000..de7e50d399841e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilroberta_base_ft_twoxchromosomes_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilroberta_base_ft_twoxchromosomes RoBertaEmbeddings from jkruk
+author: John Snow Labs
+name: distilroberta_base_ft_twoxchromosomes
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_ft_twoxchromosomes` is a English model originally trained by jkruk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_base_ft_twoxchromosomes_en_5.5.1_3.0_1737796652203.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_ft_twoxchromosomes_en_5.5.1_3.0_1737796652203.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("distilroberta_base_ft_twoxchromosomes","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("distilroberta_base_ft_twoxchromosomes","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_base_ft_twoxchromosomes|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/jkruk/distilroberta-base-ft-TwoXChromosomes
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-distilroberta_base_ft_twoxchromosomes_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-distilroberta_base_ft_twoxchromosomes_pipeline_en.md
new file mode 100644
index 00000000000000..a1fdf9845e4695
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-distilroberta_base_ft_twoxchromosomes_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilroberta_base_ft_twoxchromosomes_pipeline pipeline RoBertaEmbeddings from jkruk
+author: John Snow Labs
+name: distilroberta_base_ft_twoxchromosomes_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_ft_twoxchromosomes_pipeline` is a English model originally trained by jkruk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_base_ft_twoxchromosomes_pipeline_en_5.5.1_3.0_1737796672343.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_ft_twoxchromosomes_pipeline_en_5.5.1_3.0_1737796672343.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilroberta_base_ft_twoxchromosomes_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilroberta_base_ft_twoxchromosomes_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_base_ft_twoxchromosomes_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/jkruk/distilroberta-base-ft-TwoXChromosomes
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-document_qa_model_en.md b/docs/_posts/ahmedlone127/2025-01-25-document_qa_model_en.md
new file mode 100644
index 00000000000000..9ff4594098f539
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-document_qa_model_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English document_qa_model DistilBertForQuestionAnswering from ashbleu
+author: John Snow Labs
+name: document_qa_model
+date: 2025-01-25
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`document_qa_model` is a English model originally trained by ashbleu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/document_qa_model_en_5.5.1_3.0_1737823931149.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/document_qa_model_en_5.5.1_3.0_1737823931149.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("document_qa_model","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("document_qa_model", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|document_qa_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/ashbleu/document_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-document_qa_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-document_qa_model_pipeline_en.md
new file mode 100644
index 00000000000000..6398d1c45da145
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-document_qa_model_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English document_qa_model_pipeline pipeline DistilBertForQuestionAnswering from ashbleu
+author: John Snow Labs
+name: document_qa_model_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`document_qa_model_pipeline` is a English model originally trained by ashbleu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/document_qa_model_pipeline_en_5.5.1_3.0_1737823943809.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/document_qa_model_pipeline_en_5.5.1_3.0_1737823943809.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("document_qa_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("document_qa_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|document_qa_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/ashbleu/document_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-efficient_fine_tuning_demo_mn.md b/docs/_posts/ahmedlone127/2025-01-25-efficient_fine_tuning_demo_mn.md
new file mode 100644
index 00000000000000..0a969d03b057a3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-efficient_fine_tuning_demo_mn.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Mongolian efficient_fine_tuning_demo BertForTokenClassification from BillyBek
+author: John Snow Labs
+name: efficient_fine_tuning_demo
+date: 2025-01-25
+tags: [mn, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: mn
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`efficient_fine_tuning_demo` is a Mongolian model originally trained by BillyBek.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/efficient_fine_tuning_demo_mn_5.5.1_3.0_1737843937261.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/efficient_fine_tuning_demo_mn_5.5.1_3.0_1737843937261.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("efficient_fine_tuning_demo","mn") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("efficient_fine_tuning_demo", "mn")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|efficient_fine_tuning_demo|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|mn|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/BillyBek/efficient-fine-tuning-demo
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-efficient_fine_tuning_demo_pipeline_mn.md b/docs/_posts/ahmedlone127/2025-01-25-efficient_fine_tuning_demo_pipeline_mn.md
new file mode 100644
index 00000000000000..34167e27589c2a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-efficient_fine_tuning_demo_pipeline_mn.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Mongolian efficient_fine_tuning_demo_pipeline pipeline BertForTokenClassification from BillyBek
+author: John Snow Labs
+name: efficient_fine_tuning_demo_pipeline
+date: 2025-01-25
+tags: [mn, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: mn
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`efficient_fine_tuning_demo_pipeline` is a Mongolian model originally trained by BillyBek.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/efficient_fine_tuning_demo_pipeline_mn_5.5.1_3.0_1737843970912.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/efficient_fine_tuning_demo_pipeline_mn_5.5.1_3.0_1737843970912.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("efficient_fine_tuning_demo_pipeline", lang = "mn")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("efficient_fine_tuning_demo_pipeline", lang = "mn")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|efficient_fine_tuning_demo_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|mn|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/BillyBek/efficient-fine-tuning-demo
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-electrical_classification_bert_base_en.md b/docs/_posts/ahmedlone127/2025-01-25-electrical_classification_bert_base_en.md
new file mode 100644
index 00000000000000..b727758bac15a1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-electrical_classification_bert_base_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English electrical_classification_bert_base BertForSequenceClassification from disham993
+author: John Snow Labs
+name: electrical_classification_bert_base
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`electrical_classification_bert_base` is a English model originally trained by disham993.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electrical_classification_bert_base_en_5.5.1_3.0_1737800852456.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electrical_classification_bert_base_en_5.5.1_3.0_1737800852456.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("electrical_classification_bert_base","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("electrical_classification_bert_base", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electrical_classification_bert_base|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/disham993/electrical-classification-bert-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-electrical_classification_bert_base_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-electrical_classification_bert_base_pipeline_en.md
new file mode 100644
index 00000000000000..dc5b1c8030847f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-electrical_classification_bert_base_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English electrical_classification_bert_base_pipeline pipeline BertForSequenceClassification from disham993
+author: John Snow Labs
+name: electrical_classification_bert_base_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`electrical_classification_bert_base_pipeline` is a English model originally trained by disham993.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electrical_classification_bert_base_pipeline_en_5.5.1_3.0_1737800874595.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electrical_classification_bert_base_pipeline_en_5.5.1_3.0_1737800874595.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("electrical_classification_bert_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("electrical_classification_bert_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electrical_classification_bert_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/disham993/electrical-classification-bert-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-emotion3_en.md b/docs/_posts/ahmedlone127/2025-01-25-emotion3_en.md
new file mode 100644
index 00000000000000..0340bc1e570351
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-emotion3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English emotion3 DistilBertForSequenceClassification from jamesbos
+author: John Snow Labs
+name: emotion3
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`emotion3` is a English model originally trained by jamesbos.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/emotion3_en_5.5.1_3.0_1737837523122.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/emotion3_en_5.5.1_3.0_1737837523122.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("emotion3","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("emotion3", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|emotion3|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/jamesbos/emotion3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-emotion3_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-emotion3_pipeline_en.md
new file mode 100644
index 00000000000000..3d1f60f77b04d1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-emotion3_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English emotion3_pipeline pipeline DistilBertForSequenceClassification from jamesbos
+author: John Snow Labs
+name: emotion3_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`emotion3_pipeline` is a English model originally trained by jamesbos.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/emotion3_pipeline_en_5.5.1_3.0_1737837537359.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/emotion3_pipeline_en_5.5.1_3.0_1737837537359.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("emotion3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("emotion3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|emotion3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/jamesbos/emotion3
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-emotion_classification_model_en.md b/docs/_posts/ahmedlone127/2025-01-25-emotion_classification_model_en.md
new file mode 100644
index 00000000000000..281e279a38ecfd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-emotion_classification_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English emotion_classification_model DistilBertForSequenceClassification from hamzawaheed
+author: John Snow Labs
+name: emotion_classification_model
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`emotion_classification_model` is a English model originally trained by hamzawaheed.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/emotion_classification_model_en_5.5.1_3.0_1737812046191.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/emotion_classification_model_en_5.5.1_3.0_1737812046191.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("emotion_classification_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("emotion_classification_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|emotion_classification_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/hamzawaheed/emotion-classification-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-emotion_classification_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-emotion_classification_model_pipeline_en.md
new file mode 100644
index 00000000000000..617b89dfbc706c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-emotion_classification_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English emotion_classification_model_pipeline pipeline DistilBertForSequenceClassification from hamzawaheed
+author: John Snow Labs
+name: emotion_classification_model_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`emotion_classification_model_pipeline` is a English model originally trained by hamzawaheed.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/emotion_classification_model_pipeline_en_5.5.1_3.0_1737812059610.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/emotion_classification_model_pipeline_en_5.5.1_3.0_1737812059610.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("emotion_classification_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("emotion_classification_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|emotion_classification_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/hamzawaheed/emotion-classification-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-engish_en.md b/docs/_posts/ahmedlone127/2025-01-25-engish_en.md
new file mode 100644
index 00000000000000..a7826a80405e67
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-engish_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English engish DistilBertForSequenceClassification from swapnasa
+author: John Snow Labs
+name: engish
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`engish` is a English model originally trained by swapnasa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/engish_en_5.5.1_3.0_1737838255663.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/engish_en_5.5.1_3.0_1737838255663.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("engish","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("engish", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|engish|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|507.6 MB|
+
+## References
+
+https://huggingface.co/swapnasa/engish
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-engish_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-engish_pipeline_en.md
new file mode 100644
index 00000000000000..5a032329b794db
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-engish_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English engish_pipeline pipeline DistilBertForSequenceClassification from swapnasa
+author: John Snow Labs
+name: engish_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`engish_pipeline` is a English model originally trained by swapnasa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/engish_pipeline_en_5.5.1_3.0_1737838280966.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/engish_pipeline_en_5.5.1_3.0_1737838280966.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("engish_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("engish_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|engish_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|507.7 MB|
+
+## References
+
+https://huggingface.co/swapnasa/engish
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-english_bambara_en.md b/docs/_posts/ahmedlone127/2025-01-25-english_bambara_en.md
new file mode 100644
index 00000000000000..505a08082a7cb7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-english_bambara_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English english_bambara MarianTransformer from LocaleNLP
+author: John Snow Labs
+name: english_bambara
+date: 2025-01-25
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_bambara` is a English model originally trained by LocaleNLP.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/english_bambara_en_5.5.1_3.0_1737829016330.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_bambara_en_5.5.1_3.0_1737829016330.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("english_bambara","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("english_bambara","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|english_bambara|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|416.5 MB|
+
+## References
+
+https://huggingface.co/LocaleNLP/English_bambara
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-english_bambara_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-english_bambara_pipeline_en.md
new file mode 100644
index 00000000000000..f932230d3ac446
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-english_bambara_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English english_bambara_pipeline pipeline MarianTransformer from LocaleNLP
+author: John Snow Labs
+name: english_bambara_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_bambara_pipeline` is a English model originally trained by LocaleNLP.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/english_bambara_pipeline_en_5.5.1_3.0_1737829038199.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_bambara_pipeline_en_5.5.1_3.0_1737829038199.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("english_bambara_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("english_bambara_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|english_bambara_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|417.0 MB|
+
+## References
+
+https://huggingface.co/LocaleNLP/English_bambara
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-english_coptic_translator_en.md b/docs/_posts/ahmedlone127/2025-01-25-english_coptic_translator_en.md
new file mode 100644
index 00000000000000..2d04b35d1620b5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-english_coptic_translator_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English english_coptic_translator MarianTransformer from megalaa
+author: John Snow Labs
+name: english_coptic_translator
+date: 2025-01-25
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_coptic_translator` is a English model originally trained by megalaa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/english_coptic_translator_en_5.5.1_3.0_1737781105724.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_coptic_translator_en_5.5.1_3.0_1737781105724.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("english_coptic_translator","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("english_coptic_translator","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|english_coptic_translator|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|412.1 MB|
+
+## References
+
+https://huggingface.co/megalaa/english-coptic-translator
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-english_coptic_translator_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-english_coptic_translator_pipeline_en.md
new file mode 100644
index 00000000000000..94ace4171f4527
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-english_coptic_translator_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English english_coptic_translator_pipeline pipeline MarianTransformer from megalaa
+author: John Snow Labs
+name: english_coptic_translator_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_coptic_translator_pipeline` is a English model originally trained by megalaa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/english_coptic_translator_pipeline_en_5.5.1_3.0_1737781132136.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_coptic_translator_pipeline_en_5.5.1_3.0_1737781132136.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("english_coptic_translator_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("english_coptic_translator_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|english_coptic_translator_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|412.7 MB|
+
+## References
+
+https://huggingface.co/megalaa/english-coptic-translator
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-english_multiple_languages_en.md b/docs/_posts/ahmedlone127/2025-01-25-english_multiple_languages_en.md
new file mode 100644
index 00000000000000..f09cc556cfbf85
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-english_multiple_languages_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English english_multiple_languages MarianTransformer from daffahasan
+author: John Snow Labs
+name: english_multiple_languages
+date: 2025-01-25
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_multiple_languages` is a English model originally trained by daffahasan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/english_multiple_languages_en_5.5.1_3.0_1737782013932.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_multiple_languages_en_5.5.1_3.0_1737782013932.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("english_multiple_languages","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("english_multiple_languages","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|english_multiple_languages|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|412.0 MB|
+
+## References
+
+https://huggingface.co/daffahasan/en-mul
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-english_multiple_languages_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-english_multiple_languages_pipeline_en.md
new file mode 100644
index 00000000000000..2184800862dde2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-english_multiple_languages_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English english_multiple_languages_pipeline pipeline MarianTransformer from daffahasan
+author: John Snow Labs
+name: english_multiple_languages_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_multiple_languages_pipeline` is a English model originally trained by daffahasan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/english_multiple_languages_pipeline_en_5.5.1_3.0_1737782035822.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_multiple_languages_pipeline_en_5.5.1_3.0_1737782035822.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("english_multiple_languages_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("english_multiple_languages_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|english_multiple_languages_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|412.6 MB|
+
+## References
+
+https://huggingface.co/daffahasan/en-mul
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-esp_msl_en.md b/docs/_posts/ahmedlone127/2025-01-25-esp_msl_en.md
new file mode 100644
index 00000000000000..efb685e62f11fc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-esp_msl_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English esp_msl MarianTransformer from vania2911
+author: John Snow Labs
+name: esp_msl
+date: 2025-01-25
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`esp_msl` is a English model originally trained by vania2911.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/esp_msl_en_5.5.1_3.0_1737843428709.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/esp_msl_en_5.5.1_3.0_1737843428709.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("esp_msl","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("esp_msl","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|esp_msl|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|295.5 MB|
+
+## References
+
+https://huggingface.co/vania2911/esp_msl
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-esp_msl_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-esp_msl_pipeline_en.md
new file mode 100644
index 00000000000000..0cf41522b18ded
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-esp_msl_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English esp_msl_pipeline pipeline MarianTransformer from vania2911
+author: John Snow Labs
+name: esp_msl_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`esp_msl_pipeline` is a English model originally trained by vania2911.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/esp_msl_pipeline_en_5.5.1_3.0_1737843444610.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/esp_msl_pipeline_en_5.5.1_3.0_1737843444610.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("esp_msl_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("esp_msl_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|esp_msl_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|296.0 MB|
+
+## References
+
+https://huggingface.co/vania2911/esp_msl
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-fake_news_detection_en.md b/docs/_posts/ahmedlone127/2025-01-25-fake_news_detection_en.md
new file mode 100644
index 00000000000000..f7c1f044ae78e3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-fake_news_detection_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English fake_news_detection BertForSequenceClassification from Pulk17
+author: John Snow Labs
+name: fake_news_detection
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fake_news_detection` is a English model originally trained by Pulk17.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fake_news_detection_en_5.5.1_3.0_1737840026941.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fake_news_detection_en_5.5.1_3.0_1737840026941.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("fake_news_detection","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("fake_news_detection", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fake_news_detection|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/Pulk17/Fake-News-Detection
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-fake_news_detection_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-fake_news_detection_pipeline_en.md
new file mode 100644
index 00000000000000..bd2aa7961c8d97
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-fake_news_detection_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English fake_news_detection_pipeline pipeline BertForSequenceClassification from Pulk17
+author: John Snow Labs
+name: fake_news_detection_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fake_news_detection_pipeline` is a English model originally trained by Pulk17.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fake_news_detection_pipeline_en_5.5.1_3.0_1737840047638.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fake_news_detection_pipeline_en_5.5.1_3.0_1737840047638.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fake_news_detection_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fake_news_detection_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fake_news_detection_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/Pulk17/Fake-News-Detection
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-fine_en.md b/docs/_posts/ahmedlone127/2025-01-25-fine_en.md
new file mode 100644
index 00000000000000..255a27089208b8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-fine_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English fine MarianTransformer from clui
+author: John Snow Labs
+name: fine
+date: 2025-01-25
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine` is a English model originally trained by clui.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_en_5.5.1_3.0_1737782679861.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_en_5.5.1_3.0_1737782679861.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("fine","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("fine","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|477.1 MB|
+
+## References
+
+https://huggingface.co/clui/fine
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-fine_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-fine_pipeline_en.md
new file mode 100644
index 00000000000000..28650cd7c19bf0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-fine_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English fine_pipeline pipeline MarianTransformer from clui
+author: John Snow Labs
+name: fine_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_pipeline` is a English model originally trained by clui.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_pipeline_en_5.5.1_3.0_1737782704949.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_pipeline_en_5.5.1_3.0_1737782704949.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fine_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fine_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|477.6 MB|
+
+## References
+
+https://huggingface.co/clui/fine
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-fine_tuned_distilroberta_nosql_injection_en.md b/docs/_posts/ahmedlone127/2025-01-25-fine_tuned_distilroberta_nosql_injection_en.md
new file mode 100644
index 00000000000000..ce217af25435ec
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-fine_tuned_distilroberta_nosql_injection_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English fine_tuned_distilroberta_nosql_injection RoBertaEmbeddings from ankush-003
+author: John Snow Labs
+name: fine_tuned_distilroberta_nosql_injection
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_distilroberta_nosql_injection` is a English model originally trained by ankush-003.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_distilroberta_nosql_injection_en_5.5.1_3.0_1737797381320.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_distilroberta_nosql_injection_en_5.5.1_3.0_1737797381320.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("fine_tuned_distilroberta_nosql_injection","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("fine_tuned_distilroberta_nosql_injection","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_distilroberta_nosql_injection|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|306.4 MB|
+
+## References
+
+https://huggingface.co/ankush-003/fine-tuned-distilroberta-nosql-injection
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-fine_tuned_distilroberta_nosql_injection_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-fine_tuned_distilroberta_nosql_injection_pipeline_en.md
new file mode 100644
index 00000000000000..25c3dfbcbdfe13
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-fine_tuned_distilroberta_nosql_injection_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English fine_tuned_distilroberta_nosql_injection_pipeline pipeline RoBertaEmbeddings from ankush-003
+author: John Snow Labs
+name: fine_tuned_distilroberta_nosql_injection_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_distilroberta_nosql_injection_pipeline` is a English model originally trained by ankush-003.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_distilroberta_nosql_injection_pipeline_en_5.5.1_3.0_1737797397561.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_distilroberta_nosql_injection_pipeline_en_5.5.1_3.0_1737797397561.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fine_tuned_distilroberta_nosql_injection_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fine_tuned_distilroberta_nosql_injection_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_distilroberta_nosql_injection_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/ankush-003/fine-tuned-distilroberta-nosql-injection
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-fine_tuned_opus_maltese_japanese_english_en.md b/docs/_posts/ahmedlone127/2025-01-25-fine_tuned_opus_maltese_japanese_english_en.md
new file mode 100644
index 00000000000000..5e39605ac85b19
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-fine_tuned_opus_maltese_japanese_english_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English fine_tuned_opus_maltese_japanese_english MarianTransformer from Markio
+author: John Snow Labs
+name: fine_tuned_opus_maltese_japanese_english
+date: 2025-01-25
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_opus_maltese_japanese_english` is a English model originally trained by Markio.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_opus_maltese_japanese_english_en_5.5.1_3.0_1737780627025.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_opus_maltese_japanese_english_en_5.5.1_3.0_1737780627025.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("fine_tuned_opus_maltese_japanese_english","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("fine_tuned_opus_maltese_japanese_english","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_opus_maltese_japanese_english|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|401.4 MB|
+
+## References
+
+https://huggingface.co/Markio/fine-tuned-opus-mt-ja-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-fine_tuned_opus_maltese_japanese_english_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-fine_tuned_opus_maltese_japanese_english_pipeline_en.md
new file mode 100644
index 00000000000000..2d217428cf8d7b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-fine_tuned_opus_maltese_japanese_english_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English fine_tuned_opus_maltese_japanese_english_pipeline pipeline MarianTransformer from Markio
+author: John Snow Labs
+name: fine_tuned_opus_maltese_japanese_english_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_opus_maltese_japanese_english_pipeline` is a English model originally trained by Markio.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_opus_maltese_japanese_english_pipeline_en_5.5.1_3.0_1737780648928.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_opus_maltese_japanese_english_pipeline_en_5.5.1_3.0_1737780648928.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fine_tuned_opus_maltese_japanese_english_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fine_tuned_opus_maltese_japanese_english_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_opus_maltese_japanese_english_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|402.0 MB|
+
+## References
+
+https://huggingface.co/Markio/fine-tuned-opus-mt-ja-en
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-finetune_2_en.md b/docs/_posts/ahmedlone127/2025-01-25-finetune_2_en.md
new file mode 100644
index 00000000000000..a7d283dc97412f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-finetune_2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetune_2 DistilBertForSequenceClassification from rxh1
+author: John Snow Labs
+name: finetune_2
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetune_2` is a English model originally trained by rxh1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetune_2_en_5.5.1_3.0_1737822362276.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetune_2_en_5.5.1_3.0_1737822362276.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetune_2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetune_2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetune_2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|507.6 MB|
+
+## References
+
+https://huggingface.co/rxh1/Finetune_2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-finetune_2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-finetune_2_pipeline_en.md
new file mode 100644
index 00000000000000..cda8ea1f149044
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-finetune_2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetune_2_pipeline pipeline DistilBertForSequenceClassification from rxh1
+author: John Snow Labs
+name: finetune_2_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetune_2_pipeline` is a English model originally trained by rxh1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetune_2_pipeline_en_5.5.1_3.0_1737822388308.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetune_2_pipeline_en_5.5.1_3.0_1737822388308.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetune_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetune_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetune_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|507.6 MB|
+
+## References
+
+https://huggingface.co/rxh1/Finetune_2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-finetuned_bge_embeddings_v4_base_v1_5_en.md b/docs/_posts/ahmedlone127/2025-01-25-finetuned_bge_embeddings_v4_base_v1_5_en.md
new file mode 100644
index 00000000000000..7bb97f02dcb48f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-finetuned_bge_embeddings_v4_base_v1_5_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English finetuned_bge_embeddings_v4_base_v1_5 BGEEmbeddings from austinpatrickm
+author: John Snow Labs
+name: finetuned_bge_embeddings_v4_base_v1_5
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_bge_embeddings_v4_base_v1_5` is a English model originally trained by austinpatrickm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_bge_embeddings_v4_base_v1_5_en_5.5.1_3.0_1737784117452.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_bge_embeddings_v4_base_v1_5_en_5.5.1_3.0_1737784117452.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("finetuned_bge_embeddings_v4_base_v1_5","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("finetuned_bge_embeddings_v4_base_v1_5","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_bge_embeddings_v4_base_v1_5|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|389.4 MB|
+
+## References
+
+https://huggingface.co/austinpatrickm/finetuned_bge_embeddings_v4_base_v1.5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-finetuned_bge_embeddings_v4_base_v1_5_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-finetuned_bge_embeddings_v4_base_v1_5_pipeline_en.md
new file mode 100644
index 00000000000000..6518f7224f69da
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-finetuned_bge_embeddings_v4_base_v1_5_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English finetuned_bge_embeddings_v4_base_v1_5_pipeline pipeline BGEEmbeddings from austinpatrickm
+author: John Snow Labs
+name: finetuned_bge_embeddings_v4_base_v1_5_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_bge_embeddings_v4_base_v1_5_pipeline` is a English model originally trained by austinpatrickm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_bge_embeddings_v4_base_v1_5_pipeline_en_5.5.1_3.0_1737784144322.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_bge_embeddings_v4_base_v1_5_pipeline_en_5.5.1_3.0_1737784144322.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuned_bge_embeddings_v4_base_v1_5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuned_bge_embeddings_v4_base_v1_5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_bge_embeddings_v4_base_v1_5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|389.4 MB|
+
+## References
+
+https://huggingface.co/austinpatrickm/finetuned_bge_embeddings_v4_base_v1.5
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-finetuned_en.md b/docs/_posts/ahmedlone127/2025-01-25-finetuned_en.md
new file mode 100644
index 00000000000000..112c86cf18df2e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-finetuned_en.md
@@ -0,0 +1,96 @@
+---
+layout: model
+title: English finetuned BertEmbeddings from vppvgit
+author: John Snow Labs
+name: finetuned
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned` is a English model originally trained by vppvgit.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_en_5.5.1_3.0_1737846058993.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_en_5.5.1_3.0_1737846058993.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("finetuned","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("finetuned","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+References
+
+https://huggingface.co/vppvgit/Finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-finetuned_model1_en.md b/docs/_posts/ahmedlone127/2025-01-25-finetuned_model1_en.md
new file mode 100644
index 00000000000000..c6daf345e7cbfc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-finetuned_model1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuned_model1 DistilBertForSequenceClassification from isom5240grp21
+author: John Snow Labs
+name: finetuned_model1
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_model1` is a English model originally trained by isom5240grp21.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_model1_en_5.5.1_3.0_1737811379803.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_model1_en_5.5.1_3.0_1737811379803.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuned_model1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuned_model1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_model1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/isom5240grp21/finetuned_model1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-finetuned_model1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-finetuned_model1_pipeline_en.md
new file mode 100644
index 00000000000000..e5cc4741d29631
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-finetuned_model1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuned_model1_pipeline pipeline DistilBertForSequenceClassification from isom5240grp21
+author: John Snow Labs
+name: finetuned_model1_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_model1_pipeline` is a English model originally trained by isom5240grp21.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_model1_pipeline_en_5.5.1_3.0_1737811396465.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_model1_pipeline_en_5.5.1_3.0_1737811396465.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuned_model1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuned_model1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_model1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/isom5240grp21/finetuned_model1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-finetuned_pipeline_en.md
new file mode 100644
index 00000000000000..ef0f72018c0dc3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-finetuned_pipeline_en.md
@@ -0,0 +1,72 @@
+---
+layout: model
+title: English finetuned_pipeline pipeline BertEmbeddings from vppvgit
+author: John Snow Labs
+name: finetuned_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_pipeline` is a English model originally trained by vppvgit.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_pipeline_en_5.5.1_3.0_1737846080390.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_pipeline_en_5.5.1_3.0_1737846080390.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("finetuned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("finetuned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+References
+
+https://huggingface.co/vppvgit/Finetuned
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-finetuning_distilbert_sentiment_model_t0peerakarn_en.md b/docs/_posts/ahmedlone127/2025-01-25-finetuning_distilbert_sentiment_model_t0peerakarn_en.md
new file mode 100644
index 00000000000000..10fdf7d4bdef4d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-finetuning_distilbert_sentiment_model_t0peerakarn_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuning_distilbert_sentiment_model_t0peerakarn DistilBertForSequenceClassification from t0peerakarn
+author: John Snow Labs
+name: finetuning_distilbert_sentiment_model_t0peerakarn
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_distilbert_sentiment_model_t0peerakarn` is a English model originally trained by t0peerakarn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_distilbert_sentiment_model_t0peerakarn_en_5.5.1_3.0_1737838000554.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_distilbert_sentiment_model_t0peerakarn_en_5.5.1_3.0_1737838000554.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuning_distilbert_sentiment_model_t0peerakarn","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_distilbert_sentiment_model_t0peerakarn", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_distilbert_sentiment_model_t0peerakarn|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/t0peerakarn/finetuning-distilbert-sentiment-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-finetuning_distilbert_sentiment_model_t0peerakarn_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-finetuning_distilbert_sentiment_model_t0peerakarn_pipeline_en.md
new file mode 100644
index 00000000000000..fcb40acf81df7e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-finetuning_distilbert_sentiment_model_t0peerakarn_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuning_distilbert_sentiment_model_t0peerakarn_pipeline pipeline DistilBertForSequenceClassification from t0peerakarn
+author: John Snow Labs
+name: finetuning_distilbert_sentiment_model_t0peerakarn_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_distilbert_sentiment_model_t0peerakarn_pipeline` is a English model originally trained by t0peerakarn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_distilbert_sentiment_model_t0peerakarn_pipeline_en_5.5.1_3.0_1737838013863.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_distilbert_sentiment_model_t0peerakarn_pipeline_en_5.5.1_3.0_1737838013863.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuning_distilbert_sentiment_model_t0peerakarn_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuning_distilbert_sentiment_model_t0peerakarn_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_distilbert_sentiment_model_t0peerakarn_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/t0peerakarn/finetuning-distilbert-sentiment-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-finetuning_emotion_model_cerpintaxt_en.md b/docs/_posts/ahmedlone127/2025-01-25-finetuning_emotion_model_cerpintaxt_en.md
new file mode 100644
index 00000000000000..b0562f170953ef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-finetuning_emotion_model_cerpintaxt_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuning_emotion_model_cerpintaxt DistilBertForSequenceClassification from cerpintaxt
+author: John Snow Labs
+name: finetuning_emotion_model_cerpintaxt
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_emotion_model_cerpintaxt` is a English model originally trained by cerpintaxt.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_emotion_model_cerpintaxt_en_5.5.1_3.0_1737836267617.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_emotion_model_cerpintaxt_en_5.5.1_3.0_1737836267617.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuning_emotion_model_cerpintaxt","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_emotion_model_cerpintaxt", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_emotion_model_cerpintaxt|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/cerpintaxt/finetuning-emotion-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-finetuning_emotion_model_cerpintaxt_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-finetuning_emotion_model_cerpintaxt_pipeline_en.md
new file mode 100644
index 00000000000000..67166dcf62c177
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-finetuning_emotion_model_cerpintaxt_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuning_emotion_model_cerpintaxt_pipeline pipeline DistilBertForSequenceClassification from cerpintaxt
+author: John Snow Labs
+name: finetuning_emotion_model_cerpintaxt_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_emotion_model_cerpintaxt_pipeline` is a English model originally trained by cerpintaxt.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_emotion_model_cerpintaxt_pipeline_en_5.5.1_3.0_1737836284513.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_emotion_model_cerpintaxt_pipeline_en_5.5.1_3.0_1737836284513.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuning_emotion_model_cerpintaxt_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuning_emotion_model_cerpintaxt_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_emotion_model_cerpintaxt_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/cerpintaxt/finetuning-emotion-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-finetuning_maltese_english_arabic_english_arabic_translation_en.md b/docs/_posts/ahmedlone127/2025-01-25-finetuning_maltese_english_arabic_english_arabic_translation_en.md
new file mode 100644
index 00000000000000..6c221d3bd59fdc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-finetuning_maltese_english_arabic_english_arabic_translation_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuning_maltese_english_arabic_english_arabic_translation MarianTransformer from ahmed792002
+author: John Snow Labs
+name: finetuning_maltese_english_arabic_english_arabic_translation
+date: 2025-01-25
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_maltese_english_arabic_english_arabic_translation` is a English model originally trained by ahmed792002.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_maltese_english_arabic_english_arabic_translation_en_5.5.1_3.0_1737829969738.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_maltese_english_arabic_english_arabic_translation_en_5.5.1_3.0_1737829969738.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("finetuning_maltese_english_arabic_english_arabic_translation","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("finetuning_maltese_english_arabic_english_arabic_translation","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_maltese_english_arabic_english_arabic_translation|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|409.5 MB|
+
+## References
+
+https://huggingface.co/ahmed792002/Finetuning_mt-en-ar_English_Arabic_Translation
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-finetuning_maltese_english_arabic_english_arabic_translation_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-finetuning_maltese_english_arabic_english_arabic_translation_pipeline_en.md
new file mode 100644
index 00000000000000..38fb9fbf79b1f0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-finetuning_maltese_english_arabic_english_arabic_translation_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuning_maltese_english_arabic_english_arabic_translation_pipeline pipeline MarianTransformer from ahmed792002
+author: John Snow Labs
+name: finetuning_maltese_english_arabic_english_arabic_translation_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_maltese_english_arabic_english_arabic_translation_pipeline` is a English model originally trained by ahmed792002.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_maltese_english_arabic_english_arabic_translation_pipeline_en_5.5.1_3.0_1737829990140.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_maltese_english_arabic_english_arabic_translation_pipeline_en_5.5.1_3.0_1737829990140.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuning_maltese_english_arabic_english_arabic_translation_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuning_maltese_english_arabic_english_arabic_translation_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_maltese_english_arabic_english_arabic_translation_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.0 MB|
+
+## References
+
+https://huggingface.co/ahmed792002/Finetuning_mt-en-ar_English_Arabic_Translation
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-finetuning_sentiment_2_en.md b/docs/_posts/ahmedlone127/2025-01-25-finetuning_sentiment_2_en.md
new file mode 100644
index 00000000000000..22bdf68243293d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-finetuning_sentiment_2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuning_sentiment_2 DistilBertForSequenceClassification from Juliocrm
+author: John Snow Labs
+name: finetuning_sentiment_2
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_2` is a English model originally trained by Juliocrm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_2_en_5.5.1_3.0_1737822819196.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_2_en_5.5.1_3.0_1737822819196.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Juliocrm/finetuning-sentiment-2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-finetuning_sentiment_2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-finetuning_sentiment_2_pipeline_en.md
new file mode 100644
index 00000000000000..7b25cac1704d15
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-finetuning_sentiment_2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuning_sentiment_2_pipeline pipeline DistilBertForSequenceClassification from Juliocrm
+author: John Snow Labs
+name: finetuning_sentiment_2_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_2_pipeline` is a English model originally trained by Juliocrm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_2_pipeline_en_5.5.1_3.0_1737822832063.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_2_pipeline_en_5.5.1_3.0_1737822832063.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuning_sentiment_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuning_sentiment_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Juliocrm/finetuning-sentiment-2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-finetuning_sentiment_model_3000_en.md b/docs/_posts/ahmedlone127/2025-01-25-finetuning_sentiment_model_3000_en.md
new file mode 100644
index 00000000000000..662340447ba91f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-finetuning_sentiment_model_3000_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000 DistilBertForSequenceClassification from singhh-harshvardhan
+author: John Snow Labs
+name: finetuning_sentiment_model_3000
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000` is a English model originally trained by singhh-harshvardhan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_en_5.5.1_3.0_1737836342186.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_en_5.5.1_3.0_1737836342186.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/singhh-harshvardhan/finetuning-sentiment-model-3000
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-finetuning_sentiment_model_3000_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-finetuning_sentiment_model_3000_pipeline_en.md
new file mode 100644
index 00000000000000..31999bffc231da
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-finetuning_sentiment_model_3000_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_pipeline pipeline DistilBertForSequenceClassification from singhh-harshvardhan
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_pipeline` is a English model originally trained by singhh-harshvardhan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_pipeline_en_5.5.1_3.0_1737836354893.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_pipeline_en_5.5.1_3.0_1737836354893.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuning_sentiment_model_3000_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuning_sentiment_model_3000_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/singhh-harshvardhan/finetuning-sentiment-model-3000
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-finetuning_sentiment_model_3000_samples_jxptlr_en.md b/docs/_posts/ahmedlone127/2025-01-25-finetuning_sentiment_model_3000_samples_jxptlr_en.md
new file mode 100644
index 00000000000000..6116f806841e0b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-finetuning_sentiment_model_3000_samples_jxptlr_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_jxptlr DistilBertForSequenceClassification from Jxptlr
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_jxptlr
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_jxptlr` is a English model originally trained by Jxptlr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_jxptlr_en_5.5.1_3.0_1737822380687.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_jxptlr_en_5.5.1_3.0_1737822380687.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_jxptlr","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_jxptlr", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_jxptlr|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Jxptlr/finetuning-sentiment-model-3000-samples
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-finetuning_sentiment_model_3000_samples_jxptlr_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-finetuning_sentiment_model_3000_samples_jxptlr_pipeline_en.md
new file mode 100644
index 00000000000000..773c717fb20888
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-finetuning_sentiment_model_3000_samples_jxptlr_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_jxptlr_pipeline pipeline DistilBertForSequenceClassification from Jxptlr
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_jxptlr_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_jxptlr_pipeline` is a English model originally trained by Jxptlr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_jxptlr_pipeline_en_5.5.1_3.0_1737822394028.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_jxptlr_pipeline_en_5.5.1_3.0_1737822394028.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuning_sentiment_model_3000_samples_jxptlr_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuning_sentiment_model_3000_samples_jxptlr_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_jxptlr_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Jxptlr/finetuning-sentiment-model-3000-samples
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-finetuning_sentiment_model_3000_samples_theethernalfool_en.md b/docs/_posts/ahmedlone127/2025-01-25-finetuning_sentiment_model_3000_samples_theethernalfool_en.md
new file mode 100644
index 00000000000000..4dd4ae829bde04
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-finetuning_sentiment_model_3000_samples_theethernalfool_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_theethernalfool DistilBertForSequenceClassification from TheEthernalFool
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_theethernalfool
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_theethernalfool` is a English model originally trained by TheEthernalFool.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_theethernalfool_en_5.5.1_3.0_1737812140866.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_theethernalfool_en_5.5.1_3.0_1737812140866.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_theethernalfool","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_theethernalfool", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_theethernalfool|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/TheEthernalFool/finetuning-sentiment-model-3000-samples
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-finetuning_sentiment_model_3000_samples_theethernalfool_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-finetuning_sentiment_model_3000_samples_theethernalfool_pipeline_en.md
new file mode 100644
index 00000000000000..2ee17769167a66
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-finetuning_sentiment_model_3000_samples_theethernalfool_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_theethernalfool_pipeline pipeline DistilBertForSequenceClassification from TheEthernalFool
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_theethernalfool_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_theethernalfool_pipeline` is a English model originally trained by TheEthernalFool.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_theethernalfool_pipeline_en_5.5.1_3.0_1737812153969.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_theethernalfool_pipeline_en_5.5.1_3.0_1737812153969.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuning_sentiment_model_3000_samples_theethernalfool_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuning_sentiment_model_3000_samples_theethernalfool_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_theethernalfool_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/TheEthernalFool/finetuning-sentiment-model-3000-samples
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-finetuning_sentiment_model_3000_samples_xli187_en.md b/docs/_posts/ahmedlone127/2025-01-25-finetuning_sentiment_model_3000_samples_xli187_en.md
new file mode 100644
index 00000000000000..45f38546a020d3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-finetuning_sentiment_model_3000_samples_xli187_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_xli187 DistilBertForSequenceClassification from xli187
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_xli187
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_xli187` is a English model originally trained by xli187.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_xli187_en_5.5.1_3.0_1737837525131.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_xli187_en_5.5.1_3.0_1737837525131.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_xli187","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_xli187", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_xli187|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/xli187/finetuning-sentiment-model-3000-samples
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-finetuning_sentiment_model_3000_samples_xli187_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-finetuning_sentiment_model_3000_samples_xli187_pipeline_en.md
new file mode 100644
index 00000000000000..d0a17166c80b85
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-finetuning_sentiment_model_3000_samples_xli187_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_xli187_pipeline pipeline DistilBertForSequenceClassification from xli187
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_xli187_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_xli187_pipeline` is a English model originally trained by xli187.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_xli187_pipeline_en_5.5.1_3.0_1737837545158.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_xli187_pipeline_en_5.5.1_3.0_1737837545158.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuning_sentiment_model_3000_samples_xli187_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuning_sentiment_model_3000_samples_xli187_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_xli187_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/xli187/finetuning-sentiment-model-3000-samples
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-finetuning_sentiment_model_3800_conversations_en.md b/docs/_posts/ahmedlone127/2025-01-25-finetuning_sentiment_model_3800_conversations_en.md
new file mode 100644
index 00000000000000..ca9c33bac8c0f7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-finetuning_sentiment_model_3800_conversations_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3800_conversations DistilBertForSequenceClassification from TimDL
+author: John Snow Labs
+name: finetuning_sentiment_model_3800_conversations
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3800_conversations` is a English model originally trained by TimDL.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3800_conversations_en_5.5.1_3.0_1737836258075.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3800_conversations_en_5.5.1_3.0_1737836258075.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3800_conversations","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3800_conversations", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3800_conversations|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/TimDL/finetuning-sentiment-model-3800-conversations
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-finetuning_sentiment_model_3800_conversations_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-finetuning_sentiment_model_3800_conversations_pipeline_en.md
new file mode 100644
index 00000000000000..d27af5efe35de8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-finetuning_sentiment_model_3800_conversations_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3800_conversations_pipeline pipeline DistilBertForSequenceClassification from TimDL
+author: John Snow Labs
+name: finetuning_sentiment_model_3800_conversations_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3800_conversations_pipeline` is a English model originally trained by TimDL.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3800_conversations_pipeline_en_5.5.1_3.0_1737836271294.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3800_conversations_pipeline_en_5.5.1_3.0_1737836271294.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuning_sentiment_model_3800_conversations_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuning_sentiment_model_3800_conversations_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3800_conversations_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/TimDL/finetuning-sentiment-model-3800-conversations
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-finetuning_sentiment_model_for_c2er_en.md b/docs/_posts/ahmedlone127/2025-01-25-finetuning_sentiment_model_for_c2er_en.md
new file mode 100644
index 00000000000000..8f0cb37a92cd22
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-finetuning_sentiment_model_for_c2er_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuning_sentiment_model_for_c2er DistilBertForSequenceClassification from srmishra
+author: John Snow Labs
+name: finetuning_sentiment_model_for_c2er
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_for_c2er` is a English model originally trained by srmishra.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_for_c2er_en_5.5.1_3.0_1737837641804.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_for_c2er_en_5.5.1_3.0_1737837641804.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_for_c2er","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_for_c2er", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_for_c2er|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/srmishra/finetuning-sentiment-model-for-c2er
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-finetuning_sentiment_model_for_c2er_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-finetuning_sentiment_model_for_c2er_pipeline_en.md
new file mode 100644
index 00000000000000..c133832493c037
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-finetuning_sentiment_model_for_c2er_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuning_sentiment_model_for_c2er_pipeline pipeline DistilBertForSequenceClassification from srmishra
+author: John Snow Labs
+name: finetuning_sentiment_model_for_c2er_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_for_c2er_pipeline` is a English model originally trained by srmishra.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_for_c2er_pipeline_en_5.5.1_3.0_1737837655514.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_for_c2er_pipeline_en_5.5.1_3.0_1737837655514.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuning_sentiment_model_for_c2er_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuning_sentiment_model_for_c2er_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_for_c2er_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/srmishra/finetuning-sentiment-model-for-c2er
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-first_training_model_ipcr_claim1_en.md b/docs/_posts/ahmedlone127/2025-01-25-first_training_model_ipcr_claim1_en.md
new file mode 100644
index 00000000000000..71fb8dfd05b981
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-first_training_model_ipcr_claim1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English first_training_model_ipcr_claim1 DistilBertForSequenceClassification from mhurhangee
+author: John Snow Labs
+name: first_training_model_ipcr_claim1
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`first_training_model_ipcr_claim1` is a English model originally trained by mhurhangee.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/first_training_model_ipcr_claim1_en_5.5.1_3.0_1737836390180.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/first_training_model_ipcr_claim1_en_5.5.1_3.0_1737836390180.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("first_training_model_ipcr_claim1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("first_training_model_ipcr_claim1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|first_training_model_ipcr_claim1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/mhurhangee/first_training_model_ipcr_claim1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-first_training_model_ipcr_claim1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-first_training_model_ipcr_claim1_pipeline_en.md
new file mode 100644
index 00000000000000..ebb9800076f722
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-first_training_model_ipcr_claim1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English first_training_model_ipcr_claim1_pipeline pipeline DistilBertForSequenceClassification from mhurhangee
+author: John Snow Labs
+name: first_training_model_ipcr_claim1_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`first_training_model_ipcr_claim1_pipeline` is a English model originally trained by mhurhangee.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/first_training_model_ipcr_claim1_pipeline_en_5.5.1_3.0_1737836403113.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/first_training_model_ipcr_claim1_pipeline_en_5.5.1_3.0_1737836403113.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("first_training_model_ipcr_claim1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("first_training_model_ipcr_claim1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|first_training_model_ipcr_claim1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/mhurhangee/first_training_model_ipcr_claim1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-fm_tc_hybridxml_multilingual_spaincat_pipeline_xx.md b/docs/_posts/ahmedlone127/2025-01-25-fm_tc_hybridxml_multilingual_spaincat_pipeline_xx.md
new file mode 100644
index 00000000000000..62056452aa7835
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-fm_tc_hybridxml_multilingual_spaincat_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual fm_tc_hybridxml_multilingual_spaincat_pipeline pipeline XlmRoBertaForSequenceClassification from adriansanz
+author: John Snow Labs
+name: fm_tc_hybridxml_multilingual_spaincat_pipeline
+date: 2025-01-25
+tags: [xx, open_source, pipeline, onnx]
+task: Text Classification
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fm_tc_hybridxml_multilingual_spaincat_pipeline` is a Multilingual model originally trained by adriansanz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fm_tc_hybridxml_multilingual_spaincat_pipeline_xx_5.5.1_3.0_1737816990197.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fm_tc_hybridxml_multilingual_spaincat_pipeline_xx_5.5.1_3.0_1737816990197.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fm_tc_hybridxml_multilingual_spaincat_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fm_tc_hybridxml_multilingual_spaincat_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fm_tc_hybridxml_multilingual_spaincat_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|780.1 MB|
+
+## References
+
+https://huggingface.co/adriansanz/fm-tc-hybridXML-MULTILINGUAL-spaincat
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-fm_tc_hybridxml_multilingual_spaincat_xx.md b/docs/_posts/ahmedlone127/2025-01-25-fm_tc_hybridxml_multilingual_spaincat_xx.md
new file mode 100644
index 00000000000000..e1b64bc8191c70
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-fm_tc_hybridxml_multilingual_spaincat_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual fm_tc_hybridxml_multilingual_spaincat XlmRoBertaForSequenceClassification from adriansanz
+author: John Snow Labs
+name: fm_tc_hybridxml_multilingual_spaincat
+date: 2025-01-25
+tags: [xx, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fm_tc_hybridxml_multilingual_spaincat` is a Multilingual model originally trained by adriansanz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fm_tc_hybridxml_multilingual_spaincat_xx_5.5.1_3.0_1737816840452.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fm_tc_hybridxml_multilingual_spaincat_xx_5.5.1_3.0_1737816840452.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("fm_tc_hybridxml_multilingual_spaincat","xx") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("fm_tc_hybridxml_multilingual_spaincat", "xx")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fm_tc_hybridxml_multilingual_spaincat|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|xx|
+|Size:|780.1 MB|
+
+## References
+
+https://huggingface.co/adriansanz/fm-tc-hybridXML-MULTILINGUAL-spaincat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-frozen11_bert_multilingual_finetuned_cefr_ner_3000news_pipeline_xx.md b/docs/_posts/ahmedlone127/2025-01-25-frozen11_bert_multilingual_finetuned_cefr_ner_3000news_pipeline_xx.md
new file mode 100644
index 00000000000000..0d2bcc1ff7bda9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-frozen11_bert_multilingual_finetuned_cefr_ner_3000news_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual frozen11_bert_multilingual_finetuned_cefr_ner_3000news_pipeline pipeline BertForTokenClassification from DioBot2000
+author: John Snow Labs
+name: frozen11_bert_multilingual_finetuned_cefr_ner_3000news_pipeline
+date: 2025-01-25
+tags: [xx, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`frozen11_bert_multilingual_finetuned_cefr_ner_3000news_pipeline` is a Multilingual model originally trained by DioBot2000.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/frozen11_bert_multilingual_finetuned_cefr_ner_3000news_pipeline_xx_5.5.1_3.0_1737844251944.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/frozen11_bert_multilingual_finetuned_cefr_ner_3000news_pipeline_xx_5.5.1_3.0_1737844251944.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("frozen11_bert_multilingual_finetuned_cefr_ner_3000news_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("frozen11_bert_multilingual_finetuned_cefr_ner_3000news_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|frozen11_bert_multilingual_finetuned_cefr_ner_3000news_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/DioBot2000/Frozen11-BERT-multilingual-finetuned-CEFR_ner-3000news
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-frozen11_bert_multilingual_finetuned_cefr_ner_3000news_xx.md b/docs/_posts/ahmedlone127/2025-01-25-frozen11_bert_multilingual_finetuned_cefr_ner_3000news_xx.md
new file mode 100644
index 00000000000000..ea0e754535737f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-frozen11_bert_multilingual_finetuned_cefr_ner_3000news_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual frozen11_bert_multilingual_finetuned_cefr_ner_3000news BertForTokenClassification from DioBot2000
+author: John Snow Labs
+name: frozen11_bert_multilingual_finetuned_cefr_ner_3000news
+date: 2025-01-25
+tags: [xx, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`frozen11_bert_multilingual_finetuned_cefr_ner_3000news` is a Multilingual model originally trained by DioBot2000.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/frozen11_bert_multilingual_finetuned_cefr_ner_3000news_xx_5.5.1_3.0_1737844218215.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/frozen11_bert_multilingual_finetuned_cefr_ner_3000news_xx_5.5.1_3.0_1737844218215.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("frozen11_bert_multilingual_finetuned_cefr_ner_3000news","xx") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("frozen11_bert_multilingual_finetuned_cefr_ner_3000news", "xx")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|frozen11_bert_multilingual_finetuned_cefr_ner_3000news|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|xx|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/DioBot2000/Frozen11-BERT-multilingual-finetuned-CEFR_ner-3000news
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-frpile_mlm_basel_en.md b/docs/_posts/ahmedlone127/2025-01-25-frpile_mlm_basel_en.md
new file mode 100644
index 00000000000000..79d6bc960ff874
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-frpile_mlm_basel_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English frpile_mlm_basel BertEmbeddings from DragosGorduza
+author: John Snow Labs
+name: frpile_mlm_basel
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`frpile_mlm_basel` is a English model originally trained by DragosGorduza.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/frpile_mlm_basel_en_5.5.1_3.0_1737785072036.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/frpile_mlm_basel_en_5.5.1_3.0_1737785072036.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("frpile_mlm_basel","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("frpile_mlm_basel","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|frpile_mlm_basel|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/DragosGorduza/FRPile_MLM_Basel
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-frpile_mlm_basel_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-frpile_mlm_basel_pipeline_en.md
new file mode 100644
index 00000000000000..0a5db0acd5cb08
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-frpile_mlm_basel_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English frpile_mlm_basel_pipeline pipeline BertEmbeddings from DragosGorduza
+author: John Snow Labs
+name: frpile_mlm_basel_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`frpile_mlm_basel_pipeline` is a English model originally trained by DragosGorduza.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/frpile_mlm_basel_pipeline_en_5.5.1_3.0_1737785136845.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/frpile_mlm_basel_pipeline_en_5.5.1_3.0_1737785136845.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("frpile_mlm_basel_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("frpile_mlm_basel_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|frpile_mlm_basel_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/DragosGorduza/FRPile_MLM_Basel
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-full_5epoch_bert_base_multilingual_finetuned_cefr_ner_60000news_pipeline_xx.md b/docs/_posts/ahmedlone127/2025-01-25-full_5epoch_bert_base_multilingual_finetuned_cefr_ner_60000news_pipeline_xx.md
new file mode 100644
index 00000000000000..00c5703b0f1c0d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-full_5epoch_bert_base_multilingual_finetuned_cefr_ner_60000news_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual full_5epoch_bert_base_multilingual_finetuned_cefr_ner_60000news_pipeline pipeline BertForTokenClassification from DioBot2000
+author: John Snow Labs
+name: full_5epoch_bert_base_multilingual_finetuned_cefr_ner_60000news_pipeline
+date: 2025-01-25
+tags: [xx, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`full_5epoch_bert_base_multilingual_finetuned_cefr_ner_60000news_pipeline` is a Multilingual model originally trained by DioBot2000.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/full_5epoch_bert_base_multilingual_finetuned_cefr_ner_60000news_pipeline_xx_5.5.1_3.0_1737844389914.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/full_5epoch_bert_base_multilingual_finetuned_cefr_ner_60000news_pipeline_xx_5.5.1_3.0_1737844389914.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("full_5epoch_bert_base_multilingual_finetuned_cefr_ner_60000news_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("full_5epoch_bert_base_multilingual_finetuned_cefr_ner_60000news_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|full_5epoch_bert_base_multilingual_finetuned_cefr_ner_60000news_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/DioBot2000/Full-5epoch-BERT-base-multilingual-finetuned-CEFR_ner-60000news
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-full_5epoch_bert_base_multilingual_finetuned_cefr_ner_60000news_xx.md b/docs/_posts/ahmedlone127/2025-01-25-full_5epoch_bert_base_multilingual_finetuned_cefr_ner_60000news_xx.md
new file mode 100644
index 00000000000000..beffe60b75ef86
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-full_5epoch_bert_base_multilingual_finetuned_cefr_ner_60000news_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual full_5epoch_bert_base_multilingual_finetuned_cefr_ner_60000news BertForTokenClassification from DioBot2000
+author: John Snow Labs
+name: full_5epoch_bert_base_multilingual_finetuned_cefr_ner_60000news
+date: 2025-01-25
+tags: [xx, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`full_5epoch_bert_base_multilingual_finetuned_cefr_ner_60000news` is a Multilingual model originally trained by DioBot2000.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/full_5epoch_bert_base_multilingual_finetuned_cefr_ner_60000news_xx_5.5.1_3.0_1737844353473.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/full_5epoch_bert_base_multilingual_finetuned_cefr_ner_60000news_xx_5.5.1_3.0_1737844353473.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("full_5epoch_bert_base_multilingual_finetuned_cefr_ner_60000news","xx") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("full_5epoch_bert_base_multilingual_finetuned_cefr_ner_60000news", "xx")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|full_5epoch_bert_base_multilingual_finetuned_cefr_ner_60000news|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|xx|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/DioBot2000/Full-5epoch-BERT-base-multilingual-finetuned-CEFR_ner-60000news
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-gbert_job_en.md b/docs/_posts/ahmedlone127/2025-01-25-gbert_job_en.md
new file mode 100644
index 00000000000000..b2fabe4e7ae3a5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-gbert_job_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English gbert_job BertEmbeddings from dathi103
+author: John Snow Labs
+name: gbert_job
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gbert_job` is a English model originally trained by dathi103.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gbert_job_en_5.5.1_3.0_1737774622172.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gbert_job_en_5.5.1_3.0_1737774622172.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("gbert_job","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("gbert_job","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gbert_job|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/dathi103/gbert-job
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-gbert_job_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-gbert_job_pipeline_en.md
new file mode 100644
index 00000000000000..4beb4b4184f2b3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-gbert_job_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English gbert_job_pipeline pipeline BertEmbeddings from dathi103
+author: John Snow Labs
+name: gbert_job_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gbert_job_pipeline` is a English model originally trained by dathi103.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gbert_job_pipeline_en_5.5.1_3.0_1737774643529.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gbert_job_pipeline_en_5.5.1_3.0_1737774643529.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gbert_job_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gbert_job_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gbert_job_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/dathi103/gbert-job
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-glean_dimension_scoring_deberta_v3_small_01_22_en.md b/docs/_posts/ahmedlone127/2025-01-25-glean_dimension_scoring_deberta_v3_small_01_22_en.md
new file mode 100644
index 00000000000000..f8f42e0f32933b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-glean_dimension_scoring_deberta_v3_small_01_22_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English glean_dimension_scoring_deberta_v3_small_01_22 DeBertaForSequenceClassification from withpi
+author: John Snow Labs
+name: glean_dimension_scoring_deberta_v3_small_01_22
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`glean_dimension_scoring_deberta_v3_small_01_22` is a English model originally trained by withpi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/glean_dimension_scoring_deberta_v3_small_01_22_en_5.5.1_3.0_1737819935538.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/glean_dimension_scoring_deberta_v3_small_01_22_en_5.5.1_3.0_1737819935538.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("glean_dimension_scoring_deberta_v3_small_01_22","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("glean_dimension_scoring_deberta_v3_small_01_22", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|glean_dimension_scoring_deberta_v3_small_01_22|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|417.9 MB|
+
+## References
+
+https://huggingface.co/withpi/glean_dimension_scoring_deberta-v3-small_01-22
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-glean_dimension_scoring_deberta_v3_small_01_22_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-glean_dimension_scoring_deberta_v3_small_01_22_pipeline_en.md
new file mode 100644
index 00000000000000..6824b24062c909
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-glean_dimension_scoring_deberta_v3_small_01_22_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English glean_dimension_scoring_deberta_v3_small_01_22_pipeline pipeline DeBertaForSequenceClassification from withpi
+author: John Snow Labs
+name: glean_dimension_scoring_deberta_v3_small_01_22_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`glean_dimension_scoring_deberta_v3_small_01_22_pipeline` is a English model originally trained by withpi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/glean_dimension_scoring_deberta_v3_small_01_22_pipeline_en_5.5.1_3.0_1737819993267.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/glean_dimension_scoring_deberta_v3_small_01_22_pipeline_en_5.5.1_3.0_1737819993267.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("glean_dimension_scoring_deberta_v3_small_01_22_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("glean_dimension_scoring_deberta_v3_small_01_22_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|glean_dimension_scoring_deberta_v3_small_01_22_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|418.0 MB|
+
+## References
+
+https://huggingface.co/withpi/glean_dimension_scoring_deberta-v3-small_01-22
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-golempii_v1_he.md b/docs/_posts/ahmedlone127/2025-01-25-golempii_v1_he.md
new file mode 100644
index 00000000000000..65652a5b1949f5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-golempii_v1_he.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Hebrew golempii_v1 XlmRoBertaForTokenClassification from CordwainerSmith
+author: John Snow Labs
+name: golempii_v1
+date: 2025-01-25
+tags: [he, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: he
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`golempii_v1` is a Hebrew model originally trained by CordwainerSmith.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/golempii_v1_he_5.5.1_3.0_1737792271198.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/golempii_v1_he_5.5.1_3.0_1737792271198.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("golempii_v1","he") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("golempii_v1", "he")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|golempii_v1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|he|
+|Size:|833.8 MB|
+
+## References
+
+https://huggingface.co/CordwainerSmith/GolemPII-v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-golempii_v1_pipeline_he.md b/docs/_posts/ahmedlone127/2025-01-25-golempii_v1_pipeline_he.md
new file mode 100644
index 00000000000000..4cab4ea8163cf4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-golempii_v1_pipeline_he.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Hebrew golempii_v1_pipeline pipeline XlmRoBertaForTokenClassification from CordwainerSmith
+author: John Snow Labs
+name: golempii_v1_pipeline
+date: 2025-01-25
+tags: [he, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: he
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`golempii_v1_pipeline` is a Hebrew model originally trained by CordwainerSmith.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/golempii_v1_pipeline_he_5.5.1_3.0_1737792361279.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/golempii_v1_pipeline_he_5.5.1_3.0_1737792361279.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("golempii_v1_pipeline", lang = "he")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("golempii_v1_pipeline", lang = "he")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|golempii_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|he|
+|Size:|833.8 MB|
+
+## References
+
+https://huggingface.co/CordwainerSmith/GolemPII-v1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-google_bert_large_cased_finetuned_ner_vlsp2021_3090_15june_1_en.md b/docs/_posts/ahmedlone127/2025-01-25-google_bert_large_cased_finetuned_ner_vlsp2021_3090_15june_1_en.md
new file mode 100644
index 00000000000000..912c4b0d751fba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-google_bert_large_cased_finetuned_ner_vlsp2021_3090_15june_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English google_bert_large_cased_finetuned_ner_vlsp2021_3090_15june_1 BertForTokenClassification from Kudod
+author: John Snow Labs
+name: google_bert_large_cased_finetuned_ner_vlsp2021_3090_15june_1
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`google_bert_large_cased_finetuned_ner_vlsp2021_3090_15june_1` is a English model originally trained by Kudod.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/google_bert_large_cased_finetuned_ner_vlsp2021_3090_15june_1_en_5.5.1_3.0_1737845086088.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/google_bert_large_cased_finetuned_ner_vlsp2021_3090_15june_1_en_5.5.1_3.0_1737845086088.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("google_bert_large_cased_finetuned_ner_vlsp2021_3090_15june_1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("google_bert_large_cased_finetuned_ner_vlsp2021_3090_15june_1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|google_bert_large_cased_finetuned_ner_vlsp2021_3090_15june_1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/Kudod/google-bert-large-cased-finetuned-ner-vlsp2021-3090-15June-1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-google_bert_large_cased_finetuned_ner_vlsp2021_3090_15june_1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-google_bert_large_cased_finetuned_ner_vlsp2021_3090_15june_1_pipeline_en.md
new file mode 100644
index 00000000000000..68454adfbc40e2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-google_bert_large_cased_finetuned_ner_vlsp2021_3090_15june_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English google_bert_large_cased_finetuned_ner_vlsp2021_3090_15june_1_pipeline pipeline BertForTokenClassification from Kudod
+author: John Snow Labs
+name: google_bert_large_cased_finetuned_ner_vlsp2021_3090_15june_1_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`google_bert_large_cased_finetuned_ner_vlsp2021_3090_15june_1_pipeline` is a English model originally trained by Kudod.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/google_bert_large_cased_finetuned_ner_vlsp2021_3090_15june_1_pipeline_en_5.5.1_3.0_1737845147381.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/google_bert_large_cased_finetuned_ner_vlsp2021_3090_15june_1_pipeline_en_5.5.1_3.0_1737845147381.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("google_bert_large_cased_finetuned_ner_vlsp2021_3090_15june_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("google_bert_large_cased_finetuned_ner_vlsp2021_3090_15june_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|google_bert_large_cased_finetuned_ner_vlsp2021_3090_15june_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/Kudod/google-bert-large-cased-finetuned-ner-vlsp2021-3090-15June-1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-gpt2_bengali_bn.md b/docs/_posts/ahmedlone127/2025-01-25-gpt2_bengali_bn.md
new file mode 100644
index 00000000000000..2b1cc48cb5ea15
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-gpt2_bengali_bn.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Bengali gpt2_bengali GPT2Transformer from flax-community
+author: John Snow Labs
+name: gpt2_bengali
+date: 2025-01-25
+tags: [bn, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: bn
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_bengali` is a Bengali model originally trained by flax-community.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_bengali_bn_5.5.1_3.0_1737766019687.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_bengali_bn_5.5.1_3.0_1737766019687.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("gpt2_bengali","bn") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("gpt2_bengali","bn") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_bengali|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|bn|
+|Size:|467.2 MB|
+
+## References
+
+https://huggingface.co/flax-community/gpt2-bengali
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-gpt2_bengali_pipeline_bn.md b/docs/_posts/ahmedlone127/2025-01-25-gpt2_bengali_pipeline_bn.md
new file mode 100644
index 00000000000000..cfe875978c50e7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-gpt2_bengali_pipeline_bn.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Bengali gpt2_bengali_pipeline pipeline GPT2Transformer from flax-community
+author: John Snow Labs
+name: gpt2_bengali_pipeline
+date: 2025-01-25
+tags: [bn, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: bn
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_bengali_pipeline` is a Bengali model originally trained by flax-community.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_bengali_pipeline_bn_5.5.1_3.0_1737766044240.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_bengali_pipeline_bn_5.5.1_3.0_1737766044240.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpt2_bengali_pipeline", lang = "bn")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpt2_bengali_pipeline", lang = "bn")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_bengali_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|bn|
+|Size:|467.2 MB|
+
+## References
+
+https://huggingface.co/flax-community/gpt2-bengali
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-gpt2_expansion_en.md b/docs/_posts/ahmedlone127/2025-01-25-gpt2_expansion_en.md
new file mode 100644
index 00000000000000..8ef1c7832676c6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-gpt2_expansion_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English gpt2_expansion GPT2Transformer from polypo
+author: John Snow Labs
+name: gpt2_expansion
+date: 2025-01-25
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_expansion` is a English model originally trained by polypo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_expansion_en_5.5.1_3.0_1737764776137.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_expansion_en_5.5.1_3.0_1737764776137.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("gpt2_expansion","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("gpt2_expansion","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_expansion|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|298.8 MB|
+
+## References
+
+https://huggingface.co/polypo/gpt2-expansion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-gpt2_expansion_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-gpt2_expansion_pipeline_en.md
new file mode 100644
index 00000000000000..2553b2cf38489c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-gpt2_expansion_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English gpt2_expansion_pipeline pipeline GPT2Transformer from polypo
+author: John Snow Labs
+name: gpt2_expansion_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_expansion_pipeline` is a English model originally trained by polypo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_expansion_pipeline_en_5.5.1_3.0_1737764865255.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_expansion_pipeline_en_5.5.1_3.0_1737764865255.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpt2_expansion_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpt2_expansion_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_expansion_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|298.8 MB|
+
+## References
+
+https://huggingface.co/polypo/gpt2-expansion
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-gpt2_finetune_alpaca_en.md b/docs/_posts/ahmedlone127/2025-01-25-gpt2_finetune_alpaca_en.md
new file mode 100644
index 00000000000000..bbdfddaa4bd1c6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-gpt2_finetune_alpaca_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English gpt2_finetune_alpaca GPT2Transformer from zaanind
+author: John Snow Labs
+name: gpt2_finetune_alpaca
+date: 2025-01-25
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_finetune_alpaca` is a English model originally trained by zaanind.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_finetune_alpaca_en_5.5.1_3.0_1737825270737.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_finetune_alpaca_en_5.5.1_3.0_1737825270737.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("gpt2_finetune_alpaca","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("gpt2_finetune_alpaca","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_finetune_alpaca|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.9 MB|
+
+## References
+
+https://huggingface.co/zaanind/gpt2_finetune_alpaca
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-gpt2_finetune_alpaca_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-gpt2_finetune_alpaca_pipeline_en.md
new file mode 100644
index 00000000000000..369649e4ed34d6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-gpt2_finetune_alpaca_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English gpt2_finetune_alpaca_pipeline pipeline GPT2Transformer from zaanind
+author: John Snow Labs
+name: gpt2_finetune_alpaca_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_finetune_alpaca_pipeline` is a English model originally trained by zaanind.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_finetune_alpaca_pipeline_en_5.5.1_3.0_1737825294614.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_finetune_alpaca_pipeline_en_5.5.1_3.0_1737825294614.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpt2_finetune_alpaca_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpt2_finetune_alpaca_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_finetune_alpaca_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.9 MB|
+
+## References
+
+https://huggingface.co/zaanind/gpt2_finetune_alpaca
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-gpt2_finetuned_greek_el.md b/docs/_posts/ahmedlone127/2025-01-25-gpt2_finetuned_greek_el.md
new file mode 100644
index 00000000000000..2bf1f4de46f967
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-gpt2_finetuned_greek_el.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Modern Greek (1453-) gpt2_finetuned_greek GPT2Transformer from lighteternal
+author: John Snow Labs
+name: gpt2_finetuned_greek
+date: 2025-01-25
+tags: [el, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: el
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_finetuned_greek` is a Modern Greek (1453-) model originally trained by lighteternal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_finetuned_greek_el_5.5.1_3.0_1737826032620.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_finetuned_greek_el_5.5.1_3.0_1737826032620.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("gpt2_finetuned_greek","el") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("gpt2_finetuned_greek","el") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_finetuned_greek|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|el|
+|Size:|467.6 MB|
+
+## References
+
+https://huggingface.co/lighteternal/gpt2-finetuned-greek
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-gpt2_finetuned_greek_pipeline_el.md b/docs/_posts/ahmedlone127/2025-01-25-gpt2_finetuned_greek_pipeline_el.md
new file mode 100644
index 00000000000000..aaf7d868c4d0a9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-gpt2_finetuned_greek_pipeline_el.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Modern Greek (1453-) gpt2_finetuned_greek_pipeline pipeline GPT2Transformer from lighteternal
+author: John Snow Labs
+name: gpt2_finetuned_greek_pipeline
+date: 2025-01-25
+tags: [el, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: el
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_finetuned_greek_pipeline` is a Modern Greek (1453-) model originally trained by lighteternal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_finetuned_greek_pipeline_el_5.5.1_3.0_1737826056543.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_finetuned_greek_pipeline_el_5.5.1_3.0_1737826056543.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpt2_finetuned_greek_pipeline", lang = "el")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpt2_finetuned_greek_pipeline", lang = "el")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_finetuned_greek_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|el|
+|Size:|467.6 MB|
+
+## References
+
+https://huggingface.co/lighteternal/gpt2-finetuned-greek
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-gpt2_finetuned_wikitext103_en.md b/docs/_posts/ahmedlone127/2025-01-25-gpt2_finetuned_wikitext103_en.md
new file mode 100644
index 00000000000000..7067faa311e56b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-gpt2_finetuned_wikitext103_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English gpt2_finetuned_wikitext103 GPT2Transformer from neulab
+author: John Snow Labs
+name: gpt2_finetuned_wikitext103
+date: 2025-01-25
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_finetuned_wikitext103` is a English model originally trained by neulab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_finetuned_wikitext103_en_5.5.1_3.0_1737765563822.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_finetuned_wikitext103_en_5.5.1_3.0_1737765563822.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("gpt2_finetuned_wikitext103","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("gpt2_finetuned_wikitext103","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_finetuned_wikitext103|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.9 MB|
+
+## References
+
+https://huggingface.co/neulab/gpt2-finetuned-wikitext103
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-gpt2_finetuned_wikitext103_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-gpt2_finetuned_wikitext103_pipeline_en.md
new file mode 100644
index 00000000000000..52911d94d2d00f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-gpt2_finetuned_wikitext103_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English gpt2_finetuned_wikitext103_pipeline pipeline GPT2Transformer from neulab
+author: John Snow Labs
+name: gpt2_finetuned_wikitext103_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_finetuned_wikitext103_pipeline` is a English model originally trained by neulab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_finetuned_wikitext103_pipeline_en_5.5.1_3.0_1737765588573.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_finetuned_wikitext103_pipeline_en_5.5.1_3.0_1737765588573.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpt2_finetuned_wikitext103_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpt2_finetuned_wikitext103_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_finetuned_wikitext103_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.9 MB|
+
+## References
+
+https://huggingface.co/neulab/gpt2-finetuned-wikitext103
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-gpt2_fingpt_qa_en.md b/docs/_posts/ahmedlone127/2025-01-25-gpt2_fingpt_qa_en.md
new file mode 100644
index 00000000000000..578d1c7a896d63
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-gpt2_fingpt_qa_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English gpt2_fingpt_qa GPT2Transformer from OpenFinAL
+author: John Snow Labs
+name: gpt2_fingpt_qa
+date: 2025-01-25
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_fingpt_qa` is a English model originally trained by OpenFinAL.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_fingpt_qa_en_5.5.1_3.0_1737825264009.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_fingpt_qa_en_5.5.1_3.0_1737825264009.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("gpt2_fingpt_qa","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("gpt2_fingpt_qa","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_fingpt_qa|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.9 MB|
+
+## References
+
+https://huggingface.co/OpenFinAL/GPT2_FINGPT_QA
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-gpt2_fingpt_qa_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-gpt2_fingpt_qa_pipeline_en.md
new file mode 100644
index 00000000000000..02009dffe8003e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-gpt2_fingpt_qa_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English gpt2_fingpt_qa_pipeline pipeline GPT2Transformer from OpenFinAL
+author: John Snow Labs
+name: gpt2_fingpt_qa_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_fingpt_qa_pipeline` is a English model originally trained by OpenFinAL.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_fingpt_qa_pipeline_en_5.5.1_3.0_1737825288230.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_fingpt_qa_pipeline_en_5.5.1_3.0_1737825288230.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpt2_fingpt_qa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpt2_fingpt_qa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_fingpt_qa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.9 MB|
+
+## References
+
+https://huggingface.co/OpenFinAL/GPT2_FINGPT_QA
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-gpt2_medium_emailgen_en.md b/docs/_posts/ahmedlone127/2025-01-25-gpt2_medium_emailgen_en.md
new file mode 100644
index 00000000000000..1c20b7fab8bf2e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-gpt2_medium_emailgen_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English gpt2_medium_emailgen GPT2Transformer from postbot
+author: John Snow Labs
+name: gpt2_medium_emailgen
+date: 2025-01-25
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_medium_emailgen` is a English model originally trained by postbot.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_medium_emailgen_en_5.5.1_3.0_1737825834999.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_medium_emailgen_en_5.5.1_3.0_1737825834999.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("gpt2_medium_emailgen","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("gpt2_medium_emailgen","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_medium_emailgen|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/postbot/gpt2-medium-emailgen
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-gpt2_medium_emailgen_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-gpt2_medium_emailgen_pipeline_en.md
new file mode 100644
index 00000000000000..0edd19e698b2e5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-gpt2_medium_emailgen_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English gpt2_medium_emailgen_pipeline pipeline GPT2Transformer from postbot
+author: John Snow Labs
+name: gpt2_medium_emailgen_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_medium_emailgen_pipeline` is a English model originally trained by postbot.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_medium_emailgen_pipeline_en_5.5.1_3.0_1737825903658.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_medium_emailgen_pipeline_en_5.5.1_3.0_1737825903658.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpt2_medium_emailgen_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpt2_medium_emailgen_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_medium_emailgen_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/postbot/gpt2-medium-emailgen
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-gpt2_poems_english_en.md b/docs/_posts/ahmedlone127/2025-01-25-gpt2_poems_english_en.md
new file mode 100644
index 00000000000000..69ce21d633497e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-gpt2_poems_english_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English gpt2_poems_english GPT2Transformer from ismaelfaro
+author: John Snow Labs
+name: gpt2_poems_english
+date: 2025-01-25
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_poems_english` is a English model originally trained by ismaelfaro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_poems_english_en_5.5.1_3.0_1737826372958.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_poems_english_en_5.5.1_3.0_1737826372958.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("gpt2_poems_english","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("gpt2_poems_english","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_poems_english|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|468.0 MB|
+
+## References
+
+https://huggingface.co/ismaelfaro/gpt2-poems.en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-gpt2_poems_english_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-gpt2_poems_english_pipeline_en.md
new file mode 100644
index 00000000000000..b44a0ce6ca1a7a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-gpt2_poems_english_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English gpt2_poems_english_pipeline pipeline GPT2Transformer from ismaelfaro
+author: John Snow Labs
+name: gpt2_poems_english_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_poems_english_pipeline` is a English model originally trained by ismaelfaro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_poems_english_pipeline_en_5.5.1_3.0_1737826396485.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_poems_english_pipeline_en_5.5.1_3.0_1737826396485.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpt2_poems_english_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpt2_poems_english_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_poems_english_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|468.0 MB|
+
+## References
+
+https://huggingface.co/ismaelfaro/gpt2-poems.en
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-gpt2_question_answering_squad2_en.md b/docs/_posts/ahmedlone127/2025-01-25-gpt2_question_answering_squad2_en.md
new file mode 100644
index 00000000000000..334bb39b2acf8b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-gpt2_question_answering_squad2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English gpt2_question_answering_squad2 GPT2Transformer from danyaljj
+author: John Snow Labs
+name: gpt2_question_answering_squad2
+date: 2025-01-25
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_question_answering_squad2` is a English model originally trained by danyaljj.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_question_answering_squad2_en_5.5.1_3.0_1737768381153.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_question_answering_squad2_en_5.5.1_3.0_1737768381153.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("gpt2_question_answering_squad2","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("gpt2_question_answering_squad2","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_question_answering_squad2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/danyaljj/gpt2_question_answering_squad2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-gpt2_question_answering_squad2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-gpt2_question_answering_squad2_pipeline_en.md
new file mode 100644
index 00000000000000..de8c0ec6ca3a14
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-gpt2_question_answering_squad2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English gpt2_question_answering_squad2_pipeline pipeline GPT2Transformer from danyaljj
+author: John Snow Labs
+name: gpt2_question_answering_squad2_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_question_answering_squad2_pipeline` is a English model originally trained by danyaljj.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_question_answering_squad2_pipeline_en_5.5.1_3.0_1737768404886.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_question_answering_squad2_pipeline_en_5.5.1_3.0_1737768404886.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpt2_question_answering_squad2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpt2_question_answering_squad2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_question_answering_squad2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/danyaljj/gpt2_question_answering_squad2
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-gpt2_spanish_medium_es.md b/docs/_posts/ahmedlone127/2025-01-25-gpt2_spanish_medium_es.md
new file mode 100644
index 00000000000000..4a52f02bdcaefc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-gpt2_spanish_medium_es.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Castilian, Spanish gpt2_spanish_medium GPT2Transformer from DeepESP
+author: John Snow Labs
+name: gpt2_spanish_medium
+date: 2025-01-25
+tags: [es, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: es
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_spanish_medium` is a Castilian, Spanish model originally trained by DeepESP.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_spanish_medium_es_5.5.1_3.0_1737765659456.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_spanish_medium_es_5.5.1_3.0_1737765659456.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("gpt2_spanish_medium","es") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("gpt2_spanish_medium","es") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_spanish_medium|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|es|
+|Size:|846.7 MB|
+
+## References
+
+https://huggingface.co/DeepESP/gpt2-spanish-medium
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-gpt2_spanish_medium_pipeline_es.md b/docs/_posts/ahmedlone127/2025-01-25-gpt2_spanish_medium_pipeline_es.md
new file mode 100644
index 00000000000000..a4c231cc1248b1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-gpt2_spanish_medium_pipeline_es.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Castilian, Spanish gpt2_spanish_medium_pipeline pipeline GPT2Transformer from DeepESP
+author: John Snow Labs
+name: gpt2_spanish_medium_pipeline
+date: 2025-01-25
+tags: [es, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: es
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_spanish_medium_pipeline` is a Castilian, Spanish model originally trained by DeepESP.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_spanish_medium_pipeline_es_5.5.1_3.0_1737765916693.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_spanish_medium_pipeline_es_5.5.1_3.0_1737765916693.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpt2_spanish_medium_pipeline", lang = "es")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpt2_spanish_medium_pipeline", lang = "es")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_spanish_medium_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|es|
+|Size:|846.7 MB|
+
+## References
+
+https://huggingface.co/DeepESP/gpt2-spanish-medium
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-gpt2_tv_caption_en.md b/docs/_posts/ahmedlone127/2025-01-25-gpt2_tv_caption_en.md
new file mode 100644
index 00000000000000..1953418e440acf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-gpt2_tv_caption_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English gpt2_tv_caption GPT2Transformer from Srilalitha
+author: John Snow Labs
+name: gpt2_tv_caption
+date: 2025-01-25
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_tv_caption` is a English model originally trained by Srilalitha.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_tv_caption_en_5.5.1_3.0_1737764718609.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_tv_caption_en_5.5.1_3.0_1737764718609.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("gpt2_tv_caption","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("gpt2_tv_caption","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_tv_caption|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/Srilalitha/gpt2-tv-caption
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-gpt2_tv_caption_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-gpt2_tv_caption_pipeline_en.md
new file mode 100644
index 00000000000000..44e8f500a1b17f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-gpt2_tv_caption_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English gpt2_tv_caption_pipeline pipeline GPT2Transformer from Srilalitha
+author: John Snow Labs
+name: gpt2_tv_caption_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_tv_caption_pipeline` is a English model originally trained by Srilalitha.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_tv_caption_pipeline_en_5.5.1_3.0_1737764743027.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_tv_caption_pipeline_en_5.5.1_3.0_1737764743027.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpt2_tv_caption_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpt2_tv_caption_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_tv_caption_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/Srilalitha/gpt2-tv-caption
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-hamlet_mlm_model_2_en.md b/docs/_posts/ahmedlone127/2025-01-25-hamlet_mlm_model_2_en.md
new file mode 100644
index 00000000000000..7be0797b0d10be
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-hamlet_mlm_model_2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English hamlet_mlm_model_2 RoBertaEmbeddings from kazisami
+author: John Snow Labs
+name: hamlet_mlm_model_2
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hamlet_mlm_model_2` is a English model originally trained by kazisami.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hamlet_mlm_model_2_en_5.5.1_3.0_1737796967947.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hamlet_mlm_model_2_en_5.5.1_3.0_1737796967947.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("hamlet_mlm_model_2","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("hamlet_mlm_model_2","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hamlet_mlm_model_2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/kazisami/hamlet_mlm_model_2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-hamlet_mlm_model_2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-hamlet_mlm_model_2_pipeline_en.md
new file mode 100644
index 00000000000000..cfd11eba5e1f4c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-hamlet_mlm_model_2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English hamlet_mlm_model_2_pipeline pipeline RoBertaEmbeddings from kazisami
+author: John Snow Labs
+name: hamlet_mlm_model_2_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hamlet_mlm_model_2_pipeline` is a English model originally trained by kazisami.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hamlet_mlm_model_2_pipeline_en_5.5.1_3.0_1737796983940.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hamlet_mlm_model_2_pipeline_en_5.5.1_3.0_1737796983940.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("hamlet_mlm_model_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hamlet_mlm_model_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hamlet_mlm_model_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/kazisami/hamlet_mlm_model_2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-hatespeech_beto_cased_v1_es.md b/docs/_posts/ahmedlone127/2025-01-25-hatespeech_beto_cased_v1_es.md
new file mode 100644
index 00000000000000..aa9f27535283c5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-hatespeech_beto_cased_v1_es.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Castilian, Spanish hatespeech_beto_cased_v1 BertForSequenceClassification from delarosajav95
+author: John Snow Labs
+name: hatespeech_beto_cased_v1
+date: 2025-01-25
+tags: [es, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: es
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hatespeech_beto_cased_v1` is a Castilian, Spanish model originally trained by delarosajav95.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hatespeech_beto_cased_v1_es_5.5.1_3.0_1737801030953.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hatespeech_beto_cased_v1_es_5.5.1_3.0_1737801030953.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("hatespeech_beto_cased_v1","es") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("hatespeech_beto_cased_v1", "es")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hatespeech_beto_cased_v1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|es|
+|Size:|411.7 MB|
+
+## References
+
+https://huggingface.co/delarosajav95/HateSpeech-BETO-cased-v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-hatespeech_beto_cased_v1_pipeline_es.md b/docs/_posts/ahmedlone127/2025-01-25-hatespeech_beto_cased_v1_pipeline_es.md
new file mode 100644
index 00000000000000..f4325068749776
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-hatespeech_beto_cased_v1_pipeline_es.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Castilian, Spanish hatespeech_beto_cased_v1_pipeline pipeline BertForSequenceClassification from delarosajav95
+author: John Snow Labs
+name: hatespeech_beto_cased_v1_pipeline
+date: 2025-01-25
+tags: [es, open_source, pipeline, onnx]
+task: Text Classification
+language: es
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hatespeech_beto_cased_v1_pipeline` is a Castilian, Spanish model originally trained by delarosajav95.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hatespeech_beto_cased_v1_pipeline_es_5.5.1_3.0_1737801054087.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hatespeech_beto_cased_v1_pipeline_es_5.5.1_3.0_1737801054087.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("hatespeech_beto_cased_v1_pipeline", lang = "es")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hatespeech_beto_cased_v1_pipeline", lang = "es")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hatespeech_beto_cased_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|es|
+|Size:|411.7 MB|
+
+## References
+
+https://huggingface.co/delarosajav95/HateSpeech-BETO-cased-v1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-helsinki_danish_swedish_en.md b/docs/_posts/ahmedlone127/2025-01-25-helsinki_danish_swedish_en.md
new file mode 100644
index 00000000000000..85bcb62ae3edb6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-helsinki_danish_swedish_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English helsinki_danish_swedish MarianTransformer from Danieljacobsen
+author: John Snow Labs
+name: helsinki_danish_swedish
+date: 2025-01-25
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`helsinki_danish_swedish` is a English model originally trained by Danieljacobsen.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/helsinki_danish_swedish_en_5.5.1_3.0_1737841181085.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/helsinki_danish_swedish_en_5.5.1_3.0_1737841181085.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("helsinki_danish_swedish","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("helsinki_danish_swedish","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|helsinki_danish_swedish|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|390.8 MB|
+
+## References
+
+https://huggingface.co/Danieljacobsen/Helsinki-DA-SV
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-helsinki_danish_swedish_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-helsinki_danish_swedish_pipeline_en.md
new file mode 100644
index 00000000000000..d4571a15931f2f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-helsinki_danish_swedish_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English helsinki_danish_swedish_pipeline pipeline MarianTransformer from Danieljacobsen
+author: John Snow Labs
+name: helsinki_danish_swedish_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`helsinki_danish_swedish_pipeline` is a English model originally trained by Danieljacobsen.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/helsinki_danish_swedish_pipeline_en_5.5.1_3.0_1737841200341.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/helsinki_danish_swedish_pipeline_en_5.5.1_3.0_1737841200341.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("helsinki_danish_swedish_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("helsinki_danish_swedish_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|helsinki_danish_swedish_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|391.3 MB|
+
+## References
+
+https://huggingface.co/Danieljacobsen/Helsinki-DA-SV
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-helsinki_nlp_opus_maltese_eng_maithili_epoch5_en.md b/docs/_posts/ahmedlone127/2025-01-25-helsinki_nlp_opus_maltese_eng_maithili_epoch5_en.md
new file mode 100644
index 00000000000000..3b42d65e497957
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-helsinki_nlp_opus_maltese_eng_maithili_epoch5_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English helsinki_nlp_opus_maltese_eng_maithili_epoch5 MarianTransformer from kubershahi
+author: John Snow Labs
+name: helsinki_nlp_opus_maltese_eng_maithili_epoch5
+date: 2025-01-25
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`helsinki_nlp_opus_maltese_eng_maithili_epoch5` is a English model originally trained by kubershahi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/helsinki_nlp_opus_maltese_eng_maithili_epoch5_en_5.5.1_3.0_1737781628744.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/helsinki_nlp_opus_maltese_eng_maithili_epoch5_en_5.5.1_3.0_1737781628744.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("helsinki_nlp_opus_maltese_eng_maithili_epoch5","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("helsinki_nlp_opus_maltese_eng_maithili_epoch5","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|helsinki_nlp_opus_maltese_eng_maithili_epoch5|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|405.8 MB|
+
+## References
+
+https://huggingface.co/kubershahi/Helsinki-NLP-opus-mt-eng-mai-epoch5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-helsinki_nlp_opus_maltese_eng_maithili_epoch5_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-helsinki_nlp_opus_maltese_eng_maithili_epoch5_pipeline_en.md
new file mode 100644
index 00000000000000..d1bed60e0b01bb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-helsinki_nlp_opus_maltese_eng_maithili_epoch5_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English helsinki_nlp_opus_maltese_eng_maithili_epoch5_pipeline pipeline MarianTransformer from kubershahi
+author: John Snow Labs
+name: helsinki_nlp_opus_maltese_eng_maithili_epoch5_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`helsinki_nlp_opus_maltese_eng_maithili_epoch5_pipeline` is a English model originally trained by kubershahi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/helsinki_nlp_opus_maltese_eng_maithili_epoch5_pipeline_en_5.5.1_3.0_1737781650279.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/helsinki_nlp_opus_maltese_eng_maithili_epoch5_pipeline_en_5.5.1_3.0_1737781650279.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("helsinki_nlp_opus_maltese_eng_maithili_epoch5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("helsinki_nlp_opus_maltese_eng_maithili_epoch5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|helsinki_nlp_opus_maltese_eng_maithili_epoch5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.4 MB|
+
+## References
+
+https://huggingface.co/kubershahi/Helsinki-NLP-opus-mt-eng-mai-epoch5
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-helsinki_nlp_opus_maltese_multiple_languages_english_finetuned_hindi_tonga_tonga_islands_english_en.md b/docs/_posts/ahmedlone127/2025-01-25-helsinki_nlp_opus_maltese_multiple_languages_english_finetuned_hindi_tonga_tonga_islands_english_en.md
new file mode 100644
index 00000000000000..dbe301b73f269e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-helsinki_nlp_opus_maltese_multiple_languages_english_finetuned_hindi_tonga_tonga_islands_english_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English helsinki_nlp_opus_maltese_multiple_languages_english_finetuned_hindi_tonga_tonga_islands_english MarianTransformer from guldasta
+author: John Snow Labs
+name: helsinki_nlp_opus_maltese_multiple_languages_english_finetuned_hindi_tonga_tonga_islands_english
+date: 2025-01-25
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`helsinki_nlp_opus_maltese_multiple_languages_english_finetuned_hindi_tonga_tonga_islands_english` is a English model originally trained by guldasta.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/helsinki_nlp_opus_maltese_multiple_languages_english_finetuned_hindi_tonga_tonga_islands_english_en_5.5.1_3.0_1737782930822.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/helsinki_nlp_opus_maltese_multiple_languages_english_finetuned_hindi_tonga_tonga_islands_english_en_5.5.1_3.0_1737782930822.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("helsinki_nlp_opus_maltese_multiple_languages_english_finetuned_hindi_tonga_tonga_islands_english","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("helsinki_nlp_opus_maltese_multiple_languages_english_finetuned_hindi_tonga_tonga_islands_english","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|helsinki_nlp_opus_maltese_multiple_languages_english_finetuned_hindi_tonga_tonga_islands_english|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|414.6 MB|
+
+## References
+
+https://huggingface.co/guldasta/Helsinki-NLP-opus-mt-mul-en-finetuned-hi-to-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-helsinki_nlp_opus_maltese_multiple_languages_english_finetuned_hindi_tonga_tonga_islands_english_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-helsinki_nlp_opus_maltese_multiple_languages_english_finetuned_hindi_tonga_tonga_islands_english_pipeline_en.md
new file mode 100644
index 00000000000000..57e11bf730be4f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-helsinki_nlp_opus_maltese_multiple_languages_english_finetuned_hindi_tonga_tonga_islands_english_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English helsinki_nlp_opus_maltese_multiple_languages_english_finetuned_hindi_tonga_tonga_islands_english_pipeline pipeline MarianTransformer from guldasta
+author: John Snow Labs
+name: helsinki_nlp_opus_maltese_multiple_languages_english_finetuned_hindi_tonga_tonga_islands_english_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`helsinki_nlp_opus_maltese_multiple_languages_english_finetuned_hindi_tonga_tonga_islands_english_pipeline` is a English model originally trained by guldasta.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/helsinki_nlp_opus_maltese_multiple_languages_english_finetuned_hindi_tonga_tonga_islands_english_pipeline_en_5.5.1_3.0_1737782952509.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/helsinki_nlp_opus_maltese_multiple_languages_english_finetuned_hindi_tonga_tonga_islands_english_pipeline_en_5.5.1_3.0_1737782952509.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("helsinki_nlp_opus_maltese_multiple_languages_english_finetuned_hindi_tonga_tonga_islands_english_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("helsinki_nlp_opus_maltese_multiple_languages_english_finetuned_hindi_tonga_tonga_islands_english_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|helsinki_nlp_opus_maltese_multiple_languages_english_finetuned_hindi_tonga_tonga_islands_english_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|415.1 MB|
+
+## References
+
+https://huggingface.co/guldasta/Helsinki-NLP-opus-mt-mul-en-finetuned-hi-to-en
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-hreb_resume_en.md b/docs/_posts/ahmedlone127/2025-01-25-hreb_resume_en.md
new file mode 100644
index 00000000000000..8b3bfc29da096a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-hreb_resume_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English hreb_resume BertForTokenClassification from PassbyGrocer
+author: John Snow Labs
+name: hreb_resume
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hreb_resume` is a English model originally trained by PassbyGrocer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hreb_resume_en_5.5.1_3.0_1737844541024.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hreb_resume_en_5.5.1_3.0_1737844541024.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("hreb_resume","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("hreb_resume", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hreb_resume|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/PassbyGrocer/hreb-resume
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-hreb_resume_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-hreb_resume_pipeline_en.md
new file mode 100644
index 00000000000000..436f3dc53e00f4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-hreb_resume_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English hreb_resume_pipeline pipeline BertForTokenClassification from PassbyGrocer
+author: John Snow Labs
+name: hreb_resume_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hreb_resume_pipeline` is a English model originally trained by PassbyGrocer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hreb_resume_pipeline_en_5.5.1_3.0_1737844601400.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hreb_resume_pipeline_en_5.5.1_3.0_1737844601400.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("hreb_resume_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hreb_resume_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hreb_resume_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/PassbyGrocer/hreb-resume
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-hw_dl_10_competitions_v1_en.md b/docs/_posts/ahmedlone127/2025-01-25-hw_dl_10_competitions_v1_en.md
new file mode 100644
index 00000000000000..0b0ee778765a85
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-hw_dl_10_competitions_v1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English hw_dl_10_competitions_v1 DistilBertForSequenceClassification from kirilica
+author: John Snow Labs
+name: hw_dl_10_competitions_v1
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hw_dl_10_competitions_v1` is a English model originally trained by kirilica.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hw_dl_10_competitions_v1_en_5.5.1_3.0_1737838409322.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hw_dl_10_competitions_v1_en_5.5.1_3.0_1737838409322.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("hw_dl_10_competitions_v1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("hw_dl_10_competitions_v1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hw_dl_10_competitions_v1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/kirilica/HW_DL_10_Competitions_v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-hw_dl_10_competitions_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-hw_dl_10_competitions_v1_pipeline_en.md
new file mode 100644
index 00000000000000..6a8a008fa342db
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-hw_dl_10_competitions_v1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English hw_dl_10_competitions_v1_pipeline pipeline DistilBertForSequenceClassification from kirilica
+author: John Snow Labs
+name: hw_dl_10_competitions_v1_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hw_dl_10_competitions_v1_pipeline` is a English model originally trained by kirilica.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hw_dl_10_competitions_v1_pipeline_en_5.5.1_3.0_1737838422085.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hw_dl_10_competitions_v1_pipeline_en_5.5.1_3.0_1737838422085.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("hw_dl_10_competitions_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hw_dl_10_competitions_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hw_dl_10_competitions_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/kirilica/HW_DL_10_Competitions_v1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-ibama_29102024_20241029175942_en.md b/docs/_posts/ahmedlone127/2025-01-25-ibama_29102024_20241029175942_en.md
new file mode 100644
index 00000000000000..f0bc6262e6e57a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-ibama_29102024_20241029175942_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English ibama_29102024_20241029175942 BertForQuestionAnswering from alcalazans
+author: John Snow Labs
+name: ibama_29102024_20241029175942
+date: 2025-01-25
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ibama_29102024_20241029175942` is a English model originally trained by alcalazans.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ibama_29102024_20241029175942_en_5.5.1_3.0_1737813297406.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ibama_29102024_20241029175942_en_5.5.1_3.0_1737813297406.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("ibama_29102024_20241029175942","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("ibama_29102024_20241029175942", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ibama_29102024_20241029175942|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|405.9 MB|
+
+## References
+
+https://huggingface.co/alcalazans/ibama_29102024_20241029175942
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-ibama_29102024_20241029175942_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-ibama_29102024_20241029175942_pipeline_en.md
new file mode 100644
index 00000000000000..d35d79532ba1a9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-ibama_29102024_20241029175942_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English ibama_29102024_20241029175942_pipeline pipeline BertForQuestionAnswering from alcalazans
+author: John Snow Labs
+name: ibama_29102024_20241029175942_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ibama_29102024_20241029175942_pipeline` is a English model originally trained by alcalazans.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ibama_29102024_20241029175942_pipeline_en_5.5.1_3.0_1737813318792.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ibama_29102024_20241029175942_pipeline_en_5.5.1_3.0_1737813318792.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ibama_29102024_20241029175942_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ibama_29102024_20241029175942_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ibama_29102024_20241029175942_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.0 MB|
+
+## References
+
+https://huggingface.co/alcalazans/ibama_29102024_20241029175942
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-idt5_base_qa_qg_baseline_tydiqa_indonesian_en.md b/docs/_posts/ahmedlone127/2025-01-25-idt5_base_qa_qg_baseline_tydiqa_indonesian_en.md
new file mode 100644
index 00000000000000..fc041dc218a350
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-idt5_base_qa_qg_baseline_tydiqa_indonesian_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English idt5_base_qa_qg_baseline_tydiqa_indonesian T5Transformer from hawalurahman
+author: John Snow Labs
+name: idt5_base_qa_qg_baseline_tydiqa_indonesian
+date: 2025-01-25
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`idt5_base_qa_qg_baseline_tydiqa_indonesian` is a English model originally trained by hawalurahman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/idt5_base_qa_qg_baseline_tydiqa_indonesian_en_5.5.1_3.0_1737848520884.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/idt5_base_qa_qg_baseline_tydiqa_indonesian_en_5.5.1_3.0_1737848520884.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("idt5_base_qa_qg_baseline_tydiqa_indonesian","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("idt5_base_qa_qg_baseline_tydiqa_indonesian", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|idt5_base_qa_qg_baseline_tydiqa_indonesian|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|974.9 MB|
+
+## References
+
+https://huggingface.co/hawalurahman/idt5-base-qa-qg-baseline-TydiQA-id
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-idt5_base_qa_qg_baseline_tydiqa_indonesian_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-idt5_base_qa_qg_baseline_tydiqa_indonesian_pipeline_en.md
new file mode 100644
index 00000000000000..3acffe48e1396d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-idt5_base_qa_qg_baseline_tydiqa_indonesian_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English idt5_base_qa_qg_baseline_tydiqa_indonesian_pipeline pipeline T5Transformer from hawalurahman
+author: John Snow Labs
+name: idt5_base_qa_qg_baseline_tydiqa_indonesian_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`idt5_base_qa_qg_baseline_tydiqa_indonesian_pipeline` is a English model originally trained by hawalurahman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/idt5_base_qa_qg_baseline_tydiqa_indonesian_pipeline_en_5.5.1_3.0_1737848570397.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/idt5_base_qa_qg_baseline_tydiqa_indonesian_pipeline_en_5.5.1_3.0_1737848570397.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("idt5_base_qa_qg_baseline_tydiqa_indonesian_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("idt5_base_qa_qg_baseline_tydiqa_indonesian_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|idt5_base_qa_qg_baseline_tydiqa_indonesian_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|974.9 MB|
+
+## References
+
+https://huggingface.co/hawalurahman/idt5-base-qa-qg-baseline-TydiQA-id
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-imdbreviews_classification_distilbert_v02_clf_finetuning_mancd_en.md b/docs/_posts/ahmedlone127/2025-01-25-imdbreviews_classification_distilbert_v02_clf_finetuning_mancd_en.md
new file mode 100644
index 00000000000000..9d5e5197378e34
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-imdbreviews_classification_distilbert_v02_clf_finetuning_mancd_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English imdbreviews_classification_distilbert_v02_clf_finetuning_mancd DistilBertForSequenceClassification from ManCD
+author: John Snow Labs
+name: imdbreviews_classification_distilbert_v02_clf_finetuning_mancd
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`imdbreviews_classification_distilbert_v02_clf_finetuning_mancd` is a English model originally trained by ManCD.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/imdbreviews_classification_distilbert_v02_clf_finetuning_mancd_en_5.5.1_3.0_1737822183145.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/imdbreviews_classification_distilbert_v02_clf_finetuning_mancd_en_5.5.1_3.0_1737822183145.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("imdbreviews_classification_distilbert_v02_clf_finetuning_mancd","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("imdbreviews_classification_distilbert_v02_clf_finetuning_mancd", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|imdbreviews_classification_distilbert_v02_clf_finetuning_mancd|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/ManCD/imdbreviews_classification_distilbert_v02_clf_finetuning
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-imdbreviews_classification_distilbert_v02_clf_finetuning_mancd_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-imdbreviews_classification_distilbert_v02_clf_finetuning_mancd_pipeline_en.md
new file mode 100644
index 00000000000000..cbdc5ae9fb5d90
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-imdbreviews_classification_distilbert_v02_clf_finetuning_mancd_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English imdbreviews_classification_distilbert_v02_clf_finetuning_mancd_pipeline pipeline DistilBertForSequenceClassification from ManCD
+author: John Snow Labs
+name: imdbreviews_classification_distilbert_v02_clf_finetuning_mancd_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`imdbreviews_classification_distilbert_v02_clf_finetuning_mancd_pipeline` is a English model originally trained by ManCD.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/imdbreviews_classification_distilbert_v02_clf_finetuning_mancd_pipeline_en_5.5.1_3.0_1737822199290.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/imdbreviews_classification_distilbert_v02_clf_finetuning_mancd_pipeline_en_5.5.1_3.0_1737822199290.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("imdbreviews_classification_distilbert_v02_clf_finetuning_mancd_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("imdbreviews_classification_distilbert_v02_clf_finetuning_mancd_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|imdbreviews_classification_distilbert_v02_clf_finetuning_mancd_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/ManCD/imdbreviews_classification_distilbert_v02_clf_finetuning
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-indicbertv2_mlm_only_finetuned_imdb_en.md b/docs/_posts/ahmedlone127/2025-01-25-indicbertv2_mlm_only_finetuned_imdb_en.md
new file mode 100644
index 00000000000000..83877fa3b82be4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-indicbertv2_mlm_only_finetuned_imdb_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English indicbertv2_mlm_only_finetuned_imdb BertEmbeddings from varshith0101
+author: John Snow Labs
+name: indicbertv2_mlm_only_finetuned_imdb
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indicbertv2_mlm_only_finetuned_imdb` is a English model originally trained by varshith0101.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indicbertv2_mlm_only_finetuned_imdb_en_5.5.1_3.0_1737821036702.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indicbertv2_mlm_only_finetuned_imdb_en_5.5.1_3.0_1737821036702.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("indicbertv2_mlm_only_finetuned_imdb","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("indicbertv2_mlm_only_finetuned_imdb","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|indicbertv2_mlm_only_finetuned_imdb|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/varshith0101/IndicBERTv2-MLM-only-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-indicbertv2_mlm_only_finetuned_imdb_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-indicbertv2_mlm_only_finetuned_imdb_pipeline_en.md
new file mode 100644
index 00000000000000..2bd3a57c6ae96f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-indicbertv2_mlm_only_finetuned_imdb_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English indicbertv2_mlm_only_finetuned_imdb_pipeline pipeline BertEmbeddings from varshith0101
+author: John Snow Labs
+name: indicbertv2_mlm_only_finetuned_imdb_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indicbertv2_mlm_only_finetuned_imdb_pipeline` is a English model originally trained by varshith0101.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indicbertv2_mlm_only_finetuned_imdb_pipeline_en_5.5.1_3.0_1737821089889.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indicbertv2_mlm_only_finetuned_imdb_pipeline_en_5.5.1_3.0_1737821089889.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("indicbertv2_mlm_only_finetuned_imdb_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("indicbertv2_mlm_only_finetuned_imdb_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|indicbertv2_mlm_only_finetuned_imdb_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/varshith0101/IndicBERTv2-MLM-only-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-indobert_nusa_id.md b/docs/_posts/ahmedlone127/2025-01-25-indobert_nusa_id.md
new file mode 100644
index 00000000000000..5bd2e38119964e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-indobert_nusa_id.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Indonesian indobert_nusa BertEmbeddings from prosa-text
+author: John Snow Labs
+name: indobert_nusa
+date: 2025-01-25
+tags: [id, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: id
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indobert_nusa` is a Indonesian model originally trained by prosa-text.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indobert_nusa_id_5.5.1_3.0_1737807273585.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indobert_nusa_id_5.5.1_3.0_1737807273585.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("indobert_nusa","id") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("indobert_nusa","id") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|indobert_nusa|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|id|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/prosa-text/indobert-nusa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-indobert_nusa_pipeline_id.md b/docs/_posts/ahmedlone127/2025-01-25-indobert_nusa_pipeline_id.md
new file mode 100644
index 00000000000000..96e5a0781838a5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-indobert_nusa_pipeline_id.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Indonesian indobert_nusa_pipeline pipeline BertEmbeddings from prosa-text
+author: John Snow Labs
+name: indobert_nusa_pipeline
+date: 2025-01-25
+tags: [id, open_source, pipeline, onnx]
+task: Embeddings
+language: id
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indobert_nusa_pipeline` is a Indonesian model originally trained by prosa-text.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indobert_nusa_pipeline_id_5.5.1_3.0_1737807336877.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indobert_nusa_pipeline_id_5.5.1_3.0_1737807336877.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("indobert_nusa_pipeline", lang = "id")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("indobert_nusa_pipeline", lang = "id")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|indobert_nusa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|id|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/prosa-text/indobert-nusa
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-juan_carlos_campero_amazon_en.md b/docs/_posts/ahmedlone127/2025-01-25-juan_carlos_campero_amazon_en.md
new file mode 100644
index 00000000000000..dad6f1cf636dd8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-juan_carlos_campero_amazon_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English juan_carlos_campero_amazon DistilBertForSequenceClassification from camperro
+author: John Snow Labs
+name: juan_carlos_campero_amazon
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`juan_carlos_campero_amazon` is a English model originally trained by camperro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/juan_carlos_campero_amazon_en_5.5.1_3.0_1737837093398.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/juan_carlos_campero_amazon_en_5.5.1_3.0_1737837093398.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("juan_carlos_campero_amazon","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("juan_carlos_campero_amazon", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|juan_carlos_campero_amazon|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/camperro/juan_carlos_campero_amazon
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-juan_carlos_campero_amazon_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-juan_carlos_campero_amazon_pipeline_en.md
new file mode 100644
index 00000000000000..ab90322597c585
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-juan_carlos_campero_amazon_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English juan_carlos_campero_amazon_pipeline pipeline DistilBertForSequenceClassification from camperro
+author: John Snow Labs
+name: juan_carlos_campero_amazon_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`juan_carlos_campero_amazon_pipeline` is a English model originally trained by camperro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/juan_carlos_campero_amazon_pipeline_en_5.5.1_3.0_1737837106658.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/juan_carlos_campero_amazon_pipeline_en_5.5.1_3.0_1737837106658.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("juan_carlos_campero_amazon_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("juan_carlos_campero_amazon_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|juan_carlos_campero_amazon_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/camperro/juan_carlos_campero_amazon
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-kcbert_special_en.md b/docs/_posts/ahmedlone127/2025-01-25-kcbert_special_en.md
new file mode 100644
index 00000000000000..c0b29d23f2e4f6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-kcbert_special_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English kcbert_special BertEmbeddings from nozzi
+author: John Snow Labs
+name: kcbert_special
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kcbert_special` is a English model originally trained by nozzi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kcbert_special_en_5.5.1_3.0_1737821477579.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kcbert_special_en_5.5.1_3.0_1737821477579.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("kcbert_special","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("kcbert_special","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|kcbert_special|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|406.3 MB|
+
+## References
+
+https://huggingface.co/nozzi/kcbert-special
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-kcbert_special_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-kcbert_special_pipeline_en.md
new file mode 100644
index 00000000000000..7d03b60d6c76a1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-kcbert_special_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English kcbert_special_pipeline pipeline BertEmbeddings from nozzi
+author: John Snow Labs
+name: kcbert_special_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kcbert_special_pipeline` is a English model originally trained by nozzi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kcbert_special_pipeline_en_5.5.1_3.0_1737821498571.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kcbert_special_pipeline_en_5.5.1_3.0_1737821498571.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("kcbert_special_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("kcbert_special_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|kcbert_special_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.3 MB|
+
+## References
+
+https://huggingface.co/nozzi/kcbert-special
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-kinyabert_small_pretrained_kinyarwanda_en.md b/docs/_posts/ahmedlone127/2025-01-25-kinyabert_small_pretrained_kinyarwanda_en.md
new file mode 100644
index 00000000000000..42377e7964a7d0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-kinyabert_small_pretrained_kinyarwanda_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English kinyabert_small_pretrained_kinyarwanda BertEmbeddings from RogerB
+author: John Snow Labs
+name: kinyabert_small_pretrained_kinyarwanda
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kinyabert_small_pretrained_kinyarwanda` is a English model originally trained by RogerB.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kinyabert_small_pretrained_kinyarwanda_en_5.5.1_3.0_1737785307373.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kinyabert_small_pretrained_kinyarwanda_en_5.5.1_3.0_1737785307373.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("kinyabert_small_pretrained_kinyarwanda","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("kinyabert_small_pretrained_kinyarwanda","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|kinyabert_small_pretrained_kinyarwanda|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|247.4 MB|
+
+## References
+
+https://huggingface.co/RogerB/KinyaBERT-small-pretrained-kinyarwanda
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-kinyabert_small_pretrained_kinyarwanda_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-kinyabert_small_pretrained_kinyarwanda_pipeline_en.md
new file mode 100644
index 00000000000000..ad0daceccdc04c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-kinyabert_small_pretrained_kinyarwanda_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English kinyabert_small_pretrained_kinyarwanda_pipeline pipeline BertEmbeddings from RogerB
+author: John Snow Labs
+name: kinyabert_small_pretrained_kinyarwanda_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kinyabert_small_pretrained_kinyarwanda_pipeline` is a English model originally trained by RogerB.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kinyabert_small_pretrained_kinyarwanda_pipeline_en_5.5.1_3.0_1737785320866.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kinyabert_small_pretrained_kinyarwanda_pipeline_en_5.5.1_3.0_1737785320866.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("kinyabert_small_pretrained_kinyarwanda_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("kinyabert_small_pretrained_kinyarwanda_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|kinyabert_small_pretrained_kinyarwanda_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.5 MB|
+
+## References
+
+https://huggingface.co/RogerB/KinyaBERT-small-pretrained-kinyarwanda
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-kols_purposes_model_en.md b/docs/_posts/ahmedlone127/2025-01-25-kols_purposes_model_en.md
new file mode 100644
index 00000000000000..9ef483cdffb8e5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-kols_purposes_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English kols_purposes_model BertForSequenceClassification from Centic-AI
+author: John Snow Labs
+name: kols_purposes_model
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kols_purposes_model` is a English model originally trained by Centic-AI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kols_purposes_model_en_5.5.1_3.0_1737800454517.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kols_purposes_model_en_5.5.1_3.0_1737800454517.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("kols_purposes_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("kols_purposes_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|kols_purposes_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/Centic-AI/kols_purposes_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-kols_purposes_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-kols_purposes_model_pipeline_en.md
new file mode 100644
index 00000000000000..3f2c6aef2a0007
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-kols_purposes_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English kols_purposes_model_pipeline pipeline BertForSequenceClassification from Centic-AI
+author: John Snow Labs
+name: kols_purposes_model_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kols_purposes_model_pipeline` is a English model originally trained by Centic-AI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kols_purposes_model_pipeline_en_5.5.1_3.0_1737800475635.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kols_purposes_model_pipeline_en_5.5.1_3.0_1737800475635.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("kols_purposes_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("kols_purposes_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|kols_purposes_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/Centic-AI/kols_purposes_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-language_detection_fine_tuned_on_xlm_roberta_base_en.md b/docs/_posts/ahmedlone127/2025-01-25-language_detection_fine_tuned_on_xlm_roberta_base_en.md
new file mode 100644
index 00000000000000..04d178ae4b290a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-language_detection_fine_tuned_on_xlm_roberta_base_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English language_detection_fine_tuned_on_xlm_roberta_base XlmRoBertaForSequenceClassification from barto17
+author: John Snow Labs
+name: language_detection_fine_tuned_on_xlm_roberta_base
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`language_detection_fine_tuned_on_xlm_roberta_base` is a English model originally trained by barto17.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/language_detection_fine_tuned_on_xlm_roberta_base_en_5.5.1_3.0_1737816593341.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/language_detection_fine_tuned_on_xlm_roberta_base_en_5.5.1_3.0_1737816593341.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("language_detection_fine_tuned_on_xlm_roberta_base","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("language_detection_fine_tuned_on_xlm_roberta_base", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|language_detection_fine_tuned_on_xlm_roberta_base|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|844.0 MB|
+
+## References
+
+https://huggingface.co/barto17/language-detection-fine-tuned-on-xlm-roberta-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-language_detection_fine_tuned_on_xlm_roberta_base_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-language_detection_fine_tuned_on_xlm_roberta_base_pipeline_en.md
new file mode 100644
index 00000000000000..2fd0174c717ca5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-language_detection_fine_tuned_on_xlm_roberta_base_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English language_detection_fine_tuned_on_xlm_roberta_base_pipeline pipeline XlmRoBertaForSequenceClassification from barto17
+author: John Snow Labs
+name: language_detection_fine_tuned_on_xlm_roberta_base_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`language_detection_fine_tuned_on_xlm_roberta_base_pipeline` is a English model originally trained by barto17.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/language_detection_fine_tuned_on_xlm_roberta_base_pipeline_en_5.5.1_3.0_1737816714117.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/language_detection_fine_tuned_on_xlm_roberta_base_pipeline_en_5.5.1_3.0_1737816714117.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("language_detection_fine_tuned_on_xlm_roberta_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("language_detection_fine_tuned_on_xlm_roberta_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|language_detection_fine_tuned_on_xlm_roberta_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|844.0 MB|
+
+## References
+
+https://huggingface.co/barto17/language-detection-fine-tuned-on-xlm-roberta-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-lct_rubert_tiny2_ner_en.md b/docs/_posts/ahmedlone127/2025-01-25-lct_rubert_tiny2_ner_en.md
new file mode 100644
index 00000000000000..1fee7bdcb3ffa1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-lct_rubert_tiny2_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English lct_rubert_tiny2_ner BertForTokenClassification from Ilya-Nazimov
+author: John Snow Labs
+name: lct_rubert_tiny2_ner
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lct_rubert_tiny2_ner` is a English model originally trained by Ilya-Nazimov.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lct_rubert_tiny2_ner_en_5.5.1_3.0_1737844629686.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lct_rubert_tiny2_ner_en_5.5.1_3.0_1737844629686.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("lct_rubert_tiny2_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("lct_rubert_tiny2_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lct_rubert_tiny2_ner|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|109.1 MB|
+
+## References
+
+https://huggingface.co/Ilya-Nazimov/lct-rubert-tiny2-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-lct_rubert_tiny2_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-lct_rubert_tiny2_ner_pipeline_en.md
new file mode 100644
index 00000000000000..63c08f3aa8bd8a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-lct_rubert_tiny2_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English lct_rubert_tiny2_ner_pipeline pipeline BertForTokenClassification from Ilya-Nazimov
+author: John Snow Labs
+name: lct_rubert_tiny2_ner_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lct_rubert_tiny2_ner_pipeline` is a English model originally trained by Ilya-Nazimov.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lct_rubert_tiny2_ner_pipeline_en_5.5.1_3.0_1737844635223.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lct_rubert_tiny2_ner_pipeline_en_5.5.1_3.0_1737844635223.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("lct_rubert_tiny2_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("lct_rubert_tiny2_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lct_rubert_tiny2_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|109.2 MB|
+
+## References
+
+https://huggingface.co/Ilya-Nazimov/lct-rubert-tiny2-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-learn_hf_food_not_food_text_classifier_distilbert_base_uncased_tanvircr7_en.md b/docs/_posts/ahmedlone127/2025-01-25-learn_hf_food_not_food_text_classifier_distilbert_base_uncased_tanvircr7_en.md
new file mode 100644
index 00000000000000..63d0e5dcd1bcbe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-learn_hf_food_not_food_text_classifier_distilbert_base_uncased_tanvircr7_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English learn_hf_food_not_food_text_classifier_distilbert_base_uncased_tanvircr7 DistilBertForSequenceClassification from tanvircr7
+author: John Snow Labs
+name: learn_hf_food_not_food_text_classifier_distilbert_base_uncased_tanvircr7
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`learn_hf_food_not_food_text_classifier_distilbert_base_uncased_tanvircr7` is a English model originally trained by tanvircr7.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/learn_hf_food_not_food_text_classifier_distilbert_base_uncased_tanvircr7_en_5.5.1_3.0_1737811579687.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/learn_hf_food_not_food_text_classifier_distilbert_base_uncased_tanvircr7_en_5.5.1_3.0_1737811579687.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("learn_hf_food_not_food_text_classifier_distilbert_base_uncased_tanvircr7","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("learn_hf_food_not_food_text_classifier_distilbert_base_uncased_tanvircr7", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|learn_hf_food_not_food_text_classifier_distilbert_base_uncased_tanvircr7|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/tanvircr7/learn_hf_food_not_food_text_classifier-distilbert-base-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-learn_hf_food_not_food_text_classifier_distilbert_base_uncased_tanvircr7_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-learn_hf_food_not_food_text_classifier_distilbert_base_uncased_tanvircr7_pipeline_en.md
new file mode 100644
index 00000000000000..ef59dbed803cce
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-learn_hf_food_not_food_text_classifier_distilbert_base_uncased_tanvircr7_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English learn_hf_food_not_food_text_classifier_distilbert_base_uncased_tanvircr7_pipeline pipeline DistilBertForSequenceClassification from tanvircr7
+author: John Snow Labs
+name: learn_hf_food_not_food_text_classifier_distilbert_base_uncased_tanvircr7_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`learn_hf_food_not_food_text_classifier_distilbert_base_uncased_tanvircr7_pipeline` is a English model originally trained by tanvircr7.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/learn_hf_food_not_food_text_classifier_distilbert_base_uncased_tanvircr7_pipeline_en_5.5.1_3.0_1737811593511.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/learn_hf_food_not_food_text_classifier_distilbert_base_uncased_tanvircr7_pipeline_en_5.5.1_3.0_1737811593511.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("learn_hf_food_not_food_text_classifier_distilbert_base_uncased_tanvircr7_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("learn_hf_food_not_food_text_classifier_distilbert_base_uncased_tanvircr7_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|learn_hf_food_not_food_text_classifier_distilbert_base_uncased_tanvircr7_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/tanvircr7/learn_hf_food_not_food_text_classifier-distilbert-base-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-legal_base_v2_5__checkpoint_2_26000_en.md b/docs/_posts/ahmedlone127/2025-01-25-legal_base_v2_5__checkpoint_2_26000_en.md
new file mode 100644
index 00000000000000..dfb75302bfd25b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-legal_base_v2_5__checkpoint_2_26000_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English legal_base_v2_5__checkpoint_2_26000 RoBertaEmbeddings from eduagarcia-temp
+author: John Snow Labs
+name: legal_base_v2_5__checkpoint_2_26000
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`legal_base_v2_5__checkpoint_2_26000` is a English model originally trained by eduagarcia-temp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/legal_base_v2_5__checkpoint_2_26000_en_5.5.1_3.0_1737797566916.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/legal_base_v2_5__checkpoint_2_26000_en_5.5.1_3.0_1737797566916.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("legal_base_v2_5__checkpoint_2_26000","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("legal_base_v2_5__checkpoint_2_26000","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|legal_base_v2_5__checkpoint_2_26000|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|296.8 MB|
+
+## References
+
+https://huggingface.co/eduagarcia-temp/legal_base-v2_5__checkpoint_2_26000
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-legal_base_v2_5__checkpoint_2_26000_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-legal_base_v2_5__checkpoint_2_26000_pipeline_en.md
new file mode 100644
index 00000000000000..06d1c2f699d26f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-legal_base_v2_5__checkpoint_2_26000_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English legal_base_v2_5__checkpoint_2_26000_pipeline pipeline RoBertaEmbeddings from eduagarcia-temp
+author: John Snow Labs
+name: legal_base_v2_5__checkpoint_2_26000_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`legal_base_v2_5__checkpoint_2_26000_pipeline` is a English model originally trained by eduagarcia-temp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/legal_base_v2_5__checkpoint_2_26000_pipeline_en_5.5.1_3.0_1737797657075.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/legal_base_v2_5__checkpoint_2_26000_pipeline_en_5.5.1_3.0_1737797657075.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("legal_base_v2_5__checkpoint_2_26000_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("legal_base_v2_5__checkpoint_2_26000_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|legal_base_v2_5__checkpoint_2_26000_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|296.8 MB|
+
+## References
+
+https://huggingface.co/eduagarcia-temp/legal_base-v2_5__checkpoint_2_26000
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-len_pruned_50_model_en.md b/docs/_posts/ahmedlone127/2025-01-25-len_pruned_50_model_en.md
new file mode 100644
index 00000000000000..e99cbf8f9f4d11
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-len_pruned_50_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English len_pruned_50_model DistilBertForSequenceClassification from andygoh5
+author: John Snow Labs
+name: len_pruned_50_model
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`len_pruned_50_model` is a English model originally trained by andygoh5.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/len_pruned_50_model_en_5.5.1_3.0_1737822919039.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/len_pruned_50_model_en_5.5.1_3.0_1737822919039.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("len_pruned_50_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("len_pruned_50_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|len_pruned_50_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/andygoh5/len-pruned-50-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-len_pruned_50_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-len_pruned_50_model_pipeline_en.md
new file mode 100644
index 00000000000000..82e4bef1afc52b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-len_pruned_50_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English len_pruned_50_model_pipeline pipeline DistilBertForSequenceClassification from andygoh5
+author: John Snow Labs
+name: len_pruned_50_model_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`len_pruned_50_model_pipeline` is a English model originally trained by andygoh5.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/len_pruned_50_model_pipeline_en_5.5.1_3.0_1737822932072.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/len_pruned_50_model_pipeline_en_5.5.1_3.0_1737822932072.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("len_pruned_50_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("len_pruned_50_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|len_pruned_50_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/andygoh5/len-pruned-50-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-lettuce_sayula_popoluca_german_mono_en.md b/docs/_posts/ahmedlone127/2025-01-25-lettuce_sayula_popoluca_german_mono_en.md
new file mode 100644
index 00000000000000..0dc90b9d5bad93
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-lettuce_sayula_popoluca_german_mono_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English lettuce_sayula_popoluca_german_mono BertForTokenClassification from pranaydeeps
+author: John Snow Labs
+name: lettuce_sayula_popoluca_german_mono
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lettuce_sayula_popoluca_german_mono` is a English model originally trained by pranaydeeps.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lettuce_sayula_popoluca_german_mono_en_5.5.1_3.0_1737844171810.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lettuce_sayula_popoluca_german_mono_en_5.5.1_3.0_1737844171810.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("lettuce_sayula_popoluca_german_mono","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("lettuce_sayula_popoluca_german_mono", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lettuce_sayula_popoluca_german_mono|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|410.0 MB|
+
+## References
+
+https://huggingface.co/pranaydeeps/lettuce_pos_de_mono
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-lettuce_sayula_popoluca_german_mono_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-lettuce_sayula_popoluca_german_mono_pipeline_en.md
new file mode 100644
index 00000000000000..07ef45ec989897
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-lettuce_sayula_popoluca_german_mono_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English lettuce_sayula_popoluca_german_mono_pipeline pipeline BertForTokenClassification from pranaydeeps
+author: John Snow Labs
+name: lettuce_sayula_popoluca_german_mono_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lettuce_sayula_popoluca_german_mono_pipeline` is a English model originally trained by pranaydeeps.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lettuce_sayula_popoluca_german_mono_pipeline_en_5.5.1_3.0_1737844192698.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lettuce_sayula_popoluca_german_mono_pipeline_en_5.5.1_3.0_1737844192698.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("lettuce_sayula_popoluca_german_mono_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("lettuce_sayula_popoluca_german_mono_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lettuce_sayula_popoluca_german_mono_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.1 MB|
+
+## References
+
+https://huggingface.co/pranaydeeps/lettuce_pos_de_mono
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-lettuce_sayula_popoluca_german_xlm_en.md b/docs/_posts/ahmedlone127/2025-01-25-lettuce_sayula_popoluca_german_xlm_en.md
new file mode 100644
index 00000000000000..896e1b829e21d5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-lettuce_sayula_popoluca_german_xlm_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English lettuce_sayula_popoluca_german_xlm XlmRoBertaForTokenClassification from pranaydeeps
+author: John Snow Labs
+name: lettuce_sayula_popoluca_german_xlm
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lettuce_sayula_popoluca_german_xlm` is a English model originally trained by pranaydeeps.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lettuce_sayula_popoluca_german_xlm_en_5.5.1_3.0_1737831938069.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lettuce_sayula_popoluca_german_xlm_en_5.5.1_3.0_1737831938069.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("lettuce_sayula_popoluca_german_xlm","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("lettuce_sayula_popoluca_german_xlm", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lettuce_sayula_popoluca_german_xlm|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|867.4 MB|
+
+## References
+
+https://huggingface.co/pranaydeeps/lettuce_pos_de_xlm
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-lettuce_sayula_popoluca_german_xlm_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-lettuce_sayula_popoluca_german_xlm_pipeline_en.md
new file mode 100644
index 00000000000000..09986f0e2a3fa6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-lettuce_sayula_popoluca_german_xlm_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English lettuce_sayula_popoluca_german_xlm_pipeline pipeline XlmRoBertaForTokenClassification from pranaydeeps
+author: John Snow Labs
+name: lettuce_sayula_popoluca_german_xlm_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lettuce_sayula_popoluca_german_xlm_pipeline` is a English model originally trained by pranaydeeps.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lettuce_sayula_popoluca_german_xlm_pipeline_en_5.5.1_3.0_1737832002374.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lettuce_sayula_popoluca_german_xlm_pipeline_en_5.5.1_3.0_1737832002374.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("lettuce_sayula_popoluca_german_xlm_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("lettuce_sayula_popoluca_german_xlm_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lettuce_sayula_popoluca_german_xlm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|867.4 MB|
+
+## References
+
+https://huggingface.co/pranaydeeps/lettuce_pos_de_xlm
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-logicloom_v1_en.md b/docs/_posts/ahmedlone127/2025-01-25-logicloom_v1_en.md
new file mode 100644
index 00000000000000..7b8b5897cd6e73
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-logicloom_v1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English logicloom_v1 MarianTransformer from williamhackspeare
+author: John Snow Labs
+name: logicloom_v1
+date: 2025-01-25
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`logicloom_v1` is a English model originally trained by williamhackspeare.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/logicloom_v1_en_5.5.1_3.0_1737783070861.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/logicloom_v1_en_5.5.1_3.0_1737783070861.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("logicloom_v1","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("logicloom_v1","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|logicloom_v1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|412.3 MB|
+
+## References
+
+https://huggingface.co/williamhackspeare/LogicLoom-v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-logicloom_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-logicloom_v1_pipeline_en.md
new file mode 100644
index 00000000000000..f8192cd3453321
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-logicloom_v1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English logicloom_v1_pipeline pipeline MarianTransformer from williamhackspeare
+author: John Snow Labs
+name: logicloom_v1_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`logicloom_v1_pipeline` is a English model originally trained by williamhackspeare.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/logicloom_v1_pipeline_en_5.5.1_3.0_1737783092600.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/logicloom_v1_pipeline_en_5.5.1_3.0_1737783092600.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("logicloom_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("logicloom_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|logicloom_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|412.8 MB|
+
+## References
+
+https://huggingface.co/williamhackspeare/LogicLoom-v1
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-lolol_en.md b/docs/_posts/ahmedlone127/2025-01-25-lolol_en.md
new file mode 100644
index 00000000000000..495c30ca7d9917
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-lolol_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English lolol DistilBertForSequenceClassification from andrea9339
+author: John Snow Labs
+name: lolol
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lolol` is a English model originally trained by andrea9339.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lolol_en_5.5.1_3.0_1737836993427.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lolol_en_5.5.1_3.0_1737836993427.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("lolol","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("lolol", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lolol|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/andrea9339/lolol
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-lolol_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-lolol_pipeline_en.md
new file mode 100644
index 00000000000000..5147f6c7d31289
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-lolol_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English lolol_pipeline pipeline DistilBertForSequenceClassification from andrea9339
+author: John Snow Labs
+name: lolol_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lolol_pipeline` is a English model originally trained by andrea9339.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lolol_pipeline_en_5.5.1_3.0_1737837008730.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lolol_pipeline_en_5.5.1_3.0_1737837008730.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("lolol_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("lolol_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lolol_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/andrea9339/lolol
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-longtail_recall_indonesian_roberta_en.md b/docs/_posts/ahmedlone127/2025-01-25-longtail_recall_indonesian_roberta_en.md
new file mode 100644
index 00000000000000..14f3b0fe24ca5b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-longtail_recall_indonesian_roberta_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English longtail_recall_indonesian_roberta XlmRoBertaForSequenceClassification from yzhang0112
+author: John Snow Labs
+name: longtail_recall_indonesian_roberta
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`longtail_recall_indonesian_roberta` is a English model originally trained by yzhang0112.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/longtail_recall_indonesian_roberta_en_5.5.1_3.0_1737816555820.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/longtail_recall_indonesian_roberta_en_5.5.1_3.0_1737816555820.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("longtail_recall_indonesian_roberta","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("longtail_recall_indonesian_roberta", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|longtail_recall_indonesian_roberta|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/yzhang0112/longtail_recall_id_roberta
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-longtail_recall_indonesian_roberta_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-longtail_recall_indonesian_roberta_pipeline_en.md
new file mode 100644
index 00000000000000..28e231aeef4440
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-longtail_recall_indonesian_roberta_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English longtail_recall_indonesian_roberta_pipeline pipeline XlmRoBertaForSequenceClassification from yzhang0112
+author: John Snow Labs
+name: longtail_recall_indonesian_roberta_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`longtail_recall_indonesian_roberta_pipeline` is a English model originally trained by yzhang0112.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/longtail_recall_indonesian_roberta_pipeline_en_5.5.1_3.0_1737816682850.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/longtail_recall_indonesian_roberta_pipeline_en_5.5.1_3.0_1737816682850.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("longtail_recall_indonesian_roberta_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("longtail_recall_indonesian_roberta_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|longtail_recall_indonesian_roberta_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/yzhang0112/longtail_recall_id_roberta
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-m2_bert_128_retrieval_encoder_v1_en.md b/docs/_posts/ahmedlone127/2025-01-25-m2_bert_128_retrieval_encoder_v1_en.md
new file mode 100644
index 00000000000000..1473df6a487891
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-m2_bert_128_retrieval_encoder_v1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English m2_bert_128_retrieval_encoder_v1 BertEmbeddings from hazyresearch
+author: John Snow Labs
+name: m2_bert_128_retrieval_encoder_v1
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`m2_bert_128_retrieval_encoder_v1` is a English model originally trained by hazyresearch.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/m2_bert_128_retrieval_encoder_v1_en_5.5.1_3.0_1737846053126.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/m2_bert_128_retrieval_encoder_v1_en_5.5.1_3.0_1737846053126.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("m2_bert_128_retrieval_encoder_v1","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("m2_bert_128_retrieval_encoder_v1","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|m2_bert_128_retrieval_encoder_v1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|405.6 MB|
+
+## References
+
+https://huggingface.co/hazyresearch/M2-BERT-128-Retrieval-Encoder-V1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-m2_bert_128_retrieval_encoder_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-m2_bert_128_retrieval_encoder_v1_pipeline_en.md
new file mode 100644
index 00000000000000..c4fd72116048cd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-m2_bert_128_retrieval_encoder_v1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English m2_bert_128_retrieval_encoder_v1_pipeline pipeline BertEmbeddings from hazyresearch
+author: John Snow Labs
+name: m2_bert_128_retrieval_encoder_v1_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`m2_bert_128_retrieval_encoder_v1_pipeline` is a English model originally trained by hazyresearch.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/m2_bert_128_retrieval_encoder_v1_pipeline_en_5.5.1_3.0_1737846073682.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/m2_bert_128_retrieval_encoder_v1_pipeline_en_5.5.1_3.0_1737846073682.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("m2_bert_128_retrieval_encoder_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("m2_bert_128_retrieval_encoder_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|m2_bert_128_retrieval_encoder_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|405.6 MB|
+
+## References
+
+https://huggingface.co/hazyresearch/M2-BERT-128-Retrieval-Encoder-V1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-malay_sentiment3_en.md b/docs/_posts/ahmedlone127/2025-01-25-malay_sentiment3_en.md
new file mode 100644
index 00000000000000..e449604e9a0982
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-malay_sentiment3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English malay_sentiment3 XlmRoBertaForSequenceClassification from afiqlol
+author: John Snow Labs
+name: malay_sentiment3
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`malay_sentiment3` is a English model originally trained by afiqlol.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/malay_sentiment3_en_5.5.1_3.0_1737815274562.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/malay_sentiment3_en_5.5.1_3.0_1737815274562.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("malay_sentiment3","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("malay_sentiment3", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|malay_sentiment3|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/afiqlol/Malay-Sentiment3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-malay_sentiment3_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-malay_sentiment3_pipeline_en.md
new file mode 100644
index 00000000000000..71256673aadba4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-malay_sentiment3_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English malay_sentiment3_pipeline pipeline XlmRoBertaForSequenceClassification from afiqlol
+author: John Snow Labs
+name: malay_sentiment3_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`malay_sentiment3_pipeline` is a English model originally trained by afiqlol.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/malay_sentiment3_pipeline_en_5.5.1_3.0_1737815327512.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/malay_sentiment3_pipeline_en_5.5.1_3.0_1737815327512.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("malay_sentiment3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("malay_sentiment3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|malay_sentiment3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/afiqlol/Malay-Sentiment3
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-marianmt_nepali_tonga_tonga_islands_english_synthetic_pretrain_continued_en.md b/docs/_posts/ahmedlone127/2025-01-25-marianmt_nepali_tonga_tonga_islands_english_synthetic_pretrain_continued_en.md
new file mode 100644
index 00000000000000..3266ce8027c465
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-marianmt_nepali_tonga_tonga_islands_english_synthetic_pretrain_continued_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English marianmt_nepali_tonga_tonga_islands_english_synthetic_pretrain_continued MarianTransformer from iamTangsang
+author: John Snow Labs
+name: marianmt_nepali_tonga_tonga_islands_english_synthetic_pretrain_continued
+date: 2025-01-25
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marianmt_nepali_tonga_tonga_islands_english_synthetic_pretrain_continued` is a English model originally trained by iamTangsang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marianmt_nepali_tonga_tonga_islands_english_synthetic_pretrain_continued_en_5.5.1_3.0_1737828130230.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marianmt_nepali_tonga_tonga_islands_english_synthetic_pretrain_continued_en_5.5.1_3.0_1737828130230.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("marianmt_nepali_tonga_tonga_islands_english_synthetic_pretrain_continued","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("marianmt_nepali_tonga_tonga_islands_english_synthetic_pretrain_continued","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marianmt_nepali_tonga_tonga_islands_english_synthetic_pretrain_continued|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|414.5 MB|
+
+## References
+
+https://huggingface.co/iamTangsang/MarianMT-Nepali-to-English-Synthetic-Pretrain-Continued
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-marianmt_nepali_tonga_tonga_islands_english_synthetic_pretrain_continued_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-marianmt_nepali_tonga_tonga_islands_english_synthetic_pretrain_continued_pipeline_en.md
new file mode 100644
index 00000000000000..989a68f1a287ea
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-marianmt_nepali_tonga_tonga_islands_english_synthetic_pretrain_continued_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English marianmt_nepali_tonga_tonga_islands_english_synthetic_pretrain_continued_pipeline pipeline MarianTransformer from iamTangsang
+author: John Snow Labs
+name: marianmt_nepali_tonga_tonga_islands_english_synthetic_pretrain_continued_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marianmt_nepali_tonga_tonga_islands_english_synthetic_pretrain_continued_pipeline` is a English model originally trained by iamTangsang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marianmt_nepali_tonga_tonga_islands_english_synthetic_pretrain_continued_pipeline_en_5.5.1_3.0_1737828150991.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marianmt_nepali_tonga_tonga_islands_english_synthetic_pretrain_continued_pipeline_en_5.5.1_3.0_1737828150991.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("marianmt_nepali_tonga_tonga_islands_english_synthetic_pretrain_continued_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("marianmt_nepali_tonga_tonga_islands_english_synthetic_pretrain_continued_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marianmt_nepali_tonga_tonga_islands_english_synthetic_pretrain_continued_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|415.0 MB|
+
+## References
+
+https://huggingface.co/iamTangsang/MarianMT-Nepali-to-English-Synthetic-Pretrain-Continued
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-mario_gpt2_700_context_length_en.md b/docs/_posts/ahmedlone127/2025-01-25-mario_gpt2_700_context_length_en.md
new file mode 100644
index 00000000000000..927865eb281612
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-mario_gpt2_700_context_length_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mario_gpt2_700_context_length GPT2Transformer from shyamsn97
+author: John Snow Labs
+name: mario_gpt2_700_context_length
+date: 2025-01-25
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mario_gpt2_700_context_length` is a English model originally trained by shyamsn97.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mario_gpt2_700_context_length_en_5.5.1_3.0_1737766439417.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mario_gpt2_700_context_length_en_5.5.1_3.0_1737766439417.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("mario_gpt2_700_context_length","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("mario_gpt2_700_context_length","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mario_gpt2_700_context_length|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|307.2 MB|
+
+## References
+
+https://huggingface.co/shyamsn97/Mario-GPT2-700-context-length
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-mario_gpt2_700_context_length_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-mario_gpt2_700_context_length_pipeline_en.md
new file mode 100644
index 00000000000000..e9ab91fdac0748
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-mario_gpt2_700_context_length_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mario_gpt2_700_context_length_pipeline pipeline GPT2Transformer from shyamsn97
+author: John Snow Labs
+name: mario_gpt2_700_context_length_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mario_gpt2_700_context_length_pipeline` is a English model originally trained by shyamsn97.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mario_gpt2_700_context_length_pipeline_en_5.5.1_3.0_1737766455800.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mario_gpt2_700_context_length_pipeline_en_5.5.1_3.0_1737766455800.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mario_gpt2_700_context_length_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mario_gpt2_700_context_length_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mario_gpt2_700_context_length_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|307.3 MB|
+
+## References
+
+https://huggingface.co/shyamsn97/Mario-GPT2-700-context-length
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-max_pruned_30_model_en.md b/docs/_posts/ahmedlone127/2025-01-25-max_pruned_30_model_en.md
new file mode 100644
index 00000000000000..ce963e18ec7d53
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-max_pruned_30_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English max_pruned_30_model DistilBertForSequenceClassification from andygoh5
+author: John Snow Labs
+name: max_pruned_30_model
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`max_pruned_30_model` is a English model originally trained by andygoh5.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/max_pruned_30_model_en_5.5.1_3.0_1737822758021.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/max_pruned_30_model_en_5.5.1_3.0_1737822758021.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("max_pruned_30_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("max_pruned_30_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|max_pruned_30_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/andygoh5/max-pruned-30-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-max_pruned_30_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-max_pruned_30_model_pipeline_en.md
new file mode 100644
index 00000000000000..402cd35fe2b194
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-max_pruned_30_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English max_pruned_30_model_pipeline pipeline DistilBertForSequenceClassification from andygoh5
+author: John Snow Labs
+name: max_pruned_30_model_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`max_pruned_30_model_pipeline` is a English model originally trained by andygoh5.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/max_pruned_30_model_pipeline_en_5.5.1_3.0_1737822771680.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/max_pruned_30_model_pipeline_en_5.5.1_3.0_1737822771680.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("max_pruned_30_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("max_pruned_30_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|max_pruned_30_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/andygoh5/max-pruned-30-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-mdeberta_v3_base_autext2024_09_12_2024_detection_en.md b/docs/_posts/ahmedlone127/2025-01-25-mdeberta_v3_base_autext2024_09_12_2024_detection_en.md
new file mode 100644
index 00000000000000..5e8d158cd56a37
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-mdeberta_v3_base_autext2024_09_12_2024_detection_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mdeberta_v3_base_autext2024_09_12_2024_detection DeBertaForSequenceClassification from ISEGURA
+author: John Snow Labs
+name: mdeberta_v3_base_autext2024_09_12_2024_detection
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_autext2024_09_12_2024_detection` is a English model originally trained by ISEGURA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_autext2024_09_12_2024_detection_en_5.5.1_3.0_1737820067531.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_autext2024_09_12_2024_detection_en_5.5.1_3.0_1737820067531.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_autext2024_09_12_2024_detection","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_autext2024_09_12_2024_detection", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_autext2024_09_12_2024_detection|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|871.1 MB|
+
+## References
+
+https://huggingface.co/ISEGURA/mdeberta-v3-base-autext2024_09-12-2024_detection
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-mdeberta_v3_base_autext2024_09_12_2024_detection_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-mdeberta_v3_base_autext2024_09_12_2024_detection_pipeline_en.md
new file mode 100644
index 00000000000000..e7fa2e8c6f7a7d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-mdeberta_v3_base_autext2024_09_12_2024_detection_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mdeberta_v3_base_autext2024_09_12_2024_detection_pipeline pipeline DeBertaForSequenceClassification from ISEGURA
+author: John Snow Labs
+name: mdeberta_v3_base_autext2024_09_12_2024_detection_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_autext2024_09_12_2024_detection_pipeline` is a English model originally trained by ISEGURA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_autext2024_09_12_2024_detection_pipeline_en_5.5.1_3.0_1737820183903.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_autext2024_09_12_2024_detection_pipeline_en_5.5.1_3.0_1737820183903.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mdeberta_v3_base_autext2024_09_12_2024_detection_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mdeberta_v3_base_autext2024_09_12_2024_detection_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_autext2024_09_12_2024_detection_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|871.2 MB|
+
+## References
+
+https://huggingface.co/ISEGURA/mdeberta-v3-base-autext2024_09-12-2024_detection
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-med_model_1_en.md b/docs/_posts/ahmedlone127/2025-01-25-med_model_1_en.md
new file mode 100644
index 00000000000000..9eef188f9d8334
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-med_model_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English med_model_1 BertEmbeddings from kumarme072
+author: John Snow Labs
+name: med_model_1
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`med_model_1` is a English model originally trained by kumarme072.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/med_model_1_en_5.5.1_3.0_1737774853153.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/med_model_1_en_5.5.1_3.0_1737774853153.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("med_model_1","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("med_model_1","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|med_model_1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|486.3 MB|
+
+## References
+
+https://huggingface.co/kumarme072/med_model_1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-med_model_1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-med_model_1_pipeline_en.md
new file mode 100644
index 00000000000000..237e69971b3c48
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-med_model_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English med_model_1_pipeline pipeline BertEmbeddings from kumarme072
+author: John Snow Labs
+name: med_model_1_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`med_model_1_pipeline` is a English model originally trained by kumarme072.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/med_model_1_pipeline_en_5.5.1_3.0_1737774881590.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/med_model_1_pipeline_en_5.5.1_3.0_1737774881590.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("med_model_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("med_model_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|med_model_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|486.3 MB|
+
+## References
+
+https://huggingface.co/kumarme072/med_model_1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-medbert_base_en.md b/docs/_posts/ahmedlone127/2025-01-25-medbert_base_en.md
new file mode 100644
index 00000000000000..900ef212b99441
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-medbert_base_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English medbert_base BertEmbeddings from suayptalha
+author: John Snow Labs
+name: medbert_base
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`medbert_base` is a English model originally trained by suayptalha.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/medbert_base_en_5.5.1_3.0_1737775032597.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/medbert_base_en_5.5.1_3.0_1737775032597.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("medbert_base","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("medbert_base","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|medbert_base|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/suayptalha/medBERT-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-medbert_base_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-medbert_base_pipeline_en.md
new file mode 100644
index 00000000000000..ebd0a41a6adbf6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-medbert_base_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English medbert_base_pipeline pipeline BertEmbeddings from suayptalha
+author: John Snow Labs
+name: medbert_base_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`medbert_base_pipeline` is a English model originally trained by suayptalha.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/medbert_base_pipeline_en_5.5.1_3.0_1737775053662.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/medbert_base_pipeline_en_5.5.1_3.0_1737775053662.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("medbert_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("medbert_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|medbert_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/suayptalha/medBERT-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-mela_twi_sentiment_model_en.md b/docs/_posts/ahmedlone127/2025-01-25-mela_twi_sentiment_model_en.md
new file mode 100644
index 00000000000000..f085fadb96b558
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-mela_twi_sentiment_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mela_twi_sentiment_model DistilBertForSequenceClassification from melabelen
+author: John Snow Labs
+name: mela_twi_sentiment_model
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mela_twi_sentiment_model` is a English model originally trained by melabelen.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mela_twi_sentiment_model_en_5.5.1_3.0_1737838322787.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mela_twi_sentiment_model_en_5.5.1_3.0_1737838322787.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("mela_twi_sentiment_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("mela_twi_sentiment_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mela_twi_sentiment_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/melabelen/mela-tw-sentiment-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-mela_twi_sentiment_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-mela_twi_sentiment_model_pipeline_en.md
new file mode 100644
index 00000000000000..3af6421e1e1cc6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-mela_twi_sentiment_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mela_twi_sentiment_model_pipeline pipeline DistilBertForSequenceClassification from melabelen
+author: John Snow Labs
+name: mela_twi_sentiment_model_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mela_twi_sentiment_model_pipeline` is a English model originally trained by melabelen.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mela_twi_sentiment_model_pipeline_en_5.5.1_3.0_1737838337088.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mela_twi_sentiment_model_pipeline_en_5.5.1_3.0_1737838337088.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mela_twi_sentiment_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mela_twi_sentiment_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mela_twi_sentiment_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/melabelen/mela-tw-sentiment-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-merged_bert_sst2_model_lora_en.md b/docs/_posts/ahmedlone127/2025-01-25-merged_bert_sst2_model_lora_en.md
new file mode 100644
index 00000000000000..d4055109cc9d9d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-merged_bert_sst2_model_lora_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English merged_bert_sst2_model_lora BertForSequenceClassification from asm3515
+author: John Snow Labs
+name: merged_bert_sst2_model_lora
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`merged_bert_sst2_model_lora` is a English model originally trained by asm3515.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/merged_bert_sst2_model_lora_en_5.5.1_3.0_1737800298366.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/merged_bert_sst2_model_lora_en_5.5.1_3.0_1737800298366.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("merged_bert_sst2_model_lora","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("merged_bert_sst2_model_lora", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|merged_bert_sst2_model_lora|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/asm3515/merged-bert-sst2-model-lora
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-merged_bert_sst2_model_lora_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-merged_bert_sst2_model_lora_pipeline_en.md
new file mode 100644
index 00000000000000..24de95521774fd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-merged_bert_sst2_model_lora_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English merged_bert_sst2_model_lora_pipeline pipeline BertForSequenceClassification from asm3515
+author: John Snow Labs
+name: merged_bert_sst2_model_lora_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`merged_bert_sst2_model_lora_pipeline` is a English model originally trained by asm3515.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/merged_bert_sst2_model_lora_pipeline_en_5.5.1_3.0_1737800322917.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/merged_bert_sst2_model_lora_pipeline_en_5.5.1_3.0_1737800322917.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("merged_bert_sst2_model_lora_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("merged_bert_sst2_model_lora_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|merged_bert_sst2_model_lora_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/asm3515/merged-bert-sst2-model-lora
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-mergedistill_kmt_italian_en.md b/docs/_posts/ahmedlone127/2025-01-25-mergedistill_kmt_italian_en.md
new file mode 100644
index 00000000000000..eeb6ef06eca294
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-mergedistill_kmt_italian_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mergedistill_kmt_italian BertEmbeddings from amitness
+author: John Snow Labs
+name: mergedistill_kmt_italian
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mergedistill_kmt_italian` is a English model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mergedistill_kmt_italian_en_5.5.1_3.0_1737784871573.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mergedistill_kmt_italian_en_5.5.1_3.0_1737784871573.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("mergedistill_kmt_italian","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("mergedistill_kmt_italian","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mergedistill_kmt_italian|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|538.7 MB|
+
+## References
+
+https://huggingface.co/amitness/mergedistill-kmt-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-mergedistill_kmt_italian_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-mergedistill_kmt_italian_pipeline_en.md
new file mode 100644
index 00000000000000..ac3591249f9e7f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-mergedistill_kmt_italian_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mergedistill_kmt_italian_pipeline pipeline BertEmbeddings from amitness
+author: John Snow Labs
+name: mergedistill_kmt_italian_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mergedistill_kmt_italian_pipeline` is a English model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mergedistill_kmt_italian_pipeline_en_5.5.1_3.0_1737784902333.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mergedistill_kmt_italian_pipeline_en_5.5.1_3.0_1737784902333.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mergedistill_kmt_italian_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mergedistill_kmt_italian_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mergedistill_kmt_italian_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|538.7 MB|
+
+## References
+
+https://huggingface.co/amitness/mergedistill-kmt-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-mergedistill_maltese_128_norwegian_distill_v2_en.md b/docs/_posts/ahmedlone127/2025-01-25-mergedistill_maltese_128_norwegian_distill_v2_en.md
new file mode 100644
index 00000000000000..ad58e007dcef59
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-mergedistill_maltese_128_norwegian_distill_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mergedistill_maltese_128_norwegian_distill_v2 BertEmbeddings from amitness
+author: John Snow Labs
+name: mergedistill_maltese_128_norwegian_distill_v2
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mergedistill_maltese_128_norwegian_distill_v2` is a English model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_128_norwegian_distill_v2_en_5.5.1_3.0_1737775108466.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_128_norwegian_distill_v2_en_5.5.1_3.0_1737775108466.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("mergedistill_maltese_128_norwegian_distill_v2","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("mergedistill_maltese_128_norwegian_distill_v2","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mergedistill_maltese_128_norwegian_distill_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|470.4 MB|
+
+## References
+
+https://huggingface.co/amitness/mergedistill-mt-128-no-distill-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-mergedistill_maltese_128_norwegian_distill_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-mergedistill_maltese_128_norwegian_distill_v2_pipeline_en.md
new file mode 100644
index 00000000000000..890a2500bc3d39
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-mergedistill_maltese_128_norwegian_distill_v2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mergedistill_maltese_128_norwegian_distill_v2_pipeline pipeline BertEmbeddings from amitness
+author: John Snow Labs
+name: mergedistill_maltese_128_norwegian_distill_v2_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mergedistill_maltese_128_norwegian_distill_v2_pipeline` is a English model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_128_norwegian_distill_v2_pipeline_en_5.5.1_3.0_1737775132992.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_128_norwegian_distill_v2_pipeline_en_5.5.1_3.0_1737775132992.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mergedistill_maltese_128_norwegian_distill_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mergedistill_maltese_128_norwegian_distill_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mergedistill_maltese_128_norwegian_distill_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|470.4 MB|
+
+## References
+
+https://huggingface.co/amitness/mergedistill-mt-128-no-distill-v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-mergedistill_maltese_128_v2_en.md b/docs/_posts/ahmedlone127/2025-01-25-mergedistill_maltese_128_v2_en.md
new file mode 100644
index 00000000000000..525079ea1598fb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-mergedistill_maltese_128_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mergedistill_maltese_128_v2 BertEmbeddings from amitness
+author: John Snow Labs
+name: mergedistill_maltese_128_v2
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mergedistill_maltese_128_v2` is a English model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_128_v2_en_5.5.1_3.0_1737785030333.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_128_v2_en_5.5.1_3.0_1737785030333.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("mergedistill_maltese_128_v2","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("mergedistill_maltese_128_v2","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mergedistill_maltese_128_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|470.4 MB|
+
+## References
+
+https://huggingface.co/amitness/mergedistill-mt-128-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-mergedistill_maltese_128_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-mergedistill_maltese_128_v2_pipeline_en.md
new file mode 100644
index 00000000000000..81de560820cae7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-mergedistill_maltese_128_v2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mergedistill_maltese_128_v2_pipeline pipeline BertEmbeddings from amitness
+author: John Snow Labs
+name: mergedistill_maltese_128_v2_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mergedistill_maltese_128_v2_pipeline` is a English model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_128_v2_pipeline_en_5.5.1_3.0_1737785055152.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_128_v2_pipeline_en_5.5.1_3.0_1737785055152.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mergedistill_maltese_128_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mergedistill_maltese_128_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mergedistill_maltese_128_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|470.4 MB|
+
+## References
+
+https://huggingface.co/amitness/mergedistill-mt-128-v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-mergedistill_maltese_arabic_512_v2_en.md b/docs/_posts/ahmedlone127/2025-01-25-mergedistill_maltese_arabic_512_v2_en.md
new file mode 100644
index 00000000000000..df3a77e2543674
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-mergedistill_maltese_arabic_512_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mergedistill_maltese_arabic_512_v2 BertEmbeddings from amitness
+author: John Snow Labs
+name: mergedistill_maltese_arabic_512_v2
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mergedistill_maltese_arabic_512_v2` is a English model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_arabic_512_v2_en_5.5.1_3.0_1737821234492.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_arabic_512_v2_en_5.5.1_3.0_1737821234492.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("mergedistill_maltese_arabic_512_v2","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("mergedistill_maltese_arabic_512_v2","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mergedistill_maltese_arabic_512_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|646.9 MB|
+
+## References
+
+https://huggingface.co/amitness/mergedistill-mt-ar-512-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-mergedistill_maltese_arabic_512_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-mergedistill_maltese_arabic_512_v2_pipeline_en.md
new file mode 100644
index 00000000000000..0fc70376884062
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-mergedistill_maltese_arabic_512_v2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mergedistill_maltese_arabic_512_v2_pipeline pipeline BertEmbeddings from amitness
+author: John Snow Labs
+name: mergedistill_maltese_arabic_512_v2_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mergedistill_maltese_arabic_512_v2_pipeline` is a English model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_arabic_512_v2_pipeline_en_5.5.1_3.0_1737821271379.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_arabic_512_v2_pipeline_en_5.5.1_3.0_1737821271379.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mergedistill_maltese_arabic_512_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mergedistill_maltese_arabic_512_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mergedistill_maltese_arabic_512_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|646.9 MB|
+
+## References
+
+https://huggingface.co/amitness/mergedistill-mt-ar-512-v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-mergedistill_maltese_english_512_v2_en.md b/docs/_posts/ahmedlone127/2025-01-25-mergedistill_maltese_english_512_v2_en.md
new file mode 100644
index 00000000000000..2bd294b61b7d6f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-mergedistill_maltese_english_512_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mergedistill_maltese_english_512_v2 BertEmbeddings from amitness
+author: John Snow Labs
+name: mergedistill_maltese_english_512_v2
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mergedistill_maltese_english_512_v2` is a English model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_english_512_v2_en_5.5.1_3.0_1737784978077.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_english_512_v2_en_5.5.1_3.0_1737784978077.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("mergedistill_maltese_english_512_v2","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("mergedistill_maltese_english_512_v2","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mergedistill_maltese_english_512_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|532.5 MB|
+
+## References
+
+https://huggingface.co/amitness/mergedistill-mt-en-512-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-mergedistill_maltese_english_512_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-mergedistill_maltese_english_512_v2_pipeline_en.md
new file mode 100644
index 00000000000000..fb3023ab18ac49
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-mergedistill_maltese_english_512_v2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mergedistill_maltese_english_512_v2_pipeline pipeline BertEmbeddings from amitness
+author: John Snow Labs
+name: mergedistill_maltese_english_512_v2_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mergedistill_maltese_english_512_v2_pipeline` is a English model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_english_512_v2_pipeline_en_5.5.1_3.0_1737785006997.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_english_512_v2_pipeline_en_5.5.1_3.0_1737785006997.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mergedistill_maltese_english_512_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mergedistill_maltese_english_512_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mergedistill_maltese_english_512_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|532.6 MB|
+
+## References
+
+https://huggingface.co/amitness/mergedistill-mt-en-512-v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-mergedistill_maltese_italian_arabic_512_en.md b/docs/_posts/ahmedlone127/2025-01-25-mergedistill_maltese_italian_arabic_512_en.md
new file mode 100644
index 00000000000000..b27ee42f8e13a6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-mergedistill_maltese_italian_arabic_512_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mergedistill_maltese_italian_arabic_512 BertEmbeddings from amitness
+author: John Snow Labs
+name: mergedistill_maltese_italian_arabic_512
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mergedistill_maltese_italian_arabic_512` is a English model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_italian_arabic_512_en_5.5.1_3.0_1737821491950.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_italian_arabic_512_en_5.5.1_3.0_1737821491950.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("mergedistill_maltese_italian_arabic_512","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("mergedistill_maltese_italian_arabic_512","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mergedistill_maltese_italian_arabic_512|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|714.5 MB|
+
+## References
+
+https://huggingface.co/amitness/mergedistill-mt-it-ar-512
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-mergedistill_maltese_italian_arabic_512_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-mergedistill_maltese_italian_arabic_512_pipeline_en.md
new file mode 100644
index 00000000000000..9fc263ca39cde2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-mergedistill_maltese_italian_arabic_512_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mergedistill_maltese_italian_arabic_512_pipeline pipeline BertEmbeddings from amitness
+author: John Snow Labs
+name: mergedistill_maltese_italian_arabic_512_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mergedistill_maltese_italian_arabic_512_pipeline` is a English model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_italian_arabic_512_pipeline_en_5.5.1_3.0_1737821528863.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_italian_arabic_512_pipeline_en_5.5.1_3.0_1737821528863.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mergedistill_maltese_italian_arabic_512_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mergedistill_maltese_italian_arabic_512_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mergedistill_maltese_italian_arabic_512_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|714.5 MB|
+
+## References
+
+https://huggingface.co/amitness/mergedistill-mt-it-ar-512
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-minilm_uncased_squad2_covidqa_en.md b/docs/_posts/ahmedlone127/2025-01-25-minilm_uncased_squad2_covidqa_en.md
new file mode 100644
index 00000000000000..976340e0647274
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-minilm_uncased_squad2_covidqa_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English minilm_uncased_squad2_covidqa BertForQuestionAnswering from Frizio
+author: John Snow Labs
+name: minilm_uncased_squad2_covidqa
+date: 2025-01-25
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`minilm_uncased_squad2_covidqa` is a English model originally trained by Frizio.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/minilm_uncased_squad2_covidqa_en_5.5.1_3.0_1737812957845.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/minilm_uncased_squad2_covidqa_en_5.5.1_3.0_1737812957845.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("minilm_uncased_squad2_covidqa","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("minilm_uncased_squad2_covidqa", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|minilm_uncased_squad2_covidqa|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|123.8 MB|
+
+## References
+
+https://huggingface.co/Frizio/minilm-uncased-squad2-covidqa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-minilm_uncased_squad2_covidqa_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-minilm_uncased_squad2_covidqa_pipeline_en.md
new file mode 100644
index 00000000000000..f763fa73367d1c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-minilm_uncased_squad2_covidqa_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English minilm_uncased_squad2_covidqa_pipeline pipeline BertForQuestionAnswering from Frizio
+author: John Snow Labs
+name: minilm_uncased_squad2_covidqa_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`minilm_uncased_squad2_covidqa_pipeline` is a English model originally trained by Frizio.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/minilm_uncased_squad2_covidqa_pipeline_en_5.5.1_3.0_1737812963957.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/minilm_uncased_squad2_covidqa_pipeline_en_5.5.1_3.0_1737812963957.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("minilm_uncased_squad2_covidqa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("minilm_uncased_squad2_covidqa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|minilm_uncased_squad2_covidqa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|123.8 MB|
+
+## References
+
+https://huggingface.co/Frizio/minilm-uncased-squad2-covidqa
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-mlm_finetunedmodel_en.md b/docs/_posts/ahmedlone127/2025-01-25-mlm_finetunedmodel_en.md
new file mode 100644
index 00000000000000..7cc8e356be6e6a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-mlm_finetunedmodel_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mlm_finetunedmodel RoBertaEmbeddings from shradha01
+author: John Snow Labs
+name: mlm_finetunedmodel
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mlm_finetunedmodel` is a English model originally trained by shradha01.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mlm_finetunedmodel_en_5.5.1_3.0_1737796978682.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mlm_finetunedmodel_en_5.5.1_3.0_1737796978682.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("mlm_finetunedmodel","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("mlm_finetunedmodel","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mlm_finetunedmodel|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|466.1 MB|
+
+## References
+
+https://huggingface.co/shradha01/MLM_FinetunedModel
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-mlm_finetunedmodel_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-mlm_finetunedmodel_pipeline_en.md
new file mode 100644
index 00000000000000..071b1e4f230c2e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-mlm_finetunedmodel_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mlm_finetunedmodel_pipeline pipeline RoBertaEmbeddings from shradha01
+author: John Snow Labs
+name: mlm_finetunedmodel_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mlm_finetunedmodel_pipeline` is a English model originally trained by shradha01.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mlm_finetunedmodel_pipeline_en_5.5.1_3.0_1737797003245.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mlm_finetunedmodel_pipeline_en_5.5.1_3.0_1737797003245.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mlm_finetunedmodel_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mlm_finetunedmodel_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mlm_finetunedmodel_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.1 MB|
+
+## References
+
+https://huggingface.co/shradha01/MLM_FinetunedModel
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-modalverbstologic2_en.md b/docs/_posts/ahmedlone127/2025-01-25-modalverbstologic2_en.md
new file mode 100644
index 00000000000000..6b42ca7260f161
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-modalverbstologic2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English modalverbstologic2 XlmRoBertaForSequenceClassification from Anjalis404
+author: John Snow Labs
+name: modalverbstologic2
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`modalverbstologic2` is a English model originally trained by Anjalis404.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/modalverbstologic2_en_5.5.1_3.0_1737816328333.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/modalverbstologic2_en_5.5.1_3.0_1737816328333.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("modalverbstologic2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("modalverbstologic2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|modalverbstologic2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|796.2 MB|
+
+## References
+
+https://huggingface.co/Anjalis404/ModalVerbsToLogic2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-modalverbstologic2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-modalverbstologic2_pipeline_en.md
new file mode 100644
index 00000000000000..8c497af21bf5cf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-modalverbstologic2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English modalverbstologic2_pipeline pipeline XlmRoBertaForSequenceClassification from Anjalis404
+author: John Snow Labs
+name: modalverbstologic2_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`modalverbstologic2_pipeline` is a English model originally trained by Anjalis404.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/modalverbstologic2_pipeline_en_5.5.1_3.0_1737816459488.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/modalverbstologic2_pipeline_en_5.5.1_3.0_1737816459488.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("modalverbstologic2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("modalverbstologic2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|modalverbstologic2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|796.2 MB|
+
+## References
+
+https://huggingface.co/Anjalis404/ModalVerbsToLogic2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-model_ak729_en.md b/docs/_posts/ahmedlone127/2025-01-25-model_ak729_en.md
new file mode 100644
index 00000000000000..7b051c7d9a43b6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-model_ak729_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English model_ak729 BertEmbeddings from Ak729
+author: John Snow Labs
+name: model_ak729
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_ak729` is a English model originally trained by Ak729.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_ak729_en_5.5.1_3.0_1737846505870.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_ak729_en_5.5.1_3.0_1737846505870.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("model_ak729","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("model_ak729","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|model_ak729|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/Ak729/Model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-model_ak729_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-model_ak729_pipeline_en.md
new file mode 100644
index 00000000000000..8e8fab3f4f875b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-model_ak729_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English model_ak729_pipeline pipeline BertEmbeddings from Ak729
+author: John Snow Labs
+name: model_ak729_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_ak729_pipeline` is a English model originally trained by Ak729.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_ak729_pipeline_en_5.5.1_3.0_1737846527144.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_ak729_pipeline_en_5.5.1_3.0_1737846527144.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("model_ak729_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("model_ak729_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|model_ak729_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/Ak729/Model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-model_en.md b/docs/_posts/ahmedlone127/2025-01-25-model_en.md
new file mode 100644
index 00000000000000..e9e13c979c0495
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-model_en.md
@@ -0,0 +1,96 @@
+---
+layout: model
+title: English model DistilBertEmbeddings from Dinithi
+author: John Snow Labs
+name: model
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model` is a English model originally trained by Dinithi.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_en_5.5.1_3.0_1737813642178.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_en_5.5.1_3.0_1737813642178.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("model","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("model","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|411.7 MB|
+
+## References
+
+References
+
+https://huggingface.co/Dinithi/Model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-model_med_195_e_en.md b/docs/_posts/ahmedlone127/2025-01-25-model_med_195_e_en.md
new file mode 100644
index 00000000000000..095c20a51ca749
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-model_med_195_e_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English model_med_195_e BertEmbeddings from kumarme072
+author: John Snow Labs
+name: model_med_195_e
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_med_195_e` is a English model originally trained by kumarme072.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_med_195_e_en_5.5.1_3.0_1737774351288.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_med_195_e_en_5.5.1_3.0_1737774351288.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("model_med_195_e","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("model_med_195_e","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|model_med_195_e|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|486.4 MB|
+
+## References
+
+https://huggingface.co/kumarme072/model_med_195_E
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-model_med_195_e_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-model_med_195_e_pipeline_en.md
new file mode 100644
index 00000000000000..856a78ca585779
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-model_med_195_e_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English model_med_195_e_pipeline pipeline BertEmbeddings from kumarme072
+author: John Snow Labs
+name: model_med_195_e_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_med_195_e_pipeline` is a English model originally trained by kumarme072.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_med_195_e_pipeline_en_5.5.1_3.0_1737774379657.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_med_195_e_pipeline_en_5.5.1_3.0_1737774379657.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("model_med_195_e_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("model_med_195_e_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|model_med_195_e_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|486.4 MB|
+
+## References
+
+https://huggingface.co/kumarme072/model_med_195_E
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-model_pipeline_en.md
new file mode 100644
index 00000000000000..5c784e6c17951d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-model_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English model_pipeline pipeline DistilBertEmbeddings from Dinithi
+author: John Snow Labs
+name: model_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_pipeline` is a English model originally trained by Dinithi.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_pipeline_en_5.5.1_3.0_1737813663939.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_pipeline_en_5.5.1_3.0_1737813663939.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|411.7 MB|
+
+## References
+
+References
+
+https://huggingface.co/Dinithi/Model
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-movie_sentiment_analysis_krishnamishra8848_en.md b/docs/_posts/ahmedlone127/2025-01-25-movie_sentiment_analysis_krishnamishra8848_en.md
new file mode 100644
index 00000000000000..8fa541f97f7adf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-movie_sentiment_analysis_krishnamishra8848_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English movie_sentiment_analysis_krishnamishra8848 DistilBertForSequenceClassification from krishnamishra8848
+author: John Snow Labs
+name: movie_sentiment_analysis_krishnamishra8848
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`movie_sentiment_analysis_krishnamishra8848` is a English model originally trained by krishnamishra8848.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/movie_sentiment_analysis_krishnamishra8848_en_5.5.1_3.0_1737812169886.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/movie_sentiment_analysis_krishnamishra8848_en_5.5.1_3.0_1737812169886.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("movie_sentiment_analysis_krishnamishra8848","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("movie_sentiment_analysis_krishnamishra8848", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|movie_sentiment_analysis_krishnamishra8848|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/krishnamishra8848/movie_sentiment_analysis
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-movie_sentiment_analysis_krishnamishra8848_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-movie_sentiment_analysis_krishnamishra8848_pipeline_en.md
new file mode 100644
index 00000000000000..4d6fd6731dbaa6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-movie_sentiment_analysis_krishnamishra8848_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English movie_sentiment_analysis_krishnamishra8848_pipeline pipeline DistilBertForSequenceClassification from krishnamishra8848
+author: John Snow Labs
+name: movie_sentiment_analysis_krishnamishra8848_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`movie_sentiment_analysis_krishnamishra8848_pipeline` is a English model originally trained by krishnamishra8848.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/movie_sentiment_analysis_krishnamishra8848_pipeline_en_5.5.1_3.0_1737812182868.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/movie_sentiment_analysis_krishnamishra8848_pipeline_en_5.5.1_3.0_1737812182868.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("movie_sentiment_analysis_krishnamishra8848_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("movie_sentiment_analysis_krishnamishra8848_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|movie_sentiment_analysis_krishnamishra8848_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/krishnamishra8848/movie_sentiment_analysis
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-mt5_base_english_thai_sch_wiki_thai_spider_en.md b/docs/_posts/ahmedlone127/2025-01-25-mt5_base_english_thai_sch_wiki_thai_spider_en.md
new file mode 100644
index 00000000000000..d07a4770fab619
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-mt5_base_english_thai_sch_wiki_thai_spider_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mt5_base_english_thai_sch_wiki_thai_spider T5Transformer from e22vvb
+author: John Snow Labs
+name: mt5_base_english_thai_sch_wiki_thai_spider
+date: 2025-01-25
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_base_english_thai_sch_wiki_thai_spider` is a English model originally trained by e22vvb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_base_english_thai_sch_wiki_thai_spider_en_5.5.1_3.0_1737849349798.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_base_english_thai_sch_wiki_thai_spider_en_5.5.1_3.0_1737849349798.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("mt5_base_english_thai_sch_wiki_thai_spider","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("mt5_base_english_thai_sch_wiki_thai_spider", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_base_english_thai_sch_wiki_thai_spider|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/e22vvb/mt5-base_EN_TH_sch_wiki_TH_spider
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-multilingual_xlm_roberta_for_ner_cz_score_pipeline_xx.md b/docs/_posts/ahmedlone127/2025-01-25-multilingual_xlm_roberta_for_ner_cz_score_pipeline_xx.md
new file mode 100644
index 00000000000000..8e2f33ea6c83fe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-multilingual_xlm_roberta_for_ner_cz_score_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual multilingual_xlm_roberta_for_ner_cz_score_pipeline pipeline XlmRoBertaForTokenClassification from cz-score
+author: John Snow Labs
+name: multilingual_xlm_roberta_for_ner_cz_score_pipeline
+date: 2025-01-25
+tags: [xx, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multilingual_xlm_roberta_for_ner_cz_score_pipeline` is a Multilingual model originally trained by cz-score.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multilingual_xlm_roberta_for_ner_cz_score_pipeline_xx_5.5.1_3.0_1737833647693.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multilingual_xlm_roberta_for_ner_cz_score_pipeline_xx_5.5.1_3.0_1737833647693.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("multilingual_xlm_roberta_for_ner_cz_score_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("multilingual_xlm_roberta_for_ner_cz_score_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|multilingual_xlm_roberta_for_ner_cz_score_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|840.7 MB|
+
+## References
+
+https://huggingface.co/cz-score/multilingual-xlm-roberta-for-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-multilingual_xlm_roberta_for_ner_cz_score_xx.md b/docs/_posts/ahmedlone127/2025-01-25-multilingual_xlm_roberta_for_ner_cz_score_xx.md
new file mode 100644
index 00000000000000..573f68cde69685
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-multilingual_xlm_roberta_for_ner_cz_score_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual multilingual_xlm_roberta_for_ner_cz_score XlmRoBertaForTokenClassification from cz-score
+author: John Snow Labs
+name: multilingual_xlm_roberta_for_ner_cz_score
+date: 2025-01-25
+tags: [xx, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multilingual_xlm_roberta_for_ner_cz_score` is a Multilingual model originally trained by cz-score.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multilingual_xlm_roberta_for_ner_cz_score_xx_5.5.1_3.0_1737833560722.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multilingual_xlm_roberta_for_ner_cz_score_xx_5.5.1_3.0_1737833560722.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("multilingual_xlm_roberta_for_ner_cz_score","xx") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("multilingual_xlm_roberta_for_ner_cz_score", "xx")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|multilingual_xlm_roberta_for_ner_cz_score|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|xx|
+|Size:|840.6 MB|
+
+## References
+
+https://huggingface.co/cz-score/multilingual-xlm-roberta-for-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-multilingual_xlm_roberta_for_ner_ridadogrul_pipeline_xx.md b/docs/_posts/ahmedlone127/2025-01-25-multilingual_xlm_roberta_for_ner_ridadogrul_pipeline_xx.md
new file mode 100644
index 00000000000000..d379e44807b048
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-multilingual_xlm_roberta_for_ner_ridadogrul_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual multilingual_xlm_roberta_for_ner_ridadogrul_pipeline pipeline XlmRoBertaForTokenClassification from RidaDogrul
+author: John Snow Labs
+name: multilingual_xlm_roberta_for_ner_ridadogrul_pipeline
+date: 2025-01-25
+tags: [xx, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multilingual_xlm_roberta_for_ner_ridadogrul_pipeline` is a Multilingual model originally trained by RidaDogrul.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multilingual_xlm_roberta_for_ner_ridadogrul_pipeline_xx_5.5.1_3.0_1737778387190.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multilingual_xlm_roberta_for_ner_ridadogrul_pipeline_xx_5.5.1_3.0_1737778387190.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("multilingual_xlm_roberta_for_ner_ridadogrul_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("multilingual_xlm_roberta_for_ner_ridadogrul_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|multilingual_xlm_roberta_for_ner_ridadogrul_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/RidaDogrul/multilingual-xlm-roberta-for-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-multilingual_xlm_roberta_for_ner_ridadogrul_xx.md b/docs/_posts/ahmedlone127/2025-01-25-multilingual_xlm_roberta_for_ner_ridadogrul_xx.md
new file mode 100644
index 00000000000000..218ba72bd61c0a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-multilingual_xlm_roberta_for_ner_ridadogrul_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual multilingual_xlm_roberta_for_ner_ridadogrul XlmRoBertaForTokenClassification from RidaDogrul
+author: John Snow Labs
+name: multilingual_xlm_roberta_for_ner_ridadogrul
+date: 2025-01-25
+tags: [xx, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multilingual_xlm_roberta_for_ner_ridadogrul` is a Multilingual model originally trained by RidaDogrul.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multilingual_xlm_roberta_for_ner_ridadogrul_xx_5.5.1_3.0_1737778297190.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multilingual_xlm_roberta_for_ner_ridadogrul_xx_5.5.1_3.0_1737778297190.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("multilingual_xlm_roberta_for_ner_ridadogrul","xx") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("multilingual_xlm_roberta_for_ner_ridadogrul", "xx")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|multilingual_xlm_roberta_for_ner_ridadogrul|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|xx|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/RidaDogrul/multilingual-xlm-roberta-for-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-multilingual_xlm_roberta_for_ner_tuhanasinan_pipeline_xx.md b/docs/_posts/ahmedlone127/2025-01-25-multilingual_xlm_roberta_for_ner_tuhanasinan_pipeline_xx.md
new file mode 100644
index 00000000000000..af01c7195502aa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-multilingual_xlm_roberta_for_ner_tuhanasinan_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual multilingual_xlm_roberta_for_ner_tuhanasinan_pipeline pipeline XlmRoBertaForTokenClassification from tuhanasinan
+author: John Snow Labs
+name: multilingual_xlm_roberta_for_ner_tuhanasinan_pipeline
+date: 2025-01-25
+tags: [xx, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multilingual_xlm_roberta_for_ner_tuhanasinan_pipeline` is a Multilingual model originally trained by tuhanasinan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multilingual_xlm_roberta_for_ner_tuhanasinan_pipeline_xx_5.5.1_3.0_1737803535929.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multilingual_xlm_roberta_for_ner_tuhanasinan_pipeline_xx_5.5.1_3.0_1737803535929.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("multilingual_xlm_roberta_for_ner_tuhanasinan_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("multilingual_xlm_roberta_for_ner_tuhanasinan_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|multilingual_xlm_roberta_for_ner_tuhanasinan_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|844.6 MB|
+
+## References
+
+https://huggingface.co/tuhanasinan/multilingual-xlm-roberta-for-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-multilingual_xlm_roberta_for_ner_tuhanasinan_xx.md b/docs/_posts/ahmedlone127/2025-01-25-multilingual_xlm_roberta_for_ner_tuhanasinan_xx.md
new file mode 100644
index 00000000000000..4940df85c40c94
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-multilingual_xlm_roberta_for_ner_tuhanasinan_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual multilingual_xlm_roberta_for_ner_tuhanasinan XlmRoBertaForTokenClassification from tuhanasinan
+author: John Snow Labs
+name: multilingual_xlm_roberta_for_ner_tuhanasinan
+date: 2025-01-25
+tags: [xx, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multilingual_xlm_roberta_for_ner_tuhanasinan` is a Multilingual model originally trained by tuhanasinan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multilingual_xlm_roberta_for_ner_tuhanasinan_xx_5.5.1_3.0_1737803442771.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multilingual_xlm_roberta_for_ner_tuhanasinan_xx_5.5.1_3.0_1737803442771.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("multilingual_xlm_roberta_for_ner_tuhanasinan","xx") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("multilingual_xlm_roberta_for_ner_tuhanasinan", "xx")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|multilingual_xlm_roberta_for_ner_tuhanasinan|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|xx|
+|Size:|844.6 MB|
+
+## References
+
+https://huggingface.co/tuhanasinan/multilingual-xlm-roberta-for-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-mytoken_model_en.md b/docs/_posts/ahmedlone127/2025-01-25-mytoken_model_en.md
new file mode 100644
index 00000000000000..6118d07cae58a1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-mytoken_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mytoken_model BertEmbeddings from kumarme072
+author: John Snow Labs
+name: mytoken_model
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mytoken_model` is a English model originally trained by kumarme072.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mytoken_model_en_5.5.1_3.0_1737806930389.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mytoken_model_en_5.5.1_3.0_1737806930389.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("mytoken_model","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("mytoken_model","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mytoken_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/kumarme072/mytoken_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-mytoken_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-mytoken_model_pipeline_en.md
new file mode 100644
index 00000000000000..4ae40ff9cb345d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-mytoken_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mytoken_model_pipeline pipeline BertEmbeddings from kumarme072
+author: John Snow Labs
+name: mytoken_model_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mytoken_model_pipeline` is a English model originally trained by kumarme072.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mytoken_model_pipeline_en_5.5.1_3.0_1737806952455.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mytoken_model_pipeline_en_5.5.1_3.0_1737806952455.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mytoken_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mytoken_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mytoken_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.8 MB|
+
+## References
+
+https://huggingface.co/kumarme072/mytoken_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-ndd_dimeshift_test_tags_en.md b/docs/_posts/ahmedlone127/2025-01-25-ndd_dimeshift_test_tags_en.md
new file mode 100644
index 00000000000000..3f5e5ac5e92adb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-ndd_dimeshift_test_tags_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ndd_dimeshift_test_tags DistilBertForSequenceClassification from lgk03
+author: John Snow Labs
+name: ndd_dimeshift_test_tags
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ndd_dimeshift_test_tags` is a English model originally trained by lgk03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ndd_dimeshift_test_tags_en_5.5.1_3.0_1737837304433.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ndd_dimeshift_test_tags_en_5.5.1_3.0_1737837304433.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("ndd_dimeshift_test_tags","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("ndd_dimeshift_test_tags", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ndd_dimeshift_test_tags|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/lgk03/NDD-dimeshift_test-tags
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-ndd_dimeshift_test_tags_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-ndd_dimeshift_test_tags_pipeline_en.md
new file mode 100644
index 00000000000000..b511cbc82859ca
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-ndd_dimeshift_test_tags_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ndd_dimeshift_test_tags_pipeline pipeline DistilBertForSequenceClassification from lgk03
+author: John Snow Labs
+name: ndd_dimeshift_test_tags_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ndd_dimeshift_test_tags_pipeline` is a English model originally trained by lgk03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ndd_dimeshift_test_tags_pipeline_en_5.5.1_3.0_1737837316979.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ndd_dimeshift_test_tags_pipeline_en_5.5.1_3.0_1737837316979.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ndd_dimeshift_test_tags_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ndd_dimeshift_test_tags_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ndd_dimeshift_test_tags_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/lgk03/NDD-dimeshift_test-tags
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-ndd_ppma_test_content_tags_en.md b/docs/_posts/ahmedlone127/2025-01-25-ndd_ppma_test_content_tags_en.md
new file mode 100644
index 00000000000000..f554809f298521
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-ndd_ppma_test_content_tags_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ndd_ppma_test_content_tags DistilBertForSequenceClassification from lgk03
+author: John Snow Labs
+name: ndd_ppma_test_content_tags
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ndd_ppma_test_content_tags` is a English model originally trained by lgk03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ndd_ppma_test_content_tags_en_5.5.1_3.0_1737838093704.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ndd_ppma_test_content_tags_en_5.5.1_3.0_1737838093704.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("ndd_ppma_test_content_tags","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("ndd_ppma_test_content_tags", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ndd_ppma_test_content_tags|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/lgk03/NDD-ppma_test-content_tags
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-ndd_ppma_test_content_tags_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-ndd_ppma_test_content_tags_pipeline_en.md
new file mode 100644
index 00000000000000..e5bb7323e285aa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-ndd_ppma_test_content_tags_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ndd_ppma_test_content_tags_pipeline pipeline DistilBertForSequenceClassification from lgk03
+author: John Snow Labs
+name: ndd_ppma_test_content_tags_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ndd_ppma_test_content_tags_pipeline` is a English model originally trained by lgk03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ndd_ppma_test_content_tags_pipeline_en_5.5.1_3.0_1737838107324.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ndd_ppma_test_content_tags_pipeline_en_5.5.1_3.0_1737838107324.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ndd_ppma_test_content_tags_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ndd_ppma_test_content_tags_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ndd_ppma_test_content_tags_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/lgk03/NDD-ppma_test-content_tags
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-ner_bert_base_spanish_wwm_uncased_es.md b/docs/_posts/ahmedlone127/2025-01-25-ner_bert_base_spanish_wwm_uncased_es.md
new file mode 100644
index 00000000000000..c58d0d4031fe56
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-ner_bert_base_spanish_wwm_uncased_es.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Castilian, Spanish ner_bert_base_spanish_wwm_uncased BertForTokenClassification from jpherrerap
+author: John Snow Labs
+name: ner_bert_base_spanish_wwm_uncased
+date: 2025-01-25
+tags: [es, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: es
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_bert_base_spanish_wwm_uncased` is a Castilian, Spanish model originally trained by jpherrerap.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_bert_base_spanish_wwm_uncased_es_5.5.1_3.0_1737845196499.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_bert_base_spanish_wwm_uncased_es_5.5.1_3.0_1737845196499.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("ner_bert_base_spanish_wwm_uncased","es") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("ner_bert_base_spanish_wwm_uncased", "es")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_bert_base_spanish_wwm_uncased|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|es|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/jpherrerap/ner-bert-base-spanish-wwm-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-ner_bert_base_spanish_wwm_uncased_pipeline_es.md b/docs/_posts/ahmedlone127/2025-01-25-ner_bert_base_spanish_wwm_uncased_pipeline_es.md
new file mode 100644
index 00000000000000..ec58ddd1a88e69
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-ner_bert_base_spanish_wwm_uncased_pipeline_es.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Castilian, Spanish ner_bert_base_spanish_wwm_uncased_pipeline pipeline BertForTokenClassification from jpherrerap
+author: John Snow Labs
+name: ner_bert_base_spanish_wwm_uncased_pipeline
+date: 2025-01-25
+tags: [es, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: es
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_bert_base_spanish_wwm_uncased_pipeline` is a Castilian, Spanish model originally trained by jpherrerap.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_bert_base_spanish_wwm_uncased_pipeline_es_5.5.1_3.0_1737845217726.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_bert_base_spanish_wwm_uncased_pipeline_es_5.5.1_3.0_1737845217726.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ner_bert_base_spanish_wwm_uncased_pipeline", lang = "es")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ner_bert_base_spanish_wwm_uncased_pipeline", lang = "es")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_bert_base_spanish_wwm_uncased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|es|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/jpherrerap/ner-bert-base-spanish-wwm-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-ner_fine_tuned_en.md b/docs/_posts/ahmedlone127/2025-01-25-ner_fine_tuned_en.md
new file mode 100644
index 00000000000000..ceed64d9aa682a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-ner_fine_tuned_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ner_fine_tuned BertForTokenClassification from farizkuy
+author: John Snow Labs
+name: ner_fine_tuned
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_fine_tuned` is a English model originally trained by farizkuy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_fine_tuned_en_5.5.1_3.0_1737844061063.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_fine_tuned_en_5.5.1_3.0_1737844061063.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("ner_fine_tuned","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("ner_fine_tuned", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_fine_tuned|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|412.7 MB|
+
+## References
+
+https://huggingface.co/farizkuy/ner_fine_tuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-ner_fine_tuned_gdsc_tutoring_fariz_en.md b/docs/_posts/ahmedlone127/2025-01-25-ner_fine_tuned_gdsc_tutoring_fariz_en.md
new file mode 100644
index 00000000000000..97adc02ade938a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-ner_fine_tuned_gdsc_tutoring_fariz_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ner_fine_tuned_gdsc_tutoring_fariz BertForTokenClassification from farizkuy
+author: John Snow Labs
+name: ner_fine_tuned_gdsc_tutoring_fariz
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_fine_tuned_gdsc_tutoring_fariz` is a English model originally trained by farizkuy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_fine_tuned_gdsc_tutoring_fariz_en_5.5.1_3.0_1737835013375.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_fine_tuned_gdsc_tutoring_fariz_en_5.5.1_3.0_1737835013375.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("ner_fine_tuned_gdsc_tutoring_fariz","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("ner_fine_tuned_gdsc_tutoring_fariz", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_fine_tuned_gdsc_tutoring_fariz|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|412.7 MB|
+
+## References
+
+https://huggingface.co/farizkuy/ner_fine_tuned_gdsc_tutoring_fariz
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-ner_fine_tuned_gdsc_tutoring_fariz_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-ner_fine_tuned_gdsc_tutoring_fariz_pipeline_en.md
new file mode 100644
index 00000000000000..2888140827c3f7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-ner_fine_tuned_gdsc_tutoring_fariz_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ner_fine_tuned_gdsc_tutoring_fariz_pipeline pipeline BertForTokenClassification from farizkuy
+author: John Snow Labs
+name: ner_fine_tuned_gdsc_tutoring_fariz_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_fine_tuned_gdsc_tutoring_fariz_pipeline` is a English model originally trained by farizkuy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_fine_tuned_gdsc_tutoring_fariz_pipeline_en_5.5.1_3.0_1737835035024.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_fine_tuned_gdsc_tutoring_fariz_pipeline_en_5.5.1_3.0_1737835035024.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ner_fine_tuned_gdsc_tutoring_fariz_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ner_fine_tuned_gdsc_tutoring_fariz_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_fine_tuned_gdsc_tutoring_fariz_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|412.7 MB|
+
+## References
+
+https://huggingface.co/farizkuy/ner_fine_tuned_gdsc_tutoring_fariz
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-ner_fine_tuned_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-ner_fine_tuned_pipeline_en.md
new file mode 100644
index 00000000000000..caeb95e16ea797
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-ner_fine_tuned_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ner_fine_tuned_pipeline pipeline BertForTokenClassification from farizkuy
+author: John Snow Labs
+name: ner_fine_tuned_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_fine_tuned_pipeline` is a English model originally trained by farizkuy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_fine_tuned_pipeline_en_5.5.1_3.0_1737844081804.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_fine_tuned_pipeline_en_5.5.1_3.0_1737844081804.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ner_fine_tuned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ner_fine_tuned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_fine_tuned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|412.7 MB|
+
+## References
+
+https://huggingface.co/farizkuy/ner_fine_tuned
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-ner_medical_tm_en.md b/docs/_posts/ahmedlone127/2025-01-25-ner_medical_tm_en.md
new file mode 100644
index 00000000000000..d357e7e0847ad8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-ner_medical_tm_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ner_medical_tm BertForTokenClassification from etadevosyan
+author: John Snow Labs
+name: ner_medical_tm
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_medical_tm` is a English model originally trained by etadevosyan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_medical_tm_en_5.5.1_3.0_1737835753746.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_medical_tm_en_5.5.1_3.0_1737835753746.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("ner_medical_tm","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("ner_medical_tm", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_medical_tm|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|664.4 MB|
+
+## References
+
+https://huggingface.co/etadevosyan/ner_medical_tm
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-ner_medical_tm_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-ner_medical_tm_pipeline_en.md
new file mode 100644
index 00000000000000..7fba254077cdbb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-ner_medical_tm_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ner_medical_tm_pipeline pipeline BertForTokenClassification from etadevosyan
+author: John Snow Labs
+name: ner_medical_tm_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_medical_tm_pipeline` is a English model originally trained by etadevosyan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_medical_tm_pipeline_en_5.5.1_3.0_1737835785798.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_medical_tm_pipeline_en_5.5.1_3.0_1737835785798.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ner_medical_tm_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ner_medical_tm_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_medical_tm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|664.4 MB|
+
+## References
+
+https://huggingface.co/etadevosyan/ner_medical_tm
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-ner_xlm_roberta_english_en.md b/docs/_posts/ahmedlone127/2025-01-25-ner_xlm_roberta_english_en.md
new file mode 100644
index 00000000000000..5656c4e3fd651c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-ner_xlm_roberta_english_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ner_xlm_roberta_english XlmRoBertaForTokenClassification from Mu7annad
+author: John Snow Labs
+name: ner_xlm_roberta_english
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_xlm_roberta_english` is a English model originally trained by Mu7annad.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_xlm_roberta_english_en_5.5.1_3.0_1737778758381.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_xlm_roberta_english_en_5.5.1_3.0_1737778758381.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("ner_xlm_roberta_english","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("ner_xlm_roberta_english", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_xlm_roberta_english|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|815.6 MB|
+
+## References
+
+https://huggingface.co/Mu7annad/ner-xlm-roberta-english
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-ner_xlm_roberta_english_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-ner_xlm_roberta_english_pipeline_en.md
new file mode 100644
index 00000000000000..8c862cb69556ec
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-ner_xlm_roberta_english_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ner_xlm_roberta_english_pipeline pipeline XlmRoBertaForTokenClassification from Mu7annad
+author: John Snow Labs
+name: ner_xlm_roberta_english_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_xlm_roberta_english_pipeline` is a English model originally trained by Mu7annad.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_xlm_roberta_english_pipeline_en_5.5.1_3.0_1737778881080.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_xlm_roberta_english_pipeline_en_5.5.1_3.0_1737778881080.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ner_xlm_roberta_english_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ner_xlm_roberta_english_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_xlm_roberta_english_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|815.6 MB|
+
+## References
+
+https://huggingface.co/Mu7annad/ner-xlm-roberta-english
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-neurips_distilbert_covid_1_en.md b/docs/_posts/ahmedlone127/2025-01-25-neurips_distilbert_covid_1_en.md
new file mode 100644
index 00000000000000..ddf4cf3a3503a3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-neurips_distilbert_covid_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English neurips_distilbert_covid_1 DistilBertForSequenceClassification from neurips-user
+author: John Snow Labs
+name: neurips_distilbert_covid_1
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`neurips_distilbert_covid_1` is a English model originally trained by neurips-user.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/neurips_distilbert_covid_1_en_5.5.1_3.0_1737836861668.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/neurips_distilbert_covid_1_en_5.5.1_3.0_1737836861668.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("neurips_distilbert_covid_1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("neurips_distilbert_covid_1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|neurips_distilbert_covid_1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/neurips-user/neurips-distilbert-covid-1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-neurips_distilbert_covid_1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-neurips_distilbert_covid_1_pipeline_en.md
new file mode 100644
index 00000000000000..5dd876ac67673f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-neurips_distilbert_covid_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English neurips_distilbert_covid_1_pipeline pipeline DistilBertForSequenceClassification from neurips-user
+author: John Snow Labs
+name: neurips_distilbert_covid_1_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`neurips_distilbert_covid_1_pipeline` is a English model originally trained by neurips-user.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/neurips_distilbert_covid_1_pipeline_en_5.5.1_3.0_1737836875016.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/neurips_distilbert_covid_1_pipeline_en_5.5.1_3.0_1737836875016.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("neurips_distilbert_covid_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("neurips_distilbert_covid_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|neurips_distilbert_covid_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/neurips-user/neurips-distilbert-covid-1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-nlpf_en.md b/docs/_posts/ahmedlone127/2025-01-25-nlpf_en.md
new file mode 100644
index 00000000000000..d83e65a0ba9476
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-nlpf_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English nlpf CamemBertForSequenceClassification from queenVdu13
+author: John Snow Labs
+name: nlpf
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, camembert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nlpf` is a English model originally trained by queenVdu13.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nlpf_en_5.5.1_3.0_1737823309851.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nlpf_en_5.5.1_3.0_1737823309851.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = CamemBertForSequenceClassification.pretrained("nlpf","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = CamemBertForSequenceClassification.pretrained("nlpf", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nlpf|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|255.8 MB|
+
+## References
+
+https://huggingface.co/queenVdu13/NLPF
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-nlpf_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-nlpf_pipeline_en.md
new file mode 100644
index 00000000000000..a739a5ce54264e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-nlpf_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English nlpf_pipeline pipeline CamemBertForSequenceClassification from queenVdu13
+author: John Snow Labs
+name: nlpf_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nlpf_pipeline` is a English model originally trained by queenVdu13.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nlpf_pipeline_en_5.5.1_3.0_1737823322818.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nlpf_pipeline_en_5.5.1_3.0_1737823322818.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("nlpf_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("nlpf_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nlpf_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|255.8 MB|
+
+## References
+
+https://huggingface.co/queenVdu13/NLPF
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-nsfw_story_generator2_en.md b/docs/_posts/ahmedlone127/2025-01-25-nsfw_story_generator2_en.md
new file mode 100644
index 00000000000000..f9807a20cab90e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-nsfw_story_generator2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English nsfw_story_generator2 GPT2Transformer from coffeeee
+author: John Snow Labs
+name: nsfw_story_generator2
+date: 2025-01-25
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nsfw_story_generator2` is a English model originally trained by coffeeee.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nsfw_story_generator2_en_5.5.1_3.0_1737765680568.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nsfw_story_generator2_en_5.5.1_3.0_1737765680568.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("nsfw_story_generator2","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("nsfw_story_generator2","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nsfw_story_generator2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/coffeeee/nsfw-story-generator2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-nsfw_story_generator2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-nsfw_story_generator2_pipeline_en.md
new file mode 100644
index 00000000000000..2e7f242ff2c3ae
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-nsfw_story_generator2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English nsfw_story_generator2_pipeline pipeline GPT2Transformer from coffeeee
+author: John Snow Labs
+name: nsfw_story_generator2_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nsfw_story_generator2_pipeline` is a English model originally trained by coffeeee.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nsfw_story_generator2_pipeline_en_5.5.1_3.0_1737765748541.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nsfw_story_generator2_pipeline_en_5.5.1_3.0_1737765748541.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("nsfw_story_generator2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("nsfw_story_generator2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nsfw_story_generator2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/coffeeee/nsfw-story-generator2
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-numerical_arabic_en.md b/docs/_posts/ahmedlone127/2025-01-25-numerical_arabic_en.md
new file mode 100644
index 00000000000000..851c76bbeafd43
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-numerical_arabic_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English numerical_arabic BertForSequenceClassification from Ejada
+author: John Snow Labs
+name: numerical_arabic
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`numerical_arabic` is a English model originally trained by Ejada.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/numerical_arabic_en_5.5.1_3.0_1737800839719.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/numerical_arabic_en_5.5.1_3.0_1737800839719.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("numerical_arabic","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("numerical_arabic", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|numerical_arabic|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|507.3 MB|
+
+## References
+
+https://huggingface.co/Ejada/numerical_arabic_
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-numerical_arabic_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-numerical_arabic_pipeline_en.md
new file mode 100644
index 00000000000000..161c57bb886113
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-numerical_arabic_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English numerical_arabic_pipeline pipeline BertForSequenceClassification from Ejada
+author: John Snow Labs
+name: numerical_arabic_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`numerical_arabic_pipeline` is a English model originally trained by Ejada.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/numerical_arabic_pipeline_en_5.5.1_3.0_1737800870658.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/numerical_arabic_pipeline_en_5.5.1_3.0_1737800870658.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("numerical_arabic_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("numerical_arabic_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|numerical_arabic_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|507.3 MB|
+
+## References
+
+https://huggingface.co/Ejada/numerical_arabic_
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-ohm2_en.md b/docs/_posts/ahmedlone127/2025-01-25-ohm2_en.md
new file mode 100644
index 00000000000000..08485b1c56ba2e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-ohm2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ohm2 DistilBertForSequenceClassification from Ohmmy3847
+author: John Snow Labs
+name: ohm2
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ohm2` is a English model originally trained by Ohmmy3847.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ohm2_en_5.5.1_3.0_1737822762405.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ohm2_en_5.5.1_3.0_1737822762405.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("ohm2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("ohm2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ohm2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Ohmmy3847/Ohm2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-ohm2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-ohm2_pipeline_en.md
new file mode 100644
index 00000000000000..de4ca206a1959f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-ohm2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ohm2_pipeline pipeline DistilBertForSequenceClassification from Ohmmy3847
+author: John Snow Labs
+name: ohm2_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ohm2_pipeline` is a English model originally trained by Ohmmy3847.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ohm2_pipeline_en_5.5.1_3.0_1737822776058.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ohm2_pipeline_en_5.5.1_3.0_1737822776058.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ohm2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ohm2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ohm2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Ohmmy3847/Ohm2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-opus_base_aon_freq_wce_en.md b/docs/_posts/ahmedlone127/2025-01-25-opus_base_aon_freq_wce_en.md
new file mode 100644
index 00000000000000..2e954540db1f4e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-opus_base_aon_freq_wce_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_base_aon_freq_wce MarianTransformer from ethansimrm
+author: John Snow Labs
+name: opus_base_aon_freq_wce
+date: 2025-01-25
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_base_aon_freq_wce` is a English model originally trained by ethansimrm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_base_aon_freq_wce_en_5.5.1_3.0_1737843334101.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_base_aon_freq_wce_en_5.5.1_3.0_1737843334101.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_base_aon_freq_wce","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_base_aon_freq_wce","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_base_aon_freq_wce|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|397.2 MB|
+
+## References
+
+https://huggingface.co/ethansimrm/opus_base_AoN_freq_wce
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-opus_base_aon_freq_wce_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-opus_base_aon_freq_wce_pipeline_en.md
new file mode 100644
index 00000000000000..301db6ad249e6c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-opus_base_aon_freq_wce_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_base_aon_freq_wce_pipeline pipeline MarianTransformer from ethansimrm
+author: John Snow Labs
+name: opus_base_aon_freq_wce_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_base_aon_freq_wce_pipeline` is a English model originally trained by ethansimrm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_base_aon_freq_wce_pipeline_en_5.5.1_3.0_1737843353865.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_base_aon_freq_wce_pipeline_en_5.5.1_3.0_1737843353865.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("opus_base_aon_freq_wce_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_base_aon_freq_wce_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_base_aon_freq_wce_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|397.7 MB|
+
+## References
+
+https://huggingface.co/ethansimrm/opus_base_AoN_freq_wce
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-opus_base_simple_freq_wce_en.md b/docs/_posts/ahmedlone127/2025-01-25-opus_base_simple_freq_wce_en.md
new file mode 100644
index 00000000000000..8c046c277c85eb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-opus_base_simple_freq_wce_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_base_simple_freq_wce MarianTransformer from ethansimrm
+author: John Snow Labs
+name: opus_base_simple_freq_wce
+date: 2025-01-25
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_base_simple_freq_wce` is a English model originally trained by ethansimrm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_base_simple_freq_wce_en_5.5.1_3.0_1737827781382.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_base_simple_freq_wce_en_5.5.1_3.0_1737827781382.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_base_simple_freq_wce","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_base_simple_freq_wce","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_base_simple_freq_wce|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|397.2 MB|
+
+## References
+
+https://huggingface.co/ethansimrm/opus_base_simple_freq_wce
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-opus_base_simple_freq_wce_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-opus_base_simple_freq_wce_pipeline_en.md
new file mode 100644
index 00000000000000..eda2e8c6b9ad42
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-opus_base_simple_freq_wce_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_base_simple_freq_wce_pipeline pipeline MarianTransformer from ethansimrm
+author: John Snow Labs
+name: opus_base_simple_freq_wce_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_base_simple_freq_wce_pipeline` is a English model originally trained by ethansimrm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_base_simple_freq_wce_pipeline_en_5.5.1_3.0_1737827801615.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_base_simple_freq_wce_pipeline_en_5.5.1_3.0_1737827801615.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("opus_base_simple_freq_wce_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_base_simple_freq_wce_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_base_simple_freq_wce_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|397.7 MB|
+
+## References
+
+https://huggingface.co/ethansimrm/opus_base_simple_freq_wce
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-opus_big_simple_freq_wce_en.md b/docs/_posts/ahmedlone127/2025-01-25-opus_big_simple_freq_wce_en.md
new file mode 100644
index 00000000000000..911f604d9c5442
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-opus_big_simple_freq_wce_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_big_simple_freq_wce MarianTransformer from ethansimrm
+author: John Snow Labs
+name: opus_big_simple_freq_wce
+date: 2025-01-25
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_big_simple_freq_wce` is a English model originally trained by ethansimrm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_big_simple_freq_wce_en_5.5.1_3.0_1737841520561.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_big_simple_freq_wce_en_5.5.1_3.0_1737841520561.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_big_simple_freq_wce","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_big_simple_freq_wce","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_big_simple_freq_wce|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/ethansimrm/opus_big_simple_freq_wce
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-opus_big_simple_freq_wce_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-opus_big_simple_freq_wce_pipeline_en.md
new file mode 100644
index 00000000000000..26729c1cef2ac1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-opus_big_simple_freq_wce_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_big_simple_freq_wce_pipeline pipeline MarianTransformer from ethansimrm
+author: John Snow Labs
+name: opus_big_simple_freq_wce_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_big_simple_freq_wce_pipeline` is a English model originally trained by ethansimrm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_big_simple_freq_wce_pipeline_en_5.5.1_3.0_1737841576399.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_big_simple_freq_wce_pipeline_en_5.5.1_3.0_1737841576399.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("opus_big_simple_freq_wce_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_big_simple_freq_wce_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_big_simple_freq_wce_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/ethansimrm/opus_big_simple_freq_wce
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-opus_maltese_english_bkm_1_en.md b/docs/_posts/ahmedlone127/2025-01-25-opus_maltese_english_bkm_1_en.md
new file mode 100644
index 00000000000000..fed171d8673355
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-opus_maltese_english_bkm_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_english_bkm_1 MarianTransformer from kalese
+author: John Snow Labs
+name: opus_maltese_english_bkm_1
+date: 2025-01-25
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_bkm_1` is a English model originally trained by kalese.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_bkm_1_en_5.5.1_3.0_1737782984124.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_bkm_1_en_5.5.1_3.0_1737782984124.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_english_bkm_1","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_english_bkm_1","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_bkm_1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|396.7 MB|
+
+## References
+
+https://huggingface.co/kalese/opus-mt-en-bkm-1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-opus_maltese_english_bkm_1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-opus_maltese_english_bkm_1_pipeline_en.md
new file mode 100644
index 00000000000000..d001b038313704
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-opus_maltese_english_bkm_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_english_bkm_1_pipeline pipeline MarianTransformer from kalese
+author: John Snow Labs
+name: opus_maltese_english_bkm_1_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_bkm_1_pipeline` is a English model originally trained by kalese.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_bkm_1_pipeline_en_5.5.1_3.0_1737783004645.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_bkm_1_pipeline_en_5.5.1_3.0_1737783004645.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("opus_maltese_english_bkm_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_english_bkm_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_bkm_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|397.2 MB|
+
+## References
+
+https://huggingface.co/kalese/opus-mt-en-bkm-1
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-opus_maltese_english_vietnamese_finetuned_en.md b/docs/_posts/ahmedlone127/2025-01-25-opus_maltese_english_vietnamese_finetuned_en.md
new file mode 100644
index 00000000000000..ba5260c0b3ce9b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-opus_maltese_english_vietnamese_finetuned_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_english_vietnamese_finetuned MarianTransformer from datngo2001
+author: John Snow Labs
+name: opus_maltese_english_vietnamese_finetuned
+date: 2025-01-25
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_vietnamese_finetuned` is a English model originally trained by datngo2001.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_vietnamese_finetuned_en_5.5.1_3.0_1737843471119.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_vietnamese_finetuned_en_5.5.1_3.0_1737843471119.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_english_vietnamese_finetuned","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_english_vietnamese_finetuned","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_vietnamese_finetuned|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|374.3 MB|
+
+## References
+
+https://huggingface.co/datngo2001/opus-mt-en-vi-finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-opus_maltese_english_vietnamese_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-opus_maltese_english_vietnamese_finetuned_pipeline_en.md
new file mode 100644
index 00000000000000..d2a88b6c5a0f43
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-opus_maltese_english_vietnamese_finetuned_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_english_vietnamese_finetuned_pipeline pipeline MarianTransformer from datngo2001
+author: John Snow Labs
+name: opus_maltese_english_vietnamese_finetuned_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_vietnamese_finetuned_pipeline` is a English model originally trained by datngo2001.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_vietnamese_finetuned_pipeline_en_5.5.1_3.0_1737843489544.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_vietnamese_finetuned_pipeline_en_5.5.1_3.0_1737843489544.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("opus_maltese_english_vietnamese_finetuned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_english_vietnamese_finetuned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_vietnamese_finetuned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|374.8 MB|
+
+## References
+
+https://huggingface.co/datngo2001/opus-mt-en-vi-finetuned
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-opus_maltese_ganda_english_informal_en.md b/docs/_posts/ahmedlone127/2025-01-25-opus_maltese_ganda_english_informal_en.md
new file mode 100644
index 00000000000000..7afb6de70539d8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-opus_maltese_ganda_english_informal_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_ganda_english_informal MarianTransformer from MubarakB
+author: John Snow Labs
+name: opus_maltese_ganda_english_informal
+date: 2025-01-25
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_ganda_english_informal` is a English model originally trained by MubarakB.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_ganda_english_informal_en_5.5.1_3.0_1737783099464.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_ganda_english_informal_en_5.5.1_3.0_1737783099464.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_ganda_english_informal","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_ganda_english_informal","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_ganda_english_informal|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|399.9 MB|
+
+## References
+
+https://huggingface.co/MubarakB/opus-mt-lg-en-informal
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-opus_maltese_ganda_english_informal_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-opus_maltese_ganda_english_informal_pipeline_en.md
new file mode 100644
index 00000000000000..513c4dd1d14d25
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-opus_maltese_ganda_english_informal_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_ganda_english_informal_pipeline pipeline MarianTransformer from MubarakB
+author: John Snow Labs
+name: opus_maltese_ganda_english_informal_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_ganda_english_informal_pipeline` is a English model originally trained by MubarakB.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_ganda_english_informal_pipeline_en_5.5.1_3.0_1737783120000.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_ganda_english_informal_pipeline_en_5.5.1_3.0_1737783120000.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("opus_maltese_ganda_english_informal_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_ganda_english_informal_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_ganda_english_informal_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|400.5 MB|
+
+## References
+
+https://huggingface.co/MubarakB/opus-mt-lg-en-informal
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-opus_maltese_hindi_english_finetuned_hindi_tonga_tonga_islands_english_finetuned_hindi_tonga_tonga_islands_english_idioms_en.md b/docs/_posts/ahmedlone127/2025-01-25-opus_maltese_hindi_english_finetuned_hindi_tonga_tonga_islands_english_finetuned_hindi_tonga_tonga_islands_english_idioms_en.md
new file mode 100644
index 00000000000000..3b0798c86d83a1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-opus_maltese_hindi_english_finetuned_hindi_tonga_tonga_islands_english_finetuned_hindi_tonga_tonga_islands_english_idioms_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_hindi_english_finetuned_hindi_tonga_tonga_islands_english_finetuned_hindi_tonga_tonga_islands_english_idioms MarianTransformer from Ellight
+author: John Snow Labs
+name: opus_maltese_hindi_english_finetuned_hindi_tonga_tonga_islands_english_finetuned_hindi_tonga_tonga_islands_english_idioms
+date: 2025-01-25
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_hindi_english_finetuned_hindi_tonga_tonga_islands_english_finetuned_hindi_tonga_tonga_islands_english_idioms` is a English model originally trained by Ellight.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_hindi_english_finetuned_hindi_tonga_tonga_islands_english_finetuned_hindi_tonga_tonga_islands_english_idioms_en_5.5.1_3.0_1737841885674.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_hindi_english_finetuned_hindi_tonga_tonga_islands_english_finetuned_hindi_tonga_tonga_islands_english_idioms_en_5.5.1_3.0_1737841885674.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_hindi_english_finetuned_hindi_tonga_tonga_islands_english_finetuned_hindi_tonga_tonga_islands_english_idioms","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_hindi_english_finetuned_hindi_tonga_tonga_islands_english_finetuned_hindi_tonga_tonga_islands_english_idioms","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_hindi_english_finetuned_hindi_tonga_tonga_islands_english_finetuned_hindi_tonga_tonga_islands_english_idioms|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|402.8 MB|
+
+## References
+
+https://huggingface.co/Ellight/opus-mt-hi-en-finetuned-hi-to-en-finetuned-hi-to-en-idioms
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-opus_maltese_hindi_english_finetuned_hindi_tonga_tonga_islands_english_finetuned_hindi_tonga_tonga_islands_english_idioms_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-opus_maltese_hindi_english_finetuned_hindi_tonga_tonga_islands_english_finetuned_hindi_tonga_tonga_islands_english_idioms_pipeline_en.md
new file mode 100644
index 00000000000000..1c2c80e692f00f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-opus_maltese_hindi_english_finetuned_hindi_tonga_tonga_islands_english_finetuned_hindi_tonga_tonga_islands_english_idioms_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_hindi_english_finetuned_hindi_tonga_tonga_islands_english_finetuned_hindi_tonga_tonga_islands_english_idioms_pipeline pipeline MarianTransformer from Ellight
+author: John Snow Labs
+name: opus_maltese_hindi_english_finetuned_hindi_tonga_tonga_islands_english_finetuned_hindi_tonga_tonga_islands_english_idioms_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_hindi_english_finetuned_hindi_tonga_tonga_islands_english_finetuned_hindi_tonga_tonga_islands_english_idioms_pipeline` is a English model originally trained by Ellight.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_hindi_english_finetuned_hindi_tonga_tonga_islands_english_finetuned_hindi_tonga_tonga_islands_english_idioms_pipeline_en_5.5.1_3.0_1737841905896.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_hindi_english_finetuned_hindi_tonga_tonga_islands_english_finetuned_hindi_tonga_tonga_islands_english_idioms_pipeline_en_5.5.1_3.0_1737841905896.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("opus_maltese_hindi_english_finetuned_hindi_tonga_tonga_islands_english_finetuned_hindi_tonga_tonga_islands_english_idioms_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_hindi_english_finetuned_hindi_tonga_tonga_islands_english_finetuned_hindi_tonga_tonga_islands_english_idioms_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_hindi_english_finetuned_hindi_tonga_tonga_islands_english_finetuned_hindi_tonga_tonga_islands_english_idioms_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.4 MB|
+
+## References
+
+https://huggingface.co/Ellight/opus-mt-hi-en-finetuned-hi-to-en-finetuned-hi-to-en-idioms
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-opus_maltese_russian_english_en.md b/docs/_posts/ahmedlone127/2025-01-25-opus_maltese_russian_english_en.md
new file mode 100644
index 00000000000000..3cc6a6c057db18
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-opus_maltese_russian_english_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_russian_english MarianTransformer from ksumarshmallow
+author: John Snow Labs
+name: opus_maltese_russian_english
+date: 2025-01-25
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_russian_english` is a English model originally trained by ksumarshmallow.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_russian_english_en_5.5.1_3.0_1737841767915.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_russian_english_en_5.5.1_3.0_1737841767915.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_russian_english","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_russian_english","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_russian_english|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|408.8 MB|
+
+## References
+
+https://huggingface.co/ksumarshmallow/opus-mt-ru-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-opus_maltese_russian_english_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-opus_maltese_russian_english_pipeline_en.md
new file mode 100644
index 00000000000000..c4dfaeeab3a9fb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-opus_maltese_russian_english_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_russian_english_pipeline pipeline MarianTransformer from ksumarshmallow
+author: John Snow Labs
+name: opus_maltese_russian_english_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_russian_english_pipeline` is a English model originally trained by ksumarshmallow.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_russian_english_pipeline_en_5.5.1_3.0_1737841788059.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_russian_english_pipeline_en_5.5.1_3.0_1737841788059.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("opus_maltese_russian_english_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_russian_english_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_russian_english_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/ksumarshmallow/opus-mt-ru-en
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-original_model_final_en.md b/docs/_posts/ahmedlone127/2025-01-25-original_model_final_en.md
new file mode 100644
index 00000000000000..2b5fd09a01e66d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-original_model_final_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English original_model_final DistilBertForSequenceClassification from LeonardoFettucciari
+author: John Snow Labs
+name: original_model_final
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`original_model_final` is a English model originally trained by LeonardoFettucciari.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/original_model_final_en_5.5.1_3.0_1737836391730.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/original_model_final_en_5.5.1_3.0_1737836391730.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("original_model_final","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("original_model_final", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|original_model_final|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/LeonardoFettucciari/original_model_final
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-original_model_final_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-original_model_final_pipeline_en.md
new file mode 100644
index 00000000000000..ad8ab324b7b1d8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-original_model_final_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English original_model_final_pipeline pipeline DistilBertForSequenceClassification from LeonardoFettucciari
+author: John Snow Labs
+name: original_model_final_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`original_model_final_pipeline` is a English model originally trained by LeonardoFettucciari.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/original_model_final_pipeline_en_5.5.1_3.0_1737836405192.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/original_model_final_pipeline_en_5.5.1_3.0_1737836405192.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("original_model_final_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("original_model_final_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|original_model_final_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/LeonardoFettucciari/original_model_final
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-ottoman_berturk_en.md b/docs/_posts/ahmedlone127/2025-01-25-ottoman_berturk_en.md
new file mode 100644
index 00000000000000..81f04c4400d354
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-ottoman_berturk_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ottoman_berturk BertEmbeddings from onurkeles
+author: John Snow Labs
+name: ottoman_berturk
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ottoman_berturk` is a English model originally trained by onurkeles.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ottoman_berturk_en_5.5.1_3.0_1737846362202.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ottoman_berturk_en_5.5.1_3.0_1737846362202.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("ottoman_berturk","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("ottoman_berturk","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ottoman_berturk|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|412.3 MB|
+
+## References
+
+https://huggingface.co/onurkeles/ottoman_berturk
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-ottoman_berturk_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-ottoman_berturk_pipeline_en.md
new file mode 100644
index 00000000000000..bb3449c078d73a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-ottoman_berturk_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ottoman_berturk_pipeline pipeline BertEmbeddings from onurkeles
+author: John Snow Labs
+name: ottoman_berturk_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ottoman_berturk_pipeline` is a English model originally trained by onurkeles.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ottoman_berturk_pipeline_en_5.5.1_3.0_1737846382596.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ottoman_berturk_pipeline_en_5.5.1_3.0_1737846382596.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ottoman_berturk_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ottoman_berturk_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ottoman_berturk_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|412.3 MB|
+
+## References
+
+https://huggingface.co/onurkeles/ottoman_berturk
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-outputs_project_id2223_en.md b/docs/_posts/ahmedlone127/2025-01-25-outputs_project_id2223_en.md
new file mode 100644
index 00000000000000..6458a14a149e66
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-outputs_project_id2223_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English outputs_project_id2223 T5Transformer from rishivijayvargiya
+author: John Snow Labs
+name: outputs_project_id2223
+date: 2025-01-25
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`outputs_project_id2223` is a English model originally trained by rishivijayvargiya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/outputs_project_id2223_en_5.5.1_3.0_1737849185099.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/outputs_project_id2223_en_5.5.1_3.0_1737849185099.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("outputs_project_id2223","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("outputs_project_id2223", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|outputs_project_id2223|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|285.6 MB|
+
+## References
+
+https://huggingface.co/rishivijayvargiya/outputs-project-id2223
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-outputs_project_id2223_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-outputs_project_id2223_pipeline_en.md
new file mode 100644
index 00000000000000..3ecf20a8b8e9c3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-outputs_project_id2223_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English outputs_project_id2223_pipeline pipeline T5Transformer from rishivijayvargiya
+author: John Snow Labs
+name: outputs_project_id2223_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`outputs_project_id2223_pipeline` is a English model originally trained by rishivijayvargiya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/outputs_project_id2223_pipeline_en_5.5.1_3.0_1737849199808.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/outputs_project_id2223_pipeline_en_5.5.1_3.0_1737849199808.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("outputs_project_id2223_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("outputs_project_id2223_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|outputs_project_id2223_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|285.6 MB|
+
+## References
+
+https://huggingface.co/rishivijayvargiya/outputs-project-id2223
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-pm_modelv2_en.md b/docs/_posts/ahmedlone127/2025-01-25-pm_modelv2_en.md
new file mode 100644
index 00000000000000..b60621f596da6e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-pm_modelv2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English pm_modelv2 GPT2Transformer from BreadAi
+author: John Snow Labs
+name: pm_modelv2
+date: 2025-01-25
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pm_modelv2` is a English model originally trained by BreadAi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pm_modelv2_en_5.5.1_3.0_1737826050760.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pm_modelv2_en_5.5.1_3.0_1737826050760.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("pm_modelv2","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("pm_modelv2","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pm_modelv2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|960.5 MB|
+
+## References
+
+https://huggingface.co/BreadAi/PM_modelV2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-pm_modelv2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-pm_modelv2_pipeline_en.md
new file mode 100644
index 00000000000000..4089a72af0b6f6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-pm_modelv2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English pm_modelv2_pipeline pipeline GPT2Transformer from BreadAi
+author: John Snow Labs
+name: pm_modelv2_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pm_modelv2_pipeline` is a English model originally trained by BreadAi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pm_modelv2_pipeline_en_5.5.1_3.0_1737826101982.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pm_modelv2_pipeline_en_5.5.1_3.0_1737826101982.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("pm_modelv2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("pm_modelv2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pm_modelv2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|960.5 MB|
+
+## References
+
+https://huggingface.co/BreadAi/PM_modelV2
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-polite_guard_en.md b/docs/_posts/ahmedlone127/2025-01-25-polite_guard_en.md
new file mode 100644
index 00000000000000..cdf41e5a99ca25
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-polite_guard_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English polite_guard BertForSequenceClassification from Intel
+author: John Snow Labs
+name: polite_guard
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`polite_guard` is a English model originally trained by Intel.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/polite_guard_en_5.5.1_3.0_1737800992160.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/polite_guard_en_5.5.1_3.0_1737800992160.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("polite_guard","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("polite_guard", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|polite_guard|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/Intel/polite-guard
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-polite_guard_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-polite_guard_pipeline_en.md
new file mode 100644
index 00000000000000..fccadf9294e377
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-polite_guard_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English polite_guard_pipeline pipeline BertForSequenceClassification from Intel
+author: John Snow Labs
+name: polite_guard_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`polite_guard_pipeline` is a English model originally trained by Intel.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/polite_guard_pipeline_en_5.5.1_3.0_1737801014622.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/polite_guard_pipeline_en_5.5.1_3.0_1737801014622.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("polite_guard_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("polite_guard_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|polite_guard_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/Intel/polite-guard
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-political_bias_prediction_allsides_bert_en.md b/docs/_posts/ahmedlone127/2025-01-25-political_bias_prediction_allsides_bert_en.md
new file mode 100644
index 00000000000000..deabe3fc15c3cd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-political_bias_prediction_allsides_bert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English political_bias_prediction_allsides_bert BertForSequenceClassification from premsa
+author: John Snow Labs
+name: political_bias_prediction_allsides_bert
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`political_bias_prediction_allsides_bert` is a English model originally trained by premsa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/political_bias_prediction_allsides_bert_en_5.5.1_3.0_1737801283262.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/political_bias_prediction_allsides_bert_en_5.5.1_3.0_1737801283262.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("political_bias_prediction_allsides_bert","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("political_bias_prediction_allsides_bert", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|political_bias_prediction_allsides_bert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/premsa/political-bias-prediction-allsides-BERT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-political_bias_prediction_allsides_bert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-political_bias_prediction_allsides_bert_pipeline_en.md
new file mode 100644
index 00000000000000..e15e11c7d277c1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-political_bias_prediction_allsides_bert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English political_bias_prediction_allsides_bert_pipeline pipeline BertForSequenceClassification from premsa
+author: John Snow Labs
+name: political_bias_prediction_allsides_bert_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`political_bias_prediction_allsides_bert_pipeline` is a English model originally trained by premsa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/political_bias_prediction_allsides_bert_pipeline_en_5.5.1_3.0_1737801305352.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/political_bias_prediction_allsides_bert_pipeline_en_5.5.1_3.0_1737801305352.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("political_bias_prediction_allsides_bert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("political_bias_prediction_allsides_bert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|political_bias_prediction_allsides_bert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/premsa/political-bias-prediction-allsides-BERT
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-pop_lyrics_generator_v1_en.md b/docs/_posts/ahmedlone127/2025-01-25-pop_lyrics_generator_v1_en.md
new file mode 100644
index 00000000000000..1dc928df408dc6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-pop_lyrics_generator_v1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English pop_lyrics_generator_v1 GPT2Transformer from smgriffin
+author: John Snow Labs
+name: pop_lyrics_generator_v1
+date: 2025-01-25
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pop_lyrics_generator_v1` is a English model originally trained by smgriffin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pop_lyrics_generator_v1_en_5.5.1_3.0_1737825414126.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pop_lyrics_generator_v1_en_5.5.1_3.0_1737825414126.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("pop_lyrics_generator_v1","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("pop_lyrics_generator_v1","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pop_lyrics_generator_v1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/smgriffin/pop-lyrics-generator-v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-pop_lyrics_generator_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-pop_lyrics_generator_v1_pipeline_en.md
new file mode 100644
index 00000000000000..c14d0caa98e32f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-pop_lyrics_generator_v1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English pop_lyrics_generator_v1_pipeline pipeline GPT2Transformer from smgriffin
+author: John Snow Labs
+name: pop_lyrics_generator_v1_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pop_lyrics_generator_v1_pipeline` is a English model originally trained by smgriffin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pop_lyrics_generator_v1_pipeline_en_5.5.1_3.0_1737825443111.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pop_lyrics_generator_v1_pipeline_en_5.5.1_3.0_1737825443111.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("pop_lyrics_generator_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("pop_lyrics_generator_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pop_lyrics_generator_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/smgriffin/pop-lyrics-generator-v1
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-profanity2_1_en.md b/docs/_posts/ahmedlone127/2025-01-25-profanity2_1_en.md
new file mode 100644
index 00000000000000..02af1c0b9a74b4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-profanity2_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English profanity2_1 DistilBertForSequenceClassification from parsawar
+author: John Snow Labs
+name: profanity2_1
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`profanity2_1` is a English model originally trained by parsawar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/profanity2_1_en_5.5.1_3.0_1737811543101.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/profanity2_1_en_5.5.1_3.0_1737811543101.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("profanity2_1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("profanity2_1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|profanity2_1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/parsawar/Profanity2.1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-profanity2_1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-profanity2_1_pipeline_en.md
new file mode 100644
index 00000000000000..d1a570c7bb79dd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-profanity2_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English profanity2_1_pipeline pipeline DistilBertForSequenceClassification from parsawar
+author: John Snow Labs
+name: profanity2_1_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`profanity2_1_pipeline` is a English model originally trained by parsawar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/profanity2_1_pipeline_en_5.5.1_3.0_1737811556482.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/profanity2_1_pipeline_en_5.5.1_3.0_1737811556482.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("profanity2_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("profanity2_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|profanity2_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/parsawar/Profanity2.1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-promptgen_majinai_unsafe_en.md b/docs/_posts/ahmedlone127/2025-01-25-promptgen_majinai_unsafe_en.md
new file mode 100644
index 00000000000000..0bee082bd7cb4e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-promptgen_majinai_unsafe_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English promptgen_majinai_unsafe GPT2Transformer from AUTOMATIC
+author: John Snow Labs
+name: promptgen_majinai_unsafe
+date: 2025-01-25
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`promptgen_majinai_unsafe` is a English model originally trained by AUTOMATIC.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/promptgen_majinai_unsafe_en_5.5.1_3.0_1737771039429.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/promptgen_majinai_unsafe_en_5.5.1_3.0_1737771039429.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("promptgen_majinai_unsafe","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("promptgen_majinai_unsafe","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|promptgen_majinai_unsafe|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|308.4 MB|
+
+## References
+
+https://huggingface.co/AUTOMATIC/promptgen-majinai-unsafe
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-promptgen_majinai_unsafe_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-promptgen_majinai_unsafe_pipeline_en.md
new file mode 100644
index 00000000000000..6b06a65628163f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-promptgen_majinai_unsafe_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English promptgen_majinai_unsafe_pipeline pipeline GPT2Transformer from AUTOMATIC
+author: John Snow Labs
+name: promptgen_majinai_unsafe_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`promptgen_majinai_unsafe_pipeline` is a English model originally trained by AUTOMATIC.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/promptgen_majinai_unsafe_pipeline_en_5.5.1_3.0_1737771055845.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/promptgen_majinai_unsafe_pipeline_en_5.5.1_3.0_1737771055845.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("promptgen_majinai_unsafe_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("promptgen_majinai_unsafe_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|promptgen_majinai_unsafe_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|308.4 MB|
+
+## References
+
+https://huggingface.co/AUTOMATIC/promptgen-majinai-unsafe
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-pruned_50_model_en.md b/docs/_posts/ahmedlone127/2025-01-25-pruned_50_model_en.md
new file mode 100644
index 00000000000000..0db6ed4b4528d2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-pruned_50_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English pruned_50_model DistilBertForSequenceClassification from andygoh5
+author: John Snow Labs
+name: pruned_50_model
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pruned_50_model` is a English model originally trained by andygoh5.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pruned_50_model_en_5.5.1_3.0_1737822512427.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pruned_50_model_en_5.5.1_3.0_1737822512427.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("pruned_50_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("pruned_50_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pruned_50_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/andygoh5/pruned-50-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-pruned_50_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-pruned_50_model_pipeline_en.md
new file mode 100644
index 00000000000000..d0769e4df0c80d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-pruned_50_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English pruned_50_model_pipeline pipeline DistilBertForSequenceClassification from andygoh5
+author: John Snow Labs
+name: pruned_50_model_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pruned_50_model_pipeline` is a English model originally trained by andygoh5.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pruned_50_model_pipeline_en_5.5.1_3.0_1737822528267.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pruned_50_model_pipeline_en_5.5.1_3.0_1737822528267.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("pruned_50_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("pruned_50_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pruned_50_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/andygoh5/pruned-50-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-ptcrawl_base_v1_5__checkpoint2_en.md b/docs/_posts/ahmedlone127/2025-01-25-ptcrawl_base_v1_5__checkpoint2_en.md
new file mode 100644
index 00000000000000..16a6ff8be7ee2a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-ptcrawl_base_v1_5__checkpoint2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ptcrawl_base_v1_5__checkpoint2 RoBertaEmbeddings from eduagarcia-temp
+author: John Snow Labs
+name: ptcrawl_base_v1_5__checkpoint2
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ptcrawl_base_v1_5__checkpoint2` is a English model originally trained by eduagarcia-temp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ptcrawl_base_v1_5__checkpoint2_en_5.5.1_3.0_1737797094589.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ptcrawl_base_v1_5__checkpoint2_en_5.5.1_3.0_1737797094589.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("ptcrawl_base_v1_5__checkpoint2","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("ptcrawl_base_v1_5__checkpoint2","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ptcrawl_base_v1_5__checkpoint2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|296.9 MB|
+
+## References
+
+https://huggingface.co/eduagarcia-temp/ptcrawl_base_v1_5__checkpoint2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-ptcrawl_base_v1_5__checkpoint2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-ptcrawl_base_v1_5__checkpoint2_pipeline_en.md
new file mode 100644
index 00000000000000..84fff14d068f80
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-ptcrawl_base_v1_5__checkpoint2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ptcrawl_base_v1_5__checkpoint2_pipeline pipeline RoBertaEmbeddings from eduagarcia-temp
+author: John Snow Labs
+name: ptcrawl_base_v1_5__checkpoint2_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ptcrawl_base_v1_5__checkpoint2_pipeline` is a English model originally trained by eduagarcia-temp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ptcrawl_base_v1_5__checkpoint2_pipeline_en_5.5.1_3.0_1737797184084.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ptcrawl_base_v1_5__checkpoint2_pipeline_en_5.5.1_3.0_1737797184084.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ptcrawl_base_v1_5__checkpoint2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ptcrawl_base_v1_5__checkpoint2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ptcrawl_base_v1_5__checkpoint2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|296.9 MB|
+
+## References
+
+https://huggingface.co/eduagarcia-temp/ptcrawl_base_v1_5__checkpoint2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-qa_diet_mode_ver1_en.md b/docs/_posts/ahmedlone127/2025-01-25-qa_diet_mode_ver1_en.md
new file mode 100644
index 00000000000000..c1c0c4770d22ca
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-qa_diet_mode_ver1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English qa_diet_mode_ver1 DistilBertForQuestionAnswering from raihan02
+author: John Snow Labs
+name: qa_diet_mode_ver1
+date: 2025-01-25
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_diet_mode_ver1` is a English model originally trained by raihan02.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_diet_mode_ver1_en_5.5.1_3.0_1737823844254.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_diet_mode_ver1_en_5.5.1_3.0_1737823844254.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("qa_diet_mode_ver1","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("qa_diet_mode_ver1", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_diet_mode_ver1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/raihan02/qa_diet_mode_ver1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-qa_diet_mode_ver1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-qa_diet_mode_ver1_pipeline_en.md
new file mode 100644
index 00000000000000..0efdf2b29ecb34
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-qa_diet_mode_ver1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English qa_diet_mode_ver1_pipeline pipeline DistilBertForQuestionAnswering from raihan02
+author: John Snow Labs
+name: qa_diet_mode_ver1_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_diet_mode_ver1_pipeline` is a English model originally trained by raihan02.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_diet_mode_ver1_pipeline_en_5.5.1_3.0_1737823858282.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_diet_mode_ver1_pipeline_en_5.5.1_3.0_1737823858282.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("qa_diet_mode_ver1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("qa_diet_mode_ver1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_diet_mode_ver1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/raihan02/qa_diet_mode_ver1
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-qa_model11_test_en.md b/docs/_posts/ahmedlone127/2025-01-25-qa_model11_test_en.md
new file mode 100644
index 00000000000000..9316a5af44780d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-qa_model11_test_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English qa_model11_test BertForQuestionAnswering from MattNandavong
+author: John Snow Labs
+name: qa_model11_test
+date: 2025-01-25
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_model11_test` is a English model originally trained by MattNandavong.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_model11_test_en_5.5.1_3.0_1737813964701.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_model11_test_en_5.5.1_3.0_1737813964701.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("qa_model11_test","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("qa_model11_test", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_model11_test|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/MattNandavong/QA_model11-test
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-qa_model11_test_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-qa_model11_test_pipeline_en.md
new file mode 100644
index 00000000000000..6dda96bbb489ce
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-qa_model11_test_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English qa_model11_test_pipeline pipeline BertForQuestionAnswering from MattNandavong
+author: John Snow Labs
+name: qa_model11_test_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_model11_test_pipeline` is a English model originally trained by MattNandavong.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_model11_test_pipeline_en_5.5.1_3.0_1737814038626.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_model11_test_pipeline_en_5.5.1_3.0_1737814038626.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("qa_model11_test_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("qa_model11_test_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_model11_test_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/MattNandavong/QA_model11-test
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-qwen_textgen_model14_en.md b/docs/_posts/ahmedlone127/2025-01-25-qwen_textgen_model14_en.md
new file mode 100644
index 00000000000000..1ae59d979a50de
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-qwen_textgen_model14_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English qwen_textgen_model14 BertEmbeddings from JeloH
+author: John Snow Labs
+name: qwen_textgen_model14
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qwen_textgen_model14` is a English model originally trained by JeloH.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qwen_textgen_model14_en_5.5.1_3.0_1737821213492.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qwen_textgen_model14_en_5.5.1_3.0_1737821213492.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("qwen_textgen_model14","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("qwen_textgen_model14","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qwen_textgen_model14|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/JeloH/qwen-textgen-model14
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-qwen_textgen_model14_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-qwen_textgen_model14_pipeline_en.md
new file mode 100644
index 00000000000000..62497d56306a95
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-qwen_textgen_model14_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English qwen_textgen_model14_pipeline pipeline BertEmbeddings from JeloH
+author: John Snow Labs
+name: qwen_textgen_model14_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qwen_textgen_model14_pipeline` is a English model originally trained by JeloH.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qwen_textgen_model14_pipeline_en_5.5.1_3.0_1737821234784.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qwen_textgen_model14_pipeline_en_5.5.1_3.0_1737821234784.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("qwen_textgen_model14_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("qwen_textgen_model14_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qwen_textgen_model14_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/JeloH/qwen-textgen-model14
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-qwen_textgen_model15nnn_en.md b/docs/_posts/ahmedlone127/2025-01-25-qwen_textgen_model15nnn_en.md
new file mode 100644
index 00000000000000..bb3fa241c88533
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-qwen_textgen_model15nnn_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English qwen_textgen_model15nnn BertEmbeddings from JeloH
+author: John Snow Labs
+name: qwen_textgen_model15nnn
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qwen_textgen_model15nnn` is a English model originally trained by JeloH.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qwen_textgen_model15nnn_en_5.5.1_3.0_1737785194287.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qwen_textgen_model15nnn_en_5.5.1_3.0_1737785194287.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("qwen_textgen_model15nnn","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("qwen_textgen_model15nnn","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qwen_textgen_model15nnn|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/JeloH/qwen-textgen-model15nnn
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-qwen_textgen_model15nnn_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-qwen_textgen_model15nnn_pipeline_en.md
new file mode 100644
index 00000000000000..065b62d8720a5d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-qwen_textgen_model15nnn_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English qwen_textgen_model15nnn_pipeline pipeline BertEmbeddings from JeloH
+author: John Snow Labs
+name: qwen_textgen_model15nnn_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qwen_textgen_model15nnn_pipeline` is a English model originally trained by JeloH.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qwen_textgen_model15nnn_pipeline_en_5.5.1_3.0_1737785216215.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qwen_textgen_model15nnn_pipeline_en_5.5.1_3.0_1737785216215.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("qwen_textgen_model15nnn_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("qwen_textgen_model15nnn_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qwen_textgen_model15nnn_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/JeloH/qwen-textgen-model15nnn
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-randomly_pruned_70_model_en.md b/docs/_posts/ahmedlone127/2025-01-25-randomly_pruned_70_model_en.md
new file mode 100644
index 00000000000000..d2a6136d4f3910
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-randomly_pruned_70_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English randomly_pruned_70_model DistilBertForSequenceClassification from andygoh5
+author: John Snow Labs
+name: randomly_pruned_70_model
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`randomly_pruned_70_model` is a English model originally trained by andygoh5.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/randomly_pruned_70_model_en_5.5.1_3.0_1737822626716.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/randomly_pruned_70_model_en_5.5.1_3.0_1737822626716.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("randomly_pruned_70_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("randomly_pruned_70_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|randomly_pruned_70_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/andygoh5/randomly-pruned-70-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-randomly_pruned_70_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-randomly_pruned_70_model_pipeline_en.md
new file mode 100644
index 00000000000000..eccba18bfd7586
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-randomly_pruned_70_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English randomly_pruned_70_model_pipeline pipeline DistilBertForSequenceClassification from andygoh5
+author: John Snow Labs
+name: randomly_pruned_70_model_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`randomly_pruned_70_model_pipeline` is a English model originally trained by andygoh5.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/randomly_pruned_70_model_pipeline_en_5.5.1_3.0_1737822642197.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/randomly_pruned_70_model_pipeline_en_5.5.1_3.0_1737822642197.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("randomly_pruned_70_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("randomly_pruned_70_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|randomly_pruned_70_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/andygoh5/randomly-pruned-70-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-realdonaldtrump_en.md b/docs/_posts/ahmedlone127/2025-01-25-realdonaldtrump_en.md
new file mode 100644
index 00000000000000..a802792d68933d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-realdonaldtrump_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English realdonaldtrump GPT2Transformer from huggingtweets
+author: John Snow Labs
+name: realdonaldtrump
+date: 2025-01-25
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`realdonaldtrump` is a English model originally trained by huggingtweets.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/realdonaldtrump_en_5.5.1_3.0_1737764604039.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/realdonaldtrump_en_5.5.1_3.0_1737764604039.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("realdonaldtrump","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("realdonaldtrump","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|realdonaldtrump|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/huggingtweets/realdonaldtrump
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-realdonaldtrump_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-realdonaldtrump_pipeline_en.md
new file mode 100644
index 00000000000000..92e09bbc1ea033
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-realdonaldtrump_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English realdonaldtrump_pipeline pipeline GPT2Transformer from huggingtweets
+author: John Snow Labs
+name: realdonaldtrump_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`realdonaldtrump_pipeline` is a English model originally trained by huggingtweets.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/realdonaldtrump_pipeline_en_5.5.1_3.0_1737764628271.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/realdonaldtrump_pipeline_en_5.5.1_3.0_1737764628271.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("realdonaldtrump_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("realdonaldtrump_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|realdonaldtrump_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/huggingtweets/realdonaldtrump
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-resultados_en.md b/docs/_posts/ahmedlone127/2025-01-25-resultados_en.md
new file mode 100644
index 00000000000000..49ad4c24be5ed9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-resultados_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English resultados DistilBertForSequenceClassification from Cat-591
+author: John Snow Labs
+name: resultados
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`resultados` is a English model originally trained by Cat-591.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/resultados_en_5.5.1_3.0_1737836153608.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/resultados_en_5.5.1_3.0_1737836153608.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("resultados","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("resultados", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|resultados|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Cat-591/resultados
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-resultados_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-resultados_pipeline_en.md
new file mode 100644
index 00000000000000..f14703ab997234
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-resultados_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English resultados_pipeline pipeline DistilBertForSequenceClassification from Cat-591
+author: John Snow Labs
+name: resultados_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`resultados_pipeline` is a English model originally trained by Cat-591.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/resultados_pipeline_en_5.5.1_3.0_1737836170351.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/resultados_pipeline_en_5.5.1_3.0_1737836170351.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("resultados_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("resultados_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|resultados_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Cat-591/resultados
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-results9_en.md b/docs/_posts/ahmedlone127/2025-01-25-results9_en.md
new file mode 100644
index 00000000000000..612cedda6e39d2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-results9_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English results9 DistilBertForSequenceClassification from dianamihalache27
+author: John Snow Labs
+name: results9
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results9` is a English model originally trained by dianamihalache27.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results9_en_5.5.1_3.0_1737836152293.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results9_en_5.5.1_3.0_1737836152293.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("results9","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("results9", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results9|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/dianamihalache27/results9
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-results9_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-results9_pipeline_en.md
new file mode 100644
index 00000000000000..81304f8025ca07
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-results9_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English results9_pipeline pipeline DistilBertForSequenceClassification from dianamihalache27
+author: John Snow Labs
+name: results9_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results9_pipeline` is a English model originally trained by dianamihalache27.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results9_pipeline_en_5.5.1_3.0_1737836170185.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results9_pipeline_en_5.5.1_3.0_1737836170185.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("results9_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("results9_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results9_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/dianamihalache27/results9
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-results_apbrault_en.md b/docs/_posts/ahmedlone127/2025-01-25-results_apbrault_en.md
new file mode 100644
index 00000000000000..2e09cc7dd54662
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-results_apbrault_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English results_apbrault DistilBertForTokenClassification from apbrault
+author: John Snow Labs
+name: results_apbrault
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_apbrault` is a English model originally trained by apbrault.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_apbrault_en_5.5.1_3.0_1737764157123.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_apbrault_en_5.5.1_3.0_1737764157123.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("results_apbrault","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("results_apbrault", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_apbrault|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/apbrault/results
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-results_apbrault_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-results_apbrault_pipeline_en.md
new file mode 100644
index 00000000000000..9c5b02cb394eb7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-results_apbrault_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English results_apbrault_pipeline pipeline DistilBertForTokenClassification from apbrault
+author: John Snow Labs
+name: results_apbrault_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_apbrault_pipeline` is a English model originally trained by apbrault.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_apbrault_pipeline_en_5.5.1_3.0_1737764172984.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_apbrault_pipeline_en_5.5.1_3.0_1737764172984.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("results_apbrault_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("results_apbrault_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_apbrault_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/apbrault/results
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-results_cristianremiex_en.md b/docs/_posts/ahmedlone127/2025-01-25-results_cristianremiex_en.md
new file mode 100644
index 00000000000000..d21f392fe51faf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-results_cristianremiex_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English results_cristianremiex DistilBertForSequenceClassification from cristianremiex
+author: John Snow Labs
+name: results_cristianremiex
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_cristianremiex` is a English model originally trained by cristianremiex.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_cristianremiex_en_5.5.1_3.0_1737811653678.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_cristianremiex_en_5.5.1_3.0_1737811653678.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("results_cristianremiex","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("results_cristianremiex", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_cristianremiex|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/cristianremiex/results
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-results_cristianremiex_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-results_cristianremiex_pipeline_en.md
new file mode 100644
index 00000000000000..d3ff885d1814e1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-results_cristianremiex_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English results_cristianremiex_pipeline pipeline DistilBertForSequenceClassification from cristianremiex
+author: John Snow Labs
+name: results_cristianremiex_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_cristianremiex_pipeline` is a English model originally trained by cristianremiex.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_cristianremiex_pipeline_en_5.5.1_3.0_1737811667576.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_cristianremiex_pipeline_en_5.5.1_3.0_1737811667576.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("results_cristianremiex_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("results_cristianremiex_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_cristianremiex_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/cristianremiex/results
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-results_gayathridevirv_en.md b/docs/_posts/ahmedlone127/2025-01-25-results_gayathridevirv_en.md
new file mode 100644
index 00000000000000..3b03d0942dc81d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-results_gayathridevirv_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English results_gayathridevirv BertEmbeddings from gayathridevirv
+author: John Snow Labs
+name: results_gayathridevirv
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_gayathridevirv` is a English model originally trained by gayathridevirv.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_gayathridevirv_en_5.5.1_3.0_1737806574470.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_gayathridevirv_en_5.5.1_3.0_1737806574470.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("results_gayathridevirv","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("results_gayathridevirv","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_gayathridevirv|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|890.7 MB|
+
+## References
+
+https://huggingface.co/gayathridevirv/results
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-results_gayathridevirv_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-results_gayathridevirv_pipeline_en.md
new file mode 100644
index 00000000000000..21a504057476f9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-results_gayathridevirv_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English results_gayathridevirv_pipeline pipeline BertEmbeddings from gayathridevirv
+author: John Snow Labs
+name: results_gayathridevirv_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_gayathridevirv_pipeline` is a English model originally trained by gayathridevirv.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_gayathridevirv_pipeline_en_5.5.1_3.0_1737806620323.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_gayathridevirv_pipeline_en_5.5.1_3.0_1737806620323.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("results_gayathridevirv_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("results_gayathridevirv_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_gayathridevirv_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|890.7 MB|
+
+## References
+
+https://huggingface.co/gayathridevirv/results
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-results_ksushrut_en.md b/docs/_posts/ahmedlone127/2025-01-25-results_ksushrut_en.md
new file mode 100644
index 00000000000000..78adb3ad30533b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-results_ksushrut_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English results_ksushrut DistilBertForSequenceClassification from KSushrut
+author: John Snow Labs
+name: results_ksushrut
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_ksushrut` is a English model originally trained by KSushrut.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_ksushrut_en_5.5.1_3.0_1737822456199.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_ksushrut_en_5.5.1_3.0_1737822456199.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("results_ksushrut","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("results_ksushrut", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_ksushrut|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|243.2 MB|
+
+## References
+
+https://huggingface.co/KSushrut/results
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-results_ksushrut_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-results_ksushrut_pipeline_en.md
new file mode 100644
index 00000000000000..2429914ff8a79b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-results_ksushrut_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English results_ksushrut_pipeline pipeline DistilBertForSequenceClassification from KSushrut
+author: John Snow Labs
+name: results_ksushrut_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_ksushrut_pipeline` is a English model originally trained by KSushrut.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_ksushrut_pipeline_en_5.5.1_3.0_1737822470445.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_ksushrut_pipeline_en_5.5.1_3.0_1737822470445.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("results_ksushrut_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("results_ksushrut_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_ksushrut_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|243.3 MB|
+
+## References
+
+https://huggingface.co/KSushrut/results
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-results_suthanhcong_en.md b/docs/_posts/ahmedlone127/2025-01-25-results_suthanhcong_en.md
new file mode 100644
index 00000000000000..4821f8d02801cc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-results_suthanhcong_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English results_suthanhcong BertForQuestionAnswering from suthanhcong
+author: John Snow Labs
+name: results_suthanhcong
+date: 2025-01-25
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_suthanhcong` is a English model originally trained by suthanhcong.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_suthanhcong_en_5.5.1_3.0_1737813916199.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_suthanhcong_en_5.5.1_3.0_1737813916199.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("results_suthanhcong","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("results_suthanhcong", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_suthanhcong|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/suthanhcong/results
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-results_suthanhcong_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-results_suthanhcong_pipeline_en.md
new file mode 100644
index 00000000000000..d9c069011574f1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-results_suthanhcong_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English results_suthanhcong_pipeline pipeline BertForQuestionAnswering from suthanhcong
+author: John Snow Labs
+name: results_suthanhcong_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_suthanhcong_pipeline` is a English model originally trained by suthanhcong.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_suthanhcong_pipeline_en_5.5.1_3.0_1737813942017.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_suthanhcong_pipeline_en_5.5.1_3.0_1737813942017.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("results_suthanhcong_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("results_suthanhcong_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_suthanhcong_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/suthanhcong/results
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-results_taisiia7_en.md b/docs/_posts/ahmedlone127/2025-01-25-results_taisiia7_en.md
new file mode 100644
index 00000000000000..e0d6f8f7ce09c3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-results_taisiia7_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English results_taisiia7 T5Transformer from Taisiia7
+author: John Snow Labs
+name: results_taisiia7
+date: 2025-01-25
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_taisiia7` is a English model originally trained by Taisiia7.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_taisiia7_en_5.5.1_3.0_1737848543396.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_taisiia7_en_5.5.1_3.0_1737848543396.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("results_taisiia7","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("results_taisiia7", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_taisiia7|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|282.2 MB|
+
+## References
+
+https://huggingface.co/Taisiia7/results
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-results_taisiia7_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-results_taisiia7_pipeline_en.md
new file mode 100644
index 00000000000000..7cf60e8368cd61
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-results_taisiia7_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English results_taisiia7_pipeline pipeline T5Transformer from Taisiia7
+author: John Snow Labs
+name: results_taisiia7_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_taisiia7_pipeline` is a English model originally trained by Taisiia7.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_taisiia7_pipeline_en_5.5.1_3.0_1737848558521.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_taisiia7_pipeline_en_5.5.1_3.0_1737848558521.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("results_taisiia7_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("results_taisiia7_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_taisiia7_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|282.2 MB|
+
+## References
+
+https://huggingface.co/Taisiia7/results
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-results_yvzplay2_en.md b/docs/_posts/ahmedlone127/2025-01-25-results_yvzplay2_en.md
new file mode 100644
index 00000000000000..aac8d08cb93871
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-results_yvzplay2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English results_yvzplay2 DistilBertForSequenceClassification from yvzplay2
+author: John Snow Labs
+name: results_yvzplay2
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_yvzplay2` is a English model originally trained by yvzplay2.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_yvzplay2_en_5.5.1_3.0_1737838334358.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_yvzplay2_en_5.5.1_3.0_1737838334358.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("results_yvzplay2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("results_yvzplay2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_yvzplay2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/yvzplay2/results
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-results_yvzplay2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-results_yvzplay2_pipeline_en.md
new file mode 100644
index 00000000000000..5047a0c7ab4148
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-results_yvzplay2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English results_yvzplay2_pipeline pipeline DistilBertForSequenceClassification from yvzplay2
+author: John Snow Labs
+name: results_yvzplay2_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_yvzplay2_pipeline` is a English model originally trained by yvzplay2.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_yvzplay2_pipeline_en_5.5.1_3.0_1737838347008.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_yvzplay2_pipeline_en_5.5.1_3.0_1737838347008.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("results_yvzplay2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("results_yvzplay2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_yvzplay2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/yvzplay2/results
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-roberta_base_binary_ner_en.md b/docs/_posts/ahmedlone127/2025-01-25-roberta_base_binary_ner_en.md
new file mode 100644
index 00000000000000..bd253dcb63379d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-roberta_base_binary_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_base_binary_ner XlmRoBertaForTokenClassification from Mahesh098
+author: John Snow Labs
+name: roberta_base_binary_ner
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_binary_ner` is a English model originally trained by Mahesh098.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_binary_ner_en_5.5.1_3.0_1737790149636.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_binary_ner_en_5.5.1_3.0_1737790149636.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("roberta_base_binary_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("roberta_base_binary_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_binary_ner|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|831.6 MB|
+
+## References
+
+https://huggingface.co/Mahesh098/roberta-base-binary-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-roberta_base_binary_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-roberta_base_binary_ner_pipeline_en.md
new file mode 100644
index 00000000000000..a61207af49765d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-roberta_base_binary_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_base_binary_ner_pipeline pipeline XlmRoBertaForTokenClassification from Mahesh098
+author: John Snow Labs
+name: roberta_base_binary_ner_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_binary_ner_pipeline` is a English model originally trained by Mahesh098.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_binary_ner_pipeline_en_5.5.1_3.0_1737790266949.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_binary_ner_pipeline_en_5.5.1_3.0_1737790266949.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_base_binary_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_binary_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_binary_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|831.6 MB|
+
+## References
+
+https://huggingface.co/Mahesh098/roberta-base-binary-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-roberta_base_finetuned_bible_en.md b/docs/_posts/ahmedlone127/2025-01-25-roberta_base_finetuned_bible_en.md
new file mode 100644
index 00000000000000..f8b462f90212d6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-roberta_base_finetuned_bible_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_base_finetuned_bible RoBertaEmbeddings from Pragash-Mohanarajah
+author: John Snow Labs
+name: roberta_base_finetuned_bible
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_finetuned_bible` is a English model originally trained by Pragash-Mohanarajah.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_finetuned_bible_en_5.5.1_3.0_1737796892463.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_finetuned_bible_en_5.5.1_3.0_1737796892463.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("roberta_base_finetuned_bible","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("roberta_base_finetuned_bible","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_finetuned_bible|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|466.0 MB|
+
+## References
+
+https://huggingface.co/Pragash-Mohanarajah/roberta-base-finetuned-bible
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-roberta_base_finetuned_bible_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-roberta_base_finetuned_bible_pipeline_en.md
new file mode 100644
index 00000000000000..5e6037dbfba227
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-roberta_base_finetuned_bible_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_base_finetuned_bible_pipeline pipeline RoBertaEmbeddings from Pragash-Mohanarajah
+author: John Snow Labs
+name: roberta_base_finetuned_bible_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_finetuned_bible_pipeline` is a English model originally trained by Pragash-Mohanarajah.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_finetuned_bible_pipeline_en_5.5.1_3.0_1737796917684.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_finetuned_bible_pipeline_en_5.5.1_3.0_1737796917684.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_base_finetuned_bible_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_finetuned_bible_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_finetuned_bible_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.0 MB|
+
+## References
+
+https://huggingface.co/Pragash-Mohanarajah/roberta-base-finetuned-bible
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-roberta_base_finetuned_kintweetse_en.md b/docs/_posts/ahmedlone127/2025-01-25-roberta_base_finetuned_kintweetse_en.md
new file mode 100644
index 00000000000000..af1d791194f4f6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-roberta_base_finetuned_kintweetse_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_base_finetuned_kintweetse RoBertaEmbeddings from RogerB
+author: John Snow Labs
+name: roberta_base_finetuned_kintweetse
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_finetuned_kintweetse` is a English model originally trained by RogerB.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_finetuned_kintweetse_en_5.5.1_3.0_1737796657823.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_finetuned_kintweetse_en_5.5.1_3.0_1737796657823.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("roberta_base_finetuned_kintweetse","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("roberta_base_finetuned_kintweetse","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_finetuned_kintweetse|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|466.0 MB|
+
+## References
+
+https://huggingface.co/RogerB/roberta-base-finetuned-kintweetsE
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-roberta_base_finetuned_kintweetse_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-roberta_base_finetuned_kintweetse_pipeline_en.md
new file mode 100644
index 00000000000000..9f7cc201a3fe16
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-roberta_base_finetuned_kintweetse_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_base_finetuned_kintweetse_pipeline pipeline RoBertaEmbeddings from RogerB
+author: John Snow Labs
+name: roberta_base_finetuned_kintweetse_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_finetuned_kintweetse_pipeline` is a English model originally trained by RogerB.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_finetuned_kintweetse_pipeline_en_5.5.1_3.0_1737796685094.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_finetuned_kintweetse_pipeline_en_5.5.1_3.0_1737796685094.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_base_finetuned_kintweetse_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_finetuned_kintweetse_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_finetuned_kintweetse_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.1 MB|
+
+## References
+
+https://huggingface.co/RogerB/roberta-base-finetuned-kintweetsE
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-roberta_dhivehi_en.md b/docs/_posts/ahmedlone127/2025-01-25-roberta_dhivehi_en.md
new file mode 100644
index 00000000000000..fe628f33f4188a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-roberta_dhivehi_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_dhivehi RoBertaEmbeddings from alakxender
+author: John Snow Labs
+name: roberta_dhivehi
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_dhivehi` is a English model originally trained by alakxender.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_dhivehi_en_5.5.1_3.0_1737797518381.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_dhivehi_en_5.5.1_3.0_1737797518381.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("roberta_dhivehi","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("roberta_dhivehi","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_dhivehi|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|311.7 MB|
+
+## References
+
+https://huggingface.co/alakxender/roberta-dhivehi
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-roberta_dhivehi_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-roberta_dhivehi_pipeline_en.md
new file mode 100644
index 00000000000000..7d1b96cfa15dad
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-roberta_dhivehi_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_dhivehi_pipeline pipeline RoBertaEmbeddings from alakxender
+author: John Snow Labs
+name: roberta_dhivehi_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_dhivehi_pipeline` is a English model originally trained by alakxender.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_dhivehi_pipeline_en_5.5.1_3.0_1737797534745.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_dhivehi_pipeline_en_5.5.1_3.0_1737797534745.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_dhivehi_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_dhivehi_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_dhivehi_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|311.7 MB|
+
+## References
+
+https://huggingface.co/alakxender/roberta-dhivehi
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-roberta_large_tweetner7_en.md b/docs/_posts/ahmedlone127/2025-01-25-roberta_large_tweetner7_en.md
new file mode 100644
index 00000000000000..a6d7953dbf54b3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-roberta_large_tweetner7_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_large_tweetner7 RoBertaForTokenClassification from CheccoCando
+author: John Snow Labs
+name: roberta_large_tweetner7
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_tweetner7` is a English model originally trained by CheccoCando.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_tweetner7_en_5.5.1_3.0_1737808926243.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_tweetner7_en_5.5.1_3.0_1737808926243.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("roberta_large_tweetner7","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_large_tweetner7", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_large_tweetner7|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/CheccoCando/roberta-large_TweetNER7
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-roberta_large_tweetner7_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-roberta_large_tweetner7_pipeline_en.md
new file mode 100644
index 00000000000000..00866f9b9bcb27
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-roberta_large_tweetner7_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_large_tweetner7_pipeline pipeline RoBertaForTokenClassification from CheccoCando
+author: John Snow Labs
+name: roberta_large_tweetner7_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_tweetner7_pipeline` is a English model originally trained by CheccoCando.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_tweetner7_pipeline_en_5.5.1_3.0_1737808997234.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_tweetner7_pipeline_en_5.5.1_3.0_1737808997234.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_large_tweetner7_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_large_tweetner7_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_large_tweetner7_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/CheccoCando/roberta-large_TweetNER7
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-rubert_base_cased_russian_emotion_detection_russian_go_emotions_pipeline_ru.md b/docs/_posts/ahmedlone127/2025-01-25-rubert_base_cased_russian_emotion_detection_russian_go_emotions_pipeline_ru.md
new file mode 100644
index 00000000000000..693c268f8e8fe5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-rubert_base_cased_russian_emotion_detection_russian_go_emotions_pipeline_ru.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Russian rubert_base_cased_russian_emotion_detection_russian_go_emotions_pipeline pipeline BertForSequenceClassification from seara
+author: John Snow Labs
+name: rubert_base_cased_russian_emotion_detection_russian_go_emotions_pipeline
+date: 2025-01-25
+tags: [ru, open_source, pipeline, onnx]
+task: Text Classification
+language: ru
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_base_cased_russian_emotion_detection_russian_go_emotions_pipeline` is a Russian model originally trained by seara.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_base_cased_russian_emotion_detection_russian_go_emotions_pipeline_ru_5.5.1_3.0_1737840600545.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_base_cased_russian_emotion_detection_russian_go_emotions_pipeline_ru_5.5.1_3.0_1737840600545.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("rubert_base_cased_russian_emotion_detection_russian_go_emotions_pipeline", lang = "ru")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("rubert_base_cased_russian_emotion_detection_russian_go_emotions_pipeline", lang = "ru")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rubert_base_cased_russian_emotion_detection_russian_go_emotions_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ru|
+|Size:|666.6 MB|
+
+## References
+
+https://huggingface.co/seara/rubert-base-cased-russian-emotion-detection-ru-go-emotions
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-rubert_base_cased_russian_emotion_detection_russian_go_emotions_ru.md b/docs/_posts/ahmedlone127/2025-01-25-rubert_base_cased_russian_emotion_detection_russian_go_emotions_ru.md
new file mode 100644
index 00000000000000..887194456cee23
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-rubert_base_cased_russian_emotion_detection_russian_go_emotions_ru.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Russian rubert_base_cased_russian_emotion_detection_russian_go_emotions BertForSequenceClassification from seara
+author: John Snow Labs
+name: rubert_base_cased_russian_emotion_detection_russian_go_emotions
+date: 2025-01-25
+tags: [ru, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: ru
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_base_cased_russian_emotion_detection_russian_go_emotions` is a Russian model originally trained by seara.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_base_cased_russian_emotion_detection_russian_go_emotions_ru_5.5.1_3.0_1737840568073.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_base_cased_russian_emotion_detection_russian_go_emotions_ru_5.5.1_3.0_1737840568073.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("rubert_base_cased_russian_emotion_detection_russian_go_emotions","ru") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("rubert_base_cased_russian_emotion_detection_russian_go_emotions", "ru")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rubert_base_cased_russian_emotion_detection_russian_go_emotions|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|ru|
+|Size:|666.6 MB|
+
+## References
+
+https://huggingface.co/seara/rubert-base-cased-russian-emotion-detection-ru-go-emotions
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-rubert_base_cased_sayula_popoluca_en.md b/docs/_posts/ahmedlone127/2025-01-25-rubert_base_cased_sayula_popoluca_en.md
new file mode 100644
index 00000000000000..113e7638266662
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-rubert_base_cased_sayula_popoluca_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English rubert_base_cased_sayula_popoluca BertForTokenClassification from DimasikKurd
+author: John Snow Labs
+name: rubert_base_cased_sayula_popoluca
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_base_cased_sayula_popoluca` is a English model originally trained by DimasikKurd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_base_cased_sayula_popoluca_en_5.5.1_3.0_1737845239083.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_base_cased_sayula_popoluca_en_5.5.1_3.0_1737845239083.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("rubert_base_cased_sayula_popoluca","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("rubert_base_cased_sayula_popoluca", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rubert_base_cased_sayula_popoluca|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|664.3 MB|
+
+## References
+
+https://huggingface.co/DimasikKurd/rubert-base-cased_pos
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-rubert_base_cased_sayula_popoluca_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-rubert_base_cased_sayula_popoluca_pipeline_en.md
new file mode 100644
index 00000000000000..53f5f102307d31
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-rubert_base_cased_sayula_popoluca_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English rubert_base_cased_sayula_popoluca_pipeline pipeline BertForTokenClassification from DimasikKurd
+author: John Snow Labs
+name: rubert_base_cased_sayula_popoluca_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_base_cased_sayula_popoluca_pipeline` is a English model originally trained by DimasikKurd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_base_cased_sayula_popoluca_pipeline_en_5.5.1_3.0_1737845271306.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_base_cased_sayula_popoluca_pipeline_en_5.5.1_3.0_1737845271306.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("rubert_base_cased_sayula_popoluca_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("rubert_base_cased_sayula_popoluca_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rubert_base_cased_sayula_popoluca_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|664.3 MB|
+
+## References
+
+https://huggingface.co/DimasikKurd/rubert-base-cased_pos
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-rubert_base_finetuned_macedonian_en.md b/docs/_posts/ahmedlone127/2025-01-25-rubert_base_finetuned_macedonian_en.md
new file mode 100644
index 00000000000000..1ad0e8cbc71ecb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-rubert_base_finetuned_macedonian_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English rubert_base_finetuned_macedonian BertEmbeddings from Anya-hse
+author: John Snow Labs
+name: rubert_base_finetuned_macedonian
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_base_finetuned_macedonian` is a English model originally trained by Anya-hse.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_base_finetuned_macedonian_en_5.5.1_3.0_1737806451221.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_base_finetuned_macedonian_en_5.5.1_3.0_1737806451221.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("rubert_base_finetuned_macedonian","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("rubert_base_finetuned_macedonian","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rubert_base_finetuned_macedonian|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|667.1 MB|
+
+## References
+
+https://huggingface.co/Anya-hse/ruBert-base-finetuned-mk
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-rubert_base_finetuned_macedonian_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-rubert_base_finetuned_macedonian_pipeline_en.md
new file mode 100644
index 00000000000000..418435177f342e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-rubert_base_finetuned_macedonian_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English rubert_base_finetuned_macedonian_pipeline pipeline BertEmbeddings from Anya-hse
+author: John Snow Labs
+name: rubert_base_finetuned_macedonian_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_base_finetuned_macedonian_pipeline` is a English model originally trained by Anya-hse.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_base_finetuned_macedonian_pipeline_en_5.5.1_3.0_1737806486427.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_base_finetuned_macedonian_pipeline_en_5.5.1_3.0_1737806486427.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("rubert_base_finetuned_macedonian_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("rubert_base_finetuned_macedonian_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rubert_base_finetuned_macedonian_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|667.1 MB|
+
+## References
+
+https://huggingface.co/Anya-hse/ruBert-base-finetuned-mk
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-rubert_base_sakha_en.md b/docs/_posts/ahmedlone127/2025-01-25-rubert_base_sakha_en.md
new file mode 100644
index 00000000000000..4962bb38e94a2f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-rubert_base_sakha_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English rubert_base_sakha BertEmbeddings from bamaxi
+author: John Snow Labs
+name: rubert_base_sakha
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_base_sakha` is a English model originally trained by bamaxi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_base_sakha_en_5.5.1_3.0_1737807159563.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_base_sakha_en_5.5.1_3.0_1737807159563.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("rubert_base_sakha","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("rubert_base_sakha","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rubert_base_sakha|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|746.5 MB|
+
+## References
+
+https://huggingface.co/bamaxi/ruBert-base-sakha
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-rubert_base_sakha_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-rubert_base_sakha_pipeline_en.md
new file mode 100644
index 00000000000000..0ebc9b1a00ecc0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-rubert_base_sakha_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English rubert_base_sakha_pipeline pipeline BertEmbeddings from bamaxi
+author: John Snow Labs
+name: rubert_base_sakha_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_base_sakha_pipeline` is a English model originally trained by bamaxi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_base_sakha_pipeline_en_5.5.1_3.0_1737807198499.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_base_sakha_pipeline_en_5.5.1_3.0_1737807198499.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("rubert_base_sakha_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("rubert_base_sakha_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rubert_base_sakha_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|746.5 MB|
+
+## References
+
+https://huggingface.co/bamaxi/ruBert-base-sakha
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-rubert_emotion_slicer_pipeline_ru.md b/docs/_posts/ahmedlone127/2025-01-25-rubert_emotion_slicer_pipeline_ru.md
new file mode 100644
index 00000000000000..5970d23bde1c43
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-rubert_emotion_slicer_pipeline_ru.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Russian rubert_emotion_slicer_pipeline pipeline BertForSequenceClassification from Kostya165
+author: John Snow Labs
+name: rubert_emotion_slicer_pipeline
+date: 2025-01-25
+tags: [ru, open_source, pipeline, onnx]
+task: Text Classification
+language: ru
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_emotion_slicer_pipeline` is a Russian model originally trained by Kostya165.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_emotion_slicer_pipeline_ru_5.5.1_3.0_1737840139781.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_emotion_slicer_pipeline_ru_5.5.1_3.0_1737840139781.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("rubert_emotion_slicer_pipeline", lang = "ru")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("rubert_emotion_slicer_pipeline", lang = "ru")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rubert_emotion_slicer_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ru|
+|Size:|664.5 MB|
+
+## References
+
+https://huggingface.co/Kostya165/rubert_emotion_slicer
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-rubert_emotion_slicer_ru.md b/docs/_posts/ahmedlone127/2025-01-25-rubert_emotion_slicer_ru.md
new file mode 100644
index 00000000000000..0d97f1a73731ab
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-rubert_emotion_slicer_ru.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Russian rubert_emotion_slicer BertForSequenceClassification from Kostya165
+author: John Snow Labs
+name: rubert_emotion_slicer
+date: 2025-01-25
+tags: [ru, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: ru
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_emotion_slicer` is a Russian model originally trained by Kostya165.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_emotion_slicer_ru_5.5.1_3.0_1737840105318.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_emotion_slicer_ru_5.5.1_3.0_1737840105318.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("rubert_emotion_slicer","ru") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("rubert_emotion_slicer", "ru")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rubert_emotion_slicer|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|ru|
+|Size:|664.5 MB|
+
+## References
+
+https://huggingface.co/Kostya165/rubert_emotion_slicer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-rubert_tiny2_finetuned_imdb_en.md b/docs/_posts/ahmedlone127/2025-01-25-rubert_tiny2_finetuned_imdb_en.md
new file mode 100644
index 00000000000000..0a438ec96fb3ce
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-rubert_tiny2_finetuned_imdb_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English rubert_tiny2_finetuned_imdb BertEmbeddings from Pastushoc
+author: John Snow Labs
+name: rubert_tiny2_finetuned_imdb
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_tiny2_finetuned_imdb` is a English model originally trained by Pastushoc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_tiny2_finetuned_imdb_en_5.5.1_3.0_1737820660439.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_tiny2_finetuned_imdb_en_5.5.1_3.0_1737820660439.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("rubert_tiny2_finetuned_imdb","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("rubert_tiny2_finetuned_imdb","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rubert_tiny2_finetuned_imdb|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|109.0 MB|
+
+## References
+
+https://huggingface.co/Pastushoc/rubert-tiny2-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-rubert_tiny2_finetuned_imdb_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-rubert_tiny2_finetuned_imdb_pipeline_en.md
new file mode 100644
index 00000000000000..6ad7d9f299411a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-rubert_tiny2_finetuned_imdb_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English rubert_tiny2_finetuned_imdb_pipeline pipeline BertEmbeddings from Pastushoc
+author: John Snow Labs
+name: rubert_tiny2_finetuned_imdb_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_tiny2_finetuned_imdb_pipeline` is a English model originally trained by Pastushoc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_tiny2_finetuned_imdb_pipeline_en_5.5.1_3.0_1737820666100.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_tiny2_finetuned_imdb_pipeline_en_5.5.1_3.0_1737820666100.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("rubert_tiny2_finetuned_imdb_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("rubert_tiny2_finetuned_imdb_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rubert_tiny2_finetuned_imdb_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|109.0 MB|
+
+## References
+
+https://huggingface.co/Pastushoc/rubert-tiny2-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-rubert_tiny2_odonata_f3_ner_en.md b/docs/_posts/ahmedlone127/2025-01-25-rubert_tiny2_odonata_f3_ner_en.md
new file mode 100644
index 00000000000000..1c1933933154c8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-rubert_tiny2_odonata_f3_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English rubert_tiny2_odonata_f3_ner BertForTokenClassification from Ilya-Nazimov
+author: John Snow Labs
+name: rubert_tiny2_odonata_f3_ner
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_tiny2_odonata_f3_ner` is a English model originally trained by Ilya-Nazimov.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_tiny2_odonata_f3_ner_en_5.5.1_3.0_1737844228957.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_tiny2_odonata_f3_ner_en_5.5.1_3.0_1737844228957.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("rubert_tiny2_odonata_f3_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("rubert_tiny2_odonata_f3_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rubert_tiny2_odonata_f3_ner|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|109.1 MB|
+
+## References
+
+https://huggingface.co/Ilya-Nazimov/rubert-tiny2-odonata-f3-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-rubert_tiny2_odonata_f3_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-rubert_tiny2_odonata_f3_ner_pipeline_en.md
new file mode 100644
index 00000000000000..af42f5720bb8fe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-rubert_tiny2_odonata_f3_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English rubert_tiny2_odonata_f3_ner_pipeline pipeline BertForTokenClassification from Ilya-Nazimov
+author: John Snow Labs
+name: rubert_tiny2_odonata_f3_ner_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_tiny2_odonata_f3_ner_pipeline` is a English model originally trained by Ilya-Nazimov.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_tiny2_odonata_f3_ner_pipeline_en_5.5.1_3.0_1737844234470.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_tiny2_odonata_f3_ner_pipeline_en_5.5.1_3.0_1737844234470.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("rubert_tiny2_odonata_f3_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("rubert_tiny2_odonata_f3_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rubert_tiny2_odonata_f3_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|109.2 MB|
+
+## References
+
+https://huggingface.co/Ilya-Nazimov/rubert-tiny2-odonata-f3-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-rubert_tiny_nli_terra_v0_pipeline_ru.md b/docs/_posts/ahmedlone127/2025-01-25-rubert_tiny_nli_terra_v0_pipeline_ru.md
new file mode 100644
index 00000000000000..f2206dba44f73f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-rubert_tiny_nli_terra_v0_pipeline_ru.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Russian rubert_tiny_nli_terra_v0_pipeline pipeline BertForSequenceClassification from Marwolaeth
+author: John Snow Labs
+name: rubert_tiny_nli_terra_v0_pipeline
+date: 2025-01-25
+tags: [ru, open_source, pipeline, onnx]
+task: Text Classification
+language: ru
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_tiny_nli_terra_v0_pipeline` is a Russian model originally trained by Marwolaeth.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_tiny_nli_terra_v0_pipeline_ru_5.5.1_3.0_1737801287916.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_tiny_nli_terra_v0_pipeline_ru_5.5.1_3.0_1737801287916.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("rubert_tiny_nli_terra_v0_pipeline", lang = "ru")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("rubert_tiny_nli_terra_v0_pipeline", lang = "ru")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rubert_tiny_nli_terra_v0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ru|
+|Size:|69.6 MB|
+
+## References
+
+https://huggingface.co/Marwolaeth/rubert-tiny-nli-terra-v0
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-rubert_tiny_nli_terra_v0_ru.md b/docs/_posts/ahmedlone127/2025-01-25-rubert_tiny_nli_terra_v0_ru.md
new file mode 100644
index 00000000000000..bb13709ac4db8f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-rubert_tiny_nli_terra_v0_ru.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Russian rubert_tiny_nli_terra_v0 BertForSequenceClassification from Marwolaeth
+author: John Snow Labs
+name: rubert_tiny_nli_terra_v0
+date: 2025-01-25
+tags: [ru, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: ru
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_tiny_nli_terra_v0` is a Russian model originally trained by Marwolaeth.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_tiny_nli_terra_v0_ru_5.5.1_3.0_1737801268218.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_tiny_nli_terra_v0_ru_5.5.1_3.0_1737801268218.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("rubert_tiny_nli_terra_v0","ru") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("rubert_tiny_nli_terra_v0", "ru")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rubert_tiny_nli_terra_v0|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|ru|
+|Size:|69.6 MB|
+
+## References
+
+https://huggingface.co/Marwolaeth/rubert-tiny-nli-terra-v0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-rubert_tiny_two_example_en.md b/docs/_posts/ahmedlone127/2025-01-25-rubert_tiny_two_example_en.md
new file mode 100644
index 00000000000000..94df066ba2fc8a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-rubert_tiny_two_example_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English rubert_tiny_two_example BertForTokenClassification from Ilya-Nazimov
+author: John Snow Labs
+name: rubert_tiny_two_example
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_tiny_two_example` is a English model originally trained by Ilya-Nazimov.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_tiny_two_example_en_5.5.1_3.0_1737835288943.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_tiny_two_example_en_5.5.1_3.0_1737835288943.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("rubert_tiny_two_example","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("rubert_tiny_two_example", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rubert_tiny_two_example|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|109.1 MB|
+
+## References
+
+https://huggingface.co/Ilya-Nazimov/rubert-tiny-two-example
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-rubert_tiny_two_example_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-rubert_tiny_two_example_pipeline_en.md
new file mode 100644
index 00000000000000..767c1f7757a734
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-rubert_tiny_two_example_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English rubert_tiny_two_example_pipeline pipeline BertForTokenClassification from Ilya-Nazimov
+author: John Snow Labs
+name: rubert_tiny_two_example_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_tiny_two_example_pipeline` is a English model originally trained by Ilya-Nazimov.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_tiny_two_example_pipeline_en_5.5.1_3.0_1737835294592.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_tiny_two_example_pipeline_en_5.5.1_3.0_1737835294592.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("rubert_tiny_two_example_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("rubert_tiny_two_example_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rubert_tiny_two_example_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|109.2 MB|
+
+## References
+
+https://huggingface.co/Ilya-Nazimov/rubert-tiny-two-example
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-rundi_20240605101542_en.md b/docs/_posts/ahmedlone127/2025-01-25-rundi_20240605101542_en.md
new file mode 100644
index 00000000000000..8e63197db7c767
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-rundi_20240605101542_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English rundi_20240605101542 BertForTokenClassification from nttaii
+author: John Snow Labs
+name: rundi_20240605101542
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rundi_20240605101542` is a English model originally trained by nttaii.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rundi_20240605101542_en_5.5.1_3.0_1737845223581.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rundi_20240605101542_en_5.5.1_3.0_1737845223581.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("rundi_20240605101542","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("rundi_20240605101542", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rundi_20240605101542|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|665.2 MB|
+
+## References
+
+https://huggingface.co/nttaii/run_20240605101542
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-rundi_20240605101542_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-rundi_20240605101542_pipeline_en.md
new file mode 100644
index 00000000000000..7c9d93ff2a5db0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-rundi_20240605101542_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English rundi_20240605101542_pipeline pipeline BertForTokenClassification from nttaii
+author: John Snow Labs
+name: rundi_20240605101542_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rundi_20240605101542_pipeline` is a English model originally trained by nttaii.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rundi_20240605101542_pipeline_en_5.5.1_3.0_1737845255755.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rundi_20240605101542_pipeline_en_5.5.1_3.0_1737845255755.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("rundi_20240605101542_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("rundi_20240605101542_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rundi_20240605101542_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|665.2 MB|
+
+## References
+
+https://huggingface.co/nttaii/run_20240605101542
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-rundi_20240606175347_en.md b/docs/_posts/ahmedlone127/2025-01-25-rundi_20240606175347_en.md
new file mode 100644
index 00000000000000..d48a77f8d7821e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-rundi_20240606175347_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English rundi_20240606175347 BertForTokenClassification from nttaii
+author: John Snow Labs
+name: rundi_20240606175347
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rundi_20240606175347` is a English model originally trained by nttaii.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rundi_20240606175347_en_5.5.1_3.0_1737844861979.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rundi_20240606175347_en_5.5.1_3.0_1737844861979.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("rundi_20240606175347","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("rundi_20240606175347", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rundi_20240606175347|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|665.2 MB|
+
+## References
+
+https://huggingface.co/nttaii/run_20240606175347
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-rundi_20240606175347_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-rundi_20240606175347_pipeline_en.md
new file mode 100644
index 00000000000000..46d5311fb87a7f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-rundi_20240606175347_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English rundi_20240606175347_pipeline pipeline BertForTokenClassification from nttaii
+author: John Snow Labs
+name: rundi_20240606175347_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rundi_20240606175347_pipeline` is a English model originally trained by nttaii.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rundi_20240606175347_pipeline_en_5.5.1_3.0_1737844895161.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rundi_20240606175347_pipeline_en_5.5.1_3.0_1737844895161.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("rundi_20240606175347_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("rundi_20240606175347_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rundi_20240606175347_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|665.2 MB|
+
+## References
+
+https://huggingface.co/nttaii/run_20240606175347
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-s14_en.md b/docs/_posts/ahmedlone127/2025-01-25-s14_en.md
new file mode 100644
index 00000000000000..040fcb832af037
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-s14_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English s14 BertForQuestionAnswering from ShynBui
+author: John Snow Labs
+name: s14
+date: 2025-01-25
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`s14` is a English model originally trained by ShynBui.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/s14_en_5.5.1_3.0_1737812997605.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/s14_en_5.5.1_3.0_1737812997605.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("s14","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("s14", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|s14|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.5 MB|
+
+## References
+
+https://huggingface.co/ShynBui/s14
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-s14_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-s14_pipeline_en.md
new file mode 100644
index 00000000000000..487d7da6864957
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-s14_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English s14_pipeline pipeline BertForQuestionAnswering from ShynBui
+author: John Snow Labs
+name: s14_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`s14_pipeline` is a English model originally trained by ShynBui.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/s14_pipeline_en_5.5.1_3.0_1737813018757.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/s14_pipeline_en_5.5.1_3.0_1737813018757.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("s14_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("s14_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|s14_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.5 MB|
+
+## References
+
+https://huggingface.co/ShynBui/s14
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-s20_en.md b/docs/_posts/ahmedlone127/2025-01-25-s20_en.md
new file mode 100644
index 00000000000000..f159dd2a22f01e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-s20_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English s20 BertForQuestionAnswering from ShynBui
+author: John Snow Labs
+name: s20
+date: 2025-01-25
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`s20` is a English model originally trained by ShynBui.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/s20_en_5.5.1_3.0_1737813651226.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/s20_en_5.5.1_3.0_1737813651226.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("s20","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("s20", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|s20|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.2 MB|
+
+## References
+
+https://huggingface.co/ShynBui/s20
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-s20_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-s20_pipeline_en.md
new file mode 100644
index 00000000000000..dd60a62e9cefa4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-s20_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English s20_pipeline pipeline BertForQuestionAnswering from ShynBui
+author: John Snow Labs
+name: s20_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`s20_pipeline` is a English model originally trained by ShynBui.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/s20_pipeline_en_5.5.1_3.0_1737813674855.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/s20_pipeline_en_5.5.1_3.0_1737813674855.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("s20_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("s20_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|s20_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.2 MB|
+
+## References
+
+https://huggingface.co/ShynBui/s20
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-sarcastic_01_en.md b/docs/_posts/ahmedlone127/2025-01-25-sarcastic_01_en.md
new file mode 100644
index 00000000000000..8dae4627c153fd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-sarcastic_01_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sarcastic_01 DistilBertForSequenceClassification from PietroSaveri
+author: John Snow Labs
+name: sarcastic_01
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sarcastic_01` is a English model originally trained by PietroSaveri.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sarcastic_01_en_5.5.1_3.0_1737822285714.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sarcastic_01_en_5.5.1_3.0_1737822285714.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("sarcastic_01","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("sarcastic_01", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sarcastic_01|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|246.0 MB|
+
+## References
+
+https://huggingface.co/PietroSaveri/Sarcastic_01
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-sarcastic_01_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-sarcastic_01_pipeline_en.md
new file mode 100644
index 00000000000000..0972ef6a2288fb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-sarcastic_01_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English sarcastic_01_pipeline pipeline DistilBertForSequenceClassification from PietroSaveri
+author: John Snow Labs
+name: sarcastic_01_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sarcastic_01_pipeline` is a English model originally trained by PietroSaveri.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sarcastic_01_pipeline_en_5.5.1_3.0_1737822298580.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sarcastic_01_pipeline_en_5.5.1_3.0_1737822298580.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sarcastic_01_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sarcastic_01_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sarcastic_01_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|246.0 MB|
+
+## References
+
+https://huggingface.co/PietroSaveri/Sarcastic_01
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-sbert_large_nlu_russian_sayula_popoluca_en.md b/docs/_posts/ahmedlone127/2025-01-25-sbert_large_nlu_russian_sayula_popoluca_en.md
new file mode 100644
index 00000000000000..883774065f22ee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-sbert_large_nlu_russian_sayula_popoluca_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sbert_large_nlu_russian_sayula_popoluca BertForTokenClassification from DimasikKurd
+author: John Snow Labs
+name: sbert_large_nlu_russian_sayula_popoluca
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sbert_large_nlu_russian_sayula_popoluca` is a English model originally trained by DimasikKurd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sbert_large_nlu_russian_sayula_popoluca_en_5.5.1_3.0_1737844042333.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sbert_large_nlu_russian_sayula_popoluca_en_5.5.1_3.0_1737844042333.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("sbert_large_nlu_russian_sayula_popoluca","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("sbert_large_nlu_russian_sayula_popoluca", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sbert_large_nlu_russian_sayula_popoluca|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/DimasikKurd/sbert_large_nlu_ru_pos
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-sbert_large_nlu_russian_sayula_popoluca_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-sbert_large_nlu_russian_sayula_popoluca_pipeline_en.md
new file mode 100644
index 00000000000000..eb580477569d73
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-sbert_large_nlu_russian_sayula_popoluca_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English sbert_large_nlu_russian_sayula_popoluca_pipeline pipeline BertForTokenClassification from DimasikKurd
+author: John Snow Labs
+name: sbert_large_nlu_russian_sayula_popoluca_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sbert_large_nlu_russian_sayula_popoluca_pipeline` is a English model originally trained by DimasikKurd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sbert_large_nlu_russian_sayula_popoluca_pipeline_en_5.5.1_3.0_1737844119977.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sbert_large_nlu_russian_sayula_popoluca_pipeline_en_5.5.1_3.0_1737844119977.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sbert_large_nlu_russian_sayula_popoluca_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sbert_large_nlu_russian_sayula_popoluca_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sbert_large_nlu_russian_sayula_popoluca_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/DimasikKurd/sbert_large_nlu_ru_pos
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-scenario_tcr_data_cl_cardiff_cl_only1_en.md b/docs/_posts/ahmedlone127/2025-01-25-scenario_tcr_data_cl_cardiff_cl_only1_en.md
new file mode 100644
index 00000000000000..bd9a249f052e1b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-scenario_tcr_data_cl_cardiff_cl_only1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English scenario_tcr_data_cl_cardiff_cl_only1 XlmRoBertaForSequenceClassification from haryoaw
+author: John Snow Labs
+name: scenario_tcr_data_cl_cardiff_cl_only1
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scenario_tcr_data_cl_cardiff_cl_only1` is a English model originally trained by haryoaw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/scenario_tcr_data_cl_cardiff_cl_only1_en_5.5.1_3.0_1737815461321.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scenario_tcr_data_cl_cardiff_cl_only1_en_5.5.1_3.0_1737815461321.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("scenario_tcr_data_cl_cardiff_cl_only1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("scenario_tcr_data_cl_cardiff_cl_only1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|scenario_tcr_data_cl_cardiff_cl_only1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|850.1 MB|
+
+## References
+
+https://huggingface.co/haryoaw/scenario-TCR_data-cl-cardiff_cl_only1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-scenario_tcr_data_cl_cardiff_cl_only1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-scenario_tcr_data_cl_cardiff_cl_only1_pipeline_en.md
new file mode 100644
index 00000000000000..e26a924284ebec
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-scenario_tcr_data_cl_cardiff_cl_only1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English scenario_tcr_data_cl_cardiff_cl_only1_pipeline pipeline XlmRoBertaForSequenceClassification from haryoaw
+author: John Snow Labs
+name: scenario_tcr_data_cl_cardiff_cl_only1_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scenario_tcr_data_cl_cardiff_cl_only1_pipeline` is a English model originally trained by haryoaw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/scenario_tcr_data_cl_cardiff_cl_only1_pipeline_en_5.5.1_3.0_1737815546938.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scenario_tcr_data_cl_cardiff_cl_only1_pipeline_en_5.5.1_3.0_1737815546938.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("scenario_tcr_data_cl_cardiff_cl_only1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("scenario_tcr_data_cl_cardiff_cl_only1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|scenario_tcr_data_cl_cardiff_cl_only1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|850.1 MB|
+
+## References
+
+https://huggingface.co/haryoaw/scenario-TCR_data-cl-cardiff_cl_only1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-securebert_en.md b/docs/_posts/ahmedlone127/2025-01-25-securebert_en.md
new file mode 100644
index 00000000000000..7525fc4e2cb35e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-securebert_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English securebert RoBertaForSequenceClassification from ltkw98
+author: John Snow Labs
+name: securebert
+date: 2025-01-25
+tags: [roberta, en, open_source, sequence_classification, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`securebert` is a English model originally trained by ltkw98.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/securebert_en_5.5.1_3.0_1737797174686.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/securebert_en_5.5.1_3.0_1737797174686.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = DocumentAssembler()\
+    .setInputCol("text")\
+    .setOutputCol("document")
+
+tokenizer = Tokenizer()\
+    .setInputCols("document")\
+    .setOutputCol("token")  
+    
+sequenceClassifier = RoBertaForSequenceClassification.pretrained("securebert","en")\
+            .setInputCols(["document","token"])\
+            .setOutputCol("class")
+
+pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val document_assembler = new DocumentAssembler()
+    .setInputCol("text")
+    .setOutputCol("document")
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document") 
+    .setOutputCol("token")  
+    
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("securebert","en")
+            .setInputCols(Array("document","token"))
+            .setOutputCol("class")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|securebert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|466.1 MB|
+
+## References
+
+References
+
+References
+
+https://huggingface.co/ltkw98/SecureBert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-securebert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-securebert_pipeline_en.md
new file mode 100644
index 00000000000000..58ea6b6c03d510
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-securebert_pipeline_en.md
@@ -0,0 +1,72 @@
+---
+layout: model
+title: English securebert_pipeline pipeline RoBertaEmbeddings from ehsanaghaei
+author: John Snow Labs
+name: securebert_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`securebert_pipeline` is a English model originally trained by ehsanaghaei.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/securebert_pipeline_en_5.5.1_3.0_1737797199823.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/securebert_pipeline_en_5.5.1_3.0_1737797199823.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("securebert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("securebert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|securebert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.1 MB|
+
+## References
+
+References
+
+https://huggingface.co/ehsanaghaei/SecureBERT
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-sentence_correction_en.md b/docs/_posts/ahmedlone127/2025-01-25-sentence_correction_en.md
new file mode 100644
index 00000000000000..35946b6c4d35f3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-sentence_correction_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English sentence_correction T5Transformer from ayakiri
+author: John Snow Labs
+name: sentence_correction
+date: 2025-01-25
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentence_correction` is a English model originally trained by ayakiri.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentence_correction_en_5.5.1_3.0_1737848957394.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentence_correction_en_5.5.1_3.0_1737848957394.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("sentence_correction","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("sentence_correction", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sentence_correction|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|277.2 MB|
+
+## References
+
+https://huggingface.co/ayakiri/sentence-correction
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-sentence_correction_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-sentence_correction_pipeline_en.md
new file mode 100644
index 00000000000000..d50e02f6e8494e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-sentence_correction_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English sentence_correction_pipeline pipeline T5Transformer from ayakiri
+author: John Snow Labs
+name: sentence_correction_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentence_correction_pipeline` is a English model originally trained by ayakiri.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentence_correction_pipeline_en_5.5.1_3.0_1737848975941.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentence_correction_pipeline_en_5.5.1_3.0_1737848975941.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sentence_correction_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sentence_correction_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sentence_correction_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|277.2 MB|
+
+## References
+
+https://huggingface.co/ayakiri/sentence-correction
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-sentiment_analysis_nlp_en.md b/docs/_posts/ahmedlone127/2025-01-25-sentiment_analysis_nlp_en.md
new file mode 100644
index 00000000000000..29f870b4b4d858
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-sentiment_analysis_nlp_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sentiment_analysis_nlp DistilBertForSequenceClassification from aliciiavs
+author: John Snow Labs
+name: sentiment_analysis_nlp
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentiment_analysis_nlp` is a English model originally trained by aliciiavs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentiment_analysis_nlp_en_5.5.1_3.0_1737837761741.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentiment_analysis_nlp_en_5.5.1_3.0_1737837761741.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("sentiment_analysis_nlp","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("sentiment_analysis_nlp", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sentiment_analysis_nlp|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/aliciiavs/sentiment-analysis-nlp
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-sentiment_analysis_nlp_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-sentiment_analysis_nlp_pipeline_en.md
new file mode 100644
index 00000000000000..a86905d4f4331c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-sentiment_analysis_nlp_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English sentiment_analysis_nlp_pipeline pipeline DistilBertForSequenceClassification from aliciiavs
+author: John Snow Labs
+name: sentiment_analysis_nlp_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentiment_analysis_nlp_pipeline` is a English model originally trained by aliciiavs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentiment_analysis_nlp_pipeline_en_5.5.1_3.0_1737837774678.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentiment_analysis_nlp_pipeline_en_5.5.1_3.0_1737837774678.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sentiment_analysis_nlp_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sentiment_analysis_nlp_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sentiment_analysis_nlp_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/aliciiavs/sentiment-analysis-nlp
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-sentiment_classification_bert_mini_en.md b/docs/_posts/ahmedlone127/2025-01-25-sentiment_classification_bert_mini_en.md
new file mode 100644
index 00000000000000..2d00b1943f2ce3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-sentiment_classification_bert_mini_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sentiment_classification_bert_mini BertForSequenceClassification from Varnikasiva
+author: John Snow Labs
+name: sentiment_classification_bert_mini
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentiment_classification_bert_mini` is a English model originally trained by Varnikasiva.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentiment_classification_bert_mini_en_5.5.1_3.0_1737801229435.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentiment_classification_bert_mini_en_5.5.1_3.0_1737801229435.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("sentiment_classification_bert_mini","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("sentiment_classification_bert_mini", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sentiment_classification_bert_mini|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|42.1 MB|
+
+## References
+
+https://huggingface.co/Varnikasiva/sentiment-classification-bert-mini
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-sentiment_classification_bert_mini_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-sentiment_classification_bert_mini_pipeline_en.md
new file mode 100644
index 00000000000000..bdefaad3147f56
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-sentiment_classification_bert_mini_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English sentiment_classification_bert_mini_pipeline pipeline BertForSequenceClassification from Varnikasiva
+author: John Snow Labs
+name: sentiment_classification_bert_mini_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentiment_classification_bert_mini_pipeline` is a English model originally trained by Varnikasiva.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentiment_classification_bert_mini_pipeline_en_5.5.1_3.0_1737801231707.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentiment_classification_bert_mini_pipeline_en_5.5.1_3.0_1737801231707.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sentiment_classification_bert_mini_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sentiment_classification_bert_mini_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sentiment_classification_bert_mini_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|42.1 MB|
+
+## References
+
+https://huggingface.co/Varnikasiva/sentiment-classification-bert-mini
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-sentiment_classifier_yelp_en.md b/docs/_posts/ahmedlone127/2025-01-25-sentiment_classifier_yelp_en.md
new file mode 100644
index 00000000000000..7036d4af78661f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-sentiment_classifier_yelp_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sentiment_classifier_yelp BertForSequenceClassification from ggallipoli
+author: John Snow Labs
+name: sentiment_classifier_yelp
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentiment_classifier_yelp` is a English model originally trained by ggallipoli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentiment_classifier_yelp_en_5.5.1_3.0_1737840332236.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentiment_classifier_yelp_en_5.5.1_3.0_1737840332236.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("sentiment_classifier_yelp","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("sentiment_classifier_yelp", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sentiment_classifier_yelp|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/ggallipoli/sentiment_classifier_yelp
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-sentiment_classifier_yelp_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-sentiment_classifier_yelp_pipeline_en.md
new file mode 100644
index 00000000000000..6543d6e00b924a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-sentiment_classifier_yelp_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English sentiment_classifier_yelp_pipeline pipeline BertForSequenceClassification from ggallipoli
+author: John Snow Labs
+name: sentiment_classifier_yelp_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentiment_classifier_yelp_pipeline` is a English model originally trained by ggallipoli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentiment_classifier_yelp_pipeline_en_5.5.1_3.0_1737840353498.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentiment_classifier_yelp_pipeline_en_5.5.1_3.0_1737840353498.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sentiment_classifier_yelp_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sentiment_classifier_yelp_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sentiment_classifier_yelp_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/ggallipoli/sentiment_classifier_yelp
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-servimodel_en.md b/docs/_posts/ahmedlone127/2025-01-25-servimodel_en.md
new file mode 100644
index 00000000000000..5b245d090ee300
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-servimodel_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English servimodel DistilBertForSequenceClassification from karlitoxz
+author: John Snow Labs
+name: servimodel
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`servimodel` is a English model originally trained by karlitoxz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/servimodel_en_5.5.1_3.0_1737822076935.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/servimodel_en_5.5.1_3.0_1737822076935.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("servimodel","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("servimodel", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|servimodel|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|507.6 MB|
+
+## References
+
+https://huggingface.co/karlitoxz/ServiModel
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-servimodel_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-servimodel_pipeline_en.md
new file mode 100644
index 00000000000000..11cc4389267dee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-servimodel_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English servimodel_pipeline pipeline DistilBertForSequenceClassification from karlitoxz
+author: John Snow Labs
+name: servimodel_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`servimodel_pipeline` is a English model originally trained by karlitoxz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/servimodel_pipeline_en_5.5.1_3.0_1737822105507.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/servimodel_pipeline_en_5.5.1_3.0_1737822105507.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("servimodel_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("servimodel_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|servimodel_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|507.6 MB|
+
+## References
+
+https://huggingface.co/karlitoxz/ServiModel
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-sesto_question_answear_en.md b/docs/_posts/ahmedlone127/2025-01-25-sesto_question_answear_en.md
new file mode 100644
index 00000000000000..9e3ec064d5027f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-sesto_question_answear_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English sesto_question_answear BertForQuestionAnswering from Meziane
+author: John Snow Labs
+name: sesto_question_answear
+date: 2025-01-25
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sesto_question_answear` is a English model originally trained by Meziane.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sesto_question_answear_en_5.5.1_3.0_1737812888748.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sesto_question_answear_en_5.5.1_3.0_1737812888748.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("sesto_question_answear","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("sesto_question_answear", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sesto_question_answear|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/Meziane/sesto_question_answear
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-sesto_question_answear_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-sesto_question_answear_pipeline_en.md
new file mode 100644
index 00000000000000..1344cdc0abc03d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-sesto_question_answear_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English sesto_question_answear_pipeline pipeline BertForQuestionAnswering from Meziane
+author: John Snow Labs
+name: sesto_question_answear_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sesto_question_answear_pipeline` is a English model originally trained by Meziane.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sesto_question_answear_pipeline_en_5.5.1_3.0_1737812908896.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sesto_question_answear_pipeline_en_5.5.1_3.0_1737812908896.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sesto_question_answear_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sesto_question_answear_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sesto_question_answear_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/Meziane/sesto_question_answear
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-sexism_distilbert_en.md b/docs/_posts/ahmedlone127/2025-01-25-sexism_distilbert_en.md
new file mode 100644
index 00000000000000..50bad1119c20b1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-sexism_distilbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sexism_distilbert DistilBertForSequenceClassification from thranduil2
+author: John Snow Labs
+name: sexism_distilbert
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sexism_distilbert` is a English model originally trained by thranduil2.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sexism_distilbert_en_5.5.1_3.0_1737836619885.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sexism_distilbert_en_5.5.1_3.0_1737836619885.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("sexism_distilbert","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("sexism_distilbert", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sexism_distilbert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/thranduil2/sexism_distilbert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-sexism_distilbert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-sexism_distilbert_pipeline_en.md
new file mode 100644
index 00000000000000..8ba8ba55dc9769
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-sexism_distilbert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English sexism_distilbert_pipeline pipeline DistilBertForSequenceClassification from thranduil2
+author: John Snow Labs
+name: sexism_distilbert_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sexism_distilbert_pipeline` is a English model originally trained by thranduil2.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sexism_distilbert_pipeline_en_5.5.1_3.0_1737836633527.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sexism_distilbert_pipeline_en_5.5.1_3.0_1737836633527.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sexism_distilbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sexism_distilbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sexism_distilbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/thranduil2/sexism_distilbert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-shopee_ner_en.md b/docs/_posts/ahmedlone127/2025-01-25-shopee_ner_en.md
new file mode 100644
index 00000000000000..05daeb8be91dbb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-shopee_ner_en.md
@@ -0,0 +1,96 @@
+---
+layout: model
+title: English shopee_ner DistilBertForTokenClassification from yzzhu
+author: John Snow Labs
+name: shopee_ner
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`shopee_ner` is a English model originally trained by yzzhu.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/shopee_ner_en_5.5.1_3.0_1737833016380.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/shopee_ner_en_5.5.1_3.0_1737833016380.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("shopee_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("shopee_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|shopee_ner|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|820.7 MB|
+
+## References
+
+References
+
+https://huggingface.co/yzzhu/shopee-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-shopee_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-shopee_ner_pipeline_en.md
new file mode 100644
index 00000000000000..5d6f9658316cce
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-shopee_ner_pipeline_en.md
@@ -0,0 +1,72 @@
+---
+layout: model
+title: English shopee_ner_pipeline pipeline DistilBertForTokenClassification from yzzhu
+author: John Snow Labs
+name: shopee_ner_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`shopee_ner_pipeline` is a English model originally trained by yzzhu.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/shopee_ner_pipeline_en_5.5.1_3.0_1737833126353.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/shopee_ner_pipeline_en_5.5.1_3.0_1737833126353.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("shopee_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("shopee_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|shopee_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|820.7 MB|
+
+## References
+
+References
+
+https://huggingface.co/yzzhu/shopee-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-slm_custom_model_llama_en.md b/docs/_posts/ahmedlone127/2025-01-25-slm_custom_model_llama_en.md
new file mode 100644
index 00000000000000..db940cec53e4b0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-slm_custom_model_llama_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English slm_custom_model_llama T5Transformer from karthikeyan-r
+author: John Snow Labs
+name: slm_custom_model_llama
+date: 2025-01-25
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`slm_custom_model_llama` is a English model originally trained by karthikeyan-r.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/slm_custom_model_llama_en_5.5.1_3.0_1737849365636.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/slm_custom_model_llama_en_5.5.1_3.0_1737849365636.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("slm_custom_model_llama","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("slm_custom_model_llama", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|slm_custom_model_llama|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|277.4 MB|
+
+## References
+
+https://huggingface.co/karthikeyan-r/slm-custom-model-llama
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-slm_custom_model_llama_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-slm_custom_model_llama_pipeline_en.md
new file mode 100644
index 00000000000000..33ab96c80b3b88
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-slm_custom_model_llama_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English slm_custom_model_llama_pipeline pipeline T5Transformer from karthikeyan-r
+author: John Snow Labs
+name: slm_custom_model_llama_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`slm_custom_model_llama_pipeline` is a English model originally trained by karthikeyan-r.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/slm_custom_model_llama_pipeline_en_5.5.1_3.0_1737849381248.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/slm_custom_model_llama_pipeline_en_5.5.1_3.0_1737849381248.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("slm_custom_model_llama_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("slm_custom_model_llama_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|slm_custom_model_llama_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|277.4 MB|
+
+## References
+
+https://huggingface.co/karthikeyan-r/slm-custom-model-llama
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-smart_ner_model_en.md b/docs/_posts/ahmedlone127/2025-01-25-smart_ner_model_en.md
new file mode 100644
index 00000000000000..9300b839bb2f29
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-smart_ner_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English smart_ner_model DistilBertForTokenClassification from chidamnat2002
+author: John Snow Labs
+name: smart_ner_model
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`smart_ner_model` is a English model originally trained by chidamnat2002.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/smart_ner_model_en_5.5.1_3.0_1737764157090.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/smart_ner_model_en_5.5.1_3.0_1737764157090.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("smart_ner_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("smart_ner_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|smart_ner_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/chidamnat2002/smart_ner_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-smart_ner_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-smart_ner_model_pipeline_en.md
new file mode 100644
index 00000000000000..a1abd3eedc6295
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-smart_ner_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English smart_ner_model_pipeline pipeline DistilBertForTokenClassification from chidamnat2002
+author: John Snow Labs
+name: smart_ner_model_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`smart_ner_model_pipeline` is a English model originally trained by chidamnat2002.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/smart_ner_model_pipeline_en_5.5.1_3.0_1737764172181.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/smart_ner_model_pipeline_en_5.5.1_3.0_1737764172181.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("smart_ner_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("smart_ner_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|smart_ner_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/chidamnat2002/smart_ner_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-snacks_classifier_en.md b/docs/_posts/ahmedlone127/2025-01-25-snacks_classifier_en.md
new file mode 100644
index 00000000000000..cc2d16f66f35e3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-snacks_classifier_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English snacks_classifier SwinForImageClassification from Matthijs
+author: John Snow Labs
+name: snacks_classifier
+date: 2025-01-25
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`snacks_classifier` is a English model originally trained by Matthijs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/snacks_classifier_en_5.5.1_3.0_1737763267694.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/snacks_classifier_en_5.5.1_3.0_1737763267694.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""snacks_classifier","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("snacks_classifier","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|snacks_classifier|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/Matthijs/snacks-classifier
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-snacks_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-snacks_classifier_pipeline_en.md
new file mode 100644
index 00000000000000..f1cd45aa09a11f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-snacks_classifier_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English snacks_classifier_pipeline pipeline SwinForImageClassification from Matthijs
+author: John Snow Labs
+name: snacks_classifier_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`snacks_classifier_pipeline` is a English model originally trained by Matthijs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/snacks_classifier_pipeline_en_5.5.1_3.0_1737763286096.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/snacks_classifier_pipeline_en_5.5.1_3.0_1737763286096.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("snacks_classifier_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("snacks_classifier_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|snacks_classifier_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/Matthijs/snacks-classifier
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-spamdetectionbert_en.md b/docs/_posts/ahmedlone127/2025-01-25-spamdetectionbert_en.md
new file mode 100644
index 00000000000000..cedcbb66894a4e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-spamdetectionbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English spamdetectionbert BertForSequenceClassification from rogersinghchugh
+author: John Snow Labs
+name: spamdetectionbert
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`spamdetectionbert` is a English model originally trained by rogersinghchugh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/spamdetectionbert_en_5.5.1_3.0_1737800298416.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/spamdetectionbert_en_5.5.1_3.0_1737800298416.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("spamdetectionbert","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("spamdetectionbert", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|spamdetectionbert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/rogersinghchugh/spamDetectionBERT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-spamdetectionbert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-spamdetectionbert_pipeline_en.md
new file mode 100644
index 00000000000000..6407823cbb20ec
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-spamdetectionbert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English spamdetectionbert_pipeline pipeline BertForSequenceClassification from rogersinghchugh
+author: John Snow Labs
+name: spamdetectionbert_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`spamdetectionbert_pipeline` is a English model originally trained by rogersinghchugh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/spamdetectionbert_pipeline_en_5.5.1_3.0_1737800324296.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/spamdetectionbert_pipeline_en_5.5.1_3.0_1737800324296.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("spamdetectionbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("spamdetectionbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|spamdetectionbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/rogersinghchugh/spamDetectionBERT
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-sports_klue_finetuned_korquad_nosplit_nsp_en.md b/docs/_posts/ahmedlone127/2025-01-25-sports_klue_finetuned_korquad_nosplit_nsp_en.md
new file mode 100644
index 00000000000000..29825e32857a8d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-sports_klue_finetuned_korquad_nosplit_nsp_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English sports_klue_finetuned_korquad_nosplit_nsp BertForQuestionAnswering from Kdogs
+author: John Snow Labs
+name: sports_klue_finetuned_korquad_nosplit_nsp
+date: 2025-01-25
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sports_klue_finetuned_korquad_nosplit_nsp` is a English model originally trained by Kdogs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sports_klue_finetuned_korquad_nosplit_nsp_en_5.5.1_3.0_1737813124631.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sports_klue_finetuned_korquad_nosplit_nsp_en_5.5.1_3.0_1737813124631.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("sports_klue_finetuned_korquad_nosplit_nsp","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("sports_klue_finetuned_korquad_nosplit_nsp", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sports_klue_finetuned_korquad_nosplit_nsp|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|412.4 MB|
+
+## References
+
+https://huggingface.co/Kdogs/sports_klue_finetuned_korquad_noSplit_NSP
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-sports_klue_finetuned_korquad_nosplit_nsp_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-sports_klue_finetuned_korquad_nosplit_nsp_pipeline_en.md
new file mode 100644
index 00000000000000..6b3bbe8dc1b968
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-sports_klue_finetuned_korquad_nosplit_nsp_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English sports_klue_finetuned_korquad_nosplit_nsp_pipeline pipeline BertForQuestionAnswering from Kdogs
+author: John Snow Labs
+name: sports_klue_finetuned_korquad_nosplit_nsp_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sports_klue_finetuned_korquad_nosplit_nsp_pipeline` is a English model originally trained by Kdogs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sports_klue_finetuned_korquad_nosplit_nsp_pipeline_en_5.5.1_3.0_1737813146946.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sports_klue_finetuned_korquad_nosplit_nsp_pipeline_en_5.5.1_3.0_1737813146946.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sports_klue_finetuned_korquad_nosplit_nsp_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sports_klue_finetuned_korquad_nosplit_nsp_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sports_klue_finetuned_korquad_nosplit_nsp_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|412.4 MB|
+
+## References
+
+https://huggingface.co/Kdogs/sports_klue_finetuned_korquad_noSplit_NSP
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-stock_classifier_en.md b/docs/_posts/ahmedlone127/2025-01-25-stock_classifier_en.md
new file mode 100644
index 00000000000000..8a651a37017014
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-stock_classifier_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English stock_classifier DistilBertForSequenceClassification from hkufyp2024
+author: John Snow Labs
+name: stock_classifier
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`stock_classifier` is a English model originally trained by hkufyp2024.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/stock_classifier_en_5.5.1_3.0_1737822886065.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/stock_classifier_en_5.5.1_3.0_1737822886065.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("stock_classifier","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("stock_classifier", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|stock_classifier|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|251.3 MB|
+
+## References
+
+https://huggingface.co/hkufyp2024/stock-classifier
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-stock_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-stock_classifier_pipeline_en.md
new file mode 100644
index 00000000000000..25282167f250ef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-stock_classifier_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English stock_classifier_pipeline pipeline DistilBertForSequenceClassification from hkufyp2024
+author: John Snow Labs
+name: stock_classifier_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`stock_classifier_pipeline` is a English model originally trained by hkufyp2024.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/stock_classifier_pipeline_en_5.5.1_3.0_1737822898968.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/stock_classifier_pipeline_en_5.5.1_3.0_1737822898968.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("stock_classifier_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("stock_classifier_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|stock_classifier_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|251.3 MB|
+
+## References
+
+https://huggingface.co/hkufyp2024/stock-classifier
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-stud_fac_eval_distilbert_base_uncased_v2_pipeline_tl.md b/docs/_posts/ahmedlone127/2025-01-25-stud_fac_eval_distilbert_base_uncased_v2_pipeline_tl.md
new file mode 100644
index 00000000000000..6dbdb551881309
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-stud_fac_eval_distilbert_base_uncased_v2_pipeline_tl.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Tagalog stud_fac_eval_distilbert_base_uncased_v2_pipeline pipeline DistilBertForSequenceClassification from MENG21
+author: John Snow Labs
+name: stud_fac_eval_distilbert_base_uncased_v2_pipeline
+date: 2025-01-25
+tags: [tl, open_source, pipeline, onnx]
+task: Text Classification
+language: tl
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`stud_fac_eval_distilbert_base_uncased_v2_pipeline` is a Tagalog model originally trained by MENG21.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/stud_fac_eval_distilbert_base_uncased_v2_pipeline_tl_5.5.1_3.0_1737838122650.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/stud_fac_eval_distilbert_base_uncased_v2_pipeline_tl_5.5.1_3.0_1737838122650.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("stud_fac_eval_distilbert_base_uncased_v2_pipeline", lang = "tl")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("stud_fac_eval_distilbert_base_uncased_v2_pipeline", lang = "tl")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|stud_fac_eval_distilbert_base_uncased_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|tl|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/MENG21/stud-fac-eval-distilbert-base-uncased_v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-stud_fac_eval_distilbert_base_uncased_v2_tl.md b/docs/_posts/ahmedlone127/2025-01-25-stud_fac_eval_distilbert_base_uncased_v2_tl.md
new file mode 100644
index 00000000000000..170fe029200459
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-stud_fac_eval_distilbert_base_uncased_v2_tl.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Tagalog stud_fac_eval_distilbert_base_uncased_v2 DistilBertForSequenceClassification from MENG21
+author: John Snow Labs
+name: stud_fac_eval_distilbert_base_uncased_v2
+date: 2025-01-25
+tags: [tl, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: tl
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`stud_fac_eval_distilbert_base_uncased_v2` is a Tagalog model originally trained by MENG21.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/stud_fac_eval_distilbert_base_uncased_v2_tl_5.5.1_3.0_1737838109616.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/stud_fac_eval_distilbert_base_uncased_v2_tl_5.5.1_3.0_1737838109616.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("stud_fac_eval_distilbert_base_uncased_v2","tl") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("stud_fac_eval_distilbert_base_uncased_v2", "tl")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|stud_fac_eval_distilbert_base_uncased_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|tl|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/MENG21/stud-fac-eval-distilbert-base-uncased_v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-suicidal_bert_en.md b/docs/_posts/ahmedlone127/2025-01-25-suicidal_bert_en.md
new file mode 100644
index 00000000000000..9d08615d398c1d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-suicidal_bert_en.md
@@ -0,0 +1,96 @@
+---
+layout: model
+title: English suicidal_bert BertForSequenceClassification from gooohjy
+author: John Snow Labs
+name: suicidal_bert
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`suicidal_bert` is a English model originally trained by gooohjy.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/suicidal_bert_en_5.5.1_3.0_1737801131217.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/suicidal_bert_en_5.5.1_3.0_1737801131217.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("suicidal_bert","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("suicidal_bert", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|suicidal_bert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+References
+
+https://huggingface.co/gooohjy/suicidal-bert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-suicidal_bert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-suicidal_bert_pipeline_en.md
new file mode 100644
index 00000000000000..5ac0f413bdd8ae
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-suicidal_bert_pipeline_en.md
@@ -0,0 +1,72 @@
+---
+layout: model
+title: English suicidal_bert_pipeline pipeline BertForSequenceClassification from gooohjy
+author: John Snow Labs
+name: suicidal_bert_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`suicidal_bert_pipeline` is a English model originally trained by gooohjy.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/suicidal_bert_pipeline_en_5.5.1_3.0_1737801153146.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/suicidal_bert_pipeline_en_5.5.1_3.0_1737801153146.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("suicidal_bert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("suicidal_bert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|suicidal_bert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+References
+
+https://huggingface.co/gooohjy/suicidal-bert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-swin_tiny_patch4_window7_224_finetuned_eurosat_saffalpoosh_en.md b/docs/_posts/ahmedlone127/2025-01-25-swin_tiny_patch4_window7_224_finetuned_eurosat_saffalpoosh_en.md
new file mode 100644
index 00000000000000..f2172ef807c9ee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-swin_tiny_patch4_window7_224_finetuned_eurosat_saffalpoosh_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_saffalpoosh SwinForImageClassification from SaffalPoosh
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_saffalpoosh
+date: 2025-01-25
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_saffalpoosh` is a English model originally trained by SaffalPoosh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_saffalpoosh_en_5.5.1_3.0_1737763227728.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_saffalpoosh_en_5.5.1_3.0_1737763227728.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_saffalpoosh","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_saffalpoosh","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_saffalpoosh|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/SaffalPoosh/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-swin_tiny_patch4_window7_224_finetuned_eurosat_saffalpoosh_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-swin_tiny_patch4_window7_224_finetuned_eurosat_saffalpoosh_pipeline_en.md
new file mode 100644
index 00000000000000..bd9dd4c2ed8fc4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-swin_tiny_patch4_window7_224_finetuned_eurosat_saffalpoosh_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_saffalpoosh_pipeline pipeline SwinForImageClassification from SaffalPoosh
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_saffalpoosh_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_saffalpoosh_pipeline` is a English model originally trained by SaffalPoosh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_saffalpoosh_pipeline_en_5.5.1_3.0_1737763238925.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_saffalpoosh_pipeline_en_5.5.1_3.0_1737763238925.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_saffalpoosh_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_saffalpoosh_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_saffalpoosh_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/SaffalPoosh/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-swin_tiny_patch4_window7_224_finetuned_eurosat_suredream_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-swin_tiny_patch4_window7_224_finetuned_eurosat_suredream_pipeline_en.md
new file mode 100644
index 00000000000000..bd2ace038c5760
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-swin_tiny_patch4_window7_224_finetuned_eurosat_suredream_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_suredream_pipeline pipeline SwinForImageClassification from suredream
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_suredream_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_suredream_pipeline` is a English model originally trained by suredream.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_suredream_pipeline_en_5.5.1_3.0_1737763200272.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_suredream_pipeline_en_5.5.1_3.0_1737763200272.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_suredream_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_suredream_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_suredream_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/suredream/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-t2_arabic_en.md b/docs/_posts/ahmedlone127/2025-01-25-t2_arabic_en.md
new file mode 100644
index 00000000000000..455b7713b8288f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-t2_arabic_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English t2_arabic XlmRoBertaForSequenceClassification from keles
+author: John Snow Labs
+name: t2_arabic
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t2_arabic` is a English model originally trained by keles.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t2_arabic_en_5.5.1_3.0_1737816381652.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t2_arabic_en_5.5.1_3.0_1737816381652.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("t2_arabic","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("t2_arabic", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t2_arabic|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|818.1 MB|
+
+## References
+
+https://huggingface.co/keles/t2_ar
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-t2_arabic_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-t2_arabic_pipeline_en.md
new file mode 100644
index 00000000000000..48117046a2a24b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-t2_arabic_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English t2_arabic_pipeline pipeline XlmRoBertaForSequenceClassification from keles
+author: John Snow Labs
+name: t2_arabic_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t2_arabic_pipeline` is a English model originally trained by keles.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t2_arabic_pipeline_en_5.5.1_3.0_1737816492744.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t2_arabic_pipeline_en_5.5.1_3.0_1737816492744.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t2_arabic_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t2_arabic_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t2_arabic_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|818.1 MB|
+
+## References
+
+https://huggingface.co/keles/t2_ar
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-t5validation_en.md b/docs/_posts/ahmedlone127/2025-01-25-t5validation_en.md
new file mode 100644
index 00000000000000..4cb1d2f890dce8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-t5validation_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5validation T5Transformer from abhibheema
+author: John Snow Labs
+name: t5validation
+date: 2025-01-25
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5validation` is a English model originally trained by abhibheema.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5validation_en_5.5.1_3.0_1737849430215.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5validation_en_5.5.1_3.0_1737849430215.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5validation","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5validation", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5validation|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|282.0 MB|
+
+## References
+
+https://huggingface.co/abhibheema/T5Validation
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-t5validation_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-t5validation_pipeline_en.md
new file mode 100644
index 00000000000000..42bd971edf5029
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-t5validation_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5validation_pipeline pipeline T5Transformer from abhibheema
+author: John Snow Labs
+name: t5validation_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5validation_pipeline` is a English model originally trained by abhibheema.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5validation_pipeline_en_5.5.1_3.0_1737849446502.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5validation_pipeline_en_5.5.1_3.0_1737849446502.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5validation_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5validation_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5validation_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|282.0 MB|
+
+## References
+
+https://huggingface.co/abhibheema/T5Validation
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-taptap_distill_en.md b/docs/_posts/ahmedlone127/2025-01-25-taptap_distill_en.md
new file mode 100644
index 00000000000000..1662858bd6a240
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-taptap_distill_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English taptap_distill GPT2Transformer from ztphs980
+author: John Snow Labs
+name: taptap_distill
+date: 2025-01-25
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`taptap_distill` is a English model originally trained by ztphs980.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/taptap_distill_en_5.5.1_3.0_1737825402241.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/taptap_distill_en_5.5.1_3.0_1737825402241.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("taptap_distill","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("taptap_distill","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|taptap_distill|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|308.4 MB|
+
+## References
+
+https://huggingface.co/ztphs980/taptap-distill
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-taptap_distill_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-taptap_distill_pipeline_en.md
new file mode 100644
index 00000000000000..4eaff3f6e768ad
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-taptap_distill_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English taptap_distill_pipeline pipeline GPT2Transformer from ztphs980
+author: John Snow Labs
+name: taptap_distill_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`taptap_distill_pipeline` is a English model originally trained by ztphs980.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/taptap_distill_pipeline_en_5.5.1_3.0_1737825420213.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/taptap_distill_pipeline_en_5.5.1_3.0_1737825420213.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("taptap_distill_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("taptap_distill_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|taptap_distill_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|308.4 MB|
+
+## References
+
+https://huggingface.co/ztphs980/taptap-distill
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-tekai_en.md b/docs/_posts/ahmedlone127/2025-01-25-tekai_en.md
new file mode 100644
index 00000000000000..0a4ba6dc0ba16d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-tekai_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English tekai DistilBertForSequenceClassification from robinho46
+author: John Snow Labs
+name: tekai
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tekai` is a English model originally trained by robinho46.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tekai_en_5.5.1_3.0_1737838102382.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tekai_en_5.5.1_3.0_1737838102382.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("tekai","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("tekai", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tekai|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/robinho46/tekAI
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-tekai_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-tekai_pipeline_en.md
new file mode 100644
index 00000000000000..f6fbfebb6965dc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-tekai_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English tekai_pipeline pipeline DistilBertForSequenceClassification from robinho46
+author: John Snow Labs
+name: tekai_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tekai_pipeline` is a English model originally trained by robinho46.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tekai_pipeline_en_5.5.1_3.0_1737838115410.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tekai_pipeline_en_5.5.1_3.0_1737838115410.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("tekai_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("tekai_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tekai_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/robinho46/tekAI
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-test2_hdvd2309_en.md b/docs/_posts/ahmedlone127/2025-01-25-test2_hdvd2309_en.md
new file mode 100644
index 00000000000000..b726b4e20fed38
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-test2_hdvd2309_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English test2_hdvd2309 GPT2Transformer from hdvd2309
+author: John Snow Labs
+name: test2_hdvd2309
+date: 2025-01-25
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test2_hdvd2309` is a English model originally trained by hdvd2309.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test2_hdvd2309_en_5.5.1_3.0_1737825009360.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test2_hdvd2309_en_5.5.1_3.0_1737825009360.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("test2_hdvd2309","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("test2_hdvd2309","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test2_hdvd2309|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|73.7 MB|
+
+## References
+
+https://huggingface.co/hdvd2309/test2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-test2_hdvd2309_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-test2_hdvd2309_pipeline_en.md
new file mode 100644
index 00000000000000..e9ba69640a56d8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-test2_hdvd2309_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English test2_hdvd2309_pipeline pipeline GPT2Transformer from hdvd2309
+author: John Snow Labs
+name: test2_hdvd2309_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test2_hdvd2309_pipeline` is a English model originally trained by hdvd2309.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test2_hdvd2309_pipeline_en_5.5.1_3.0_1737825013210.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test2_hdvd2309_pipeline_en_5.5.1_3.0_1737825013210.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("test2_hdvd2309_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("test2_hdvd2309_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test2_hdvd2309_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|73.7 MB|
+
+## References
+
+https://huggingface.co/hdvd2309/test2
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-test_trainer_leonardosegurat_en.md b/docs/_posts/ahmedlone127/2025-01-25-test_trainer_leonardosegurat_en.md
new file mode 100644
index 00000000000000..701f89d0ff17ab
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-test_trainer_leonardosegurat_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English test_trainer_leonardosegurat DistilBertForSequenceClassification from leonardosegurat
+author: John Snow Labs
+name: test_trainer_leonardosegurat
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_trainer_leonardosegurat` is a English model originally trained by leonardosegurat.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_trainer_leonardosegurat_en_5.5.1_3.0_1737836883313.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_trainer_leonardosegurat_en_5.5.1_3.0_1737836883313.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("test_trainer_leonardosegurat","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("test_trainer_leonardosegurat", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_trainer_leonardosegurat|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/leonardosegurat/test_trainer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-test_trainer_leonardosegurat_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-test_trainer_leonardosegurat_pipeline_en.md
new file mode 100644
index 00000000000000..140290660ecd37
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-test_trainer_leonardosegurat_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English test_trainer_leonardosegurat_pipeline pipeline DistilBertForSequenceClassification from leonardosegurat
+author: John Snow Labs
+name: test_trainer_leonardosegurat_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_trainer_leonardosegurat_pipeline` is a English model originally trained by leonardosegurat.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_trainer_leonardosegurat_pipeline_en_5.5.1_3.0_1737836898046.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_trainer_leonardosegurat_pipeline_en_5.5.1_3.0_1737836898046.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("test_trainer_leonardosegurat_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("test_trainer_leonardosegurat_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_trainer_leonardosegurat_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/leonardosegurat/test_trainer
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-testmodel_en.md b/docs/_posts/ahmedlone127/2025-01-25-testmodel_en.md
new file mode 100644
index 00000000000000..b887b89b6c9660
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-testmodel_en.md
@@ -0,0 +1,88 @@
+---
+layout: model
+title: English testmodel DistilBertForQuestionAnswering from petersirka
+author: John Snow Labs
+name: testmodel
+date: 2025-01-25
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`testmodel` is a English model originally trained by petersirka.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/testmodel_en_5.5.1_3.0_1737824414217.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/testmodel_en_5.5.1_3.0_1737824414217.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("testmodel","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("testmodel", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|testmodel|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|213.1 MB|
+
+## References
+
+References
+
+https://huggingface.co/petersirka/testmodel
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-testmodel_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-testmodel_pipeline_en.md
new file mode 100644
index 00000000000000..b2a769429aab0d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-testmodel_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English testmodel_pipeline pipeline DistilBertForQuestionAnswering from petersirka
+author: John Snow Labs
+name: testmodel_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`testmodel_pipeline` is a English model originally trained by petersirka.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/testmodel_pipeline_en_5.5.1_3.0_1737824486289.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/testmodel_pipeline_en_5.5.1_3.0_1737824486289.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("testmodel_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("testmodel_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|testmodel_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|213.2 MB|
+
+## References
+
+References
+
+https://huggingface.co/petersirka/testmodel
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-testwfh_en.md b/docs/_posts/ahmedlone127/2025-01-25-testwfh_en.md
new file mode 100644
index 00000000000000..d38c7fb57e3b7b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-testwfh_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English testwfh DistilBertForSequenceClassification from mmine
+author: John Snow Labs
+name: testwfh
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`testwfh` is a English model originally trained by mmine.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/testwfh_en_5.5.1_3.0_1737838445750.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/testwfh_en_5.5.1_3.0_1737838445750.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("testwfh","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("testwfh", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|testwfh|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.0 MB|
+
+## References
+
+https://huggingface.co/mmine/testwfh
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-testwfh_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-testwfh_pipeline_en.md
new file mode 100644
index 00000000000000..d976225d0c1669
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-testwfh_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English testwfh_pipeline pipeline DistilBertForSequenceClassification from mmine
+author: John Snow Labs
+name: testwfh_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`testwfh_pipeline` is a English model originally trained by mmine.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/testwfh_pipeline_en_5.5.1_3.0_1737838459511.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/testwfh_pipeline_en_5.5.1_3.0_1737838459511.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("testwfh_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("testwfh_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|testwfh_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.0 MB|
+
+## References
+
+https://huggingface.co/mmine/testwfh
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-text_model_en.md b/docs/_posts/ahmedlone127/2025-01-25-text_model_en.md
new file mode 100644
index 00000000000000..e6b86be068428d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-text_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English text_model DistilBertForSequenceClassification from techme
+author: John Snow Labs
+name: text_model
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`text_model` is a English model originally trained by techme.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/text_model_en_5.5.1_3.0_1737836153105.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/text_model_en_5.5.1_3.0_1737836153105.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("text_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("text_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|text_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/techme/text_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-text_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-text_model_pipeline_en.md
new file mode 100644
index 00000000000000..30bedd6cea63b1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-text_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English text_model_pipeline pipeline DistilBertForSequenceClassification from techme
+author: John Snow Labs
+name: text_model_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`text_model_pipeline` is a English model originally trained by techme.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/text_model_pipeline_en_5.5.1_3.0_1737836168402.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/text_model_pipeline_en_5.5.1_3.0_1737836168402.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("text_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("text_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|text_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/techme/text_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-tgt2ceq_dgpt_v1_4_en.md b/docs/_posts/ahmedlone127/2025-01-25-tgt2ceq_dgpt_v1_4_en.md
new file mode 100644
index 00000000000000..79f24fdc8fb748
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-tgt2ceq_dgpt_v1_4_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English tgt2ceq_dgpt_v1_4 GPT2Transformer from RyotaroOKabe
+author: John Snow Labs
+name: tgt2ceq_dgpt_v1_4
+date: 2025-01-25
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tgt2ceq_dgpt_v1_4` is a English model originally trained by RyotaroOKabe.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tgt2ceq_dgpt_v1_4_en_5.5.1_3.0_1737771148517.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tgt2ceq_dgpt_v1_4_en_5.5.1_3.0_1737771148517.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("tgt2ceq_dgpt_v1_4","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("tgt2ceq_dgpt_v1_4","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tgt2ceq_dgpt_v1_4|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|308.4 MB|
+
+## References
+
+https://huggingface.co/RyotaroOKabe/tgt2ceq_dgpt_v1.4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-tgt2ceq_dgpt_v1_4_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-tgt2ceq_dgpt_v1_4_pipeline_en.md
new file mode 100644
index 00000000000000..7d20f3a4c630c8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-tgt2ceq_dgpt_v1_4_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English tgt2ceq_dgpt_v1_4_pipeline pipeline GPT2Transformer from RyotaroOKabe
+author: John Snow Labs
+name: tgt2ceq_dgpt_v1_4_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tgt2ceq_dgpt_v1_4_pipeline` is a English model originally trained by RyotaroOKabe.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tgt2ceq_dgpt_v1_4_pipeline_en_5.5.1_3.0_1737771164268.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tgt2ceq_dgpt_v1_4_pipeline_en_5.5.1_3.0_1737771164268.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("tgt2ceq_dgpt_v1_4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("tgt2ceq_dgpt_v1_4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tgt2ceq_dgpt_v1_4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|308.4 MB|
+
+## References
+
+https://huggingface.co/RyotaroOKabe/tgt2ceq_dgpt_v1.4
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-thai_lyrics_wangchan_en.md b/docs/_posts/ahmedlone127/2025-01-25-thai_lyrics_wangchan_en.md
new file mode 100644
index 00000000000000..741d753cee3f90
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-thai_lyrics_wangchan_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English thai_lyrics_wangchan CamemBertForSequenceClassification from Nitcha
+author: John Snow Labs
+name: thai_lyrics_wangchan
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, camembert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`thai_lyrics_wangchan` is a English model originally trained by Nitcha.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/thai_lyrics_wangchan_en_5.5.1_3.0_1737823329280.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/thai_lyrics_wangchan_en_5.5.1_3.0_1737823329280.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = CamemBertForSequenceClassification.pretrained("thai_lyrics_wangchan","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = CamemBertForSequenceClassification.pretrained("thai_lyrics_wangchan", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|thai_lyrics_wangchan|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|394.3 MB|
+
+## References
+
+https://huggingface.co/Nitcha/thai-lyrics-wangchan
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-thai_lyrics_wangchan_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-thai_lyrics_wangchan_pipeline_en.md
new file mode 100644
index 00000000000000..be9be35ab7fb22
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-thai_lyrics_wangchan_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English thai_lyrics_wangchan_pipeline pipeline CamemBertForSequenceClassification from Nitcha
+author: John Snow Labs
+name: thai_lyrics_wangchan_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`thai_lyrics_wangchan_pipeline` is a English model originally trained by Nitcha.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/thai_lyrics_wangchan_pipeline_en_5.5.1_3.0_1737823349108.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/thai_lyrics_wangchan_pipeline_en_5.5.1_3.0_1737823349108.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("thai_lyrics_wangchan_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("thai_lyrics_wangchan_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|thai_lyrics_wangchan_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|394.4 MB|
+
+## References
+
+https://huggingface.co/Nitcha/thai-lyrics-wangchan
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-three_class_5e_5_hausa_en.md b/docs/_posts/ahmedlone127/2025-01-25-three_class_5e_5_hausa_en.md
new file mode 100644
index 00000000000000..27560feff85324
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-three_class_5e_5_hausa_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English three_class_5e_5_hausa XlmRoBertaForTokenClassification from grace-pro
+author: John Snow Labs
+name: three_class_5e_5_hausa
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`three_class_5e_5_hausa` is a English model originally trained by grace-pro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/three_class_5e_5_hausa_en_5.5.1_3.0_1737791131667.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/three_class_5e_5_hausa_en_5.5.1_3.0_1737791131667.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("three_class_5e_5_hausa","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("three_class_5e_5_hausa", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|three_class_5e_5_hausa|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/grace-pro/three_class_5e-5_hausa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-three_class_5e_5_hausa_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-three_class_5e_5_hausa_pipeline_en.md
new file mode 100644
index 00000000000000..6865c6001d082d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-three_class_5e_5_hausa_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English three_class_5e_5_hausa_pipeline pipeline XlmRoBertaForTokenClassification from grace-pro
+author: John Snow Labs
+name: three_class_5e_5_hausa_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`three_class_5e_5_hausa_pipeline` is a English model originally trained by grace-pro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/three_class_5e_5_hausa_pipeline_en_5.5.1_3.0_1737791186793.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/three_class_5e_5_hausa_pipeline_en_5.5.1_3.0_1737791186793.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("three_class_5e_5_hausa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("three_class_5e_5_hausa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|three_class_5e_5_hausa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/grace-pro/three_class_5e-5_hausa
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-tibetan_roberta_a_v1_770840_en.md b/docs/_posts/ahmedlone127/2025-01-25-tibetan_roberta_a_v1_770840_en.md
new file mode 100644
index 00000000000000..afab9e3127c971
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-tibetan_roberta_a_v1_770840_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English tibetan_roberta_a_v1_770840 RoBertaEmbeddings from spsither
+author: John Snow Labs
+name: tibetan_roberta_a_v1_770840
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tibetan_roberta_a_v1_770840` is a English model originally trained by spsither.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tibetan_roberta_a_v1_770840_en_5.5.1_3.0_1737797163114.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tibetan_roberta_a_v1_770840_en_5.5.1_3.0_1737797163114.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("tibetan_roberta_a_v1_770840","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("tibetan_roberta_a_v1_770840","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tibetan_roberta_a_v1_770840|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|311.2 MB|
+
+## References
+
+https://huggingface.co/spsither/tibetan_RoBERTa_A_v1_770840
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-tibetan_roberta_a_v1_770840_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-tibetan_roberta_a_v1_770840_pipeline_en.md
new file mode 100644
index 00000000000000..a4fc2d91e210b1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-tibetan_roberta_a_v1_770840_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English tibetan_roberta_a_v1_770840_pipeline pipeline RoBertaEmbeddings from spsither
+author: John Snow Labs
+name: tibetan_roberta_a_v1_770840_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tibetan_roberta_a_v1_770840_pipeline` is a English model originally trained by spsither.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tibetan_roberta_a_v1_770840_pipeline_en_5.5.1_3.0_1737797179782.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tibetan_roberta_a_v1_770840_pipeline_en_5.5.1_3.0_1737797179782.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("tibetan_roberta_a_v1_770840_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("tibetan_roberta_a_v1_770840_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tibetan_roberta_a_v1_770840_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|311.3 MB|
+
+## References
+
+https://huggingface.co/spsither/tibetan_RoBERTa_A_v1_770840
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-tibetan_roberta_afd_e1_en.md b/docs/_posts/ahmedlone127/2025-01-25-tibetan_roberta_afd_e1_en.md
new file mode 100644
index 00000000000000..484687c713e443
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-tibetan_roberta_afd_e1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English tibetan_roberta_afd_e1 RoBertaEmbeddings from spsither
+author: John Snow Labs
+name: tibetan_roberta_afd_e1
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tibetan_roberta_afd_e1` is a English model originally trained by spsither.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tibetan_roberta_afd_e1_en_5.5.1_3.0_1737797764511.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tibetan_roberta_afd_e1_en_5.5.1_3.0_1737797764511.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("tibetan_roberta_afd_e1","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("tibetan_roberta_afd_e1","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tibetan_roberta_afd_e1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|616.6 MB|
+
+## References
+
+https://huggingface.co/spsither/tibetan_RoBERTa_Afd_e1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-tibetan_roberta_afd_e1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-tibetan_roberta_afd_e1_pipeline_en.md
new file mode 100644
index 00000000000000..c0c91b36a13bbe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-tibetan_roberta_afd_e1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English tibetan_roberta_afd_e1_pipeline pipeline RoBertaEmbeddings from spsither
+author: John Snow Labs
+name: tibetan_roberta_afd_e1_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tibetan_roberta_afd_e1_pipeline` is a English model originally trained by spsither.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tibetan_roberta_afd_e1_pipeline_en_5.5.1_3.0_1737797799499.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tibetan_roberta_afd_e1_pipeline_en_5.5.1_3.0_1737797799499.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("tibetan_roberta_afd_e1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("tibetan_roberta_afd_e1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tibetan_roberta_afd_e1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|616.6 MB|
+
+## References
+
+https://huggingface.co/spsither/tibetan_RoBERTa_Afd_e1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-tiny_random_gpt2_kmfoda_en.md b/docs/_posts/ahmedlone127/2025-01-25-tiny_random_gpt2_kmfoda_en.md
new file mode 100644
index 00000000000000..6f31de8b413cd4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-tiny_random_gpt2_kmfoda_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English tiny_random_gpt2_kmfoda GPT2Transformer from kmfoda
+author: John Snow Labs
+name: tiny_random_gpt2_kmfoda
+date: 2025-01-25
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_random_gpt2_kmfoda` is a English model originally trained by kmfoda.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_random_gpt2_kmfoda_en_5.5.1_3.0_1737825943786.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_random_gpt2_kmfoda_en_5.5.1_3.0_1737825943786.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("tiny_random_gpt2_kmfoda","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("tiny_random_gpt2_kmfoda","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tiny_random_gpt2_kmfoda|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|1.5 MB|
+
+## References
+
+https://huggingface.co/kmfoda/tiny-random-gpt2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-tiny_random_gpt2_kmfoda_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-tiny_random_gpt2_kmfoda_pipeline_en.md
new file mode 100644
index 00000000000000..1ec456e4e6bd3b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-tiny_random_gpt2_kmfoda_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English tiny_random_gpt2_kmfoda_pipeline pipeline GPT2Transformer from kmfoda
+author: John Snow Labs
+name: tiny_random_gpt2_kmfoda_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_random_gpt2_kmfoda_pipeline` is a English model originally trained by kmfoda.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_random_gpt2_kmfoda_pipeline_en_5.5.1_3.0_1737825944219.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_random_gpt2_kmfoda_pipeline_en_5.5.1_3.0_1737825944219.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("tiny_random_gpt2_kmfoda_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("tiny_random_gpt2_kmfoda_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tiny_random_gpt2_kmfoda_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 MB|
+
+## References
+
+https://huggingface.co/kmfoda/tiny-random-gpt2
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-topic_classifier_en.md b/docs/_posts/ahmedlone127/2025-01-25-topic_classifier_en.md
new file mode 100644
index 00000000000000..9fad9f0b002118
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-topic_classifier_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English topic_classifier DistilBertForSequenceClassification from shahidmo99
+author: John Snow Labs
+name: topic_classifier
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`topic_classifier` is a English model originally trained by shahidmo99.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/topic_classifier_en_5.5.1_3.0_1737838509971.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/topic_classifier_en_5.5.1_3.0_1737838509971.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("topic_classifier","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("topic_classifier", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|topic_classifier|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/shahidmo99/topic-classifier
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-topic_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-topic_classifier_pipeline_en.md
new file mode 100644
index 00000000000000..cd0489c2a1da21
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-topic_classifier_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English topic_classifier_pipeline pipeline DistilBertForSequenceClassification from shahidmo99
+author: John Snow Labs
+name: topic_classifier_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`topic_classifier_pipeline` is a English model originally trained by shahidmo99.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/topic_classifier_pipeline_en_5.5.1_3.0_1737838524207.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/topic_classifier_pipeline_en_5.5.1_3.0_1737838524207.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("topic_classifier_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("topic_classifier_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|topic_classifier_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/shahidmo99/topic-classifier
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-trainer_indiana500_en.md b/docs/_posts/ahmedlone127/2025-01-25-trainer_indiana500_en.md
new file mode 100644
index 00000000000000..eacae413978b95
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-trainer_indiana500_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English trainer_indiana500 DistilBertForSequenceClassification from indiana500
+author: John Snow Labs
+name: trainer_indiana500
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`trainer_indiana500` is a English model originally trained by indiana500.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/trainer_indiana500_en_5.5.1_3.0_1737837893105.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/trainer_indiana500_en_5.5.1_3.0_1737837893105.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("trainer_indiana500","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("trainer_indiana500", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|trainer_indiana500|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/indiana500/trainer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-trainer_indiana500_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-trainer_indiana500_pipeline_en.md
new file mode 100644
index 00000000000000..42fe472246af1e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-trainer_indiana500_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English trainer_indiana500_pipeline pipeline DistilBertForSequenceClassification from indiana500
+author: John Snow Labs
+name: trainer_indiana500_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`trainer_indiana500_pipeline` is a English model originally trained by indiana500.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/trainer_indiana500_pipeline_en_5.5.1_3.0_1737837907316.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/trainer_indiana500_pipeline_en_5.5.1_3.0_1737837907316.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("trainer_indiana500_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("trainer_indiana500_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|trainer_indiana500_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/indiana500/trainer
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-trainer_simonejlaudani_en.md b/docs/_posts/ahmedlone127/2025-01-25-trainer_simonejlaudani_en.md
new file mode 100644
index 00000000000000..cbb12e28248d4e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-trainer_simonejlaudani_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English trainer_simonejlaudani DistilBertForSequenceClassification from SimoneJLaudani
+author: John Snow Labs
+name: trainer_simonejlaudani
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`trainer_simonejlaudani` is a English model originally trained by SimoneJLaudani.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/trainer_simonejlaudani_en_5.5.1_3.0_1737836971748.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/trainer_simonejlaudani_en_5.5.1_3.0_1737836971748.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("trainer_simonejlaudani","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("trainer_simonejlaudani", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|trainer_simonejlaudani|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/SimoneJLaudani/trainer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-trainer_simonejlaudani_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-trainer_simonejlaudani_pipeline_en.md
new file mode 100644
index 00000000000000..f0d7a7095de053
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-trainer_simonejlaudani_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English trainer_simonejlaudani_pipeline pipeline DistilBertForSequenceClassification from SimoneJLaudani
+author: John Snow Labs
+name: trainer_simonejlaudani_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`trainer_simonejlaudani_pipeline` is a English model originally trained by SimoneJLaudani.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/trainer_simonejlaudani_pipeline_en_5.5.1_3.0_1737836985616.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/trainer_simonejlaudani_pipeline_en_5.5.1_3.0_1737836985616.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("trainer_simonejlaudani_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("trainer_simonejlaudani_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|trainer_simonejlaudani_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/SimoneJLaudani/trainer
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-transformers_project_en.md b/docs/_posts/ahmedlone127/2025-01-25-transformers_project_en.md
new file mode 100644
index 00000000000000..58f2fbfdf84c2f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-transformers_project_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English transformers_project DistilBertForSequenceClassification from MuradA
+author: John Snow Labs
+name: transformers_project
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`transformers_project` is a English model originally trained by MuradA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/transformers_project_en_5.5.1_3.0_1737837177168.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/transformers_project_en_5.5.1_3.0_1737837177168.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("transformers_project","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("transformers_project", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|transformers_project|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|246.0 MB|
+
+## References
+
+https://huggingface.co/MuradA/Transformers_Project
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-transformers_project_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-transformers_project_pipeline_en.md
new file mode 100644
index 00000000000000..6eb7eb85e19b7d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-transformers_project_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English transformers_project_pipeline pipeline DistilBertForSequenceClassification from MuradA
+author: John Snow Labs
+name: transformers_project_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`transformers_project_pipeline` is a English model originally trained by MuradA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/transformers_project_pipeline_en_5.5.1_3.0_1737837190198.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/transformers_project_pipeline_en_5.5.1_3.0_1737837190198.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("transformers_project_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("transformers_project_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|transformers_project_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|246.0 MB|
+
+## References
+
+https://huggingface.co/MuradA/Transformers_Project
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-translation_jam01_en.md b/docs/_posts/ahmedlone127/2025-01-25-translation_jam01_en.md
new file mode 100644
index 00000000000000..b6dc8b6986393d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-translation_jam01_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English translation_jam01 MarianTransformer from Jam01
+author: John Snow Labs
+name: translation_jam01
+date: 2025-01-25
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`translation_jam01` is a English model originally trained by Jam01.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/translation_jam01_en_5.5.1_3.0_1737829567642.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/translation_jam01_en_5.5.1_3.0_1737829567642.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("translation_jam01","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("translation_jam01","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|translation_jam01|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|188.0 MB|
+
+## References
+
+https://huggingface.co/Jam01/Translation
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-translation_jam01_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-translation_jam01_pipeline_en.md
new file mode 100644
index 00000000000000..8f2531a99cfb59
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-translation_jam01_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English translation_jam01_pipeline pipeline MarianTransformer from Jam01
+author: John Snow Labs
+name: translation_jam01_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`translation_jam01_pipeline` is a English model originally trained by Jam01.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/translation_jam01_pipeline_en_5.5.1_3.0_1737829621095.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/translation_jam01_pipeline_en_5.5.1_3.0_1737829621095.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("translation_jam01_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("translation_jam01_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|translation_jam01_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|188.5 MB|
+
+## References
+
+https://huggingface.co/Jam01/Translation
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-travel_data_en.md b/docs/_posts/ahmedlone127/2025-01-25-travel_data_en.md
new file mode 100644
index 00000000000000..2404cca40ea5fb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-travel_data_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English travel_data T5Transformer from alexlawtengyi
+author: John Snow Labs
+name: travel_data
+date: 2025-01-25
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`travel_data` is a English model originally trained by alexlawtengyi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/travel_data_en_5.5.1_3.0_1737848799115.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/travel_data_en_5.5.1_3.0_1737848799115.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("travel_data","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("travel_data", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|travel_data|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|254.2 MB|
+
+## References
+
+https://huggingface.co/alexlawtengyi/travel_data
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-travel_data_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-travel_data_pipeline_en.md
new file mode 100644
index 00000000000000..74214f11212232
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-travel_data_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English travel_data_pipeline pipeline T5Transformer from alexlawtengyi
+author: John Snow Labs
+name: travel_data_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`travel_data_pipeline` is a English model originally trained by alexlawtengyi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/travel_data_pipeline_en_5.5.1_3.0_1737848818950.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/travel_data_pipeline_en_5.5.1_3.0_1737848818950.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("travel_data_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("travel_data_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|travel_data_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|254.2 MB|
+
+## References
+
+https://huggingface.co/alexlawtengyi/travel_data
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-turbo_en.md b/docs/_posts/ahmedlone127/2025-01-25-turbo_en.md
new file mode 100644
index 00000000000000..08e1d9279e781c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-turbo_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English turbo GPT2Transformer from SourAsslips
+author: John Snow Labs
+name: turbo
+date: 2025-01-25
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`turbo` is a English model originally trained by SourAsslips.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/turbo_en_5.5.1_3.0_1737824849187.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/turbo_en_5.5.1_3.0_1737824849187.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("turbo","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("turbo","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|turbo|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/SourAsslips/Turbo
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-turbo_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-turbo_pipeline_en.md
new file mode 100644
index 00000000000000..d401bfb1759ee3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-turbo_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English turbo_pipeline pipeline GPT2Transformer from SourAsslips
+author: John Snow Labs
+name: turbo_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`turbo_pipeline` is a English model originally trained by SourAsslips.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/turbo_pipeline_en_5.5.1_3.0_1737824914951.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/turbo_pipeline_en_5.5.1_3.0_1737824914951.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("turbo_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("turbo_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|turbo_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/SourAsslips/Turbo
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-turkish_gpt2_medium_pipeline_tr.md b/docs/_posts/ahmedlone127/2025-01-25-turkish_gpt2_medium_pipeline_tr.md
new file mode 100644
index 00000000000000..d0586ba2322028
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-turkish_gpt2_medium_pipeline_tr.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Turkish turkish_gpt2_medium_pipeline pipeline GPT2Transformer from ytu-ce-cosmos
+author: John Snow Labs
+name: turkish_gpt2_medium_pipeline
+date: 2025-01-25
+tags: [tr, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: tr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`turkish_gpt2_medium_pipeline` is a Turkish model originally trained by ytu-ce-cosmos.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/turkish_gpt2_medium_pipeline_tr_5.5.1_3.0_1737825397178.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/turkish_gpt2_medium_pipeline_tr_5.5.1_3.0_1737825397178.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("turkish_gpt2_medium_pipeline", lang = "tr")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("turkish_gpt2_medium_pipeline", lang = "tr")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|turkish_gpt2_medium_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|tr|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/ytu-ce-cosmos/turkish-gpt2-medium
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-turkish_gpt2_medium_tr.md b/docs/_posts/ahmedlone127/2025-01-25-turkish_gpt2_medium_tr.md
new file mode 100644
index 00000000000000..9bee2cfe0c2f1f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-turkish_gpt2_medium_tr.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Turkish turkish_gpt2_medium GPT2Transformer from ytu-ce-cosmos
+author: John Snow Labs
+name: turkish_gpt2_medium
+date: 2025-01-25
+tags: [tr, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: tr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`turkish_gpt2_medium` is a Turkish model originally trained by ytu-ce-cosmos.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/turkish_gpt2_medium_tr_5.5.1_3.0_1737825330132.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/turkish_gpt2_medium_tr_5.5.1_3.0_1737825330132.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("turkish_gpt2_medium","tr") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("turkish_gpt2_medium","tr") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|turkish_gpt2_medium|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|tr|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/ytu-ce-cosmos/turkish-gpt2-medium
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-turkish_gpt2_pipeline_tr.md b/docs/_posts/ahmedlone127/2025-01-25-turkish_gpt2_pipeline_tr.md
new file mode 100644
index 00000000000000..dd4b1c5a825b3f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-turkish_gpt2_pipeline_tr.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Turkish turkish_gpt2_pipeline pipeline GPT2Transformer from ytu-ce-cosmos
+author: John Snow Labs
+name: turkish_gpt2_pipeline
+date: 2025-01-25
+tags: [tr, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: tr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`turkish_gpt2_pipeline` is a Turkish model originally trained by ytu-ce-cosmos.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/turkish_gpt2_pipeline_tr_5.5.1_3.0_1737825720451.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/turkish_gpt2_pipeline_tr_5.5.1_3.0_1737825720451.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("turkish_gpt2_pipeline", lang = "tr")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("turkish_gpt2_pipeline", lang = "tr")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|turkish_gpt2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|tr|
+|Size:|467.5 MB|
+
+## References
+
+https://huggingface.co/ytu-ce-cosmos/turkish-gpt2
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-turkish_gpt2_tr.md b/docs/_posts/ahmedlone127/2025-01-25-turkish_gpt2_tr.md
new file mode 100644
index 00000000000000..5d22524d1cab91
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-turkish_gpt2_tr.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Turkish turkish_gpt2 GPT2Transformer from ytu-ce-cosmos
+author: John Snow Labs
+name: turkish_gpt2
+date: 2025-01-25
+tags: [tr, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: tr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`turkish_gpt2` is a Turkish model originally trained by ytu-ce-cosmos.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/turkish_gpt2_tr_5.5.1_3.0_1737825696639.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/turkish_gpt2_tr_5.5.1_3.0_1737825696639.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("turkish_gpt2","tr") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("turkish_gpt2","tr") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|turkish_gpt2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|tr|
+|Size:|467.4 MB|
+
+## References
+
+https://huggingface.co/ytu-ce-cosmos/turkish-gpt2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-tweet_topic_base_multilingual_pipeline_xx.md b/docs/_posts/ahmedlone127/2025-01-25-tweet_topic_base_multilingual_pipeline_xx.md
new file mode 100644
index 00000000000000..72b56da72f2f6f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-tweet_topic_base_multilingual_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual tweet_topic_base_multilingual_pipeline pipeline XlmRoBertaForSequenceClassification from cardiffnlp
+author: John Snow Labs
+name: tweet_topic_base_multilingual_pipeline
+date: 2025-01-25
+tags: [xx, open_source, pipeline, onnx]
+task: Text Classification
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tweet_topic_base_multilingual_pipeline` is a Multilingual model originally trained by cardiffnlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tweet_topic_base_multilingual_pipeline_xx_5.5.1_3.0_1737817020646.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tweet_topic_base_multilingual_pipeline_xx_5.5.1_3.0_1737817020646.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("tweet_topic_base_multilingual_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("tweet_topic_base_multilingual_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tweet_topic_base_multilingual_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/cardiffnlp/tweet-topic-base-multilingual
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-tweet_topic_base_multilingual_xx.md b/docs/_posts/ahmedlone127/2025-01-25-tweet_topic_base_multilingual_xx.md
new file mode 100644
index 00000000000000..ba65747e342530
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-tweet_topic_base_multilingual_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual tweet_topic_base_multilingual XlmRoBertaForSequenceClassification from cardiffnlp
+author: John Snow Labs
+name: tweet_topic_base_multilingual
+date: 2025-01-25
+tags: [xx, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tweet_topic_base_multilingual` is a Multilingual model originally trained by cardiffnlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tweet_topic_base_multilingual_xx_5.5.1_3.0_1737816965632.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tweet_topic_base_multilingual_xx_5.5.1_3.0_1737816965632.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("tweet_topic_base_multilingual","xx") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("tweet_topic_base_multilingual", "xx")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tweet_topic_base_multilingual|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|xx|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/cardiffnlp/tweet-topic-base-multilingual
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-tweets_gender_classifier_distilbert_en.md b/docs/_posts/ahmedlone127/2025-01-25-tweets_gender_classifier_distilbert_en.md
new file mode 100644
index 00000000000000..ff398f3f042309
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-tweets_gender_classifier_distilbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English tweets_gender_classifier_distilbert BertForSequenceClassification from dima806
+author: John Snow Labs
+name: tweets_gender_classifier_distilbert
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tweets_gender_classifier_distilbert` is a English model originally trained by dima806.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tweets_gender_classifier_distilbert_en_5.5.1_3.0_1737840364846.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tweets_gender_classifier_distilbert_en_5.5.1_3.0_1737840364846.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("tweets_gender_classifier_distilbert","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("tweets_gender_classifier_distilbert", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tweets_gender_classifier_distilbert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/dima806/tweets-gender-classifier-distilbert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-tweets_gender_classifier_distilbert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-tweets_gender_classifier_distilbert_pipeline_en.md
new file mode 100644
index 00000000000000..01d1d518ebba5f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-tweets_gender_classifier_distilbert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English tweets_gender_classifier_distilbert_pipeline pipeline BertForSequenceClassification from dima806
+author: John Snow Labs
+name: tweets_gender_classifier_distilbert_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tweets_gender_classifier_distilbert_pipeline` is a English model originally trained by dima806.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tweets_gender_classifier_distilbert_pipeline_en_5.5.1_3.0_1737840386342.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tweets_gender_classifier_distilbert_pipeline_en_5.5.1_3.0_1737840386342.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("tweets_gender_classifier_distilbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("tweets_gender_classifier_distilbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tweets_gender_classifier_distilbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/dima806/tweets-gender-classifier-distilbert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-vietnamese_t5_doc2query_legal_en.md b/docs/_posts/ahmedlone127/2025-01-25-vietnamese_t5_doc2query_legal_en.md
new file mode 100644
index 00000000000000..94e98f9b6250d1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-vietnamese_t5_doc2query_legal_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English vietnamese_t5_doc2query_legal T5Transformer from Turbo-AI
+author: John Snow Labs
+name: vietnamese_t5_doc2query_legal
+date: 2025-01-25
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vietnamese_t5_doc2query_legal` is a English model originally trained by Turbo-AI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vietnamese_t5_doc2query_legal_en_5.5.1_3.0_1737849216989.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vietnamese_t5_doc2query_legal_en_5.5.1_3.0_1737849216989.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("vietnamese_t5_doc2query_legal","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("vietnamese_t5_doc2query_legal", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vietnamese_t5_doc2query_legal|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|945.9 MB|
+
+## References
+
+https://huggingface.co/Turbo-AI/vi-t5-doc2query-legal
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-vietnamese_t5_doc2query_legal_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-vietnamese_t5_doc2query_legal_pipeline_en.md
new file mode 100644
index 00000000000000..54fc9fb8cea18a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-vietnamese_t5_doc2query_legal_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vietnamese_t5_doc2query_legal_pipeline pipeline T5Transformer from Turbo-AI
+author: John Snow Labs
+name: vietnamese_t5_doc2query_legal_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vietnamese_t5_doc2query_legal_pipeline` is a English model originally trained by Turbo-AI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vietnamese_t5_doc2query_legal_pipeline_en_5.5.1_3.0_1737849264571.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vietnamese_t5_doc2query_legal_pipeline_en_5.5.1_3.0_1737849264571.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vietnamese_t5_doc2query_legal_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vietnamese_t5_doc2query_legal_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vietnamese_t5_doc2query_legal_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|945.9 MB|
+
+## References
+
+https://huggingface.co/Turbo-AI/vi-t5-doc2query-legal
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-vizwiz_bert_base_en.md b/docs/_posts/ahmedlone127/2025-01-25-vizwiz_bert_base_en.md
new file mode 100644
index 00000000000000..d92c5f9e10e154
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-vizwiz_bert_base_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vizwiz_bert_base BertEmbeddings from nanom
+author: John Snow Labs
+name: vizwiz_bert_base
+date: 2025-01-25
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vizwiz_bert_base` is a English model originally trained by nanom.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vizwiz_bert_base_en_5.5.1_3.0_1737785326810.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vizwiz_bert_base_en_5.5.1_3.0_1737785326810.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("vizwiz_bert_base","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("vizwiz_bert_base","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vizwiz_bert_base|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/nanom/vizwiz-bert-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-vizwiz_bert_base_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-vizwiz_bert_base_pipeline_en.md
new file mode 100644
index 00000000000000..973c3b4be3703e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-vizwiz_bert_base_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English vizwiz_bert_base_pipeline pipeline BertEmbeddings from nanom
+author: John Snow Labs
+name: vizwiz_bert_base_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vizwiz_bert_base_pipeline` is a English model originally trained by nanom.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vizwiz_bert_base_pipeline_en_5.5.1_3.0_1737785348442.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vizwiz_bert_base_pipeline_en_5.5.1_3.0_1737785348442.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vizwiz_bert_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vizwiz_bert_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vizwiz_bert_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/nanom/vizwiz-bert-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-withinapps_ndd_mrbs_test_tags_en.md b/docs/_posts/ahmedlone127/2025-01-25-withinapps_ndd_mrbs_test_tags_en.md
new file mode 100644
index 00000000000000..15508ccecc5eee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-withinapps_ndd_mrbs_test_tags_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English withinapps_ndd_mrbs_test_tags DistilBertForSequenceClassification from lgk03
+author: John Snow Labs
+name: withinapps_ndd_mrbs_test_tags
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`withinapps_ndd_mrbs_test_tags` is a English model originally trained by lgk03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/withinapps_ndd_mrbs_test_tags_en_5.5.1_3.0_1737836989799.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/withinapps_ndd_mrbs_test_tags_en_5.5.1_3.0_1737836989799.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("withinapps_ndd_mrbs_test_tags","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("withinapps_ndd_mrbs_test_tags", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|withinapps_ndd_mrbs_test_tags|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/lgk03/WITHINAPPS_NDD-mrbs_test-tags
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-withinapps_ndd_mrbs_test_tags_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-withinapps_ndd_mrbs_test_tags_pipeline_en.md
new file mode 100644
index 00000000000000..60ce84b695b29d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-withinapps_ndd_mrbs_test_tags_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English withinapps_ndd_mrbs_test_tags_pipeline pipeline DistilBertForSequenceClassification from lgk03
+author: John Snow Labs
+name: withinapps_ndd_mrbs_test_tags_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`withinapps_ndd_mrbs_test_tags_pipeline` is a English model originally trained by lgk03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/withinapps_ndd_mrbs_test_tags_pipeline_en_5.5.1_3.0_1737837004342.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/withinapps_ndd_mrbs_test_tags_pipeline_en_5.5.1_3.0_1737837004342.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("withinapps_ndd_mrbs_test_tags_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("withinapps_ndd_mrbs_test_tags_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|withinapps_ndd_mrbs_test_tags_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/lgk03/WITHINAPPS_NDD-mrbs_test-tags
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-withinapps_ndd_petclinic_test_tags_en.md b/docs/_posts/ahmedlone127/2025-01-25-withinapps_ndd_petclinic_test_tags_en.md
new file mode 100644
index 00000000000000..05011908bdaae4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-withinapps_ndd_petclinic_test_tags_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English withinapps_ndd_petclinic_test_tags DistilBertForSequenceClassification from lgk03
+author: John Snow Labs
+name: withinapps_ndd_petclinic_test_tags
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`withinapps_ndd_petclinic_test_tags` is a English model originally trained by lgk03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/withinapps_ndd_petclinic_test_tags_en_5.5.1_3.0_1737836137761.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/withinapps_ndd_petclinic_test_tags_en_5.5.1_3.0_1737836137761.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("withinapps_ndd_petclinic_test_tags","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("withinapps_ndd_petclinic_test_tags", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|withinapps_ndd_petclinic_test_tags|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/lgk03/WITHINAPPS_NDD-petclinic_test-tags
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-withinapps_ndd_petclinic_test_tags_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-withinapps_ndd_petclinic_test_tags_pipeline_en.md
new file mode 100644
index 00000000000000..a32ad7bc04d790
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-withinapps_ndd_petclinic_test_tags_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English withinapps_ndd_petclinic_test_tags_pipeline pipeline DistilBertForSequenceClassification from lgk03
+author: John Snow Labs
+name: withinapps_ndd_petclinic_test_tags_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`withinapps_ndd_petclinic_test_tags_pipeline` is a English model originally trained by lgk03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/withinapps_ndd_petclinic_test_tags_pipeline_en_5.5.1_3.0_1737836151003.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/withinapps_ndd_petclinic_test_tags_pipeline_en_5.5.1_3.0_1737836151003.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("withinapps_ndd_petclinic_test_tags_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("withinapps_ndd_petclinic_test_tags_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|withinapps_ndd_petclinic_test_tags_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/lgk03/WITHINAPPS_NDD-petclinic_test-tags
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-withinapps_ndd_phoenix_test_tags_en.md b/docs/_posts/ahmedlone127/2025-01-25-withinapps_ndd_phoenix_test_tags_en.md
new file mode 100644
index 00000000000000..a58f3e25cd7d42
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-withinapps_ndd_phoenix_test_tags_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English withinapps_ndd_phoenix_test_tags DistilBertForSequenceClassification from lgk03
+author: John Snow Labs
+name: withinapps_ndd_phoenix_test_tags
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`withinapps_ndd_phoenix_test_tags` is a English model originally trained by lgk03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/withinapps_ndd_phoenix_test_tags_en_5.5.1_3.0_1737836747755.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/withinapps_ndd_phoenix_test_tags_en_5.5.1_3.0_1737836747755.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("withinapps_ndd_phoenix_test_tags","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("withinapps_ndd_phoenix_test_tags", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|withinapps_ndd_phoenix_test_tags|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/lgk03/WITHINAPPS_NDD-phoenix_test-tags
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-withinapps_ndd_phoenix_test_tags_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-withinapps_ndd_phoenix_test_tags_pipeline_en.md
new file mode 100644
index 00000000000000..ebd7af4b584820
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-withinapps_ndd_phoenix_test_tags_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English withinapps_ndd_phoenix_test_tags_pipeline pipeline DistilBertForSequenceClassification from lgk03
+author: John Snow Labs
+name: withinapps_ndd_phoenix_test_tags_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`withinapps_ndd_phoenix_test_tags_pipeline` is a English model originally trained by lgk03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/withinapps_ndd_phoenix_test_tags_pipeline_en_5.5.1_3.0_1737836760929.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/withinapps_ndd_phoenix_test_tags_pipeline_en_5.5.1_3.0_1737836760929.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("withinapps_ndd_phoenix_test_tags_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("withinapps_ndd_phoenix_test_tags_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|withinapps_ndd_phoenix_test_tags_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/lgk03/WITHINAPPS_NDD-phoenix_test-tags
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xl_en.md b/docs/_posts/ahmedlone127/2025-01-25-xl_en.md
new file mode 100644
index 00000000000000..bc3521682ecc6a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xl_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xl XlmRoBertaForTokenClassification from Dharmesh1243
+author: John Snow Labs
+name: xl
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xl` is a English model originally trained by Dharmesh1243.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xl_en_5.5.1_3.0_1737831618617.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xl_en_5.5.1_3.0_1737831618617.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xl","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xl", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xl|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|879.7 MB|
+
+## References
+
+https://huggingface.co/Dharmesh1243/xl
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xl_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xl_pipeline_en.md
new file mode 100644
index 00000000000000..a93e5138977217
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xl_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xl_pipeline pipeline XlmRoBertaForTokenClassification from Dharmesh1243
+author: John Snow Labs
+name: xl_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xl_pipeline` is a English model originally trained by Dharmesh1243.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xl_pipeline_en_5.5.1_3.0_1737831711092.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xl_pipeline_en_5.5.1_3.0_1737831711092.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xl_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xl_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xl_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|879.7 MB|
+
+## References
+
+https://huggingface.co/Dharmesh1243/xl
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_en.md
new file mode 100644
index 00000000000000..8e74f08523ab87
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base XlmRoBertaForTokenClassification from hungphongtrn
+author: John Snow Labs
+name: xlm_roberta_base
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base` is a English model originally trained by hungphongtrn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_en_5.5.1_3.0_1737791850120.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_en_5.5.1_3.0_1737791850120.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|794.9 MB|
+
+## References
+
+https://huggingface.co/hungphongtrn/xlm-roberta-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_filnetuend_panx_english_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_filnetuend_panx_english_en.md
new file mode 100644
index 00000000000000..32e322c14679b8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_filnetuend_panx_english_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_filnetuend_panx_english XlmRoBertaForTokenClassification from Kuzumaru2017
+author: John Snow Labs
+name: xlm_roberta_base_filnetuend_panx_english
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_filnetuend_panx_english` is a English model originally trained by Kuzumaru2017.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_filnetuend_panx_english_en_5.5.1_3.0_1737804274272.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_filnetuend_panx_english_en_5.5.1_3.0_1737804274272.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_filnetuend_panx_english","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_filnetuend_panx_english", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_filnetuend_panx_english|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/Kuzumaru2017/xlm-roberta-base-filnetuend-panx-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_filnetuend_panx_english_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_filnetuend_panx_english_pipeline_en.md
new file mode 100644
index 00000000000000..2682c9b65a0417
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_filnetuend_panx_english_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_filnetuend_panx_english_pipeline pipeline XlmRoBertaForTokenClassification from Kuzumaru2017
+author: John Snow Labs
+name: xlm_roberta_base_filnetuend_panx_english_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_filnetuend_panx_english_pipeline` is a English model originally trained by Kuzumaru2017.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_filnetuend_panx_english_pipeline_en_5.5.1_3.0_1737804387606.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_filnetuend_panx_english_pipeline_en_5.5.1_3.0_1737804387606.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_filnetuend_panx_english_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_filnetuend_panx_english_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_filnetuend_panx_english_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/Kuzumaru2017/xlm-roberta-base-filnetuend-panx-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_sent2_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_sent2_en.md
new file mode 100644
index 00000000000000..2e2c3e26dfd7eb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_sent2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_sent2 XlmRoBertaForSequenceClassification from RogerB
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_sent2
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_sent2` is a English model originally trained by RogerB.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_sent2_en_5.5.1_3.0_1737816156415.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_sent2_en_5.5.1_3.0_1737816156415.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_sent2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_sent2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_sent2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/RogerB/xlm-roberta-base-finetuned-kinyarwanda-kin-finetuned-kin-sent2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_sent2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_sent2_pipeline_en.md
new file mode 100644
index 00000000000000..f274691622c7ca
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_sent2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_sent2_pipeline pipeline XlmRoBertaForSequenceClassification from RogerB
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_sent2_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_sent2_pipeline` is a English model originally trained by RogerB.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_sent2_pipeline_en_5.5.1_3.0_1737816211112.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_sent2_pipeline_en_5.5.1_3.0_1737816211112.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_sent2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_sent2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_kinyarwanda_kinyarwanda_finetuned_kinyarwanda_sent2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/RogerB/xlm-roberta-base-finetuned-kinyarwanda-kin-finetuned-kin-sent2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_m_reach_seller_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_m_reach_seller_en.md
new file mode 100644
index 00000000000000..172af82c4605fa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_m_reach_seller_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_m_reach_seller XlmRoBertaForSequenceClassification from Gregorig
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_m_reach_seller
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_m_reach_seller` is a English model originally trained by Gregorig.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_m_reach_seller_en_5.5.1_3.0_1737816260416.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_m_reach_seller_en_5.5.1_3.0_1737816260416.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_finetuned_m_reach_seller","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_finetuned_m_reach_seller", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_m_reach_seller|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|796.4 MB|
+
+## References
+
+https://huggingface.co/Gregorig/xlm-roberta-base-finetuned-m_reach_seller
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_m_reach_seller_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_m_reach_seller_pipeline_en.md
new file mode 100644
index 00000000000000..a596f0ab16f8e5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_m_reach_seller_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_m_reach_seller_pipeline pipeline XlmRoBertaForSequenceClassification from Gregorig
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_m_reach_seller_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_m_reach_seller_pipeline` is a English model originally trained by Gregorig.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_m_reach_seller_pipeline_en_5.5.1_3.0_1737816387641.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_m_reach_seller_pipeline_en_5.5.1_3.0_1737816387641.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_m_reach_seller_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_m_reach_seller_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_m_reach_seller_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|796.4 MB|
+
+## References
+
+https://huggingface.co/Gregorig/xlm-roberta-base-finetuned-m_reach_seller
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_ner_spa_english_9_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_ner_spa_english_9_en.md
new file mode 100644
index 00000000000000..6f955f052bc1e2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_ner_spa_english_9_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_ner_spa_english_9 XlmRoBertaForTokenClassification from gus07ven
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_ner_spa_english_9
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_ner_spa_english_9` is a English model originally trained by gus07ven.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_ner_spa_english_9_en_5.5.1_3.0_1737803077972.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_ner_spa_english_9_en_5.5.1_3.0_1737803077972.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_ner_spa_english_9","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_ner_spa_english_9", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_ner_spa_english_9|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|848.4 MB|
+
+## References
+
+https://huggingface.co/gus07ven/xlm-roberta-base-finetuned-ner-spa-en-9
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_ner_spa_english_9_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_ner_spa_english_9_pipeline_en.md
new file mode 100644
index 00000000000000..fab8c8610b549f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_ner_spa_english_9_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_ner_spa_english_9_pipeline pipeline XlmRoBertaForTokenClassification from gus07ven
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_ner_spa_english_9_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_ner_spa_english_9_pipeline` is a English model originally trained by gus07ven.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_ner_spa_english_9_pipeline_en_5.5.1_3.0_1737803158632.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_ner_spa_english_9_pipeline_en_5.5.1_3.0_1737803158632.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_ner_spa_english_9_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_ner_spa_english_9_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_ner_spa_english_9_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|848.5 MB|
+
+## References
+
+https://huggingface.co/gus07ven/xlm-roberta-base-finetuned-ner-spa-en-9
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_ner_vahan123_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_ner_vahan123_en.md
new file mode 100644
index 00000000000000..7360ef6e091aa9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_ner_vahan123_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_ner_vahan123 XlmRoBertaForTokenClassification from Vahan123
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_ner_vahan123
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_ner_vahan123` is a English model originally trained by Vahan123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_ner_vahan123_en_5.5.1_3.0_1737831315488.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_ner_vahan123_en_5.5.1_3.0_1737831315488.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_ner_vahan123","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_ner_vahan123", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_ner_vahan123|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|803.9 MB|
+
+## References
+
+https://huggingface.co/Vahan123/xlm-roberta-base-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_ner_vahan123_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_ner_vahan123_pipeline_en.md
new file mode 100644
index 00000000000000..9e96ddf1ed58c6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_ner_vahan123_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_ner_vahan123_pipeline pipeline XlmRoBertaForTokenClassification from Vahan123
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_ner_vahan123_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_ner_vahan123_pipeline` is a English model originally trained by Vahan123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_ner_vahan123_pipeline_en_5.5.1_3.0_1737831429207.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_ner_vahan123_pipeline_en_5.5.1_3.0_1737831429207.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_ner_vahan123_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_ner_vahan123_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_ner_vahan123_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|803.9 MB|
+
+## References
+
+https://huggingface.co/Vahan123/xlm-roberta-base-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_ahid1_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_ahid1_en.md
new file mode 100644
index 00000000000000..f2bbe83531f20f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_ahid1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_ahid1 XlmRoBertaForTokenClassification from ahid1
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_ahid1
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_ahid1` is a English model originally trained by ahid1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_ahid1_en_5.5.1_3.0_1737831056852.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_ahid1_en_5.5.1_3.0_1737831056852.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_ahid1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_ahid1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_ahid1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/ahid1/xlm-roberta-base-finetuned-panx-all
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_ahid1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_ahid1_pipeline_en.md
new file mode 100644
index 00000000000000..b70d60fe19f9e5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_ahid1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_ahid1_pipeline pipeline XlmRoBertaForTokenClassification from ahid1
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_ahid1_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_ahid1_pipeline` is a English model originally trained by ahid1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_ahid1_pipeline_en_5.5.1_3.0_1737831157491.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_ahid1_pipeline_en_5.5.1_3.0_1737831157491.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_ahid1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_ahid1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_ahid1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/ahid1/xlm-roberta-base-finetuned-panx-all
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_andrew45_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_andrew45_en.md
new file mode 100644
index 00000000000000..bfdba4c34bc138
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_andrew45_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_andrew45 XlmRoBertaForTokenClassification from andrew45
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_andrew45
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_andrew45` is a English model originally trained by andrew45.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_andrew45_en_5.5.1_3.0_1737804601870.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_andrew45_en_5.5.1_3.0_1737804601870.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_andrew45","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_andrew45", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_andrew45|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/andrew45/xlm-roberta-base-finetuned-panx-all
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_andrew45_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_andrew45_pipeline_en.md
new file mode 100644
index 00000000000000..040df5d8743985
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_andrew45_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_andrew45_pipeline pipeline XlmRoBertaForTokenClassification from andrew45
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_andrew45_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_andrew45_pipeline` is a English model originally trained by andrew45.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_andrew45_pipeline_en_5.5.1_3.0_1737804689744.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_andrew45_pipeline_en_5.5.1_3.0_1737804689744.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_andrew45_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_andrew45_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_andrew45_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/andrew45/xlm-roberta-base-finetuned-panx-all
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_arkya_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_arkya_en.md
new file mode 100644
index 00000000000000..38db2a97421bfd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_arkya_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_arkya XlmRoBertaForTokenClassification from Arkya
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_arkya
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_arkya` is a English model originally trained by Arkya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_arkya_en_5.5.1_3.0_1737777267073.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_arkya_en_5.5.1_3.0_1737777267073.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_arkya","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_arkya", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_arkya|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/Arkya/xlm-roberta-base-finetuned-panx-all
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_arkya_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_arkya_pipeline_en.md
new file mode 100644
index 00000000000000..b2e8fdc0c5ca87
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_arkya_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_arkya_pipeline pipeline XlmRoBertaForTokenClassification from Arkya
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_arkya_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_arkya_pipeline` is a English model originally trained by Arkya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_arkya_pipeline_en_5.5.1_3.0_1737777353345.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_arkya_pipeline_en_5.5.1_3.0_1737777353345.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_arkya_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_arkya_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_arkya_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/Arkya/xlm-roberta-base-finetuned-panx-all
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_darinj2_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_darinj2_en.md
new file mode 100644
index 00000000000000..567ec117c8fe88
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_darinj2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_darinj2 XlmRoBertaForTokenClassification from darinj2
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_darinj2
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_darinj2` is a English model originally trained by darinj2.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_darinj2_en_5.5.1_3.0_1737802974619.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_darinj2_en_5.5.1_3.0_1737802974619.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_darinj2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_darinj2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_darinj2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/darinj2/xlm-roberta-base-finetuned-panx-all
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_darinj2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_darinj2_pipeline_en.md
new file mode 100644
index 00000000000000..9bb3fce5740e78
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_darinj2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_darinj2_pipeline pipeline XlmRoBertaForTokenClassification from darinj2
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_darinj2_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_darinj2_pipeline` is a English model originally trained by darinj2.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_darinj2_pipeline_en_5.5.1_3.0_1737803061379.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_darinj2_pipeline_en_5.5.1_3.0_1737803061379.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_darinj2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_darinj2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_darinj2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/darinj2/xlm-roberta-base-finetuned-panx-all
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_jongbaly_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_jongbaly_en.md
new file mode 100644
index 00000000000000..a50c13422a708f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_jongbaly_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_jongbaly XlmRoBertaForTokenClassification from jongbaly
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_jongbaly
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_jongbaly` is a English model originally trained by jongbaly.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_jongbaly_en_5.5.1_3.0_1737791564509.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_jongbaly_en_5.5.1_3.0_1737791564509.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_jongbaly","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_jongbaly", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_jongbaly|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/jongbaly/xlm-roberta-base-finetuned-panx-all
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_jongbaly_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_jongbaly_pipeline_en.md
new file mode 100644
index 00000000000000..0ca70f30596dc5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_jongbaly_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_jongbaly_pipeline pipeline XlmRoBertaForTokenClassification from jongbaly
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_jongbaly_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_jongbaly_pipeline` is a English model originally trained by jongbaly.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_jongbaly_pipeline_en_5.5.1_3.0_1737791650485.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_jongbaly_pipeline_en_5.5.1_3.0_1737791650485.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_jongbaly_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_jongbaly_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_jongbaly_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/jongbaly/xlm-roberta-base-finetuned-panx-all
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_july_tokyo_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_july_tokyo_en.md
new file mode 100644
index 00000000000000..a1efb6aa67055d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_july_tokyo_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_july_tokyo XlmRoBertaForTokenClassification from July-Tokyo
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_july_tokyo
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_july_tokyo` is a English model originally trained by July-Tokyo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_july_tokyo_en_5.5.1_3.0_1737832281843.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_july_tokyo_en_5.5.1_3.0_1737832281843.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_july_tokyo","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_july_tokyo", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_july_tokyo|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/July-Tokyo/xlm-roberta-base-finetuned-panx-all
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_july_tokyo_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_july_tokyo_pipeline_en.md
new file mode 100644
index 00000000000000..5f1670164a68ea
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_july_tokyo_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_july_tokyo_pipeline pipeline XlmRoBertaForTokenClassification from July-Tokyo
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_july_tokyo_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_july_tokyo_pipeline` is a English model originally trained by July-Tokyo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_july_tokyo_pipeline_en_5.5.1_3.0_1737832367067.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_july_tokyo_pipeline_en_5.5.1_3.0_1737832367067.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_july_tokyo_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_july_tokyo_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_july_tokyo_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/July-Tokyo/xlm-roberta-base-finetuned-panx-all
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_kikim6114_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_kikim6114_en.md
new file mode 100644
index 00000000000000..ee0b213fe32c13
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_kikim6114_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_kikim6114 XlmRoBertaForTokenClassification from kikim6114
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_kikim6114
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_kikim6114` is a English model originally trained by kikim6114.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_kikim6114_en_5.5.1_3.0_1737779762303.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_kikim6114_en_5.5.1_3.0_1737779762303.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_kikim6114","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_kikim6114", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_kikim6114|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/kikim6114/xlm-roberta-base-finetuned-panx-all
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_kikim6114_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_kikim6114_pipeline_en.md
new file mode 100644
index 00000000000000..bc9e9030702240
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_kikim6114_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_kikim6114_pipeline pipeline XlmRoBertaForTokenClassification from kikim6114
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_kikim6114_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_kikim6114_pipeline` is a English model originally trained by kikim6114.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_kikim6114_pipeline_en_5.5.1_3.0_1737779849024.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_kikim6114_pipeline_en_5.5.1_3.0_1737779849024.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_kikim6114_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_kikim6114_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_kikim6114_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/kikim6114/xlm-roberta-base-finetuned-panx-all
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_langs_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_langs_en.md
new file mode 100644
index 00000000000000..1ad567dee6d22a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_langs_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_langs XlmRoBertaForTokenClassification from tommyjin
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_langs
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_langs` is a English model originally trained by tommyjin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_langs_en_5.5.1_3.0_1737802372787.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_langs_en_5.5.1_3.0_1737802372787.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_langs","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_langs", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_langs|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|848.3 MB|
+
+## References
+
+https://huggingface.co/tommyjin/xlm-roberta-base-finetuned-panx-all-langs
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_langs_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_langs_pipeline_en.md
new file mode 100644
index 00000000000000..786f2ae0c19cf1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_langs_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_langs_pipeline pipeline XlmRoBertaForTokenClassification from tommyjin
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_langs_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_langs_pipeline` is a English model originally trained by tommyjin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_langs_pipeline_en_5.5.1_3.0_1737802460591.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_langs_pipeline_en_5.5.1_3.0_1737802460591.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_langs_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_langs_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_langs_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|848.4 MB|
+
+## References
+
+https://huggingface.co/tommyjin/xlm-roberta-base-finetuned-panx-all-langs
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_loki47_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_loki47_en.md
new file mode 100644
index 00000000000000..d7a17e01a04ebe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_loki47_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_loki47 XlmRoBertaForTokenClassification from loki47
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_loki47
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_loki47` is a English model originally trained by loki47.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_loki47_en_5.5.1_3.0_1737776728032.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_loki47_en_5.5.1_3.0_1737776728032.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_loki47","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_loki47", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_loki47|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/loki47/xlm-roberta-base-finetuned-panx-all
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_loki47_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_loki47_pipeline_en.md
new file mode 100644
index 00000000000000..a2e9e787d62886
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_loki47_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_loki47_pipeline pipeline XlmRoBertaForTokenClassification from loki47
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_loki47_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_loki47_pipeline` is a English model originally trained by loki47.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_loki47_pipeline_en_5.5.1_3.0_1737776839147.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_loki47_pipeline_en_5.5.1_3.0_1737776839147.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_loki47_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_loki47_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_loki47_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/loki47/xlm-roberta-base-finetuned-panx-all
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_mcguiver_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_mcguiver_en.md
new file mode 100644
index 00000000000000..3a17ce520f0104
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_mcguiver_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_mcguiver XlmRoBertaForTokenClassification from mcguiver
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_mcguiver
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_mcguiver` is a English model originally trained by mcguiver.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_mcguiver_en_5.5.1_3.0_1737831466667.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_mcguiver_en_5.5.1_3.0_1737831466667.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_mcguiver","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_mcguiver", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_mcguiver|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/mcguiver/xlm-roberta-base-finetuned-panx-all
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_mcguiver_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_mcguiver_pipeline_en.md
new file mode 100644
index 00000000000000..7a9a79a3a4c162
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_mcguiver_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_mcguiver_pipeline pipeline XlmRoBertaForTokenClassification from mcguiver
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_mcguiver_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_mcguiver_pipeline` is a English model originally trained by mcguiver.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_mcguiver_pipeline_en_5.5.1_3.0_1737831558551.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_mcguiver_pipeline_en_5.5.1_3.0_1737831558551.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_mcguiver_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_mcguiver_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_mcguiver_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/mcguiver/xlm-roberta-base-finetuned-panx-all
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_mkanare_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_mkanare_en.md
new file mode 100644
index 00000000000000..7fa61e14352e2e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_mkanare_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_mkanare XlmRoBertaForTokenClassification from mkanare
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_mkanare
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_mkanare` is a English model originally trained by mkanare.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_mkanare_en_5.5.1_3.0_1737831056766.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_mkanare_en_5.5.1_3.0_1737831056766.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_mkanare","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_mkanare", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_mkanare|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/mkanare/xlm-roberta-base-finetuned-panx-all
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_mkanare_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_mkanare_pipeline_en.md
new file mode 100644
index 00000000000000..d99cbb06225498
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_mkanare_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_mkanare_pipeline pipeline XlmRoBertaForTokenClassification from mkanare
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_mkanare_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_mkanare_pipeline` is a English model originally trained by mkanare.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_mkanare_pipeline_en_5.5.1_3.0_1737831157145.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_mkanare_pipeline_en_5.5.1_3.0_1737831157145.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_mkanare_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_mkanare_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_mkanare_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/mkanare/xlm-roberta-base-finetuned-panx-all
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_qkdaf_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_qkdaf_en.md
new file mode 100644
index 00000000000000..c01c5beefc9ed5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_qkdaf_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_qkdaf XlmRoBertaForTokenClassification from qkdaf
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_qkdaf
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_qkdaf` is a English model originally trained by qkdaf.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_qkdaf_en_5.5.1_3.0_1737804277352.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_qkdaf_en_5.5.1_3.0_1737804277352.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_qkdaf","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_qkdaf", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_qkdaf|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/qkdaf/xlm-roberta-base-finetuned-panx-all
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_qkdaf_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_qkdaf_pipeline_en.md
new file mode 100644
index 00000000000000..be4434d01d549d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_qkdaf_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_qkdaf_pipeline pipeline XlmRoBertaForTokenClassification from qkdaf
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_qkdaf_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_qkdaf_pipeline` is a English model originally trained by qkdaf.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_qkdaf_pipeline_en_5.5.1_3.0_1737804367343.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_qkdaf_pipeline_en_5.5.1_3.0_1737804367343.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_qkdaf_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_qkdaf_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_qkdaf_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/qkdaf/xlm-roberta-base-finetuned-panx-all
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_raegold_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_raegold_en.md
new file mode 100644
index 00000000000000..2dc4e163c6ff75
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_raegold_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_raegold XlmRoBertaForTokenClassification from RaeGold
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_raegold
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_raegold` is a English model originally trained by RaeGold.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_raegold_en_5.5.1_3.0_1737803935092.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_raegold_en_5.5.1_3.0_1737803935092.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_raegold","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_raegold", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_raegold|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/RaeGold/xlm-roberta-base-finetuned-panx-all
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_raegold_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_raegold_pipeline_en.md
new file mode 100644
index 00000000000000..76919924597a5a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_raegold_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_raegold_pipeline pipeline XlmRoBertaForTokenClassification from RaeGold
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_raegold_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_raegold_pipeline` is a English model originally trained by RaeGold.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_raegold_pipeline_en_5.5.1_3.0_1737804027614.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_raegold_pipeline_en_5.5.1_3.0_1737804027614.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_raegold_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_raegold_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_raegold_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/RaeGold/xlm-roberta-base-finetuned-panx-all
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_rlawltjd_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_rlawltjd_en.md
new file mode 100644
index 00000000000000..6e79c751743fa2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_rlawltjd_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_rlawltjd XlmRoBertaForTokenClassification from rlawltjd
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_rlawltjd
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_rlawltjd` is a English model originally trained by rlawltjd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_rlawltjd_en_5.5.1_3.0_1737833901369.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_rlawltjd_en_5.5.1_3.0_1737833901369.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_rlawltjd","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_rlawltjd", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_rlawltjd|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/rlawltjd/xlm-roberta-base-finetuned-panx-all
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_rlawltjd_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_rlawltjd_pipeline_en.md
new file mode 100644
index 00000000000000..5619eafafe2b4f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_rlawltjd_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_rlawltjd_pipeline pipeline XlmRoBertaForTokenClassification from rlawltjd
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_rlawltjd_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_rlawltjd_pipeline` is a English model originally trained by rlawltjd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_rlawltjd_pipeline_en_5.5.1_3.0_1737833985772.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_rlawltjd_pipeline_en_5.5.1_3.0_1737833985772.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_rlawltjd_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_rlawltjd_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_rlawltjd_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/rlawltjd/xlm-roberta-base-finetuned-panx-all
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_starklin_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_starklin_en.md
new file mode 100644
index 00000000000000..3a58e3402353dd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_starklin_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_starklin XlmRoBertaForTokenClassification from starklin
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_starklin
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_starklin` is a English model originally trained by starklin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_starklin_en_5.5.1_3.0_1737804708168.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_starklin_en_5.5.1_3.0_1737804708168.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_starklin","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_starklin", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_starklin|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/starklin/xlm-roberta-base-finetuned-panx-all
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_starklin_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_starklin_pipeline_en.md
new file mode 100644
index 00000000000000..4b853d4c68cda8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_starklin_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_starklin_pipeline pipeline XlmRoBertaForTokenClassification from starklin
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_starklin_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_starklin_pipeline` is a English model originally trained by starklin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_starklin_pipeline_en_5.5.1_3.0_1737804795178.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_starklin_pipeline_en_5.5.1_3.0_1737804795178.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_starklin_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_starklin_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_starklin_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/starklin/xlm-roberta-base-finetuned-panx-all
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_taoyoung_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_taoyoung_en.md
new file mode 100644
index 00000000000000..2ee4f012045f13
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_taoyoung_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_taoyoung XlmRoBertaForTokenClassification from taoyoung
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_taoyoung
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_taoyoung` is a English model originally trained by taoyoung.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_taoyoung_en_5.5.1_3.0_1737778403668.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_taoyoung_en_5.5.1_3.0_1737778403668.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_taoyoung","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_taoyoung", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_taoyoung|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|849.7 MB|
+
+## References
+
+https://huggingface.co/taoyoung/xlm-roberta-base-finetuned-panx-all
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_taoyoung_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_taoyoung_pipeline_en.md
new file mode 100644
index 00000000000000..d191f2cfeef464
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_taoyoung_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_taoyoung_pipeline pipeline XlmRoBertaForTokenClassification from taoyoung
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_taoyoung_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_taoyoung_pipeline` is a English model originally trained by taoyoung.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_taoyoung_pipeline_en_5.5.1_3.0_1737778490096.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_taoyoung_pipeline_en_5.5.1_3.0_1737778490096.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_taoyoung_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_taoyoung_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_taoyoung_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|849.7 MB|
+
+## References
+
+https://huggingface.co/taoyoung/xlm-roberta-base-finetuned-panx-all
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_thundergod_zenitsu_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_thundergod_zenitsu_en.md
new file mode 100644
index 00000000000000..7cbb047d358619
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_thundergod_zenitsu_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_thundergod_zenitsu XlmRoBertaForTokenClassification from thundergod-zenitsu
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_thundergod_zenitsu
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_thundergod_zenitsu` is a English model originally trained by thundergod-zenitsu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_thundergod_zenitsu_en_5.5.1_3.0_1737832114606.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_thundergod_zenitsu_en_5.5.1_3.0_1737832114606.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_thundergod_zenitsu","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_thundergod_zenitsu", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_thundergod_zenitsu|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/thundergod-zenitsu/xlm-roberta-base-finetuned-panx-all
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_thundergod_zenitsu_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_thundergod_zenitsu_pipeline_en.md
new file mode 100644
index 00000000000000..85870664cfa722
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_thundergod_zenitsu_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_thundergod_zenitsu_pipeline pipeline XlmRoBertaForTokenClassification from thundergod-zenitsu
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_thundergod_zenitsu_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_thundergod_zenitsu_pipeline` is a English model originally trained by thundergod-zenitsu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_thundergod_zenitsu_pipeline_en_5.5.1_3.0_1737832199855.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_thundergod_zenitsu_pipeline_en_5.5.1_3.0_1737832199855.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_thundergod_zenitsu_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_thundergod_zenitsu_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_thundergod_zenitsu_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/thundergod-zenitsu/xlm-roberta-base-finetuned-panx-all
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_ysige_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_ysige_en.md
new file mode 100644
index 00000000000000..5e50bed4da1cf0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_ysige_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_ysige XlmRoBertaForTokenClassification from ysige
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_ysige
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_ysige` is a English model originally trained by ysige.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_ysige_en_5.5.1_3.0_1737832183141.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_ysige_en_5.5.1_3.0_1737832183141.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_ysige","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_ysige", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_ysige|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|861.0 MB|
+
+## References
+
+https://huggingface.co/ysige/xlm-roberta-base-finetuned-panx-all
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_ysige_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_ysige_pipeline_en.md
new file mode 100644
index 00000000000000..57dc18e13b6ffe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_ysige_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_ysige_pipeline pipeline XlmRoBertaForTokenClassification from ysige
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_ysige_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_ysige_pipeline` is a English model originally trained by ysige.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_ysige_pipeline_en_5.5.1_3.0_1737832249253.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_ysige_pipeline_en_5.5.1_3.0_1737832249253.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_ysige_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_ysige_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_ysige_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|861.0 MB|
+
+## References
+
+https://huggingface.co/ysige/xlm-roberta-base-finetuned-panx-all
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_zachhofstad_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_zachhofstad_en.md
new file mode 100644
index 00000000000000..d9ef180c6bcac2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_zachhofstad_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_zachhofstad XlmRoBertaForTokenClassification from zachhofstad
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_zachhofstad
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_zachhofstad` is a English model originally trained by zachhofstad.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_zachhofstad_en_5.5.1_3.0_1737779185945.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_zachhofstad_en_5.5.1_3.0_1737779185945.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_zachhofstad","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_zachhofstad", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_zachhofstad|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/zachhofstad/xlm-roberta-base-finetuned-panx-all
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_zachhofstad_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_zachhofstad_pipeline_en.md
new file mode 100644
index 00000000000000..545807f989709e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_all_zachhofstad_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_zachhofstad_pipeline pipeline XlmRoBertaForTokenClassification from zachhofstad
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_zachhofstad_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_zachhofstad_pipeline` is a English model originally trained by zachhofstad.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_zachhofstad_pipeline_en_5.5.1_3.0_1737779272654.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_zachhofstad_pipeline_en_5.5.1_3.0_1737779272654.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_zachhofstad_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_zachhofstad_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_zachhofstad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/zachhofstad/xlm-roberta-base-finetuned-panx-all
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_arabic_abot3mar_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_arabic_abot3mar_en.md
new file mode 100644
index 00000000000000..a233bb8c77e3e8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_arabic_abot3mar_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_arabic_abot3mar XlmRoBertaForTokenClassification from abot3mar
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_arabic_abot3mar
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_arabic_abot3mar` is a English model originally trained by abot3mar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_arabic_abot3mar_en_5.5.1_3.0_1737793326253.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_arabic_abot3mar_en_5.5.1_3.0_1737793326253.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_arabic_abot3mar","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_arabic_abot3mar", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_arabic_abot3mar|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|821.4 MB|
+
+## References
+
+https://huggingface.co/abot3mar/xlm-roberta-base-finetuned-panx-ar
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_arabic_abot3mar_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_arabic_abot3mar_pipeline_en.md
new file mode 100644
index 00000000000000..7c3d5255c584cc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_arabic_abot3mar_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_arabic_abot3mar_pipeline pipeline XlmRoBertaForTokenClassification from abot3mar
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_arabic_abot3mar_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_arabic_abot3mar_pipeline` is a English model originally trained by abot3mar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_arabic_abot3mar_pipeline_en_5.5.1_3.0_1737793429403.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_arabic_abot3mar_pipeline_en_5.5.1_3.0_1737793429403.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_arabic_abot3mar_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_arabic_abot3mar_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_arabic_abot3mar_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|821.4 MB|
+
+## References
+
+https://huggingface.co/abot3mar/xlm-roberta-base-finetuned-panx-ar
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_arabic_habahbeh_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_arabic_habahbeh_en.md
new file mode 100644
index 00000000000000..04d418793b666f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_arabic_habahbeh_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_arabic_habahbeh XlmRoBertaForTokenClassification from habahbeh
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_arabic_habahbeh
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_arabic_habahbeh` is a English model originally trained by habahbeh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_arabic_habahbeh_en_5.5.1_3.0_1737803741177.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_arabic_habahbeh_en_5.5.1_3.0_1737803741177.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_arabic_habahbeh","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_arabic_habahbeh", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_arabic_habahbeh|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|829.8 MB|
+
+## References
+
+https://huggingface.co/habahbeh/xlm-roberta-base-finetuned-panx-ar
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_arabic_habahbeh_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_arabic_habahbeh_pipeline_en.md
new file mode 100644
index 00000000000000..65c5765eb8c146
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_arabic_habahbeh_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_arabic_habahbeh_pipeline pipeline XlmRoBertaForTokenClassification from habahbeh
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_arabic_habahbeh_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_arabic_habahbeh_pipeline` is a English model originally trained by habahbeh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_arabic_habahbeh_pipeline_en_5.5.1_3.0_1737803831269.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_arabic_habahbeh_pipeline_en_5.5.1_3.0_1737803831269.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_arabic_habahbeh_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_arabic_habahbeh_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_arabic_habahbeh_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|829.8 MB|
+
+## References
+
+https://huggingface.co/habahbeh/xlm-roberta-base-finetuned-panx-ar
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_arabic_mayasalsa3_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_arabic_mayasalsa3_en.md
new file mode 100644
index 00000000000000..7764e3c65610cb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_arabic_mayasalsa3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_arabic_mayasalsa3 XlmRoBertaForTokenClassification from MayaSalsa3
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_arabic_mayasalsa3
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_arabic_mayasalsa3` is a English model originally trained by MayaSalsa3.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_arabic_mayasalsa3_en_5.5.1_3.0_1737801978645.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_arabic_mayasalsa3_en_5.5.1_3.0_1737801978645.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_arabic_mayasalsa3","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_arabic_mayasalsa3", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_arabic_mayasalsa3|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|821.4 MB|
+
+## References
+
+https://huggingface.co/MayaSalsa3/xlm-roberta-base-finetuned-panx-ar
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_arabic_mayasalsa3_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_arabic_mayasalsa3_pipeline_en.md
new file mode 100644
index 00000000000000..478a7a6fc29acf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_arabic_mayasalsa3_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_arabic_mayasalsa3_pipeline pipeline XlmRoBertaForTokenClassification from MayaSalsa3
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_arabic_mayasalsa3_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_arabic_mayasalsa3_pipeline` is a English model originally trained by MayaSalsa3.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_arabic_mayasalsa3_pipeline_en_5.5.1_3.0_1737802083179.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_arabic_mayasalsa3_pipeline_en_5.5.1_3.0_1737802083179.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_arabic_mayasalsa3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_arabic_mayasalsa3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_arabic_mayasalsa3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|821.4 MB|
+
+## References
+
+https://huggingface.co/MayaSalsa3/xlm-roberta-base-finetuned-panx-ar
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_arabic_ornsteinthe3rd_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_arabic_ornsteinthe3rd_en.md
new file mode 100644
index 00000000000000..c73be475cf23a1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_arabic_ornsteinthe3rd_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_arabic_ornsteinthe3rd XlmRoBertaForTokenClassification from OrnsteinThe3rd
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_arabic_ornsteinthe3rd
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_arabic_ornsteinthe3rd` is a English model originally trained by OrnsteinThe3rd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_arabic_ornsteinthe3rd_en_5.5.1_3.0_1737804901152.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_arabic_ornsteinthe3rd_en_5.5.1_3.0_1737804901152.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_arabic_ornsteinthe3rd","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_arabic_ornsteinthe3rd", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_arabic_ornsteinthe3rd|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|821.4 MB|
+
+## References
+
+https://huggingface.co/OrnsteinThe3rd/xlm-roberta-base-finetuned-panx-ar
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_arabic_ornsteinthe3rd_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_arabic_ornsteinthe3rd_pipeline_en.md
new file mode 100644
index 00000000000000..e35e86573492a0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_arabic_ornsteinthe3rd_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_arabic_ornsteinthe3rd_pipeline pipeline XlmRoBertaForTokenClassification from OrnsteinThe3rd
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_arabic_ornsteinthe3rd_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_arabic_ornsteinthe3rd_pipeline` is a English model originally trained by OrnsteinThe3rd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_arabic_ornsteinthe3rd_pipeline_en_5.5.1_3.0_1737805003294.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_arabic_ornsteinthe3rd_pipeline_en_5.5.1_3.0_1737805003294.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_arabic_ornsteinthe3rd_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_arabic_ornsteinthe3rd_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_arabic_ornsteinthe3rd_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|821.4 MB|
+
+## References
+
+https://huggingface.co/OrnsteinThe3rd/xlm-roberta-base-finetuned-panx-ar
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_arkya_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_arkya_en.md
new file mode 100644
index 00000000000000..12f3a38dd428a5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_arkya_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_arkya XlmRoBertaForTokenClassification from Arkya
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_arkya
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_arkya` is a English model originally trained by Arkya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_arkya_en_5.5.1_3.0_1737779372513.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_arkya_en_5.5.1_3.0_1737779372513.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_arkya","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_arkya", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_arkya|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/Arkya/xlm-roberta-base-finetuned-panx-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_arkya_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_arkya_pipeline_en.md
new file mode 100644
index 00000000000000..9b61dc9ad134bf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_arkya_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_arkya_pipeline pipeline XlmRoBertaForTokenClassification from Arkya
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_arkya_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_arkya_pipeline` is a English model originally trained by Arkya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_arkya_pipeline_en_5.5.1_3.0_1737779483604.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_arkya_pipeline_en_5.5.1_3.0_1737779483604.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_arkya_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_arkya_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_arkya_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/Arkya/xlm-roberta-base-finetuned-panx-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_cotysong113_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_cotysong113_en.md
new file mode 100644
index 00000000000000..fa828e62e393b0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_cotysong113_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_cotysong113 XlmRoBertaForTokenClassification from cotysong113
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_cotysong113
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_cotysong113` is a English model originally trained by cotysong113.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_cotysong113_en_5.5.1_3.0_1737802108128.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_cotysong113_en_5.5.1_3.0_1737802108128.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_cotysong113","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_cotysong113", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_cotysong113|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|825.0 MB|
+
+## References
+
+https://huggingface.co/cotysong113/xlm-roberta-base-finetuned-panx-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_cotysong113_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_cotysong113_pipeline_en.md
new file mode 100644
index 00000000000000..e860e6884ad4ed
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_cotysong113_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_cotysong113_pipeline pipeline XlmRoBertaForTokenClassification from cotysong113
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_cotysong113_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_cotysong113_pipeline` is a English model originally trained by cotysong113.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_cotysong113_pipeline_en_5.5.1_3.0_1737802206150.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_cotysong113_pipeline_en_5.5.1_3.0_1737802206150.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_cotysong113_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_cotysong113_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_cotysong113_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|825.0 MB|
+
+## References
+
+https://huggingface.co/cotysong113/xlm-roberta-base-finetuned-panx-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_danielbyiringiro_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_danielbyiringiro_en.md
new file mode 100644
index 00000000000000..13531ad36b03ce
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_danielbyiringiro_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_danielbyiringiro XlmRoBertaForTokenClassification from danielbyiringiro
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_danielbyiringiro
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_danielbyiringiro` is a English model originally trained by danielbyiringiro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_danielbyiringiro_en_5.5.1_3.0_1737802554947.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_danielbyiringiro_en_5.5.1_3.0_1737802554947.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_danielbyiringiro","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_danielbyiringiro", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_danielbyiringiro|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/danielbyiringiro/xlm-roberta-base-finetuned-panx-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_danielbyiringiro_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_danielbyiringiro_pipeline_en.md
new file mode 100644
index 00000000000000..d545c21a1aeba6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_danielbyiringiro_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_danielbyiringiro_pipeline pipeline XlmRoBertaForTokenClassification from danielbyiringiro
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_danielbyiringiro_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_danielbyiringiro_pipeline` is a English model originally trained by danielbyiringiro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_danielbyiringiro_pipeline_en_5.5.1_3.0_1737802664573.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_danielbyiringiro_pipeline_en_5.5.1_3.0_1737802664573.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_danielbyiringiro_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_danielbyiringiro_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_danielbyiringiro_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/danielbyiringiro/xlm-roberta-base-finetuned-panx-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_eulerevangelista_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_eulerevangelista_en.md
new file mode 100644
index 00000000000000..6ba91bf6415612
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_eulerevangelista_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_eulerevangelista XlmRoBertaForTokenClassification from eulerevangelista
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_eulerevangelista
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_eulerevangelista` is a English model originally trained by eulerevangelista.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_eulerevangelista_en_5.5.1_3.0_1737831520855.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_eulerevangelista_en_5.5.1_3.0_1737831520855.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_eulerevangelista","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_eulerevangelista", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_eulerevangelista|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|844.2 MB|
+
+## References
+
+https://huggingface.co/eulerevangelista/xlm-roberta-base-finetuned-panx-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_eulerevangelista_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_eulerevangelista_pipeline_en.md
new file mode 100644
index 00000000000000..37525871851ee9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_eulerevangelista_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_eulerevangelista_pipeline pipeline XlmRoBertaForTokenClassification from eulerevangelista
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_eulerevangelista_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_eulerevangelista_pipeline` is a English model originally trained by eulerevangelista.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_eulerevangelista_pipeline_en_5.5.1_3.0_1737831608308.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_eulerevangelista_pipeline_en_5.5.1_3.0_1737831608308.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_eulerevangelista_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_eulerevangelista_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_eulerevangelista_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|844.3 MB|
+
+## References
+
+https://huggingface.co/eulerevangelista/xlm-roberta-base-finetuned-panx-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_haoj1_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_haoj1_en.md
new file mode 100644
index 00000000000000..cac7b0cd7fc1eb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_haoj1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_haoj1 XlmRoBertaForTokenClassification from haoj1
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_haoj1
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_haoj1` is a English model originally trained by haoj1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_haoj1_en_5.5.1_3.0_1737791104297.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_haoj1_en_5.5.1_3.0_1737791104297.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_haoj1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_haoj1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_haoj1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/haoj1/xlm-roberta-base-finetuned-panx-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_haoj1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_haoj1_pipeline_en.md
new file mode 100644
index 00000000000000..41d1f716ecc0a3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_haoj1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_haoj1_pipeline pipeline XlmRoBertaForTokenClassification from haoj1
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_haoj1_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_haoj1_pipeline` is a English model originally trained by haoj1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_haoj1_pipeline_en_5.5.1_3.0_1737791214906.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_haoj1_pipeline_en_5.5.1_3.0_1737791214906.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_haoj1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_haoj1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_haoj1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/haoj1/xlm-roberta-base-finetuned-panx-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_hebrew_modern_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_hebrew_modern_en.md
new file mode 100644
index 00000000000000..c3db7cf804a958
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_hebrew_modern_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_hebrew_modern XlmRoBertaForTokenClassification from eulerevangelista
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_hebrew_modern
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_hebrew_modern` is a English model originally trained by eulerevangelista.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_hebrew_modern_en_5.5.1_3.0_1737804121777.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_hebrew_modern_en_5.5.1_3.0_1737804121777.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_hebrew_modern","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_hebrew_modern", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_hebrew_modern|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/eulerevangelista/xlm-roberta-base-finetuned-panx-en-he
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_hebrew_modern_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_hebrew_modern_pipeline_en.md
new file mode 100644
index 00000000000000..fff51c32ee2625
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_hebrew_modern_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_hebrew_modern_pipeline pipeline XlmRoBertaForTokenClassification from eulerevangelista
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_hebrew_modern_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_hebrew_modern_pipeline` is a English model originally trained by eulerevangelista.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_hebrew_modern_pipeline_en_5.5.1_3.0_1737804213985.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_hebrew_modern_pipeline_en_5.5.1_3.0_1737804213985.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_hebrew_modern_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_hebrew_modern_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_hebrew_modern_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/eulerevangelista/xlm-roberta-base-finetuned-panx-en-he
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_imaditya123_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_imaditya123_en.md
new file mode 100644
index 00000000000000..814a2abe4461d2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_imaditya123_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_imaditya123 XlmRoBertaForTokenClassification from imaditya123
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_imaditya123
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_imaditya123` is a English model originally trained by imaditya123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_imaditya123_en_5.5.1_3.0_1737804716360.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_imaditya123_en_5.5.1_3.0_1737804716360.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_imaditya123","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_imaditya123", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_imaditya123|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/imaditya123/xlm-roberta-base-finetuned-panx-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_imaditya123_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_imaditya123_pipeline_en.md
new file mode 100644
index 00000000000000..5439ef94c1e78f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_imaditya123_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_imaditya123_pipeline pipeline XlmRoBertaForTokenClassification from imaditya123
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_imaditya123_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_imaditya123_pipeline` is a English model originally trained by imaditya123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_imaditya123_pipeline_en_5.5.1_3.0_1737804833014.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_imaditya123_pipeline_en_5.5.1_3.0_1737804833014.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_imaditya123_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_imaditya123_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_imaditya123_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/imaditya123/xlm-roberta-base-finetuned-panx-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_jinujara_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_jinujara_en.md
new file mode 100644
index 00000000000000..1b5647d0443b34
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_jinujara_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_jinujara XlmRoBertaForTokenClassification from jinujara
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_jinujara
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_jinujara` is a English model originally trained by jinujara.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_jinujara_en_5.5.1_3.0_1737779509853.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_jinujara_en_5.5.1_3.0_1737779509853.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_jinujara","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_jinujara", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_jinujara|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/jinujara/xlm-roberta-base-finetuned-panx-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_jinujara_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_jinujara_pipeline_en.md
new file mode 100644
index 00000000000000..094cae028cbe7a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_jinujara_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_jinujara_pipeline pipeline XlmRoBertaForTokenClassification from jinujara
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_jinujara_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_jinujara_pipeline` is a English model originally trained by jinujara.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_jinujara_pipeline_en_5.5.1_3.0_1737779621395.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_jinujara_pipeline_en_5.5.1_3.0_1737779621395.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_jinujara_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_jinujara_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_jinujara_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/jinujara/xlm-roberta-base-finetuned-panx-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_jongbaly_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_jongbaly_en.md
new file mode 100644
index 00000000000000..6031f2e62d631a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_jongbaly_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_jongbaly XlmRoBertaForTokenClassification from jongbaly
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_jongbaly
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_jongbaly` is a English model originally trained by jongbaly.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_jongbaly_en_5.5.1_3.0_1737779744187.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_jongbaly_en_5.5.1_3.0_1737779744187.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_jongbaly","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_jongbaly", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_jongbaly|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/jongbaly/xlm-roberta-base-finetuned-panx-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_jongbaly_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_jongbaly_pipeline_en.md
new file mode 100644
index 00000000000000..39d36ace2745f2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_jongbaly_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_jongbaly_pipeline pipeline XlmRoBertaForTokenClassification from jongbaly
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_jongbaly_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_jongbaly_pipeline` is a English model originally trained by jongbaly.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_jongbaly_pipeline_en_5.5.1_3.0_1737779854547.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_jongbaly_pipeline_en_5.5.1_3.0_1737779854547.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_jongbaly_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_jongbaly_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_jongbaly_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/jongbaly/xlm-roberta-base-finetuned-panx-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_july_tokyo_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_july_tokyo_en.md
new file mode 100644
index 00000000000000..c1161002190059
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_july_tokyo_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_july_tokyo XlmRoBertaForTokenClassification from July-Tokyo
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_july_tokyo
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_july_tokyo` is a English model originally trained by July-Tokyo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_july_tokyo_en_5.5.1_3.0_1737834049689.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_july_tokyo_en_5.5.1_3.0_1737834049689.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_july_tokyo","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_july_tokyo", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_july_tokyo|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/July-Tokyo/xlm-roberta-base-finetuned-panx-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_july_tokyo_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_july_tokyo_pipeline_en.md
new file mode 100644
index 00000000000000..d3359a5955b9d4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_july_tokyo_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_july_tokyo_pipeline pipeline XlmRoBertaForTokenClassification from July-Tokyo
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_july_tokyo_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_july_tokyo_pipeline` is a English model originally trained by July-Tokyo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_july_tokyo_pipeline_en_5.5.1_3.0_1737834157570.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_july_tokyo_pipeline_en_5.5.1_3.0_1737834157570.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_july_tokyo_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_july_tokyo_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_july_tokyo_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/July-Tokyo/xlm-roberta-base-finetuned-panx-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_loki47_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_loki47_en.md
new file mode 100644
index 00000000000000..8a227897bd4039
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_loki47_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_loki47 XlmRoBertaForTokenClassification from loki47
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_loki47
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_loki47` is a English model originally trained by loki47.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_loki47_en_5.5.1_3.0_1737790636854.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_loki47_en_5.5.1_3.0_1737790636854.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_loki47","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_loki47", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_loki47|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/loki47/xlm-roberta-base-finetuned-panx-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_loki47_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_loki47_pipeline_en.md
new file mode 100644
index 00000000000000..46b2c3090abf2d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_loki47_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_loki47_pipeline pipeline XlmRoBertaForTokenClassification from loki47
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_loki47_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_loki47_pipeline` is a English model originally trained by loki47.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_loki47_pipeline_en_5.5.1_3.0_1737790774161.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_loki47_pipeline_en_5.5.1_3.0_1737790774161.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_loki47_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_loki47_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_loki47_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/loki47/xlm-roberta-base-finetuned-panx-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_maarten1953_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_maarten1953_en.md
new file mode 100644
index 00000000000000..144b2edadd957b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_maarten1953_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_maarten1953 XlmRoBertaForTokenClassification from Maarten1953
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_maarten1953
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_maarten1953` is a English model originally trained by Maarten1953.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_maarten1953_en_5.5.1_3.0_1737832916021.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_maarten1953_en_5.5.1_3.0_1737832916021.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_maarten1953","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_maarten1953", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_maarten1953|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/Maarten1953/xlm-roberta-base-finetuned-panx-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_maarten1953_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_maarten1953_pipeline_en.md
new file mode 100644
index 00000000000000..b4cab5ae1638d8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_maarten1953_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_maarten1953_pipeline pipeline XlmRoBertaForTokenClassification from Maarten1953
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_maarten1953_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_maarten1953_pipeline` is a English model originally trained by Maarten1953.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_maarten1953_pipeline_en_5.5.1_3.0_1737833026768.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_maarten1953_pipeline_en_5.5.1_3.0_1737833026768.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_maarten1953_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_maarten1953_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_maarten1953_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/Maarten1953/xlm-roberta-base-finetuned-panx-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_mcguiver_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_mcguiver_en.md
new file mode 100644
index 00000000000000..cf3c90afc11bf4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_mcguiver_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_mcguiver XlmRoBertaForTokenClassification from mcguiver
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_mcguiver
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_mcguiver` is a English model originally trained by mcguiver.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_mcguiver_en_5.5.1_3.0_1737833687487.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_mcguiver_en_5.5.1_3.0_1737833687487.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_mcguiver","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_mcguiver", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_mcguiver|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/mcguiver/xlm-roberta-base-finetuned-panx-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_mcguiver_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_mcguiver_pipeline_en.md
new file mode 100644
index 00000000000000..509937c31f440d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_mcguiver_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_mcguiver_pipeline pipeline XlmRoBertaForTokenClassification from mcguiver
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_mcguiver_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_mcguiver_pipeline` is a English model originally trained by mcguiver.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_mcguiver_pipeline_en_5.5.1_3.0_1737833797574.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_mcguiver_pipeline_en_5.5.1_3.0_1737833797574.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_mcguiver_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_mcguiver_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_mcguiver_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/mcguiver/xlm-roberta-base-finetuned-panx-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_nik135_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_nik135_en.md
new file mode 100644
index 00000000000000..c12eef2507277d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_nik135_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_nik135 XlmRoBertaForTokenClassification from nik135
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_nik135
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_nik135` is a English model originally trained by nik135.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_nik135_en_5.5.1_3.0_1737790870596.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_nik135_en_5.5.1_3.0_1737790870596.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_nik135","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_nik135", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_nik135|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/nik135/xlm-roberta-base-finetuned-panx-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_nik135_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_nik135_pipeline_en.md
new file mode 100644
index 00000000000000..930b71e76dd050
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_nik135_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_nik135_pipeline pipeline XlmRoBertaForTokenClassification from nik135
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_nik135_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_nik135_pipeline` is a English model originally trained by nik135.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_nik135_pipeline_en_5.5.1_3.0_1737790981626.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_nik135_pipeline_en_5.5.1_3.0_1737790981626.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_nik135_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_nik135_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_nik135_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/nik135/xlm-roberta-base-finetuned-panx-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_qkdaf_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_qkdaf_en.md
new file mode 100644
index 00000000000000..a0c668a711f0b5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_qkdaf_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_qkdaf XlmRoBertaForTokenClassification from qkdaf
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_qkdaf
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_qkdaf` is a English model originally trained by qkdaf.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_qkdaf_en_5.5.1_3.0_1737802283203.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_qkdaf_en_5.5.1_3.0_1737802283203.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_qkdaf","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_qkdaf", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_qkdaf|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/qkdaf/xlm-roberta-base-finetuned-panx-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_qkdaf_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_qkdaf_pipeline_en.md
new file mode 100644
index 00000000000000..999d7ca28f5d4d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_qkdaf_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_qkdaf_pipeline pipeline XlmRoBertaForTokenClassification from qkdaf
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_qkdaf_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_qkdaf_pipeline` is a English model originally trained by qkdaf.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_qkdaf_pipeline_en_5.5.1_3.0_1737802398259.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_qkdaf_pipeline_en_5.5.1_3.0_1737802398259.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_qkdaf_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_qkdaf_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_qkdaf_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/qkdaf/xlm-roberta-base-finetuned-panx-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_raegold_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_raegold_en.md
new file mode 100644
index 00000000000000..3f829b8ef9d5d3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_raegold_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_raegold XlmRoBertaForTokenClassification from RaeGold
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_raegold
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_raegold` is a English model originally trained by RaeGold.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_raegold_en_5.5.1_3.0_1737777244950.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_raegold_en_5.5.1_3.0_1737777244950.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_raegold","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_raegold", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_raegold|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/RaeGold/xlm-roberta-base-finetuned-panx-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_raegold_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_raegold_pipeline_en.md
new file mode 100644
index 00000000000000..9f6d07a919eed6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_raegold_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_raegold_pipeline pipeline XlmRoBertaForTokenClassification from RaeGold
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_raegold_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_raegold_pipeline` is a English model originally trained by RaeGold.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_raegold_pipeline_en_5.5.1_3.0_1737777355117.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_raegold_pipeline_en_5.5.1_3.0_1737777355117.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_raegold_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_raegold_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_raegold_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/RaeGold/xlm-roberta-base-finetuned-panx-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_snagmin_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_snagmin_en.md
new file mode 100644
index 00000000000000..c0d6f6594320fb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_snagmin_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_snagmin XlmRoBertaForTokenClassification from snagmin
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_snagmin
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_snagmin` is a English model originally trained by snagmin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_snagmin_en_5.5.1_3.0_1737792498369.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_snagmin_en_5.5.1_3.0_1737792498369.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_snagmin","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_snagmin", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_snagmin|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/snagmin/xlm-roberta-base-finetuned-panx-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_snagmin_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_snagmin_pipeline_en.md
new file mode 100644
index 00000000000000..b69646417d50c4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_snagmin_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_snagmin_pipeline pipeline XlmRoBertaForTokenClassification from snagmin
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_snagmin_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_snagmin_pipeline` is a English model originally trained by snagmin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_snagmin_pipeline_en_5.5.1_3.0_1737792609075.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_snagmin_pipeline_en_5.5.1_3.0_1737792609075.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_snagmin_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_snagmin_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_snagmin_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/snagmin/xlm-roberta-base-finetuned-panx-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_soumilj_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_soumilj_en.md
new file mode 100644
index 00000000000000..9e146a5482543b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_soumilj_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_soumilj XlmRoBertaForTokenClassification from soumilj
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_soumilj
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_soumilj` is a English model originally trained by soumilj.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_soumilj_en_5.5.1_3.0_1737804815592.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_soumilj_en_5.5.1_3.0_1737804815592.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_soumilj","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_soumilj", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_soumilj|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|811.9 MB|
+
+## References
+
+https://huggingface.co/soumilj/xlm-roberta-base-finetuned-panx-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_soumilj_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_soumilj_pipeline_en.md
new file mode 100644
index 00000000000000..548d6470e0fbbb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_soumilj_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_soumilj_pipeline pipeline XlmRoBertaForTokenClassification from soumilj
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_soumilj_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_soumilj_pipeline` is a English model originally trained by soumilj.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_soumilj_pipeline_en_5.5.1_3.0_1737804927134.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_soumilj_pipeline_en_5.5.1_3.0_1737804927134.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_soumilj_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_soumilj_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_soumilj_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|811.9 MB|
+
+## References
+
+https://huggingface.co/soumilj/xlm-roberta-base-finetuned-panx-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_yashcfc_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_yashcfc_en.md
new file mode 100644
index 00000000000000..ed0885ae8348e1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_yashcfc_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_yashcfc XlmRoBertaForTokenClassification from yashcfc
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_yashcfc
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_yashcfc` is a English model originally trained by yashcfc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_yashcfc_en_5.5.1_3.0_1737803822135.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_yashcfc_en_5.5.1_3.0_1737803822135.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_yashcfc","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_yashcfc", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_yashcfc|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/yashcfc/xlm-roberta-base-finetuned-panx-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_yashcfc_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_yashcfc_pipeline_en.md
new file mode 100644
index 00000000000000..f835964f61513a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_yashcfc_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_yashcfc_pipeline pipeline XlmRoBertaForTokenClassification from yashcfc
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_yashcfc_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_yashcfc_pipeline` is a English model originally trained by yashcfc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_yashcfc_pipeline_en_5.5.1_3.0_1737803933164.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_yashcfc_pipeline_en_5.5.1_3.0_1737803933164.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_yashcfc_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_yashcfc_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_yashcfc_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/yashcfc/xlm-roberta-base-finetuned-panx-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_zachhofstad_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_zachhofstad_en.md
new file mode 100644
index 00000000000000..30da7e157f89a9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_zachhofstad_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_zachhofstad XlmRoBertaForTokenClassification from zachhofstad
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_zachhofstad
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_zachhofstad` is a English model originally trained by zachhofstad.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_zachhofstad_en_5.5.1_3.0_1737790406498.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_zachhofstad_en_5.5.1_3.0_1737790406498.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_zachhofstad","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_zachhofstad", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_zachhofstad|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/zachhofstad/xlm-roberta-base-finetuned-panx-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_zachhofstad_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_zachhofstad_pipeline_en.md
new file mode 100644
index 00000000000000..7a8a085df35a4c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_english_zachhofstad_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_zachhofstad_pipeline pipeline XlmRoBertaForTokenClassification from zachhofstad
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_zachhofstad_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_zachhofstad_pipeline` is a English model originally trained by zachhofstad.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_zachhofstad_pipeline_en_5.5.1_3.0_1737790517169.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_zachhofstad_pipeline_en_5.5.1_3.0_1737790517169.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_zachhofstad_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_zachhofstad_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_zachhofstad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/zachhofstad/xlm-roberta-base-finetuned-panx-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_ahmedelzayat077_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_ahmedelzayat077_en.md
new file mode 100644
index 00000000000000..9e66b4a7e95c04
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_ahmedelzayat077_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_ahmedelzayat077 BertForTokenClassification from ahmedelzayat077
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_ahmedelzayat077
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_ahmedelzayat077` is a English model originally trained by ahmedelzayat077.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_ahmedelzayat077_en_5.5.1_3.0_1737835174067.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_ahmedelzayat077_en_5.5.1_3.0_1737835174067.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_ahmedelzayat077","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_ahmedelzayat077", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_ahmedelzayat077|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/ahmedelzayat077/xlm-roberta-base-finetuned-panx-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_ahmedelzayat077_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_ahmedelzayat077_pipeline_en.md
new file mode 100644
index 00000000000000..9e5f83045caa3e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_ahmedelzayat077_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_ahmedelzayat077_pipeline pipeline BertForTokenClassification from ahmedelzayat077
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_ahmedelzayat077_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_ahmedelzayat077_pipeline` is a English model originally trained by ahmedelzayat077.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_ahmedelzayat077_pipeline_en_5.5.1_3.0_1737835207808.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_ahmedelzayat077_pipeline_en_5.5.1_3.0_1737835207808.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_ahmedelzayat077_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_ahmedelzayat077_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_ahmedelzayat077_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/ahmedelzayat077/xlm-roberta-base-finetuned-panx-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_danielbyiringiro_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_danielbyiringiro_en.md
new file mode 100644
index 00000000000000..d564e3e3259c97
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_danielbyiringiro_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_danielbyiringiro XlmRoBertaForTokenClassification from danielbyiringiro
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_danielbyiringiro
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_danielbyiringiro` is a English model originally trained by danielbyiringiro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_danielbyiringiro_en_5.5.1_3.0_1737776732480.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_danielbyiringiro_en_5.5.1_3.0_1737776732480.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_danielbyiringiro","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_danielbyiringiro", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_danielbyiringiro|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/danielbyiringiro/xlm-roberta-base-finetuned-panx-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_danielbyiringiro_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_danielbyiringiro_pipeline_en.md
new file mode 100644
index 00000000000000..65563a538e89ec
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_danielbyiringiro_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_danielbyiringiro_pipeline pipeline XlmRoBertaForTokenClassification from danielbyiringiro
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_danielbyiringiro_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_danielbyiringiro_pipeline` is a English model originally trained by danielbyiringiro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_danielbyiringiro_pipeline_en_5.5.1_3.0_1737776835915.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_danielbyiringiro_pipeline_en_5.5.1_3.0_1737776835915.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_danielbyiringiro_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_danielbyiringiro_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_danielbyiringiro_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/danielbyiringiro/xlm-roberta-base-finetuned-panx-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_imaditya123_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_imaditya123_en.md
new file mode 100644
index 00000000000000..d25de5cdc26a2e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_imaditya123_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_imaditya123 XlmRoBertaForTokenClassification from imaditya123
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_imaditya123
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_imaditya123` is a English model originally trained by imaditya123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_imaditya123_en_5.5.1_3.0_1737779918570.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_imaditya123_en_5.5.1_3.0_1737779918570.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_imaditya123","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_imaditya123", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_imaditya123|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/imaditya123/xlm-roberta-base-finetuned-panx-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_imaditya123_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_imaditya123_pipeline_en.md
new file mode 100644
index 00000000000000..7131d9c29f0dce
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_imaditya123_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_imaditya123_pipeline pipeline XlmRoBertaForTokenClassification from imaditya123
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_imaditya123_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_imaditya123_pipeline` is a English model originally trained by imaditya123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_imaditya123_pipeline_en_5.5.1_3.0_1737780010840.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_imaditya123_pipeline_en_5.5.1_3.0_1737780010840.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_imaditya123_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_imaditya123_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_imaditya123_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/imaditya123/xlm-roberta-base-finetuned-panx-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_jongbaly_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_jongbaly_en.md
new file mode 100644
index 00000000000000..582f8abe5cd036
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_jongbaly_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_jongbaly XlmRoBertaForTokenClassification from jongbaly
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_jongbaly
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_jongbaly` is a English model originally trained by jongbaly.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_jongbaly_en_5.5.1_3.0_1737802803252.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_jongbaly_en_5.5.1_3.0_1737802803252.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_jongbaly","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_jongbaly", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_jongbaly|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/jongbaly/xlm-roberta-base-finetuned-panx-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_jongbaly_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_jongbaly_pipeline_en.md
new file mode 100644
index 00000000000000..36c4bed4835751
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_jongbaly_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_jongbaly_pipeline pipeline XlmRoBertaForTokenClassification from jongbaly
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_jongbaly_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_jongbaly_pipeline` is a English model originally trained by jongbaly.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_jongbaly_pipeline_en_5.5.1_3.0_1737802897870.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_jongbaly_pipeline_en_5.5.1_3.0_1737802897870.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_jongbaly_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_jongbaly_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_jongbaly_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/jongbaly/xlm-roberta-base-finetuned-panx-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_krish2218_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_krish2218_en.md
new file mode 100644
index 00000000000000..e2cb7b143958dc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_krish2218_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_krish2218 XlmRoBertaForTokenClassification from Krish2218
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_krish2218
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_krish2218` is a English model originally trained by Krish2218.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_krish2218_en_5.5.1_3.0_1737831066369.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_krish2218_en_5.5.1_3.0_1737831066369.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_krish2218","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_krish2218", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_krish2218|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/Krish2218/xlm-roberta-base-finetuned-panx-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_krish2218_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_krish2218_pipeline_en.md
new file mode 100644
index 00000000000000..937e2ab55f9615
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_krish2218_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_krish2218_pipeline pipeline XlmRoBertaForTokenClassification from Krish2218
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_krish2218_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_krish2218_pipeline` is a English model originally trained by Krish2218.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_krish2218_pipeline_en_5.5.1_3.0_1737831165746.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_krish2218_pipeline_en_5.5.1_3.0_1737831165746.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_krish2218_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_krish2218_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_krish2218_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/Krish2218/xlm-roberta-base-finetuned-panx-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_loki47_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_loki47_en.md
new file mode 100644
index 00000000000000..4e2a0bfc10e439
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_loki47_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_loki47 XlmRoBertaForTokenClassification from loki47
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_loki47
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_loki47` is a English model originally trained by loki47.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_loki47_en_5.5.1_3.0_1737793193224.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_loki47_en_5.5.1_3.0_1737793193224.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_loki47","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_loki47", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_loki47|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/loki47/xlm-roberta-base-finetuned-panx-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_loki47_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_loki47_pipeline_en.md
new file mode 100644
index 00000000000000..0dd169c9888c1e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_loki47_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_loki47_pipeline pipeline XlmRoBertaForTokenClassification from loki47
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_loki47_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_loki47_pipeline` is a English model originally trained by loki47.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_loki47_pipeline_en_5.5.1_3.0_1737793288104.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_loki47_pipeline_en_5.5.1_3.0_1737793288104.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_loki47_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_loki47_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_loki47_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/loki47/xlm-roberta-base-finetuned-panx-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_mcguiver_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_mcguiver_en.md
new file mode 100644
index 00000000000000..ae29030b6c112a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_mcguiver_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_mcguiver XlmRoBertaForTokenClassification from mcguiver
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_mcguiver
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_mcguiver` is a English model originally trained by mcguiver.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_mcguiver_en_5.5.1_3.0_1737831721597.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_mcguiver_en_5.5.1_3.0_1737831721597.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_mcguiver","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_mcguiver", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_mcguiver|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/mcguiver/xlm-roberta-base-finetuned-panx-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_mcguiver_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_mcguiver_pipeline_en.md
new file mode 100644
index 00000000000000..15951d259b4680
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_mcguiver_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_mcguiver_pipeline pipeline XlmRoBertaForTokenClassification from mcguiver
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_mcguiver_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_mcguiver_pipeline` is a English model originally trained by mcguiver.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_mcguiver_pipeline_en_5.5.1_3.0_1737831815348.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_mcguiver_pipeline_en_5.5.1_3.0_1737831815348.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_mcguiver_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_mcguiver_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_mcguiver_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/mcguiver/xlm-roberta-base-finetuned-panx-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_nik135_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_nik135_en.md
new file mode 100644
index 00000000000000..73fe3527f137bc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_nik135_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_nik135 XlmRoBertaForTokenClassification from nik135
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_nik135
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_nik135` is a English model originally trained by nik135.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_nik135_en_5.5.1_3.0_1737803879425.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_nik135_en_5.5.1_3.0_1737803879425.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_nik135","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_nik135", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_nik135|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/nik135/xlm-roberta-base-finetuned-panx-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_nik135_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_nik135_pipeline_en.md
new file mode 100644
index 00000000000000..1811da51c39a52
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_nik135_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_nik135_pipeline pipeline XlmRoBertaForTokenClassification from nik135
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_nik135_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_nik135_pipeline` is a English model originally trained by nik135.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_nik135_pipeline_en_5.5.1_3.0_1737803975054.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_nik135_pipeline_en_5.5.1_3.0_1737803975054.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_nik135_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_nik135_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_nik135_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/nik135/xlm-roberta-base-finetuned-panx-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_snagmin_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_snagmin_en.md
new file mode 100644
index 00000000000000..9c1b47d0dae5d4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_snagmin_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_snagmin XlmRoBertaForTokenClassification from snagmin
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_snagmin
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_snagmin` is a English model originally trained by snagmin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_snagmin_en_5.5.1_3.0_1737834015264.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_snagmin_en_5.5.1_3.0_1737834015264.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_snagmin","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_snagmin", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_snagmin|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/snagmin/xlm-roberta-base-finetuned-panx-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_snagmin_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_snagmin_pipeline_en.md
new file mode 100644
index 00000000000000..d6d90c983c79d9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_snagmin_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_snagmin_pipeline pipeline XlmRoBertaForTokenClassification from snagmin
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_snagmin_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_snagmin_pipeline` is a English model originally trained by snagmin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_snagmin_pipeline_en_5.5.1_3.0_1737834108289.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_snagmin_pipeline_en_5.5.1_3.0_1737834108289.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_snagmin_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_snagmin_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_snagmin_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/snagmin/xlm-roberta-base-finetuned-panx-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_soumilj_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_soumilj_en.md
new file mode 100644
index 00000000000000..0ae3ba067e20e3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_soumilj_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_soumilj XlmRoBertaForTokenClassification from soumilj
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_soumilj
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_soumilj` is a English model originally trained by soumilj.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_soumilj_en_5.5.1_3.0_1737777916081.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_soumilj_en_5.5.1_3.0_1737777916081.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_soumilj","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_soumilj", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_soumilj|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|822.6 MB|
+
+## References
+
+https://huggingface.co/soumilj/xlm-roberta-base-finetuned-panx-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_soumilj_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_soumilj_pipeline_en.md
new file mode 100644
index 00000000000000..37d5e0563033fd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_soumilj_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_soumilj_pipeline pipeline XlmRoBertaForTokenClassification from soumilj
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_soumilj_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_soumilj_pipeline` is a English model originally trained by soumilj.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_soumilj_pipeline_en_5.5.1_3.0_1737778013862.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_soumilj_pipeline_en_5.5.1_3.0_1737778013862.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_soumilj_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_soumilj_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_soumilj_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|822.6 MB|
+
+## References
+
+https://huggingface.co/soumilj/xlm-roberta-base-finetuned-panx-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_zachhofstad_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_zachhofstad_en.md
new file mode 100644
index 00000000000000..e32fece2d1dfb8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_zachhofstad_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_zachhofstad XlmRoBertaForTokenClassification from zachhofstad
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_zachhofstad
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_zachhofstad` is a English model originally trained by zachhofstad.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_zachhofstad_en_5.5.1_3.0_1737790163577.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_zachhofstad_en_5.5.1_3.0_1737790163577.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_zachhofstad","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_zachhofstad", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_zachhofstad|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/zachhofstad/xlm-roberta-base-finetuned-panx-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_zachhofstad_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_zachhofstad_pipeline_en.md
new file mode 100644
index 00000000000000..f196d0f4523b19
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_french_zachhofstad_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_zachhofstad_pipeline pipeline XlmRoBertaForTokenClassification from zachhofstad
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_zachhofstad_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_zachhofstad_pipeline` is a English model originally trained by zachhofstad.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_zachhofstad_pipeline_en_5.5.1_3.0_1737790264413.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_zachhofstad_pipeline_en_5.5.1_3.0_1737790264413.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_zachhofstad_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_zachhofstad_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_zachhofstad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/zachhofstad/xlm-roberta-base-finetuned-panx-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_54data_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_54data_en.md
new file mode 100644
index 00000000000000..50f4f5d241e6e9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_54data_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_54data XlmRoBertaForTokenClassification from 54data
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_54data
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_54data` is a English model originally trained by 54data.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_54data_en_5.5.1_3.0_1737777425197.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_54data_en_5.5.1_3.0_1737777425197.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_54data","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_54data", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_54data|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/54data/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_54data_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_54data_pipeline_en.md
new file mode 100644
index 00000000000000..b2c4fa5ff3c607
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_54data_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_54data_pipeline pipeline XlmRoBertaForTokenClassification from 54data
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_54data_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_54data_pipeline` is a English model originally trained by 54data.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_54data_pipeline_en_5.5.1_3.0_1737777513565.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_54data_pipeline_en_5.5.1_3.0_1737777513565.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_54data_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_54data_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_54data_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/54data/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_aiventurer_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_aiventurer_en.md
new file mode 100644
index 00000000000000..1fdc9cad0532bd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_aiventurer_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_aiventurer XlmRoBertaForTokenClassification from AIventurer
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_aiventurer
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_aiventurer` is a English model originally trained by AIventurer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_aiventurer_en_5.5.1_3.0_1737791252921.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_aiventurer_en_5.5.1_3.0_1737791252921.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_aiventurer","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_aiventurer", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_aiventurer|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/AIventurer/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_aiventurer_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_aiventurer_pipeline_en.md
new file mode 100644
index 00000000000000..f79e827d7960b2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_aiventurer_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_aiventurer_pipeline pipeline XlmRoBertaForTokenClassification from AIventurer
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_aiventurer_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_aiventurer_pipeline` is a English model originally trained by AIventurer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_aiventurer_pipeline_en_5.5.1_3.0_1737791324239.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_aiventurer_pipeline_en_5.5.1_3.0_1737791324239.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_aiventurer_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_aiventurer_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_aiventurer_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/AIventurer/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_bekalebendong_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_bekalebendong_en.md
new file mode 100644
index 00000000000000..a20071d79ef1f5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_bekalebendong_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_bekalebendong XlmRoBertaForTokenClassification from bekalebendong
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_bekalebendong
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_bekalebendong` is a English model originally trained by bekalebendong.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_bekalebendong_en_5.5.1_3.0_1737834086594.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_bekalebendong_en_5.5.1_3.0_1737834086594.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_bekalebendong","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_bekalebendong", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_bekalebendong|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/bekalebendong/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_bekalebendong_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_bekalebendong_pipeline_en.md
new file mode 100644
index 00000000000000..33d550fb3fc93b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_bekalebendong_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_bekalebendong_pipeline pipeline XlmRoBertaForTokenClassification from bekalebendong
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_bekalebendong_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_bekalebendong_pipeline` is a English model originally trained by bekalebendong.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_bekalebendong_pipeline_en_5.5.1_3.0_1737834172623.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_bekalebendong_pipeline_en_5.5.1_3.0_1737834172623.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_bekalebendong_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_bekalebendong_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_bekalebendong_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/bekalebendong/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_bh8648_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_bh8648_en.md
new file mode 100644
index 00000000000000..fc67c23999b736
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_bh8648_en.md
@@ -0,0 +1,96 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_bh8648 XlmRoBertaForTokenClassification from bh8648
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_bh8648
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_bh8648` is a English model originally trained by bh8648.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_bh8648_en_5.5.1_3.0_1737833293308.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_bh8648_en_5.5.1_3.0_1737833293308.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_bh8648","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_bh8648", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_bh8648|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|854.5 MB|
+
+## References
+
+References
+
+https://huggingface.co/bh8648/xlm-roberta-base-finetuned-panx-de_
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_bh8648_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_bh8648_pipeline_en.md
new file mode 100644
index 00000000000000..d6180dfa3ed849
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_bh8648_pipeline_en.md
@@ -0,0 +1,72 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_bh8648_pipeline pipeline XlmRoBertaForTokenClassification from bh8648
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_bh8648_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_bh8648_pipeline` is a English model originally trained by bh8648.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_bh8648_pipeline_en_5.5.1_3.0_1737833358648.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_bh8648_pipeline_en_5.5.1_3.0_1737833358648.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_bh8648_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_bh8648_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_bh8648_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|854.5 MB|
+
+## References
+
+References
+
+https://huggingface.co/bh8648/xlm-roberta-base-finetuned-panx-de_
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_bluetree99_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_bluetree99_en.md
new file mode 100644
index 00000000000000..db581e611b1d5f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_bluetree99_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_bluetree99 XlmRoBertaForTokenClassification from bluetree99
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_bluetree99
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_bluetree99` is a English model originally trained by bluetree99.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_bluetree99_en_5.5.1_3.0_1737832962832.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_bluetree99_en_5.5.1_3.0_1737832962832.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_bluetree99","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_bluetree99", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_bluetree99|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/bluetree99/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_bluetree99_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_bluetree99_pipeline_en.md
new file mode 100644
index 00000000000000..7bf64fc37a2a65
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_bluetree99_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_bluetree99_pipeline pipeline XlmRoBertaForTokenClassification from bluetree99
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_bluetree99_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_bluetree99_pipeline` is a English model originally trained by bluetree99.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_bluetree99_pipeline_en_5.5.1_3.0_1737833034292.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_bluetree99_pipeline_en_5.5.1_3.0_1737833034292.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_bluetree99_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_bluetree99_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_bluetree99_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/bluetree99/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_conorjudge_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_conorjudge_en.md
new file mode 100644
index 00000000000000..e497a5475a9c8c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_conorjudge_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_conorjudge XlmRoBertaForTokenClassification from conorjudge
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_conorjudge
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_conorjudge` is a English model originally trained by conorjudge.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_conorjudge_en_5.5.1_3.0_1737790237583.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_conorjudge_en_5.5.1_3.0_1737790237583.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_conorjudge","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_conorjudge", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_conorjudge|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/conorjudge/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_conorjudge_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_conorjudge_pipeline_en.md
new file mode 100644
index 00000000000000..db1cd731163916
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_conorjudge_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_conorjudge_pipeline pipeline XlmRoBertaForTokenClassification from conorjudge
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_conorjudge_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_conorjudge_pipeline` is a English model originally trained by conorjudge.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_conorjudge_pipeline_en_5.5.1_3.0_1737790310260.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_conorjudge_pipeline_en_5.5.1_3.0_1737790310260.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_conorjudge_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_conorjudge_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_conorjudge_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/conorjudge/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_do1232_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_do1232_en.md
new file mode 100644
index 00000000000000..0458ca51e4d44c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_do1232_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_do1232 XlmRoBertaForTokenClassification from do1232
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_do1232
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_do1232` is a English model originally trained by do1232.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_do1232_en_5.5.1_3.0_1737779538379.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_do1232_en_5.5.1_3.0_1737779538379.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_do1232","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_do1232", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_do1232|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/do1232/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_do1232_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_do1232_pipeline_en.md
new file mode 100644
index 00000000000000..5e0cc46ce7cfcc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_do1232_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_do1232_pipeline pipeline XlmRoBertaForTokenClassification from do1232
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_do1232_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_do1232_pipeline` is a English model originally trained by do1232.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_do1232_pipeline_en_5.5.1_3.0_1737779627388.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_do1232_pipeline_en_5.5.1_3.0_1737779627388.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_do1232_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_do1232_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_do1232_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/do1232/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_blue2959_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_blue2959_en.md
new file mode 100644
index 00000000000000..93bd7b923ba629
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_blue2959_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_blue2959 XlmRoBertaForTokenClassification from blue2959
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_blue2959
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_blue2959` is a English model originally trained by blue2959.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_blue2959_en_5.5.1_3.0_1737777850125.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_blue2959_en_5.5.1_3.0_1737777850125.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_blue2959","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_blue2959", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_blue2959|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/blue2959/xlm-roberta-base-finetuned-panx-de-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_blue2959_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_blue2959_pipeline_en.md
new file mode 100644
index 00000000000000..e547a6aff12eb1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_blue2959_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_blue2959_pipeline pipeline XlmRoBertaForTokenClassification from blue2959
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_blue2959_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_blue2959_pipeline` is a English model originally trained by blue2959.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_blue2959_pipeline_en_5.5.1_3.0_1737777941380.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_blue2959_pipeline_en_5.5.1_3.0_1737777941380.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_blue2959_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_blue2959_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_blue2959_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/blue2959/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_bluetree99_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_bluetree99_en.md
new file mode 100644
index 00000000000000..90c916015695c7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_bluetree99_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_bluetree99 XlmRoBertaForTokenClassification from bluetree99
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_bluetree99
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_bluetree99` is a English model originally trained by bluetree99.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_bluetree99_en_5.5.1_3.0_1737833130956.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_bluetree99_en_5.5.1_3.0_1737833130956.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_bluetree99","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_bluetree99", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_bluetree99|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|858.2 MB|
+
+## References
+
+https://huggingface.co/bluetree99/xlm-roberta-base-finetuned-panx-de-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_bluetree99_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_bluetree99_pipeline_en.md
new file mode 100644
index 00000000000000..8ffae21dcce771
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_bluetree99_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_bluetree99_pipeline pipeline XlmRoBertaForTokenClassification from bluetree99
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_bluetree99_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_bluetree99_pipeline` is a English model originally trained by bluetree99.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_bluetree99_pipeline_en_5.5.1_3.0_1737833206017.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_bluetree99_pipeline_en_5.5.1_3.0_1737833206017.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_bluetree99_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_bluetree99_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_bluetree99_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|858.2 MB|
+
+## References
+
+https://huggingface.co/bluetree99/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_cyrildever_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_cyrildever_en.md
new file mode 100644
index 00000000000000..4e90238a2c594f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_cyrildever_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_cyrildever XlmRoBertaForTokenClassification from cyrildever
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_cyrildever
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_cyrildever` is a English model originally trained by cyrildever.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_cyrildever_en_5.5.1_3.0_1737791884207.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_cyrildever_en_5.5.1_3.0_1737791884207.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_cyrildever","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_cyrildever", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_cyrildever|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|858.2 MB|
+
+## References
+
+https://huggingface.co/cyrildever/xlm-roberta-base-finetuned-panx-de-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_cyrildever_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_cyrildever_pipeline_en.md
new file mode 100644
index 00000000000000..e7d6a751225cd6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_cyrildever_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_cyrildever_pipeline pipeline XlmRoBertaForTokenClassification from cyrildever
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_cyrildever_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_cyrildever_pipeline` is a English model originally trained by cyrildever.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_cyrildever_pipeline_en_5.5.1_3.0_1737791954861.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_cyrildever_pipeline_en_5.5.1_3.0_1737791954861.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_cyrildever_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_cyrildever_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_cyrildever_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|858.2 MB|
+
+## References
+
+https://huggingface.co/cyrildever/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_haoj1_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_haoj1_en.md
new file mode 100644
index 00000000000000..ce52d37d287593
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_haoj1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_haoj1 XlmRoBertaForTokenClassification from haoj1
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_haoj1
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_haoj1` is a English model originally trained by haoj1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_haoj1_en_5.5.1_3.0_1737778218692.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_haoj1_en_5.5.1_3.0_1737778218692.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_haoj1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_haoj1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_haoj1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/haoj1/xlm-roberta-base-finetuned-panx-de-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_haoj1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_haoj1_pipeline_en.md
new file mode 100644
index 00000000000000..5c73dc858d4c36
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_haoj1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_haoj1_pipeline pipeline XlmRoBertaForTokenClassification from haoj1
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_haoj1_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_haoj1_pipeline` is a English model originally trained by haoj1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_haoj1_pipeline_en_5.5.1_3.0_1737778309319.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_haoj1_pipeline_en_5.5.1_3.0_1737778309319.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_haoj1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_haoj1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_haoj1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/haoj1/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_havagoodday_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_havagoodday_en.md
new file mode 100644
index 00000000000000..6809865f168f96
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_havagoodday_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_havagoodday XlmRoBertaForTokenClassification from HavaGoodDay
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_havagoodday
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_havagoodday` is a English model originally trained by HavaGoodDay.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_havagoodday_en_5.5.1_3.0_1737831464215.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_havagoodday_en_5.5.1_3.0_1737831464215.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_havagoodday","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_havagoodday", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_havagoodday|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/HavaGoodDay/xlm-roberta-base-finetuned-panx-de-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_havagoodday_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_havagoodday_pipeline_en.md
new file mode 100644
index 00000000000000..4a7a28920f269b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_havagoodday_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_havagoodday_pipeline pipeline XlmRoBertaForTokenClassification from HavaGoodDay
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_havagoodday_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_havagoodday_pipeline` is a English model originally trained by HavaGoodDay.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_havagoodday_pipeline_en_5.5.1_3.0_1737831560490.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_havagoodday_pipeline_en_5.5.1_3.0_1737831560490.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_havagoodday_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_havagoodday_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_havagoodday_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/HavaGoodDay/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_imaditya123_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_imaditya123_en.md
new file mode 100644
index 00000000000000..62f32482ce9a22
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_imaditya123_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_imaditya123 XlmRoBertaForTokenClassification from imaditya123
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_imaditya123
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_imaditya123` is a English model originally trained by imaditya123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_imaditya123_en_5.5.1_3.0_1737804035412.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_imaditya123_en_5.5.1_3.0_1737804035412.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_imaditya123","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_imaditya123", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_imaditya123|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/imaditya123/xlm-roberta-base-finetuned-panx-de-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_imaditya123_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_imaditya123_pipeline_en.md
new file mode 100644
index 00000000000000..7961d872841818
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_imaditya123_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_imaditya123_pipeline pipeline XlmRoBertaForTokenClassification from imaditya123
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_imaditya123_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_imaditya123_pipeline` is a English model originally trained by imaditya123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_imaditya123_pipeline_en_5.5.1_3.0_1737804125288.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_imaditya123_pipeline_en_5.5.1_3.0_1737804125288.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_imaditya123_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_imaditya123_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_imaditya123_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/imaditya123/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_k4west_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_k4west_en.md
new file mode 100644
index 00000000000000..cf219becf9a374
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_k4west_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_k4west XlmRoBertaForTokenClassification from k4west
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_k4west
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_k4west` is a English model originally trained by k4west.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_k4west_en_5.5.1_3.0_1737832718293.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_k4west_en_5.5.1_3.0_1737832718293.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_k4west","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_k4west", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_k4west|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/k4west/xlm-roberta-base-finetuned-panx-de-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_k4west_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_k4west_pipeline_en.md
new file mode 100644
index 00000000000000..a39a914659e5ed
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_k4west_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_k4west_pipeline pipeline XlmRoBertaForTokenClassification from k4west
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_k4west_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_k4west_pipeline` is a English model originally trained by k4west.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_k4west_pipeline_en_5.5.1_3.0_1737832806611.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_k4west_pipeline_en_5.5.1_3.0_1737832806611.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_k4west_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_k4west_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_k4west_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/k4west/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_kajetanfrackowiak_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_kajetanfrackowiak_en.md
new file mode 100644
index 00000000000000..8ff2f9fe83aacb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_kajetanfrackowiak_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_kajetanfrackowiak XlmRoBertaForTokenClassification from KajetanFrackowiak
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_kajetanfrackowiak
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_kajetanfrackowiak` is a English model originally trained by KajetanFrackowiak.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_kajetanfrackowiak_en_5.5.1_3.0_1737777461747.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_kajetanfrackowiak_en_5.5.1_3.0_1737777461747.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_kajetanfrackowiak","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_kajetanfrackowiak", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_kajetanfrackowiak|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/KajetanFrackowiak/xlm-roberta-base-finetuned-panx-de-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_kajetanfrackowiak_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_kajetanfrackowiak_pipeline_en.md
new file mode 100644
index 00000000000000..29af6b7b47cf9a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_kajetanfrackowiak_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_kajetanfrackowiak_pipeline pipeline XlmRoBertaForTokenClassification from KajetanFrackowiak
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_kajetanfrackowiak_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_kajetanfrackowiak_pipeline` is a English model originally trained by KajetanFrackowiak.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_kajetanfrackowiak_pipeline_en_5.5.1_3.0_1737777551864.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_kajetanfrackowiak_pipeline_en_5.5.1_3.0_1737777551864.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_kajetanfrackowiak_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_kajetanfrackowiak_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_kajetanfrackowiak_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/KajetanFrackowiak/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_krish2218_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_krish2218_en.md
new file mode 100644
index 00000000000000..c5e772dedf29a6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_krish2218_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_krish2218 XlmRoBertaForTokenClassification from Krish2218
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_krish2218
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_krish2218` is a English model originally trained by Krish2218.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_krish2218_en_5.5.1_3.0_1737778976645.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_krish2218_en_5.5.1_3.0_1737778976645.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_krish2218","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_krish2218", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_krish2218|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/Krish2218/xlm-roberta-base-finetuned-panx-de-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_krish2218_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_krish2218_pipeline_en.md
new file mode 100644
index 00000000000000..6e963ded60d738
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_krish2218_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_krish2218_pipeline pipeline XlmRoBertaForTokenClassification from Krish2218
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_krish2218_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_krish2218_pipeline` is a English model originally trained by Krish2218.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_krish2218_pipeline_en_5.5.1_3.0_1737779066073.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_krish2218_pipeline_en_5.5.1_3.0_1737779066073.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_krish2218_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_krish2218_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_krish2218_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/Krish2218/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_m_rezaei_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_m_rezaei_en.md
new file mode 100644
index 00000000000000..2fc5139ae3c838
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_m_rezaei_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_m_rezaei XlmRoBertaForTokenClassification from M-Rezaei
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_m_rezaei
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_m_rezaei` is a English model originally trained by M-Rezaei.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_m_rezaei_en_5.5.1_3.0_1737777083438.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_m_rezaei_en_5.5.1_3.0_1737777083438.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_m_rezaei","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_m_rezaei", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_m_rezaei|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|845.6 MB|
+
+## References
+
+https://huggingface.co/M-Rezaei/xlm-roberta-base-finetuned-panx-de-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_m_rezaei_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_m_rezaei_pipeline_en.md
new file mode 100644
index 00000000000000..88aa34407a1cd3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_m_rezaei_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_m_rezaei_pipeline pipeline XlmRoBertaForTokenClassification from M-Rezaei
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_m_rezaei_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_m_rezaei_pipeline` is a English model originally trained by M-Rezaei.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_m_rezaei_pipeline_en_5.5.1_3.0_1737777171329.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_m_rezaei_pipeline_en_5.5.1_3.0_1737777171329.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_m_rezaei_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_m_rezaei_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_m_rezaei_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|845.6 MB|
+
+## References
+
+https://huggingface.co/M-Rezaei/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_mcguiver_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_mcguiver_en.md
new file mode 100644
index 00000000000000..683393372f6820
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_mcguiver_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_mcguiver XlmRoBertaForTokenClassification from mcguiver
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_mcguiver
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_mcguiver` is a English model originally trained by mcguiver.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_mcguiver_en_5.5.1_3.0_1737831875431.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_mcguiver_en_5.5.1_3.0_1737831875431.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_mcguiver","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_mcguiver", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_mcguiver|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/mcguiver/xlm-roberta-base-finetuned-panx-de-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_mcguiver_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_mcguiver_pipeline_en.md
new file mode 100644
index 00000000000000..0c272f5a9ed155
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_mcguiver_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_mcguiver_pipeline pipeline XlmRoBertaForTokenClassification from mcguiver
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_mcguiver_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_mcguiver_pipeline` is a English model originally trained by mcguiver.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_mcguiver_pipeline_en_5.5.1_3.0_1737831971347.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_mcguiver_pipeline_en_5.5.1_3.0_1737831971347.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_mcguiver_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_mcguiver_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_mcguiver_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/mcguiver/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_qihehehehe_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_qihehehehe_en.md
new file mode 100644
index 00000000000000..ab88d5e563adde
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_qihehehehe_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_qihehehehe XlmRoBertaForTokenClassification from QiHehehehe
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_qihehehehe
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_qihehehehe` is a English model originally trained by QiHehehehe.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_qihehehehe_en_5.5.1_3.0_1737802985520.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_qihehehehe_en_5.5.1_3.0_1737802985520.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_qihehehehe","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_qihehehehe", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_qihehehehe|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/QiHehehehe/xlm-roberta-base-finetuned-panx-de-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_qihehehehe_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_qihehehehe_pipeline_en.md
new file mode 100644
index 00000000000000..711b13c2c7dca3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_qihehehehe_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_qihehehehe_pipeline pipeline XlmRoBertaForTokenClassification from QiHehehehe
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_qihehehehe_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_qihehehehe_pipeline` is a English model originally trained by QiHehehehe.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_qihehehehe_pipeline_en_5.5.1_3.0_1737803079605.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_qihehehehe_pipeline_en_5.5.1_3.0_1737803079605.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_qihehehehe_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_qihehehehe_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_qihehehehe_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/QiHehehehe/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_qkdaf_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_qkdaf_en.md
new file mode 100644
index 00000000000000..e489227b5621dd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_qkdaf_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_qkdaf XlmRoBertaForTokenClassification from qkdaf
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_qkdaf
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_qkdaf` is a English model originally trained by qkdaf.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_qkdaf_en_5.5.1_3.0_1737804981671.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_qkdaf_en_5.5.1_3.0_1737804981671.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_qkdaf","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_qkdaf", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_qkdaf|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/qkdaf/xlm-roberta-base-finetuned-panx-de-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_qkdaf_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_qkdaf_pipeline_en.md
new file mode 100644
index 00000000000000..4d0b1b3b5eb986
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_qkdaf_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_qkdaf_pipeline pipeline XlmRoBertaForTokenClassification from qkdaf
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_qkdaf_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_qkdaf_pipeline` is a English model originally trained by qkdaf.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_qkdaf_pipeline_en_5.5.1_3.0_1737805069966.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_qkdaf_pipeline_en_5.5.1_3.0_1737805069966.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_qkdaf_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_qkdaf_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_qkdaf_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/qkdaf/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_snagmin_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_snagmin_en.md
new file mode 100644
index 00000000000000..1ed89d85c65b74
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_snagmin_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_snagmin XlmRoBertaForTokenClassification from snagmin
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_snagmin
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_snagmin` is a English model originally trained by snagmin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_snagmin_en_5.5.1_3.0_1737778640120.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_snagmin_en_5.5.1_3.0_1737778640120.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_snagmin","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_snagmin", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_snagmin|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/snagmin/xlm-roberta-base-finetuned-panx-de-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_snagmin_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_snagmin_pipeline_en.md
new file mode 100644
index 00000000000000..d5562ea52119b5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_snagmin_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_snagmin_pipeline pipeline XlmRoBertaForTokenClassification from snagmin
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_snagmin_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_snagmin_pipeline` is a English model originally trained by snagmin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_snagmin_pipeline_en_5.5.1_3.0_1737778731106.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_snagmin_pipeline_en_5.5.1_3.0_1737778731106.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_snagmin_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_snagmin_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_snagmin_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/snagmin/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_soumilj_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_soumilj_en.md
new file mode 100644
index 00000000000000..df72897d8b832d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_soumilj_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_soumilj XlmRoBertaForTokenClassification from soumilj
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_soumilj
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_soumilj` is a English model originally trained by soumilj.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_soumilj_en_5.5.1_3.0_1737776706967.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_soumilj_en_5.5.1_3.0_1737776706967.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_soumilj","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_soumilj", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_soumilj|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|832.7 MB|
+
+## References
+
+https://huggingface.co/soumilj/xlm-roberta-base-finetuned-panx-de-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_soumilj_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_soumilj_pipeline_en.md
new file mode 100644
index 00000000000000..493bfa4f64045f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_soumilj_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_soumilj_pipeline pipeline XlmRoBertaForTokenClassification from soumilj
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_soumilj_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_soumilj_pipeline` is a English model originally trained by soumilj.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_soumilj_pipeline_en_5.5.1_3.0_1737776798680.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_soumilj_pipeline_en_5.5.1_3.0_1737776798680.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_soumilj_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_soumilj_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_soumilj_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|832.7 MB|
+
+## References
+
+https://huggingface.co/soumilj/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_thundergod_zenitsu_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_thundergod_zenitsu_en.md
new file mode 100644
index 00000000000000..0e6b5f09d1ef1f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_thundergod_zenitsu_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_thundergod_zenitsu XlmRoBertaForTokenClassification from thundergod-zenitsu
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_thundergod_zenitsu
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_thundergod_zenitsu` is a English model originally trained by thundergod-zenitsu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_thundergod_zenitsu_en_5.5.1_3.0_1737804370108.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_thundergod_zenitsu_en_5.5.1_3.0_1737804370108.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_thundergod_zenitsu","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_thundergod_zenitsu", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_thundergod_zenitsu|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/thundergod-zenitsu/xlm-roberta-base-finetuned-panx-de-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_thundergod_zenitsu_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_thundergod_zenitsu_pipeline_en.md
new file mode 100644
index 00000000000000..240c3666a53f0d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_thundergod_zenitsu_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_thundergod_zenitsu_pipeline pipeline XlmRoBertaForTokenClassification from thundergod-zenitsu
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_thundergod_zenitsu_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_thundergod_zenitsu_pipeline` is a English model originally trained by thundergod-zenitsu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_thundergod_zenitsu_pipeline_en_5.5.1_3.0_1737804466221.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_thundergod_zenitsu_pipeline_en_5.5.1_3.0_1737804466221.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_thundergod_zenitsu_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_thundergod_zenitsu_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_thundergod_zenitsu_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/thundergod-zenitsu/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_wndlek3_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_wndlek3_en.md
new file mode 100644
index 00000000000000..1325dd86bddb52
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_wndlek3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_wndlek3 XlmRoBertaForTokenClassification from wndlek3
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_wndlek3
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_wndlek3` is a English model originally trained by wndlek3.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_wndlek3_en_5.5.1_3.0_1737791518490.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_wndlek3_en_5.5.1_3.0_1737791518490.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_wndlek3","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_wndlek3", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_wndlek3|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/wndlek3/xlm-roberta-base-finetuned-panx-de-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_wndlek3_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_wndlek3_pipeline_en.md
new file mode 100644
index 00000000000000..33bb26fe520f87
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_wndlek3_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_wndlek3_pipeline pipeline XlmRoBertaForTokenClassification from wndlek3
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_wndlek3_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_wndlek3_pipeline` is a English model originally trained by wndlek3.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_wndlek3_pipeline_en_5.5.1_3.0_1737791608879.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_wndlek3_pipeline_en_5.5.1_3.0_1737791608879.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_wndlek3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_wndlek3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_wndlek3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/wndlek3/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_zachhofstad_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_zachhofstad_en.md
new file mode 100644
index 00000000000000..59a832dd4424c7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_zachhofstad_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_zachhofstad XlmRoBertaForTokenClassification from zachhofstad
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_zachhofstad
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_zachhofstad` is a English model originally trained by zachhofstad.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_zachhofstad_en_5.5.1_3.0_1737803358679.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_zachhofstad_en_5.5.1_3.0_1737803358679.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_zachhofstad","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_zachhofstad", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_zachhofstad|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/zachhofstad/xlm-roberta-base-finetuned-panx-de-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_zachhofstad_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_zachhofstad_pipeline_en.md
new file mode 100644
index 00000000000000..9c12eba38dff70
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_french_zachhofstad_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_zachhofstad_pipeline pipeline XlmRoBertaForTokenClassification from zachhofstad
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_zachhofstad_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_zachhofstad_pipeline` is a English model originally trained by zachhofstad.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_zachhofstad_pipeline_en_5.5.1_3.0_1737803449129.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_zachhofstad_pipeline_en_5.5.1_3.0_1737803449129.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_zachhofstad_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_zachhofstad_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_zachhofstad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/zachhofstad/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_hahaha121_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_hahaha121_en.md
new file mode 100644
index 00000000000000..a24765edfd03a9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_hahaha121_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_hahaha121 XlmRoBertaForTokenClassification from hahaha121
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_hahaha121
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_hahaha121` is a English model originally trained by hahaha121.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_hahaha121_en_5.5.1_3.0_1737833093418.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_hahaha121_en_5.5.1_3.0_1737833093418.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_hahaha121","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_hahaha121", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_hahaha121|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/hahaha121/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_hahaha121_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_hahaha121_pipeline_en.md
new file mode 100644
index 00000000000000..8a53d02565d055
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_hahaha121_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_hahaha121_pipeline pipeline XlmRoBertaForTokenClassification from hahaha121
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_hahaha121_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_hahaha121_pipeline` is a English model originally trained by hahaha121.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_hahaha121_pipeline_en_5.5.1_3.0_1737833181559.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_hahaha121_pipeline_en_5.5.1_3.0_1737833181559.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_hahaha121_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_hahaha121_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_hahaha121_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/hahaha121/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_halteroxhunter_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_halteroxhunter_en.md
new file mode 100644
index 00000000000000..ec3595c084d612
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_halteroxhunter_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_halteroxhunter XlmRoBertaForTokenClassification from HalteroXHunter
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_halteroxhunter
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_halteroxhunter` is a English model originally trained by HalteroXHunter.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_halteroxhunter_en_5.5.1_3.0_1737802168939.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_halteroxhunter_en_5.5.1_3.0_1737802168939.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_halteroxhunter","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_halteroxhunter", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_halteroxhunter|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/HalteroXHunter/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_halteroxhunter_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_halteroxhunter_pipeline_en.md
new file mode 100644
index 00000000000000..f8f97826eebd94
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_halteroxhunter_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_halteroxhunter_pipeline pipeline XlmRoBertaForTokenClassification from HalteroXHunter
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_halteroxhunter_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_halteroxhunter_pipeline` is a English model originally trained by HalteroXHunter.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_halteroxhunter_pipeline_en_5.5.1_3.0_1737802240933.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_halteroxhunter_pipeline_en_5.5.1_3.0_1737802240933.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_halteroxhunter_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_halteroxhunter_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_halteroxhunter_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/HalteroXHunter/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_hanlforever_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_hanlforever_en.md
new file mode 100644
index 00000000000000..8535c29bf79a9e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_hanlforever_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_hanlforever XlmRoBertaForTokenClassification from hanlforever
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_hanlforever
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_hanlforever` is a English model originally trained by hanlforever.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_hanlforever_en_5.5.1_3.0_1737803635116.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_hanlforever_en_5.5.1_3.0_1737803635116.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_hanlforever","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_hanlforever", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_hanlforever|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/hanlforever/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_hanlforever_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_hanlforever_pipeline_en.md
new file mode 100644
index 00000000000000..5ba21b084fa8d3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_hanlforever_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_hanlforever_pipeline pipeline XlmRoBertaForTokenClassification from hanlforever
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_hanlforever_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_hanlforever_pipeline` is a English model originally trained by hanlforever.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_hanlforever_pipeline_en_5.5.1_3.0_1737803706620.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_hanlforever_pipeline_en_5.5.1_3.0_1737803706620.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_hanlforever_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_hanlforever_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_hanlforever_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/hanlforever/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_haoj1_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_haoj1_en.md
new file mode 100644
index 00000000000000..ffd2735418c9bb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_haoj1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_haoj1 XlmRoBertaForTokenClassification from haoj1
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_haoj1
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_haoj1` is a English model originally trained by haoj1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_haoj1_en_5.5.1_3.0_1737778113686.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_haoj1_en_5.5.1_3.0_1737778113686.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_haoj1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_haoj1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_haoj1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/haoj1/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_haoj1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_haoj1_pipeline_en.md
new file mode 100644
index 00000000000000..35c25e38928cd5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_haoj1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_haoj1_pipeline pipeline XlmRoBertaForTokenClassification from haoj1
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_haoj1_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_haoj1_pipeline` is a English model originally trained by haoj1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_haoj1_pipeline_en_5.5.1_3.0_1737778203210.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_haoj1_pipeline_en_5.5.1_3.0_1737778203210.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_haoj1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_haoj1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_haoj1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/haoj1/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_hawary365_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_hawary365_en.md
new file mode 100644
index 00000000000000..44f7cc1f9836fd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_hawary365_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_hawary365 XlmRoBertaForTokenClassification from Hawary365
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_hawary365
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_hawary365` is a English model originally trained by Hawary365.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_hawary365_en_5.5.1_3.0_1737803241029.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_hawary365_en_5.5.1_3.0_1737803241029.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_hawary365","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_hawary365", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_hawary365|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/Hawary365/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_hawary365_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_hawary365_pipeline_en.md
new file mode 100644
index 00000000000000..87637156f51bf9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_hawary365_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_hawary365_pipeline pipeline XlmRoBertaForTokenClassification from Hawary365
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_hawary365_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_hawary365_pipeline` is a English model originally trained by Hawary365.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_hawary365_pipeline_en_5.5.1_3.0_1737803329729.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_hawary365_pipeline_en_5.5.1_3.0_1737803329729.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_hawary365_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_hawary365_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_hawary365_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/Hawary365/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_imaditya123_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_imaditya123_en.md
new file mode 100644
index 00000000000000..22356f368556cf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_imaditya123_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_imaditya123 XlmRoBertaForTokenClassification from imaditya123
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_imaditya123
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_imaditya123` is a English model originally trained by imaditya123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_imaditya123_en_5.5.1_3.0_1737779637534.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_imaditya123_en_5.5.1_3.0_1737779637534.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_imaditya123","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_imaditya123", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_imaditya123|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/imaditya123/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_imaditya123_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_imaditya123_pipeline_en.md
new file mode 100644
index 00000000000000..18dbc9a9a95925
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_imaditya123_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_imaditya123_pipeline pipeline XlmRoBertaForTokenClassification from imaditya123
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_imaditya123_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_imaditya123_pipeline` is a English model originally trained by imaditya123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_imaditya123_pipeline_en_5.5.1_3.0_1737779730854.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_imaditya123_pipeline_en_5.5.1_3.0_1737779730854.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_imaditya123_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_imaditya123_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_imaditya123_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/imaditya123/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_kkosidla_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_kkosidla_en.md
new file mode 100644
index 00000000000000..9eb3684f130401
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_kkosidla_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_kkosidla XlmRoBertaForTokenClassification from kkosidla
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_kkosidla
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_kkosidla` is a English model originally trained by kkosidla.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_kkosidla_en_5.5.1_3.0_1737801801394.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_kkosidla_en_5.5.1_3.0_1737801801394.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_kkosidla","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_kkosidla", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_kkosidla|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/kkosidla/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_kkosidla_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_kkosidla_pipeline_en.md
new file mode 100644
index 00000000000000..bfd1edb14d5236
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_kkosidla_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_kkosidla_pipeline pipeline XlmRoBertaForTokenClassification from kkosidla
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_kkosidla_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_kkosidla_pipeline` is a English model originally trained by kkosidla.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_kkosidla_pipeline_en_5.5.1_3.0_1737801891287.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_kkosidla_pipeline_en_5.5.1_3.0_1737801891287.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_kkosidla_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_kkosidla_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_kkosidla_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/kkosidla/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_lee_soha_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_lee_soha_en.md
new file mode 100644
index 00000000000000..7233de4f548f95
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_lee_soha_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_lee_soha XlmRoBertaForTokenClassification from Lee-soha
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_lee_soha
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_lee_soha` is a English model originally trained by Lee-soha.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_lee_soha_en_5.5.1_3.0_1737803511036.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_lee_soha_en_5.5.1_3.0_1737803511036.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_lee_soha","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_lee_soha", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_lee_soha|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/Lee-soha/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_lee_soha_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_lee_soha_pipeline_en.md
new file mode 100644
index 00000000000000..8aebc22901d136
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_lee_soha_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_lee_soha_pipeline pipeline XlmRoBertaForTokenClassification from Lee-soha
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_lee_soha_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_lee_soha_pipeline` is a English model originally trained by Lee-soha.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_lee_soha_pipeline_en_5.5.1_3.0_1737803599422.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_lee_soha_pipeline_en_5.5.1_3.0_1737803599422.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_lee_soha_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_lee_soha_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_lee_soha_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/Lee-soha/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_marumaro_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_marumaro_en.md
new file mode 100644
index 00000000000000..6ebff57f4a242f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_marumaro_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_marumaro XlmRoBertaForTokenClassification from marumaro
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_marumaro
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_marumaro` is a English model originally trained by marumaro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_marumaro_en_5.5.1_3.0_1737790441256.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_marumaro_en_5.5.1_3.0_1737790441256.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_marumaro","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_marumaro", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_marumaro|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/marumaro/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_marumaro_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_marumaro_pipeline_en.md
new file mode 100644
index 00000000000000..f67067befe39f7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_marumaro_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_marumaro_pipeline pipeline XlmRoBertaForTokenClassification from marumaro
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_marumaro_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_marumaro_pipeline` is a English model originally trained by marumaro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_marumaro_pipeline_en_5.5.1_3.0_1737790515326.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_marumaro_pipeline_en_5.5.1_3.0_1737790515326.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_marumaro_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_marumaro_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_marumaro_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/marumaro/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_maybehesham_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_maybehesham_en.md
new file mode 100644
index 00000000000000..af21e1c1f927b9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_maybehesham_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_maybehesham XlmRoBertaForTokenClassification from MayBeHesham
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_maybehesham
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_maybehesham` is a English model originally trained by MayBeHesham.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_maybehesham_en_5.5.1_3.0_1737802592553.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_maybehesham_en_5.5.1_3.0_1737802592553.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_maybehesham","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_maybehesham", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_maybehesham|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/MayBeHesham/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_maybehesham_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_maybehesham_pipeline_en.md
new file mode 100644
index 00000000000000..6d74c47e136ec3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_maybehesham_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_maybehesham_pipeline pipeline XlmRoBertaForTokenClassification from MayBeHesham
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_maybehesham_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_maybehesham_pipeline` is a English model originally trained by MayBeHesham.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_maybehesham_pipeline_en_5.5.1_3.0_1737802681374.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_maybehesham_pipeline_en_5.5.1_3.0_1737802681374.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_maybehesham_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_maybehesham_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_maybehesham_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/MayBeHesham/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_mhmd2125_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_mhmd2125_en.md
new file mode 100644
index 00000000000000..cedfc9d01561b0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_mhmd2125_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_mhmd2125 XlmRoBertaForTokenClassification from mhmd2125
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_mhmd2125
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_mhmd2125` is a English model originally trained by mhmd2125.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_mhmd2125_en_5.5.1_3.0_1737792873253.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_mhmd2125_en_5.5.1_3.0_1737792873253.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_mhmd2125","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_mhmd2125", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_mhmd2125|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/mhmd2125/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_mhmd2125_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_mhmd2125_pipeline_en.md
new file mode 100644
index 00000000000000..fe09de35aea2b3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_mhmd2125_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_mhmd2125_pipeline pipeline XlmRoBertaForTokenClassification from mhmd2125
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_mhmd2125_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_mhmd2125_pipeline` is a English model originally trained by mhmd2125.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_mhmd2125_pipeline_en_5.5.1_3.0_1737792968675.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_mhmd2125_pipeline_en_5.5.1_3.0_1737792968675.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_mhmd2125_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_mhmd2125_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_mhmd2125_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/mhmd2125/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_mohamedalaa00_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_mohamedalaa00_en.md
new file mode 100644
index 00000000000000..c773e3024fca7c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_mohamedalaa00_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_mohamedalaa00 XlmRoBertaForTokenClassification from MohamedAlaa00
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_mohamedalaa00
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_mohamedalaa00` is a English model originally trained by MohamedAlaa00.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_mohamedalaa00_en_5.5.1_3.0_1737791605305.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_mohamedalaa00_en_5.5.1_3.0_1737791605305.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_mohamedalaa00","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_mohamedalaa00", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_mohamedalaa00|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|844.5 MB|
+
+## References
+
+https://huggingface.co/MohamedAlaa00/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_mohamedalaa00_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_mohamedalaa00_pipeline_en.md
new file mode 100644
index 00000000000000..5bd4d960d78509
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_mohamedalaa00_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_mohamedalaa00_pipeline pipeline XlmRoBertaForTokenClassification from MohamedAlaa00
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_mohamedalaa00_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_mohamedalaa00_pipeline` is a English model originally trained by MohamedAlaa00.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_mohamedalaa00_pipeline_en_5.5.1_3.0_1737791698597.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_mohamedalaa00_pipeline_en_5.5.1_3.0_1737791698597.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_mohamedalaa00_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_mohamedalaa00_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_mohamedalaa00_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|844.5 MB|
+
+## References
+
+https://huggingface.co/MohamedAlaa00/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_nickovchinnikov_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_nickovchinnikov_en.md
new file mode 100644
index 00000000000000..77dd9a4c7d2b23
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_nickovchinnikov_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_nickovchinnikov XlmRoBertaForTokenClassification from nickovchinnikov
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_nickovchinnikov
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_nickovchinnikov` is a English model originally trained by nickovchinnikov.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_nickovchinnikov_en_5.5.1_3.0_1737789957443.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_nickovchinnikov_en_5.5.1_3.0_1737789957443.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_nickovchinnikov","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_nickovchinnikov", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_nickovchinnikov|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|854.5 MB|
+
+## References
+
+https://huggingface.co/nickovchinnikov/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_nickovchinnikov_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_nickovchinnikov_pipeline_en.md
new file mode 100644
index 00000000000000..c258b4ba576768
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_nickovchinnikov_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_nickovchinnikov_pipeline pipeline XlmRoBertaForTokenClassification from nickovchinnikov
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_nickovchinnikov_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_nickovchinnikov_pipeline` is a English model originally trained by nickovchinnikov.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_nickovchinnikov_pipeline_en_5.5.1_3.0_1737790024309.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_nickovchinnikov_pipeline_en_5.5.1_3.0_1737790024309.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_nickovchinnikov_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_nickovchinnikov_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_nickovchinnikov_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|854.5 MB|
+
+## References
+
+https://huggingface.co/nickovchinnikov/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_parksuna_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_parksuna_en.md
new file mode 100644
index 00000000000000..1376b366e24001
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_parksuna_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_parksuna XlmRoBertaForTokenClassification from parksuna
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_parksuna
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_parksuna` is a English model originally trained by parksuna.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_parksuna_en_5.5.1_3.0_1737802417309.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_parksuna_en_5.5.1_3.0_1737802417309.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_parksuna","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_parksuna", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_parksuna|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/parksuna/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_parksuna_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_parksuna_pipeline_en.md
new file mode 100644
index 00000000000000..b1b206f46743d9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_parksuna_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_parksuna_pipeline pipeline XlmRoBertaForTokenClassification from parksuna
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_parksuna_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_parksuna_pipeline` is a English model originally trained by parksuna.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_parksuna_pipeline_en_5.5.1_3.0_1737802506530.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_parksuna_pipeline_en_5.5.1_3.0_1737802506530.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_parksuna_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_parksuna_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_parksuna_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/parksuna/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_raegold_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_raegold_en.md
new file mode 100644
index 00000000000000..58afae0c76a3f0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_raegold_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_raegold XlmRoBertaForTokenClassification from RaeGold
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_raegold
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_raegold` is a English model originally trained by RaeGold.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_raegold_en_5.5.1_3.0_1737832311749.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_raegold_en_5.5.1_3.0_1737832311749.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_raegold","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_raegold", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_raegold|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/RaeGold/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_raegold_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_raegold_pipeline_en.md
new file mode 100644
index 00000000000000..673798d1b911ae
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_raegold_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_raegold_pipeline pipeline XlmRoBertaForTokenClassification from RaeGold
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_raegold_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_raegold_pipeline` is a English model originally trained by RaeGold.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_raegold_pipeline_en_5.5.1_3.0_1737832399257.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_raegold_pipeline_en_5.5.1_3.0_1737832399257.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_raegold_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_raegold_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_raegold_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/RaeGold/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_rlawltjd_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_rlawltjd_en.md
new file mode 100644
index 00000000000000..c7d48ecc65ad97
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_rlawltjd_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_rlawltjd XlmRoBertaForTokenClassification from rlawltjd
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_rlawltjd
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_rlawltjd` is a English model originally trained by rlawltjd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_rlawltjd_en_5.5.1_3.0_1737833739590.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_rlawltjd_en_5.5.1_3.0_1737833739590.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_rlawltjd","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_rlawltjd", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_rlawltjd|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/rlawltjd/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_rlawltjd_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_rlawltjd_pipeline_en.md
new file mode 100644
index 00000000000000..545e8e5fda8045
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_rlawltjd_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_rlawltjd_pipeline pipeline XlmRoBertaForTokenClassification from rlawltjd
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_rlawltjd_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_rlawltjd_pipeline` is a English model originally trained by rlawltjd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_rlawltjd_pipeline_en_5.5.1_3.0_1737833828845.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_rlawltjd_pipeline_en_5.5.1_3.0_1737833828845.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_rlawltjd_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_rlawltjd_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_rlawltjd_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/rlawltjd/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_sangminj_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_sangminj_en.md
new file mode 100644
index 00000000000000..c48ff2f0e5b0d8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_sangminj_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_sangminj XlmRoBertaForTokenClassification from sangminJ
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_sangminj
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_sangminj` is a English model originally trained by sangminJ.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_sangminj_en_5.5.1_3.0_1737790829879.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_sangminj_en_5.5.1_3.0_1737790829879.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_sangminj","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_sangminj", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_sangminj|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/sangminJ/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_sangminj_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_sangminj_pipeline_en.md
new file mode 100644
index 00000000000000..df6a310e1cd409
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_sangminj_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_sangminj_pipeline pipeline XlmRoBertaForTokenClassification from sangminJ
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_sangminj_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_sangminj_pipeline` is a English model originally trained by sangminJ.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_sangminj_pipeline_en_5.5.1_3.0_1737790918774.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_sangminj_pipeline_en_5.5.1_3.0_1737790918774.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_sangminj_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_sangminj_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_sangminj_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/sangminJ/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_shinyaoka_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_shinyaoka_en.md
new file mode 100644
index 00000000000000..74dd64a1769f73
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_shinyaoka_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_shinyaoka XlmRoBertaForTokenClassification from shinyaoka
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_shinyaoka
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_shinyaoka` is a English model originally trained by shinyaoka.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_shinyaoka_en_5.5.1_3.0_1737776730445.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_shinyaoka_en_5.5.1_3.0_1737776730445.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_shinyaoka","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_shinyaoka", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_shinyaoka|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/shinyaoka/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_shinyaoka_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_shinyaoka_pipeline_en.md
new file mode 100644
index 00000000000000..802daf24018e3b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_shinyaoka_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_shinyaoka_pipeline pipeline XlmRoBertaForTokenClassification from shinyaoka
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_shinyaoka_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_shinyaoka_pipeline` is a English model originally trained by shinyaoka.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_shinyaoka_pipeline_en_5.5.1_3.0_1737776841767.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_shinyaoka_pipeline_en_5.5.1_3.0_1737776841767.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_shinyaoka_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_shinyaoka_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_shinyaoka_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/shinyaoka/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_shng2025_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_shng2025_en.md
new file mode 100644
index 00000000000000..459213b52ac3fb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_shng2025_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_shng2025 XlmRoBertaForTokenClassification from shng2025
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_shng2025
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_shng2025` is a English model originally trained by shng2025.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_shng2025_en_5.5.1_3.0_1737791937461.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_shng2025_en_5.5.1_3.0_1737791937461.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_shng2025","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_shng2025", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_shng2025|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/shng2025/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_shng2025_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_shng2025_pipeline_en.md
new file mode 100644
index 00000000000000..8352d46be0ba0b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_shng2025_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_shng2025_pipeline pipeline XlmRoBertaForTokenClassification from shng2025
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_shng2025_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_shng2025_pipeline` is a English model originally trained by shng2025.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_shng2025_pipeline_en_5.5.1_3.0_1737792026154.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_shng2025_pipeline_en_5.5.1_3.0_1737792026154.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_shng2025_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_shng2025_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_shng2025_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/shng2025/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_soumilj_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_soumilj_en.md
new file mode 100644
index 00000000000000..6455f775fa29f9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_soumilj_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_soumilj XlmRoBertaForTokenClassification from soumilj
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_soumilj
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_soumilj` is a English model originally trained by soumilj.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_soumilj_en_5.5.1_3.0_1737778814357.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_soumilj_en_5.5.1_3.0_1737778814357.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_soumilj","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_soumilj", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_soumilj|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|831.4 MB|
+
+## References
+
+https://huggingface.co/soumilj/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_soumilj_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_soumilj_pipeline_en.md
new file mode 100644
index 00000000000000..242d6c236d6c64
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_soumilj_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_soumilj_pipeline pipeline XlmRoBertaForTokenClassification from soumilj
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_soumilj_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_soumilj_pipeline` is a English model originally trained by soumilj.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_soumilj_pipeline_en_5.5.1_3.0_1737778904719.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_soumilj_pipeline_en_5.5.1_3.0_1737778904719.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_soumilj_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_soumilj_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_soumilj_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|831.4 MB|
+
+## References
+
+https://huggingface.co/soumilj/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_sr042000_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_sr042000_en.md
new file mode 100644
index 00000000000000..b227f1770646d2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_sr042000_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_sr042000 XlmRoBertaForTokenClassification from sr042000
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_sr042000
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_sr042000` is a English model originally trained by sr042000.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_sr042000_en_5.5.1_3.0_1737779206593.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_sr042000_en_5.5.1_3.0_1737779206593.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_sr042000","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_sr042000", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_sr042000|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|839.3 MB|
+
+## References
+
+https://huggingface.co/sr042000/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_sr042000_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_sr042000_pipeline_en.md
new file mode 100644
index 00000000000000..feb65795d8c444
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_sr042000_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_sr042000_pipeline pipeline XlmRoBertaForTokenClassification from sr042000
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_sr042000_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_sr042000_pipeline` is a English model originally trained by sr042000.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_sr042000_pipeline_en_5.5.1_3.0_1737779295337.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_sr042000_pipeline_en_5.5.1_3.0_1737779295337.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_sr042000_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_sr042000_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_sr042000_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|839.3 MB|
+
+## References
+
+https://huggingface.co/sr042000/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_tarti_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_tarti_en.md
new file mode 100644
index 00000000000000..02576a26760bea
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_tarti_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_tarti XlmRoBertaForTokenClassification from Tarti
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_tarti
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_tarti` is a English model originally trained by Tarti.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_tarti_en_5.5.1_3.0_1737832408963.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_tarti_en_5.5.1_3.0_1737832408963.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_tarti","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_tarti", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_tarti|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/Tarti/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_tarti_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_tarti_pipeline_en.md
new file mode 100644
index 00000000000000..98e4ba3bd530a8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_tarti_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_tarti_pipeline pipeline XlmRoBertaForTokenClassification from Tarti
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_tarti_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_tarti_pipeline` is a English model originally trained by Tarti.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_tarti_pipeline_en_5.5.1_3.0_1737832483421.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_tarti_pipeline_en_5.5.1_3.0_1737832483421.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_tarti_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_tarti_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_tarti_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/Tarti/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_thundergod_zenitsu_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_thundergod_zenitsu_en.md
new file mode 100644
index 00000000000000..d27cadff63fd6a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_thundergod_zenitsu_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_thundergod_zenitsu XlmRoBertaForTokenClassification from thundergod-zenitsu
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_thundergod_zenitsu
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_thundergod_zenitsu` is a English model originally trained by thundergod-zenitsu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_thundergod_zenitsu_en_5.5.1_3.0_1737777117007.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_thundergod_zenitsu_en_5.5.1_3.0_1737777117007.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_thundergod_zenitsu","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_thundergod_zenitsu", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_thundergod_zenitsu|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/thundergod-zenitsu/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_thundergod_zenitsu_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_thundergod_zenitsu_pipeline_en.md
new file mode 100644
index 00000000000000..e37bdd8863bee1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_thundergod_zenitsu_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_thundergod_zenitsu_pipeline pipeline XlmRoBertaForTokenClassification from thundergod-zenitsu
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_thundergod_zenitsu_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_thundergod_zenitsu_pipeline` is a English model originally trained by thundergod-zenitsu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_thundergod_zenitsu_pipeline_en_5.5.1_3.0_1737777205225.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_thundergod_zenitsu_pipeline_en_5.5.1_3.0_1737777205225.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_thundergod_zenitsu_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_thundergod_zenitsu_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_thundergod_zenitsu_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/thundergod-zenitsu/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_tyayoi_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_tyayoi_en.md
new file mode 100644
index 00000000000000..9e5cf13a5eca99
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_tyayoi_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_tyayoi XlmRoBertaForTokenClassification from tyayoi
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_tyayoi
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_tyayoi` is a English model originally trained by tyayoi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_tyayoi_en_5.5.1_3.0_1737793388442.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_tyayoi_en_5.5.1_3.0_1737793388442.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_tyayoi","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_tyayoi", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_tyayoi|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/tyayoi/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_tyayoi_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_tyayoi_pipeline_en.md
new file mode 100644
index 00000000000000..0fd9b48d39df28
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_tyayoi_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_tyayoi_pipeline pipeline XlmRoBertaForTokenClassification from tyayoi
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_tyayoi_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_tyayoi_pipeline` is a English model originally trained by tyayoi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_tyayoi_pipeline_en_5.5.1_3.0_1737793475089.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_tyayoi_pipeline_en_5.5.1_3.0_1737793475089.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_tyayoi_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_tyayoi_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_tyayoi_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/tyayoi/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_vaibhavdlights_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_vaibhavdlights_en.md
new file mode 100644
index 00000000000000..124cb1c1d8ddc0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_vaibhavdlights_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_vaibhavdlights XlmRoBertaForTokenClassification from VaibhavdLights
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_vaibhavdlights
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_vaibhavdlights` is a English model originally trained by VaibhavdLights.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_vaibhavdlights_en_5.5.1_3.0_1737792034643.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_vaibhavdlights_en_5.5.1_3.0_1737792034643.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_vaibhavdlights","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_vaibhavdlights", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_vaibhavdlights|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/VaibhavdLights/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_vaibhavdlights_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_vaibhavdlights_pipeline_en.md
new file mode 100644
index 00000000000000..98649a20709202
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_vaibhavdlights_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_vaibhavdlights_pipeline pipeline XlmRoBertaForTokenClassification from VaibhavdLights
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_vaibhavdlights_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_vaibhavdlights_pipeline` is a English model originally trained by VaibhavdLights.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_vaibhavdlights_pipeline_en_5.5.1_3.0_1737792128076.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_vaibhavdlights_pipeline_en_5.5.1_3.0_1737792128076.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_vaibhavdlights_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_vaibhavdlights_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_vaibhavdlights_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/VaibhavdLights/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_wndlek3_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_wndlek3_en.md
new file mode 100644
index 00000000000000..b80fef8cf20127
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_wndlek3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_wndlek3 XlmRoBertaForTokenClassification from wndlek3
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_wndlek3
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_wndlek3` is a English model originally trained by wndlek3.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_wndlek3_en_5.5.1_3.0_1737793248284.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_wndlek3_en_5.5.1_3.0_1737793248284.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_wndlek3","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_wndlek3", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_wndlek3|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/wndlek3/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_wndlek3_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_wndlek3_pipeline_en.md
new file mode 100644
index 00000000000000..7d11365c274ac4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_wndlek3_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_wndlek3_pipeline pipeline XlmRoBertaForTokenClassification from wndlek3
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_wndlek3_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_wndlek3_pipeline` is a English model originally trained by wndlek3.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_wndlek3_pipeline_en_5.5.1_3.0_1737793337051.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_wndlek3_pipeline_en_5.5.1_3.0_1737793337051.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_wndlek3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_wndlek3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_wndlek3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/wndlek3/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_yezune_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_yezune_en.md
new file mode 100644
index 00000000000000..5036f5b12c677c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_yezune_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_yezune XlmRoBertaForTokenClassification from yezune
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_yezune
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_yezune` is a English model originally trained by yezune.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_yezune_en_5.5.1_3.0_1737778061681.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_yezune_en_5.5.1_3.0_1737778061681.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_yezune","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_yezune", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_yezune|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/yezune/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_yezune_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_yezune_pipeline_en.md
new file mode 100644
index 00000000000000..b53d4bbcfe4b80
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_yezune_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_yezune_pipeline pipeline XlmRoBertaForTokenClassification from yezune
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_yezune_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_yezune_pipeline` is a English model originally trained by yezune.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_yezune_pipeline_en_5.5.1_3.0_1737778133591.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_yezune_pipeline_en_5.5.1_3.0_1737778133591.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_yezune_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_yezune_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_yezune_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/yezune/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_yimisiyang_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_yimisiyang_en.md
new file mode 100644
index 00000000000000..adde8ea85a6700
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_yimisiyang_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_yimisiyang XlmRoBertaForTokenClassification from yimisiyang
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_yimisiyang
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_yimisiyang` is a English model originally trained by yimisiyang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_yimisiyang_en_5.5.1_3.0_1737776727669.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_yimisiyang_en_5.5.1_3.0_1737776727669.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_yimisiyang","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_yimisiyang", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_yimisiyang|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/yimisiyang/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_yimisiyang_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_yimisiyang_pipeline_en.md
new file mode 100644
index 00000000000000..86ac296cb207b0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_yimisiyang_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_yimisiyang_pipeline pipeline XlmRoBertaForTokenClassification from yimisiyang
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_yimisiyang_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_yimisiyang_pipeline` is a English model originally trained by yimisiyang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_yimisiyang_pipeline_en_5.5.1_3.0_1737776841755.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_yimisiyang_pipeline_en_5.5.1_3.0_1737776841755.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_yimisiyang_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_yimisiyang_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_yimisiyang_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/yimisiyang/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_zachhofstad_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_zachhofstad_en.md
new file mode 100644
index 00000000000000..1aac34e845463b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_zachhofstad_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_zachhofstad XlmRoBertaForTokenClassification from zachhofstad
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_zachhofstad
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_zachhofstad` is a English model originally trained by zachhofstad.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_zachhofstad_en_5.5.1_3.0_1737779005818.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_zachhofstad_en_5.5.1_3.0_1737779005818.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_zachhofstad","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_zachhofstad", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_zachhofstad|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/zachhofstad/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_zachhofstad_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_zachhofstad_pipeline_en.md
new file mode 100644
index 00000000000000..53f4ca06e84a92
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_german_zachhofstad_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_zachhofstad_pipeline pipeline XlmRoBertaForTokenClassification from zachhofstad
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_zachhofstad_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_zachhofstad_pipeline` is a English model originally trained by zachhofstad.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_zachhofstad_pipeline_en_5.5.1_3.0_1737779093504.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_zachhofstad_pipeline_en_5.5.1_3.0_1737779093504.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_zachhofstad_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_zachhofstad_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_zachhofstad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/zachhofstad/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_hindi_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_hindi_en.md
new file mode 100644
index 00000000000000..a50fc70961412c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_hindi_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_hindi XlmRoBertaForTokenClassification from gfx-labs
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_hindi
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_hindi` is a English model originally trained by gfx-labs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_hindi_en_5.5.1_3.0_1737793047971.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_hindi_en_5.5.1_3.0_1737793047971.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_hindi","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_hindi", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_hindi|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|835.4 MB|
+
+## References
+
+https://huggingface.co/gfx-labs/xlm-roberta-base-finetuned-panx-hindi
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_hindi_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_hindi_pipeline_en.md
new file mode 100644
index 00000000000000..0c78857fbc7e3c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_hindi_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_hindi_pipeline pipeline XlmRoBertaForTokenClassification from gfx-labs
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_hindi_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_hindi_pipeline` is a English model originally trained by gfx-labs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_hindi_pipeline_en_5.5.1_3.0_1737793129296.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_hindi_pipeline_en_5.5.1_3.0_1737793129296.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_hindi_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_hindi_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_hindi_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|835.4 MB|
+
+## References
+
+https://huggingface.co/gfx-labs/xlm-roberta-base-finetuned-panx-hindi
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_ameko_dev_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_ameko_dev_en.md
new file mode 100644
index 00000000000000..56b95c1c05f448
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_ameko_dev_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_ameko_dev XlmRoBertaForTokenClassification from ameko-dev
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_ameko_dev
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_ameko_dev` is a English model originally trained by ameko-dev.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_ameko_dev_en_5.5.1_3.0_1737777664100.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_ameko_dev_en_5.5.1_3.0_1737777664100.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_ameko_dev","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_ameko_dev", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_ameko_dev|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|816.7 MB|
+
+## References
+
+https://huggingface.co/ameko-dev/xlm-roberta-base-finetuned-panx-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_ameko_dev_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_ameko_dev_pipeline_en.md
new file mode 100644
index 00000000000000..9b74ee33f228b8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_ameko_dev_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_ameko_dev_pipeline pipeline XlmRoBertaForTokenClassification from ameko-dev
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_ameko_dev_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_ameko_dev_pipeline` is a English model originally trained by ameko-dev.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_ameko_dev_pipeline_en_5.5.1_3.0_1737777766910.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_ameko_dev_pipeline_en_5.5.1_3.0_1737777766910.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_ameko_dev_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_ameko_dev_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_ameko_dev_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|816.8 MB|
+
+## References
+
+https://huggingface.co/ameko-dev/xlm-roberta-base-finetuned-panx-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_andrew45_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_andrew45_en.md
new file mode 100644
index 00000000000000..ee849ebb3a93fb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_andrew45_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_andrew45 XlmRoBertaForTokenClassification from andrew45
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_andrew45
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_andrew45` is a English model originally trained by andrew45.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_andrew45_en_5.5.1_3.0_1737791405446.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_andrew45_en_5.5.1_3.0_1737791405446.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_andrew45","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_andrew45", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_andrew45|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|816.7 MB|
+
+## References
+
+https://huggingface.co/andrew45/xlm-roberta-base-finetuned-panx-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_andrew45_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_andrew45_pipeline_en.md
new file mode 100644
index 00000000000000..d94f22cb713bc5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_andrew45_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_andrew45_pipeline pipeline XlmRoBertaForTokenClassification from andrew45
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_andrew45_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_andrew45_pipeline` is a English model originally trained by andrew45.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_andrew45_pipeline_en_5.5.1_3.0_1737791509066.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_andrew45_pipeline_en_5.5.1_3.0_1737791509066.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_andrew45_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_andrew45_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_andrew45_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|816.8 MB|
+
+## References
+
+https://huggingface.co/andrew45/xlm-roberta-base-finetuned-panx-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_cotysong113_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_cotysong113_en.md
new file mode 100644
index 00000000000000..10ca8076ac3769
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_cotysong113_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_cotysong113 XlmRoBertaForTokenClassification from cotysong113
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_cotysong113
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_cotysong113` is a English model originally trained by cotysong113.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_cotysong113_en_5.5.1_3.0_1737802193114.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_cotysong113_en_5.5.1_3.0_1737802193114.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_cotysong113","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_cotysong113", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_cotysong113|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|829.8 MB|
+
+## References
+
+https://huggingface.co/cotysong113/xlm-roberta-base-finetuned-panx-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_cotysong113_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_cotysong113_pipeline_en.md
new file mode 100644
index 00000000000000..d4eaa9954900ba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_cotysong113_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_cotysong113_pipeline pipeline XlmRoBertaForTokenClassification from cotysong113
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_cotysong113_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_cotysong113_pipeline` is a English model originally trained by cotysong113.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_cotysong113_pipeline_en_5.5.1_3.0_1737802288063.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_cotysong113_pipeline_en_5.5.1_3.0_1737802288063.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_cotysong113_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_cotysong113_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_cotysong113_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|829.8 MB|
+
+## References
+
+https://huggingface.co/cotysong113/xlm-roberta-base-finetuned-panx-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_cyrildever_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_cyrildever_en.md
new file mode 100644
index 00000000000000..6fabc2734d7413
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_cyrildever_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_cyrildever XlmRoBertaForTokenClassification from cyrildever
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_cyrildever
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_cyrildever` is a English model originally trained by cyrildever.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_cyrildever_en_5.5.1_3.0_1737778455714.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_cyrildever_en_5.5.1_3.0_1737778455714.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_cyrildever","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_cyrildever", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_cyrildever|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|828.6 MB|
+
+## References
+
+https://huggingface.co/cyrildever/xlm-roberta-base-finetuned-panx-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_cyrildever_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_cyrildever_pipeline_en.md
new file mode 100644
index 00000000000000..0f21497dde760e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_cyrildever_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_cyrildever_pipeline pipeline XlmRoBertaForTokenClassification from cyrildever
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_cyrildever_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_cyrildever_pipeline` is a English model originally trained by cyrildever.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_cyrildever_pipeline_en_5.5.1_3.0_1737778547061.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_cyrildever_pipeline_en_5.5.1_3.0_1737778547061.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_cyrildever_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_cyrildever_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_cyrildever_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|828.6 MB|
+
+## References
+
+https://huggingface.co/cyrildever/xlm-roberta-base-finetuned-panx-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_danielbyiringiro_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_danielbyiringiro_en.md
new file mode 100644
index 00000000000000..6360fe0ade9e57
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_danielbyiringiro_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_danielbyiringiro XlmRoBertaForTokenClassification from danielbyiringiro
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_danielbyiringiro
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_danielbyiringiro` is a English model originally trained by danielbyiringiro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_danielbyiringiro_en_5.5.1_3.0_1737803173504.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_danielbyiringiro_en_5.5.1_3.0_1737803173504.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_danielbyiringiro","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_danielbyiringiro", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_danielbyiringiro|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|816.7 MB|
+
+## References
+
+https://huggingface.co/danielbyiringiro/xlm-roberta-base-finetuned-panx-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_danielbyiringiro_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_danielbyiringiro_pipeline_en.md
new file mode 100644
index 00000000000000..c2d834ad9f669f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_danielbyiringiro_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_danielbyiringiro_pipeline pipeline XlmRoBertaForTokenClassification from danielbyiringiro
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_danielbyiringiro_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_danielbyiringiro_pipeline` is a English model originally trained by danielbyiringiro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_danielbyiringiro_pipeline_en_5.5.1_3.0_1737803276015.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_danielbyiringiro_pipeline_en_5.5.1_3.0_1737803276015.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_danielbyiringiro_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_danielbyiringiro_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_danielbyiringiro_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|816.8 MB|
+
+## References
+
+https://huggingface.co/danielbyiringiro/xlm-roberta-base-finetuned-panx-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_do1232_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_do1232_en.md
new file mode 100644
index 00000000000000..479ad48cc91146
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_do1232_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_do1232 XlmRoBertaForTokenClassification from do1232
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_do1232
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_do1232` is a English model originally trained by do1232.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_do1232_en_5.5.1_3.0_1737792769112.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_do1232_en_5.5.1_3.0_1737792769112.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_do1232","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_do1232", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_do1232|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|816.7 MB|
+
+## References
+
+https://huggingface.co/do1232/xlm-roberta-base-finetuned-panx-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_do1232_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_do1232_pipeline_en.md
new file mode 100644
index 00000000000000..8ec6c9118cec1a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_do1232_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_do1232_pipeline pipeline XlmRoBertaForTokenClassification from do1232
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_do1232_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_do1232_pipeline` is a English model originally trained by do1232.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_do1232_pipeline_en_5.5.1_3.0_1737792871367.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_do1232_pipeline_en_5.5.1_3.0_1737792871367.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_do1232_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_do1232_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_do1232_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|816.8 MB|
+
+## References
+
+https://huggingface.co/do1232/xlm-roberta-base-finetuned-panx-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_haoj1_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_haoj1_en.md
new file mode 100644
index 00000000000000..664ff168448988
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_haoj1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_haoj1 XlmRoBertaForTokenClassification from haoj1
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_haoj1
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_haoj1` is a English model originally trained by haoj1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_haoj1_en_5.5.1_3.0_1737801815117.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_haoj1_en_5.5.1_3.0_1737801815117.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_haoj1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_haoj1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_haoj1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|816.7 MB|
+
+## References
+
+https://huggingface.co/haoj1/xlm-roberta-base-finetuned-panx-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_haoj1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_haoj1_pipeline_en.md
new file mode 100644
index 00000000000000..2dfefe76809fb3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_haoj1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_haoj1_pipeline pipeline XlmRoBertaForTokenClassification from haoj1
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_haoj1_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_haoj1_pipeline` is a English model originally trained by haoj1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_haoj1_pipeline_en_5.5.1_3.0_1737801917243.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_haoj1_pipeline_en_5.5.1_3.0_1737801917243.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_haoj1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_haoj1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_haoj1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|816.8 MB|
+
+## References
+
+https://huggingface.co/haoj1/xlm-roberta-base-finetuned-panx-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_imaditya123_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_imaditya123_en.md
new file mode 100644
index 00000000000000..515394e83ae41e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_imaditya123_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_imaditya123 XlmRoBertaForTokenClassification from imaditya123
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_imaditya123
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_imaditya123` is a English model originally trained by imaditya123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_imaditya123_en_5.5.1_3.0_1737792258303.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_imaditya123_en_5.5.1_3.0_1737792258303.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_imaditya123","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_imaditya123", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_imaditya123|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|816.7 MB|
+
+## References
+
+https://huggingface.co/imaditya123/xlm-roberta-base-finetuned-panx-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_imaditya123_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_imaditya123_pipeline_en.md
new file mode 100644
index 00000000000000..f1bccf363ad057
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_imaditya123_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_imaditya123_pipeline pipeline XlmRoBertaForTokenClassification from imaditya123
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_imaditya123_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_imaditya123_pipeline` is a English model originally trained by imaditya123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_imaditya123_pipeline_en_5.5.1_3.0_1737792364145.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_imaditya123_pipeline_en_5.5.1_3.0_1737792364145.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_imaditya123_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_imaditya123_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_imaditya123_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|816.8 MB|
+
+## References
+
+https://huggingface.co/imaditya123/xlm-roberta-base-finetuned-panx-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_jonghwanbaek1_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_jonghwanbaek1_en.md
new file mode 100644
index 00000000000000..544e07123fbb70
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_jonghwanbaek1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_jonghwanbaek1 XlmRoBertaForTokenClassification from jonghwanbaek1
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_jonghwanbaek1
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_jonghwanbaek1` is a English model originally trained by jonghwanbaek1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_jonghwanbaek1_en_5.5.1_3.0_1737833463416.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_jonghwanbaek1_en_5.5.1_3.0_1737833463416.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_jonghwanbaek1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_jonghwanbaek1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_jonghwanbaek1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|816.7 MB|
+
+## References
+
+https://huggingface.co/jonghwanbaek1/xlm-roberta-base-finetuned-panx-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_jonghwanbaek1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_jonghwanbaek1_pipeline_en.md
new file mode 100644
index 00000000000000..8a6a10c7b61172
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_jonghwanbaek1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_jonghwanbaek1_pipeline pipeline XlmRoBertaForTokenClassification from jonghwanbaek1
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_jonghwanbaek1_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_jonghwanbaek1_pipeline` is a English model originally trained by jonghwanbaek1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_jonghwanbaek1_pipeline_en_5.5.1_3.0_1737833566610.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_jonghwanbaek1_pipeline_en_5.5.1_3.0_1737833566610.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_jonghwanbaek1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_jonghwanbaek1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_jonghwanbaek1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|816.7 MB|
+
+## References
+
+https://huggingface.co/jonghwanbaek1/xlm-roberta-base-finetuned-panx-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_krish2218_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_krish2218_en.md
new file mode 100644
index 00000000000000..816c6d266c49ea
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_krish2218_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_krish2218 XlmRoBertaForTokenClassification from Krish2218
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_krish2218
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_krish2218` is a English model originally trained by Krish2218.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_krish2218_en_5.5.1_3.0_1737792687400.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_krish2218_en_5.5.1_3.0_1737792687400.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_krish2218","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_krish2218", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_krish2218|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|816.7 MB|
+
+## References
+
+https://huggingface.co/Krish2218/xlm-roberta-base-finetuned-panx-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_krish2218_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_krish2218_pipeline_en.md
new file mode 100644
index 00000000000000..56fd641acc1f4a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_krish2218_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_krish2218_pipeline pipeline XlmRoBertaForTokenClassification from Krish2218
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_krish2218_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_krish2218_pipeline` is a English model originally trained by Krish2218.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_krish2218_pipeline_en_5.5.1_3.0_1737792789967.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_krish2218_pipeline_en_5.5.1_3.0_1737792789967.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_krish2218_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_krish2218_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_krish2218_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|816.8 MB|
+
+## References
+
+https://huggingface.co/Krish2218/xlm-roberta-base-finetuned-panx-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_loki47_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_loki47_en.md
new file mode 100644
index 00000000000000..56d7b1e4233194
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_loki47_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_loki47 XlmRoBertaForTokenClassification from loki47
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_loki47
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_loki47` is a English model originally trained by loki47.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_loki47_en_5.5.1_3.0_1737792345943.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_loki47_en_5.5.1_3.0_1737792345943.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_loki47","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_loki47", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_loki47|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|816.7 MB|
+
+## References
+
+https://huggingface.co/loki47/xlm-roberta-base-finetuned-panx-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_loki47_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_loki47_pipeline_en.md
new file mode 100644
index 00000000000000..437a54f21a9798
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_loki47_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_loki47_pipeline pipeline XlmRoBertaForTokenClassification from loki47
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_loki47_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_loki47_pipeline` is a English model originally trained by loki47.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_loki47_pipeline_en_5.5.1_3.0_1737792449027.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_loki47_pipeline_en_5.5.1_3.0_1737792449027.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_loki47_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_loki47_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_loki47_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|816.7 MB|
+
+## References
+
+https://huggingface.co/loki47/xlm-roberta-base-finetuned-panx-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_nik135_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_nik135_en.md
new file mode 100644
index 00000000000000..44881a33595541
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_nik135_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_nik135 XlmRoBertaForTokenClassification from nik135
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_nik135
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_nik135` is a English model originally trained by nik135.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_nik135_en_5.5.1_3.0_1737802712670.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_nik135_en_5.5.1_3.0_1737802712670.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_nik135","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_nik135", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_nik135|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|816.7 MB|
+
+## References
+
+https://huggingface.co/nik135/xlm-roberta-base-finetuned-panx-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_nik135_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_nik135_pipeline_en.md
new file mode 100644
index 00000000000000..e2dd11df155180
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_nik135_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_nik135_pipeline pipeline XlmRoBertaForTokenClassification from nik135
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_nik135_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_nik135_pipeline` is a English model originally trained by nik135.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_nik135_pipeline_en_5.5.1_3.0_1737802813509.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_nik135_pipeline_en_5.5.1_3.0_1737802813509.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_nik135_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_nik135_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_nik135_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|816.8 MB|
+
+## References
+
+https://huggingface.co/nik135/xlm-roberta-base-finetuned-panx-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_qkdaf_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_qkdaf_en.md
new file mode 100644
index 00000000000000..ca0901858f3d78
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_qkdaf_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_qkdaf XlmRoBertaForTokenClassification from qkdaf
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_qkdaf
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_qkdaf` is a English model originally trained by qkdaf.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_qkdaf_en_5.5.1_3.0_1737790629513.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_qkdaf_en_5.5.1_3.0_1737790629513.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_qkdaf","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_qkdaf", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_qkdaf|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|816.7 MB|
+
+## References
+
+https://huggingface.co/qkdaf/xlm-roberta-base-finetuned-panx-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_qkdaf_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_qkdaf_pipeline_en.md
new file mode 100644
index 00000000000000..9cdf8732da744a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_qkdaf_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_qkdaf_pipeline pipeline XlmRoBertaForTokenClassification from qkdaf
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_qkdaf_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_qkdaf_pipeline` is a English model originally trained by qkdaf.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_qkdaf_pipeline_en_5.5.1_3.0_1737790731393.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_qkdaf_pipeline_en_5.5.1_3.0_1737790731393.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_qkdaf_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_qkdaf_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_qkdaf_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|816.8 MB|
+
+## References
+
+https://huggingface.co/qkdaf/xlm-roberta-base-finetuned-panx-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_reynaldhavard_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_reynaldhavard_en.md
new file mode 100644
index 00000000000000..454472d00eccf9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_reynaldhavard_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_reynaldhavard XlmRoBertaForTokenClassification from reynaldhavard
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_reynaldhavard
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_reynaldhavard` is a English model originally trained by reynaldhavard.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_reynaldhavard_en_5.5.1_3.0_1737790890372.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_reynaldhavard_en_5.5.1_3.0_1737790890372.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_reynaldhavard","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_reynaldhavard", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_reynaldhavard|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|816.7 MB|
+
+## References
+
+https://huggingface.co/reynaldhavard/xlm-roberta-base-finetuned-panx-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_reynaldhavard_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_reynaldhavard_pipeline_en.md
new file mode 100644
index 00000000000000..6d834cdef98fce
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_reynaldhavard_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_reynaldhavard_pipeline pipeline XlmRoBertaForTokenClassification from reynaldhavard
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_reynaldhavard_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_reynaldhavard_pipeline` is a English model originally trained by reynaldhavard.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_reynaldhavard_pipeline_en_5.5.1_3.0_1737790991602.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_reynaldhavard_pipeline_en_5.5.1_3.0_1737790991602.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_reynaldhavard_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_reynaldhavard_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_reynaldhavard_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|816.8 MB|
+
+## References
+
+https://huggingface.co/reynaldhavard/xlm-roberta-base-finetuned-panx-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_rlawltjd_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_rlawltjd_en.md
new file mode 100644
index 00000000000000..fcb6d6169e331d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_rlawltjd_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_rlawltjd XlmRoBertaForTokenClassification from rlawltjd
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_rlawltjd
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_rlawltjd` is a English model originally trained by rlawltjd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_rlawltjd_en_5.5.1_3.0_1737832553498.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_rlawltjd_en_5.5.1_3.0_1737832553498.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_rlawltjd","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_rlawltjd", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_rlawltjd|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|816.7 MB|
+
+## References
+
+https://huggingface.co/rlawltjd/xlm-roberta-base-finetuned-panx-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_rlawltjd_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_rlawltjd_pipeline_en.md
new file mode 100644
index 00000000000000..6b21d03259f1fb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_rlawltjd_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_rlawltjd_pipeline pipeline XlmRoBertaForTokenClassification from rlawltjd
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_rlawltjd_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_rlawltjd_pipeline` is a English model originally trained by rlawltjd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_rlawltjd_pipeline_en_5.5.1_3.0_1737832656646.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_rlawltjd_pipeline_en_5.5.1_3.0_1737832656646.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_rlawltjd_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_rlawltjd_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_rlawltjd_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|816.8 MB|
+
+## References
+
+https://huggingface.co/rlawltjd/xlm-roberta-base-finetuned-panx-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_snagmin_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_snagmin_en.md
new file mode 100644
index 00000000000000..9a566be7602730
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_snagmin_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_snagmin XlmRoBertaForTokenClassification from snagmin
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_snagmin
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_snagmin` is a English model originally trained by snagmin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_snagmin_en_5.5.1_3.0_1737792460610.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_snagmin_en_5.5.1_3.0_1737792460610.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_snagmin","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_snagmin", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_snagmin|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|816.7 MB|
+
+## References
+
+https://huggingface.co/snagmin/xlm-roberta-base-finetuned-panx-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_snagmin_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_snagmin_pipeline_en.md
new file mode 100644
index 00000000000000..f3d942f9c2a96e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_snagmin_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_snagmin_pipeline pipeline XlmRoBertaForTokenClassification from snagmin
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_snagmin_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_snagmin_pipeline` is a English model originally trained by snagmin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_snagmin_pipeline_en_5.5.1_3.0_1737792562154.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_snagmin_pipeline_en_5.5.1_3.0_1737792562154.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_snagmin_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_snagmin_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_snagmin_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|816.8 MB|
+
+## References
+
+https://huggingface.co/snagmin/xlm-roberta-base-finetuned-panx-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_thundergod_zenitsu_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_thundergod_zenitsu_en.md
new file mode 100644
index 00000000000000..18f80641896715
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_thundergod_zenitsu_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_thundergod_zenitsu XlmRoBertaForTokenClassification from thundergod-zenitsu
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_thundergod_zenitsu
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_thundergod_zenitsu` is a English model originally trained by thundergod-zenitsu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_thundergod_zenitsu_en_5.5.1_3.0_1737790152126.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_thundergod_zenitsu_en_5.5.1_3.0_1737790152126.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_thundergod_zenitsu","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_thundergod_zenitsu", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_thundergod_zenitsu|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|816.7 MB|
+
+## References
+
+https://huggingface.co/thundergod-zenitsu/xlm-roberta-base-finetuned-panx-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_thundergod_zenitsu_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_thundergod_zenitsu_pipeline_en.md
new file mode 100644
index 00000000000000..98ccdf17d6f18c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_thundergod_zenitsu_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_thundergod_zenitsu_pipeline pipeline XlmRoBertaForTokenClassification from thundergod-zenitsu
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_thundergod_zenitsu_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_thundergod_zenitsu_pipeline` is a English model originally trained by thundergod-zenitsu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_thundergod_zenitsu_pipeline_en_5.5.1_3.0_1737790260155.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_thundergod_zenitsu_pipeline_en_5.5.1_3.0_1737790260155.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_thundergod_zenitsu_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_thundergod_zenitsu_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_thundergod_zenitsu_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|816.8 MB|
+
+## References
+
+https://huggingface.co/thundergod-zenitsu/xlm-roberta-base-finetuned-panx-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_vaibhavdlights_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_vaibhavdlights_en.md
new file mode 100644
index 00000000000000..939218accf19b3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_vaibhavdlights_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_vaibhavdlights XlmRoBertaForTokenClassification from VaibhavdLights
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_vaibhavdlights
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_vaibhavdlights` is a English model originally trained by VaibhavdLights.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_vaibhavdlights_en_5.5.1_3.0_1737777544215.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_vaibhavdlights_en_5.5.1_3.0_1737777544215.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_vaibhavdlights","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_vaibhavdlights", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_vaibhavdlights|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|816.7 MB|
+
+## References
+
+https://huggingface.co/VaibhavdLights/xlm-roberta-base-finetuned-panx-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_vaibhavdlights_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_vaibhavdlights_pipeline_en.md
new file mode 100644
index 00000000000000..7b44ec58099fbd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_vaibhavdlights_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_vaibhavdlights_pipeline pipeline XlmRoBertaForTokenClassification from VaibhavdLights
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_vaibhavdlights_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_vaibhavdlights_pipeline` is a English model originally trained by VaibhavdLights.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_vaibhavdlights_pipeline_en_5.5.1_3.0_1737777647737.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_vaibhavdlights_pipeline_en_5.5.1_3.0_1737777647737.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_vaibhavdlights_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_vaibhavdlights_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_vaibhavdlights_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|816.8 MB|
+
+## References
+
+https://huggingface.co/VaibhavdLights/xlm-roberta-base-finetuned-panx-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_yashcfc_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_yashcfc_en.md
new file mode 100644
index 00000000000000..69f9de57077a54
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_yashcfc_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_yashcfc XlmRoBertaForTokenClassification from yashcfc
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_yashcfc
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_yashcfc` is a English model originally trained by yashcfc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_yashcfc_en_5.5.1_3.0_1737832738516.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_yashcfc_en_5.5.1_3.0_1737832738516.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_yashcfc","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_yashcfc", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_yashcfc|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|816.7 MB|
+
+## References
+
+https://huggingface.co/yashcfc/xlm-roberta-base-finetuned-panx-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_yashcfc_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_yashcfc_pipeline_en.md
new file mode 100644
index 00000000000000..e2e9a5b5d54f9a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_yashcfc_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_yashcfc_pipeline pipeline XlmRoBertaForTokenClassification from yashcfc
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_yashcfc_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_yashcfc_pipeline` is a English model originally trained by yashcfc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_yashcfc_pipeline_en_5.5.1_3.0_1737832839038.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_yashcfc_pipeline_en_5.5.1_3.0_1737832839038.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_yashcfc_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_yashcfc_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_yashcfc_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|816.8 MB|
+
+## References
+
+https://huggingface.co/yashcfc/xlm-roberta-base-finetuned-panx-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_zachhofstad_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_zachhofstad_en.md
new file mode 100644
index 00000000000000..4e626c1d28502f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_zachhofstad_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_zachhofstad XlmRoBertaForTokenClassification from zachhofstad
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_zachhofstad
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_zachhofstad` is a English model originally trained by zachhofstad.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_zachhofstad_en_5.5.1_3.0_1737831072742.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_zachhofstad_en_5.5.1_3.0_1737831072742.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_zachhofstad","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_zachhofstad", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_zachhofstad|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|816.7 MB|
+
+## References
+
+https://huggingface.co/zachhofstad/xlm-roberta-base-finetuned-panx-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_zachhofstad_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_zachhofstad_pipeline_en.md
new file mode 100644
index 00000000000000..8e93157684d839
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_italian_zachhofstad_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_zachhofstad_pipeline pipeline XlmRoBertaForTokenClassification from zachhofstad
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_zachhofstad_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_zachhofstad_pipeline` is a English model originally trained by zachhofstad.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_zachhofstad_pipeline_en_5.5.1_3.0_1737831185076.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_zachhofstad_pipeline_en_5.5.1_3.0_1737831185076.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_zachhofstad_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_zachhofstad_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_zachhofstad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|816.8 MB|
+
+## References
+
+https://huggingface.co/zachhofstad/xlm-roberta-base-finetuned-panx-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_korean_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_korean_en.md
new file mode 100644
index 00000000000000..e2554cebd3823f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_korean_en.md
@@ -0,0 +1,96 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_korean XlmRoBertaForTokenClassification from sungkwangjoong
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_korean
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_korean` is a English model originally trained by sungkwangjoong.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_korean_en_5.5.1_3.0_1737833568009.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_korean_en_5.5.1_3.0_1737833568009.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_korean","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_korean", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_korean|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|808.6 MB|
+
+## References
+
+References
+
+https://huggingface.co/sungkwangjoong/xlm-roberta-base-finetuned-panx-ko
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_korean_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_korean_pipeline_en.md
new file mode 100644
index 00000000000000..9654cc6967fefc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_panx_korean_pipeline_en.md
@@ -0,0 +1,72 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_korean_pipeline pipeline XlmRoBertaForTokenClassification from sungkwangjoong
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_korean_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_korean_pipeline` is a English model originally trained by sungkwangjoong.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_korean_pipeline_en_5.5.1_3.0_1737833672096.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_korean_pipeline_en_5.5.1_3.0_1737833672096.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_korean_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_korean_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_korean_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|808.7 MB|
+
+## References
+
+References
+
+https://huggingface.co/sungkwangjoong/xlm-roberta-base-finetuned-panx-ko
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_ud_arabic_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_ud_arabic_en.md
new file mode 100644
index 00000000000000..d51b816ac0e2a5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_ud_arabic_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_ud_arabic XlmRoBertaForTokenClassification from Mohamedsheded33
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_ud_arabic
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_ud_arabic` is a English model originally trained by Mohamedsheded33.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_ud_arabic_en_5.5.1_3.0_1737831880375.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_ud_arabic_en_5.5.1_3.0_1737831880375.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_ud_arabic","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_ud_arabic", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_ud_arabic|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|828.4 MB|
+
+## References
+
+https://huggingface.co/Mohamedsheded33/xlm-roberta-base-finetuned-ud-arabic
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_ud_arabic_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_ud_arabic_pipeline_en.md
new file mode 100644
index 00000000000000..b243b7c796cc32
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_finetuned_ud_arabic_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_ud_arabic_pipeline pipeline XlmRoBertaForTokenClassification from Mohamedsheded33
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_ud_arabic_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_ud_arabic_pipeline` is a English model originally trained by Mohamedsheded33.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_ud_arabic_pipeline_en_5.5.1_3.0_1737831972166.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_ud_arabic_pipeline_en_5.5.1_3.0_1737831972166.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_ud_arabic_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_ud_arabic_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_ud_arabic_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|828.4 MB|
+
+## References
+
+https://huggingface.co/Mohamedsheded33/xlm-roberta-base-finetuned-ud-arabic
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_pipeline_en.md
new file mode 100644
index 00000000000000..d1869331c9de91
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_pipeline pipeline XlmRoBertaForTokenClassification from hungphongtrn
+author: John Snow Labs
+name: xlm_roberta_base_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_pipeline` is a English model originally trained by hungphongtrn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_pipeline_en_5.5.1_3.0_1737791980797.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_pipeline_en_5.5.1_3.0_1737791980797.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|794.9 MB|
+
+## References
+
+https://huggingface.co/hungphongtrn/xlm-roberta-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_reranker_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_reranker_en.md
new file mode 100644
index 00000000000000..d4fb1129c6996c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_reranker_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_reranker XlmRoBertaForSequenceClassification from PMJAi
+author: John Snow Labs
+name: xlm_roberta_base_reranker
+date: 2025-01-25
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_reranker` is a English model originally trained by PMJAi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_reranker_en_5.5.1_3.0_1737816723246.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_reranker_en_5.5.1_3.0_1737816723246.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_reranker","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_reranker", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_reranker|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|843.8 MB|
+
+## References
+
+https://huggingface.co/PMJAi/xlm-roberta-base-reranker
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_reranker_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_reranker_pipeline_en.md
new file mode 100644
index 00000000000000..33c086ba33328b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlm_roberta_base_reranker_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_reranker_pipeline pipeline XlmRoBertaForSequenceClassification from PMJAi
+author: John Snow Labs
+name: xlm_roberta_base_reranker_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_reranker_pipeline` is a English model originally trained by PMJAi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_reranker_pipeline_en_5.5.1_3.0_1737816835083.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_reranker_pipeline_en_5.5.1_3.0_1737816835083.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_reranker_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_reranker_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_reranker_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|843.8 MB|
+
+## References
+
+https://huggingface.co/PMJAi/xlm-roberta-base-reranker
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlmr_base_refusal_classifier_pipeline_xx.md b/docs/_posts/ahmedlone127/2025-01-25-xlmr_base_refusal_classifier_pipeline_xx.md
new file mode 100644
index 00000000000000..e10f8eea6e24a5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlmr_base_refusal_classifier_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual xlmr_base_refusal_classifier_pipeline pipeline XlmRoBertaForSequenceClassification from chameleon-lizard
+author: John Snow Labs
+name: xlmr_base_refusal_classifier_pipeline
+date: 2025-01-25
+tags: [xx, open_source, pipeline, onnx]
+task: Text Classification
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmr_base_refusal_classifier_pipeline` is a Multilingual model originally trained by chameleon-lizard.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmr_base_refusal_classifier_pipeline_xx_5.5.1_3.0_1737815328241.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmr_base_refusal_classifier_pipeline_xx_5.5.1_3.0_1737815328241.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlmr_base_refusal_classifier_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmr_base_refusal_classifier_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmr_base_refusal_classifier_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|845.0 MB|
+
+## References
+
+https://huggingface.co/chameleon-lizard/xlmr-base-refusal-classifier
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlmr_base_refusal_classifier_xx.md b/docs/_posts/ahmedlone127/2025-01-25-xlmr_base_refusal_classifier_xx.md
new file mode 100644
index 00000000000000..1d05b78b14fb0b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlmr_base_refusal_classifier_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual xlmr_base_refusal_classifier XlmRoBertaForSequenceClassification from chameleon-lizard
+author: John Snow Labs
+name: xlmr_base_refusal_classifier
+date: 2025-01-25
+tags: [xx, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmr_base_refusal_classifier` is a Multilingual model originally trained by chameleon-lizard.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmr_base_refusal_classifier_xx_5.5.1_3.0_1737815209931.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmr_base_refusal_classifier_xx_5.5.1_3.0_1737815209931.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlmr_base_refusal_classifier","xx") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlmr_base_refusal_classifier", "xx")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmr_base_refusal_classifier|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|xx|
+|Size:|845.0 MB|
+
+## References
+
+https://huggingface.co/chameleon-lizard/xlmr-base-refusal-classifier
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlmr_cross_lingual_ner_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlmr_cross_lingual_ner_en.md
new file mode 100644
index 00000000000000..238f5f281e9f6a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlmr_cross_lingual_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlmr_cross_lingual_ner XlmRoBertaForTokenClassification from Sharpaxis
+author: John Snow Labs
+name: xlmr_cross_lingual_ner
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmr_cross_lingual_ner` is a English model originally trained by Sharpaxis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmr_cross_lingual_ner_en_5.5.1_3.0_1737791062862.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmr_cross_lingual_ner_en_5.5.1_3.0_1737791062862.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlmr_cross_lingual_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlmr_cross_lingual_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmr_cross_lingual_ner|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|816.8 MB|
+
+## References
+
+https://huggingface.co/Sharpaxis/XLMR-Cross-Lingual-NER
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlmr_cross_lingual_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlmr_cross_lingual_ner_pipeline_en.md
new file mode 100644
index 00000000000000..bbbabf20dabb9a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlmr_cross_lingual_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlmr_cross_lingual_ner_pipeline pipeline XlmRoBertaForTokenClassification from Sharpaxis
+author: John Snow Labs
+name: xlmr_cross_lingual_ner_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmr_cross_lingual_ner_pipeline` is a English model originally trained by Sharpaxis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmr_cross_lingual_ner_pipeline_en_5.5.1_3.0_1737791184130.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmr_cross_lingual_ner_pipeline_en_5.5.1_3.0_1737791184130.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlmr_cross_lingual_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmr_cross_lingual_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmr_cross_lingual_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|816.8 MB|
+
+## References
+
+https://huggingface.co/Sharpaxis/XLMR-Cross-Lingual-NER
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlmr_finetuned_ner_hmb_e3_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlmr_finetuned_ner_hmb_e3_en.md
new file mode 100644
index 00000000000000..d7af37edd3c5c7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlmr_finetuned_ner_hmb_e3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlmr_finetuned_ner_hmb_e3 XlmRoBertaForTokenClassification from AmaanDhamaskar
+author: John Snow Labs
+name: xlmr_finetuned_ner_hmb_e3
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmr_finetuned_ner_hmb_e3` is a English model originally trained by AmaanDhamaskar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmr_finetuned_ner_hmb_e3_en_5.5.1_3.0_1737833328972.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmr_finetuned_ner_hmb_e3_en_5.5.1_3.0_1737833328972.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlmr_finetuned_ner_hmb_e3","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlmr_finetuned_ner_hmb_e3", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmr_finetuned_ner_hmb_e3|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|814.5 MB|
+
+## References
+
+https://huggingface.co/AmaanDhamaskar/xlmr_finetuned_ner_hmb_e3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlmr_finetuned_ner_hmb_e3_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlmr_finetuned_ner_hmb_e3_pipeline_en.md
new file mode 100644
index 00000000000000..46f8e735a30a2c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlmr_finetuned_ner_hmb_e3_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlmr_finetuned_ner_hmb_e3_pipeline pipeline XlmRoBertaForTokenClassification from AmaanDhamaskar
+author: John Snow Labs
+name: xlmr_finetuned_ner_hmb_e3_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmr_finetuned_ner_hmb_e3_pipeline` is a English model originally trained by AmaanDhamaskar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmr_finetuned_ner_hmb_e3_pipeline_en_5.5.1_3.0_1737833445280.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmr_finetuned_ner_hmb_e3_pipeline_en_5.5.1_3.0_1737833445280.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlmr_finetuned_ner_hmb_e3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmr_finetuned_ner_hmb_e3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmr_finetuned_ner_hmb_e3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|814.5 MB|
+
+## References
+
+https://huggingface.co/AmaanDhamaskar/xlmr_finetuned_ner_hmb_e3
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlmr_finetuned_ner_hmb_e5_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlmr_finetuned_ner_hmb_e5_en.md
new file mode 100644
index 00000000000000..c67c32db7dcc27
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlmr_finetuned_ner_hmb_e5_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlmr_finetuned_ner_hmb_e5 XlmRoBertaForTokenClassification from AmaanDhamaskar
+author: John Snow Labs
+name: xlmr_finetuned_ner_hmb_e5
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmr_finetuned_ner_hmb_e5` is a English model originally trained by AmaanDhamaskar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmr_finetuned_ner_hmb_e5_en_5.5.1_3.0_1737777748373.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmr_finetuned_ner_hmb_e5_en_5.5.1_3.0_1737777748373.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlmr_finetuned_ner_hmb_e5","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlmr_finetuned_ner_hmb_e5", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmr_finetuned_ner_hmb_e5|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|813.9 MB|
+
+## References
+
+https://huggingface.co/AmaanDhamaskar/xlmr_finetuned_ner_hmb_e5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-xlmr_finetuned_ner_hmb_e5_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-xlmr_finetuned_ner_hmb_e5_pipeline_en.md
new file mode 100644
index 00000000000000..596ec940c3e4cb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-xlmr_finetuned_ner_hmb_e5_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlmr_finetuned_ner_hmb_e5_pipeline pipeline XlmRoBertaForTokenClassification from AmaanDhamaskar
+author: John Snow Labs
+name: xlmr_finetuned_ner_hmb_e5_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmr_finetuned_ner_hmb_e5_pipeline` is a English model originally trained by AmaanDhamaskar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmr_finetuned_ner_hmb_e5_pipeline_en_5.5.1_3.0_1737777866430.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmr_finetuned_ner_hmb_e5_pipeline_en_5.5.1_3.0_1737777866430.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlmr_finetuned_ner_hmb_e5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmr_finetuned_ner_hmb_e5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmr_finetuned_ner_hmb_e5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|814.0 MB|
+
+## References
+
+https://huggingface.co/AmaanDhamaskar/xlmr_finetuned_ner_hmb_e5
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-yepes_5e_05_0404_es6_en.md b/docs/_posts/ahmedlone127/2025-01-25-yepes_5e_05_0404_es6_en.md
new file mode 100644
index 00000000000000..368141fcb9bae1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-yepes_5e_05_0404_es6_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English yepes_5e_05_0404_es6 BertForTokenClassification from Brizape
+author: John Snow Labs
+name: yepes_5e_05_0404_es6
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`yepes_5e_05_0404_es6` is a English model originally trained by Brizape.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/yepes_5e_05_0404_es6_en_5.5.1_3.0_1737844400122.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/yepes_5e_05_0404_es6_en_5.5.1_3.0_1737844400122.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("yepes_5e_05_0404_es6","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("yepes_5e_05_0404_es6", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|yepes_5e_05_0404_es6|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|408.2 MB|
+
+## References
+
+https://huggingface.co/Brizape/Yepes_5e-05_0404_ES6
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-yepes_5e_05_0404_es6_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-yepes_5e_05_0404_es6_pipeline_en.md
new file mode 100644
index 00000000000000..2df0a1791a3b20
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-yepes_5e_05_0404_es6_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English yepes_5e_05_0404_es6_pipeline pipeline BertForTokenClassification from Brizape
+author: John Snow Labs
+name: yepes_5e_05_0404_es6_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`yepes_5e_05_0404_es6_pipeline` is a English model originally trained by Brizape.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/yepes_5e_05_0404_es6_pipeline_en_5.5.1_3.0_1737844420667.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/yepes_5e_05_0404_es6_pipeline_en_5.5.1_3.0_1737844420667.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("yepes_5e_05_0404_es6_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("yepes_5e_05_0404_es6_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|yepes_5e_05_0404_es6_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|408.2 MB|
+
+## References
+
+https://huggingface.co/Brizape/Yepes_5e-05_0404_ES6
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-zabantu_ven_120m_ner_tshivenda_en.md b/docs/_posts/ahmedlone127/2025-01-25-zabantu_ven_120m_ner_tshivenda_en.md
new file mode 100644
index 00000000000000..cdb35272cbb85a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-zabantu_ven_120m_ner_tshivenda_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English zabantu_ven_120m_ner_tshivenda XlmRoBertaForTokenClassification from ndamulelonemakh
+author: John Snow Labs
+name: zabantu_ven_120m_ner_tshivenda
+date: 2025-01-25
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`zabantu_ven_120m_ner_tshivenda` is a English model originally trained by ndamulelonemakh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/zabantu_ven_120m_ner_tshivenda_en_5.5.1_3.0_1737803250657.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/zabantu_ven_120m_ner_tshivenda_en_5.5.1_3.0_1737803250657.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("zabantu_ven_120m_ner_tshivenda","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("zabantu_ven_120m_ner_tshivenda", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|zabantu_ven_120m_ner_tshivenda|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|459.3 MB|
+
+## References
+
+https://huggingface.co/ndamulelonemakh/zabantu-ven-120m-ner-tshivenda
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-zabantu_ven_120m_ner_tshivenda_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-zabantu_ven_120m_ner_tshivenda_pipeline_en.md
new file mode 100644
index 00000000000000..5e9f1e8e0ddc0c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-zabantu_ven_120m_ner_tshivenda_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English zabantu_ven_120m_ner_tshivenda_pipeline pipeline XlmRoBertaForTokenClassification from ndamulelonemakh
+author: John Snow Labs
+name: zabantu_ven_120m_ner_tshivenda_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`zabantu_ven_120m_ner_tshivenda_pipeline` is a English model originally trained by ndamulelonemakh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/zabantu_ven_120m_ner_tshivenda_pipeline_en_5.5.1_3.0_1737803277953.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/zabantu_ven_120m_ner_tshivenda_pipeline_en_5.5.1_3.0_1737803277953.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("zabantu_ven_120m_ner_tshivenda_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("zabantu_ven_120m_ner_tshivenda_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|zabantu_ven_120m_ner_tshivenda_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|459.3 MB|
+
+## References
+
+https://huggingface.co/ndamulelonemakh/zabantu-ven-120m-ner-tshivenda
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-zizi2_en.md b/docs/_posts/ahmedlone127/2025-01-25-zizi2_en.md
new file mode 100644
index 00000000000000..79c6781603f5fd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-zizi2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English zizi2 MarianTransformer from Moleys
+author: John Snow Labs
+name: zizi2
+date: 2025-01-25
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`zizi2` is a English model originally trained by Moleys.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/zizi2_en_5.5.1_3.0_1737828049700.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/zizi2_en_5.5.1_3.0_1737828049700.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("zizi2","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("zizi2","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|zizi2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|281.2 MB|
+
+## References
+
+https://huggingface.co/Moleys/zizi2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-25-zizi2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-25-zizi2_pipeline_en.md
new file mode 100644
index 00000000000000..fb0aa0227987e1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-25-zizi2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English zizi2_pipeline pipeline MarianTransformer from Moleys
+author: John Snow Labs
+name: zizi2_pipeline
+date: 2025-01-25
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`zizi2_pipeline` is a English model originally trained by Moleys.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/zizi2_pipeline_en_5.5.1_3.0_1737828064745.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/zizi2_pipeline_en_5.5.1_3.0_1737828064745.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("zizi2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("zizi2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|zizi2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|281.7 MB|
+
+## References
+
+https://huggingface.co/Moleys/zizi2
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-13_epoch_edu_model_finetuned_fintech_en.md b/docs/_posts/ahmedlone127/2025-01-26-13_epoch_edu_model_finetuned_fintech_en.md
new file mode 100644
index 00000000000000..138a2786956cc8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-13_epoch_edu_model_finetuned_fintech_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English 13_epoch_edu_model_finetuned_fintech BertEmbeddings from Pastushoc
+author: John Snow Labs
+name: 13_epoch_edu_model_finetuned_fintech
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`13_epoch_edu_model_finetuned_fintech` is a English model originally trained by Pastushoc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/13_epoch_edu_model_finetuned_fintech_en_5.5.1_3.0_1737861313964.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/13_epoch_edu_model_finetuned_fintech_en_5.5.1_3.0_1737861313964.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("13_epoch_edu_model_finetuned_fintech","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("13_epoch_edu_model_finetuned_fintech","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|13_epoch_edu_model_finetuned_fintech|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|108.7 MB|
+
+## References
+
+https://huggingface.co/Pastushoc/13_epoch_edu_model-finetuned-fintech
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-13_epoch_edu_model_finetuned_fintech_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-13_epoch_edu_model_finetuned_fintech_pipeline_en.md
new file mode 100644
index 00000000000000..517e4d303ac26e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-13_epoch_edu_model_finetuned_fintech_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English 13_epoch_edu_model_finetuned_fintech_pipeline pipeline BertEmbeddings from Pastushoc
+author: John Snow Labs
+name: 13_epoch_edu_model_finetuned_fintech_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`13_epoch_edu_model_finetuned_fintech_pipeline` is a English model originally trained by Pastushoc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/13_epoch_edu_model_finetuned_fintech_pipeline_en_5.5.1_3.0_1737861320056.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/13_epoch_edu_model_finetuned_fintech_pipeline_en_5.5.1_3.0_1737861320056.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("13_epoch_edu_model_finetuned_fintech_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("13_epoch_edu_model_finetuned_fintech_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|13_epoch_edu_model_finetuned_fintech_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|108.7 MB|
+
+## References
+
+https://huggingface.co/Pastushoc/13_epoch_edu_model-finetuned-fintech
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-2020_q2_50p_filtered_en.md b/docs/_posts/ahmedlone127/2025-01-26-2020_q2_50p_filtered_en.md
new file mode 100644
index 00000000000000..01855e0c323a96
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-2020_q2_50p_filtered_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English 2020_q2_50p_filtered RoBertaEmbeddings from DouglasPontes
+author: John Snow Labs
+name: 2020_q2_50p_filtered
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`2020_q2_50p_filtered` is a English model originally trained by DouglasPontes.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/2020_q2_50p_filtered_en_5.5.1_3.0_1737907070273.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/2020_q2_50p_filtered_en_5.5.1_3.0_1737907070273.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("2020_q2_50p_filtered","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("2020_q2_50p_filtered","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|2020_q2_50p_filtered|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|465.9 MB|
+
+## References
+
+https://huggingface.co/DouglasPontes/2020-Q2-50p-filtered
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-2020_q2_50p_filtered_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-2020_q2_50p_filtered_pipeline_en.md
new file mode 100644
index 00000000000000..035e3a794e821f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-2020_q2_50p_filtered_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English 2020_q2_50p_filtered_pipeline pipeline RoBertaEmbeddings from DouglasPontes
+author: John Snow Labs
+name: 2020_q2_50p_filtered_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`2020_q2_50p_filtered_pipeline` is a English model originally trained by DouglasPontes.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/2020_q2_50p_filtered_pipeline_en_5.5.1_3.0_1737907097009.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/2020_q2_50p_filtered_pipeline_en_5.5.1_3.0_1737907097009.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("2020_q2_50p_filtered_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("2020_q2_50p_filtered_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|2020_q2_50p_filtered_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|465.9 MB|
+
+## References
+
+https://huggingface.co/DouglasPontes/2020-Q2-50p-filtered
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-2020_q2_75p_filtered_en.md b/docs/_posts/ahmedlone127/2025-01-26-2020_q2_75p_filtered_en.md
new file mode 100644
index 00000000000000..3378e60116ec01
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-2020_q2_75p_filtered_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English 2020_q2_75p_filtered RoBertaEmbeddings from DouglasPontes
+author: John Snow Labs
+name: 2020_q2_75p_filtered
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`2020_q2_75p_filtered` is a English model originally trained by DouglasPontes.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/2020_q2_75p_filtered_en_5.5.1_3.0_1737865203289.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/2020_q2_75p_filtered_en_5.5.1_3.0_1737865203289.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("2020_q2_75p_filtered","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("2020_q2_75p_filtered","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|2020_q2_75p_filtered|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|465.9 MB|
+
+## References
+
+https://huggingface.co/DouglasPontes/2020-Q2-75p-filtered
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-2020_q2_75p_filtered_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-2020_q2_75p_filtered_pipeline_en.md
new file mode 100644
index 00000000000000..c131fdcc259e75
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-2020_q2_75p_filtered_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English 2020_q2_75p_filtered_pipeline pipeline RoBertaEmbeddings from DouglasPontes
+author: John Snow Labs
+name: 2020_q2_75p_filtered_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`2020_q2_75p_filtered_pipeline` is a English model originally trained by DouglasPontes.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/2020_q2_75p_filtered_pipeline_en_5.5.1_3.0_1737865233071.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/2020_q2_75p_filtered_pipeline_en_5.5.1_3.0_1737865233071.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("2020_q2_75p_filtered_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("2020_q2_75p_filtered_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|2020_q2_75p_filtered_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|465.9 MB|
+
+## References
+
+https://huggingface.co/DouglasPontes/2020-Q2-75p-filtered
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-2020_q4_90p_filtered_random_en.md b/docs/_posts/ahmedlone127/2025-01-26-2020_q4_90p_filtered_random_en.md
new file mode 100644
index 00000000000000..88c0498dd8c603
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-2020_q4_90p_filtered_random_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English 2020_q4_90p_filtered_random RoBertaEmbeddings from DouglasPontes
+author: John Snow Labs
+name: 2020_q4_90p_filtered_random
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`2020_q4_90p_filtered_random` is a English model originally trained by DouglasPontes.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/2020_q4_90p_filtered_random_en_5.5.1_3.0_1737866062202.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/2020_q4_90p_filtered_random_en_5.5.1_3.0_1737866062202.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("2020_q4_90p_filtered_random","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("2020_q4_90p_filtered_random","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|2020_q4_90p_filtered_random|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|466.1 MB|
+
+## References
+
+https://huggingface.co/DouglasPontes/2020-Q4-90p-filtered-random
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-2020_q4_90p_filtered_random_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-2020_q4_90p_filtered_random_pipeline_en.md
new file mode 100644
index 00000000000000..6cff7d276faf38
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-2020_q4_90p_filtered_random_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English 2020_q4_90p_filtered_random_pipeline pipeline RoBertaEmbeddings from DouglasPontes
+author: John Snow Labs
+name: 2020_q4_90p_filtered_random_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`2020_q4_90p_filtered_random_pipeline` is a English model originally trained by DouglasPontes.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/2020_q4_90p_filtered_random_pipeline_en_5.5.1_3.0_1737866100492.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/2020_q4_90p_filtered_random_pipeline_en_5.5.1_3.0_1737866100492.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("2020_q4_90p_filtered_random_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("2020_q4_90p_filtered_random_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|2020_q4_90p_filtered_random_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.1 MB|
+
+## References
+
+https://huggingface.co/DouglasPontes/2020-Q4-90p-filtered-random
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-24thankyou_lyrics_generator_en.md b/docs/_posts/ahmedlone127/2025-01-26-24thankyou_lyrics_generator_en.md
new file mode 100644
index 00000000000000..970c0df7026940
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-24thankyou_lyrics_generator_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English 24thankyou_lyrics_generator GPT2Transformer from smgriffin
+author: John Snow Labs
+name: 24thankyou_lyrics_generator
+date: 2025-01-26
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`24thankyou_lyrics_generator` is a English model originally trained by smgriffin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/24thankyou_lyrics_generator_en_5.5.1_3.0_1737913636199.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/24thankyou_lyrics_generator_en_5.5.1_3.0_1737913636199.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("24thankyou_lyrics_generator","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("24thankyou_lyrics_generator","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|24thankyou_lyrics_generator|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/smgriffin/24thankyou-lyrics-generator
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-24thankyou_lyrics_generator_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-24thankyou_lyrics_generator_pipeline_en.md
new file mode 100644
index 00000000000000..fdd0695de502d9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-24thankyou_lyrics_generator_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English 24thankyou_lyrics_generator_pipeline pipeline GPT2Transformer from smgriffin
+author: John Snow Labs
+name: 24thankyou_lyrics_generator_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`24thankyou_lyrics_generator_pipeline` is a English model originally trained by smgriffin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/24thankyou_lyrics_generator_pipeline_en_5.5.1_3.0_1737913659403.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/24thankyou_lyrics_generator_pipeline_en_5.5.1_3.0_1737913659403.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("24thankyou_lyrics_generator_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("24thankyou_lyrics_generator_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|24thankyou_lyrics_generator_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/smgriffin/24thankyou-lyrics-generator
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-6000_en.md b/docs/_posts/ahmedlone127/2025-01-26-6000_en.md
new file mode 100644
index 00000000000000..ebdd8d59cbba0b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-6000_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English 6000 MarianTransformer from vania2911
+author: John Snow Labs
+name: 6000
+date: 2025-01-26
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6000` is a English model originally trained by vania2911.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6000_en_5.5.1_3.0_1737863278184.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6000_en_5.5.1_3.0_1737863278184.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("6000","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("6000","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|6000|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|295.5 MB|
+
+## References
+
+https://huggingface.co/vania2911/6000
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-6000_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-6000_pipeline_en.md
new file mode 100644
index 00000000000000..cbfede384ff3de
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-6000_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English 6000_pipeline pipeline MarianTransformer from vania2911
+author: John Snow Labs
+name: 6000_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6000_pipeline` is a English model originally trained by vania2911.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6000_pipeline_en_5.5.1_3.0_1737863294287.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6000_pipeline_en_5.5.1_3.0_1737863294287.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("6000_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("6000_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|6000_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|296.0 MB|
+
+## References
+
+https://huggingface.co/vania2911/6000
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-ai_chat_underage_moderation2_en.md b/docs/_posts/ahmedlone127/2025-01-26-ai_chat_underage_moderation2_en.md
new file mode 100644
index 00000000000000..df0cde5d694712
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-ai_chat_underage_moderation2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ai_chat_underage_moderation2 DistilBertForSequenceClassification from andriadze
+author: John Snow Labs
+name: ai_chat_underage_moderation2
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ai_chat_underage_moderation2` is a English model originally trained by andriadze.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ai_chat_underage_moderation2_en_5.5.1_3.0_1737904617004.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ai_chat_underage_moderation2_en_5.5.1_3.0_1737904617004.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("ai_chat_underage_moderation2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("ai_chat_underage_moderation2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ai_chat_underage_moderation2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/andriadze/ai-chat-underage-moderation2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-ai_chat_underage_moderation2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-ai_chat_underage_moderation2_pipeline_en.md
new file mode 100644
index 00000000000000..35693a76cd3dc5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-ai_chat_underage_moderation2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ai_chat_underage_moderation2_pipeline pipeline DistilBertForSequenceClassification from andriadze
+author: John Snow Labs
+name: ai_chat_underage_moderation2_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ai_chat_underage_moderation2_pipeline` is a English model originally trained by andriadze.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ai_chat_underage_moderation2_pipeline_en_5.5.1_3.0_1737904635517.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ai_chat_underage_moderation2_pipeline_en_5.5.1_3.0_1737904635517.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ai_chat_underage_moderation2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ai_chat_underage_moderation2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ai_chat_underage_moderation2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/andriadze/ai-chat-underage-moderation2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-ai_guru_pipeline_si.md b/docs/_posts/ahmedlone127/2025-01-26-ai_guru_pipeline_si.md
new file mode 100644
index 00000000000000..f17dc7d6ce6d81
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-ai_guru_pipeline_si.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Sinhala, Sinhalese ai_guru_pipeline pipeline GPT2Transformer from enzer1992
+author: John Snow Labs
+name: ai_guru_pipeline
+date: 2025-01-26
+tags: [si, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: si
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ai_guru_pipeline` is a Sinhala, Sinhalese model originally trained by enzer1992.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ai_guru_pipeline_si_5.5.1_3.0_1737916173820.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ai_guru_pipeline_si_5.5.1_3.0_1737916173820.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ai_guru_pipeline", lang = "si")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ai_guru_pipeline", lang = "si")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ai_guru_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|si|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/enzer1992/AI-Guru
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-ai_guru_si.md b/docs/_posts/ahmedlone127/2025-01-26-ai_guru_si.md
new file mode 100644
index 00000000000000..e93a31c4e16f92
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-ai_guru_si.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Sinhala, Sinhalese ai_guru GPT2Transformer from enzer1992
+author: John Snow Labs
+name: ai_guru
+date: 2025-01-26
+tags: [si, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: si
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ai_guru` is a Sinhala, Sinhalese model originally trained by enzer1992.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ai_guru_si_5.5.1_3.0_1737916150548.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ai_guru_si_5.5.1_3.0_1737916150548.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("ai_guru","si") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("ai_guru","si") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ai_guru|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|si|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/enzer1992/AI-Guru
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-ai_vs_real_image_detection_hemg_en.md b/docs/_posts/ahmedlone127/2025-01-26-ai_vs_real_image_detection_hemg_en.md
new file mode 100644
index 00000000000000..d194aff0eb0982
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-ai_vs_real_image_detection_hemg_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ai_vs_real_image_detection_hemg ViTForImageClassification from Hemg
+author: John Snow Labs
+name: ai_vs_real_image_detection_hemg
+date: 2025-01-26
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ai_vs_real_image_detection_hemg` is a English model originally trained by Hemg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ai_vs_real_image_detection_hemg_en_5.5.1_3.0_1737925977153.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ai_vs_real_image_detection_hemg_en_5.5.1_3.0_1737925977153.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""ai_vs_real_image_detection_hemg","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("ai_vs_real_image_detection_hemg","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ai_vs_real_image_detection_hemg|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/Hemg/AI-VS-REAL-IMAGE-DETECTION
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-ai_vs_real_image_detection_hemg_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-ai_vs_real_image_detection_hemg_pipeline_en.md
new file mode 100644
index 00000000000000..fae22fc21b9275
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-ai_vs_real_image_detection_hemg_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English ai_vs_real_image_detection_hemg_pipeline pipeline ViTForImageClassification from Hemg
+author: John Snow Labs
+name: ai_vs_real_image_detection_hemg_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ai_vs_real_image_detection_hemg_pipeline` is a English model originally trained by Hemg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ai_vs_real_image_detection_hemg_pipeline_en_5.5.1_3.0_1737925994090.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ai_vs_real_image_detection_hemg_pipeline_en_5.5.1_3.0_1737925994090.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ai_vs_real_image_detection_hemg_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ai_vs_real_image_detection_hemg_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ai_vs_real_image_detection_hemg_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/Hemg/AI-VS-REAL-IMAGE-DETECTION
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-all_minilm_l6_v2_personal_project_default_2024_03_22_en.md b/docs/_posts/ahmedlone127/2025-01-26-all_minilm_l6_v2_personal_project_default_2024_03_22_en.md
new file mode 100644
index 00000000000000..675bed5cd9a480
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-all_minilm_l6_v2_personal_project_default_2024_03_22_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English all_minilm_l6_v2_personal_project_default_2024_03_22 BertEmbeddings from brugmark
+author: John Snow Labs
+name: all_minilm_l6_v2_personal_project_default_2024_03_22
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_minilm_l6_v2_personal_project_default_2024_03_22` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_default_2024_03_22_en_5.5.1_3.0_1737861851795.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_default_2024_03_22_en_5.5.1_3.0_1737861851795.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("all_minilm_l6_v2_personal_project_default_2024_03_22","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("all_minilm_l6_v2_personal_project_default_2024_03_22","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_minilm_l6_v2_personal_project_default_2024_03_22|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|83.9 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-default-2024-03-22
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-all_minilm_l6_v2_personal_project_default_2024_03_22_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-all_minilm_l6_v2_personal_project_default_2024_03_22_pipeline_en.md
new file mode 100644
index 00000000000000..dc3d7903147273
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-all_minilm_l6_v2_personal_project_default_2024_03_22_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English all_minilm_l6_v2_personal_project_default_2024_03_22_pipeline pipeline BertEmbeddings from brugmark
+author: John Snow Labs
+name: all_minilm_l6_v2_personal_project_default_2024_03_22_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_minilm_l6_v2_personal_project_default_2024_03_22_pipeline` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_default_2024_03_22_pipeline_en_5.5.1_3.0_1737861856623.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_default_2024_03_22_pipeline_en_5.5.1_3.0_1737861856623.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("all_minilm_l6_v2_personal_project_default_2024_03_22_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("all_minilm_l6_v2_personal_project_default_2024_03_22_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_minilm_l6_v2_personal_project_default_2024_03_22_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|83.9 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-default-2024-03-22
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-all_minilm_l6_v2_personal_project_default_2024_06_14_en.md b/docs/_posts/ahmedlone127/2025-01-26-all_minilm_l6_v2_personal_project_default_2024_06_14_en.md
new file mode 100644
index 00000000000000..e756559ffec159
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-all_minilm_l6_v2_personal_project_default_2024_06_14_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English all_minilm_l6_v2_personal_project_default_2024_06_14 BertEmbeddings from brugmark
+author: John Snow Labs
+name: all_minilm_l6_v2_personal_project_default_2024_06_14
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_minilm_l6_v2_personal_project_default_2024_06_14` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_default_2024_06_14_en_5.5.1_3.0_1737890556401.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_default_2024_06_14_en_5.5.1_3.0_1737890556401.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("all_minilm_l6_v2_personal_project_default_2024_06_14","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("all_minilm_l6_v2_personal_project_default_2024_06_14","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_minilm_l6_v2_personal_project_default_2024_06_14|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|83.9 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-default-2024-06-14
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-all_minilm_l6_v2_personal_project_default_2024_06_14_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-all_minilm_l6_v2_personal_project_default_2024_06_14_pipeline_en.md
new file mode 100644
index 00000000000000..776f2711821094
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-all_minilm_l6_v2_personal_project_default_2024_06_14_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English all_minilm_l6_v2_personal_project_default_2024_06_14_pipeline pipeline BertEmbeddings from brugmark
+author: John Snow Labs
+name: all_minilm_l6_v2_personal_project_default_2024_06_14_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_minilm_l6_v2_personal_project_default_2024_06_14_pipeline` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_default_2024_06_14_pipeline_en_5.5.1_3.0_1737890561085.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_default_2024_06_14_pipeline_en_5.5.1_3.0_1737890561085.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("all_minilm_l6_v2_personal_project_default_2024_06_14_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("all_minilm_l6_v2_personal_project_default_2024_06_14_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_minilm_l6_v2_personal_project_default_2024_06_14_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|83.9 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-default-2024-06-14
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-arabert_dialect_en.md b/docs/_posts/ahmedlone127/2025-01-26-arabert_dialect_en.md
new file mode 100644
index 00000000000000..a9c15d71a9b8e3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-arabert_dialect_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English arabert_dialect BertEmbeddings from HossamElsafty
+author: John Snow Labs
+name: arabert_dialect
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`arabert_dialect` is a English model originally trained by HossamElsafty.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/arabert_dialect_en_5.5.1_3.0_1737861520710.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/arabert_dialect_en_5.5.1_3.0_1737861520710.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("arabert_dialect","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("arabert_dialect","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|arabert_dialect|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|604.6 MB|
+
+## References
+
+https://huggingface.co/HossamElsafty/AraBERT_Dialect
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-arabert_dialect_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-arabert_dialect_pipeline_en.md
new file mode 100644
index 00000000000000..11b25fb5b3a263
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-arabert_dialect_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English arabert_dialect_pipeline pipeline BertEmbeddings from HossamElsafty
+author: John Snow Labs
+name: arabert_dialect_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`arabert_dialect_pipeline` is a English model originally trained by HossamElsafty.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/arabert_dialect_pipeline_en_5.5.1_3.0_1737861556445.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/arabert_dialect_pipeline_en_5.5.1_3.0_1737861556445.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("arabert_dialect_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("arabert_dialect_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|arabert_dialect_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|604.6 MB|
+
+## References
+
+https://huggingface.co/HossamElsafty/AraBERT_Dialect
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-arbert_entitylinking_pre_training_en.md b/docs/_posts/ahmedlone127/2025-01-26-arbert_entitylinking_pre_training_en.md
new file mode 100644
index 00000000000000..8f7ea0249e0761
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-arbert_entitylinking_pre_training_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English arbert_entitylinking_pre_training BertForTokenClassification from AfnanTS
+author: John Snow Labs
+name: arbert_entitylinking_pre_training
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`arbert_entitylinking_pre_training` is a English model originally trained by AfnanTS.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/arbert_entitylinking_pre_training_en_5.5.1_3.0_1737935504740.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/arbert_entitylinking_pre_training_en_5.5.1_3.0_1737935504740.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("arbert_entitylinking_pre_training","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("arbert_entitylinking_pre_training", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|arbert_entitylinking_pre_training|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|605.4 MB|
+
+## References
+
+https://huggingface.co/AfnanTS/ARBERT_EntityLinking_pre-training
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-arbert_entitylinking_pre_training_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-arbert_entitylinking_pre_training_pipeline_en.md
new file mode 100644
index 00000000000000..6fa39510b900e3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-arbert_entitylinking_pre_training_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English arbert_entitylinking_pre_training_pipeline pipeline BertForTokenClassification from AfnanTS
+author: John Snow Labs
+name: arbert_entitylinking_pre_training_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`arbert_entitylinking_pre_training_pipeline` is a English model originally trained by AfnanTS.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/arbert_entitylinking_pre_training_pipeline_en_5.5.1_3.0_1737935536893.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/arbert_entitylinking_pre_training_pipeline_en_5.5.1_3.0_1737935536893.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("arbert_entitylinking_pre_training_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("arbert_entitylinking_pre_training_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|arbert_entitylinking_pre_training_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|605.4 MB|
+
+## References
+
+https://huggingface.co/AfnanTS/ARBERT_EntityLinking_pre-training
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-ardiabertv2_cosine_en.md b/docs/_posts/ahmedlone127/2025-01-26-ardiabertv2_cosine_en.md
new file mode 100644
index 00000000000000..31cd46bd3b1731
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-ardiabertv2_cosine_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ardiabertv2_cosine BertEmbeddings from HossamElsafty
+author: John Snow Labs
+name: ardiabertv2_cosine
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ardiabertv2_cosine` is a English model originally trained by HossamElsafty.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ardiabertv2_cosine_en_5.5.1_3.0_1737861294319.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ardiabertv2_cosine_en_5.5.1_3.0_1737861294319.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("ardiabertv2_cosine","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("ardiabertv2_cosine","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ardiabertv2_cosine|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|605.3 MB|
+
+## References
+
+https://huggingface.co/HossamElsafty/ArDiaBERTv2_cosine
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-ardiabertv2_cosine_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-ardiabertv2_cosine_pipeline_en.md
new file mode 100644
index 00000000000000..5aca0f8e3e6dd3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-ardiabertv2_cosine_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ardiabertv2_cosine_pipeline pipeline BertEmbeddings from HossamElsafty
+author: John Snow Labs
+name: ardiabertv2_cosine_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ardiabertv2_cosine_pipeline` is a English model originally trained by HossamElsafty.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ardiabertv2_cosine_pipeline_en_5.5.1_3.0_1737861326006.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ardiabertv2_cosine_pipeline_en_5.5.1_3.0_1737861326006.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ardiabertv2_cosine_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ardiabertv2_cosine_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ardiabertv2_cosine_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|605.3 MB|
+
+## References
+
+https://huggingface.co/HossamElsafty/ArDiaBERTv2_cosine
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-arg_quality_en.md b/docs/_posts/ahmedlone127/2025-01-26-arg_quality_en.md
new file mode 100644
index 00000000000000..cef21278e1e6c6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-arg_quality_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English arg_quality DistilBertForSequenceClassification from austenem
+author: John Snow Labs
+name: arg_quality
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`arg_quality` is a English model originally trained by austenem.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/arg_quality_en_5.5.1_3.0_1737905316161.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/arg_quality_en_5.5.1_3.0_1737905316161.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("arg_quality","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("arg_quality", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|arg_quality|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.7 MB|
+
+## References
+
+https://huggingface.co/austenem/arg-quality
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-arg_quality_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-arg_quality_pipeline_en.md
new file mode 100644
index 00000000000000..6cc33432c161ef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-arg_quality_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English arg_quality_pipeline pipeline DistilBertForSequenceClassification from austenem
+author: John Snow Labs
+name: arg_quality_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`arg_quality_pipeline` is a English model originally trained by austenem.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/arg_quality_pipeline_en_5.5.1_3.0_1737905329341.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/arg_quality_pipeline_en_5.5.1_3.0_1737905329341.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("arg_quality_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("arg_quality_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|arg_quality_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.8 MB|
+
+## References
+
+https://huggingface.co/austenem/arg-quality
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-autotrain_lasiocampidae_73081139111_en.md b/docs/_posts/ahmedlone127/2025-01-26-autotrain_lasiocampidae_73081139111_en.md
new file mode 100644
index 00000000000000..5dbbf3d2182167
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-autotrain_lasiocampidae_73081139111_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English autotrain_lasiocampidae_73081139111 SwinForImageClassification from rdmpage
+author: John Snow Labs
+name: autotrain_lasiocampidae_73081139111
+date: 2025-01-26
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_lasiocampidae_73081139111` is a English model originally trained by rdmpage.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_lasiocampidae_73081139111_en_5.5.1_3.0_1737889503463.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_lasiocampidae_73081139111_en_5.5.1_3.0_1737889503463.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""autotrain_lasiocampidae_73081139111","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("autotrain_lasiocampidae_73081139111","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_lasiocampidae_73081139111|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/rdmpage/autotrain-lasiocampidae-73081139111
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-autotrain_lasiocampidae_73081139111_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-autotrain_lasiocampidae_73081139111_pipeline_en.md
new file mode 100644
index 00000000000000..f2bddb286e7755
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-autotrain_lasiocampidae_73081139111_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English autotrain_lasiocampidae_73081139111_pipeline pipeline SwinForImageClassification from rdmpage
+author: John Snow Labs
+name: autotrain_lasiocampidae_73081139111_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_lasiocampidae_73081139111_pipeline` is a English model originally trained by rdmpage.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_lasiocampidae_73081139111_pipeline_en_5.5.1_3.0_1737889514065.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_lasiocampidae_73081139111_pipeline_en_5.5.1_3.0_1737889514065.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("autotrain_lasiocampidae_73081139111_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("autotrain_lasiocampidae_73081139111_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_lasiocampidae_73081139111_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/rdmpage/autotrain-lasiocampidae-73081139111
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-autotrain_parking_en.md b/docs/_posts/ahmedlone127/2025-01-26-autotrain_parking_en.md
new file mode 100644
index 00000000000000..5bf496e7234f7e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-autotrain_parking_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English autotrain_parking SwinForImageClassification from mietlinski
+author: John Snow Labs
+name: autotrain_parking
+date: 2025-01-26
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_parking` is a English model originally trained by mietlinski.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_parking_en_5.5.1_3.0_1737888947825.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_parking_en_5.5.1_3.0_1737888947825.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""autotrain_parking","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("autotrain_parking","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_parking|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|649.8 MB|
+
+## References
+
+https://huggingface.co/mietlinski/autotrain-parking
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-autotrain_parking_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-autotrain_parking_pipeline_en.md
new file mode 100644
index 00000000000000..9364a68c4e1088
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-autotrain_parking_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English autotrain_parking_pipeline pipeline SwinForImageClassification from mietlinski
+author: John Snow Labs
+name: autotrain_parking_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_parking_pipeline` is a English model originally trained by mietlinski.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_parking_pipeline_en_5.5.1_3.0_1737888981236.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_parking_pipeline_en_5.5.1_3.0_1737888981236.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("autotrain_parking_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("autotrain_parking_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_parking_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|649.8 MB|
+
+## References
+
+https://huggingface.co/mietlinski/autotrain-parking
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-babylm_jde_larger_10_en.md b/docs/_posts/ahmedlone127/2025-01-26-babylm_jde_larger_10_en.md
new file mode 100644
index 00000000000000..48597507549c15
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-babylm_jde_larger_10_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English babylm_jde_larger_10 RoBertaEmbeddings from jdebene
+author: John Snow Labs
+name: babylm_jde_larger_10
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`babylm_jde_larger_10` is a English model originally trained by jdebene.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/babylm_jde_larger_10_en_5.5.1_3.0_1737907056309.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/babylm_jde_larger_10_en_5.5.1_3.0_1737907056309.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("babylm_jde_larger_10","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("babylm_jde_larger_10","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|babylm_jde_larger_10|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|310.5 MB|
+
+## References
+
+https://huggingface.co/jdebene/BabyLM-jde-larger-10
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-babylm_jde_larger_10_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-babylm_jde_larger_10_pipeline_en.md
new file mode 100644
index 00000000000000..d150a88fc5fb16
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-babylm_jde_larger_10_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English babylm_jde_larger_10_pipeline pipeline RoBertaEmbeddings from jdebene
+author: John Snow Labs
+name: babylm_jde_larger_10_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`babylm_jde_larger_10_pipeline` is a English model originally trained by jdebene.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/babylm_jde_larger_10_pipeline_en_5.5.1_3.0_1737907072660.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/babylm_jde_larger_10_pipeline_en_5.5.1_3.0_1737907072660.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("babylm_jde_larger_10_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("babylm_jde_larger_10_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|babylm_jde_larger_10_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|310.5 MB|
+
+## References
+
+https://huggingface.co/jdebene/BabyLM-jde-larger-10
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-babylm_roberta_base_epoch_20_en.md b/docs/_posts/ahmedlone127/2025-01-26-babylm_roberta_base_epoch_20_en.md
new file mode 100644
index 00000000000000..b7ba762de06c48
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-babylm_roberta_base_epoch_20_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English babylm_roberta_base_epoch_20 RoBertaEmbeddings from Raj-Sanjay-Shah
+author: John Snow Labs
+name: babylm_roberta_base_epoch_20
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`babylm_roberta_base_epoch_20` is a English model originally trained by Raj-Sanjay-Shah.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/babylm_roberta_base_epoch_20_en_5.5.1_3.0_1737906321754.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/babylm_roberta_base_epoch_20_en_5.5.1_3.0_1737906321754.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("babylm_roberta_base_epoch_20","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("babylm_roberta_base_epoch_20","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|babylm_roberta_base_epoch_20|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|465.7 MB|
+
+## References
+
+https://huggingface.co/Raj-Sanjay-Shah/babyLM_roberta_base_epoch_20
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-babylm_roberta_base_epoch_20_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-babylm_roberta_base_epoch_20_pipeline_en.md
new file mode 100644
index 00000000000000..ea47a3cc4fa39b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-babylm_roberta_base_epoch_20_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English babylm_roberta_base_epoch_20_pipeline pipeline RoBertaEmbeddings from Raj-Sanjay-Shah
+author: John Snow Labs
+name: babylm_roberta_base_epoch_20_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`babylm_roberta_base_epoch_20_pipeline` is a English model originally trained by Raj-Sanjay-Shah.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/babylm_roberta_base_epoch_20_pipeline_en_5.5.1_3.0_1737906345803.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/babylm_roberta_base_epoch_20_pipeline_en_5.5.1_3.0_1737906345803.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("babylm_roberta_base_epoch_20_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("babylm_roberta_base_epoch_20_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|babylm_roberta_base_epoch_20_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|465.7 MB|
+
+## References
+
+https://huggingface.co/Raj-Sanjay-Shah/babyLM_roberta_base_epoch_20
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bart_finetuned_keyphrase_extraction_en.md b/docs/_posts/ahmedlone127/2025-01-26-bart_finetuned_keyphrase_extraction_en.md
new file mode 100644
index 00000000000000..dfc16a00e72d89
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bart_finetuned_keyphrase_extraction_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bart_finetuned_keyphrase_extraction BartTransformer from aglazkova
+author: John Snow Labs
+name: bart_finetuned_keyphrase_extraction
+date: 2025-01-26
+tags: [en, open_source, onnx, text_generation, bart]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BartTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bart_finetuned_keyphrase_extraction` is a English model originally trained by aglazkova.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bart_finetuned_keyphrase_extraction_en_5.5.1_3.0_1737901800835.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bart_finetuned_keyphrase_extraction_en_5.5.1_3.0_1737901800835.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = BartTransformer.pretrained("bart_finetuned_keyphrase_extraction","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = BartTransformer.pretrained("bart_finetuned_keyphrase_extraction","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bart_finetuned_keyphrase_extraction|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|809.5 MB|
+
+## References
+
+https://huggingface.co/aglazkova/bart_finetuned_keyphrase_extraction
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bart_finetuned_keyphrase_extraction_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bart_finetuned_keyphrase_extraction_pipeline_en.md
new file mode 100644
index 00000000000000..bfee7da4c53951
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bart_finetuned_keyphrase_extraction_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bart_finetuned_keyphrase_extraction_pipeline pipeline BartTransformer from aglazkova
+author: John Snow Labs
+name: bart_finetuned_keyphrase_extraction_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bart_finetuned_keyphrase_extraction_pipeline` is a English model originally trained by aglazkova.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bart_finetuned_keyphrase_extraction_pipeline_en_5.5.1_3.0_1737901843247.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bart_finetuned_keyphrase_extraction_pipeline_en_5.5.1_3.0_1737901843247.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bart_finetuned_keyphrase_extraction_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bart_finetuned_keyphrase_extraction_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bart_finetuned_keyphrase_extraction_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|809.6 MB|
+
+## References
+
+https://huggingface.co/aglazkova/bart_finetuned_keyphrase_extraction
+
+## Included Models
+
+- DocumentAssembler
+- BartTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bart_large_cnn_facebook_en.md b/docs/_posts/ahmedlone127/2025-01-26-bart_large_cnn_facebook_en.md
new file mode 100644
index 00000000000000..204249b2826e88
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bart_large_cnn_facebook_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bart_large_cnn_facebook BartTransformer from facebook
+author: John Snow Labs
+name: bart_large_cnn_facebook
+date: 2025-01-26
+tags: [en, open_source, onnx, text_generation, bart]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BartTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bart_large_cnn_facebook` is a English model originally trained by facebook.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bart_large_cnn_facebook_en_5.5.1_3.0_1737924836062.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bart_large_cnn_facebook_en_5.5.1_3.0_1737924836062.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = BartTransformer.pretrained("bart_large_cnn_facebook","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = BartTransformer.pretrained("bart_large_cnn_facebook","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bart_large_cnn_facebook|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/facebook/bart-large-cnn
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bart_large_cnn_facebook_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bart_large_cnn_facebook_pipeline_en.md
new file mode 100644
index 00000000000000..2e4715bc0f32c5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bart_large_cnn_facebook_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bart_large_cnn_facebook_pipeline pipeline BartTransformer from facebook
+author: John Snow Labs
+name: bart_large_cnn_facebook_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bart_large_cnn_facebook_pipeline` is a English model originally trained by facebook.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bart_large_cnn_facebook_pipeline_en_5.5.1_3.0_1737925182182.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bart_large_cnn_facebook_pipeline_en_5.5.1_3.0_1737925182182.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bart_large_cnn_facebook_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bart_large_cnn_facebook_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bart_large_cnn_facebook_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/facebook/bart-large-cnn
+
+## Included Models
+
+- DocumentAssembler
+- BartTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bart_large_emojilm_en.md b/docs/_posts/ahmedlone127/2025-01-26-bart_large_emojilm_en.md
new file mode 100644
index 00000000000000..36d85f67375b1f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bart_large_emojilm_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bart_large_emojilm BartTransformer from KomeijiForce
+author: John Snow Labs
+name: bart_large_emojilm
+date: 2025-01-26
+tags: [en, open_source, onnx, text_generation, bart]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BartTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bart_large_emojilm` is a English model originally trained by KomeijiForce.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bart_large_emojilm_en_5.5.1_3.0_1737902339222.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bart_large_emojilm_en_5.5.1_3.0_1737902339222.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = BartTransformer.pretrained("bart_large_emojilm","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = BartTransformer.pretrained("bart_large_emojilm","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bart_large_emojilm|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.9 GB|
+
+## References
+
+https://huggingface.co/KomeijiForce/bart-large-emojilm
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bart_large_emojilm_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bart_large_emojilm_pipeline_en.md
new file mode 100644
index 00000000000000..5d3e6a0bc08924
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bart_large_emojilm_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bart_large_emojilm_pipeline pipeline BartTransformer from KomeijiForce
+author: John Snow Labs
+name: bart_large_emojilm_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bart_large_emojilm_pipeline` is a English model originally trained by KomeijiForce.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bart_large_emojilm_pipeline_en_5.5.1_3.0_1737902432047.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bart_large_emojilm_pipeline_en_5.5.1_3.0_1737902432047.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bart_large_emojilm_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bart_large_emojilm_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bart_large_emojilm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.9 GB|
+
+## References
+
+https://huggingface.co/KomeijiForce/bart-large-emojilm
+
+## Included Models
+
+- DocumentAssembler
+- BartTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-base_backbone_2_10_en.md b/docs/_posts/ahmedlone127/2025-01-26-base_backbone_2_10_en.md
new file mode 100644
index 00000000000000..19b9cece446145
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-base_backbone_2_10_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English base_backbone_2_10 XlmRoBertaForSequenceClassification from sreddy109
+author: John Snow Labs
+name: base_backbone_2_10
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`base_backbone_2_10` is a English model originally trained by sreddy109.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/base_backbone_2_10_en_5.5.1_3.0_1737879714788.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/base_backbone_2_10_en_5.5.1_3.0_1737879714788.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("base_backbone_2_10","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("base_backbone_2_10", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|base_backbone_2_10|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|994.1 MB|
+
+## References
+
+https://huggingface.co/sreddy109/base-backbone-2-10
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-base_backbone_2_10_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-base_backbone_2_10_pipeline_en.md
new file mode 100644
index 00000000000000..b5695334bc40ed
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-base_backbone_2_10_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English base_backbone_2_10_pipeline pipeline XlmRoBertaForSequenceClassification from sreddy109
+author: John Snow Labs
+name: base_backbone_2_10_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`base_backbone_2_10_pipeline` is a English model originally trained by sreddy109.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/base_backbone_2_10_pipeline_en_5.5.1_3.0_1737879768636.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/base_backbone_2_10_pipeline_en_5.5.1_3.0_1737879768636.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("base_backbone_2_10_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("base_backbone_2_10_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|base_backbone_2_10_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|994.1 MB|
+
+## References
+
+https://huggingface.co/sreddy109/base-backbone-2-10
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-base_full_v0_1000_en.md b/docs/_posts/ahmedlone127/2025-01-26-base_full_v0_1000_en.md
new file mode 100644
index 00000000000000..29acd110c783cf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-base_full_v0_1000_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English base_full_v0_1000 XlmRoBertaForSequenceClassification from sreddy109
+author: John Snow Labs
+name: base_full_v0_1000
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`base_full_v0_1000` is a English model originally trained by sreddy109.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/base_full_v0_1000_en_5.5.1_3.0_1737882723444.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/base_full_v0_1000_en_5.5.1_3.0_1737882723444.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("base_full_v0_1000","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("base_full_v0_1000", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|base_full_v0_1000|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|994.0 MB|
+
+## References
+
+https://huggingface.co/sreddy109/base-full-v0-1000
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-base_full_v0_1000_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-base_full_v0_1000_pipeline_en.md
new file mode 100644
index 00000000000000..d0ae375468a4ce
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-base_full_v0_1000_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English base_full_v0_1000_pipeline pipeline XlmRoBertaForSequenceClassification from sreddy109
+author: John Snow Labs
+name: base_full_v0_1000_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`base_full_v0_1000_pipeline` is a English model originally trained by sreddy109.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/base_full_v0_1000_pipeline_en_5.5.1_3.0_1737882777751.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/base_full_v0_1000_pipeline_en_5.5.1_3.0_1737882777751.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("base_full_v0_1000_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("base_full_v0_1000_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|base_full_v0_1000_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|994.0 MB|
+
+## References
+
+https://huggingface.co/sreddy109/base-full-v0-1000
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-base_full_v0_50_en.md b/docs/_posts/ahmedlone127/2025-01-26-base_full_v0_50_en.md
new file mode 100644
index 00000000000000..df234f7e3a81e8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-base_full_v0_50_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English base_full_v0_50 XlmRoBertaForSequenceClassification from sreddy109
+author: John Snow Labs
+name: base_full_v0_50
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`base_full_v0_50` is a English model originally trained by sreddy109.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/base_full_v0_50_en_5.5.1_3.0_1737879552888.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/base_full_v0_50_en_5.5.1_3.0_1737879552888.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("base_full_v0_50","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("base_full_v0_50", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|base_full_v0_50|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|994.0 MB|
+
+## References
+
+https://huggingface.co/sreddy109/base-full-v0-50
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-base_full_v0_50_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-base_full_v0_50_pipeline_en.md
new file mode 100644
index 00000000000000..e1b3504c897116
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-base_full_v0_50_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English base_full_v0_50_pipeline pipeline XlmRoBertaForSequenceClassification from sreddy109
+author: John Snow Labs
+name: base_full_v0_50_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`base_full_v0_50_pipeline` is a English model originally trained by sreddy109.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/base_full_v0_50_pipeline_en_5.5.1_3.0_1737879610438.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/base_full_v0_50_pipeline_en_5.5.1_3.0_1737879610438.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("base_full_v0_50_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("base_full_v0_50_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|base_full_v0_50_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|994.0 MB|
+
+## References
+
+https://huggingface.co/sreddy109/base-full-v0-50
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-based_trained_dilibert_sentiment_analysis_en.md b/docs/_posts/ahmedlone127/2025-01-26-based_trained_dilibert_sentiment_analysis_en.md
new file mode 100644
index 00000000000000..63dd8de1c53304
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-based_trained_dilibert_sentiment_analysis_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English based_trained_dilibert_sentiment_analysis DistilBertForSequenceClassification from dmo0798
+author: John Snow Labs
+name: based_trained_dilibert_sentiment_analysis
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`based_trained_dilibert_sentiment_analysis` is a English model originally trained by dmo0798.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/based_trained_dilibert_sentiment_analysis_en_5.5.1_3.0_1737905137394.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/based_trained_dilibert_sentiment_analysis_en_5.5.1_3.0_1737905137394.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("based_trained_dilibert_sentiment_analysis","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("based_trained_dilibert_sentiment_analysis", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|based_trained_dilibert_sentiment_analysis|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/dmo0798/based_trained_dilibert_sentiment_analysis
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-based_trained_dilibert_sentiment_analysis_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-based_trained_dilibert_sentiment_analysis_pipeline_en.md
new file mode 100644
index 00000000000000..c05528d8579ea7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-based_trained_dilibert_sentiment_analysis_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English based_trained_dilibert_sentiment_analysis_pipeline pipeline DistilBertForSequenceClassification from dmo0798
+author: John Snow Labs
+name: based_trained_dilibert_sentiment_analysis_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`based_trained_dilibert_sentiment_analysis_pipeline` is a English model originally trained by dmo0798.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/based_trained_dilibert_sentiment_analysis_pipeline_en_5.5.1_3.0_1737905150506.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/based_trained_dilibert_sentiment_analysis_pipeline_en_5.5.1_3.0_1737905150506.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("based_trained_dilibert_sentiment_analysis_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("based_trained_dilibert_sentiment_analysis_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|based_trained_dilibert_sentiment_analysis_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/dmo0798/based_trained_dilibert_sentiment_analysis
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-batch_size16_celeb_df_opencv_1fps_unaugmentation_en.md b/docs/_posts/ahmedlone127/2025-01-26-batch_size16_celeb_df_opencv_1fps_unaugmentation_en.md
new file mode 100644
index 00000000000000..6676731baae11a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-batch_size16_celeb_df_opencv_1fps_unaugmentation_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English batch_size16_celeb_df_opencv_1fps_unaugmentation SwinForImageClassification from hchcsuim
+author: John Snow Labs
+name: batch_size16_celeb_df_opencv_1fps_unaugmentation
+date: 2025-01-26
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`batch_size16_celeb_df_opencv_1fps_unaugmentation` is a English model originally trained by hchcsuim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/batch_size16_celeb_df_opencv_1fps_unaugmentation_en_5.5.1_3.0_1737888718557.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/batch_size16_celeb_df_opencv_1fps_unaugmentation_en_5.5.1_3.0_1737888718557.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""batch_size16_celeb_df_opencv_1fps_unaugmentation","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("batch_size16_celeb_df_opencv_1fps_unaugmentation","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|batch_size16_celeb_df_opencv_1fps_unaugmentation|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/hchcsuim/batch-size16_Celeb-DF_opencv-1FPS_unaugmentation
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-batch_size16_celeb_df_opencv_1fps_unaugmentation_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-batch_size16_celeb_df_opencv_1fps_unaugmentation_pipeline_en.md
new file mode 100644
index 00000000000000..b71df7a5477856
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-batch_size16_celeb_df_opencv_1fps_unaugmentation_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English batch_size16_celeb_df_opencv_1fps_unaugmentation_pipeline pipeline SwinForImageClassification from hchcsuim
+author: John Snow Labs
+name: batch_size16_celeb_df_opencv_1fps_unaugmentation_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`batch_size16_celeb_df_opencv_1fps_unaugmentation_pipeline` is a English model originally trained by hchcsuim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/batch_size16_celeb_df_opencv_1fps_unaugmentation_pipeline_en_5.5.1_3.0_1737888729371.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/batch_size16_celeb_df_opencv_1fps_unaugmentation_pipeline_en_5.5.1_3.0_1737888729371.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("batch_size16_celeb_df_opencv_1fps_unaugmentation_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("batch_size16_celeb_df_opencv_1fps_unaugmentation_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|batch_size16_celeb_df_opencv_1fps_unaugmentation_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/hchcsuim/batch-size16_Celeb-DF_opencv-1FPS_unaugmentation
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-batch_size16_ffpp_c23_ffmpeg_1fps_qv1_unaugmentation_en.md b/docs/_posts/ahmedlone127/2025-01-26-batch_size16_ffpp_c23_ffmpeg_1fps_qv1_unaugmentation_en.md
new file mode 100644
index 00000000000000..03720f168cae81
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-batch_size16_ffpp_c23_ffmpeg_1fps_qv1_unaugmentation_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English batch_size16_ffpp_c23_ffmpeg_1fps_qv1_unaugmentation SwinForImageClassification from hchcsuim
+author: John Snow Labs
+name: batch_size16_ffpp_c23_ffmpeg_1fps_qv1_unaugmentation
+date: 2025-01-26
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`batch_size16_ffpp_c23_ffmpeg_1fps_qv1_unaugmentation` is a English model originally trained by hchcsuim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/batch_size16_ffpp_c23_ffmpeg_1fps_qv1_unaugmentation_en_5.5.1_3.0_1737889122279.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/batch_size16_ffpp_c23_ffmpeg_1fps_qv1_unaugmentation_en_5.5.1_3.0_1737889122279.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""batch_size16_ffpp_c23_ffmpeg_1fps_qv1_unaugmentation","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("batch_size16_ffpp_c23_ffmpeg_1fps_qv1_unaugmentation","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|batch_size16_ffpp_c23_ffmpeg_1fps_qv1_unaugmentation|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/hchcsuim/batch-size16_FFPP-c23_ffmpeg-1FPS-qv1_unaugmentation
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-batch_size16_ffpp_c23_ffmpeg_1fps_qv1_unaugmentation_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-batch_size16_ffpp_c23_ffmpeg_1fps_qv1_unaugmentation_pipeline_en.md
new file mode 100644
index 00000000000000..f24f517a10d0e4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-batch_size16_ffpp_c23_ffmpeg_1fps_qv1_unaugmentation_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English batch_size16_ffpp_c23_ffmpeg_1fps_qv1_unaugmentation_pipeline pipeline SwinForImageClassification from hchcsuim
+author: John Snow Labs
+name: batch_size16_ffpp_c23_ffmpeg_1fps_qv1_unaugmentation_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`batch_size16_ffpp_c23_ffmpeg_1fps_qv1_unaugmentation_pipeline` is a English model originally trained by hchcsuim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/batch_size16_ffpp_c23_ffmpeg_1fps_qv1_unaugmentation_pipeline_en_5.5.1_3.0_1737889137814.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/batch_size16_ffpp_c23_ffmpeg_1fps_qv1_unaugmentation_pipeline_en_5.5.1_3.0_1737889137814.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("batch_size16_ffpp_c23_ffmpeg_1fps_qv1_unaugmentation_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("batch_size16_ffpp_c23_ffmpeg_1fps_qv1_unaugmentation_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|batch_size16_ffpp_c23_ffmpeg_1fps_qv1_unaugmentation_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/hchcsuim/batch-size16_FFPP-c23_ffmpeg-1FPS-qv1_unaugmentation
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-batch_size16_ffpp_c23_ffmpeg_1fps_qv31_unaugmentation_en.md b/docs/_posts/ahmedlone127/2025-01-26-batch_size16_ffpp_c23_ffmpeg_1fps_qv31_unaugmentation_en.md
new file mode 100644
index 00000000000000..a3b807ec8f8e82
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-batch_size16_ffpp_c23_ffmpeg_1fps_qv31_unaugmentation_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English batch_size16_ffpp_c23_ffmpeg_1fps_qv31_unaugmentation SwinForImageClassification from hchcsuim
+author: John Snow Labs
+name: batch_size16_ffpp_c23_ffmpeg_1fps_qv31_unaugmentation
+date: 2025-01-26
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`batch_size16_ffpp_c23_ffmpeg_1fps_qv31_unaugmentation` is a English model originally trained by hchcsuim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/batch_size16_ffpp_c23_ffmpeg_1fps_qv31_unaugmentation_en_5.5.1_3.0_1737889203430.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/batch_size16_ffpp_c23_ffmpeg_1fps_qv31_unaugmentation_en_5.5.1_3.0_1737889203430.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""batch_size16_ffpp_c23_ffmpeg_1fps_qv31_unaugmentation","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("batch_size16_ffpp_c23_ffmpeg_1fps_qv31_unaugmentation","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|batch_size16_ffpp_c23_ffmpeg_1fps_qv31_unaugmentation|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/hchcsuim/batch-size16_FFPP-c23_ffmpeg-1FPS-qv31_unaugmentation
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-batch_size16_ffpp_c23_ffmpeg_1fps_qv31_unaugmentation_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-batch_size16_ffpp_c23_ffmpeg_1fps_qv31_unaugmentation_pipeline_en.md
new file mode 100644
index 00000000000000..5a2b33c11e3629
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-batch_size16_ffpp_c23_ffmpeg_1fps_qv31_unaugmentation_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English batch_size16_ffpp_c23_ffmpeg_1fps_qv31_unaugmentation_pipeline pipeline SwinForImageClassification from hchcsuim
+author: John Snow Labs
+name: batch_size16_ffpp_c23_ffmpeg_1fps_qv31_unaugmentation_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`batch_size16_ffpp_c23_ffmpeg_1fps_qv31_unaugmentation_pipeline` is a English model originally trained by hchcsuim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/batch_size16_ffpp_c23_ffmpeg_1fps_qv31_unaugmentation_pipeline_en_5.5.1_3.0_1737889215186.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/batch_size16_ffpp_c23_ffmpeg_1fps_qv31_unaugmentation_pipeline_en_5.5.1_3.0_1737889215186.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("batch_size16_ffpp_c23_ffmpeg_1fps_qv31_unaugmentation_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("batch_size16_ffpp_c23_ffmpeg_1fps_qv31_unaugmentation_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|batch_size16_ffpp_c23_ffmpeg_1fps_qv31_unaugmentation_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/hchcsuim/batch-size16_FFPP-c23_ffmpeg-1FPS-qv31_unaugmentation
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_adaptation_martin_fierro_caraboy_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_adaptation_martin_fierro_caraboy_en.md
new file mode 100644
index 00000000000000..35de8a44f2b610
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_adaptation_martin_fierro_caraboy_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_adaptation_martin_fierro_caraboy BertEmbeddings from caraboy
+author: John Snow Labs
+name: bert_adaptation_martin_fierro_caraboy
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_martin_fierro_caraboy` is a English model originally trained by caraboy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_martin_fierro_caraboy_en_5.5.1_3.0_1737861540105.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_martin_fierro_caraboy_en_5.5.1_3.0_1737861540105.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_adaptation_martin_fierro_caraboy","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_adaptation_martin_fierro_caraboy","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_martin_fierro_caraboy|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/caraboy/bert_adaptation_martin_fierro
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_adaptation_martin_fierro_caraboy_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_adaptation_martin_fierro_caraboy_pipeline_en.md
new file mode 100644
index 00000000000000..84783a510dd263
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_adaptation_martin_fierro_caraboy_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_adaptation_martin_fierro_caraboy_pipeline pipeline BertEmbeddings from caraboy
+author: John Snow Labs
+name: bert_adaptation_martin_fierro_caraboy_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_martin_fierro_caraboy_pipeline` is a English model originally trained by caraboy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_martin_fierro_caraboy_pipeline_en_5.5.1_3.0_1737861565236.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_martin_fierro_caraboy_pipeline_en_5.5.1_3.0_1737861565236.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_adaptation_martin_fierro_caraboy_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_adaptation_martin_fierro_caraboy_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_martin_fierro_caraboy_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/caraboy/bert_adaptation_martin_fierro
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_adaptation_peppa_pig_eugeniahaluszka_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_adaptation_peppa_pig_eugeniahaluszka_en.md
new file mode 100644
index 00000000000000..dc1d3f51ce5853
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_adaptation_peppa_pig_eugeniahaluszka_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_adaptation_peppa_pig_eugeniahaluszka BertEmbeddings from eugeniahaluszka
+author: John Snow Labs
+name: bert_adaptation_peppa_pig_eugeniahaluszka
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_peppa_pig_eugeniahaluszka` is a English model originally trained by eugeniahaluszka.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_peppa_pig_eugeniahaluszka_en_5.5.1_3.0_1737890899698.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_peppa_pig_eugeniahaluszka_en_5.5.1_3.0_1737890899698.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_adaptation_peppa_pig_eugeniahaluszka","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_adaptation_peppa_pig_eugeniahaluszka","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_peppa_pig_eugeniahaluszka|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/eugeniahaluszka/bert_adaptation_peppa_pig
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_adaptation_peppa_pig_eugeniahaluszka_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_adaptation_peppa_pig_eugeniahaluszka_pipeline_en.md
new file mode 100644
index 00000000000000..a9675463b584ca
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_adaptation_peppa_pig_eugeniahaluszka_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_adaptation_peppa_pig_eugeniahaluszka_pipeline pipeline BertEmbeddings from eugeniahaluszka
+author: John Snow Labs
+name: bert_adaptation_peppa_pig_eugeniahaluszka_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_peppa_pig_eugeniahaluszka_pipeline` is a English model originally trained by eugeniahaluszka.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_peppa_pig_eugeniahaluszka_pipeline_en_5.5.1_3.0_1737890920756.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_peppa_pig_eugeniahaluszka_pipeline_en_5.5.1_3.0_1737890920756.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_adaptation_peppa_pig_eugeniahaluszka_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_adaptation_peppa_pig_eugeniahaluszka_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_peppa_pig_eugeniahaluszka_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/eugeniahaluszka/bert_adaptation_peppa_pig
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_adaptation_peppa_pig_federidos_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_adaptation_peppa_pig_federidos_en.md
new file mode 100644
index 00000000000000..b1d1cda310fad5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_adaptation_peppa_pig_federidos_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_adaptation_peppa_pig_federidos BertEmbeddings from federidos
+author: John Snow Labs
+name: bert_adaptation_peppa_pig_federidos
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_peppa_pig_federidos` is a English model originally trained by federidos.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_peppa_pig_federidos_en_5.5.1_3.0_1737861898766.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_peppa_pig_federidos_en_5.5.1_3.0_1737861898766.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_adaptation_peppa_pig_federidos","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_adaptation_peppa_pig_federidos","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_peppa_pig_federidos|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/federidos/bert_adaptation_peppa_pig
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_adaptation_peppa_pig_federidos_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_adaptation_peppa_pig_federidos_pipeline_en.md
new file mode 100644
index 00000000000000..1d52077deb4bbf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_adaptation_peppa_pig_federidos_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_adaptation_peppa_pig_federidos_pipeline pipeline BertEmbeddings from federidos
+author: John Snow Labs
+name: bert_adaptation_peppa_pig_federidos_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_peppa_pig_federidos_pipeline` is a English model originally trained by federidos.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_peppa_pig_federidos_pipeline_en_5.5.1_3.0_1737861924421.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_peppa_pig_federidos_pipeline_en_5.5.1_3.0_1737861924421.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_adaptation_peppa_pig_federidos_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_adaptation_peppa_pig_federidos_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_peppa_pig_federidos_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/federidos/bert_adaptation_peppa_pig
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_adaptation_peppa_pig_hdrobins_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_adaptation_peppa_pig_hdrobins_en.md
new file mode 100644
index 00000000000000..033b937d1e9b1f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_adaptation_peppa_pig_hdrobins_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_adaptation_peppa_pig_hdrobins BertEmbeddings from hdrobins
+author: John Snow Labs
+name: bert_adaptation_peppa_pig_hdrobins
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_peppa_pig_hdrobins` is a English model originally trained by hdrobins.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_peppa_pig_hdrobins_en_5.5.1_3.0_1737861254466.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_peppa_pig_hdrobins_en_5.5.1_3.0_1737861254466.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_adaptation_peppa_pig_hdrobins","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_adaptation_peppa_pig_hdrobins","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_peppa_pig_hdrobins|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/hdrobins/bert_adaptation_peppa_pig
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_adaptation_peppa_pig_hdrobins_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_adaptation_peppa_pig_hdrobins_pipeline_en.md
new file mode 100644
index 00000000000000..d2900edb2b4455
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_adaptation_peppa_pig_hdrobins_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_adaptation_peppa_pig_hdrobins_pipeline pipeline BertEmbeddings from hdrobins
+author: John Snow Labs
+name: bert_adaptation_peppa_pig_hdrobins_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_peppa_pig_hdrobins_pipeline` is a English model originally trained by hdrobins.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_peppa_pig_hdrobins_pipeline_en_5.5.1_3.0_1737861275662.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_peppa_pig_hdrobins_pipeline_en_5.5.1_3.0_1737861275662.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_adaptation_peppa_pig_hdrobins_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_adaptation_peppa_pig_hdrobins_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_peppa_pig_hdrobins_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/hdrobins/bert_adaptation_peppa_pig
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_adaptation_peppa_pig_maximilianoeze_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_adaptation_peppa_pig_maximilianoeze_en.md
new file mode 100644
index 00000000000000..bafbefad77cbdd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_adaptation_peppa_pig_maximilianoeze_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_adaptation_peppa_pig_maximilianoeze BertEmbeddings from Maximilianoeze
+author: John Snow Labs
+name: bert_adaptation_peppa_pig_maximilianoeze
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_peppa_pig_maximilianoeze` is a English model originally trained by Maximilianoeze.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_peppa_pig_maximilianoeze_en_5.5.1_3.0_1737890852962.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_peppa_pig_maximilianoeze_en_5.5.1_3.0_1737890852962.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_adaptation_peppa_pig_maximilianoeze","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_adaptation_peppa_pig_maximilianoeze","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_peppa_pig_maximilianoeze|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/Maximilianoeze/bert_adaptation_peppa_pig
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_adaptation_peppa_pig_maximilianoeze_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_adaptation_peppa_pig_maximilianoeze_pipeline_en.md
new file mode 100644
index 00000000000000..1681108f8740e1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_adaptation_peppa_pig_maximilianoeze_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_adaptation_peppa_pig_maximilianoeze_pipeline pipeline BertEmbeddings from Maximilianoeze
+author: John Snow Labs
+name: bert_adaptation_peppa_pig_maximilianoeze_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_peppa_pig_maximilianoeze_pipeline` is a English model originally trained by Maximilianoeze.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_peppa_pig_maximilianoeze_pipeline_en_5.5.1_3.0_1737890875052.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_peppa_pig_maximilianoeze_pipeline_en_5.5.1_3.0_1737890875052.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_adaptation_peppa_pig_maximilianoeze_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_adaptation_peppa_pig_maximilianoeze_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_peppa_pig_maximilianoeze_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/Maximilianoeze/bert_adaptation_peppa_pig
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_amh_telegram_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_amh_telegram_en.md
new file mode 100644
index 00000000000000..74fcc77e86d506
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_amh_telegram_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_amh_telegram BertForTokenClassification from Naod-Demissie
+author: John Snow Labs
+name: bert_amh_telegram
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_amh_telegram` is a English model originally trained by Naod-Demissie.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_amh_telegram_en_5.5.1_3.0_1737933828889.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_amh_telegram_en_5.5.1_3.0_1737933828889.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_amh_telegram","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_amh_telegram", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_amh_telegram|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.8 MB|
+
+## References
+
+https://huggingface.co/Naod-Demissie/bert-amh-telegram
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_amh_telegram_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_amh_telegram_pipeline_en.md
new file mode 100644
index 00000000000000..248ef057b8ee35
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_amh_telegram_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_amh_telegram_pipeline pipeline BertForTokenClassification from Naod-Demissie
+author: John Snow Labs
+name: bert_amh_telegram_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_amh_telegram_pipeline` is a English model originally trained by Naod-Demissie.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_amh_telegram_pipeline_en_5.5.1_3.0_1737933850032.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_amh_telegram_pipeline_en_5.5.1_3.0_1737933850032.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_amh_telegram_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_amh_telegram_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_amh_telegram_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.8 MB|
+
+## References
+
+https://huggingface.co/Naod-Demissie/bert-amh-telegram
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_base_cased_finetuned_ner_dfki_slt_few_nerd_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_base_cased_finetuned_ner_dfki_slt_few_nerd_en.md
new file mode 100644
index 00000000000000..698d208e90a633
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_base_cased_finetuned_ner_dfki_slt_few_nerd_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_cased_finetuned_ner_dfki_slt_few_nerd BertForTokenClassification from DunnBC22
+author: John Snow Labs
+name: bert_base_cased_finetuned_ner_dfki_slt_few_nerd
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_finetuned_ner_dfki_slt_few_nerd` is a English model originally trained by DunnBC22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_finetuned_ner_dfki_slt_few_nerd_en_5.5.1_3.0_1737933910289.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_finetuned_ner_dfki_slt_few_nerd_en_5.5.1_3.0_1737933910289.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_base_cased_finetuned_ner_dfki_slt_few_nerd","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_base_cased_finetuned_ner_dfki_slt_few_nerd", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_cased_finetuned_ner_dfki_slt_few_nerd|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/DunnBC22/bert-base-cased-finetuned-ner-DFKI-SLT_few-NERd
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_base_cased_finetuned_ner_dfki_slt_few_nerd_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_base_cased_finetuned_ner_dfki_slt_few_nerd_pipeline_en.md
new file mode 100644
index 00000000000000..8c5a4e40184e59
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_base_cased_finetuned_ner_dfki_slt_few_nerd_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_cased_finetuned_ner_dfki_slt_few_nerd_pipeline pipeline BertForTokenClassification from DunnBC22
+author: John Snow Labs
+name: bert_base_cased_finetuned_ner_dfki_slt_few_nerd_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_finetuned_ner_dfki_slt_few_nerd_pipeline` is a English model originally trained by DunnBC22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_finetuned_ner_dfki_slt_few_nerd_pipeline_en_5.5.1_3.0_1737933932039.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_finetuned_ner_dfki_slt_few_nerd_pipeline_en_5.5.1_3.0_1737933932039.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_cased_finetuned_ner_dfki_slt_few_nerd_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_cased_finetuned_ner_dfki_slt_few_nerd_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_cased_finetuned_ner_dfki_slt_few_nerd_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/DunnBC22/bert-base-cased-finetuned-ner-DFKI-SLT_few-NERd
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_base_cased_marasaki_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_base_cased_marasaki_en.md
new file mode 100644
index 00000000000000..da77035f9e1617
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_base_cased_marasaki_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_cased_marasaki BertEmbeddings from marasaki
+author: John Snow Labs
+name: bert_base_cased_marasaki
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_marasaki` is a English model originally trained by marasaki.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_marasaki_en_5.5.1_3.0_1737861676871.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_marasaki_en_5.5.1_3.0_1737861676871.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_base_cased_marasaki","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_base_cased_marasaki","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_cased_marasaki|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/marasaki/bert_base_cased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_base_cased_marasaki_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_base_cased_marasaki_pipeline_en.md
new file mode 100644
index 00000000000000..f30b08be64feaa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_base_cased_marasaki_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_cased_marasaki_pipeline pipeline BertEmbeddings from marasaki
+author: John Snow Labs
+name: bert_base_cased_marasaki_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_marasaki_pipeline` is a English model originally trained by marasaki.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_marasaki_pipeline_en_5.5.1_3.0_1737861699411.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_marasaki_pipeline_en_5.5.1_3.0_1737861699411.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_cased_marasaki_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_cased_marasaki_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_cased_marasaki_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/marasaki/bert_base_cased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_base_cased_structurized_squad_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_base_cased_structurized_squad_en.md
new file mode 100644
index 00000000000000..2be795dc6c4093
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_base_cased_structurized_squad_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_cased_structurized_squad BertForQuestionAnswering from martineden
+author: John Snow Labs
+name: bert_base_cased_structurized_squad
+date: 2025-01-26
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_structurized_squad` is a English model originally trained by martineden.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_structurized_squad_en_5.5.1_3.0_1737919348936.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_structurized_squad_en_5.5.1_3.0_1737919348936.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_cased_structurized_squad","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_cased_structurized_squad", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_cased_structurized_squad|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/martineden/bert-base-cased-structurized-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_base_cased_structurized_squad_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_base_cased_structurized_squad_pipeline_en.md
new file mode 100644
index 00000000000000..cd3f8e39e57143
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_base_cased_structurized_squad_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_cased_structurized_squad_pipeline pipeline BertForQuestionAnswering from martineden
+author: John Snow Labs
+name: bert_base_cased_structurized_squad_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_structurized_squad_pipeline` is a English model originally trained by martineden.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_structurized_squad_pipeline_en_5.5.1_3.0_1737919369768.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_structurized_squad_pipeline_en_5.5.1_3.0_1737919369768.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_cased_structurized_squad_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_cased_structurized_squad_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_cased_structurized_squad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/martineden/bert-base-cased-structurized-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_ep_1_0_b_8_lr_4e_07_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_100_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_ep_1_0_b_8_lr_4e_07_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_100_en.md
new file mode 100644
index 00000000000000..9b40f4aa8e9704
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_ep_1_0_b_8_lr_4e_07_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_100_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_ep_1_0_b_8_lr_4e_07_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_100 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_1_0_b_8_lr_4e_07_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_100
+date: 2025-01-26
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_1_0_b_8_lr_4e_07_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_100` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_0_b_8_lr_4e_07_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_100_en_5.5.1_3.0_1737919254942.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_0_b_8_lr_4e_07_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_100_en_5.5.1_3.0_1737919254942.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_1_0_b_8_lr_4e_07_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_100","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_1_0_b_8_lr_4e_07_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_100", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_1_0_b_8_lr_4e_07_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_100|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-1.0-b-8-lr-4e-07-dp-1.0-ss-0-st-False-fh-False-hs-100
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_ep_1_0_b_8_lr_4e_07_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_100_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_ep_1_0_b_8_lr_4e_07_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_100_pipeline_en.md
new file mode 100644
index 00000000000000..f0cf75562ae001
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_ep_1_0_b_8_lr_4e_07_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_100_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_ep_1_0_b_8_lr_4e_07_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_100_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_1_0_b_8_lr_4e_07_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_100_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_1_0_b_8_lr_4e_07_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_100_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_0_b_8_lr_4e_07_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_100_pipeline_en_5.5.1_3.0_1737919275506.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_0_b_8_lr_4e_07_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_100_pipeline_en_5.5.1_3.0_1737919275506.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_ep_1_0_b_8_lr_4e_07_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_100_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_ep_1_0_b_8_lr_4e_07_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_100_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_1_0_b_8_lr_4e_07_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_100_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-1.0-b-8-lr-4e-07-dp-1.0-ss-0-st-False-fh-False-hs-100
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_ep_1_45_b_32_lr_4e_07_dp_1_0_swati_300_southern_sotho_false_fh_true_hs_0_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_ep_1_45_b_32_lr_4e_07_dp_1_0_swati_300_southern_sotho_false_fh_true_hs_0_en.md
new file mode 100644
index 00000000000000..5f30bf40014f14
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_ep_1_45_b_32_lr_4e_07_dp_1_0_swati_300_southern_sotho_false_fh_true_hs_0_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_ep_1_45_b_32_lr_4e_07_dp_1_0_swati_300_southern_sotho_false_fh_true_hs_0 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_1_45_b_32_lr_4e_07_dp_1_0_swati_300_southern_sotho_false_fh_true_hs_0
+date: 2025-01-26
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_1_45_b_32_lr_4e_07_dp_1_0_swati_300_southern_sotho_false_fh_true_hs_0` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_45_b_32_lr_4e_07_dp_1_0_swati_300_southern_sotho_false_fh_true_hs_0_en_5.5.1_3.0_1737918514157.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_45_b_32_lr_4e_07_dp_1_0_swati_300_southern_sotho_false_fh_true_hs_0_en_5.5.1_3.0_1737918514157.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_1_45_b_32_lr_4e_07_dp_1_0_swati_300_southern_sotho_false_fh_true_hs_0","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_1_45_b_32_lr_4e_07_dp_1_0_swati_300_southern_sotho_false_fh_true_hs_0", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_1_45_b_32_lr_4e_07_dp_1_0_swati_300_southern_sotho_false_fh_true_hs_0|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-1.45-b-32-lr-4e-07-dp-1.0-ss-300-st-False-fh-True-hs-0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_ep_1_45_b_32_lr_4e_07_dp_1_0_swati_300_southern_sotho_false_fh_true_hs_0_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_ep_1_45_b_32_lr_4e_07_dp_1_0_swati_300_southern_sotho_false_fh_true_hs_0_pipeline_en.md
new file mode 100644
index 00000000000000..b952c1fe48f119
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_ep_1_45_b_32_lr_4e_07_dp_1_0_swati_300_southern_sotho_false_fh_true_hs_0_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_ep_1_45_b_32_lr_4e_07_dp_1_0_swati_300_southern_sotho_false_fh_true_hs_0_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_1_45_b_32_lr_4e_07_dp_1_0_swati_300_southern_sotho_false_fh_true_hs_0_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_1_45_b_32_lr_4e_07_dp_1_0_swati_300_southern_sotho_false_fh_true_hs_0_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_45_b_32_lr_4e_07_dp_1_0_swati_300_southern_sotho_false_fh_true_hs_0_pipeline_en_5.5.1_3.0_1737918537468.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_1_45_b_32_lr_4e_07_dp_1_0_swati_300_southern_sotho_false_fh_true_hs_0_pipeline_en_5.5.1_3.0_1737918537468.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_ep_1_45_b_32_lr_4e_07_dp_1_0_swati_300_southern_sotho_false_fh_true_hs_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_ep_1_45_b_32_lr_4e_07_dp_1_0_swati_300_southern_sotho_false_fh_true_hs_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_1_45_b_32_lr_4e_07_dp_1_0_swati_300_southern_sotho_false_fh_true_hs_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-1.45-b-32-lr-4e-07-dp-1.0-ss-300-st-False-fh-True-hs-0
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_fillmask_cve_cpe_20240322_152719_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_fillmask_cve_cpe_20240322_152719_en.md
new file mode 100644
index 00000000000000..298e4a39f4df01
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_fillmask_cve_cpe_20240322_152719_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_uncased_fillmask_cve_cpe_20240322_152719 BertEmbeddings from eknroki
+author: John Snow Labs
+name: bert_base_uncased_fillmask_cve_cpe_20240322_152719
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_fillmask_cve_cpe_20240322_152719` is a English model originally trained by eknroki.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_fillmask_cve_cpe_20240322_152719_en_5.5.1_3.0_1737890697458.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_fillmask_cve_cpe_20240322_152719_en_5.5.1_3.0_1737890697458.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_base_uncased_fillmask_cve_cpe_20240322_152719","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_base_uncased_fillmask_cve_cpe_20240322_152719","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_fillmask_cve_cpe_20240322_152719|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|428.7 MB|
+
+## References
+
+https://huggingface.co/eknroki/bert-base-uncased-fillmask-cve-cpe-20240322-152719
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_fillmask_cve_cpe_20240322_152719_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_fillmask_cve_cpe_20240322_152719_pipeline_en.md
new file mode 100644
index 00000000000000..9f3229abc63e64
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_fillmask_cve_cpe_20240322_152719_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_uncased_fillmask_cve_cpe_20240322_152719_pipeline pipeline BertEmbeddings from eknroki
+author: John Snow Labs
+name: bert_base_uncased_fillmask_cve_cpe_20240322_152719_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_fillmask_cve_cpe_20240322_152719_pipeline` is a English model originally trained by eknroki.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_fillmask_cve_cpe_20240322_152719_pipeline_en_5.5.1_3.0_1737890719829.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_fillmask_cve_cpe_20240322_152719_pipeline_en_5.5.1_3.0_1737890719829.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_fillmask_cve_cpe_20240322_152719_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_fillmask_cve_cpe_20240322_152719_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_fillmask_cve_cpe_20240322_152719_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|428.7 MB|
+
+## References
+
+https://huggingface.co/eknroki/bert-base-uncased-fillmask-cve-cpe-20240322-152719
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_900_southern_sotho_false_fh_true_hs_666_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_900_southern_sotho_false_fh_true_hs_666_en.md
new file mode 100644
index 00000000000000..2fc7d04b897f39
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_900_southern_sotho_false_fh_true_hs_666_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_900_southern_sotho_false_fh_true_hs_666 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_900_southern_sotho_false_fh_true_hs_666
+date: 2025-01-26
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_900_southern_sotho_false_fh_true_hs_666` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_900_southern_sotho_false_fh_true_hs_666_en_5.5.1_3.0_1737919050270.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_900_southern_sotho_false_fh_true_hs_666_en_5.5.1_3.0_1737919050270.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_900_southern_sotho_false_fh_true_hs_666","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_900_southern_sotho_false_fh_true_hs_666", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_900_southern_sotho_false_fh_true_hs_666|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.0-lr-1e-05-wd-0.001-dp-0.2-ss-900-st-False-fh-True-hs-666
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_900_southern_sotho_false_fh_true_hs_666_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_900_southern_sotho_false_fh_true_hs_666_pipeline_en.md
new file mode 100644
index 00000000000000..5219fbbb56655b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_900_southern_sotho_false_fh_true_hs_666_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_900_southern_sotho_false_fh_true_hs_666_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_900_southern_sotho_false_fh_true_hs_666_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_900_southern_sotho_false_fh_true_hs_666_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_900_southern_sotho_false_fh_true_hs_666_pipeline_en_5.5.1_3.0_1737919071042.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_900_southern_sotho_false_fh_true_hs_666_pipeline_en_5.5.1_3.0_1737919071042.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_900_southern_sotho_false_fh_true_hs_666_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_900_southern_sotho_false_fh_true_hs_666_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_0_lr_1e_05_wd_0_001_dp_0_2_swati_900_southern_sotho_false_fh_true_hs_666_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.0-lr-1e-05-wd-0.001-dp-0.2-ss-900-st-False-fh-True-hs-666
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500_en.md
new file mode 100644
index 00000000000000..a37db4396c20e5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500
+date: 2025-01-26
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500_en_5.5.1_3.0_1737918629431.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500_en_5.5.1_3.0_1737918629431.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.0-lr-1e-06-wd-0.001-dp-0.2-ss-0-st-False-fh-False-hs-500
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500_pipeline_en.md
new file mode 100644
index 00000000000000..d632c3d48d80db
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500_pipeline_en_5.5.1_3.0_1737918650804.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500_pipeline_en_5.5.1_3.0_1737918650804.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_500_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.0-lr-1e-06-wd-0.001-dp-0.2-ss-0-st-False-fh-False-hs-500
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_900_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_900_en.md
new file mode 100644
index 00000000000000..fc32c35f0d523d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_900_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_900 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_900
+date: 2025-01-26
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_900` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_900_en_5.5.1_3.0_1737918539380.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_900_en_5.5.1_3.0_1737918539380.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_900","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_900", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_900|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.0-lr-1e-06-wd-0.001-dp-0.2-ss-0-st-False-fh-False-hs-900
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_900_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_900_pipeline_en.md
new file mode 100644
index 00000000000000..b110beb94e74a3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_900_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_900_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_900_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_900_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_900_pipeline_en_5.5.1_3.0_1737918562847.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_900_pipeline_en_5.5.1_3.0_1737918562847.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_900_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_900_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_900_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.0-lr-1e-06-wd-0.001-dp-0.2-ss-0-st-False-fh-False-hs-900
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_2_0_lr_0_0001_wd_0_001_dp_0_8_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_2_0_lr_0_0001_wd_0_001_dp_0_8_en.md
new file mode 100644
index 00000000000000..65b4a27a8fc76d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_2_0_lr_0_0001_wd_0_001_dp_0_8_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_2_0_lr_0_0001_wd_0_001_dp_0_8 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_2_0_lr_0_0001_wd_0_001_dp_0_8
+date: 2025-01-26
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_2_0_lr_0_0001_wd_0_001_dp_0_8` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_0_0001_wd_0_001_dp_0_8_en_5.5.1_3.0_1737919681771.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_0_0001_wd_0_001_dp_0_8_en_5.5.1_3.0_1737919681771.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_2_0_lr_0_0001_wd_0_001_dp_0_8","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_2_0_lr_0_0001_wd_0_001_dp_0_8", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_2_0_lr_0_0001_wd_0_001_dp_0_8|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-2.0-lr-0.0001-wd-0.001-dp-0.8
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_2_0_lr_0_0001_wd_0_001_dp_0_8_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_2_0_lr_0_0001_wd_0_001_dp_0_8_pipeline_en.md
new file mode 100644
index 00000000000000..341eeeef224fb5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_2_0_lr_0_0001_wd_0_001_dp_0_8_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_2_0_lr_0_0001_wd_0_001_dp_0_8_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_2_0_lr_0_0001_wd_0_001_dp_0_8_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_2_0_lr_0_0001_wd_0_001_dp_0_8_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_0_0001_wd_0_001_dp_0_8_pipeline_en_5.5.1_3.0_1737919702646.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_0_0001_wd_0_001_dp_0_8_pipeline_en_5.5.1_3.0_1737919702646.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_2_0_lr_0_0001_wd_0_001_dp_0_8_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_2_0_lr_0_0001_wd_0_001_dp_0_8_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_2_0_lr_0_0001_wd_0_001_dp_0_8_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-2.0-lr-0.0001-wd-0.001-dp-0.8
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_2_0_lr_2e_06_wd_0_001_dp_0_999_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_2_0_lr_2e_06_wd_0_001_dp_0_999_en.md
new file mode 100644
index 00000000000000..8bd1c07e17c924
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_2_0_lr_2e_06_wd_0_001_dp_0_999_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_2_0_lr_2e_06_wd_0_001_dp_0_999 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_2_0_lr_2e_06_wd_0_001_dp_0_999
+date: 2025-01-26
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_2_0_lr_2e_06_wd_0_001_dp_0_999` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_2e_06_wd_0_001_dp_0_999_en_5.5.1_3.0_1737919187629.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_2e_06_wd_0_001_dp_0_999_en_5.5.1_3.0_1737919187629.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_2_0_lr_2e_06_wd_0_001_dp_0_999","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_2_0_lr_2e_06_wd_0_001_dp_0_999", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_2_0_lr_2e_06_wd_0_001_dp_0_999|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-2.0-lr-2e-06-wd-0.001-dp-0.999
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_2_0_lr_2e_06_wd_0_001_dp_0_999_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_2_0_lr_2e_06_wd_0_001_dp_0_999_pipeline_en.md
new file mode 100644
index 00000000000000..ac84120a7012a8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_2_0_lr_2e_06_wd_0_001_dp_0_999_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_2_0_lr_2e_06_wd_0_001_dp_0_999_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_2_0_lr_2e_06_wd_0_001_dp_0_999_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_2_0_lr_2e_06_wd_0_001_dp_0_999_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_2e_06_wd_0_001_dp_0_999_pipeline_en_5.5.1_3.0_1737919210525.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_2e_06_wd_0_001_dp_0_999_pipeline_en_5.5.1_3.0_1737919210525.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_2_0_lr_2e_06_wd_0_001_dp_0_999_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_2_0_lr_2e_06_wd_0_001_dp_0_999_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_2_0_lr_2e_06_wd_0_001_dp_0_999_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-2.0-lr-2e-06-wd-0.001-dp-0.999
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_3_0_lr_2e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_600_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_3_0_lr_2e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_600_en.md
new file mode 100644
index 00000000000000..a2d91c3461b30f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_3_0_lr_2e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_600_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_3_0_lr_2e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_600 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_3_0_lr_2e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_600
+date: 2025-01-26
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_3_0_lr_2e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_600` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_3_0_lr_2e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_600_en_5.5.1_3.0_1737918967767.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_3_0_lr_2e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_600_en_5.5.1_3.0_1737918967767.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_3_0_lr_2e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_600","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_3_0_lr_2e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_600", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_3_0_lr_2e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_600|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-3.0-lr-2e-05-wd-0.001-dp-0.2-ss-0-st-False-fh-False-hs-600
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_3_0_lr_2e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_600_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_3_0_lr_2e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_600_pipeline_en.md
new file mode 100644
index 00000000000000..43124b6c784802
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_3_0_lr_2e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_600_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_3_0_lr_2e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_600_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_3_0_lr_2e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_600_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_3_0_lr_2e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_600_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_3_0_lr_2e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_600_pipeline_en_5.5.1_3.0_1737918988615.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_3_0_lr_2e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_600_pipeline_en_5.5.1_3.0_1737918988615.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_3_0_lr_2e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_600_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_3_0_lr_2e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_600_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_3_0_lr_2e_05_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_600_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-3.0-lr-2e-05-wd-0.001-dp-0.2-ss-0-st-False-fh-False-hs-600
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_008_swati_0_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_008_swati_0_en.md
new file mode 100644
index 00000000000000..3b8bf650ca15a1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_008_swati_0_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_008_swati_0 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_008_swati_0
+date: 2025-01-26
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_008_swati_0` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_008_swati_0_en_5.5.1_3.0_1737919147649.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_008_swati_0_en_5.5.1_3.0_1737919147649.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_008_swati_0","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_008_swati_0", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_008_swati_0|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-4.0-lr-1e-05-wd-0.001-dp-0.008-ss-0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_008_swati_0_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_008_swati_0_pipeline_en.md
new file mode 100644
index 00000000000000..885569f8ff894c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_008_swati_0_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_008_swati_0_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_008_swati_0_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_008_swati_0_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_008_swati_0_pipeline_en_5.5.1_3.0_1737919168831.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_008_swati_0_pipeline_en_5.5.1_3.0_1737919168831.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_008_swati_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_008_swati_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_008_swati_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-4.0-lr-1e-05-wd-0.001-dp-0.008-ss-0
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_4664_southern_sotho_false_fh_true_hs_666_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_4664_southern_sotho_false_fh_true_hs_666_en.md
new file mode 100644
index 00000000000000..b891f1c85f217a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_4664_southern_sotho_false_fh_true_hs_666_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_4664_southern_sotho_false_fh_true_hs_666 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_4664_southern_sotho_false_fh_true_hs_666
+date: 2025-01-26
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_4664_southern_sotho_false_fh_true_hs_666` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_4664_southern_sotho_false_fh_true_hs_666_en_5.5.1_3.0_1737919393315.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_4664_southern_sotho_false_fh_true_hs_666_en_5.5.1_3.0_1737919393315.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_4664_southern_sotho_false_fh_true_hs_666","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_4664_southern_sotho_false_fh_true_hs_666", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_4664_southern_sotho_false_fh_true_hs_666|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-4.0-lr-1e-06-wd-0.001-dp-0.2-ss-4664-st-False-fh-True-hs-666
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_4664_southern_sotho_false_fh_true_hs_666_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_4664_southern_sotho_false_fh_true_hs_666_pipeline_en.md
new file mode 100644
index 00000000000000..673feef252ddb8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_4664_southern_sotho_false_fh_true_hs_666_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_4664_southern_sotho_false_fh_true_hs_666_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_4664_southern_sotho_false_fh_true_hs_666_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_4664_southern_sotho_false_fh_true_hs_666_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_4664_southern_sotho_false_fh_true_hs_666_pipeline_en_5.5.1_3.0_1737919417103.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_4664_southern_sotho_false_fh_true_hs_666_pipeline_en_5.5.1_3.0_1737919417103.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_4664_southern_sotho_false_fh_true_hs_666_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_4664_southern_sotho_false_fh_true_hs_666_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_4_0_lr_1e_06_wd_0_001_dp_0_2_swati_4664_southern_sotho_false_fh_true_hs_666_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-4.0-lr-1e-06-wd-0.001-dp-0.2-ss-4664-st-False-fh-True-hs-666
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_5_0_lr_1e_06_wd_0_001_dp_0_2_swati_1000_southern_sotho_false_fh_true_hs_666_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_5_0_lr_1e_06_wd_0_001_dp_0_2_swati_1000_southern_sotho_false_fh_true_hs_666_en.md
new file mode 100644
index 00000000000000..41053a94d7360f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_5_0_lr_1e_06_wd_0_001_dp_0_2_swati_1000_southern_sotho_false_fh_true_hs_666_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_5_0_lr_1e_06_wd_0_001_dp_0_2_swati_1000_southern_sotho_false_fh_true_hs_666 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_5_0_lr_1e_06_wd_0_001_dp_0_2_swati_1000_southern_sotho_false_fh_true_hs_666
+date: 2025-01-26
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_5_0_lr_1e_06_wd_0_001_dp_0_2_swati_1000_southern_sotho_false_fh_true_hs_666` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_5_0_lr_1e_06_wd_0_001_dp_0_2_swati_1000_southern_sotho_false_fh_true_hs_666_en_5.5.1_3.0_1737918623951.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_5_0_lr_1e_06_wd_0_001_dp_0_2_swati_1000_southern_sotho_false_fh_true_hs_666_en_5.5.1_3.0_1737918623951.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_5_0_lr_1e_06_wd_0_001_dp_0_2_swati_1000_southern_sotho_false_fh_true_hs_666","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_5_0_lr_1e_06_wd_0_001_dp_0_2_swati_1000_southern_sotho_false_fh_true_hs_666", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_5_0_lr_1e_06_wd_0_001_dp_0_2_swati_1000_southern_sotho_false_fh_true_hs_666|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-5.0-lr-1e-06-wd-0.001-dp-0.2-ss-1000-st-False-fh-True-hs-666
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_5_0_lr_1e_06_wd_0_001_dp_0_2_swati_1000_southern_sotho_false_fh_true_hs_666_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_5_0_lr_1e_06_wd_0_001_dp_0_2_swati_1000_southern_sotho_false_fh_true_hs_666_pipeline_en.md
new file mode 100644
index 00000000000000..a74b76e1c98513
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetune_squad_ep_5_0_lr_1e_06_wd_0_001_dp_0_2_swati_1000_southern_sotho_false_fh_true_hs_666_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_5_0_lr_1e_06_wd_0_001_dp_0_2_swati_1000_southern_sotho_false_fh_true_hs_666_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_5_0_lr_1e_06_wd_0_001_dp_0_2_swati_1000_southern_sotho_false_fh_true_hs_666_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_5_0_lr_1e_06_wd_0_001_dp_0_2_swati_1000_southern_sotho_false_fh_true_hs_666_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_5_0_lr_1e_06_wd_0_001_dp_0_2_swati_1000_southern_sotho_false_fh_true_hs_666_pipeline_en_5.5.1_3.0_1737918644684.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_5_0_lr_1e_06_wd_0_001_dp_0_2_swati_1000_southern_sotho_false_fh_true_hs_666_pipeline_en_5.5.1_3.0_1737918644684.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_5_0_lr_1e_06_wd_0_001_dp_0_2_swati_1000_southern_sotho_false_fh_true_hs_666_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_5_0_lr_1e_06_wd_0_001_dp_0_2_swati_1000_southern_sotho_false_fh_true_hs_666_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_5_0_lr_1e_06_wd_0_001_dp_0_2_swati_1000_southern_sotho_false_fh_true_hs_666_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-5.0-lr-1e-06-wd-0.001-dp-0.2-ss-1000-st-False-fh-True-hs-666
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetuned_advanced_srl_arg_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetuned_advanced_srl_arg_en.md
new file mode 100644
index 00000000000000..28584f341e56e6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetuned_advanced_srl_arg_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_uncased_finetuned_advanced_srl_arg BertForTokenClassification from dannashao
+author: John Snow Labs
+name: bert_base_uncased_finetuned_advanced_srl_arg
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_advanced_srl_arg` is a English model originally trained by dannashao.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_advanced_srl_arg_en_5.5.1_3.0_1737934334110.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_advanced_srl_arg_en_5.5.1_3.0_1737934334110.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_base_uncased_finetuned_advanced_srl_arg","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_base_uncased_finetuned_advanced_srl_arg", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetuned_advanced_srl_arg|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|407.4 MB|
+
+## References
+
+https://huggingface.co/dannashao/bert-base-uncased-finetuned-advanced-srl_arg
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetuned_advanced_srl_arg_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetuned_advanced_srl_arg_pipeline_en.md
new file mode 100644
index 00000000000000..ffb268c665f29f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetuned_advanced_srl_arg_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_uncased_finetuned_advanced_srl_arg_pipeline pipeline BertForTokenClassification from dannashao
+author: John Snow Labs
+name: bert_base_uncased_finetuned_advanced_srl_arg_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_advanced_srl_arg_pipeline` is a English model originally trained by dannashao.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_advanced_srl_arg_pipeline_en_5.5.1_3.0_1737934354948.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_advanced_srl_arg_pipeline_en_5.5.1_3.0_1737934354948.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetuned_advanced_srl_arg_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_advanced_srl_arg_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetuned_advanced_srl_arg_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.4 MB|
+
+## References
+
+https://huggingface.co/dannashao/bert-base-uncased-finetuned-advanced-srl_arg
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetuned_czech_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetuned_czech_en.md
new file mode 100644
index 00000000000000..e369f4e82bb6fd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetuned_czech_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_uncased_finetuned_czech BertEmbeddings from fahadal
+author: John Snow Labs
+name: bert_base_uncased_finetuned_czech
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_czech` is a English model originally trained by fahadal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_czech_en_5.5.1_3.0_1737908587774.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_czech_en_5.5.1_3.0_1737908587774.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_base_uncased_finetuned_czech","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_base_uncased_finetuned_czech","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetuned_czech|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/fahadal/bert-base-uncased-finetuned-cs
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetuned_czech_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetuned_czech_pipeline_en.md
new file mode 100644
index 00000000000000..511a842478ecf4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetuned_czech_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_uncased_finetuned_czech_pipeline pipeline BertEmbeddings from fahadal
+author: John Snow Labs
+name: bert_base_uncased_finetuned_czech_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_czech_pipeline` is a English model originally trained by fahadal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_czech_pipeline_en_5.5.1_3.0_1737908608595.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_czech_pipeline_en_5.5.1_3.0_1737908608595.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetuned_czech_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_czech_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetuned_czech_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/fahadal/bert-base-uncased-finetuned-cs
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetuned_mlm_nef_20240320_test_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetuned_mlm_nef_20240320_test_en.md
new file mode 100644
index 00000000000000..8f66485bab296d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetuned_mlm_nef_20240320_test_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_uncased_finetuned_mlm_nef_20240320_test BertEmbeddings from JTh34
+author: John Snow Labs
+name: bert_base_uncased_finetuned_mlm_nef_20240320_test
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_mlm_nef_20240320_test` is a English model originally trained by JTh34.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_mlm_nef_20240320_test_en_5.5.1_3.0_1737908708827.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_mlm_nef_20240320_test_en_5.5.1_3.0_1737908708827.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_base_uncased_finetuned_mlm_nef_20240320_test","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_base_uncased_finetuned_mlm_nef_20240320_test","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetuned_mlm_nef_20240320_test|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|417.5 MB|
+
+## References
+
+https://huggingface.co/JTh34/bert-base-uncased-finetuned-mlm-nef-20240320-test
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetuned_mlm_nef_20240320_test_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetuned_mlm_nef_20240320_test_pipeline_en.md
new file mode 100644
index 00000000000000..7ba1ccb92f93eb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetuned_mlm_nef_20240320_test_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_uncased_finetuned_mlm_nef_20240320_test_pipeline pipeline BertEmbeddings from JTh34
+author: John Snow Labs
+name: bert_base_uncased_finetuned_mlm_nef_20240320_test_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_mlm_nef_20240320_test_pipeline` is a English model originally trained by JTh34.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_mlm_nef_20240320_test_pipeline_en_5.5.1_3.0_1737908730312.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_mlm_nef_20240320_test_pipeline_en_5.5.1_3.0_1737908730312.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetuned_mlm_nef_20240320_test_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_mlm_nef_20240320_test_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetuned_mlm_nef_20240320_test_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|417.5 MB|
+
+## References
+
+https://huggingface.co/JTh34/bert-base-uncased-finetuned-mlm-nef-20240320-test
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetuned_shushuile_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetuned_shushuile_en.md
new file mode 100644
index 00000000000000..5553ec49d9e240
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetuned_shushuile_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_uncased_finetuned_shushuile BertEmbeddings from shushuile
+author: John Snow Labs
+name: bert_base_uncased_finetuned_shushuile
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_shushuile` is a English model originally trained by shushuile.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_shushuile_en_5.5.1_3.0_1737861894868.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_shushuile_en_5.5.1_3.0_1737861894868.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_base_uncased_finetuned_shushuile","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_base_uncased_finetuned_shushuile","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetuned_shushuile|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/shushuile/bert-base-uncased-finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetuned_shushuile_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetuned_shushuile_pipeline_en.md
new file mode 100644
index 00000000000000..7de5c30198e655
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_finetuned_shushuile_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_uncased_finetuned_shushuile_pipeline pipeline BertEmbeddings from shushuile
+author: John Snow Labs
+name: bert_base_uncased_finetuned_shushuile_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_shushuile_pipeline` is a English model originally trained by shushuile.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_shushuile_pipeline_en_5.5.1_3.0_1737861917151.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_shushuile_pipeline_en_5.5.1_3.0_1737861917151.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetuned_shushuile_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_shushuile_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetuned_shushuile_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/shushuile/bert-base-uncased-finetuned
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_issues_128_taoyoung_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_issues_128_taoyoung_en.md
new file mode 100644
index 00000000000000..5957f79c754dd0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_issues_128_taoyoung_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_uncased_issues_128_taoyoung BertEmbeddings from taoyoung
+author: John Snow Labs
+name: bert_base_uncased_issues_128_taoyoung
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_issues_128_taoyoung` is a English model originally trained by taoyoung.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_issues_128_taoyoung_en_5.5.1_3.0_1737908181287.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_issues_128_taoyoung_en_5.5.1_3.0_1737908181287.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_base_uncased_issues_128_taoyoung","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_base_uncased_issues_128_taoyoung","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_issues_128_taoyoung|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/taoyoung/bert-base-uncased-issues-128
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_issues_128_taoyoung_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_issues_128_taoyoung_pipeline_en.md
new file mode 100644
index 00000000000000..7e62cd719c880e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_issues_128_taoyoung_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_uncased_issues_128_taoyoung_pipeline pipeline BertEmbeddings from taoyoung
+author: John Snow Labs
+name: bert_base_uncased_issues_128_taoyoung_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_issues_128_taoyoung_pipeline` is a English model originally trained by taoyoung.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_issues_128_taoyoung_pipeline_en_5.5.1_3.0_1737908202283.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_issues_128_taoyoung_pipeline_en_5.5.1_3.0_1737908202283.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_issues_128_taoyoung_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_issues_128_taoyoung_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_issues_128_taoyoung_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/taoyoung/bert-base-uncased-issues-128
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_tweet_disaster_classification_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_tweet_disaster_classification_en.md
new file mode 100644
index 00000000000000..5ca5e5e629c54e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_tweet_disaster_classification_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_uncased_tweet_disaster_classification DistilBertForSequenceClassification from MoGHenry
+author: John Snow Labs
+name: bert_base_uncased_tweet_disaster_classification
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_tweet_disaster_classification` is a English model originally trained by MoGHenry.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_tweet_disaster_classification_en_5.5.1_3.0_1737904960808.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_tweet_disaster_classification_en_5.5.1_3.0_1737904960808.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("bert_base_uncased_tweet_disaster_classification","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("bert_base_uncased_tweet_disaster_classification", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_tweet_disaster_classification|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/MoGHenry/bert-base-uncased-tweet-disaster-classification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_tweet_disaster_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_tweet_disaster_classification_pipeline_en.md
new file mode 100644
index 00000000000000..48c30245a8a269
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_base_uncased_tweet_disaster_classification_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_uncased_tweet_disaster_classification_pipeline pipeline DistilBertForSequenceClassification from MoGHenry
+author: John Snow Labs
+name: bert_base_uncased_tweet_disaster_classification_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_tweet_disaster_classification_pipeline` is a English model originally trained by MoGHenry.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_tweet_disaster_classification_pipeline_en_5.5.1_3.0_1737904974269.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_tweet_disaster_classification_pipeline_en_5.5.1_3.0_1737904974269.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_tweet_disaster_classification_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_tweet_disaster_classification_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_tweet_disaster_classification_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/MoGHenry/bert-base-uncased-tweet-disaster-classification
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_bibtex_classifier_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_bibtex_classifier_en.md
new file mode 100644
index 00000000000000..3d49bc51ec5aca
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_bibtex_classifier_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_bibtex_classifier BertForTokenClassification from aurelvu
+author: John Snow Labs
+name: bert_bibtex_classifier
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_bibtex_classifier` is a English model originally trained by aurelvu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_bibtex_classifier_en_5.5.1_3.0_1737933833920.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_bibtex_classifier_en_5.5.1_3.0_1737933833920.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_bibtex_classifier","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_bibtex_classifier", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_bibtex_classifier|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|664.5 MB|
+
+## References
+
+https://huggingface.co/aurelvu/bert-bibtex-classifier
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_bibtex_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_bibtex_classifier_pipeline_en.md
new file mode 100644
index 00000000000000..effebe6a3f58a2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_bibtex_classifier_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_bibtex_classifier_pipeline pipeline BertForTokenClassification from aurelvu
+author: John Snow Labs
+name: bert_bibtex_classifier_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_bibtex_classifier_pipeline` is a English model originally trained by aurelvu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_bibtex_classifier_pipeline_en_5.5.1_3.0_1737933870427.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_bibtex_classifier_pipeline_en_5.5.1_3.0_1737933870427.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_bibtex_classifier_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_bibtex_classifier_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_bibtex_classifier_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|664.5 MB|
+
+## References
+
+https://huggingface.co/aurelvu/bert-bibtex-classifier
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_chat_moderation_x_v2_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_chat_moderation_x_v2_en.md
new file mode 100644
index 00000000000000..5743fb6df1c263
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_chat_moderation_x_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_chat_moderation_x_v2 DistilBertForSequenceClassification from andriadze
+author: John Snow Labs
+name: bert_chat_moderation_x_v2
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_chat_moderation_x_v2` is a English model originally trained by andriadze.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_chat_moderation_x_v2_en_5.5.1_3.0_1737873727094.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_chat_moderation_x_v2_en_5.5.1_3.0_1737873727094.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("bert_chat_moderation_x_v2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("bert_chat_moderation_x_v2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_chat_moderation_x_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/andriadze/bert-chat-moderation-X-V2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_chat_moderation_x_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_chat_moderation_x_v2_pipeline_en.md
new file mode 100644
index 00000000000000..b3b0d11c813893
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_chat_moderation_x_v2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_chat_moderation_x_v2_pipeline pipeline DistilBertForSequenceClassification from andriadze
+author: John Snow Labs
+name: bert_chat_moderation_x_v2_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_chat_moderation_x_v2_pipeline` is a English model originally trained by andriadze.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_chat_moderation_x_v2_pipeline_en_5.5.1_3.0_1737873740673.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_chat_moderation_x_v2_pipeline_en_5.5.1_3.0_1737873740673.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_chat_moderation_x_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_chat_moderation_x_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_chat_moderation_x_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/andriadze/bert-chat-moderation-X-V2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_ner_15_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_ner_15_en.md
new file mode 100644
index 00000000000000..bd0fd81daa687f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_ner_15_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_finetuned_ner_15 BertForTokenClassification from jdavit
+author: John Snow Labs
+name: bert_finetuned_ner_15
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_15` is a English model originally trained by jdavit.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_15_en_5.5.1_3.0_1737935477260.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_15_en_5.5.1_3.0_1737935477260.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_finetuned_ner_15","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner_15", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_15|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/jdavit/bert-finetuned-ner-15
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_ner_15_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_ner_15_pipeline_en.md
new file mode 100644
index 00000000000000..1e823235ea9c8e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_ner_15_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_finetuned_ner_15_pipeline pipeline BertForTokenClassification from jdavit
+author: John Snow Labs
+name: bert_finetuned_ner_15_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_15_pipeline` is a English model originally trained by jdavit.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_15_pipeline_en_5.5.1_3.0_1737935499027.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_15_pipeline_en_5.5.1_3.0_1737935499027.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_ner_15_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_ner_15_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_15_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/jdavit/bert-finetuned-ner-15
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_ner_accelerate_2_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_ner_accelerate_2_en.md
new file mode 100644
index 00000000000000..3a8632420250d4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_ner_accelerate_2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_finetuned_ner_accelerate_2 BertForTokenClassification from jmarcosh
+author: John Snow Labs
+name: bert_finetuned_ner_accelerate_2
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_accelerate_2` is a English model originally trained by jmarcosh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_accelerate_2_en_5.5.1_3.0_1737935931434.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_accelerate_2_en_5.5.1_3.0_1737935931434.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_finetuned_ner_accelerate_2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner_accelerate_2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_accelerate_2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/jmarcosh/bert-finetuned-ner-accelerate_2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_ner_accelerate_2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_ner_accelerate_2_pipeline_en.md
new file mode 100644
index 00000000000000..ef14f8838174aa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_ner_accelerate_2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_finetuned_ner_accelerate_2_pipeline pipeline BertForTokenClassification from jmarcosh
+author: John Snow Labs
+name: bert_finetuned_ner_accelerate_2_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_accelerate_2_pipeline` is a English model originally trained by jmarcosh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_accelerate_2_pipeline_en_5.5.1_3.0_1737935952043.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_accelerate_2_pipeline_en_5.5.1_3.0_1737935952043.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_ner_accelerate_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_ner_accelerate_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_accelerate_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/jmarcosh/bert-finetuned-ner-accelerate_2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_ner_explorertcf_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_ner_explorertcf_en.md
new file mode 100644
index 00000000000000..4d66698c4806f7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_ner_explorertcf_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_finetuned_ner_explorertcf BertForTokenClassification from ExplorerTCF
+author: John Snow Labs
+name: bert_finetuned_ner_explorertcf
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_explorertcf` is a English model originally trained by ExplorerTCF.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_explorertcf_en_5.5.1_3.0_1737935602284.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_explorertcf_en_5.5.1_3.0_1737935602284.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_finetuned_ner_explorertcf","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner_explorertcf", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_explorertcf|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/ExplorerTCF/bert-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_ner_explorertcf_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_ner_explorertcf_pipeline_en.md
new file mode 100644
index 00000000000000..366af27454d602
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_ner_explorertcf_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_finetuned_ner_explorertcf_pipeline pipeline BertForTokenClassification from ExplorerTCF
+author: John Snow Labs
+name: bert_finetuned_ner_explorertcf_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_explorertcf_pipeline` is a English model originally trained by ExplorerTCF.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_explorertcf_pipeline_en_5.5.1_3.0_1737935623273.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_explorertcf_pipeline_en_5.5.1_3.0_1737935623273.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_ner_explorertcf_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_ner_explorertcf_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_explorertcf_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/ExplorerTCF/bert-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_ner_jeffery4428_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_ner_jeffery4428_en.md
new file mode 100644
index 00000000000000..3c381512d1593f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_ner_jeffery4428_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_finetuned_ner_jeffery4428 BertForTokenClassification from jeffery4428
+author: John Snow Labs
+name: bert_finetuned_ner_jeffery4428
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_jeffery4428` is a English model originally trained by jeffery4428.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_jeffery4428_en_5.5.1_3.0_1737935259687.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_jeffery4428_en_5.5.1_3.0_1737935259687.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_finetuned_ner_jeffery4428","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner_jeffery4428", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_jeffery4428|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/jeffery4428/bert-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_ner_jeffery4428_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_ner_jeffery4428_pipeline_en.md
new file mode 100644
index 00000000000000..fb2a71f3320cb9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_ner_jeffery4428_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_finetuned_ner_jeffery4428_pipeline pipeline BertForTokenClassification from jeffery4428
+author: John Snow Labs
+name: bert_finetuned_ner_jeffery4428_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_jeffery4428_pipeline` is a English model originally trained by jeffery4428.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_jeffery4428_pipeline_en_5.5.1_3.0_1737935281081.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_jeffery4428_pipeline_en_5.5.1_3.0_1737935281081.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_ner_jeffery4428_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_ner_jeffery4428_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_jeffery4428_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/jeffery4428/bert-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_ner_jin_cheon_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_ner_jin_cheon_en.md
new file mode 100644
index 00000000000000..3a5ff1e768b321
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_ner_jin_cheon_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_finetuned_ner_jin_cheon BertForTokenClassification from jin-cheon
+author: John Snow Labs
+name: bert_finetuned_ner_jin_cheon
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_jin_cheon` is a English model originally trained by jin-cheon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_jin_cheon_en_5.5.1_3.0_1737935697804.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_jin_cheon_en_5.5.1_3.0_1737935697804.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_finetuned_ner_jin_cheon","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner_jin_cheon", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_jin_cheon|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/jin-cheon/bert-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_ner_jin_cheon_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_ner_jin_cheon_pipeline_en.md
new file mode 100644
index 00000000000000..4026cdd3c32f1e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_ner_jin_cheon_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_finetuned_ner_jin_cheon_pipeline pipeline BertForTokenClassification from jin-cheon
+author: John Snow Labs
+name: bert_finetuned_ner_jin_cheon_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_jin_cheon_pipeline` is a English model originally trained by jin-cheon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_jin_cheon_pipeline_en_5.5.1_3.0_1737935719093.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_jin_cheon_pipeline_en_5.5.1_3.0_1737935719093.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_ner_jin_cheon_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_ner_jin_cheon_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_jin_cheon_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/jin-cheon/bert-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_ner_samsaver_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_ner_samsaver_en.md
new file mode 100644
index 00000000000000..5ffd69256a55b9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_ner_samsaver_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_finetuned_ner_samsaver BertForTokenClassification from SamSaver
+author: John Snow Labs
+name: bert_finetuned_ner_samsaver
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_samsaver` is a English model originally trained by SamSaver.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_samsaver_en_5.5.1_3.0_1737934840707.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_samsaver_en_5.5.1_3.0_1737934840707.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_finetuned_ner_samsaver","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner_samsaver", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_samsaver|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/SamSaver/bert-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_ner_samsaver_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_ner_samsaver_pipeline_en.md
new file mode 100644
index 00000000000000..0c3f45a293348d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_ner_samsaver_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_finetuned_ner_samsaver_pipeline pipeline BertForTokenClassification from SamSaver
+author: John Snow Labs
+name: bert_finetuned_ner_samsaver_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_samsaver_pipeline` is a English model originally trained by SamSaver.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_samsaver_pipeline_en_5.5.1_3.0_1737934862469.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_samsaver_pipeline_en_5.5.1_3.0_1737934862469.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_ner_samsaver_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_ner_samsaver_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_samsaver_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/SamSaver/bert-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_squad_jpalmer18_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_squad_jpalmer18_en.md
new file mode 100644
index 00000000000000..3e9dcccf33899d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_squad_jpalmer18_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_finetuned_squad_jpalmer18 BertForQuestionAnswering from jpalmer18
+author: John Snow Labs
+name: bert_finetuned_squad_jpalmer18
+date: 2025-01-26
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_jpalmer18` is a English model originally trained by jpalmer18.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_jpalmer18_en_5.5.1_3.0_1737919466095.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_jpalmer18_en_5.5.1_3.0_1737919466095.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_jpalmer18","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_jpalmer18", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_jpalmer18|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/jpalmer18/bert-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_squad_jpalmer18_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_squad_jpalmer18_pipeline_en.md
new file mode 100644
index 00000000000000..4f22752902742b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_squad_jpalmer18_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_finetuned_squad_jpalmer18_pipeline pipeline BertForQuestionAnswering from jpalmer18
+author: John Snow Labs
+name: bert_finetuned_squad_jpalmer18_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_jpalmer18_pipeline` is a English model originally trained by jpalmer18.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_jpalmer18_pipeline_en_5.5.1_3.0_1737919491006.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_jpalmer18_pipeline_en_5.5.1_3.0_1737919491006.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_squad_jpalmer18_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_squad_jpalmer18_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_jpalmer18_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/jpalmer18/bert-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_squad_nada25_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_squad_nada25_en.md
new file mode 100644
index 00000000000000..7b6392e8d0980c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_squad_nada25_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_finetuned_squad_nada25 BertForQuestionAnswering from Nada25
+author: John Snow Labs
+name: bert_finetuned_squad_nada25
+date: 2025-01-26
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_nada25` is a English model originally trained by Nada25.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_nada25_en_5.5.1_3.0_1737919628070.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_nada25_en_5.5.1_3.0_1737919628070.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_nada25","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_nada25", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_nada25|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/Nada25/bert-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_squad_nada25_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_squad_nada25_pipeline_en.md
new file mode 100644
index 00000000000000..f89e5fb893cb77
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_squad_nada25_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_finetuned_squad_nada25_pipeline pipeline BertForQuestionAnswering from Nada25
+author: John Snow Labs
+name: bert_finetuned_squad_nada25_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_nada25_pipeline` is a English model originally trained by Nada25.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_nada25_pipeline_en_5.5.1_3.0_1737919648657.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_nada25_pipeline_en_5.5.1_3.0_1737919648657.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_squad_nada25_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_squad_nada25_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_nada25_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/Nada25/bert-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_squad_ronenh24_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_squad_ronenh24_en.md
new file mode 100644
index 00000000000000..faa09c19095f40
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_squad_ronenh24_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_finetuned_squad_ronenh24 BertForQuestionAnswering from ronenh24
+author: John Snow Labs
+name: bert_finetuned_squad_ronenh24
+date: 2025-01-26
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_ronenh24` is a English model originally trained by ronenh24.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_ronenh24_en_5.5.1_3.0_1737919532422.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_ronenh24_en_5.5.1_3.0_1737919532422.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_ronenh24","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_ronenh24", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_ronenh24|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/ronenh24/bert-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_squad_ronenh24_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_squad_ronenh24_pipeline_en.md
new file mode 100644
index 00000000000000..091d6ae36002f5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_squad_ronenh24_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_finetuned_squad_ronenh24_pipeline pipeline BertForQuestionAnswering from ronenh24
+author: John Snow Labs
+name: bert_finetuned_squad_ronenh24_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_ronenh24_pipeline` is a English model originally trained by ronenh24.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_ronenh24_pipeline_en_5.5.1_3.0_1737919553391.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_ronenh24_pipeline_en_5.5.1_3.0_1737919553391.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_squad_ronenh24_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_squad_ronenh24_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_ronenh24_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/ronenh24/bert-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_squad_seungahson_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_squad_seungahson_en.md
new file mode 100644
index 00000000000000..fae3f7c0e5fe10
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_squad_seungahson_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_finetuned_squad_seungahson BertForQuestionAnswering from SeungAhSon
+author: John Snow Labs
+name: bert_finetuned_squad_seungahson
+date: 2025-01-26
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_seungahson` is a English model originally trained by SeungAhSon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_seungahson_en_5.5.1_3.0_1737919771506.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_seungahson_en_5.5.1_3.0_1737919771506.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_seungahson","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_seungahson", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_seungahson|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/SeungAhSon/bert-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_squad_seungahson_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_squad_seungahson_pipeline_en.md
new file mode 100644
index 00000000000000..72e6481bc5a9c7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_squad_seungahson_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_finetuned_squad_seungahson_pipeline pipeline BertForQuestionAnswering from SeungAhSon
+author: John Snow Labs
+name: bert_finetuned_squad_seungahson_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_seungahson_pipeline` is a English model originally trained by SeungAhSon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_seungahson_pipeline_en_5.5.1_3.0_1737919794171.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_seungahson_pipeline_en_5.5.1_3.0_1737919794171.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_squad_seungahson_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_squad_seungahson_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_seungahson_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/SeungAhSon/bert-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_squad_vsrinivas_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_squad_vsrinivas_en.md
new file mode 100644
index 00000000000000..d6a4a829114ed9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_squad_vsrinivas_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_finetuned_squad_vsrinivas BertForQuestionAnswering from vsrinivas
+author: John Snow Labs
+name: bert_finetuned_squad_vsrinivas
+date: 2025-01-26
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_vsrinivas` is a English model originally trained by vsrinivas.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_vsrinivas_en_5.5.1_3.0_1737918991668.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_vsrinivas_en_5.5.1_3.0_1737918991668.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_vsrinivas","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_vsrinivas", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_vsrinivas|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/vsrinivas/bert-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_squad_vsrinivas_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_squad_vsrinivas_pipeline_en.md
new file mode 100644
index 00000000000000..fe322600ca04fd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_squad_vsrinivas_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_finetuned_squad_vsrinivas_pipeline pipeline BertForQuestionAnswering from vsrinivas
+author: John Snow Labs
+name: bert_finetuned_squad_vsrinivas_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_vsrinivas_pipeline` is a English model originally trained by vsrinivas.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_vsrinivas_pipeline_en_5.5.1_3.0_1737919020234.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_vsrinivas_pipeline_en_5.5.1_3.0_1737919020234.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_squad_vsrinivas_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_squad_vsrinivas_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_vsrinivas_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/vsrinivas/bert-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_squad_yaojingguo_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_squad_yaojingguo_en.md
new file mode 100644
index 00000000000000..cc4b0dcafb00c6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_squad_yaojingguo_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_finetuned_squad_yaojingguo BertForQuestionAnswering from yaojingguo
+author: John Snow Labs
+name: bert_finetuned_squad_yaojingguo
+date: 2025-01-26
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_yaojingguo` is a English model originally trained by yaojingguo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_yaojingguo_en_5.5.1_3.0_1737918482245.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_yaojingguo_en_5.5.1_3.0_1737918482245.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_yaojingguo","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_yaojingguo", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_yaojingguo|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/yaojingguo/bert-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_squad_yaojingguo_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_squad_yaojingguo_pipeline_en.md
new file mode 100644
index 00000000000000..ab57f8793265da
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_finetuned_squad_yaojingguo_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_finetuned_squad_yaojingguo_pipeline pipeline BertForQuestionAnswering from yaojingguo
+author: John Snow Labs
+name: bert_finetuned_squad_yaojingguo_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_yaojingguo_pipeline` is a English model originally trained by yaojingguo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_yaojingguo_pipeline_en_5.5.1_3.0_1737918507264.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_yaojingguo_pipeline_en_5.5.1_3.0_1737918507264.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_squad_yaojingguo_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_squad_yaojingguo_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_yaojingguo_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/yaojingguo/bert-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_ganda_cased_malay_ner_v3_test_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_ganda_cased_malay_ner_v3_test_en.md
new file mode 100644
index 00000000000000..9435d3805f060f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_ganda_cased_malay_ner_v3_test_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_ganda_cased_malay_ner_v3_test BertForTokenClassification from nxaliao
+author: John Snow Labs
+name: bert_ganda_cased_malay_ner_v3_test
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ganda_cased_malay_ner_v3_test` is a English model originally trained by nxaliao.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ganda_cased_malay_ner_v3_test_en_5.5.1_3.0_1737934909258.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ganda_cased_malay_ner_v3_test_en_5.5.1_3.0_1737934909258.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_ganda_cased_malay_ner_v3_test","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_ganda_cased_malay_ner_v3_test", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_ganda_cased_malay_ner_v3_test|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/nxaliao/bert-lg-cased-ms-ner-v3-test
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_ganda_cased_malay_ner_v3_test_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_ganda_cased_malay_ner_v3_test_pipeline_en.md
new file mode 100644
index 00000000000000..c3420ff5ed3541
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_ganda_cased_malay_ner_v3_test_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_ganda_cased_malay_ner_v3_test_pipeline pipeline BertForTokenClassification from nxaliao
+author: John Snow Labs
+name: bert_ganda_cased_malay_ner_v3_test_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ganda_cased_malay_ner_v3_test_pipeline` is a English model originally trained by nxaliao.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ganda_cased_malay_ner_v3_test_pipeline_en_5.5.1_3.0_1737934972419.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ganda_cased_malay_ner_v3_test_pipeline_en_5.5.1_3.0_1737934972419.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_ganda_cased_malay_ner_v3_test_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_ganda_cased_malay_ner_v3_test_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_ganda_cased_malay_ner_v3_test_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/nxaliao/bert-lg-cased-ms-ner-v3-test
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_l10_h128_uncased_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_l10_h128_uncased_en.md
new file mode 100644
index 00000000000000..1626059a5aee91
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_l10_h128_uncased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_l10_h128_uncased BertEmbeddings from gaunernst
+author: John Snow Labs
+name: bert_l10_h128_uncased
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_l10_h128_uncased` is a English model originally trained by gaunernst.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_l10_h128_uncased_en_5.5.1_3.0_1737908298757.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_l10_h128_uncased_en_5.5.1_3.0_1737908298757.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_l10_h128_uncased","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_l10_h128_uncased","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_l10_h128_uncased|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|22.6 MB|
+
+## References
+
+https://huggingface.co/gaunernst/bert-L10-H128-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_l10_h128_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_l10_h128_uncased_pipeline_en.md
new file mode 100644
index 00000000000000..691d335e80ae4e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_l10_h128_uncased_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_l10_h128_uncased_pipeline pipeline BertEmbeddings from gaunernst
+author: John Snow Labs
+name: bert_l10_h128_uncased_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_l10_h128_uncased_pipeline` is a English model originally trained by gaunernst.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_l10_h128_uncased_pipeline_en_5.5.1_3.0_1737908304226.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_l10_h128_uncased_pipeline_en_5.5.1_3.0_1737908304226.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_l10_h128_uncased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_l10_h128_uncased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_l10_h128_uncased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|22.6 MB|
+
+## References
+
+https://huggingface.co/gaunernst/bert-L10-H128-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_l12_h128_uncased_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_l12_h128_uncased_en.md
new file mode 100644
index 00000000000000..a6c9e66475f0a5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_l12_h128_uncased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_l12_h128_uncased BertEmbeddings from gaunernst
+author: John Snow Labs
+name: bert_l12_h128_uncased
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_l12_h128_uncased` is a English model originally trained by gaunernst.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_l12_h128_uncased_en_5.5.1_3.0_1737908514100.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_l12_h128_uncased_en_5.5.1_3.0_1737908514100.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_l12_h128_uncased","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_l12_h128_uncased","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_l12_h128_uncased|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|24.1 MB|
+
+## References
+
+https://huggingface.co/gaunernst/bert-L12-H128-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_l12_h128_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_l12_h128_uncased_pipeline_en.md
new file mode 100644
index 00000000000000..124afd853efb7e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_l12_h128_uncased_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_l12_h128_uncased_pipeline pipeline BertEmbeddings from gaunernst
+author: John Snow Labs
+name: bert_l12_h128_uncased_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_l12_h128_uncased_pipeline` is a English model originally trained by gaunernst.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_l12_h128_uncased_pipeline_en_5.5.1_3.0_1737908515539.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_l12_h128_uncased_pipeline_en_5.5.1_3.0_1737908515539.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_l12_h128_uncased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_l12_h128_uncased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_l12_h128_uncased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|24.1 MB|
+
+## References
+
+https://huggingface.co/gaunernst/bert-L12-H128-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_l4_h128_uncased_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_l4_h128_uncased_en.md
new file mode 100644
index 00000000000000..2959f2238b3ef7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_l4_h128_uncased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_l4_h128_uncased BertEmbeddings from gaunernst
+author: John Snow Labs
+name: bert_l4_h128_uncased
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_l4_h128_uncased` is a English model originally trained by gaunernst.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_l4_h128_uncased_en_5.5.1_3.0_1737908529113.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_l4_h128_uncased_en_5.5.1_3.0_1737908529113.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_l4_h128_uncased","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_l4_h128_uncased","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_l4_h128_uncased|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|18.1 MB|
+
+## References
+
+https://huggingface.co/gaunernst/bert-L4-H128-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_l4_h128_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_l4_h128_uncased_pipeline_en.md
new file mode 100644
index 00000000000000..405b24cf9ebb8d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_l4_h128_uncased_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_l4_h128_uncased_pipeline pipeline BertEmbeddings from gaunernst
+author: John Snow Labs
+name: bert_l4_h128_uncased_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_l4_h128_uncased_pipeline` is a English model originally trained by gaunernst.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_l4_h128_uncased_pipeline_en_5.5.1_3.0_1737908530335.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_l4_h128_uncased_pipeline_en_5.5.1_3.0_1737908530335.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_l4_h128_uncased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_l4_h128_uncased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_l4_h128_uncased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|18.2 MB|
+
+## References
+
+https://huggingface.co/gaunernst/bert-L4-H128-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_large_mmshmblogs_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_large_mmshmblogs_en.md
new file mode 100644
index 00000000000000..dfa1270823b4fa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_large_mmshmblogs_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_large_mmshmblogs BertEmbeddings from MMShmBlogs
+author: John Snow Labs
+name: bert_large_mmshmblogs
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_mmshmblogs` is a English model originally trained by MMShmBlogs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_mmshmblogs_en_5.5.1_3.0_1737908134237.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_mmshmblogs_en_5.5.1_3.0_1737908134237.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_large_mmshmblogs","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_large_mmshmblogs","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_large_mmshmblogs|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/MMShmBlogs/BERT-large
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_large_mmshmblogs_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_large_mmshmblogs_pipeline_en.md
new file mode 100644
index 00000000000000..9741299fbb9b9b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_large_mmshmblogs_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_large_mmshmblogs_pipeline pipeline BertEmbeddings from MMShmBlogs
+author: John Snow Labs
+name: bert_large_mmshmblogs_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_mmshmblogs_pipeline` is a English model originally trained by MMShmBlogs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_mmshmblogs_pipeline_en_5.5.1_3.0_1737908202242.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_mmshmblogs_pipeline_en_5.5.1_3.0_1737908202242.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_large_mmshmblogs_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_large_mmshmblogs_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_large_mmshmblogs_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/MMShmBlogs/BERT-large
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_large_ner_rupesh2_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_large_ner_rupesh2_en.md
new file mode 100644
index 00000000000000..58453925ae6a20
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_large_ner_rupesh2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_large_ner_rupesh2 BertForTokenClassification from Rupesh2
+author: John Snow Labs
+name: bert_large_ner_rupesh2
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_ner_rupesh2` is a English model originally trained by Rupesh2.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_ner_rupesh2_en_5.5.1_3.0_1737935074076.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_ner_rupesh2_en_5.5.1_3.0_1737935074076.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_large_ner_rupesh2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_large_ner_rupesh2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_large_ner_rupesh2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/Rupesh2/bert-large-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_large_ner_rupesh2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_large_ner_rupesh2_pipeline_en.md
new file mode 100644
index 00000000000000..49459da0c9730f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_large_ner_rupesh2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_large_ner_rupesh2_pipeline pipeline BertForTokenClassification from Rupesh2
+author: John Snow Labs
+name: bert_large_ner_rupesh2_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_ner_rupesh2_pipeline` is a English model originally trained by Rupesh2.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_ner_rupesh2_pipeline_en_5.5.1_3.0_1737935139914.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_ner_rupesh2_pipeline_en_5.5.1_3.0_1737935139914.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_large_ner_rupesh2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_large_ner_rupesh2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_large_ner_rupesh2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/Rupesh2/bert-large-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_large_uncased_squad1_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_large_uncased_squad1_en.md
new file mode 100644
index 00000000000000..a530b172eabcaa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_large_uncased_squad1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_large_uncased_squad1 BertForQuestionAnswering from Yannis98
+author: John Snow Labs
+name: bert_large_uncased_squad1
+date: 2025-01-26
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_squad1` is a English model originally trained by Yannis98.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_squad1_en_5.5.1_3.0_1737919697995.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_squad1_en_5.5.1_3.0_1737919697995.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_large_uncased_squad1","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_large_uncased_squad1", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_large_uncased_squad1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/Yannis98/bert-large-uncased_squad1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_large_uncased_squad1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_large_uncased_squad1_pipeline_en.md
new file mode 100644
index 00000000000000..89261a3d2c5763
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_large_uncased_squad1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_large_uncased_squad1_pipeline pipeline BertForQuestionAnswering from Yannis98
+author: John Snow Labs
+name: bert_large_uncased_squad1_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_squad1_pipeline` is a English model originally trained by Yannis98.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_squad1_pipeline_en_5.5.1_3.0_1737919762356.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_squad1_pipeline_en_5.5.1_3.0_1737919762356.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_large_uncased_squad1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_large_uncased_squad1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_large_uncased_squad1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/Yannis98/bert-large-uncased_squad1
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_medquad_15052024_electra_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_medquad_15052024_electra_en.md
new file mode 100644
index 00000000000000..af55dd82d47d9d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_medquad_15052024_electra_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_medquad_15052024_electra BertForQuestionAnswering from DataScientist1122
+author: John Snow Labs
+name: bert_medquad_15052024_electra
+date: 2025-01-26
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_medquad_15052024_electra` is a English model originally trained by DataScientist1122.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_medquad_15052024_electra_en_5.5.1_3.0_1737918483877.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_medquad_15052024_electra_en_5.5.1_3.0_1737918483877.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_medquad_15052024_electra","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_medquad_15052024_electra", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_medquad_15052024_electra|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/DataScientist1122/BERT_MedQuad_15052024_electra
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_medquad_15052024_electra_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_medquad_15052024_electra_pipeline_en.md
new file mode 100644
index 00000000000000..c04e9c0675c7f3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_medquad_15052024_electra_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_medquad_15052024_electra_pipeline pipeline BertForQuestionAnswering from DataScientist1122
+author: John Snow Labs
+name: bert_medquad_15052024_electra_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_medquad_15052024_electra_pipeline` is a English model originally trained by DataScientist1122.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_medquad_15052024_electra_pipeline_en_5.5.1_3.0_1737918507640.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_medquad_15052024_electra_pipeline_en_5.5.1_3.0_1737918507640.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_medquad_15052024_electra_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_medquad_15052024_electra_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_medquad_15052024_electra_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/DataScientist1122/BERT_MedQuad_15052024_electra
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_ner_indonesian_cards_v2_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_ner_indonesian_cards_v2_en.md
new file mode 100644
index 00000000000000..d6610066b659cf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_ner_indonesian_cards_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_ner_indonesian_cards_v2 BertForTokenClassification from oualidlamrini
+author: John Snow Labs
+name: bert_ner_indonesian_cards_v2
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ner_indonesian_cards_v2` is a English model originally trained by oualidlamrini.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ner_indonesian_cards_v2_en_5.5.1_3.0_1737933362169.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ner_indonesian_cards_v2_en_5.5.1_3.0_1737933362169.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_ner_indonesian_cards_v2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_ner_indonesian_cards_v2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_ner_indonesian_cards_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/oualidlamrini/bert-ner-id_cards_v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_ner_indonesian_cards_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_ner_indonesian_cards_v2_pipeline_en.md
new file mode 100644
index 00000000000000..14b6f3615f59da
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_ner_indonesian_cards_v2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_ner_indonesian_cards_v2_pipeline pipeline BertForTokenClassification from oualidlamrini
+author: John Snow Labs
+name: bert_ner_indonesian_cards_v2_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ner_indonesian_cards_v2_pipeline` is a English model originally trained by oualidlamrini.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ner_indonesian_cards_v2_pipeline_en_5.5.1_3.0_1737933397011.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ner_indonesian_cards_v2_pipeline_en_5.5.1_3.0_1737933397011.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_ner_indonesian_cards_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_ner_indonesian_cards_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_ner_indonesian_cards_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/oualidlamrini/bert-ner-id_cards_v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_ner_pii_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_ner_pii_en.md
new file mode 100644
index 00000000000000..8a5dea61634ac4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_ner_pii_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_ner_pii BertForTokenClassification from vuminhtue
+author: John Snow Labs
+name: bert_ner_pii
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ner_pii` is a English model originally trained by vuminhtue.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ner_pii_en_5.5.1_3.0_1737933322962.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ner_pii_en_5.5.1_3.0_1737933322962.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_ner_pii","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_ner_pii", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_ner_pii|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|407.3 MB|
+
+## References
+
+https://huggingface.co/vuminhtue/Bert_NER_PII
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_ner_pii_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_ner_pii_pipeline_en.md
new file mode 100644
index 00000000000000..613f63c1bbedc7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_ner_pii_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_ner_pii_pipeline pipeline BertForTokenClassification from vuminhtue
+author: John Snow Labs
+name: bert_ner_pii_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ner_pii_pipeline` is a English model originally trained by vuminhtue.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ner_pii_pipeline_en_5.5.1_3.0_1737933349675.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ner_pii_pipeline_en_5.5.1_3.0_1737933349675.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_ner_pii_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_ner_pii_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_ner_pii_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.3 MB|
+
+## References
+
+https://huggingface.co/vuminhtue/Bert_NER_PII
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_question_ner_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_question_ner_en.md
new file mode 100644
index 00000000000000..1d6ffbeff2b6df
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_question_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_question_ner DistilBertForTokenClassification from lekhnathrijal
+author: John Snow Labs
+name: bert_question_ner
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_question_ner` is a English model originally trained by lekhnathrijal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_question_ner_en_5.5.1_3.0_1737909629692.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_question_ner_en_5.5.1_3.0_1737909629692.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("bert_question_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("bert_question_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_question_ner|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/lekhnathrijal/bert-question-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_question_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_question_ner_pipeline_en.md
new file mode 100644
index 00000000000000..cf3520820dbc61
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_question_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_question_ner_pipeline pipeline DistilBertForTokenClassification from lekhnathrijal
+author: John Snow Labs
+name: bert_question_ner_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_question_ner_pipeline` is a English model originally trained by lekhnathrijal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_question_ner_pipeline_en_5.5.1_3.0_1737909643383.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_question_ner_pipeline_en_5.5.1_3.0_1737909643383.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_question_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_question_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_question_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/lekhnathrijal/bert-question-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_tsonga_wordpiece_phonetic_wikitext_0_5_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_tsonga_wordpiece_phonetic_wikitext_0_5_en.md
new file mode 100644
index 00000000000000..58d70612d77027
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_tsonga_wordpiece_phonetic_wikitext_0_5_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_tsonga_wordpiece_phonetic_wikitext_0_5 BertEmbeddings from psktoure
+author: John Snow Labs
+name: bert_tsonga_wordpiece_phonetic_wikitext_0_5
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_tsonga_wordpiece_phonetic_wikitext_0_5` is a English model originally trained by psktoure.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_tsonga_wordpiece_phonetic_wikitext_0_5_en_5.5.1_3.0_1737908784783.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_tsonga_wordpiece_phonetic_wikitext_0_5_en_5.5.1_3.0_1737908784783.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_tsonga_wordpiece_phonetic_wikitext_0_5","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_tsonga_wordpiece_phonetic_wikitext_0_5","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_tsonga_wordpiece_phonetic_wikitext_0_5|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|408.2 MB|
+
+## References
+
+https://huggingface.co/psktoure/BERT_TS_WordPiece_phonetic_wikitext_0.5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bert_tsonga_wordpiece_phonetic_wikitext_0_5_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bert_tsonga_wordpiece_phonetic_wikitext_0_5_pipeline_en.md
new file mode 100644
index 00000000000000..a808fa1640dba8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bert_tsonga_wordpiece_phonetic_wikitext_0_5_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_tsonga_wordpiece_phonetic_wikitext_0_5_pipeline pipeline BertEmbeddings from psktoure
+author: John Snow Labs
+name: bert_tsonga_wordpiece_phonetic_wikitext_0_5_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_tsonga_wordpiece_phonetic_wikitext_0_5_pipeline` is a English model originally trained by psktoure.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_tsonga_wordpiece_phonetic_wikitext_0_5_pipeline_en_5.5.1_3.0_1737908805503.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_tsonga_wordpiece_phonetic_wikitext_0_5_pipeline_en_5.5.1_3.0_1737908805503.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_tsonga_wordpiece_phonetic_wikitext_0_5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_tsonga_wordpiece_phonetic_wikitext_0_5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_tsonga_wordpiece_phonetic_wikitext_0_5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|408.3 MB|
+
+## References
+
+https://huggingface.co/psktoure/BERT_TS_WordPiece_phonetic_wikitext_0.5
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-berttest_en.md b/docs/_posts/ahmedlone127/2025-01-26-berttest_en.md
new file mode 100644
index 00000000000000..7e31ca152e6642
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-berttest_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English berttest BertEmbeddings from hiert
+author: John Snow Labs
+name: berttest
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`berttest` is a English model originally trained by hiert.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/berttest_en_5.5.1_3.0_1737861100198.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/berttest_en_5.5.1_3.0_1737861100198.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("berttest","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("berttest","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|berttest|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/hiert/berttest
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-berttest_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-berttest_pipeline_en.md
new file mode 100644
index 00000000000000..f838c0cd20d49b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-berttest_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English berttest_pipeline pipeline BertEmbeddings from hiert
+author: John Snow Labs
+name: berttest_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`berttest_pipeline` is a English model originally trained by hiert.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/berttest_pipeline_en_5.5.1_3.0_1737861134681.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/berttest_pipeline_en_5.5.1_3.0_1737861134681.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("berttest_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("berttest_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|berttest_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/hiert/berttest
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bge_base_english_v1_5_76_keys_phase_6_exp_v1_en.md b/docs/_posts/ahmedlone127/2025-01-26-bge_base_english_v1_5_76_keys_phase_6_exp_v1_en.md
new file mode 100644
index 00000000000000..dfd69e338a2731
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bge_base_english_v1_5_76_keys_phase_6_exp_v1_en.md
@@ -0,0 +1,87 @@
+---
+layout: model
+title: English bge_base_english_v1_5_76_keys_phase_6_exp_v1 BGEEmbeddings from RishuD7
+author: John Snow Labs
+name: bge_base_english_v1_5_76_keys_phase_6_exp_v1
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, bge]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BGEEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_english_v1_5_76_keys_phase_6_exp_v1` is a English model originally trained by RishuD7.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_76_keys_phase_6_exp_v1_en_5.5.1_3.0_1737896542372.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_76_keys_phase_6_exp_v1_en_5.5.1_3.0_1737896542372.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = BGEEmbeddings.pretrained("bge_base_english_v1_5_76_keys_phase_6_exp_v1","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+
+val embeddings = BGEEmbeddings.pretrained("bge_base_english_v1_5_76_keys_phase_6_exp_v1","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp).toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_english_v1_5_76_keys_phase_6_exp_v1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[bge]|
+|Language:|en|
+|Size:|392.7 MB|
+
+## References
+
+https://huggingface.co/RishuD7/bge-base-en-v1.5-76-keys-phase-6-exp_v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-bge_base_english_v1_5_76_keys_phase_6_exp_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-bge_base_english_v1_5_76_keys_phase_6_exp_v1_pipeline_en.md
new file mode 100644
index 00000000000000..c53adeeec4d50f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-bge_base_english_v1_5_76_keys_phase_6_exp_v1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bge_base_english_v1_5_76_keys_phase_6_exp_v1_pipeline pipeline BGEEmbeddings from RishuD7
+author: John Snow Labs
+name: bge_base_english_v1_5_76_keys_phase_6_exp_v1_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_english_v1_5_76_keys_phase_6_exp_v1_pipeline` is a English model originally trained by RishuD7.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_76_keys_phase_6_exp_v1_pipeline_en_5.5.1_3.0_1737896567106.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_76_keys_phase_6_exp_v1_pipeline_en_5.5.1_3.0_1737896567106.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bge_base_english_v1_5_76_keys_phase_6_exp_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bge_base_english_v1_5_76_keys_phase_6_exp_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bge_base_english_v1_5_76_keys_phase_6_exp_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|392.7 MB|
+
+## References
+
+https://huggingface.co/RishuD7/bge-base-en-v1.5-76-keys-phase-6-exp_v1
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-biobert_ner_cased_en.md b/docs/_posts/ahmedlone127/2025-01-26-biobert_ner_cased_en.md
new file mode 100644
index 00000000000000..64dd14f40b3f5c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-biobert_ner_cased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English biobert_ner_cased BertForTokenClassification from lakshankarunathilake
+author: John Snow Labs
+name: biobert_ner_cased
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biobert_ner_cased` is a English model originally trained by lakshankarunathilake.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biobert_ner_cased_en_5.5.1_3.0_1737935569276.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biobert_ner_cased_en_5.5.1_3.0_1737935569276.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("biobert_ner_cased","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("biobert_ner_cased", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|biobert_ner_cased|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.1 MB|
+
+## References
+
+https://huggingface.co/lakshankarunathilake/biobert-ner-cased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-biobert_ner_cased_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-biobert_ner_cased_pipeline_en.md
new file mode 100644
index 00000000000000..e2d26062b186ea
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-biobert_ner_cased_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English biobert_ner_cased_pipeline pipeline BertForTokenClassification from lakshankarunathilake
+author: John Snow Labs
+name: biobert_ner_cased_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biobert_ner_cased_pipeline` is a English model originally trained by lakshankarunathilake.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biobert_ner_cased_pipeline_en_5.5.1_3.0_1737935591641.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biobert_ner_cased_pipeline_en_5.5.1_3.0_1737935591641.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("biobert_ner_cased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("biobert_ner_cased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|biobert_ner_cased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.1 MB|
+
+## References
+
+https://huggingface.co/lakshankarunathilake/biobert-ner-cased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-biobert_v1_1_pubmed_squad_v2_finetuned_covidqa_nepal_bhasa_batch_size_en.md b/docs/_posts/ahmedlone127/2025-01-26-biobert_v1_1_pubmed_squad_v2_finetuned_covidqa_nepal_bhasa_batch_size_en.md
new file mode 100644
index 00000000000000..6aaf88edff7eff
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-biobert_v1_1_pubmed_squad_v2_finetuned_covidqa_nepal_bhasa_batch_size_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English biobert_v1_1_pubmed_squad_v2_finetuned_covidqa_nepal_bhasa_batch_size BertForQuestionAnswering from chiendvhust
+author: John Snow Labs
+name: biobert_v1_1_pubmed_squad_v2_finetuned_covidqa_nepal_bhasa_batch_size
+date: 2025-01-26
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biobert_v1_1_pubmed_squad_v2_finetuned_covidqa_nepal_bhasa_batch_size` is a English model originally trained by chiendvhust.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biobert_v1_1_pubmed_squad_v2_finetuned_covidqa_nepal_bhasa_batch_size_en_5.5.1_3.0_1737918891983.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biobert_v1_1_pubmed_squad_v2_finetuned_covidqa_nepal_bhasa_batch_size_en_5.5.1_3.0_1737918891983.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("biobert_v1_1_pubmed_squad_v2_finetuned_covidqa_nepal_bhasa_batch_size","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("biobert_v1_1_pubmed_squad_v2_finetuned_covidqa_nepal_bhasa_batch_size", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|biobert_v1_1_pubmed_squad_v2_finetuned_covidqa_nepal_bhasa_batch_size|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.1 MB|
+
+## References
+
+https://huggingface.co/chiendvhust/biobert_v1.1_pubmed_squad_v2-finetuned-covidQA-new-batch-size
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-biobert_v1_1_pubmed_squad_v2_finetuned_covidqa_nepal_bhasa_batch_size_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-biobert_v1_1_pubmed_squad_v2_finetuned_covidqa_nepal_bhasa_batch_size_pipeline_en.md
new file mode 100644
index 00000000000000..983d387a7f36b2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-biobert_v1_1_pubmed_squad_v2_finetuned_covidqa_nepal_bhasa_batch_size_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English biobert_v1_1_pubmed_squad_v2_finetuned_covidqa_nepal_bhasa_batch_size_pipeline pipeline BertForQuestionAnswering from chiendvhust
+author: John Snow Labs
+name: biobert_v1_1_pubmed_squad_v2_finetuned_covidqa_nepal_bhasa_batch_size_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biobert_v1_1_pubmed_squad_v2_finetuned_covidqa_nepal_bhasa_batch_size_pipeline` is a English model originally trained by chiendvhust.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biobert_v1_1_pubmed_squad_v2_finetuned_covidqa_nepal_bhasa_batch_size_pipeline_en_5.5.1_3.0_1737918912933.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biobert_v1_1_pubmed_squad_v2_finetuned_covidqa_nepal_bhasa_batch_size_pipeline_en_5.5.1_3.0_1737918912933.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("biobert_v1_1_pubmed_squad_v2_finetuned_covidqa_nepal_bhasa_batch_size_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("biobert_v1_1_pubmed_squad_v2_finetuned_covidqa_nepal_bhasa_batch_size_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|biobert_v1_1_pubmed_squad_v2_finetuned_covidqa_nepal_bhasa_batch_size_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.1 MB|
+
+## References
+
+https://huggingface.co/chiendvhust/biobert_v1.1_pubmed_squad_v2-finetuned-covidQA-new-batch-size
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-biolinkbert_multicardioner_en.md b/docs/_posts/ahmedlone127/2025-01-26-biolinkbert_multicardioner_en.md
new file mode 100644
index 00000000000000..0924f0d79d27f2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-biolinkbert_multicardioner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English biolinkbert_multicardioner BertForTokenClassification from aaaksenova
+author: John Snow Labs
+name: biolinkbert_multicardioner
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biolinkbert_multicardioner` is a English model originally trained by aaaksenova.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biolinkbert_multicardioner_en_5.5.1_3.0_1737935919223.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biolinkbert_multicardioner_en_5.5.1_3.0_1737935919223.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("biolinkbert_multicardioner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("biolinkbert_multicardioner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|biolinkbert_multicardioner|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.5 MB|
+
+## References
+
+https://huggingface.co/aaaksenova/BioLinkBert_multicardioner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-biolinkbert_multicardioner_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-biolinkbert_multicardioner_pipeline_en.md
new file mode 100644
index 00000000000000..c2bc3fa63bdf26
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-biolinkbert_multicardioner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English biolinkbert_multicardioner_pipeline pipeline BertForTokenClassification from aaaksenova
+author: John Snow Labs
+name: biolinkbert_multicardioner_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biolinkbert_multicardioner_pipeline` is a English model originally trained by aaaksenova.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biolinkbert_multicardioner_pipeline_en_5.5.1_3.0_1737935939853.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biolinkbert_multicardioner_pipeline_en_5.5.1_3.0_1737935939853.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("biolinkbert_multicardioner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("biolinkbert_multicardioner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|biolinkbert_multicardioner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.5 MB|
+
+## References
+
+https://huggingface.co/aaaksenova/BioLinkBert_multicardioner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-biomed_ner_en.md b/docs/_posts/ahmedlone127/2025-01-26-biomed_ner_en.md
new file mode 100644
index 00000000000000..8cca3f35cef4f9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-biomed_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English biomed_ner DistilBertForTokenClassification from Pkompally
+author: John Snow Labs
+name: biomed_ner
+date: 2025-01-26
+tags: [bert, en, open_source, token_classification, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biomed_ner` is a English model originally trained by Pkompally.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biomed_ner_en_5.5.1_3.0_1737927294073.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biomed_ner_en_5.5.1_3.0_1737927294073.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("documents")
+    
+    
+tokenClassifier = DistilBertForTokenClassification.pretrained("biomed_ner","en") \
+            .setInputCols(["documents","token"]) \
+            .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCol("text") 
+    .setOutputCol("embeddings")
+    
+val tokenClassifier = DistilBertForTokenClassification  
+    .pretrained("biomed_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|biomed_ner|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|576.7 MB|
+
+## References
+
+References
+
+References
+
+https://huggingface.co/Pkompally/biomed-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-biomed_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-biomed_ner_pipeline_en.md
new file mode 100644
index 00000000000000..83b277a12233d6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-biomed_ner_pipeline_en.md
@@ -0,0 +1,72 @@
+---
+layout: model
+title: English biomed_ner_pipeline pipeline DeBertaForTokenClassification from venkatd
+author: John Snow Labs
+name: biomed_ner_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biomed_ner_pipeline` is a English model originally trained by venkatd.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biomed_ner_pipeline_en_5.5.1_3.0_1737927364063.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biomed_ner_pipeline_en_5.5.1_3.0_1737927364063.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("biomed_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("biomed_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|biomed_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|576.7 MB|
+
+## References
+
+References
+
+https://huggingface.co/venkatd/BioMed_NER
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-biomed_roberta_vilid_mlm_en.md b/docs/_posts/ahmedlone127/2025-01-26-biomed_roberta_vilid_mlm_en.md
new file mode 100644
index 00000000000000..941f0d7e59af02
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-biomed_roberta_vilid_mlm_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English biomed_roberta_vilid_mlm RoBertaEmbeddings from zhangzeyu
+author: John Snow Labs
+name: biomed_roberta_vilid_mlm
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biomed_roberta_vilid_mlm` is a English model originally trained by zhangzeyu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biomed_roberta_vilid_mlm_en_5.5.1_3.0_1737866203316.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biomed_roberta_vilid_mlm_en_5.5.1_3.0_1737866203316.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("biomed_roberta_vilid_mlm","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("biomed_roberta_vilid_mlm","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|biomed_roberta_vilid_mlm|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|466.0 MB|
+
+## References
+
+https://huggingface.co/zhangzeyu/BioMed-RoBERTa-VILID-MLM
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-biomed_roberta_vilid_mlm_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-biomed_roberta_vilid_mlm_pipeline_en.md
new file mode 100644
index 00000000000000..4ea2c0b790eef8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-biomed_roberta_vilid_mlm_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English biomed_roberta_vilid_mlm_pipeline pipeline RoBertaEmbeddings from zhangzeyu
+author: John Snow Labs
+name: biomed_roberta_vilid_mlm_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biomed_roberta_vilid_mlm_pipeline` is a English model originally trained by zhangzeyu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biomed_roberta_vilid_mlm_pipeline_en_5.5.1_3.0_1737866238677.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biomed_roberta_vilid_mlm_pipeline_en_5.5.1_3.0_1737866238677.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("biomed_roberta_vilid_mlm_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("biomed_roberta_vilid_mlm_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|biomed_roberta_vilid_mlm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.0 MB|
+
+## References
+
+https://huggingface.co/zhangzeyu/BioMed-RoBERTa-VILID-MLM
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-brabant_xvii_shallow_en.md b/docs/_posts/ahmedlone127/2025-01-26-brabant_xvii_shallow_en.md
new file mode 100644
index 00000000000000..67d8ae6c1cb0cf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-brabant_xvii_shallow_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English brabant_xvii_shallow BertEmbeddings from xaviergillard
+author: John Snow Labs
+name: brabant_xvii_shallow
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`brabant_xvii_shallow` is a English model originally trained by xaviergillard.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/brabant_xvii_shallow_en_5.5.1_3.0_1737908850898.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/brabant_xvii_shallow_en_5.5.1_3.0_1737908850898.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("brabant_xvii_shallow","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("brabant_xvii_shallow","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|brabant_xvii_shallow|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|408.1 MB|
+
+## References
+
+https://huggingface.co/xaviergillard/brabant-xvii-shallow
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-brabant_xvii_shallow_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-brabant_xvii_shallow_pipeline_en.md
new file mode 100644
index 00000000000000..e9f8fa9087e6d3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-brabant_xvii_shallow_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English brabant_xvii_shallow_pipeline pipeline BertEmbeddings from xaviergillard
+author: John Snow Labs
+name: brabant_xvii_shallow_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`brabant_xvii_shallow_pipeline` is a English model originally trained by xaviergillard.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/brabant_xvii_shallow_pipeline_en_5.5.1_3.0_1737908871483.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/brabant_xvii_shallow_pipeline_en_5.5.1_3.0_1737908871483.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("brabant_xvii_shallow_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("brabant_xvii_shallow_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|brabant_xvii_shallow_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|408.1 MB|
+
+## References
+
+https://huggingface.co/xaviergillard/brabant-xvii-shallow
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-brain_tumor_classification_krishna_exe_en.md b/docs/_posts/ahmedlone127/2025-01-26-brain_tumor_classification_krishna_exe_en.md
new file mode 100644
index 00000000000000..66d692c86ec3d0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-brain_tumor_classification_krishna_exe_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English brain_tumor_classification_krishna_exe SwinForImageClassification from krishna-exe
+author: John Snow Labs
+name: brain_tumor_classification_krishna_exe
+date: 2025-01-26
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`brain_tumor_classification_krishna_exe` is a English model originally trained by krishna-exe.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/brain_tumor_classification_krishna_exe_en_5.5.1_3.0_1737888821659.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/brain_tumor_classification_krishna_exe_en_5.5.1_3.0_1737888821659.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""brain_tumor_classification_krishna_exe","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("brain_tumor_classification_krishna_exe","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|brain_tumor_classification_krishna_exe|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/krishna-exe/brain-tumor-classification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-brain_tumor_classification_krishna_exe_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-brain_tumor_classification_krishna_exe_pipeline_en.md
new file mode 100644
index 00000000000000..611edcf39ce5bf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-brain_tumor_classification_krishna_exe_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English brain_tumor_classification_krishna_exe_pipeline pipeline SwinForImageClassification from krishna-exe
+author: John Snow Labs
+name: brain_tumor_classification_krishna_exe_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`brain_tumor_classification_krishna_exe_pipeline` is a English model originally trained by krishna-exe.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/brain_tumor_classification_krishna_exe_pipeline_en_5.5.1_3.0_1737888833506.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/brain_tumor_classification_krishna_exe_pipeline_en_5.5.1_3.0_1737888833506.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("brain_tumor_classification_krishna_exe_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("brain_tumor_classification_krishna_exe_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|brain_tumor_classification_krishna_exe_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/krishna-exe/brain-tumor-classification
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-brwac_v1_5__checkpoint8_en.md b/docs/_posts/ahmedlone127/2025-01-26-brwac_v1_5__checkpoint8_en.md
new file mode 100644
index 00000000000000..42fb56d9437b09
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-brwac_v1_5__checkpoint8_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English brwac_v1_5__checkpoint8 RoBertaEmbeddings from eduagarcia-temp
+author: John Snow Labs
+name: brwac_v1_5__checkpoint8
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`brwac_v1_5__checkpoint8` is a English model originally trained by eduagarcia-temp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/brwac_v1_5__checkpoint8_en_5.5.1_3.0_1737906573816.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/brwac_v1_5__checkpoint8_en_5.5.1_3.0_1737906573816.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("brwac_v1_5__checkpoint8","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("brwac_v1_5__checkpoint8","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|brwac_v1_5__checkpoint8|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|297.1 MB|
+
+## References
+
+https://huggingface.co/eduagarcia-temp/brwac_v1_5__checkpoint8
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-brwac_v1_5__checkpoint8_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-brwac_v1_5__checkpoint8_pipeline_en.md
new file mode 100644
index 00000000000000..5280edafe12743
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-brwac_v1_5__checkpoint8_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English brwac_v1_5__checkpoint8_pipeline pipeline RoBertaEmbeddings from eduagarcia-temp
+author: John Snow Labs
+name: brwac_v1_5__checkpoint8_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`brwac_v1_5__checkpoint8_pipeline` is a English model originally trained by eduagarcia-temp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/brwac_v1_5__checkpoint8_pipeline_en_5.5.1_3.0_1737906659856.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/brwac_v1_5__checkpoint8_pipeline_en_5.5.1_3.0_1737906659856.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("brwac_v1_5__checkpoint8_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("brwac_v1_5__checkpoint8_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|brwac_v1_5__checkpoint8_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|297.2 MB|
+
+## References
+
+https://huggingface.co/eduagarcia-temp/brwac_v1_5__checkpoint8
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_eli5_mlm_model_awastiang_en.md b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_eli5_mlm_model_awastiang_en.md
new file mode 100644
index 00000000000000..edeecb8391354e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_eli5_mlm_model_awastiang_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_eli5_mlm_model_awastiang RoBertaEmbeddings from awastiang
+author: John Snow Labs
+name: burmese_awesome_eli5_mlm_model_awastiang
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_eli5_mlm_model_awastiang` is a English model originally trained by awastiang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_awastiang_en_5.5.1_3.0_1737866440692.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_awastiang_en_5.5.1_3.0_1737866440692.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("burmese_awesome_eli5_mlm_model_awastiang","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("burmese_awesome_eli5_mlm_model_awastiang","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_eli5_mlm_model_awastiang|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/awastiang/my_awesome_eli5_mlm_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_eli5_mlm_model_awastiang_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_eli5_mlm_model_awastiang_pipeline_en.md
new file mode 100644
index 00000000000000..2cfc6ef26b0004
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_eli5_mlm_model_awastiang_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_eli5_mlm_model_awastiang_pipeline pipeline RoBertaEmbeddings from awastiang
+author: John Snow Labs
+name: burmese_awesome_eli5_mlm_model_awastiang_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_eli5_mlm_model_awastiang_pipeline` is a English model originally trained by awastiang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_awastiang_pipeline_en_5.5.1_3.0_1737866458794.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_awastiang_pipeline_en_5.5.1_3.0_1737866458794.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_eli5_mlm_model_awastiang_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_eli5_mlm_model_awastiang_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_eli5_mlm_model_awastiang_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/awastiang/my_awesome_eli5_mlm_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_eli5_mlm_model_imene_kolli_en.md b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_eli5_mlm_model_imene_kolli_en.md
new file mode 100644
index 00000000000000..86768659314489
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_eli5_mlm_model_imene_kolli_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_eli5_mlm_model_imene_kolli RoBertaEmbeddings from imene-kolli
+author: John Snow Labs
+name: burmese_awesome_eli5_mlm_model_imene_kolli
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_eli5_mlm_model_imene_kolli` is a English model originally trained by imene-kolli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_imene_kolli_en_5.5.1_3.0_1737906979224.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_imene_kolli_en_5.5.1_3.0_1737906979224.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("burmese_awesome_eli5_mlm_model_imene_kolli","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("burmese_awesome_eli5_mlm_model_imene_kolli","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_eli5_mlm_model_imene_kolli|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/imene-kolli/my_awesome_eli5_mlm_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_eli5_mlm_model_imene_kolli_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_eli5_mlm_model_imene_kolli_pipeline_en.md
new file mode 100644
index 00000000000000..784fca9a0da7e5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_eli5_mlm_model_imene_kolli_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_eli5_mlm_model_imene_kolli_pipeline pipeline RoBertaEmbeddings from imene-kolli
+author: John Snow Labs
+name: burmese_awesome_eli5_mlm_model_imene_kolli_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_eli5_mlm_model_imene_kolli_pipeline` is a English model originally trained by imene-kolli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_imene_kolli_pipeline_en_5.5.1_3.0_1737906994887.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_imene_kolli_pipeline_en_5.5.1_3.0_1737906994887.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_eli5_mlm_model_imene_kolli_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_eli5_mlm_model_imene_kolli_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_eli5_mlm_model_imene_kolli_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/imene-kolli/my_awesome_eli5_mlm_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_eli5_mlm_model_keagan2346_en.md b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_eli5_mlm_model_keagan2346_en.md
new file mode 100644
index 00000000000000..302412dc09aa9e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_eli5_mlm_model_keagan2346_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_eli5_mlm_model_keagan2346 RoBertaEmbeddings from keagan2346
+author: John Snow Labs
+name: burmese_awesome_eli5_mlm_model_keagan2346
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_eli5_mlm_model_keagan2346` is a English model originally trained by keagan2346.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_keagan2346_en_5.5.1_3.0_1737906791447.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_keagan2346_en_5.5.1_3.0_1737906791447.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("burmese_awesome_eli5_mlm_model_keagan2346","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("burmese_awesome_eli5_mlm_model_keagan2346","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_eli5_mlm_model_keagan2346|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/keagan2346/my_awesome_eli5_mlm_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_eli5_mlm_model_keagan2346_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_eli5_mlm_model_keagan2346_pipeline_en.md
new file mode 100644
index 00000000000000..c4219fb77ca17a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_eli5_mlm_model_keagan2346_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_eli5_mlm_model_keagan2346_pipeline pipeline RoBertaEmbeddings from keagan2346
+author: John Snow Labs
+name: burmese_awesome_eli5_mlm_model_keagan2346_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_eli5_mlm_model_keagan2346_pipeline` is a English model originally trained by keagan2346.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_keagan2346_pipeline_en_5.5.1_3.0_1737906807270.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_keagan2346_pipeline_en_5.5.1_3.0_1737906807270.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_eli5_mlm_model_keagan2346_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_eli5_mlm_model_keagan2346_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_eli5_mlm_model_keagan2346_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/keagan2346/my_awesome_eli5_mlm_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_eli5_mlm_model_keffy04_en.md b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_eli5_mlm_model_keffy04_en.md
new file mode 100644
index 00000000000000..382248513318f3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_eli5_mlm_model_keffy04_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_eli5_mlm_model_keffy04 RoBertaEmbeddings from keffy04
+author: John Snow Labs
+name: burmese_awesome_eli5_mlm_model_keffy04
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_eli5_mlm_model_keffy04` is a English model originally trained by keffy04.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_keffy04_en_5.5.1_3.0_1737906766069.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_keffy04_en_5.5.1_3.0_1737906766069.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("burmese_awesome_eli5_mlm_model_keffy04","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("burmese_awesome_eli5_mlm_model_keffy04","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_eli5_mlm_model_keffy04|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/keffy04/my_awesome_eli5_mlm_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_eli5_mlm_model_keffy04_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_eli5_mlm_model_keffy04_pipeline_en.md
new file mode 100644
index 00000000000000..61f4137e48217b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_eli5_mlm_model_keffy04_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_eli5_mlm_model_keffy04_pipeline pipeline RoBertaEmbeddings from keffy04
+author: John Snow Labs
+name: burmese_awesome_eli5_mlm_model_keffy04_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_eli5_mlm_model_keffy04_pipeline` is a English model originally trained by keffy04.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_keffy04_pipeline_en_5.5.1_3.0_1737906782752.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_keffy04_pipeline_en_5.5.1_3.0_1737906782752.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_eli5_mlm_model_keffy04_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_eli5_mlm_model_keffy04_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_eli5_mlm_model_keffy04_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/keffy04/my_awesome_eli5_mlm_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_eli5_mlm_model_waynetiang_en.md b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_eli5_mlm_model_waynetiang_en.md
new file mode 100644
index 00000000000000..541de962329e6a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_eli5_mlm_model_waynetiang_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_eli5_mlm_model_waynetiang RoBertaEmbeddings from Waynetiang
+author: John Snow Labs
+name: burmese_awesome_eli5_mlm_model_waynetiang
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_eli5_mlm_model_waynetiang` is a English model originally trained by Waynetiang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_waynetiang_en_5.5.1_3.0_1737906469301.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_waynetiang_en_5.5.1_3.0_1737906469301.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("burmese_awesome_eli5_mlm_model_waynetiang","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("burmese_awesome_eli5_mlm_model_waynetiang","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_eli5_mlm_model_waynetiang|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|306.4 MB|
+
+## References
+
+https://huggingface.co/Waynetiang/my_awesome_eli5_mlm_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_eli5_mlm_model_waynetiang_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_eli5_mlm_model_waynetiang_pipeline_en.md
new file mode 100644
index 00000000000000..80eb9fd29e9d7c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_eli5_mlm_model_waynetiang_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_eli5_mlm_model_waynetiang_pipeline pipeline RoBertaEmbeddings from Waynetiang
+author: John Snow Labs
+name: burmese_awesome_eli5_mlm_model_waynetiang_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_eli5_mlm_model_waynetiang_pipeline` is a English model originally trained by Waynetiang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_waynetiang_pipeline_en_5.5.1_3.0_1737906485954.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_waynetiang_pipeline_en_5.5.1_3.0_1737906485954.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_eli5_mlm_model_waynetiang_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_eli5_mlm_model_waynetiang_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_eli5_mlm_model_waynetiang_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/Waynetiang/my_awesome_eli5_mlm_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_andrei22george_en.md b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_andrei22george_en.md
new file mode 100644
index 00000000000000..a32208d08a81c1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_andrei22george_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_andrei22george DistilBertForSequenceClassification from andrei22george
+author: John Snow Labs
+name: burmese_awesome_model_andrei22george
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_andrei22george` is a English model originally trained by andrei22george.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_andrei22george_en_5.5.1_3.0_1737929251937.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_andrei22george_en_5.5.1_3.0_1737929251937.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_andrei22george","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_andrei22george", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_andrei22george|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/andrei22george/my_awesome_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_andrei22george_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_andrei22george_pipeline_en.md
new file mode 100644
index 00000000000000..e69ab86012f816
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_andrei22george_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_andrei22george_pipeline pipeline DistilBertForSequenceClassification from andrei22george
+author: John Snow Labs
+name: burmese_awesome_model_andrei22george_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_andrei22george_pipeline` is a English model originally trained by andrei22george.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_andrei22george_pipeline_en_5.5.1_3.0_1737929266134.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_andrei22george_pipeline_en_5.5.1_3.0_1737929266134.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_andrei22george_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_andrei22george_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_andrei22george_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/andrei22george/my_awesome_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_dalia123123_en.md b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_dalia123123_en.md
new file mode 100644
index 00000000000000..60a72ad6706f54
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_dalia123123_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_dalia123123 DistilBertForSequenceClassification from dalia123123
+author: John Snow Labs
+name: burmese_awesome_model_dalia123123
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_dalia123123` is a English model originally trained by dalia123123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_dalia123123_en_5.5.1_3.0_1737873620928.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_dalia123123_en_5.5.1_3.0_1737873620928.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_dalia123123","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_dalia123123", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_dalia123123|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/dalia123123/my_awesome_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_dalia123123_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_dalia123123_pipeline_en.md
new file mode 100644
index 00000000000000..7bbd2156e695ab
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_dalia123123_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_dalia123123_pipeline pipeline DistilBertForSequenceClassification from dalia123123
+author: John Snow Labs
+name: burmese_awesome_model_dalia123123_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_dalia123123_pipeline` is a English model originally trained by dalia123123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_dalia123123_pipeline_en_5.5.1_3.0_1737873635122.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_dalia123123_pipeline_en_5.5.1_3.0_1737873635122.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_dalia123123_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_dalia123123_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_dalia123123_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/dalia123123/my_awesome_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_daniboar_en.md b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_daniboar_en.md
new file mode 100644
index 00000000000000..4b3ccd9032e4e9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_daniboar_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_daniboar DistilBertForSequenceClassification from daniboar
+author: John Snow Labs
+name: burmese_awesome_model_daniboar
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_daniboar` is a English model originally trained by daniboar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_daniboar_en_5.5.1_3.0_1737904856372.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_daniboar_en_5.5.1_3.0_1737904856372.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_daniboar","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_daniboar", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_daniboar|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/daniboar/my_awesome_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_daniboar_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_daniboar_pipeline_en.md
new file mode 100644
index 00000000000000..6f9a98b757ee4b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_daniboar_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_daniboar_pipeline pipeline DistilBertForSequenceClassification from daniboar
+author: John Snow Labs
+name: burmese_awesome_model_daniboar_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_daniboar_pipeline` is a English model originally trained by daniboar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_daniboar_pipeline_en_5.5.1_3.0_1737904869295.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_daniboar_pipeline_en_5.5.1_3.0_1737904869295.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_daniboar_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_daniboar_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_daniboar_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/daniboar/my_awesome_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_danielfujiya_en.md b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_danielfujiya_en.md
new file mode 100644
index 00000000000000..4df4fe39218193
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_danielfujiya_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_danielfujiya DistilBertForSequenceClassification from danielfujiya
+author: John Snow Labs
+name: burmese_awesome_model_danielfujiya
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_danielfujiya` is a English model originally trained by danielfujiya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_danielfujiya_en_5.5.1_3.0_1737905221297.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_danielfujiya_en_5.5.1_3.0_1737905221297.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_danielfujiya","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_danielfujiya", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_danielfujiya|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/danielfujiya/my_awesome_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_danielfujiya_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_danielfujiya_pipeline_en.md
new file mode 100644
index 00000000000000..27212bf57c0813
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_danielfujiya_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_danielfujiya_pipeline pipeline DistilBertForSequenceClassification from danielfujiya
+author: John Snow Labs
+name: burmese_awesome_model_danielfujiya_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_danielfujiya_pipeline` is a English model originally trained by danielfujiya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_danielfujiya_pipeline_en_5.5.1_3.0_1737905234605.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_danielfujiya_pipeline_en_5.5.1_3.0_1737905234605.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_danielfujiya_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_danielfujiya_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_danielfujiya_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/danielfujiya/my_awesome_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_icy123_en.md b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_icy123_en.md
new file mode 100644
index 00000000000000..77a92fde588035
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_icy123_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_icy123 DistilBertForSequenceClassification from icy123
+author: John Snow Labs
+name: burmese_awesome_model_icy123
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_icy123` is a English model originally trained by icy123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_icy123_en_5.5.1_3.0_1737905021485.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_icy123_en_5.5.1_3.0_1737905021485.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_icy123","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_icy123", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_icy123|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/icy123/my_awesome_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_icy123_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_icy123_pipeline_en.md
new file mode 100644
index 00000000000000..06189f2f6d82a2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_icy123_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_icy123_pipeline pipeline DistilBertForSequenceClassification from icy123
+author: John Snow Labs
+name: burmese_awesome_model_icy123_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_icy123_pipeline` is a English model originally trained by icy123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_icy123_pipeline_en_5.5.1_3.0_1737905034662.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_icy123_pipeline_en_5.5.1_3.0_1737905034662.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_icy123_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_icy123_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_icy123_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/icy123/my_awesome_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_isyufeng_en.md b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_isyufeng_en.md
new file mode 100644
index 00000000000000..e9cc67a43aa6d9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_isyufeng_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_isyufeng DistilBertForSequenceClassification from isYufeng
+author: John Snow Labs
+name: burmese_awesome_model_isyufeng
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_isyufeng` is a English model originally trained by isYufeng.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_isyufeng_en_5.5.1_3.0_1737904660287.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_isyufeng_en_5.5.1_3.0_1737904660287.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_isyufeng","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_isyufeng", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_isyufeng|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/isYufeng/my_awesome_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_isyufeng_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_isyufeng_pipeline_en.md
new file mode 100644
index 00000000000000..182ab97a52b8ac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_isyufeng_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_isyufeng_pipeline pipeline DistilBertForSequenceClassification from isYufeng
+author: John Snow Labs
+name: burmese_awesome_model_isyufeng_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_isyufeng_pipeline` is a English model originally trained by isYufeng.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_isyufeng_pipeline_en_5.5.1_3.0_1737904673538.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_isyufeng_pipeline_en_5.5.1_3.0_1737904673538.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_isyufeng_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_isyufeng_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_isyufeng_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/isYufeng/my_awesome_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_jevon11_en.md b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_jevon11_en.md
new file mode 100644
index 00000000000000..d6327786860d65
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_jevon11_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_jevon11 DistilBertForSequenceClassification from jevon11
+author: John Snow Labs
+name: burmese_awesome_model_jevon11
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_jevon11` is a English model originally trained by jevon11.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_jevon11_en_5.5.1_3.0_1737905327252.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_jevon11_en_5.5.1_3.0_1737905327252.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_jevon11","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_jevon11", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_jevon11|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/jevon11/my_awesome_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_jevon11_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_jevon11_pipeline_en.md
new file mode 100644
index 00000000000000..752c2e325a7f1b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_jevon11_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_jevon11_pipeline pipeline DistilBertForSequenceClassification from jevon11
+author: John Snow Labs
+name: burmese_awesome_model_jevon11_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_jevon11_pipeline` is a English model originally trained by jevon11.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_jevon11_pipeline_en_5.5.1_3.0_1737905340093.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_jevon11_pipeline_en_5.5.1_3.0_1737905340093.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_jevon11_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_jevon11_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_jevon11_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/jevon11/my_awesome_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_khatrimann_en.md b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_khatrimann_en.md
new file mode 100644
index 00000000000000..c208be5c338378
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_khatrimann_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_khatrimann DistilBertForSequenceClassification from khatrimann
+author: John Snow Labs
+name: burmese_awesome_model_khatrimann
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_khatrimann` is a English model originally trained by khatrimann.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_khatrimann_en_5.5.1_3.0_1737873886256.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_khatrimann_en_5.5.1_3.0_1737873886256.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_khatrimann","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_khatrimann", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_khatrimann|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/khatrimann/my_awesome_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_khatrimann_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_khatrimann_pipeline_en.md
new file mode 100644
index 00000000000000..bf64cbc061fa97
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_khatrimann_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_khatrimann_pipeline pipeline DistilBertForSequenceClassification from khatrimann
+author: John Snow Labs
+name: burmese_awesome_model_khatrimann_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_khatrimann_pipeline` is a English model originally trained by khatrimann.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_khatrimann_pipeline_en_5.5.1_3.0_1737873901317.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_khatrimann_pipeline_en_5.5.1_3.0_1737873901317.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_khatrimann_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_khatrimann_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_khatrimann_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/khatrimann/my_awesome_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_lwizz_en.md b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_lwizz_en.md
new file mode 100644
index 00000000000000..d3fa780aa5a316
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_lwizz_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_lwizz DistilBertForSequenceClassification from Lwizz
+author: John Snow Labs
+name: burmese_awesome_model_lwizz
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_lwizz` is a English model originally trained by Lwizz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_lwizz_en_5.5.1_3.0_1737929568745.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_lwizz_en_5.5.1_3.0_1737929568745.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_lwizz","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_lwizz", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_lwizz|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Lwizz/my_awesome_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_lwizz_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_lwizz_pipeline_en.md
new file mode 100644
index 00000000000000..df42a080d66440
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_lwizz_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_lwizz_pipeline pipeline DistilBertForSequenceClassification from Lwizz
+author: John Snow Labs
+name: burmese_awesome_model_lwizz_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_lwizz_pipeline` is a English model originally trained by Lwizz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_lwizz_pipeline_en_5.5.1_3.0_1737929581935.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_lwizz_pipeline_en_5.5.1_3.0_1737929581935.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_lwizz_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_lwizz_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_lwizz_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Lwizz/my_awesome_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_nicolehao7_en.md b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_nicolehao7_en.md
new file mode 100644
index 00000000000000..ea0369f020de29
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_nicolehao7_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_nicolehao7 DistilBertForSequenceClassification from nicolehao7
+author: John Snow Labs
+name: burmese_awesome_model_nicolehao7
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_nicolehao7` is a English model originally trained by nicolehao7.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_nicolehao7_en_5.5.1_3.0_1737873357729.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_nicolehao7_en_5.5.1_3.0_1737873357729.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_nicolehao7","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_nicolehao7", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_nicolehao7|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.9 MB|
+
+## References
+
+https://huggingface.co/nicolehao7/my_awesome_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_nicolehao7_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_nicolehao7_pipeline_en.md
new file mode 100644
index 00000000000000..31e734f749140c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_nicolehao7_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_nicolehao7_pipeline pipeline DistilBertForSequenceClassification from nicolehao7
+author: John Snow Labs
+name: burmese_awesome_model_nicolehao7_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_nicolehao7_pipeline` is a English model originally trained by nicolehao7.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_nicolehao7_pipeline_en_5.5.1_3.0_1737873371524.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_nicolehao7_pipeline_en_5.5.1_3.0_1737873371524.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_nicolehao7_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_nicolehao7_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_nicolehao7_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.9 MB|
+
+## References
+
+https://huggingface.co/nicolehao7/my_awesome_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_okita12345_en.md b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_okita12345_en.md
new file mode 100644
index 00000000000000..aec951b1b9633b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_okita12345_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_okita12345 XlmRoBertaForSequenceClassification from Okita12345
+author: John Snow Labs
+name: burmese_awesome_model_okita12345
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_okita12345` is a English model originally trained by Okita12345.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_okita12345_en_5.5.1_3.0_1737885749117.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_okita12345_en_5.5.1_3.0_1737885749117.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("burmese_awesome_model_okita12345","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("burmese_awesome_model_okita12345", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_okita12345|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|834.8 MB|
+
+## References
+
+https://huggingface.co/Okita12345/my_awesome_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_okita12345_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_okita12345_pipeline_en.md
new file mode 100644
index 00000000000000..07628df94e6991
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_okita12345_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_okita12345_pipeline pipeline XlmRoBertaForSequenceClassification from Okita12345
+author: John Snow Labs
+name: burmese_awesome_model_okita12345_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_okita12345_pipeline` is a English model originally trained by Okita12345.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_okita12345_pipeline_en_5.5.1_3.0_1737885859993.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_okita12345_pipeline_en_5.5.1_3.0_1737885859993.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_okita12345_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_okita12345_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_okita12345_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|834.9 MB|
+
+## References
+
+https://huggingface.co/Okita12345/my_awesome_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_sachi020991_en.md b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_sachi020991_en.md
new file mode 100644
index 00000000000000..bfd984a180e141
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_sachi020991_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_sachi020991 DistilBertForSequenceClassification from sachi020991
+author: John Snow Labs
+name: burmese_awesome_model_sachi020991
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_sachi020991` is a English model originally trained by sachi020991.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_sachi020991_en_5.5.1_3.0_1737928844867.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_sachi020991_en_5.5.1_3.0_1737928844867.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_sachi020991","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_sachi020991", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_sachi020991|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/sachi020991/my_awesome_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_sachi020991_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_sachi020991_pipeline_en.md
new file mode 100644
index 00000000000000..cc4b574ccb8254
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_sachi020991_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_sachi020991_pipeline pipeline DistilBertForSequenceClassification from sachi020991
+author: John Snow Labs
+name: burmese_awesome_model_sachi020991_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_sachi020991_pipeline` is a English model originally trained by sachi020991.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_sachi020991_pipeline_en_5.5.1_3.0_1737928858449.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_sachi020991_pipeline_en_5.5.1_3.0_1737928858449.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_sachi020991_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_sachi020991_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_sachi020991_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/sachi020991/my_awesome_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_storuky_en.md b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_storuky_en.md
new file mode 100644
index 00000000000000..41508d49cb6646
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_storuky_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_storuky DistilBertForSequenceClassification from storuky
+author: John Snow Labs
+name: burmese_awesome_model_storuky
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_storuky` is a English model originally trained by storuky.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_storuky_en_5.5.1_3.0_1737873114852.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_storuky_en_5.5.1_3.0_1737873114852.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_storuky","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_storuky", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_storuky|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/storuky/my_awesome_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_storuky_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_storuky_pipeline_en.md
new file mode 100644
index 00000000000000..e2d40494a06480
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_storuky_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_storuky_pipeline pipeline DistilBertForSequenceClassification from storuky
+author: John Snow Labs
+name: burmese_awesome_model_storuky_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_storuky_pipeline` is a English model originally trained by storuky.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_storuky_pipeline_en_5.5.1_3.0_1737873129787.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_storuky_pipeline_en_5.5.1_3.0_1737873129787.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_storuky_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_storuky_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_storuky_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/storuky/my_awesome_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_zhangsan4_en.md b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_zhangsan4_en.md
new file mode 100644
index 00000000000000..46ff404f8370e3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_zhangsan4_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_zhangsan4 DistilBertForSequenceClassification from zhangsan4
+author: John Snow Labs
+name: burmese_awesome_model_zhangsan4
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_zhangsan4` is a English model originally trained by zhangsan4.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_zhangsan4_en_5.5.1_3.0_1737929386740.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_zhangsan4_en_5.5.1_3.0_1737929386740.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_zhangsan4","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_zhangsan4", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_zhangsan4|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/zhangsan4/my_awesome_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_zhangsan4_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_zhangsan4_pipeline_en.md
new file mode 100644
index 00000000000000..eaeb783e3a5fd2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_model_zhangsan4_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_zhangsan4_pipeline pipeline DistilBertForSequenceClassification from zhangsan4
+author: John Snow Labs
+name: burmese_awesome_model_zhangsan4_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_zhangsan4_pipeline` is a English model originally trained by zhangsan4.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_zhangsan4_pipeline_en_5.5.1_3.0_1737929400230.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_zhangsan4_pipeline_en_5.5.1_3.0_1737929400230.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_zhangsan4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_zhangsan4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_zhangsan4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/zhangsan4/my_awesome_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_opus_books_model_hoangttrang_en.md b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_opus_books_model_hoangttrang_en.md
new file mode 100644
index 00000000000000..8cdef75affedd7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_opus_books_model_hoangttrang_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_opus_books_model_hoangttrang MarianTransformer from hoangttrang
+author: John Snow Labs
+name: burmese_awesome_opus_books_model_hoangttrang
+date: 2025-01-26
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_opus_books_model_hoangttrang` is a English model originally trained by hoangttrang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_hoangttrang_en_5.5.1_3.0_1737864241726.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_hoangttrang_en_5.5.1_3.0_1737864241726.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("burmese_awesome_opus_books_model_hoangttrang","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("burmese_awesome_opus_books_model_hoangttrang","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_opus_books_model_hoangttrang|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|475.8 MB|
+
+## References
+
+https://huggingface.co/hoangttrang/my_awesome_opus_books_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_opus_books_model_hoangttrang_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_opus_books_model_hoangttrang_pipeline_en.md
new file mode 100644
index 00000000000000..13dda5a51a2caf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_opus_books_model_hoangttrang_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_opus_books_model_hoangttrang_pipeline pipeline MarianTransformer from hoangttrang
+author: John Snow Labs
+name: burmese_awesome_opus_books_model_hoangttrang_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_opus_books_model_hoangttrang_pipeline` is a English model originally trained by hoangttrang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_hoangttrang_pipeline_en_5.5.1_3.0_1737864267541.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_hoangttrang_pipeline_en_5.5.1_3.0_1737864267541.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_opus_books_model_hoangttrang_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_opus_books_model_hoangttrang_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_opus_books_model_hoangttrang_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|476.4 MB|
+
+## References
+
+https://huggingface.co/hoangttrang/my_awesome_opus_books_model
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_wnut_model_ali972_en.md b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_wnut_model_ali972_en.md
new file mode 100644
index 00000000000000..10b531757e8004
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_wnut_model_ali972_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_ali972 DistilBertForTokenClassification from ali972
+author: John Snow Labs
+name: burmese_awesome_wnut_model_ali972
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_ali972` is a English model originally trained by ali972.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_ali972_en_5.5.1_3.0_1737909885901.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_ali972_en_5.5.1_3.0_1737909885901.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_ali972","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_ali972", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_ali972|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/ali972/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_wnut_model_ali972_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_wnut_model_ali972_pipeline_en.md
new file mode 100644
index 00000000000000..83ff16c73cd18d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_wnut_model_ali972_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_ali972_pipeline pipeline DistilBertForTokenClassification from ali972
+author: John Snow Labs
+name: burmese_awesome_wnut_model_ali972_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_ali972_pipeline` is a English model originally trained by ali972.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_ali972_pipeline_en_5.5.1_3.0_1737909898223.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_ali972_pipeline_en_5.5.1_3.0_1737909898223.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_wnut_model_ali972_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_wnut_model_ali972_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_ali972_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/ali972/my_awesome_wnut_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_wnut_model_fcheboukh_en.md b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_wnut_model_fcheboukh_en.md
new file mode 100644
index 00000000000000..5fc2d81ad33def
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_wnut_model_fcheboukh_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_fcheboukh DistilBertForTokenClassification from fcheboukh
+author: John Snow Labs
+name: burmese_awesome_wnut_model_fcheboukh
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_fcheboukh` is a English model originally trained by fcheboukh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_fcheboukh_en_5.5.1_3.0_1737909606318.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_fcheboukh_en_5.5.1_3.0_1737909606318.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_fcheboukh","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_fcheboukh", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_fcheboukh|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/fcheboukh/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_wnut_model_fcheboukh_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_wnut_model_fcheboukh_pipeline_en.md
new file mode 100644
index 00000000000000..8d9009dfa4d480
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-burmese_awesome_wnut_model_fcheboukh_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_fcheboukh_pipeline pipeline DistilBertForTokenClassification from fcheboukh
+author: John Snow Labs
+name: burmese_awesome_wnut_model_fcheboukh_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_fcheboukh_pipeline` is a English model originally trained by fcheboukh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_fcheboukh_pipeline_en_5.5.1_3.0_1737909619077.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_fcheboukh_pipeline_en_5.5.1_3.0_1737909619077.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_wnut_model_fcheboukh_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_wnut_model_fcheboukh_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_fcheboukh_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/fcheboukh/my_awesome_wnut_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-burmese_ner_arbertv2_en.md b/docs/_posts/ahmedlone127/2025-01-26-burmese_ner_arbertv2_en.md
new file mode 100644
index 00000000000000..ecd972d2b8d4c9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-burmese_ner_arbertv2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_ner_arbertv2 BertForTokenClassification from ahmedoumar
+author: John Snow Labs
+name: burmese_ner_arbertv2
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_ner_arbertv2` is a English model originally trained by ahmedoumar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_ner_arbertv2_en_5.5.1_3.0_1737934852233.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_ner_arbertv2_en_5.5.1_3.0_1737934852233.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("burmese_ner_arbertv2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("burmese_ner_arbertv2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_ner_arbertv2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|607.3 MB|
+
+## References
+
+https://huggingface.co/ahmedoumar/my_ner_ARBERTv2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-burmese_ner_arbertv2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-burmese_ner_arbertv2_pipeline_en.md
new file mode 100644
index 00000000000000..20f29532193c77
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-burmese_ner_arbertv2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_ner_arbertv2_pipeline pipeline BertForTokenClassification from ahmedoumar
+author: John Snow Labs
+name: burmese_ner_arbertv2_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_ner_arbertv2_pipeline` is a English model originally trained by ahmedoumar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_ner_arbertv2_pipeline_en_5.5.1_3.0_1737934883328.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_ner_arbertv2_pipeline_en_5.5.1_3.0_1737934883328.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_ner_arbertv2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_ner_arbertv2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_ner_arbertv2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|607.3 MB|
+
+## References
+
+https://huggingface.co/ahmedoumar/my_ner_ARBERTv2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-burmese_ner_marbertv2_en.md b/docs/_posts/ahmedlone127/2025-01-26-burmese_ner_marbertv2_en.md
new file mode 100644
index 00000000000000..df5dd81c9f13b1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-burmese_ner_marbertv2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_ner_marbertv2 BertForTokenClassification from ahmedoumar
+author: John Snow Labs
+name: burmese_ner_marbertv2
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_ner_marbertv2` is a English model originally trained by ahmedoumar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_ner_marbertv2_en_5.5.1_3.0_1737934285778.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_ner_marbertv2_en_5.5.1_3.0_1737934285778.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("burmese_ner_marbertv2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("burmese_ner_marbertv2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_ner_marbertv2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|606.7 MB|
+
+## References
+
+https://huggingface.co/ahmedoumar/my_ner_MARBERTv2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-burmese_ner_marbertv2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-burmese_ner_marbertv2_pipeline_en.md
new file mode 100644
index 00000000000000..0a001861fc1b44
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-burmese_ner_marbertv2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_ner_marbertv2_pipeline pipeline BertForTokenClassification from ahmedoumar
+author: John Snow Labs
+name: burmese_ner_marbertv2_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_ner_marbertv2_pipeline` is a English model originally trained by ahmedoumar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_ner_marbertv2_pipeline_en_5.5.1_3.0_1737934317377.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_ner_marbertv2_pipeline_en_5.5.1_3.0_1737934317377.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_ner_marbertv2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_ner_marbertv2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_ner_marbertv2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|606.7 MB|
+
+## References
+
+https://huggingface.co/ahmedoumar/my_ner_MARBERTv2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-capstone_keywordsearch_en.md b/docs/_posts/ahmedlone127/2025-01-26-capstone_keywordsearch_en.md
new file mode 100644
index 00000000000000..13fb9fd8bfc01f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-capstone_keywordsearch_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English capstone_keywordsearch BertForTokenClassification from HyoungGeun
+author: John Snow Labs
+name: capstone_keywordsearch
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`capstone_keywordsearch` is a English model originally trained by HyoungGeun.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/capstone_keywordsearch_en_5.5.1_3.0_1737935803542.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/capstone_keywordsearch_en_5.5.1_3.0_1737935803542.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("capstone_keywordsearch","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("capstone_keywordsearch", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|capstone_keywordsearch|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/HyoungGeun/Capstone_KeywordSearch
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-capstone_keywordsearch_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-capstone_keywordsearch_pipeline_en.md
new file mode 100644
index 00000000000000..b6531e9aae3341
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-capstone_keywordsearch_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English capstone_keywordsearch_pipeline pipeline BertForTokenClassification from HyoungGeun
+author: John Snow Labs
+name: capstone_keywordsearch_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`capstone_keywordsearch_pipeline` is a English model originally trained by HyoungGeun.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/capstone_keywordsearch_pipeline_en_5.5.1_3.0_1737935826078.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/capstone_keywordsearch_pipeline_en_5.5.1_3.0_1737935826078.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("capstone_keywordsearch_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("capstone_keywordsearch_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|capstone_keywordsearch_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/HyoungGeun/Capstone_KeywordSearch
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-checks_en.md b/docs/_posts/ahmedlone127/2025-01-26-checks_en.md
new file mode 100644
index 00000000000000..50a4b9dd8bd1db
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-checks_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English checks DistilBertForSequenceClassification from PolinaSemeniuk
+author: John Snow Labs
+name: checks
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`checks` is a English model originally trained by PolinaSemeniuk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/checks_en_5.5.1_3.0_1737873312563.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/checks_en_5.5.1_3.0_1737873312563.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("checks","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("checks", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|checks|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/PolinaSemeniuk/checks
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-checks_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-checks_pipeline_en.md
new file mode 100644
index 00000000000000..77f932d3969bed
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-checks_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English checks_pipeline pipeline DistilBertForSequenceClassification from PolinaSemeniuk
+author: John Snow Labs
+name: checks_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`checks_pipeline` is a English model originally trained by PolinaSemeniuk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/checks_pipeline_en_5.5.1_3.0_1737873326304.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/checks_pipeline_en_5.5.1_3.0_1737873326304.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("checks_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("checks_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|checks_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/PolinaSemeniuk/checks
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-chinese_question_answering_en.md b/docs/_posts/ahmedlone127/2025-01-26-chinese_question_answering_en.md
new file mode 100644
index 00000000000000..ac14a040d797db
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-chinese_question_answering_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English chinese_question_answering BertForQuestionAnswering from TingChenChang
+author: John Snow Labs
+name: chinese_question_answering
+date: 2025-01-26
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`chinese_question_answering` is a English model originally trained by TingChenChang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/chinese_question_answering_en_5.5.1_3.0_1737919359863.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/chinese_question_answering_en_5.5.1_3.0_1737919359863.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("chinese_question_answering","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("chinese_question_answering", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|chinese_question_answering|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|381.1 MB|
+
+## References
+
+https://huggingface.co/TingChenChang/chinese-question-answering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-chinese_question_answering_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-chinese_question_answering_pipeline_en.md
new file mode 100644
index 00000000000000..b5738adce1fe01
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-chinese_question_answering_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English chinese_question_answering_pipeline pipeline BertForQuestionAnswering from TingChenChang
+author: John Snow Labs
+name: chinese_question_answering_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`chinese_question_answering_pipeline` is a English model originally trained by TingChenChang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/chinese_question_answering_pipeline_en_5.5.1_3.0_1737919379627.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/chinese_question_answering_pipeline_en_5.5.1_3.0_1737919379627.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("chinese_question_answering_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("chinese_question_answering_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|chinese_question_answering_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|381.1 MB|
+
+## References
+
+https://huggingface.co/TingChenChang/chinese-question-answering
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-chinese_roberta_wwm_ext_2_0_8_en.md b/docs/_posts/ahmedlone127/2025-01-26-chinese_roberta_wwm_ext_2_0_8_en.md
new file mode 100644
index 00000000000000..c2e03909944cd0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-chinese_roberta_wwm_ext_2_0_8_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English chinese_roberta_wwm_ext_2_0_8 BertForQuestionAnswering from DaydreamerF
+author: John Snow Labs
+name: chinese_roberta_wwm_ext_2_0_8
+date: 2025-01-26
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`chinese_roberta_wwm_ext_2_0_8` is a English model originally trained by DaydreamerF.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/chinese_roberta_wwm_ext_2_0_8_en_5.5.1_3.0_1737919168215.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/chinese_roberta_wwm_ext_2_0_8_en_5.5.1_3.0_1737919168215.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("chinese_roberta_wwm_ext_2_0_8","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("chinese_roberta_wwm_ext_2_0_8", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|chinese_roberta_wwm_ext_2_0_8|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|381.0 MB|
+
+## References
+
+https://huggingface.co/DaydreamerF/chinese-roberta-wwm-ext-2.0-8
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-chinese_roberta_wwm_ext_2_0_8_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-chinese_roberta_wwm_ext_2_0_8_pipeline_en.md
new file mode 100644
index 00000000000000..0467959e8357b3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-chinese_roberta_wwm_ext_2_0_8_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English chinese_roberta_wwm_ext_2_0_8_pipeline pipeline BertForQuestionAnswering from DaydreamerF
+author: John Snow Labs
+name: chinese_roberta_wwm_ext_2_0_8_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`chinese_roberta_wwm_ext_2_0_8_pipeline` is a English model originally trained by DaydreamerF.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/chinese_roberta_wwm_ext_2_0_8_pipeline_en_5.5.1_3.0_1737919190569.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/chinese_roberta_wwm_ext_2_0_8_pipeline_en_5.5.1_3.0_1737919190569.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("chinese_roberta_wwm_ext_2_0_8_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("chinese_roberta_wwm_ext_2_0_8_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|chinese_roberta_wwm_ext_2_0_8_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|381.0 MB|
+
+## References
+
+https://huggingface.co/DaydreamerF/chinese-roberta-wwm-ext-2.0-8
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-citation_parser_select_en.md b/docs/_posts/ahmedlone127/2025-01-26-citation_parser_select_en.md
new file mode 100644
index 00000000000000..9fc7ca4581a983
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-citation_parser_select_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English citation_parser_select DistilBertForSequenceClassification from SIRIS-Lab
+author: John Snow Labs
+name: citation_parser_select
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`citation_parser_select` is a English model originally trained by SIRIS-Lab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/citation_parser_select_en_5.5.1_3.0_1737929508870.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/citation_parser_select_en_5.5.1_3.0_1737929508870.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("citation_parser_select","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("citation_parser_select", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|citation_parser_select|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|507.6 MB|
+
+## References
+
+https://huggingface.co/SIRIS-Lab/citation-parser-SELECT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-citation_parser_select_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-citation_parser_select_pipeline_en.md
new file mode 100644
index 00000000000000..2749999aef0995
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-citation_parser_select_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English citation_parser_select_pipeline pipeline DistilBertForSequenceClassification from SIRIS-Lab
+author: John Snow Labs
+name: citation_parser_select_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`citation_parser_select_pipeline` is a English model originally trained by SIRIS-Lab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/citation_parser_select_pipeline_en_5.5.1_3.0_1737929535930.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/citation_parser_select_pipeline_en_5.5.1_3.0_1737929535930.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("citation_parser_select_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("citation_parser_select_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|citation_parser_select_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|507.6 MB|
+
+## References
+
+https://huggingface.co/SIRIS-Lab/citation-parser-SELECT
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-clasificador_languagedetection_en.md b/docs/_posts/ahmedlone127/2025-01-26-clasificador_languagedetection_en.md
new file mode 100644
index 00000000000000..6b79d291b3bb74
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-clasificador_languagedetection_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English clasificador_languagedetection XlmRoBertaForSequenceClassification from mfuentelsaz
+author: John Snow Labs
+name: clasificador_languagedetection
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clasificador_languagedetection` is a English model originally trained by mfuentelsaz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clasificador_languagedetection_en_5.5.1_3.0_1737885193352.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clasificador_languagedetection_en_5.5.1_3.0_1737885193352.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("clasificador_languagedetection","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("clasificador_languagedetection", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clasificador_languagedetection|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|870.4 MB|
+
+## References
+
+https://huggingface.co/mfuentelsaz/clasificador-languagedetection
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-clasificador_languagedetection_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-clasificador_languagedetection_pipeline_en.md
new file mode 100644
index 00000000000000..4a4e033ebbf4a2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-clasificador_languagedetection_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English clasificador_languagedetection_pipeline pipeline XlmRoBertaForSequenceClassification from mfuentelsaz
+author: John Snow Labs
+name: clasificador_languagedetection_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clasificador_languagedetection_pipeline` is a English model originally trained by mfuentelsaz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clasificador_languagedetection_pipeline_en_5.5.1_3.0_1737885300400.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clasificador_languagedetection_pipeline_en_5.5.1_3.0_1737885300400.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("clasificador_languagedetection_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("clasificador_languagedetection_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clasificador_languagedetection_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|870.4 MB|
+
+## References
+
+https://huggingface.co/mfuentelsaz/clasificador-languagedetection
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-climate_sentiment_model_taimoor_ahmed1_en.md b/docs/_posts/ahmedlone127/2025-01-26-climate_sentiment_model_taimoor_ahmed1_en.md
new file mode 100644
index 00000000000000..e0486b56075bbd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-climate_sentiment_model_taimoor_ahmed1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English climate_sentiment_model_taimoor_ahmed1 DistilBertForSequenceClassification from taimoor-ahmed1
+author: John Snow Labs
+name: climate_sentiment_model_taimoor_ahmed1
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`climate_sentiment_model_taimoor_ahmed1` is a English model originally trained by taimoor-ahmed1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/climate_sentiment_model_taimoor_ahmed1_en_5.5.1_3.0_1737929073798.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/climate_sentiment_model_taimoor_ahmed1_en_5.5.1_3.0_1737929073798.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("climate_sentiment_model_taimoor_ahmed1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("climate_sentiment_model_taimoor_ahmed1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|climate_sentiment_model_taimoor_ahmed1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/taimoor-ahmed1/climate-sentiment-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-climate_sentiment_model_taimoor_ahmed1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-climate_sentiment_model_taimoor_ahmed1_pipeline_en.md
new file mode 100644
index 00000000000000..2cfda449aa27fa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-climate_sentiment_model_taimoor_ahmed1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English climate_sentiment_model_taimoor_ahmed1_pipeline pipeline DistilBertForSequenceClassification from taimoor-ahmed1
+author: John Snow Labs
+name: climate_sentiment_model_taimoor_ahmed1_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`climate_sentiment_model_taimoor_ahmed1_pipeline` is a English model originally trained by taimoor-ahmed1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/climate_sentiment_model_taimoor_ahmed1_pipeline_en_5.5.1_3.0_1737929087050.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/climate_sentiment_model_taimoor_ahmed1_pipeline_en_5.5.1_3.0_1737929087050.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("climate_sentiment_model_taimoor_ahmed1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("climate_sentiment_model_taimoor_ahmed1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|climate_sentiment_model_taimoor_ahmed1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/taimoor-ahmed1/climate-sentiment-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-clinical_transcripts_roberta_en.md b/docs/_posts/ahmedlone127/2025-01-26-clinical_transcripts_roberta_en.md
new file mode 100644
index 00000000000000..6dcb3b7aeb440c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-clinical_transcripts_roberta_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English clinical_transcripts_roberta RoBertaEmbeddings from Zamoranesis
+author: John Snow Labs
+name: clinical_transcripts_roberta
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clinical_transcripts_roberta` is a English model originally trained by Zamoranesis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clinical_transcripts_roberta_en_5.5.1_3.0_1737866284470.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clinical_transcripts_roberta_en_5.5.1_3.0_1737866284470.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("clinical_transcripts_roberta","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("clinical_transcripts_roberta","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clinical_transcripts_roberta|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|466.1 MB|
+
+## References
+
+https://huggingface.co/Zamoranesis/clinical_transcripts_roberta
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-clinical_transcripts_roberta_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-clinical_transcripts_roberta_pipeline_en.md
new file mode 100644
index 00000000000000..9463ae70287edc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-clinical_transcripts_roberta_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English clinical_transcripts_roberta_pipeline pipeline RoBertaEmbeddings from Zamoranesis
+author: John Snow Labs
+name: clinical_transcripts_roberta_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clinical_transcripts_roberta_pipeline` is a English model originally trained by Zamoranesis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clinical_transcripts_roberta_pipeline_en_5.5.1_3.0_1737866320590.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clinical_transcripts_roberta_pipeline_en_5.5.1_3.0_1737866320590.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("clinical_transcripts_roberta_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("clinical_transcripts_roberta_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clinical_transcripts_roberta_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.1 MB|
+
+## References
+
+https://huggingface.co/Zamoranesis/clinical_transcripts_roberta
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-codebert_base_mlm_en.md b/docs/_posts/ahmedlone127/2025-01-26-codebert_base_mlm_en.md
new file mode 100644
index 00000000000000..28107eef1926eb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-codebert_base_mlm_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English codebert_base_mlm RoBertaEmbeddings from claudios
+author: John Snow Labs
+name: codebert_base_mlm
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`codebert_base_mlm` is a English model originally trained by claudios.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/codebert_base_mlm_en_5.5.1_3.0_1737906417687.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/codebert_base_mlm_en_5.5.1_3.0_1737906417687.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("codebert_base_mlm","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("codebert_base_mlm","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|codebert_base_mlm|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|466.1 MB|
+
+## References
+
+https://huggingface.co/claudios/codebert-base-mlm
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-codebert_base_mlm_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-codebert_base_mlm_pipeline_en.md
new file mode 100644
index 00000000000000..b4547df514d02d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-codebert_base_mlm_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English codebert_base_mlm_pipeline pipeline RoBertaEmbeddings from claudios
+author: John Snow Labs
+name: codebert_base_mlm_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`codebert_base_mlm_pipeline` is a English model originally trained by claudios.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/codebert_base_mlm_pipeline_en_5.5.1_3.0_1737906441661.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/codebert_base_mlm_pipeline_en_5.5.1_3.0_1737906441661.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("codebert_base_mlm_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("codebert_base_mlm_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|codebert_base_mlm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.1 MB|
+
+## References
+
+https://huggingface.co/claudios/codebert-base-mlm
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-cold_fusion_en.md b/docs/_posts/ahmedlone127/2025-01-26-cold_fusion_en.md
new file mode 100644
index 00000000000000..63e0dde53dd9bf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-cold_fusion_en.md
@@ -0,0 +1,98 @@
+---
+layout: model
+title: English cold_fusion RoBertaForSequenceClassification from ibm
+author: John Snow Labs
+name: cold_fusion
+date: 2025-01-26
+tags: [roberta, en, open_source, sequence_classification, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cold_fusion` is a English model originally trained by ibm.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cold_fusion_en_5.5.1_3.0_1737876600561.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cold_fusion_en_5.5.1_3.0_1737876600561.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = DocumentAssembler()\
+    .setInputCol("text")\
+    .setOutputCol("document")
+
+tokenizer = Tokenizer()\
+    .setInputCols("document")\
+    .setOutputCol("token")  
+    
+sequenceClassifier = RoBertaForSequenceClassification.pretrained("cold_fusion","en")\
+            .setInputCols(["document","token"])\
+            .setOutputCol("class")
+
+pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val document_assembler = new DocumentAssembler()
+    .setInputCol("text")
+    .setOutputCol("document")
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document") 
+    .setOutputCol("token")  
+    
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("cold_fusion","en")
+            .setInputCols(Array("document","token"))
+            .setOutputCol("class")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cold_fusion|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|468.0 MB|
+
+## References
+
+References
+
+https://huggingface.co/ibm/ColD-Fusion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-cold_fusion_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-cold_fusion_pipeline_en.md
new file mode 100644
index 00000000000000..8ed5467858859e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-cold_fusion_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English cold_fusion_pipeline pipeline RoBertaForSequenceClassification from ibm-research
+author: John Snow Labs
+name: cold_fusion_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cold_fusion_pipeline` is a English model originally trained by ibm-research.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cold_fusion_pipeline_en_5.5.1_3.0_1737876626724.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cold_fusion_pipeline_en_5.5.1_3.0_1737876626724.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("cold_fusion_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cold_fusion_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cold_fusion_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|468.0 MB|
+
+## References
+
+https://huggingface.co/ibm-research/ColD-Fusion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-colombian_sign_language_small_biased_random_20_en.md b/docs/_posts/ahmedlone127/2025-01-26-colombian_sign_language_small_biased_random_20_en.md
new file mode 100644
index 00000000000000..2e4c96806ba82b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-colombian_sign_language_small_biased_random_20_en.md
@@ -0,0 +1,96 @@
+---
+layout: model
+title: English colombian_sign_language_small_biased_random_20 RoBertaEmbeddings from antolin
+author: John Snow Labs
+name: colombian_sign_language_small_biased_random_20
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`colombian_sign_language_small_biased_random_20` is a English model originally trained by antolin.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/colombian_sign_language_small_biased_random_20_en_5.5.1_3.0_1737907351249.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/colombian_sign_language_small_biased_random_20_en_5.5.1_3.0_1737907351249.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("colombian_sign_language_small_biased_random_20","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("colombian_sign_language_small_biased_random_20","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|colombian_sign_language_small_biased_random_20|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|470.6 MB|
+
+## References
+
+References
+
+https://huggingface.co/antolin/csn-small-biased-random-20
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-colombian_sign_language_small_biased_random_20_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-colombian_sign_language_small_biased_random_20_pipeline_en.md
new file mode 100644
index 00000000000000..d8a39ba4ae7797
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-colombian_sign_language_small_biased_random_20_pipeline_en.md
@@ -0,0 +1,72 @@
+---
+layout: model
+title: English colombian_sign_language_small_biased_random_20_pipeline pipeline RoBertaEmbeddings from antolin
+author: John Snow Labs
+name: colombian_sign_language_small_biased_random_20_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`colombian_sign_language_small_biased_random_20_pipeline` is a English model originally trained by antolin.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/colombian_sign_language_small_biased_random_20_pipeline_en_5.5.1_3.0_1737907376183.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/colombian_sign_language_small_biased_random_20_pipeline_en_5.5.1_3.0_1737907376183.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("colombian_sign_language_small_biased_random_20_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("colombian_sign_language_small_biased_random_20_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|colombian_sign_language_small_biased_random_20_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|470.6 MB|
+
+## References
+
+References
+
+https://huggingface.co/antolin/csn-small-biased-random-20
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-communication_style_oliver12315_en.md b/docs/_posts/ahmedlone127/2025-01-26-communication_style_oliver12315_en.md
new file mode 100644
index 00000000000000..e0fe5cf80159d2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-communication_style_oliver12315_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English communication_style_oliver12315 BertForSequenceClassification from Oliver12315
+author: John Snow Labs
+name: communication_style_oliver12315
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`communication_style_oliver12315` is a English model originally trained by Oliver12315.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/communication_style_oliver12315_en_5.5.1_3.0_1737921532934.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/communication_style_oliver12315_en_5.5.1_3.0_1737921532934.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("communication_style_oliver12315","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("communication_style_oliver12315", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|communication_style_oliver12315|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/Oliver12315/Communication_Style
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-communication_style_oliver12315_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-communication_style_oliver12315_pipeline_en.md
new file mode 100644
index 00000000000000..2e08e17dd5d6c5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-communication_style_oliver12315_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English communication_style_oliver12315_pipeline pipeline BertForSequenceClassification from Oliver12315
+author: John Snow Labs
+name: communication_style_oliver12315_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`communication_style_oliver12315_pipeline` is a English model originally trained by Oliver12315.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/communication_style_oliver12315_pipeline_en_5.5.1_3.0_1737921554064.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/communication_style_oliver12315_pipeline_en_5.5.1_3.0_1737921554064.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("communication_style_oliver12315_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("communication_style_oliver12315_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|communication_style_oliver12315_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/Oliver12315/Communication_Style
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-convbert_base_turkish_mc4_uncased_offensive_mlm_pipeline_tr.md b/docs/_posts/ahmedlone127/2025-01-26-convbert_base_turkish_mc4_uncased_offensive_mlm_pipeline_tr.md
new file mode 100644
index 00000000000000..0de36857725210
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-convbert_base_turkish_mc4_uncased_offensive_mlm_pipeline_tr.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Turkish convbert_base_turkish_mc4_uncased_offensive_mlm_pipeline pipeline BertEmbeddings from Overfit-GM
+author: John Snow Labs
+name: convbert_base_turkish_mc4_uncased_offensive_mlm_pipeline
+date: 2025-01-26
+tags: [tr, open_source, pipeline, onnx]
+task: Embeddings
+language: tr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`convbert_base_turkish_mc4_uncased_offensive_mlm_pipeline` is a Turkish model originally trained by Overfit-GM.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/convbert_base_turkish_mc4_uncased_offensive_mlm_pipeline_tr_5.5.1_3.0_1737861972035.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/convbert_base_turkish_mc4_uncased_offensive_mlm_pipeline_tr_5.5.1_3.0_1737861972035.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("convbert_base_turkish_mc4_uncased_offensive_mlm_pipeline", lang = "tr")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("convbert_base_turkish_mc4_uncased_offensive_mlm_pipeline", lang = "tr")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|convbert_base_turkish_mc4_uncased_offensive_mlm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|tr|
+|Size:|400.1 MB|
+
+## References
+
+https://huggingface.co/Overfit-GM/convbert-base-turkish-mc4-uncased-offensive-mlm
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-convbert_base_turkish_mc4_uncased_offensive_mlm_tr.md b/docs/_posts/ahmedlone127/2025-01-26-convbert_base_turkish_mc4_uncased_offensive_mlm_tr.md
new file mode 100644
index 00000000000000..d10e6ab7a1df9c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-convbert_base_turkish_mc4_uncased_offensive_mlm_tr.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Turkish convbert_base_turkish_mc4_uncased_offensive_mlm BertEmbeddings from Overfit-GM
+author: John Snow Labs
+name: convbert_base_turkish_mc4_uncased_offensive_mlm
+date: 2025-01-26
+tags: [tr, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: tr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`convbert_base_turkish_mc4_uncased_offensive_mlm` is a Turkish model originally trained by Overfit-GM.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/convbert_base_turkish_mc4_uncased_offensive_mlm_tr_5.5.1_3.0_1737861951320.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/convbert_base_turkish_mc4_uncased_offensive_mlm_tr_5.5.1_3.0_1737861951320.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("convbert_base_turkish_mc4_uncased_offensive_mlm","tr") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("convbert_base_turkish_mc4_uncased_offensive_mlm","tr") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|convbert_base_turkish_mc4_uncased_offensive_mlm|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|tr|
+|Size:|400.1 MB|
+
+## References
+
+https://huggingface.co/Overfit-GM/convbert-base-turkish-mc4-uncased-offensive-mlm
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-covid_roberta_15_40_masked_en.md b/docs/_posts/ahmedlone127/2025-01-26-covid_roberta_15_40_masked_en.md
new file mode 100644
index 00000000000000..454e2151f07126
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-covid_roberta_15_40_masked_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English covid_roberta_15_40_masked RoBertaEmbeddings from timoneda
+author: John Snow Labs
+name: covid_roberta_15_40_masked
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`covid_roberta_15_40_masked` is a English model originally trained by timoneda.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/covid_roberta_15_40_masked_en_5.5.1_3.0_1737907357462.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/covid_roberta_15_40_masked_en_5.5.1_3.0_1737907357462.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("covid_roberta_15_40_masked","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("covid_roberta_15_40_masked","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|covid_roberta_15_40_masked|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/timoneda/covid_roberta_15_40_masked
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-covid_roberta_15_40_masked_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-covid_roberta_15_40_masked_pipeline_en.md
new file mode 100644
index 00000000000000..7505e4594625e5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-covid_roberta_15_40_masked_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English covid_roberta_15_40_masked_pipeline pipeline RoBertaEmbeddings from timoneda
+author: John Snow Labs
+name: covid_roberta_15_40_masked_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`covid_roberta_15_40_masked_pipeline` is a English model originally trained by timoneda.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/covid_roberta_15_40_masked_pipeline_en_5.5.1_3.0_1737907424829.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/covid_roberta_15_40_masked_pipeline_en_5.5.1_3.0_1737907424829.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("covid_roberta_15_40_masked_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("covid_roberta_15_40_masked_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|covid_roberta_15_40_masked_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/timoneda/covid_roberta_15_40_masked
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-covid_roberta_40_clean_en.md b/docs/_posts/ahmedlone127/2025-01-26-covid_roberta_40_clean_en.md
new file mode 100644
index 00000000000000..2972e609609d3e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-covid_roberta_40_clean_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English covid_roberta_40_clean RoBertaEmbeddings from timoneda
+author: John Snow Labs
+name: covid_roberta_40_clean
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`covid_roberta_40_clean` is a English model originally trained by timoneda.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/covid_roberta_40_clean_en_5.5.1_3.0_1737906292780.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/covid_roberta_40_clean_en_5.5.1_3.0_1737906292780.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("covid_roberta_40_clean","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("covid_roberta_40_clean","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|covid_roberta_40_clean|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/timoneda/covid_roberta_40_clean
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-covid_roberta_40_clean_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-covid_roberta_40_clean_pipeline_en.md
new file mode 100644
index 00000000000000..7322e9521158fc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-covid_roberta_40_clean_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English covid_roberta_40_clean_pipeline pipeline RoBertaEmbeddings from timoneda
+author: John Snow Labs
+name: covid_roberta_40_clean_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`covid_roberta_40_clean_pipeline` is a English model originally trained by timoneda.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/covid_roberta_40_clean_pipeline_en_5.5.1_3.0_1737906358639.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/covid_roberta_40_clean_pipeline_en_5.5.1_3.0_1737906358639.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("covid_roberta_40_clean_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("covid_roberta_40_clean_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|covid_roberta_40_clean_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/timoneda/covid_roberta_40_clean
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-covid_roberta_40_en.md b/docs/_posts/ahmedlone127/2025-01-26-covid_roberta_40_en.md
new file mode 100644
index 00000000000000..2a2e94e5d45179
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-covid_roberta_40_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English covid_roberta_40 RoBertaEmbeddings from timoneda
+author: John Snow Labs
+name: covid_roberta_40
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`covid_roberta_40` is a English model originally trained by timoneda.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/covid_roberta_40_en_5.5.1_3.0_1737865972550.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/covid_roberta_40_en_5.5.1_3.0_1737865972550.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("covid_roberta_40","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("covid_roberta_40","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|covid_roberta_40|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/timoneda/covid_roberta_40
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-covid_roberta_40_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-covid_roberta_40_pipeline_en.md
new file mode 100644
index 00000000000000..1a7ffea8239e1f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-covid_roberta_40_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English covid_roberta_40_pipeline pipeline RoBertaEmbeddings from timoneda
+author: John Snow Labs
+name: covid_roberta_40_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`covid_roberta_40_pipeline` is a English model originally trained by timoneda.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/covid_roberta_40_pipeline_en_5.5.1_3.0_1737866048658.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/covid_roberta_40_pipeline_en_5.5.1_3.0_1737866048658.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("covid_roberta_40_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("covid_roberta_40_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|covid_roberta_40_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/timoneda/covid_roberta_40
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-covid_roberta_40_sel_mask_1e_en.md b/docs/_posts/ahmedlone127/2025-01-26-covid_roberta_40_sel_mask_1e_en.md
new file mode 100644
index 00000000000000..3e043230f39cb0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-covid_roberta_40_sel_mask_1e_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English covid_roberta_40_sel_mask_1e RoBertaEmbeddings from timoneda
+author: John Snow Labs
+name: covid_roberta_40_sel_mask_1e
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`covid_roberta_40_sel_mask_1e` is a English model originally trained by timoneda.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/covid_roberta_40_sel_mask_1e_en_5.5.1_3.0_1737865290375.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/covid_roberta_40_sel_mask_1e_en_5.5.1_3.0_1737865290375.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("covid_roberta_40_sel_mask_1e","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("covid_roberta_40_sel_mask_1e","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|covid_roberta_40_sel_mask_1e|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/timoneda/covid_roberta_40_sel_mask_1e
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-covid_roberta_40_sel_mask_1e_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-covid_roberta_40_sel_mask_1e_pipeline_en.md
new file mode 100644
index 00000000000000..740b06bb5bb29b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-covid_roberta_40_sel_mask_1e_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English covid_roberta_40_sel_mask_1e_pipeline pipeline RoBertaEmbeddings from timoneda
+author: John Snow Labs
+name: covid_roberta_40_sel_mask_1e_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`covid_roberta_40_sel_mask_1e_pipeline` is a English model originally trained by timoneda.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/covid_roberta_40_sel_mask_1e_pipeline_en_5.5.1_3.0_1737865359453.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/covid_roberta_40_sel_mask_1e_pipeline_en_5.5.1_3.0_1737865359453.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("covid_roberta_40_sel_mask_1e_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("covid_roberta_40_sel_mask_1e_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|covid_roberta_40_sel_mask_1e_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/timoneda/covid_roberta_40_sel_mask_1e
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-covid_roberta_60_en.md b/docs/_posts/ahmedlone127/2025-01-26-covid_roberta_60_en.md
new file mode 100644
index 00000000000000..cd48418c06372f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-covid_roberta_60_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English covid_roberta_60 RoBertaEmbeddings from timoneda
+author: John Snow Labs
+name: covid_roberta_60
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`covid_roberta_60` is a English model originally trained by timoneda.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/covid_roberta_60_en_5.5.1_3.0_1737865669575.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/covid_roberta_60_en_5.5.1_3.0_1737865669575.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("covid_roberta_60","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("covid_roberta_60","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|covid_roberta_60|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/timoneda/covid_roberta_60
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-covid_roberta_60_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-covid_roberta_60_pipeline_en.md
new file mode 100644
index 00000000000000..9e9bc3e9a21f86
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-covid_roberta_60_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English covid_roberta_60_pipeline pipeline RoBertaEmbeddings from timoneda
+author: John Snow Labs
+name: covid_roberta_60_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`covid_roberta_60_pipeline` is a English model originally trained by timoneda.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/covid_roberta_60_pipeline_en_5.5.1_3.0_1737865740728.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/covid_roberta_60_pipeline_en_5.5.1_3.0_1737865740728.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("covid_roberta_60_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("covid_roberta_60_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|covid_roberta_60_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/timoneda/covid_roberta_60
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-covid_roberta_80_masked_en.md b/docs/_posts/ahmedlone127/2025-01-26-covid_roberta_80_masked_en.md
new file mode 100644
index 00000000000000..f023acf794e3d8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-covid_roberta_80_masked_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English covid_roberta_80_masked RoBertaEmbeddings from timoneda
+author: John Snow Labs
+name: covid_roberta_80_masked
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`covid_roberta_80_masked` is a English model originally trained by timoneda.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/covid_roberta_80_masked_en_5.5.1_3.0_1737866150305.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/covid_roberta_80_masked_en_5.5.1_3.0_1737866150305.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("covid_roberta_80_masked","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("covid_roberta_80_masked","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|covid_roberta_80_masked|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/timoneda/covid_roberta_80_masked
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-covid_roberta_80_masked_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-covid_roberta_80_masked_pipeline_en.md
new file mode 100644
index 00000000000000..9c5b39aba10d06
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-covid_roberta_80_masked_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English covid_roberta_80_masked_pipeline pipeline RoBertaEmbeddings from timoneda
+author: John Snow Labs
+name: covid_roberta_80_masked_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`covid_roberta_80_masked_pipeline` is a English model originally trained by timoneda.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/covid_roberta_80_masked_pipeline_en_5.5.1_3.0_1737866220328.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/covid_roberta_80_masked_pipeline_en_5.5.1_3.0_1737866220328.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("covid_roberta_80_masked_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("covid_roberta_80_masked_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|covid_roberta_80_masked_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/timoneda/covid_roberta_80_masked
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-custom_trainer_en.md b/docs/_posts/ahmedlone127/2025-01-26-custom_trainer_en.md
new file mode 100644
index 00000000000000..607bb1018dbb47
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-custom_trainer_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English custom_trainer DistilBertForSequenceClassification from StefanSpijkerman
+author: John Snow Labs
+name: custom_trainer
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`custom_trainer` is a English model originally trained by StefanSpijkerman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/custom_trainer_en_5.5.1_3.0_1737872998385.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/custom_trainer_en_5.5.1_3.0_1737872998385.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("custom_trainer","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("custom_trainer", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|custom_trainer|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|246.0 MB|
+
+## References
+
+https://huggingface.co/StefanSpijkerman/custom-trainer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-custom_trainer_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-custom_trainer_pipeline_en.md
new file mode 100644
index 00000000000000..0ced77b1a77524
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-custom_trainer_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English custom_trainer_pipeline pipeline DistilBertForSequenceClassification from StefanSpijkerman
+author: John Snow Labs
+name: custom_trainer_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`custom_trainer_pipeline` is a English model originally trained by StefanSpijkerman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/custom_trainer_pipeline_en_5.5.1_3.0_1737873018214.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/custom_trainer_pipeline_en_5.5.1_3.0_1737873018214.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("custom_trainer_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("custom_trainer_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|custom_trainer_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|246.1 MB|
+
+## References
+
+https://huggingface.co/StefanSpijkerman/custom-trainer
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-custommodel_jl_en.md b/docs/_posts/ahmedlone127/2025-01-26-custommodel_jl_en.md
new file mode 100644
index 00000000000000..32cd4ca44b9322
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-custommodel_jl_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English custommodel_jl DistilBertForSequenceClassification from JACOBBBB
+author: John Snow Labs
+name: custommodel_jl
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`custommodel_jl` is a English model originally trained by JACOBBBB.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/custommodel_jl_en_5.5.1_3.0_1737873044487.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/custommodel_jl_en_5.5.1_3.0_1737873044487.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("custommodel_jl","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("custommodel_jl", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|custommodel_jl|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/JACOBBBB/CustomModel_JL
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-custommodel_jl_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-custommodel_jl_pipeline_en.md
new file mode 100644
index 00000000000000..3527e24134db07
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-custommodel_jl_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English custommodel_jl_pipeline pipeline DistilBertForSequenceClassification from JACOBBBB
+author: John Snow Labs
+name: custommodel_jl_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`custommodel_jl_pipeline` is a English model originally trained by JACOBBBB.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/custommodel_jl_pipeline_en_5.5.1_3.0_1737873058180.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/custommodel_jl_pipeline_en_5.5.1_3.0_1737873058180.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("custommodel_jl_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("custommodel_jl_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|custommodel_jl_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/JACOBBBB/CustomModel_JL
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-custommodel_yelp_mintiny_en.md b/docs/_posts/ahmedlone127/2025-01-26-custommodel_yelp_mintiny_en.md
new file mode 100644
index 00000000000000..00fe9ec104d1fc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-custommodel_yelp_mintiny_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English custommodel_yelp_mintiny DistilBertForSequenceClassification from Mintiny
+author: John Snow Labs
+name: custommodel_yelp_mintiny
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`custommodel_yelp_mintiny` is a English model originally trained by Mintiny.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/custommodel_yelp_mintiny_en_5.5.1_3.0_1737929270801.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/custommodel_yelp_mintiny_en_5.5.1_3.0_1737929270801.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("custommodel_yelp_mintiny","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("custommodel_yelp_mintiny", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|custommodel_yelp_mintiny|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Mintiny/CustomModel_yelp
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-custommodel_yelp_mintiny_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-custommodel_yelp_mintiny_pipeline_en.md
new file mode 100644
index 00000000000000..eb463963e4f6cd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-custommodel_yelp_mintiny_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English custommodel_yelp_mintiny_pipeline pipeline DistilBertForSequenceClassification from Mintiny
+author: John Snow Labs
+name: custommodel_yelp_mintiny_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`custommodel_yelp_mintiny_pipeline` is a English model originally trained by Mintiny.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/custommodel_yelp_mintiny_pipeline_en_5.5.1_3.0_1737929284206.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/custommodel_yelp_mintiny_pipeline_en_5.5.1_3.0_1737929284206.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("custommodel_yelp_mintiny_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("custommodel_yelp_mintiny_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|custommodel_yelp_mintiny_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Mintiny/CustomModel_yelp
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-cybert_base_mlm_v1_1_en.md b/docs/_posts/ahmedlone127/2025-01-26-cybert_base_mlm_v1_1_en.md
new file mode 100644
index 00000000000000..c99130d09a491e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-cybert_base_mlm_v1_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English cybert_base_mlm_v1_1 BertEmbeddings from jenfung
+author: John Snow Labs
+name: cybert_base_mlm_v1_1
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cybert_base_mlm_v1_1` is a English model originally trained by jenfung.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cybert_base_mlm_v1_1_en_5.5.1_3.0_1737908728032.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cybert_base_mlm_v1_1_en_5.5.1_3.0_1737908728032.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("cybert_base_mlm_v1_1","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("cybert_base_mlm_v1_1","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cybert_base_mlm_v1_1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|410.9 MB|
+
+## References
+
+https://huggingface.co/jenfung/CyBERT-Base-MLM-v1.1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-cybert_base_mlm_v1_1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-cybert_base_mlm_v1_1_pipeline_en.md
new file mode 100644
index 00000000000000..66d9417ddcf571
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-cybert_base_mlm_v1_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English cybert_base_mlm_v1_1_pipeline pipeline BertEmbeddings from jenfung
+author: John Snow Labs
+name: cybert_base_mlm_v1_1_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cybert_base_mlm_v1_1_pipeline` is a English model originally trained by jenfung.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cybert_base_mlm_v1_1_pipeline_en_5.5.1_3.0_1737908750788.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cybert_base_mlm_v1_1_pipeline_en_5.5.1_3.0_1737908750788.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("cybert_base_mlm_v1_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cybert_base_mlm_v1_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cybert_base_mlm_v1_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.9 MB|
+
+## References
+
+https://huggingface.co/jenfung/CyBERT-Base-MLM-v1.1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-d_filter_v1_2_en.md b/docs/_posts/ahmedlone127/2025-01-26-d_filter_v1_2_en.md
new file mode 100644
index 00000000000000..cdbf6f755ce6aa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-d_filter_v1_2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English d_filter_v1_2 XlmRoBertaForSequenceClassification from DuongTrongChi
+author: John Snow Labs
+name: d_filter_v1_2
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`d_filter_v1_2` is a English model originally trained by DuongTrongChi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/d_filter_v1_2_en_5.5.1_3.0_1737881313287.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/d_filter_v1_2_en_5.5.1_3.0_1737881313287.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("d_filter_v1_2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("d_filter_v1_2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|d_filter_v1_2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|365.9 MB|
+
+## References
+
+https://huggingface.co/DuongTrongChi/d-filter-v1.2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-d_filter_v1_2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-d_filter_v1_2_pipeline_en.md
new file mode 100644
index 00000000000000..ca976929da5623
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-d_filter_v1_2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English d_filter_v1_2_pipeline pipeline XlmRoBertaForSequenceClassification from DuongTrongChi
+author: John Snow Labs
+name: d_filter_v1_2_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`d_filter_v1_2_pipeline` is a English model originally trained by DuongTrongChi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/d_filter_v1_2_pipeline_en_5.5.1_3.0_1737881334300.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/d_filter_v1_2_pipeline_en_5.5.1_3.0_1737881334300.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("d_filter_v1_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("d_filter_v1_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|d_filter_v1_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|365.9 MB|
+
+## References
+
+https://huggingface.co/DuongTrongChi/d-filter-v1.2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-danish_mrm8488_distilroberta_finetuned_financial_news_sentiment_analysis_en.md b/docs/_posts/ahmedlone127/2025-01-26-danish_mrm8488_distilroberta_finetuned_financial_news_sentiment_analysis_en.md
new file mode 100644
index 00000000000000..b99a35726fc474
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-danish_mrm8488_distilroberta_finetuned_financial_news_sentiment_analysis_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English danish_mrm8488_distilroberta_finetuned_financial_news_sentiment_analysis RoBertaEmbeddings from rnribeiro
+author: John Snow Labs
+name: danish_mrm8488_distilroberta_finetuned_financial_news_sentiment_analysis
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`danish_mrm8488_distilroberta_finetuned_financial_news_sentiment_analysis` is a English model originally trained by rnribeiro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/danish_mrm8488_distilroberta_finetuned_financial_news_sentiment_analysis_en_5.5.1_3.0_1737865777235.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/danish_mrm8488_distilroberta_finetuned_financial_news_sentiment_analysis_en_5.5.1_3.0_1737865777235.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("danish_mrm8488_distilroberta_finetuned_financial_news_sentiment_analysis","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("danish_mrm8488_distilroberta_finetuned_financial_news_sentiment_analysis","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|danish_mrm8488_distilroberta_finetuned_financial_news_sentiment_analysis|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|306.8 MB|
+
+## References
+
+https://huggingface.co/rnribeiro/DA-mrm8488-distilroberta-finetuned-financial-news-sentiment-analysis
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-danish_mrm8488_distilroberta_finetuned_financial_news_sentiment_analysis_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-danish_mrm8488_distilroberta_finetuned_financial_news_sentiment_analysis_pipeline_en.md
new file mode 100644
index 00000000000000..110c7a7ad6b12f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-danish_mrm8488_distilroberta_finetuned_financial_news_sentiment_analysis_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English danish_mrm8488_distilroberta_finetuned_financial_news_sentiment_analysis_pipeline pipeline RoBertaEmbeddings from rnribeiro
+author: John Snow Labs
+name: danish_mrm8488_distilroberta_finetuned_financial_news_sentiment_analysis_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`danish_mrm8488_distilroberta_finetuned_financial_news_sentiment_analysis_pipeline` is a English model originally trained by rnribeiro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/danish_mrm8488_distilroberta_finetuned_financial_news_sentiment_analysis_pipeline_en_5.5.1_3.0_1737865792833.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/danish_mrm8488_distilroberta_finetuned_financial_news_sentiment_analysis_pipeline_en_5.5.1_3.0_1737865792833.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("danish_mrm8488_distilroberta_finetuned_financial_news_sentiment_analysis_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("danish_mrm8488_distilroberta_finetuned_financial_news_sentiment_analysis_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|danish_mrm8488_distilroberta_finetuned_financial_news_sentiment_analysis_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|306.8 MB|
+
+## References
+
+https://huggingface.co/rnribeiro/DA-mrm8488-distilroberta-finetuned-financial-news-sentiment-analysis
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-datosw_v1_en.md b/docs/_posts/ahmedlone127/2025-01-26-datosw_v1_en.md
new file mode 100644
index 00000000000000..61f36236da3e5a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-datosw_v1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English datosw_v1 MarianTransformer from ZcepZtar
+author: John Snow Labs
+name: datosw_v1
+date: 2025-01-26
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`datosw_v1` is a English model originally trained by ZcepZtar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/datosw_v1_en_5.5.1_3.0_1737863935460.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/datosw_v1_en_5.5.1_3.0_1737863935460.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("datosw_v1","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("datosw_v1","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|datosw_v1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|394.2 MB|
+
+## References
+
+https://huggingface.co/ZcepZtar/DaToSw_V1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-datosw_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-datosw_v1_pipeline_en.md
new file mode 100644
index 00000000000000..bb04615f507153
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-datosw_v1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English datosw_v1_pipeline pipeline MarianTransformer from ZcepZtar
+author: John Snow Labs
+name: datosw_v1_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`datosw_v1_pipeline` is a English model originally trained by ZcepZtar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/datosw_v1_pipeline_en_5.5.1_3.0_1737863955562.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/datosw_v1_pipeline_en_5.5.1_3.0_1737863955562.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("datosw_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("datosw_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|datosw_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|394.8 MB|
+
+## References
+
+https://huggingface.co/ZcepZtar/DaToSw_V1
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-db_aca_4_1_en.md b/docs/_posts/ahmedlone127/2025-01-26-db_aca_4_1_en.md
new file mode 100644
index 00000000000000..8fa64d867edbc0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-db_aca_4_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English db_aca_4_1 DistilBertForSequenceClassification from exala
+author: John Snow Labs
+name: db_aca_4_1
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`db_aca_4_1` is a English model originally trained by exala.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/db_aca_4_1_en_5.5.1_3.0_1737905513870.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/db_aca_4_1_en_5.5.1_3.0_1737905513870.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("db_aca_4_1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("db_aca_4_1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|db_aca_4_1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.6 MB|
+
+## References
+
+https://huggingface.co/exala/db_aca_4.1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-db_aca_4_1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-db_aca_4_1_pipeline_en.md
new file mode 100644
index 00000000000000..b74b7007a0b3f1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-db_aca_4_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English db_aca_4_1_pipeline pipeline DistilBertForSequenceClassification from exala
+author: John Snow Labs
+name: db_aca_4_1_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`db_aca_4_1_pipeline` is a English model originally trained by exala.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/db_aca_4_1_pipeline_en_5.5.1_3.0_1737905527230.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/db_aca_4_1_pipeline_en_5.5.1_3.0_1737905527230.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("db_aca_4_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("db_aca_4_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|db_aca_4_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.6 MB|
+
+## References
+
+https://huggingface.co/exala/db_aca_4.1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-db_mc2_8_3_en.md b/docs/_posts/ahmedlone127/2025-01-26-db_mc2_8_3_en.md
new file mode 100644
index 00000000000000..b4931acd2e7922
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-db_mc2_8_3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English db_mc2_8_3 DistilBertForSequenceClassification from exala
+author: John Snow Labs
+name: db_mc2_8_3
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`db_mc2_8_3` is a English model originally trained by exala.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/db_mc2_8_3_en_5.5.1_3.0_1737928986316.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/db_mc2_8_3_en_5.5.1_3.0_1737928986316.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("db_mc2_8_3","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("db_mc2_8_3", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|db_mc2_8_3|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.7 MB|
+
+## References
+
+https://huggingface.co/exala/db_mc2_8.3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-db_mc2_8_3_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-db_mc2_8_3_pipeline_en.md
new file mode 100644
index 00000000000000..046d27ffe90302
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-db_mc2_8_3_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English db_mc2_8_3_pipeline pipeline DistilBertForSequenceClassification from exala
+author: John Snow Labs
+name: db_mc2_8_3_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`db_mc2_8_3_pipeline` is a English model originally trained by exala.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/db_mc2_8_3_pipeline_en_5.5.1_3.0_1737929000060.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/db_mc2_8_3_pipeline_en_5.5.1_3.0_1737929000060.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("db_mc2_8_3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("db_mc2_8_3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|db_mc2_8_3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.7 MB|
+
+## References
+
+https://huggingface.co/exala/db_mc2_8.3
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-deberta_v3_xsmall_sst2_en.md b/docs/_posts/ahmedlone127/2025-01-26-deberta_v3_xsmall_sst2_en.md
new file mode 100644
index 00000000000000..0b029f7c71a1fd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-deberta_v3_xsmall_sst2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_xsmall_sst2 DeBertaForSequenceClassification from cliang1453
+author: John Snow Labs
+name: deberta_v3_xsmall_sst2
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_xsmall_sst2` is a English model originally trained by cliang1453.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_sst2_en_5.5.1_3.0_1737917713990.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_sst2_en_5.5.1_3.0_1737917713990.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_xsmall_sst2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_xsmall_sst2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_xsmall_sst2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|208.0 MB|
+
+## References
+
+https://huggingface.co/cliang1453/deberta-v3-xsmall-sst2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-deberta_v3_xsmall_sst2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-deberta_v3_xsmall_sst2_pipeline_en.md
new file mode 100644
index 00000000000000..c9065fdb09d62d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-deberta_v3_xsmall_sst2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_xsmall_sst2_pipeline pipeline DeBertaForSequenceClassification from cliang1453
+author: John Snow Labs
+name: deberta_v3_xsmall_sst2_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_xsmall_sst2_pipeline` is a English model originally trained by cliang1453.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_sst2_pipeline_en_5.5.1_3.0_1737917748495.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_sst2_pipeline_en_5.5.1_3.0_1737917748495.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_xsmall_sst2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_xsmall_sst2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_xsmall_sst2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|208.1 MB|
+
+## References
+
+https://huggingface.co/cliang1453/deberta-v3-xsmall-sst2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-deep_fake_detector_model_en.md b/docs/_posts/ahmedlone127/2025-01-26-deep_fake_detector_model_en.md
new file mode 100644
index 00000000000000..2d18a595f0e528
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-deep_fake_detector_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deep_fake_detector_model ViTForImageClassification from prithivMLmods
+author: John Snow Labs
+name: deep_fake_detector_model
+date: 2025-01-26
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deep_fake_detector_model` is a English model originally trained by prithivMLmods.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deep_fake_detector_model_en_5.5.1_3.0_1737926232164.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deep_fake_detector_model_en_5.5.1_3.0_1737926232164.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""deep_fake_detector_model","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("deep_fake_detector_model","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deep_fake_detector_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/prithivMLmods/Deep-Fake-Detector-Model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-deep_fake_detector_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-deep_fake_detector_model_pipeline_en.md
new file mode 100644
index 00000000000000..1dcad327e907d9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-deep_fake_detector_model_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English deep_fake_detector_model_pipeline pipeline ViTForImageClassification from prithivMLmods
+author: John Snow Labs
+name: deep_fake_detector_model_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deep_fake_detector_model_pipeline` is a English model originally trained by prithivMLmods.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deep_fake_detector_model_pipeline_en_5.5.1_3.0_1737926250418.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deep_fake_detector_model_pipeline_en_5.5.1_3.0_1737926250418.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deep_fake_detector_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deep_fake_detector_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deep_fake_detector_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/prithivMLmods/Deep-Fake-Detector-Model
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-deit_base_patch16_224_en.md b/docs/_posts/ahmedlone127/2025-01-26-deit_base_patch16_224_en.md
new file mode 100644
index 00000000000000..dbd1d304950ae5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-deit_base_patch16_224_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deit_base_patch16_224 ViTForImageClassification from facebook
+author: John Snow Labs
+name: deit_base_patch16_224
+date: 2025-01-26
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deit_base_patch16_224` is a English model originally trained by facebook.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deit_base_patch16_224_en_5.5.1_3.0_1737926545361.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deit_base_patch16_224_en_5.5.1_3.0_1737926545361.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""deit_base_patch16_224","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("deit_base_patch16_224","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deit_base_patch16_224|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|324.1 MB|
+
+## References
+
+https://huggingface.co/facebook/deit-base-patch16-224
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-deit_base_patch16_224_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-deit_base_patch16_224_pipeline_en.md
new file mode 100644
index 00000000000000..41f6ea5170227f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-deit_base_patch16_224_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English deit_base_patch16_224_pipeline pipeline ViTForImageClassification from facebook
+author: John Snow Labs
+name: deit_base_patch16_224_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deit_base_patch16_224_pipeline` is a English model originally trained by facebook.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deit_base_patch16_224_pipeline_en_5.5.1_3.0_1737926562077.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deit_base_patch16_224_pipeline_en_5.5.1_3.0_1737926562077.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deit_base_patch16_224_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deit_base_patch16_224_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deit_base_patch16_224_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|324.1 MB|
+
+## References
+
+https://huggingface.co/facebook/deit-base-patch16-224
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-delirium_roberta_en.md b/docs/_posts/ahmedlone127/2025-01-26-delirium_roberta_en.md
new file mode 100644
index 00000000000000..e7cb63e1f16511
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-delirium_roberta_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English delirium_roberta RoBertaEmbeddings from Zamoranesis
+author: John Snow Labs
+name: delirium_roberta
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`delirium_roberta` is a English model originally trained by Zamoranesis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/delirium_roberta_en_5.5.1_3.0_1737865582985.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/delirium_roberta_en_5.5.1_3.0_1737865582985.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("delirium_roberta","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("delirium_roberta","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|delirium_roberta|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|466.1 MB|
+
+## References
+
+https://huggingface.co/Zamoranesis/delirium_roberta
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-delirium_roberta_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-delirium_roberta_pipeline_en.md
new file mode 100644
index 00000000000000..7baac2c4c44930
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-delirium_roberta_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English delirium_roberta_pipeline pipeline RoBertaEmbeddings from Zamoranesis
+author: John Snow Labs
+name: delirium_roberta_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`delirium_roberta_pipeline` is a English model originally trained by Zamoranesis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/delirium_roberta_pipeline_en_5.5.1_3.0_1737865608445.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/delirium_roberta_pipeline_en_5.5.1_3.0_1737865608445.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("delirium_roberta_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("delirium_roberta_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|delirium_roberta_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.1 MB|
+
+## References
+
+https://huggingface.co/Zamoranesis/delirium_roberta
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-dialogpt_medium_elon_2_en.md b/docs/_posts/ahmedlone127/2025-01-26-dialogpt_medium_elon_2_en.md
new file mode 100644
index 00000000000000..c6a3dac6d56b63
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-dialogpt_medium_elon_2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English dialogpt_medium_elon_2 GPT2Transformer from Pi3141
+author: John Snow Labs
+name: dialogpt_medium_elon_2
+date: 2025-01-26
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dialogpt_medium_elon_2` is a English model originally trained by Pi3141.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dialogpt_medium_elon_2_en_5.5.1_3.0_1737867639418.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dialogpt_medium_elon_2_en_5.5.1_3.0_1737867639418.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("dialogpt_medium_elon_2","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("dialogpt_medium_elon_2","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dialogpt_medium_elon_2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/Pi3141/DialoGPT-medium-elon-2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-dialogpt_medium_elon_2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-dialogpt_medium_elon_2_pipeline_en.md
new file mode 100644
index 00000000000000..39d7b30bc61db7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-dialogpt_medium_elon_2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English dialogpt_medium_elon_2_pipeline pipeline GPT2Transformer from Pi3141
+author: John Snow Labs
+name: dialogpt_medium_elon_2_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dialogpt_medium_elon_2_pipeline` is a English model originally trained by Pi3141.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dialogpt_medium_elon_2_pipeline_en_5.5.1_3.0_1737867709179.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dialogpt_medium_elon_2_pipeline_en_5.5.1_3.0_1737867709179.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dialogpt_medium_elon_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dialogpt_medium_elon_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dialogpt_medium_elon_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/Pi3141/DialoGPT-medium-elon-2
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-dialogpt_shohanursobuj_en.md b/docs/_posts/ahmedlone127/2025-01-26-dialogpt_shohanursobuj_en.md
new file mode 100644
index 00000000000000..533242018ab9f0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-dialogpt_shohanursobuj_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English dialogpt_shohanursobuj GPT2Transformer from shohanursobuj
+author: John Snow Labs
+name: dialogpt_shohanursobuj
+date: 2025-01-26
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dialogpt_shohanursobuj` is a English model originally trained by shohanursobuj.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dialogpt_shohanursobuj_en_5.5.1_3.0_1737916397499.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dialogpt_shohanursobuj_en_5.5.1_3.0_1737916397499.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("dialogpt_shohanursobuj","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("dialogpt_shohanursobuj","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dialogpt_shohanursobuj|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|298.3 MB|
+
+## References
+
+https://huggingface.co/shohanursobuj/DialoGPT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-dialogpt_shohanursobuj_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-dialogpt_shohanursobuj_pipeline_en.md
new file mode 100644
index 00000000000000..c5515a5a799274
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-dialogpt_shohanursobuj_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English dialogpt_shohanursobuj_pipeline pipeline GPT2Transformer from shohanursobuj
+author: John Snow Labs
+name: dialogpt_shohanursobuj_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dialogpt_shohanursobuj_pipeline` is a English model originally trained by shohanursobuj.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dialogpt_shohanursobuj_pipeline_en_5.5.1_3.0_1737916482967.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dialogpt_shohanursobuj_pipeline_en_5.5.1_3.0_1737916482967.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dialogpt_shohanursobuj_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dialogpt_shohanursobuj_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dialogpt_shohanursobuj_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|298.3 MB|
+
+## References
+
+https://huggingface.co/shohanursobuj/DialoGPT
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-disaster_tweet_classification_en.md b/docs/_posts/ahmedlone127/2025-01-26-disaster_tweet_classification_en.md
new file mode 100644
index 00000000000000..9f681ff208d305
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-disaster_tweet_classification_en.md
@@ -0,0 +1,98 @@
+---
+layout: model
+title: English disaster_tweet_classification RoBertaForSequenceClassification from aellxx
+author: John Snow Labs
+name: disaster_tweet_classification
+date: 2025-01-26
+tags: [roberta, en, open_source, sequence_classification, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`disaster_tweet_classification` is a English model originally trained by aellxx.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/disaster_tweet_classification_en_5.5.1_3.0_1737881279651.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/disaster_tweet_classification_en_5.5.1_3.0_1737881279651.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = DocumentAssembler()\
+    .setInputCol("text")\
+    .setOutputCol("document")
+
+tokenizer = Tokenizer()\
+    .setInputCols("document")\
+    .setOutputCol("token")  
+    
+sequenceClassifier = RoBertaForSequenceClassification.pretrained("disaster_tweet_classification","en")\
+            .setInputCols(["document","token"])\
+            .setOutputCol("class")
+
+pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val document_assembler = new DocumentAssembler()
+    .setInputCol("text")
+    .setOutputCol("document")
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document") 
+    .setOutputCol("token")  
+    
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("disaster_tweet_classification","en")
+            .setInputCols(Array("document","token"))
+            .setOutputCol("class")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|disaster_tweet_classification|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+References
+
+https://huggingface.co/aellxx/disaster-tweet-classification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-disaster_tweet_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-disaster_tweet_classification_pipeline_en.md
new file mode 100644
index 00000000000000..471c9d238dc1ea
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-disaster_tweet_classification_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English disaster_tweet_classification_pipeline pipeline XlmRoBertaForSequenceClassification from DeGrimer
+author: John Snow Labs
+name: disaster_tweet_classification_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`disaster_tweet_classification_pipeline` is a English model originally trained by DeGrimer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/disaster_tweet_classification_pipeline_en_5.5.1_3.0_1737881346289.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/disaster_tweet_classification_pipeline_en_5.5.1_3.0_1737881346289.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("disaster_tweet_classification_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("disaster_tweet_classification_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|disaster_tweet_classification_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/DeGrimer/disaster_tweet_classification
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distil_bert_fine_tuned_boolq_v2_en.md b/docs/_posts/ahmedlone127/2025-01-26-distil_bert_fine_tuned_boolq_v2_en.md
new file mode 100644
index 00000000000000..506e7f46be7236
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distil_bert_fine_tuned_boolq_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distil_bert_fine_tuned_boolq_v2 DistilBertForSequenceClassification from rycecorn
+author: John Snow Labs
+name: distil_bert_fine_tuned_boolq_v2
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distil_bert_fine_tuned_boolq_v2` is a English model originally trained by rycecorn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distil_bert_fine_tuned_boolq_v2_en_5.5.1_3.0_1737928792339.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distil_bert_fine_tuned_boolq_v2_en_5.5.1_3.0_1737928792339.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distil_bert_fine_tuned_boolq_v2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distil_bert_fine_tuned_boolq_v2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distil_bert_fine_tuned_boolq_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/rycecorn/distil-bert-fine-tuned-boolq-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distil_bert_fine_tuned_boolq_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-distil_bert_fine_tuned_boolq_v2_pipeline_en.md
new file mode 100644
index 00000000000000..1085bba000c509
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distil_bert_fine_tuned_boolq_v2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distil_bert_fine_tuned_boolq_v2_pipeline pipeline DistilBertForSequenceClassification from rycecorn
+author: John Snow Labs
+name: distil_bert_fine_tuned_boolq_v2_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distil_bert_fine_tuned_boolq_v2_pipeline` is a English model originally trained by rycecorn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distil_bert_fine_tuned_boolq_v2_pipeline_en_5.5.1_3.0_1737928806185.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distil_bert_fine_tuned_boolq_v2_pipeline_en_5.5.1_3.0_1737928806185.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distil_bert_fine_tuned_boolq_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distil_bert_fine_tuned_boolq_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distil_bert_fine_tuned_boolq_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/rycecorn/distil-bert-fine-tuned-boolq-v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distil_bert_pii_model_en.md b/docs/_posts/ahmedlone127/2025-01-26-distil_bert_pii_model_en.md
new file mode 100644
index 00000000000000..ef55134bce3d82
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distil_bert_pii_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distil_bert_pii_model DistilBertForTokenClassification from Ozgunn
+author: John Snow Labs
+name: distil_bert_pii_model
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distil_bert_pii_model` is a English model originally trained by Ozgunn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distil_bert_pii_model_en_5.5.1_3.0_1737909656144.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distil_bert_pii_model_en_5.5.1_3.0_1737909656144.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distil_bert_pii_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distil_bert_pii_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distil_bert_pii_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/Ozgunn/distil_bert_pii_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distil_bert_pii_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-distil_bert_pii_model_pipeline_en.md
new file mode 100644
index 00000000000000..c4690854359b30
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distil_bert_pii_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distil_bert_pii_model_pipeline pipeline DistilBertForTokenClassification from Ozgunn
+author: John Snow Labs
+name: distil_bert_pii_model_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distil_bert_pii_model_pipeline` is a English model originally trained by Ozgunn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distil_bert_pii_model_pipeline_en_5.5.1_3.0_1737909668889.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distil_bert_pii_model_pipeline_en_5.5.1_3.0_1737909668889.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distil_bert_pii_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distil_bert_pii_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distil_bert_pii_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|243.9 MB|
+
+## References
+
+https://huggingface.co/Ozgunn/distil_bert_pii_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbart_xsum_9_6_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbart_xsum_9_6_en.md
new file mode 100644
index 00000000000000..b889a098b79cc7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbart_xsum_9_6_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilbart_xsum_9_6 BartTransformer from sshleifer
+author: John Snow Labs
+name: distilbart_xsum_9_6
+date: 2025-01-26
+tags: [en, open_source, onnx, text_generation, bart]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BartTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbart_xsum_9_6` is a English model originally trained by sshleifer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbart_xsum_9_6_en_5.5.1_3.0_1737924453005.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbart_xsum_9_6_en_5.5.1_3.0_1737924453005.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = BartTransformer.pretrained("distilbart_xsum_9_6","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = BartTransformer.pretrained("distilbart_xsum_9_6","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbart_xsum_9_6|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|886.8 MB|
+
+## References
+
+https://huggingface.co/sshleifer/distilbart-xsum-9-6
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbart_xsum_9_6_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbart_xsum_9_6_pipeline_en.md
new file mode 100644
index 00000000000000..c910919a16f607
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbart_xsum_9_6_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbart_xsum_9_6_pipeline pipeline BartTransformer from sshleifer
+author: John Snow Labs
+name: distilbart_xsum_9_6_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbart_xsum_9_6_pipeline` is a English model originally trained by sshleifer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbart_xsum_9_6_pipeline_en_5.5.1_3.0_1737924701942.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbart_xsum_9_6_pipeline_en_5.5.1_3.0_1737924701942.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbart_xsum_9_6_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbart_xsum_9_6_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbart_xsum_9_6_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|886.8 MB|
+
+## References
+
+https://huggingface.co/sshleifer/distilbart-xsum-9-6
+
+## Included Models
+
+- DocumentAssembler
+- BartTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_fire_class_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_fire_class_en.md
new file mode 100644
index 00000000000000..fe0af5d2fc6a96
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_fire_class_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_fire_class DistilBertForSequenceClassification from JudeChaer
+author: John Snow Labs
+name: distilbert_base_fire_class
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_fire_class` is a English model originally trained by JudeChaer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_fire_class_en_5.5.1_3.0_1737905128706.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_fire_class_en_5.5.1_3.0_1737905128706.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_fire_class","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_fire_class", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_fire_class|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/JudeChaer/distilbert-base-fire-class
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_fire_class_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_fire_class_pipeline_en.md
new file mode 100644
index 00000000000000..41cbde932db2c1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_fire_class_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_fire_class_pipeline pipeline DistilBertForSequenceClassification from JudeChaer
+author: John Snow Labs
+name: distilbert_base_fire_class_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_fire_class_pipeline` is a English model originally trained by JudeChaer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_fire_class_pipeline_en_5.5.1_3.0_1737905142031.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_fire_class_pipeline_en_5.5.1_3.0_1737905142031.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_fire_class_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_fire_class_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_fire_class_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/JudeChaer/distilbert-base-fire-class
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_imdb_jialicheng_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_imdb_jialicheng_en.md
new file mode 100644
index 00000000000000..032cf724a966bd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_imdb_jialicheng_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_imdb_jialicheng DistilBertForSequenceClassification from jialicheng
+author: John Snow Labs
+name: distilbert_base_imdb_jialicheng
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_imdb_jialicheng` is a English model originally trained by jialicheng.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_imdb_jialicheng_en_5.5.1_3.0_1737904846875.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_imdb_jialicheng_en_5.5.1_3.0_1737904846875.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_imdb_jialicheng","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_imdb_jialicheng", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_imdb_jialicheng|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/jialicheng/distilbert-base-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_imdb_jialicheng_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_imdb_jialicheng_pipeline_en.md
new file mode 100644
index 00000000000000..06c4ed5bc6249f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_imdb_jialicheng_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_imdb_jialicheng_pipeline pipeline DistilBertForSequenceClassification from jialicheng
+author: John Snow Labs
+name: distilbert_base_imdb_jialicheng_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_imdb_jialicheng_pipeline` is a English model originally trained by jialicheng.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_imdb_jialicheng_pipeline_en_5.5.1_3.0_1737904860491.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_imdb_jialicheng_pipeline_en_5.5.1_3.0_1737904860491.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_imdb_jialicheng_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_imdb_jialicheng_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_imdb_jialicheng_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/jialicheng/distilbert-base-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_multilingual_cased_finetuned_language_identification_pipeline_xx.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_multilingual_cased_finetuned_language_identification_pipeline_xx.md
new file mode 100644
index 00000000000000..95fe9d9048c415
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_multilingual_cased_finetuned_language_identification_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual distilbert_base_multilingual_cased_finetuned_language_identification_pipeline pipeline DistilBertForSequenceClassification from niharrp9
+author: John Snow Labs
+name: distilbert_base_multilingual_cased_finetuned_language_identification_pipeline
+date: 2025-01-26
+tags: [xx, open_source, pipeline, onnx]
+task: Text Classification
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_multilingual_cased_finetuned_language_identification_pipeline` is a Multilingual model originally trained by niharrp9.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_multilingual_cased_finetuned_language_identification_pipeline_xx_5.5.1_3.0_1737873204741.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_multilingual_cased_finetuned_language_identification_pipeline_xx_5.5.1_3.0_1737873204741.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_multilingual_cased_finetuned_language_identification_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_multilingual_cased_finetuned_language_identification_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_multilingual_cased_finetuned_language_identification_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|507.7 MB|
+
+## References
+
+https://huggingface.co/niharrp9/distilbert-base-multilingual-cased-finetuned-language-identification
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_multilingual_cased_finetuned_language_identification_xx.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_multilingual_cased_finetuned_language_identification_xx.md
new file mode 100644
index 00000000000000..90bb5090e789a6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_multilingual_cased_finetuned_language_identification_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual distilbert_base_multilingual_cased_finetuned_language_identification DistilBertForSequenceClassification from niharrp9
+author: John Snow Labs
+name: distilbert_base_multilingual_cased_finetuned_language_identification
+date: 2025-01-26
+tags: [xx, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_multilingual_cased_finetuned_language_identification` is a Multilingual model originally trained by niharrp9.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_multilingual_cased_finetuned_language_identification_xx_5.5.1_3.0_1737873177013.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_multilingual_cased_finetuned_language_identification_xx_5.5.1_3.0_1737873177013.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_multilingual_cased_finetuned_language_identification","xx") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_multilingual_cased_finetuned_language_identification", "xx")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_multilingual_cased_finetuned_language_identification|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|xx|
+|Size:|507.7 MB|
+
+## References
+
+https://huggingface.co/niharrp9/distilbert-base-multilingual-cased-finetuned-language-identification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_multilingual_cased_finetuned_ner_pipeline_xx.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_multilingual_cased_finetuned_ner_pipeline_xx.md
new file mode 100644
index 00000000000000..52b849dba4e4c1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_multilingual_cased_finetuned_ner_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual distilbert_base_multilingual_cased_finetuned_ner_pipeline pipeline DistilBertForTokenClassification from janko
+author: John Snow Labs
+name: distilbert_base_multilingual_cased_finetuned_ner_pipeline
+date: 2025-01-26
+tags: [xx, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_multilingual_cased_finetuned_ner_pipeline` is a Multilingual model originally trained by janko.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_multilingual_cased_finetuned_ner_pipeline_xx_5.5.1_3.0_1737909928973.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_multilingual_cased_finetuned_ner_pipeline_xx_5.5.1_3.0_1737909928973.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_multilingual_cased_finetuned_ner_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_multilingual_cased_finetuned_ner_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_multilingual_cased_finetuned_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|505.4 MB|
+
+## References
+
+https://huggingface.co/janko/distilbert-base-multilingual-cased-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_multilingual_cased_finetuned_ner_xx.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_multilingual_cased_finetuned_ner_xx.md
new file mode 100644
index 00000000000000..6881e580d5fb2a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_multilingual_cased_finetuned_ner_xx.md
@@ -0,0 +1,92 @@
+---
+layout: model
+title: Multilingual distilbert_base_multilingual_cased_finetuned_ner DistilBertForTokenClassification from ALWN
+author: John Snow Labs
+name: distilbert_base_multilingual_cased_finetuned_ner
+date: 2025-01-26
+tags: [bert, xx, open_source, token_classification, onnx]
+task: Named Entity Recognition
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_multilingual_cased_finetuned_ner` is a Multilingual model originally trained by ALWN.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_multilingual_cased_finetuned_ner_xx_5.5.1_3.0_1737909897648.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_multilingual_cased_finetuned_ner_xx_5.5.1_3.0_1737909897648.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("documents")
+    
+    
+tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_multilingual_cased_finetuned_ner","xx") \
+            .setInputCols(["documents","token"]) \
+            .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCol("text") 
+    .setOutputCol("embeddings")
+    
+val tokenClassifier = DistilBertForTokenClassification  
+    .pretrained("distilbert_base_multilingual_cased_finetuned_ner", "xx")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_multilingual_cased_finetuned_ner|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|xx|
+|Size:|505.4 MB|
+
+## References
+
+References
+
+https://huggingface.co/ALWN/distilbert-base-multilingual-cased-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_thai_sentiment_pipeline_th.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_thai_sentiment_pipeline_th.md
new file mode 100644
index 00000000000000..cf7715301a5674
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_thai_sentiment_pipeline_th.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Thai distilbert_base_thai_sentiment_pipeline pipeline DistilBertForSequenceClassification from FlukeTJ
+author: John Snow Labs
+name: distilbert_base_thai_sentiment_pipeline
+date: 2025-01-26
+tags: [th, open_source, pipeline, onnx]
+task: Text Classification
+language: th
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_thai_sentiment_pipeline` is a Thai model originally trained by FlukeTJ.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_thai_sentiment_pipeline_th_5.5.1_3.0_1737873247245.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_thai_sentiment_pipeline_th_5.5.1_3.0_1737873247245.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_thai_sentiment_pipeline", lang = "th")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_thai_sentiment_pipeline", lang = "th")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_thai_sentiment_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|th|
+|Size:|220.6 MB|
+
+## References
+
+https://huggingface.co/FlukeTJ/distilbert-base-thai-sentiment
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_thai_sentiment_th.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_thai_sentiment_th.md
new file mode 100644
index 00000000000000..6dcc2b92aeb391
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_thai_sentiment_th.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Thai distilbert_base_thai_sentiment DistilBertForSequenceClassification from FlukeTJ
+author: John Snow Labs
+name: distilbert_base_thai_sentiment
+date: 2025-01-26
+tags: [th, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: th
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_thai_sentiment` is a Thai model originally trained by FlukeTJ.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_thai_sentiment_th_5.5.1_3.0_1737873235334.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_thai_sentiment_th_5.5.1_3.0_1737873235334.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_thai_sentiment","th") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_thai_sentiment", "th")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_thai_sentiment|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|th|
+|Size:|220.6 MB|
+
+## References
+
+https://huggingface.co/FlukeTJ/distilbert-base-thai-sentiment
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_3epoch7_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_3epoch7_en.md
new file mode 100644
index 00000000000000..a90ef7518c0657
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_3epoch7_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_3epoch7 DistilBertForSequenceClassification from dianamihalache27
+author: John Snow Labs
+name: distilbert_base_uncased_3epoch7
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_3epoch7` is a English model originally trained by dianamihalache27.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_3epoch7_en_5.5.1_3.0_1737873436326.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_3epoch7_en_5.5.1_3.0_1737873436326.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_3epoch7","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_3epoch7", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_3epoch7|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/dianamihalache27/distilbert-base-uncased_3epoch7
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_3epoch7_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_3epoch7_pipeline_en.md
new file mode 100644
index 00000000000000..7b3492cf588b76
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_3epoch7_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_3epoch7_pipeline pipeline DistilBertForSequenceClassification from dianamihalache27
+author: John Snow Labs
+name: distilbert_base_uncased_3epoch7_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_3epoch7_pipeline` is a English model originally trained by dianamihalache27.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_3epoch7_pipeline_en_5.5.1_3.0_1737873450207.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_3epoch7_pipeline_en_5.5.1_3.0_1737873450207.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_3epoch7_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_3epoch7_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_3epoch7_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/dianamihalache27/distilbert-base-uncased_3epoch7
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_address_model_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_address_model_en.md
new file mode 100644
index 00000000000000..e4b1d5de2d65c7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_address_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_address_model DistilBertForTokenClassification from Sunmar
+author: John Snow Labs
+name: distilbert_base_uncased_address_model
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_address_model` is a English model originally trained by Sunmar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_address_model_en_5.5.1_3.0_1737909779807.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_address_model_en_5.5.1_3.0_1737909779807.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_address_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_address_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_address_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Sunmar/distilbert-base-uncased_address_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_address_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_address_model_pipeline_en.md
new file mode 100644
index 00000000000000..57a39e46d3cee8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_address_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_address_model_pipeline pipeline DistilBertForTokenClassification from Sunmar
+author: John Snow Labs
+name: distilbert_base_uncased_address_model_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_address_model_pipeline` is a English model originally trained by Sunmar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_address_model_pipeline_en_5.5.1_3.0_1737909793027.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_address_model_pipeline_en_5.5.1_3.0_1737909793027.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_address_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_address_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_address_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Sunmar/distilbert-base-uncased_address_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_cola_markyyds_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_cola_markyyds_en.md
new file mode 100644
index 00000000000000..90dbe14d7604fe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_cola_markyyds_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_cola_markyyds DistilBertForSequenceClassification from markyyds
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_cola_markyyds
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_cola_markyyds` is a English model originally trained by markyyds.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_cola_markyyds_en_5.5.1_3.0_1737929035413.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_cola_markyyds_en_5.5.1_3.0_1737929035413.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_cola_markyyds","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_cola_markyyds", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_cola_markyyds|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/markyyds/distilbert-base-uncased-finetuned-cola
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_cola_markyyds_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_cola_markyyds_pipeline_en.md
new file mode 100644
index 00000000000000..2ea4b707ade188
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_cola_markyyds_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_cola_markyyds_pipeline pipeline DistilBertForSequenceClassification from markyyds
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_cola_markyyds_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_cola_markyyds_pipeline` is a English model originally trained by markyyds.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_cola_markyyds_pipeline_en_5.5.1_3.0_1737929049075.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_cola_markyyds_pipeline_en_5.5.1_3.0_1737929049075.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_cola_markyyds_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_cola_markyyds_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_cola_markyyds_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/markyyds/distilbert-base-uncased-finetuned-cola
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_cola_wangjiawei2003_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_cola_wangjiawei2003_en.md
new file mode 100644
index 00000000000000..b741a9317fc422
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_cola_wangjiawei2003_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_cola_wangjiawei2003 DistilBertForSequenceClassification from wangjiawei2003
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_cola_wangjiawei2003
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_cola_wangjiawei2003` is a English model originally trained by wangjiawei2003.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_cola_wangjiawei2003_en_5.5.1_3.0_1737905448523.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_cola_wangjiawei2003_en_5.5.1_3.0_1737905448523.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_cola_wangjiawei2003","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_cola_wangjiawei2003", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_cola_wangjiawei2003|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/wangjiawei2003/distilbert-base-uncased-finetuned-cola
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_cola_wangjiawei2003_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_cola_wangjiawei2003_pipeline_en.md
new file mode 100644
index 00000000000000..f628a09ccbe0d7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_cola_wangjiawei2003_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_cola_wangjiawei2003_pipeline pipeline DistilBertForSequenceClassification from wangjiawei2003
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_cola_wangjiawei2003_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_cola_wangjiawei2003_pipeline` is a English model originally trained by wangjiawei2003.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_cola_wangjiawei2003_pipeline_en_5.5.1_3.0_1737905462530.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_cola_wangjiawei2003_pipeline_en_5.5.1_3.0_1737905462530.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_cola_wangjiawei2003_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_cola_wangjiawei2003_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_cola_wangjiawei2003_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/wangjiawei2003/distilbert-base-uncased-finetuned-cola
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_35m_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_35m_en.md
new file mode 100644
index 00000000000000..3bd28b711e15ad
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_35m_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_35m DistilBertForSequenceClassification from 35m
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_35m
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_35m` is a English model originally trained by 35m.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_35m_en_5.5.1_3.0_1737904970578.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_35m_en_5.5.1_3.0_1737904970578.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_35m","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_35m", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_35m|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/35m/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_35m_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_35m_pipeline_en.md
new file mode 100644
index 00000000000000..9326bf55282d51
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_35m_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_35m_pipeline pipeline DistilBertForSequenceClassification from 35m
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_35m_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_35m_pipeline` is a English model originally trained by 35m.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_35m_pipeline_en_5.5.1_3.0_1737904984177.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_35m_pipeline_en_5.5.1_3.0_1737904984177.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_35m_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_35m_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_35m_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/35m/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_amnamahmood122_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_amnamahmood122_en.md
new file mode 100644
index 00000000000000..c463ee12363895
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_amnamahmood122_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_amnamahmood122 DistilBertForSequenceClassification from Amnamahmood122
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_amnamahmood122
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_amnamahmood122` is a English model originally trained by Amnamahmood122.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_amnamahmood122_en_5.5.1_3.0_1737905435902.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_amnamahmood122_en_5.5.1_3.0_1737905435902.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_amnamahmood122","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_amnamahmood122", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_amnamahmood122|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Amnamahmood122/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_amnamahmood122_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_amnamahmood122_pipeline_en.md
new file mode 100644
index 00000000000000..514c9f35ad7651
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_amnamahmood122_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_amnamahmood122_pipeline pipeline DistilBertForSequenceClassification from Amnamahmood122
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_amnamahmood122_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_amnamahmood122_pipeline` is a English model originally trained by Amnamahmood122.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_amnamahmood122_pipeline_en_5.5.1_3.0_1737905449081.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_amnamahmood122_pipeline_en_5.5.1_3.0_1737905449081.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_amnamahmood122_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_amnamahmood122_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_amnamahmood122_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Amnamahmood122/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_bovision_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_bovision_en.md
new file mode 100644
index 00000000000000..84d5ce5c89b590
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_bovision_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_bovision DistilBertForSequenceClassification from bovision
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_bovision
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_bovision` is a English model originally trained by bovision.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_bovision_en_5.5.1_3.0_1737928815457.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_bovision_en_5.5.1_3.0_1737928815457.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_bovision","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_bovision", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_bovision|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/bovision/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_bovision_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_bovision_pipeline_en.md
new file mode 100644
index 00000000000000..e8b33d0308dd83
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_bovision_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_bovision_pipeline pipeline DistilBertForSequenceClassification from bovision
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_bovision_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_bovision_pipeline` is a English model originally trained by bovision.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_bovision_pipeline_en_5.5.1_3.0_1737928828893.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_bovision_pipeline_en_5.5.1_3.0_1737928828893.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_bovision_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_bovision_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_bovision_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/bovision/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_byungsangkim_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_byungsangkim_en.md
new file mode 100644
index 00000000000000..a05357ee6b4ad0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_byungsangkim_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_byungsangkim DistilBertForSequenceClassification from byungsangkim
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_byungsangkim
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_byungsangkim` is a English model originally trained by byungsangkim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_byungsangkim_en_5.5.1_3.0_1737873557519.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_byungsangkim_en_5.5.1_3.0_1737873557519.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_byungsangkim","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_byungsangkim", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_byungsangkim|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/byungsangkim/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_byungsangkim_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_byungsangkim_pipeline_en.md
new file mode 100644
index 00000000000000..18c25b6687848c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_byungsangkim_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_byungsangkim_pipeline pipeline DistilBertForSequenceClassification from byungsangkim
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_byungsangkim_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_byungsangkim_pipeline` is a English model originally trained by byungsangkim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_byungsangkim_pipeline_en_5.5.1_3.0_1737873571111.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_byungsangkim_pipeline_en_5.5.1_3.0_1737873571111.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_byungsangkim_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_byungsangkim_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_byungsangkim_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/byungsangkim/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_cheng_cherry_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_cheng_cherry_en.md
new file mode 100644
index 00000000000000..eb4b0b8623cd2d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_cheng_cherry_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_cheng_cherry DistilBertForSequenceClassification from cheng-cherry
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_cheng_cherry
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_cheng_cherry` is a English model originally trained by cheng-cherry.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_cheng_cherry_en_5.5.1_3.0_1737873450634.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_cheng_cherry_en_5.5.1_3.0_1737873450634.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_cheng_cherry","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_cheng_cherry", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_cheng_cherry|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/cheng-cherry/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_cheng_cherry_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_cheng_cherry_pipeline_en.md
new file mode 100644
index 00000000000000..847a75b9b8fe6c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_cheng_cherry_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_cheng_cherry_pipeline pipeline DistilBertForSequenceClassification from cheng-cherry
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_cheng_cherry_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_cheng_cherry_pipeline` is a English model originally trained by cheng-cherry.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_cheng_cherry_pipeline_en_5.5.1_3.0_1737873467280.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_cheng_cherry_pipeline_en_5.5.1_3.0_1737873467280.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_cheng_cherry_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_cheng_cherry_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_cheng_cherry_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/cheng-cherry/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_darmendarizp_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_darmendarizp_en.md
new file mode 100644
index 00000000000000..34feba1e12c433
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_darmendarizp_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_darmendarizp DistilBertForSequenceClassification from darmendarizp
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_darmendarizp
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_darmendarizp` is a English model originally trained by darmendarizp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_darmendarizp_en_5.5.1_3.0_1737873597612.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_darmendarizp_en_5.5.1_3.0_1737873597612.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_darmendarizp","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_darmendarizp", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_darmendarizp|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/darmendarizp/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_darmendarizp_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_darmendarizp_pipeline_en.md
new file mode 100644
index 00000000000000..9e8983ae092a63
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_darmendarizp_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_darmendarizp_pipeline pipeline DistilBertForSequenceClassification from darmendarizp
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_darmendarizp_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_darmendarizp_pipeline` is a English model originally trained by darmendarizp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_darmendarizp_pipeline_en_5.5.1_3.0_1737873612252.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_darmendarizp_pipeline_en_5.5.1_3.0_1737873612252.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_darmendarizp_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_darmendarizp_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_darmendarizp_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/darmendarizp/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_dd3434_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_dd3434_en.md
new file mode 100644
index 00000000000000..ca0c9d533de698
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_dd3434_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_dd3434 DistilBertForSequenceClassification from dd3434
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_dd3434
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_dd3434` is a English model originally trained by dd3434.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_dd3434_en_5.5.1_3.0_1737904860163.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_dd3434_en_5.5.1_3.0_1737904860163.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_dd3434","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_dd3434", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_dd3434|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/dd3434/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_dd3434_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_dd3434_pipeline_en.md
new file mode 100644
index 00000000000000..8759a8661155ee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_dd3434_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_dd3434_pipeline pipeline DistilBertForSequenceClassification from dd3434
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_dd3434_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_dd3434_pipeline` is a English model originally trained by dd3434.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_dd3434_pipeline_en_5.5.1_3.0_1737904875866.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_dd3434_pipeline_en_5.5.1_3.0_1737904875866.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_dd3434_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_dd3434_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_dd3434_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/dd3434/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_ecoabhi_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_ecoabhi_en.md
new file mode 100644
index 00000000000000..cc1bad07365387
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_ecoabhi_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_ecoabhi DistilBertForSequenceClassification from ecoabhi
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_ecoabhi
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_ecoabhi` is a English model originally trained by ecoabhi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_ecoabhi_en_5.5.1_3.0_1737904617237.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_ecoabhi_en_5.5.1_3.0_1737904617237.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_ecoabhi","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_ecoabhi", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_ecoabhi|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/ecoabhi/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_ecoabhi_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_ecoabhi_pipeline_en.md
new file mode 100644
index 00000000000000..bc1a5197118810
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_ecoabhi_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_ecoabhi_pipeline pipeline DistilBertForSequenceClassification from ecoabhi
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_ecoabhi_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_ecoabhi_pipeline` is a English model originally trained by ecoabhi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_ecoabhi_pipeline_en_5.5.1_3.0_1737904635463.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_ecoabhi_pipeline_en_5.5.1_3.0_1737904635463.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_ecoabhi_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_ecoabhi_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_ecoabhi_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/ecoabhi/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_graduation_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_graduation_en.md
new file mode 100644
index 00000000000000..808a501bdb3a6a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_graduation_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_graduation DistilBertForSequenceClassification from 3bdoo
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_graduation
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_graduation` is a English model originally trained by 3bdoo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_graduation_en_5.5.1_3.0_1737904743937.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_graduation_en_5.5.1_3.0_1737904743937.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_graduation","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_graduation", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_graduation|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/3bdoo/distilbert-base-uncased-finetuned-emotion-graduation
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_graduation_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_graduation_pipeline_en.md
new file mode 100644
index 00000000000000..83a33b9ffae39a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_graduation_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_graduation_pipeline pipeline DistilBertForSequenceClassification from 3bdoo
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_graduation_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_graduation_pipeline` is a English model originally trained by 3bdoo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_graduation_pipeline_en_5.5.1_3.0_1737904757051.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_graduation_pipeline_en_5.5.1_3.0_1737904757051.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_graduation_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_graduation_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_graduation_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/3bdoo/distilbert-base-uncased-finetuned-emotion-graduation
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_hungcu09_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_hungcu09_en.md
new file mode 100644
index 00000000000000..a99c59b9cf299e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_hungcu09_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_hungcu09 DistilBertForSequenceClassification from hungcu09
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_hungcu09
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_hungcu09` is a English model originally trained by hungcu09.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_hungcu09_en_5.5.1_3.0_1737904746524.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_hungcu09_en_5.5.1_3.0_1737904746524.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_hungcu09","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_hungcu09", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_hungcu09|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/hungcu09/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_hungcu09_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_hungcu09_pipeline_en.md
new file mode 100644
index 00000000000000..977419818cee80
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_hungcu09_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_hungcu09_pipeline pipeline DistilBertForSequenceClassification from hungcu09
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_hungcu09_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_hungcu09_pipeline` is a English model originally trained by hungcu09.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_hungcu09_pipeline_en_5.5.1_3.0_1737904759589.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_hungcu09_pipeline_en_5.5.1_3.0_1737904759589.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_hungcu09_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_hungcu09_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_hungcu09_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/hungcu09/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_jpgacrama_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_jpgacrama_en.md
new file mode 100644
index 00000000000000..99535b1cca1daa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_jpgacrama_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_jpgacrama DistilBertForSequenceClassification from jpgacrama
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_jpgacrama
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_jpgacrama` is a English model originally trained by jpgacrama.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_jpgacrama_en_5.5.1_3.0_1737928698688.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_jpgacrama_en_5.5.1_3.0_1737928698688.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_jpgacrama","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_jpgacrama", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_jpgacrama|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/jpgacrama/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_jpgacrama_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_jpgacrama_pipeline_en.md
new file mode 100644
index 00000000000000..732c37e743dbd2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_jpgacrama_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_jpgacrama_pipeline pipeline DistilBertForSequenceClassification from jpgacrama
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_jpgacrama_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_jpgacrama_pipeline` is a English model originally trained by jpgacrama.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_jpgacrama_pipeline_en_5.5.1_3.0_1737928712756.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_jpgacrama_pipeline_en_5.5.1_3.0_1737928712756.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_jpgacrama_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_jpgacrama_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_jpgacrama_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/jpgacrama/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_pedrolance_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_pedrolance_en.md
new file mode 100644
index 00000000000000..b4aec6a8c20171
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_pedrolance_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_pedrolance DistilBertForSequenceClassification from pedrolance
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_pedrolance
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_pedrolance` is a English model originally trained by pedrolance.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_pedrolance_en_5.5.1_3.0_1737928928181.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_pedrolance_en_5.5.1_3.0_1737928928181.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_pedrolance","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_pedrolance", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_pedrolance|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/pedrolance/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_pedrolance_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_pedrolance_pipeline_en.md
new file mode 100644
index 00000000000000..f43a57aa783329
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_pedrolance_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_pedrolance_pipeline pipeline DistilBertForSequenceClassification from pedrolance
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_pedrolance_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_pedrolance_pipeline` is a English model originally trained by pedrolance.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_pedrolance_pipeline_en_5.5.1_3.0_1737928941901.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_pedrolance_pipeline_en_5.5.1_3.0_1737928941901.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_pedrolance_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_pedrolance_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_pedrolance_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/pedrolance/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_shanzey_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_shanzey_en.md
new file mode 100644
index 00000000000000..2168f2f31a13d6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_shanzey_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_shanzey DistilBertForSequenceClassification from Shanzey
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_shanzey
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_shanzey` is a English model originally trained by Shanzey.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_shanzey_en_5.5.1_3.0_1737929357560.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_shanzey_en_5.5.1_3.0_1737929357560.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_shanzey","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_shanzey", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_shanzey|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Shanzey/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_shanzey_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_shanzey_pipeline_en.md
new file mode 100644
index 00000000000000..1274e2f942caa4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_emotion_shanzey_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_shanzey_pipeline pipeline DistilBertForSequenceClassification from Shanzey
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_shanzey_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_shanzey_pipeline` is a English model originally trained by Shanzey.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_shanzey_pipeline_en_5.5.1_3.0_1737929371529.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_shanzey_pipeline_en_5.5.1_3.0_1737929371529.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_shanzey_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_shanzey_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_shanzey_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Shanzey/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_fake_news_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_fake_news_en.md
new file mode 100644
index 00000000000000..87bad232a47683
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_fake_news_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_fake_news DistilBertForSequenceClassification from jaranohaal
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_fake_news
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_fake_news` is a English model originally trained by jaranohaal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_fake_news_en_5.5.1_3.0_1737873321822.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_fake_news_en_5.5.1_3.0_1737873321822.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_fake_news","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_fake_news", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_fake_news|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/jaranohaal/distilbert-base-uncased-finetuned-fake-news
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_fake_news_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_fake_news_pipeline_en.md
new file mode 100644
index 00000000000000..c3268bbfc26418
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_fake_news_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_fake_news_pipeline pipeline DistilBertForSequenceClassification from jaranohaal
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_fake_news_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_fake_news_pipeline` is a English model originally trained by jaranohaal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_fake_news_pipeline_en_5.5.1_3.0_1737873344973.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_fake_news_pipeline_en_5.5.1_3.0_1737873344973.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_fake_news_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_fake_news_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_fake_news_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/jaranohaal/distilbert-base-uncased-finetuned-fake-news
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_imdb_abdulkoko_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_imdb_abdulkoko_en.md
new file mode 100644
index 00000000000000..817f6e20f29c45
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_imdb_abdulkoko_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_abdulkoko DistilBertEmbeddings from Abdulkoko
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_abdulkoko
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_abdulkoko` is a English model originally trained by Abdulkoko.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_abdulkoko_en_5.5.1_3.0_1737930325572.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_abdulkoko_en_5.5.1_3.0_1737930325572.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_abdulkoko","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_abdulkoko","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_abdulkoko|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Abdulkoko/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_imdb_abdulkoko_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_imdb_abdulkoko_pipeline_en.md
new file mode 100644
index 00000000000000..ac287ccc628710
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_imdb_abdulkoko_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_abdulkoko_pipeline pipeline DistilBertEmbeddings from Abdulkoko
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_abdulkoko_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_abdulkoko_pipeline` is a English model originally trained by Abdulkoko.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_abdulkoko_pipeline_en_5.5.1_3.0_1737930338473.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_abdulkoko_pipeline_en_5.5.1_3.0_1737930338473.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_abdulkoko_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_abdulkoko_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_abdulkoko_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Abdulkoko/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_ner_cloud093_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_ner_cloud093_en.md
new file mode 100644
index 00000000000000..09124d45f9b3ca
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_ner_cloud093_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_cloud093 DistilBertForTokenClassification from cloud093
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_cloud093
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_cloud093` is a English model originally trained by cloud093.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_cloud093_en_5.5.1_3.0_1737909535405.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_cloud093_en_5.5.1_3.0_1737909535405.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_cloud093","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_cloud093", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_cloud093|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/cloud093/distilbert-base-uncased-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_ner_cloud093_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_ner_cloud093_pipeline_en.md
new file mode 100644
index 00000000000000..04ab68c4bdf0d1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_ner_cloud093_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_cloud093_pipeline pipeline DistilBertForTokenClassification from cloud093
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_cloud093_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_cloud093_pipeline` is a English model originally trained by cloud093.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_cloud093_pipeline_en_5.5.1_3.0_1737909552972.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_cloud093_pipeline_en_5.5.1_3.0_1737909552972.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_ner_cloud093_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_ner_cloud093_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_cloud093_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/cloud093/distilbert-base-uncased-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_on_emotions_data_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_on_emotions_data_en.md
new file mode 100644
index 00000000000000..a3a407b1468455
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_on_emotions_data_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_on_emotions_data DistilBertForSequenceClassification from Shubhu07
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_on_emotions_data
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_on_emotions_data` is a English model originally trained by Shubhu07.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_on_emotions_data_en_5.5.1_3.0_1737904617022.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_on_emotions_data_en_5.5.1_3.0_1737904617022.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_on_emotions_data","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_on_emotions_data", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_on_emotions_data|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Shubhu07/distilbert-base-uncased_finetuned_on_emotions_data
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_on_emotions_data_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_on_emotions_data_pipeline_en.md
new file mode 100644
index 00000000000000..59c4bfd22455d7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_on_emotions_data_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_on_emotions_data_pipeline pipeline DistilBertForSequenceClassification from Shubhu07
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_on_emotions_data_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_on_emotions_data_pipeline` is a English model originally trained by Shubhu07.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_on_emotions_data_pipeline_en_5.5.1_3.0_1737904631410.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_on_emotions_data_pipeline_en_5.5.1_3.0_1737904631410.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_on_emotions_data_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_on_emotions_data_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_on_emotions_data_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Shubhu07/distilbert-base-uncased_finetuned_on_emotions_data
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_wine_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_wine_en.md
new file mode 100644
index 00000000000000..f3f89b77e183d4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_wine_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_wine DistilBertForSequenceClassification from danieljhand
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_wine
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_wine` is a English model originally trained by danieljhand.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_wine_en_5.5.1_3.0_1737929278084.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_wine_en_5.5.1_3.0_1737929278084.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_wine","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_wine", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_wine|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/danieljhand/distilbert-base-uncased-finetuned-wine
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_wine_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_wine_pipeline_en.md
new file mode 100644
index 00000000000000..3bfe3b956ed4cf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_finetuned_wine_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_wine_pipeline pipeline DistilBertForSequenceClassification from danieljhand
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_wine_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_wine_pipeline` is a English model originally trained by danieljhand.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_wine_pipeline_en_5.5.1_3.0_1737929292851.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_wine_pipeline_en_5.5.1_3.0_1737929292851.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_wine_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_wine_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_wine_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.6 MB|
+
+## References
+
+https://huggingface.co/danieljhand/distilbert-base-uncased-finetuned-wine
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_juan_mathew_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_juan_mathew_en.md
new file mode 100644
index 00000000000000..3cc6e04d07121a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_juan_mathew_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_juan_mathew DistilBertForSequenceClassification from juan-mathew
+author: John Snow Labs
+name: distilbert_base_uncased_juan_mathew
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_juan_mathew` is a English model originally trained by juan-mathew.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_juan_mathew_en_5.5.1_3.0_1737929042010.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_juan_mathew_en_5.5.1_3.0_1737929042010.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_juan_mathew","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_juan_mathew", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_juan_mathew|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/juan-mathew/distilbert-base-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_juan_mathew_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_juan_mathew_pipeline_en.md
new file mode 100644
index 00000000000000..8469c1122232f5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_juan_mathew_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_juan_mathew_pipeline pipeline DistilBertForSequenceClassification from juan-mathew
+author: John Snow Labs
+name: distilbert_base_uncased_juan_mathew_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_juan_mathew_pipeline` is a English model originally trained by juan-mathew.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_juan_mathew_pipeline_en_5.5.1_3.0_1737929055569.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_juan_mathew_pipeline_en_5.5.1_3.0_1737929055569.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_juan_mathew_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_juan_mathew_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_juan_mathew_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/juan-mathew/distilbert-base-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_ner_finer_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_ner_finer_en.md
new file mode 100644
index 00000000000000..80b71cd32a4196
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_ner_finer_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_ner_finer DistilBertForTokenClassification from itsbilal90
+author: John Snow Labs
+name: distilbert_base_uncased_ner_finer
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_ner_finer` is a English model originally trained by itsbilal90.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_ner_finer_en_5.5.1_3.0_1737909535208.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_ner_finer_en_5.5.1_3.0_1737909535208.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_ner_finer","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_ner_finer", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_ner_finer|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/itsbilal90/distilbert-base-uncased-ner-finer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_ner_finer_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_ner_finer_pipeline_en.md
new file mode 100644
index 00000000000000..8c281c46086f12
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_ner_finer_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_ner_finer_pipeline pipeline DistilBertForTokenClassification from itsbilal90
+author: John Snow Labs
+name: distilbert_base_uncased_ner_finer_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_ner_finer_pipeline` is a English model originally trained by itsbilal90.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_ner_finer_pipeline_en_5.5.1_3.0_1737909549137.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_ner_finer_pipeline_en_5.5.1_3.0_1737909549137.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_ner_finer_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_ner_finer_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_ner_finer_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/itsbilal90/distilbert-base-uncased-ner-finer
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_stsb_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_stsb_en.md
new file mode 100644
index 00000000000000..616e63d4ded074
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_stsb_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_stsb DistilBertForSequenceClassification from gokulsrinivasagan
+author: John Snow Labs
+name: distilbert_base_uncased_stsb
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_stsb` is a English model originally trained by gokulsrinivasagan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_stsb_en_5.5.1_3.0_1737929452974.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_stsb_en_5.5.1_3.0_1737929452974.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_stsb","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_stsb", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_stsb|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/gokulsrinivasagan/distilbert-base-uncased_stsb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_stsb_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_stsb_pipeline_en.md
new file mode 100644
index 00000000000000..05660c15a19dbf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_stsb_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_stsb_pipeline pipeline DistilBertForSequenceClassification from gokulsrinivasagan
+author: John Snow Labs
+name: distilbert_base_uncased_stsb_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_stsb_pipeline` is a English model originally trained by gokulsrinivasagan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_stsb_pipeline_en_5.5.1_3.0_1737929466649.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_stsb_pipeline_en_5.5.1_3.0_1737929466649.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_stsb_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_stsb_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_stsb_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/gokulsrinivasagan/distilbert-base-uncased_stsb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_survey_identical_category_0_0_1_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_survey_identical_category_0_0_1_en.md
new file mode 100644
index 00000000000000..c3fbac83ceb66f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_survey_identical_category_0_0_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_survey_identical_category_0_0_1 DistilBertForSequenceClassification from ansilmbabl
+author: John Snow Labs
+name: distilbert_base_uncased_survey_identical_category_0_0_1
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_survey_identical_category_0_0_1` is a English model originally trained by ansilmbabl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_survey_identical_category_0_0_1_en_5.5.1_3.0_1737873491174.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_survey_identical_category_0_0_1_en_5.5.1_3.0_1737873491174.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_survey_identical_category_0_0_1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_survey_identical_category_0_0_1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_survey_identical_category_0_0_1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/ansilmbabl/distilbert-base-uncased-survey-identical-category-0.0.1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_survey_identical_category_0_0_1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_survey_identical_category_0_0_1_pipeline_en.md
new file mode 100644
index 00000000000000..678b874d7d4ad3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_base_uncased_survey_identical_category_0_0_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_survey_identical_category_0_0_1_pipeline pipeline DistilBertForSequenceClassification from ansilmbabl
+author: John Snow Labs
+name: distilbert_base_uncased_survey_identical_category_0_0_1_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_survey_identical_category_0_0_1_pipeline` is a English model originally trained by ansilmbabl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_survey_identical_category_0_0_1_pipeline_en_5.5.1_3.0_1737873504502.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_survey_identical_category_0_0_1_pipeline_en_5.5.1_3.0_1737873504502.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_survey_identical_category_0_0_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_survey_identical_category_0_0_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_survey_identical_category_0_0_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/ansilmbabl/distilbert-base-uncased-survey-identical-category-0.0.1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_emotion_model_v4_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_emotion_model_v4_en.md
new file mode 100644
index 00000000000000..2109250f1f90d8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_emotion_model_v4_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_emotion_model_v4 DistilBertForSequenceClassification from SagarVidya
+author: John Snow Labs
+name: distilbert_emotion_model_v4
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_emotion_model_v4` is a English model originally trained by SagarVidya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_emotion_model_v4_en_5.5.1_3.0_1737873766682.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_emotion_model_v4_en_5.5.1_3.0_1737873766682.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_emotion_model_v4","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_emotion_model_v4", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_emotion_model_v4|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/SagarVidya/distilbert-emotion-model_v4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_emotion_model_v4_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_emotion_model_v4_pipeline_en.md
new file mode 100644
index 00000000000000..46082af287733a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_emotion_model_v4_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_emotion_model_v4_pipeline pipeline DistilBertForSequenceClassification from SagarVidya
+author: John Snow Labs
+name: distilbert_emotion_model_v4_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_emotion_model_v4_pipeline` is a English model originally trained by SagarVidya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_emotion_model_v4_pipeline_en_5.5.1_3.0_1737873779961.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_emotion_model_v4_pipeline_en_5.5.1_3.0_1737873779961.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_emotion_model_v4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_emotion_model_v4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_emotion_model_v4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/SagarVidya/distilbert-emotion-model_v4
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_mini_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_mini_en.md
new file mode 100644
index 00000000000000..cff45436f95232
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_mini_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_mini DistilBertForSequenceClassification from Drigoro
+author: John Snow Labs
+name: distilbert_mini
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_mini` is a English model originally trained by Drigoro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_mini_en_5.5.1_3.0_1737872998772.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_mini_en_5.5.1_3.0_1737872998772.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_mini","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_mini", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_mini|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Drigoro/distilbert_mini
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_mini_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_mini_pipeline_en.md
new file mode 100644
index 00000000000000..302e316de06a20
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_mini_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_mini_pipeline pipeline DistilBertForSequenceClassification from Drigoro
+author: John Snow Labs
+name: distilbert_mini_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_mini_pipeline` is a English model originally trained by Drigoro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_mini_pipeline_en_5.5.1_3.0_1737873018563.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_mini_pipeline_en_5.5.1_3.0_1737873018563.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_mini_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_mini_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_mini_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Drigoro/distilbert_mini
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_sentiment_encrypted_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_sentiment_encrypted_en.md
new file mode 100644
index 00000000000000..dd9668801e8d4e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_sentiment_encrypted_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_sentiment_encrypted DistilBertForSequenceClassification from nesaorg
+author: John Snow Labs
+name: distilbert_sentiment_encrypted
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_sentiment_encrypted` is a English model originally trained by nesaorg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_sentiment_encrypted_en_5.5.1_3.0_1737873324242.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_sentiment_encrypted_en_5.5.1_3.0_1737873324242.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_sentiment_encrypted","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_sentiment_encrypted", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_sentiment_encrypted|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/nesaorg/distilbert-sentiment-encrypted
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_sentiment_encrypted_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_sentiment_encrypted_pipeline_en.md
new file mode 100644
index 00000000000000..76c4451415f953
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_sentiment_encrypted_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_sentiment_encrypted_pipeline pipeline DistilBertForSequenceClassification from nesaorg
+author: John Snow Labs
+name: distilbert_sentiment_encrypted_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_sentiment_encrypted_pipeline` is a English model originally trained by nesaorg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_sentiment_encrypted_pipeline_en_5.5.1_3.0_1737873344970.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_sentiment_encrypted_pipeline_en_5.5.1_3.0_1737873344970.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_sentiment_encrypted_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_sentiment_encrypted_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_sentiment_encrypted_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/nesaorg/distilbert-sentiment-encrypted
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_sst2_yelp_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_sst2_yelp_en.md
new file mode 100644
index 00000000000000..9b1119f7d0ac49
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_sst2_yelp_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_sst2_yelp DistilBertForSequenceClassification from AirrStorm
+author: John Snow Labs
+name: distilbert_sst2_yelp
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_sst2_yelp` is a English model originally trained by AirrStorm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_sst2_yelp_en_5.5.1_3.0_1737873906701.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_sst2_yelp_en_5.5.1_3.0_1737873906701.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_sst2_yelp","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_sst2_yelp", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_sst2_yelp|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/AirrStorm/DistilBERT-SST2-Yelp
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilbert_sst2_yelp_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilbert_sst2_yelp_pipeline_en.md
new file mode 100644
index 00000000000000..8fae1c7e64f81e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilbert_sst2_yelp_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_sst2_yelp_pipeline pipeline DistilBertForSequenceClassification from AirrStorm
+author: John Snow Labs
+name: distilbert_sst2_yelp_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_sst2_yelp_pipeline` is a English model originally trained by AirrStorm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_sst2_yelp_pipeline_en_5.5.1_3.0_1737873921039.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_sst2_yelp_pipeline_en_5.5.1_3.0_1737873921039.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_sst2_yelp_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_sst2_yelp_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_sst2_yelp_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/AirrStorm/DistilBERT-SST2-Yelp
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilgpt2_rap_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilgpt2_rap_en.md
new file mode 100644
index 00000000000000..2badc081d09d88
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilgpt2_rap_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilgpt2_rap GPT2Transformer from dzionek
+author: John Snow Labs
+name: distilgpt2_rap
+date: 2025-01-26
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilgpt2_rap` is a English model originally trained by dzionek.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilgpt2_rap_en_5.5.1_3.0_1737874600489.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilgpt2_rap_en_5.5.1_3.0_1737874600489.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("distilgpt2_rap","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("distilgpt2_rap","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilgpt2_rap|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|308.5 MB|
+
+## References
+
+https://huggingface.co/dzionek/distilgpt2-rap
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilgpt2_rap_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilgpt2_rap_pipeline_en.md
new file mode 100644
index 00000000000000..ac8bc94f137690
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilgpt2_rap_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilgpt2_rap_pipeline pipeline GPT2Transformer from dzionek
+author: John Snow Labs
+name: distilgpt2_rap_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilgpt2_rap_pipeline` is a English model originally trained by dzionek.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilgpt2_rap_pipeline_en_5.5.1_3.0_1737874617871.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilgpt2_rap_pipeline_en_5.5.1_3.0_1737874617871.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilgpt2_rap_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilgpt2_rap_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilgpt2_rap_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|308.5 MB|
+
+## References
+
+https://huggingface.co/dzionek/distilgpt2-rap
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilroberta_base_finetuned_financial_news_superior_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilroberta_base_finetuned_financial_news_superior_en.md
new file mode 100644
index 00000000000000..8b26fe7c8b3ed8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilroberta_base_finetuned_financial_news_superior_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilroberta_base_finetuned_financial_news_superior RoBertaEmbeddings from cm309
+author: John Snow Labs
+name: distilroberta_base_finetuned_financial_news_superior
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_finetuned_financial_news_superior` is a English model originally trained by cm309.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_base_finetuned_financial_news_superior_en_5.5.1_3.0_1737866427617.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_finetuned_financial_news_superior_en_5.5.1_3.0_1737866427617.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("distilroberta_base_finetuned_financial_news_superior","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("distilroberta_base_finetuned_financial_news_superior","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_base_finetuned_financial_news_superior|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/cm309/distilroberta-base-finetuned-Financial-News-Superior
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilroberta_base_finetuned_financial_news_superior_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilroberta_base_finetuned_financial_news_superior_pipeline_en.md
new file mode 100644
index 00000000000000..839ce1873ea6ed
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilroberta_base_finetuned_financial_news_superior_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilroberta_base_finetuned_financial_news_superior_pipeline pipeline RoBertaEmbeddings from cm309
+author: John Snow Labs
+name: distilroberta_base_finetuned_financial_news_superior_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_finetuned_financial_news_superior_pipeline` is a English model originally trained by cm309.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_base_finetuned_financial_news_superior_pipeline_en_5.5.1_3.0_1737866447219.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_finetuned_financial_news_superior_pipeline_en_5.5.1_3.0_1737866447219.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilroberta_base_finetuned_financial_news_superior_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilroberta_base_finetuned_financial_news_superior_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_base_finetuned_financial_news_superior_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/cm309/distilroberta-base-finetuned-Financial-News-Superior
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilroberta_base_ft_worldnews_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilroberta_base_ft_worldnews_en.md
new file mode 100644
index 00000000000000..87de19bf009e50
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilroberta_base_ft_worldnews_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilroberta_base_ft_worldnews RoBertaEmbeddings from jkruk
+author: John Snow Labs
+name: distilroberta_base_ft_worldnews
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_ft_worldnews` is a English model originally trained by jkruk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_base_ft_worldnews_en_5.5.1_3.0_1737865340966.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_ft_worldnews_en_5.5.1_3.0_1737865340966.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("distilroberta_base_ft_worldnews","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("distilroberta_base_ft_worldnews","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_base_ft_worldnews|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/jkruk/distilroberta-base-ft-worldnews
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distilroberta_base_ft_worldnews_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-distilroberta_base_ft_worldnews_pipeline_en.md
new file mode 100644
index 00000000000000..783f38e6af053b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distilroberta_base_ft_worldnews_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilroberta_base_ft_worldnews_pipeline pipeline RoBertaEmbeddings from jkruk
+author: John Snow Labs
+name: distilroberta_base_ft_worldnews_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_ft_worldnews_pipeline` is a English model originally trained by jkruk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_base_ft_worldnews_pipeline_en_5.5.1_3.0_1737865362784.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_ft_worldnews_pipeline_en_5.5.1_3.0_1737865362784.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilroberta_base_ft_worldnews_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilroberta_base_ft_worldnews_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_base_ft_worldnews_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/jkruk/distilroberta-base-ft-worldnews
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distlbert_amh_telegram_en.md b/docs/_posts/ahmedlone127/2025-01-26-distlbert_amh_telegram_en.md
new file mode 100644
index 00000000000000..f1e4a6ccbb08e1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distlbert_amh_telegram_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distlbert_amh_telegram DistilBertForTokenClassification from Naod-Demissie
+author: John Snow Labs
+name: distlbert_amh_telegram
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distlbert_amh_telegram` is a English model originally trained by Naod-Demissie.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distlbert_amh_telegram_en_5.5.1_3.0_1737909784481.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distlbert_amh_telegram_en_5.5.1_3.0_1737909784481.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distlbert_amh_telegram","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distlbert_amh_telegram", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distlbert_amh_telegram|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|243.9 MB|
+
+## References
+
+https://huggingface.co/Naod-Demissie/distlbert-amh-telegram
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distlbert_amh_telegram_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-distlbert_amh_telegram_pipeline_en.md
new file mode 100644
index 00000000000000..946610bfc34d50
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distlbert_amh_telegram_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distlbert_amh_telegram_pipeline pipeline DistilBertForTokenClassification from Naod-Demissie
+author: John Snow Labs
+name: distlbert_amh_telegram_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distlbert_amh_telegram_pipeline` is a English model originally trained by Naod-Demissie.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distlbert_amh_telegram_pipeline_en_5.5.1_3.0_1737909798873.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distlbert_amh_telegram_pipeline_en_5.5.1_3.0_1737909798873.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distlbert_amh_telegram_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distlbert_amh_telegram_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distlbert_amh_telegram_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|243.9 MB|
+
+## References
+
+https://huggingface.co/Naod-Demissie/distlbert-amh-telegram
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distlbert_amh_telegram_trained_merged_en.md b/docs/_posts/ahmedlone127/2025-01-26-distlbert_amh_telegram_trained_merged_en.md
new file mode 100644
index 00000000000000..1a63265c7f655e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distlbert_amh_telegram_trained_merged_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distlbert_amh_telegram_trained_merged DistilBertForTokenClassification from Naod-Demissie
+author: John Snow Labs
+name: distlbert_amh_telegram_trained_merged
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distlbert_amh_telegram_trained_merged` is a English model originally trained by Naod-Demissie.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distlbert_amh_telegram_trained_merged_en_5.5.1_3.0_1737909660409.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distlbert_amh_telegram_trained_merged_en_5.5.1_3.0_1737909660409.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distlbert_amh_telegram_trained_merged","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distlbert_amh_telegram_trained_merged", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distlbert_amh_telegram_trained_merged|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|243.9 MB|
+
+## References
+
+https://huggingface.co/Naod-Demissie/distlbert-amh-telegram-trained-merged
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-distlbert_amh_telegram_trained_merged_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-distlbert_amh_telegram_trained_merged_pipeline_en.md
new file mode 100644
index 00000000000000..b218d4b70192e2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-distlbert_amh_telegram_trained_merged_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distlbert_amh_telegram_trained_merged_pipeline pipeline DistilBertForTokenClassification from Naod-Demissie
+author: John Snow Labs
+name: distlbert_amh_telegram_trained_merged_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distlbert_amh_telegram_trained_merged_pipeline` is a English model originally trained by Naod-Demissie.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distlbert_amh_telegram_trained_merged_pipeline_en_5.5.1_3.0_1737909675298.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distlbert_amh_telegram_trained_merged_pipeline_en_5.5.1_3.0_1737909675298.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distlbert_amh_telegram_trained_merged_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distlbert_amh_telegram_trained_merged_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distlbert_amh_telegram_trained_merged_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|243.9 MB|
+
+## References
+
+https://huggingface.co/Naod-Demissie/distlbert-amh-telegram-trained-merged
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-dlite_v1_124m_en.md b/docs/_posts/ahmedlone127/2025-01-26-dlite_v1_124m_en.md
new file mode 100644
index 00000000000000..24a8310abd94fe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-dlite_v1_124m_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English dlite_v1_124m GPT2Transformer from aisquared
+author: John Snow Labs
+name: dlite_v1_124m
+date: 2025-01-26
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dlite_v1_124m` is a English model originally trained by aisquared.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dlite_v1_124m_en_5.5.1_3.0_1737912246431.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dlite_v1_124m_en_5.5.1_3.0_1737912246431.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("dlite_v1_124m","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("dlite_v1_124m","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dlite_v1_124m|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/aisquared/dlite-v1-124m
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-dlite_v1_124m_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-dlite_v1_124m_pipeline_en.md
new file mode 100644
index 00000000000000..d04a5aab6d1643
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-dlite_v1_124m_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English dlite_v1_124m_pipeline pipeline GPT2Transformer from aisquared
+author: John Snow Labs
+name: dlite_v1_124m_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dlite_v1_124m_pipeline` is a English model originally trained by aisquared.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dlite_v1_124m_pipeline_en_5.5.1_3.0_1737912269868.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dlite_v1_124m_pipeline_en_5.5.1_3.0_1737912269868.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dlite_v1_124m_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dlite_v1_124m_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dlite_v1_124m_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.9 MB|
+
+## References
+
+https://huggingface.co/aisquared/dlite-v1-124m
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-dog_breeds_multiclass_image_classification_with_vit_en.md b/docs/_posts/ahmedlone127/2025-01-26-dog_breeds_multiclass_image_classification_with_vit_en.md
new file mode 100644
index 00000000000000..e22928709f62db
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-dog_breeds_multiclass_image_classification_with_vit_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dog_breeds_multiclass_image_classification_with_vit ViTForImageClassification from wesleyacheng
+author: John Snow Labs
+name: dog_breeds_multiclass_image_classification_with_vit
+date: 2025-01-26
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dog_breeds_multiclass_image_classification_with_vit` is a English model originally trained by wesleyacheng.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dog_breeds_multiclass_image_classification_with_vit_en_5.5.1_3.0_1737926556623.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dog_breeds_multiclass_image_classification_with_vit_en_5.5.1_3.0_1737926556623.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""dog_breeds_multiclass_image_classification_with_vit","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("dog_breeds_multiclass_image_classification_with_vit","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dog_breeds_multiclass_image_classification_with_vit|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.7 MB|
+
+## References
+
+https://huggingface.co/wesleyacheng/dog-breeds-multiclass-image-classification-with-vit
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-dog_breeds_multiclass_image_classification_with_vit_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-dog_breeds_multiclass_image_classification_with_vit_pipeline_en.md
new file mode 100644
index 00000000000000..a751af9d20e3be
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-dog_breeds_multiclass_image_classification_with_vit_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English dog_breeds_multiclass_image_classification_with_vit_pipeline pipeline ViTForImageClassification from wesleyacheng
+author: John Snow Labs
+name: dog_breeds_multiclass_image_classification_with_vit_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dog_breeds_multiclass_image_classification_with_vit_pipeline` is a English model originally trained by wesleyacheng.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dog_breeds_multiclass_image_classification_with_vit_pipeline_en_5.5.1_3.0_1737926573401.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dog_breeds_multiclass_image_classification_with_vit_pipeline_en_5.5.1_3.0_1737926573401.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dog_breeds_multiclass_image_classification_with_vit_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dog_breeds_multiclass_image_classification_with_vit_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dog_breeds_multiclass_image_classification_with_vit_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.7 MB|
+
+## References
+
+https://huggingface.co/wesleyacheng/dog-breeds-multiclass-image-classification-with-vit
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-dummy_model2_en.md b/docs/_posts/ahmedlone127/2025-01-26-dummy_model2_en.md
new file mode 100644
index 00000000000000..e1092f87f5e963
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-dummy_model2_en.md
@@ -0,0 +1,92 @@
+---
+layout: model
+title: English dummy_model2 BertEmbeddings from vsrinivas
+author: John Snow Labs
+name: dummy_model2
+date: 2025-01-26
+tags: [bert, en, open_source, fill_mask, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings  model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model2` is a English model originally trained by vsrinivas.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model2_en_5.5.1_3.0_1737890787032.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model2_en_5.5.1_3.0_1737890787032.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("documents")
+    
+    
+embeddings =BertEmbeddings.pretrained("dummy_model2","en") \
+            .setInputCols(["documents","token"]) \
+            .setOutputCol("embeddings")
+
+pipeline = Pipeline().setStages([document_assembler, embeddings])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val document_assembler = new DocumentAssembler()
+    .setInputCol("text") 
+    .setOutputCol("embeddings")
+    
+val embeddings = BertEmbeddings 
+    .pretrained("dummy_model2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("embeddings") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+References
+
+https://huggingface.co/vsrinivas/dummy_model2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-dummy_model2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-dummy_model2_pipeline_en.md
new file mode 100644
index 00000000000000..ae7481546c2743
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-dummy_model2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model2_pipeline pipeline BertEmbeddings from MindNetML
+author: John Snow Labs
+name: dummy_model2_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model2_pipeline` is a English model originally trained by MindNetML.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model2_pipeline_en_5.5.1_3.0_1737890807292.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model2_pipeline_en_5.5.1_3.0_1737890807292.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/MindNetML/dummy-model2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-dummy_model3_en.md b/docs/_posts/ahmedlone127/2025-01-26-dummy_model3_en.md
new file mode 100644
index 00000000000000..4913d99c2198ea
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-dummy_model3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model3 CamemBertEmbeddings from karigri
+author: John Snow Labs
+name: dummy_model3
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model3` is a English model originally trained by karigri.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model3_en_5.5.1_3.0_1737858175193.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model3_en_5.5.1_3.0_1737858175193.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model3","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model3","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model3|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/karigri/dummy-model3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-dummy_model3_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-dummy_model3_pipeline_en.md
new file mode 100644
index 00000000000000..b2fad7c83d9716
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-dummy_model3_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model3_pipeline pipeline CamemBertEmbeddings from karigri
+author: John Snow Labs
+name: dummy_model3_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model3_pipeline` is a English model originally trained by karigri.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model3_pipeline_en_5.5.1_3.0_1737858253547.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model3_pipeline_en_5.5.1_3.0_1737858253547.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/karigri/dummy-model3
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-dummy_model_1_en.md b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_1_en.md
new file mode 100644
index 00000000000000..ce28aa5fffd005
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_1 CamemBertEmbeddings from cotysong113
+author: John Snow Labs
+name: dummy_model_1
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_1` is a English model originally trained by cotysong113.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_1_en_5.5.1_3.0_1737858308699.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_1_en_5.5.1_3.0_1737858308699.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_1","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_1","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/cotysong113/dummy-model-1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-dummy_model_1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_1_pipeline_en.md
new file mode 100644
index 00000000000000..d0a321d8969cf6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_1_pipeline pipeline CamemBertEmbeddings from cotysong113
+author: John Snow Labs
+name: dummy_model_1_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_1_pipeline` is a English model originally trained by cotysong113.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_1_pipeline_en_5.5.1_3.0_1737858388044.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_1_pipeline_en_5.5.1_3.0_1737858388044.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/cotysong113/dummy-model-1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-dummy_model_dimkkozhemyako_en.md b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_dimkkozhemyako_en.md
new file mode 100644
index 00000000000000..d7c5487015df08
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_dimkkozhemyako_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_dimkkozhemyako BertEmbeddings from DimkKozhemyako
+author: John Snow Labs
+name: dummy_model_dimkkozhemyako
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_dimkkozhemyako` is a English model originally trained by DimkKozhemyako.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_dimkkozhemyako_en_5.5.1_3.0_1737890845945.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_dimkkozhemyako_en_5.5.1_3.0_1737890845945.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("dummy_model_dimkkozhemyako","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("dummy_model_dimkkozhemyako","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_dimkkozhemyako|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|108.6 MB|
+
+## References
+
+https://huggingface.co/DimkKozhemyako/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-dummy_model_dimkkozhemyako_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_dimkkozhemyako_pipeline_en.md
new file mode 100644
index 00000000000000..081fa7a0fb1259
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_dimkkozhemyako_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_dimkkozhemyako_pipeline pipeline BertEmbeddings from DimkKozhemyako
+author: John Snow Labs
+name: dummy_model_dimkkozhemyako_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_dimkkozhemyako_pipeline` is a English model originally trained by DimkKozhemyako.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_dimkkozhemyako_pipeline_en_5.5.1_3.0_1737890858092.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_dimkkozhemyako_pipeline_en_5.5.1_3.0_1737890858092.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_dimkkozhemyako_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_dimkkozhemyako_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_dimkkozhemyako_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|108.6 MB|
+
+## References
+
+https://huggingface.co/DimkKozhemyako/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-dummy_model_dokakhero_en.md b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_dokakhero_en.md
new file mode 100644
index 00000000000000..822f084082a371
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_dokakhero_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_dokakhero CamemBertEmbeddings from dokakhero
+author: John Snow Labs
+name: dummy_model_dokakhero
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_dokakhero` is a English model originally trained by dokakhero.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_dokakhero_en_5.5.1_3.0_1737858415597.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_dokakhero_en_5.5.1_3.0_1737858415597.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_dokakhero","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_dokakhero","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_dokakhero|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/dokakhero/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-dummy_model_dokakhero_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_dokakhero_pipeline_en.md
new file mode 100644
index 00000000000000..0e8c002088e432
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_dokakhero_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_dokakhero_pipeline pipeline CamemBertEmbeddings from dokakhero
+author: John Snow Labs
+name: dummy_model_dokakhero_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_dokakhero_pipeline` is a English model originally trained by dokakhero.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_dokakhero_pipeline_en_5.5.1_3.0_1737858492406.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_dokakhero_pipeline_en_5.5.1_3.0_1737858492406.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_dokakhero_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_dokakhero_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_dokakhero_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/dokakhero/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-dummy_model_karigri_en.md b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_karigri_en.md
new file mode 100644
index 00000000000000..9b1a40dc0eb3a2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_karigri_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_karigri CamemBertEmbeddings from karigri
+author: John Snow Labs
+name: dummy_model_karigri
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_karigri` is a English model originally trained by karigri.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_karigri_en_5.5.1_3.0_1737858584020.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_karigri_en_5.5.1_3.0_1737858584020.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_karigri","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_karigri","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_karigri|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/karigri/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-dummy_model_karigri_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_karigri_pipeline_en.md
new file mode 100644
index 00000000000000..59b6123354b43f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_karigri_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_karigri_pipeline pipeline CamemBertEmbeddings from karigri
+author: John Snow Labs
+name: dummy_model_karigri_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_karigri_pipeline` is a English model originally trained by karigri.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_karigri_pipeline_en_5.5.1_3.0_1737858660357.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_karigri_pipeline_en_5.5.1_3.0_1737858660357.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_karigri_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_karigri_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_karigri_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/karigri/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-dummy_model_linmatrix_en.md b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_linmatrix_en.md
new file mode 100644
index 00000000000000..98e1d320551713
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_linmatrix_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_linmatrix CamemBertEmbeddings from linmatrix
+author: John Snow Labs
+name: dummy_model_linmatrix
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_linmatrix` is a English model originally trained by linmatrix.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_linmatrix_en_5.5.1_3.0_1737858079299.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_linmatrix_en_5.5.1_3.0_1737858079299.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_linmatrix","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_linmatrix","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_linmatrix|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/linmatrix/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-dummy_model_linmatrix_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_linmatrix_pipeline_en.md
new file mode 100644
index 00000000000000..7c9c189d4b130e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_linmatrix_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_linmatrix_pipeline pipeline CamemBertEmbeddings from linmatrix
+author: John Snow Labs
+name: dummy_model_linmatrix_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_linmatrix_pipeline` is a English model originally trained by linmatrix.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_linmatrix_pipeline_en_5.5.1_3.0_1737858157811.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_linmatrix_pipeline_en_5.5.1_3.0_1737858157811.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_linmatrix_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_linmatrix_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_linmatrix_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/linmatrix/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-dummy_model_lyonliuyang_en.md b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_lyonliuyang_en.md
new file mode 100644
index 00000000000000..92f8217f8fbc55
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_lyonliuyang_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_lyonliuyang BertEmbeddings from lyonliuyang
+author: John Snow Labs
+name: dummy_model_lyonliuyang
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_lyonliuyang` is a English model originally trained by lyonliuyang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_lyonliuyang_en_5.5.1_3.0_1737908452193.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_lyonliuyang_en_5.5.1_3.0_1737908452193.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("dummy_model_lyonliuyang","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("dummy_model_lyonliuyang","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_lyonliuyang|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/lyonliuyang/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-dummy_model_lyonliuyang_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_lyonliuyang_pipeline_en.md
new file mode 100644
index 00000000000000..9fa94509a32f8f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_lyonliuyang_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_lyonliuyang_pipeline pipeline BertEmbeddings from lyonliuyang
+author: John Snow Labs
+name: dummy_model_lyonliuyang_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_lyonliuyang_pipeline` is a English model originally trained by lyonliuyang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_lyonliuyang_pipeline_en_5.5.1_3.0_1737908473224.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_lyonliuyang_pipeline_en_5.5.1_3.0_1737908473224.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_lyonliuyang_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_lyonliuyang_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_lyonliuyang_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/lyonliuyang/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-dummy_model_pipidepulus_en.md b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_pipidepulus_en.md
new file mode 100644
index 00000000000000..f37e18797b9dc7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_pipidepulus_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_pipidepulus CamemBertEmbeddings from pipidepulus
+author: John Snow Labs
+name: dummy_model_pipidepulus
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_pipidepulus` is a English model originally trained by pipidepulus.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_pipidepulus_en_5.5.1_3.0_1737857974529.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_pipidepulus_en_5.5.1_3.0_1737857974529.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_pipidepulus","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_pipidepulus","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_pipidepulus|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/pipidepulus/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-dummy_model_pipidepulus_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_pipidepulus_pipeline_en.md
new file mode 100644
index 00000000000000..db1c71b3d234e0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_pipidepulus_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_pipidepulus_pipeline pipeline CamemBertEmbeddings from pipidepulus
+author: John Snow Labs
+name: dummy_model_pipidepulus_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_pipidepulus_pipeline` is a English model originally trained by pipidepulus.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_pipidepulus_pipeline_en_5.5.1_3.0_1737858052943.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_pipidepulus_pipeline_en_5.5.1_3.0_1737858052943.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_pipidepulus_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_pipidepulus_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_pipidepulus_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/pipidepulus/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-dummy_model_ronaldo_en.md b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_ronaldo_en.md
new file mode 100644
index 00000000000000..ef539fd2fc7c86
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_ronaldo_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_ronaldo CamemBertEmbeddings from Ronaldo
+author: John Snow Labs
+name: dummy_model_ronaldo
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_ronaldo` is a English model originally trained by Ronaldo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_ronaldo_en_5.5.1_3.0_1737858468435.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_ronaldo_en_5.5.1_3.0_1737858468435.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_ronaldo","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_ronaldo","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_ronaldo|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/Ronaldo/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-dummy_model_ronaldo_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_ronaldo_pipeline_en.md
new file mode 100644
index 00000000000000..6e3cd49f11f12b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_ronaldo_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_ronaldo_pipeline pipeline CamemBertEmbeddings from Ronaldo
+author: John Snow Labs
+name: dummy_model_ronaldo_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_ronaldo_pipeline` is a English model originally trained by Ronaldo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_ronaldo_pipeline_en_5.5.1_3.0_1737858545592.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_ronaldo_pipeline_en_5.5.1_3.0_1737858545592.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_ronaldo_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_ronaldo_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_ronaldo_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/Ronaldo/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-dummy_model_u00890358_en.md b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_u00890358_en.md
new file mode 100644
index 00000000000000..fee54e339e2598
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_u00890358_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_u00890358 BertEmbeddings from u00890358
+author: John Snow Labs
+name: dummy_model_u00890358
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_u00890358` is a English model originally trained by u00890358.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_u00890358_en_5.5.1_3.0_1737861354290.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_u00890358_en_5.5.1_3.0_1737861354290.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("dummy_model_u00890358","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("dummy_model_u00890358","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_u00890358|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/u00890358/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-dummy_model_u00890358_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_u00890358_pipeline_en.md
new file mode 100644
index 00000000000000..cb55496a79814e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_u00890358_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_u00890358_pipeline pipeline BertEmbeddings from u00890358
+author: John Snow Labs
+name: dummy_model_u00890358_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_u00890358_pipeline` is a English model originally trained by u00890358.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_u00890358_pipeline_en_5.5.1_3.0_1737861376194.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_u00890358_pipeline_en_5.5.1_3.0_1737861376194.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_u00890358_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_u00890358_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_u00890358_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/u00890358/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-dummy_model_viper237_en.md b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_viper237_en.md
new file mode 100644
index 00000000000000..695e031e56e358
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_viper237_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_viper237 CamemBertEmbeddings from viper237
+author: John Snow Labs
+name: dummy_model_viper237
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_viper237` is a English model originally trained by viper237.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_viper237_en_5.5.1_3.0_1737858090380.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_viper237_en_5.5.1_3.0_1737858090380.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_viper237","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_viper237","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_viper237|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/viper237/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-dummy_model_viper237_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_viper237_pipeline_en.md
new file mode 100644
index 00000000000000..6f1fc1dc31a604
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_viper237_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_viper237_pipeline pipeline CamemBertEmbeddings from viper237
+author: John Snow Labs
+name: dummy_model_viper237_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_viper237_pipeline` is a English model originally trained by viper237.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_viper237_pipeline_en_5.5.1_3.0_1737858169375.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_viper237_pipeline_en_5.5.1_3.0_1737858169375.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_viper237_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_viper237_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_viper237_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/viper237/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-dummy_model_wangzech_en.md b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_wangzech_en.md
new file mode 100644
index 00000000000000..dc54ec6877ce4d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_wangzech_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_wangzech CamemBertEmbeddings from wangzech
+author: John Snow Labs
+name: dummy_model_wangzech
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_wangzech` is a English model originally trained by wangzech.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_wangzech_en_5.5.1_3.0_1737858317554.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_wangzech_en_5.5.1_3.0_1737858317554.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_wangzech","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_wangzech","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_wangzech|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/wangzech/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-dummy_model_wangzech_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_wangzech_pipeline_en.md
new file mode 100644
index 00000000000000..c3d8047234d0d2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_wangzech_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_wangzech_pipeline pipeline CamemBertEmbeddings from wangzech
+author: John Snow Labs
+name: dummy_model_wangzech_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_wangzech_pipeline` is a English model originally trained by wangzech.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_wangzech_pipeline_en_5.5.1_3.0_1737858395954.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_wangzech_pipeline_en_5.5.1_3.0_1737858395954.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_wangzech_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_wangzech_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_wangzech_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/wangzech/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-dummy_model_wedalu_en.md b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_wedalu_en.md
new file mode 100644
index 00000000000000..e9ded513f0885a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_wedalu_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_wedalu CamemBertEmbeddings from wedalu
+author: John Snow Labs
+name: dummy_model_wedalu
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_wedalu` is a English model originally trained by wedalu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_wedalu_en_5.5.1_3.0_1737858172404.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_wedalu_en_5.5.1_3.0_1737858172404.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_wedalu","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_wedalu","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_wedalu|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/wedalu/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-dummy_model_wedalu_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_wedalu_pipeline_en.md
new file mode 100644
index 00000000000000..5b86c473b2156a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_wedalu_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_wedalu_pipeline pipeline CamemBertEmbeddings from wedalu
+author: John Snow Labs
+name: dummy_model_wedalu_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_wedalu_pipeline` is a English model originally trained by wedalu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_wedalu_pipeline_en_5.5.1_3.0_1737858250916.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_wedalu_pipeline_en_5.5.1_3.0_1737858250916.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_wedalu_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_wedalu_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_wedalu_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/wedalu/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-dummy_model_xbb123456_en.md b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_xbb123456_en.md
new file mode 100644
index 00000000000000..2f74910d81beb2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_xbb123456_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_xbb123456 BertEmbeddings from xbb123456
+author: John Snow Labs
+name: dummy_model_xbb123456
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_xbb123456` is a English model originally trained by xbb123456.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_xbb123456_en_5.5.1_3.0_1737861241107.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_xbb123456_en_5.5.1_3.0_1737861241107.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("dummy_model_xbb123456","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("dummy_model_xbb123456","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_xbb123456|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/xbb123456/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-dummy_model_xbb123456_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_xbb123456_pipeline_en.md
new file mode 100644
index 00000000000000..591043bbc5b515
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-dummy_model_xbb123456_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_xbb123456_pipeline pipeline BertEmbeddings from xbb123456
+author: John Snow Labs
+name: dummy_model_xbb123456_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_xbb123456_pipeline` is a English model originally trained by xbb123456.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_xbb123456_pipeline_en_5.5.1_3.0_1737861262696.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_xbb123456_pipeline_en_5.5.1_3.0_1737861262696.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_xbb123456_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_xbb123456_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_xbb123456_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/xbb123456/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-e5_base_wb_p2_4ep_en.md b/docs/_posts/ahmedlone127/2025-01-26-e5_base_wb_p2_4ep_en.md
new file mode 100644
index 00000000000000..e7bcc92e267c4d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-e5_base_wb_p2_4ep_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English e5_base_wb_p2_4ep XlmRoBertaForSequenceClassification from Hvixze
+author: John Snow Labs
+name: e5_base_wb_p2_4ep
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_base_wb_p2_4ep` is a English model originally trained by Hvixze.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_base_wb_p2_4ep_en_5.5.1_3.0_1737885593443.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_base_wb_p2_4ep_en_5.5.1_3.0_1737885593443.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("e5_base_wb_p2_4ep","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("e5_base_wb_p2_4ep", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|e5_base_wb_p2_4ep|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|824.5 MB|
+
+## References
+
+https://huggingface.co/Hvixze/e5_base_wb_p2_4ep
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-e5_base_wb_p2_4ep_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-e5_base_wb_p2_4ep_pipeline_en.md
new file mode 100644
index 00000000000000..11fbe6a12f3f1f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-e5_base_wb_p2_4ep_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English e5_base_wb_p2_4ep_pipeline pipeline XlmRoBertaForSequenceClassification from Hvixze
+author: John Snow Labs
+name: e5_base_wb_p2_4ep_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_base_wb_p2_4ep_pipeline` is a English model originally trained by Hvixze.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_base_wb_p2_4ep_pipeline_en_5.5.1_3.0_1737885714042.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_base_wb_p2_4ep_pipeline_en_5.5.1_3.0_1737885714042.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("e5_base_wb_p2_4ep_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("e5_base_wb_p2_4ep_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|e5_base_wb_p2_4ep_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|824.5 MB|
+
+## References
+
+https://huggingface.co/Hvixze/e5_base_wb_p2_4ep
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-eminem_en.md b/docs/_posts/ahmedlone127/2025-01-26-eminem_en.md
new file mode 100644
index 00000000000000..29a403a74d373e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-eminem_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English eminem GPT2Transformer from huggingartists
+author: John Snow Labs
+name: eminem
+date: 2025-01-26
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`eminem` is a English model originally trained by huggingartists.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/eminem_en_5.5.1_3.0_1737914224386.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/eminem_en_5.5.1_3.0_1737914224386.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("eminem","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("eminem","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|eminem|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.9 MB|
+
+## References
+
+https://huggingface.co/huggingartists/eminem
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-eminem_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-eminem_pipeline_en.md
new file mode 100644
index 00000000000000..188b9129de3636
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-eminem_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English eminem_pipeline pipeline GPT2Transformer from huggingartists
+author: John Snow Labs
+name: eminem_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`eminem_pipeline` is a English model originally trained by huggingartists.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/eminem_pipeline_en_5.5.1_3.0_1737914247770.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/eminem_pipeline_en_5.5.1_3.0_1737914247770.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("eminem_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("eminem_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|eminem_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.9 MB|
+
+## References
+
+https://huggingface.co/huggingartists/eminem
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-emotion_ai_en.md b/docs/_posts/ahmedlone127/2025-01-26-emotion_ai_en.md
new file mode 100644
index 00000000000000..562213ec3e332b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-emotion_ai_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English emotion_ai DistilBertForSequenceClassification from Hemg
+author: John Snow Labs
+name: emotion_ai
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`emotion_ai` is a English model originally trained by Hemg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/emotion_ai_en_5.5.1_3.0_1737905191343.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/emotion_ai_en_5.5.1_3.0_1737905191343.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("emotion_ai","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("emotion_ai", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|emotion_ai|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Hemg/EMOTION-AI
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-emotion_ai_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-emotion_ai_pipeline_en.md
new file mode 100644
index 00000000000000..ebcf880521462a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-emotion_ai_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English emotion_ai_pipeline pipeline DistilBertForSequenceClassification from Hemg
+author: John Snow Labs
+name: emotion_ai_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`emotion_ai_pipeline` is a English model originally trained by Hemg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/emotion_ai_pipeline_en_5.5.1_3.0_1737905204264.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/emotion_ai_pipeline_en_5.5.1_3.0_1737905204264.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("emotion_ai_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("emotion_ai_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|emotion_ai_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.6 MB|
+
+## References
+
+https://huggingface.co/Hemg/EMOTION-AI
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-english_darija_en.md b/docs/_posts/ahmedlone127/2025-01-26-english_darija_en.md
new file mode 100644
index 00000000000000..8819895ec47f00
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-english_darija_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English english_darija MarianTransformer from LocaleNLP
+author: John Snow Labs
+name: english_darija
+date: 2025-01-26
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_darija` is a English model originally trained by LocaleNLP.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/english_darija_en_5.5.1_3.0_1737863115709.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_darija_en_5.5.1_3.0_1737863115709.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("english_darija","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("english_darija","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|english_darija|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|416.5 MB|
+
+## References
+
+https://huggingface.co/LocaleNLP/English_darija
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-english_darija_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-english_darija_pipeline_en.md
new file mode 100644
index 00000000000000..27508065ba1d8a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-english_darija_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English english_darija_pipeline pipeline MarianTransformer from LocaleNLP
+author: John Snow Labs
+name: english_darija_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_darija_pipeline` is a English model originally trained by LocaleNLP.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/english_darija_pipeline_en_5.5.1_3.0_1737863137463.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_darija_pipeline_en_5.5.1_3.0_1737863137463.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("english_darija_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("english_darija_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|english_darija_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|417.1 MB|
+
+## References
+
+https://huggingface.co/LocaleNLP/English_darija
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-english_model_en.md b/docs/_posts/ahmedlone127/2025-01-26-english_model_en.md
new file mode 100644
index 00000000000000..0bb21c953f3962
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-english_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English english_model BertEmbeddings from AfnanTS
+author: John Snow Labs
+name: english_model
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_model` is a English model originally trained by AfnanTS.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/english_model_en_5.5.1_3.0_1737908222177.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_model_en_5.5.1_3.0_1737908222177.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("english_model","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("english_model","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|english_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/AfnanTS/ENGLISH-MODEL
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-english_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-english_model_pipeline_en.md
new file mode 100644
index 00000000000000..aa97293156e6ef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-english_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English english_model_pipeline pipeline BertEmbeddings from AfnanTS
+author: John Snow Labs
+name: english_model_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_model_pipeline` is a English model originally trained by AfnanTS.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/english_model_pipeline_en_5.5.1_3.0_1737908284135.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_model_pipeline_en_5.5.1_3.0_1737908284135.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("english_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("english_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|english_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/AfnanTS/ENGLISH-MODEL
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-enpas_classify_en.md b/docs/_posts/ahmedlone127/2025-01-26-enpas_classify_en.md
new file mode 100644
index 00000000000000..31dc494895cc59
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-enpas_classify_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English enpas_classify XlmRoBertaForSequenceClassification from Enpas
+author: John Snow Labs
+name: enpas_classify
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`enpas_classify` is a English model originally trained by Enpas.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/enpas_classify_en_5.5.1_3.0_1737884877350.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/enpas_classify_en_5.5.1_3.0_1737884877350.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("enpas_classify","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("enpas_classify", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|enpas_classify|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|812.2 MB|
+
+## References
+
+https://huggingface.co/Enpas/Enpas-classify
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-enpas_classify_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-enpas_classify_pipeline_en.md
new file mode 100644
index 00000000000000..e27411f41c80d3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-enpas_classify_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English enpas_classify_pipeline pipeline XlmRoBertaForSequenceClassification from Enpas
+author: John Snow Labs
+name: enpas_classify_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`enpas_classify_pipeline` is a English model originally trained by Enpas.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/enpas_classify_pipeline_en_5.5.1_3.0_1737885005598.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/enpas_classify_pipeline_en_5.5.1_3.0_1737885005598.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("enpas_classify_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("enpas_classify_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|enpas_classify_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|812.2 MB|
+
+## References
+
+https://huggingface.co/Enpas/Enpas-classify
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-esperberto_rdaneelolivaw_en.md b/docs/_posts/ahmedlone127/2025-01-26-esperberto_rdaneelolivaw_en.md
new file mode 100644
index 00000000000000..9830ffd76a2815
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-esperberto_rdaneelolivaw_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English esperberto_rdaneelolivaw RoBertaEmbeddings from RDaneelOlivaw
+author: John Snow Labs
+name: esperberto_rdaneelolivaw
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`esperberto_rdaneelolivaw` is a English model originally trained by RDaneelOlivaw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/esperberto_rdaneelolivaw_en_5.5.1_3.0_1737906577534.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/esperberto_rdaneelolivaw_en_5.5.1_3.0_1737906577534.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("esperberto_rdaneelolivaw","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("esperberto_rdaneelolivaw","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|esperberto_rdaneelolivaw|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|311.4 MB|
+
+## References
+
+https://huggingface.co/RDaneelOlivaw/EsperBERTo
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-esperberto_rdaneelolivaw_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-esperberto_rdaneelolivaw_pipeline_en.md
new file mode 100644
index 00000000000000..645da79307654e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-esperberto_rdaneelolivaw_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English esperberto_rdaneelolivaw_pipeline pipeline RoBertaEmbeddings from RDaneelOlivaw
+author: John Snow Labs
+name: esperberto_rdaneelolivaw_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`esperberto_rdaneelolivaw_pipeline` is a English model originally trained by RDaneelOlivaw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/esperberto_rdaneelolivaw_pipeline_en_5.5.1_3.0_1737906594594.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/esperberto_rdaneelolivaw_pipeline_en_5.5.1_3.0_1737906594594.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("esperberto_rdaneelolivaw_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("esperberto_rdaneelolivaw_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|esperberto_rdaneelolivaw_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|311.5 MB|
+
+## References
+
+https://huggingface.co/RDaneelOlivaw/EsperBERTo
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-ethix4data2347context_en.md b/docs/_posts/ahmedlone127/2025-01-26-ethix4data2347context_en.md
new file mode 100644
index 00000000000000..de4ba1ba015ff8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-ethix4data2347context_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ethix4data2347context DistilBertForTokenClassification from Somisetty2347
+author: John Snow Labs
+name: ethix4data2347context
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ethix4data2347context` is a English model originally trained by Somisetty2347.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ethix4data2347context_en_5.5.1_3.0_1737909535036.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ethix4data2347context_en_5.5.1_3.0_1737909535036.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("ethix4data2347context","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("ethix4data2347context", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ethix4data2347context|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|244.0 MB|
+
+## References
+
+https://huggingface.co/Somisetty2347/Ethix4data2347context
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-ethix4data2347context_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-ethix4data2347context_pipeline_en.md
new file mode 100644
index 00000000000000..e28bd31d2d218f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-ethix4data2347context_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ethix4data2347context_pipeline pipeline DistilBertForTokenClassification from Somisetty2347
+author: John Snow Labs
+name: ethix4data2347context_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ethix4data2347context_pipeline` is a English model originally trained by Somisetty2347.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ethix4data2347context_pipeline_en_5.5.1_3.0_1737909552675.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ethix4data2347context_pipeline_en_5.5.1_3.0_1737909552675.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ethix4data2347context_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ethix4data2347context_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ethix4data2347context_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|244.0 MB|
+
+## References
+
+https://huggingface.co/Somisetty2347/Ethix4data2347context
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-ethix4datacontext_en.md b/docs/_posts/ahmedlone127/2025-01-26-ethix4datacontext_en.md
new file mode 100644
index 00000000000000..8a173bb0debcc6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-ethix4datacontext_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ethix4datacontext DistilBertForTokenClassification from Somisetty2347
+author: John Snow Labs
+name: ethix4datacontext
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ethix4datacontext` is a English model originally trained by Somisetty2347.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ethix4datacontext_en_5.5.1_3.0_1737909771332.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ethix4datacontext_en_5.5.1_3.0_1737909771332.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("ethix4datacontext","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("ethix4datacontext", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ethix4datacontext|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|244.0 MB|
+
+## References
+
+https://huggingface.co/Somisetty2347/Ethix4DATAcontext
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-ethix4datacontext_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-ethix4datacontext_pipeline_en.md
new file mode 100644
index 00000000000000..a7893f5dbe575d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-ethix4datacontext_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ethix4datacontext_pipeline pipeline DistilBertForTokenClassification from Somisetty2347
+author: John Snow Labs
+name: ethix4datacontext_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ethix4datacontext_pipeline` is a English model originally trained by Somisetty2347.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ethix4datacontext_pipeline_en_5.5.1_3.0_1737909784052.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ethix4datacontext_pipeline_en_5.5.1_3.0_1737909784052.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ethix4datacontext_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ethix4datacontext_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ethix4datacontext_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|244.0 MB|
+
+## References
+
+https://huggingface.co/Somisetty2347/Ethix4DATAcontext
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-facebook_commet_classification_small_en.md b/docs/_posts/ahmedlone127/2025-01-26-facebook_commet_classification_small_en.md
new file mode 100644
index 00000000000000..57c2d88b993e4b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-facebook_commet_classification_small_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English facebook_commet_classification_small XlmRoBertaForSequenceClassification from DuongTrongChi
+author: John Snow Labs
+name: facebook_commet_classification_small
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`facebook_commet_classification_small` is a English model originally trained by DuongTrongChi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/facebook_commet_classification_small_en_5.5.1_3.0_1737887004019.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/facebook_commet_classification_small_en_5.5.1_3.0_1737887004019.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("facebook_commet_classification_small","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("facebook_commet_classification_small", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|facebook_commet_classification_small|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|365.9 MB|
+
+## References
+
+https://huggingface.co/DuongTrongChi/facebook-commet-classification-small
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-facebook_commet_classification_small_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-facebook_commet_classification_small_pipeline_en.md
new file mode 100644
index 00000000000000..0643172e54c4c8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-facebook_commet_classification_small_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English facebook_commet_classification_small_pipeline pipeline XlmRoBertaForSequenceClassification from DuongTrongChi
+author: John Snow Labs
+name: facebook_commet_classification_small_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`facebook_commet_classification_small_pipeline` is a English model originally trained by DuongTrongChi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/facebook_commet_classification_small_pipeline_en_5.5.1_3.0_1737887024349.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/facebook_commet_classification_small_pipeline_en_5.5.1_3.0_1737887024349.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("facebook_commet_classification_small_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("facebook_commet_classification_small_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|facebook_commet_classification_small_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|365.9 MB|
+
+## References
+
+https://huggingface.co/DuongTrongChi/facebook-commet-classification-small
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-fernando_anotantion_bio_multiple_norwegian_group_clean_en.md b/docs/_posts/ahmedlone127/2025-01-26-fernando_anotantion_bio_multiple_norwegian_group_clean_en.md
new file mode 100644
index 00000000000000..d2dadbecee7e32
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-fernando_anotantion_bio_multiple_norwegian_group_clean_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English fernando_anotantion_bio_multiple_norwegian_group_clean BertForTokenClassification from GLeite
+author: John Snow Labs
+name: fernando_anotantion_bio_multiple_norwegian_group_clean
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fernando_anotantion_bio_multiple_norwegian_group_clean` is a English model originally trained by GLeite.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fernando_anotantion_bio_multiple_norwegian_group_clean_en_5.5.1_3.0_1737935524011.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fernando_anotantion_bio_multiple_norwegian_group_clean_en_5.5.1_3.0_1737935524011.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("fernando_anotantion_bio_multiple_norwegian_group_clean","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("fernando_anotantion_bio_multiple_norwegian_group_clean", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fernando_anotantion_bio_multiple_norwegian_group_clean|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|665.4 MB|
+
+## References
+
+https://huggingface.co/GLeite/Fernando-Anotantion-BIO-multiple-no-group-clean
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-fernando_anotantion_bio_multiple_norwegian_group_clean_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-fernando_anotantion_bio_multiple_norwegian_group_clean_pipeline_en.md
new file mode 100644
index 00000000000000..f3ced8721f9a48
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-fernando_anotantion_bio_multiple_norwegian_group_clean_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English fernando_anotantion_bio_multiple_norwegian_group_clean_pipeline pipeline BertForTokenClassification from GLeite
+author: John Snow Labs
+name: fernando_anotantion_bio_multiple_norwegian_group_clean_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fernando_anotantion_bio_multiple_norwegian_group_clean_pipeline` is a English model originally trained by GLeite.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fernando_anotantion_bio_multiple_norwegian_group_clean_pipeline_en_5.5.1_3.0_1737935559153.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fernando_anotantion_bio_multiple_norwegian_group_clean_pipeline_en_5.5.1_3.0_1737935559153.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fernando_anotantion_bio_multiple_norwegian_group_clean_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fernando_anotantion_bio_multiple_norwegian_group_clean_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fernando_anotantion_bio_multiple_norwegian_group_clean_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|665.4 MB|
+
+## References
+
+https://huggingface.co/GLeite/Fernando-Anotantion-BIO-multiple-no-group-clean
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-ffpp_raw_1fps_faces_expand_40_aligned_metric_en.md b/docs/_posts/ahmedlone127/2025-01-26-ffpp_raw_1fps_faces_expand_40_aligned_metric_en.md
new file mode 100644
index 00000000000000..e72516ca3211e6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-ffpp_raw_1fps_faces_expand_40_aligned_metric_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ffpp_raw_1fps_faces_expand_40_aligned_metric SwinForImageClassification from hchcsuim
+author: John Snow Labs
+name: ffpp_raw_1fps_faces_expand_40_aligned_metric
+date: 2025-01-26
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ffpp_raw_1fps_faces_expand_40_aligned_metric` is a English model originally trained by hchcsuim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ffpp_raw_1fps_faces_expand_40_aligned_metric_en_5.5.1_3.0_1737888988346.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ffpp_raw_1fps_faces_expand_40_aligned_metric_en_5.5.1_3.0_1737888988346.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""ffpp_raw_1fps_faces_expand_40_aligned_metric","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("ffpp_raw_1fps_faces_expand_40_aligned_metric","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ffpp_raw_1fps_faces_expand_40_aligned_metric|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/hchcsuim/FFPP-Raw_1FPS_faces-expand-40-aligned_metric
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-ffpp_raw_1fps_faces_expand_40_aligned_metric_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-ffpp_raw_1fps_faces_expand_40_aligned_metric_pipeline_en.md
new file mode 100644
index 00000000000000..49498ee2b4dea2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-ffpp_raw_1fps_faces_expand_40_aligned_metric_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English ffpp_raw_1fps_faces_expand_40_aligned_metric_pipeline pipeline SwinForImageClassification from hchcsuim
+author: John Snow Labs
+name: ffpp_raw_1fps_faces_expand_40_aligned_metric_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ffpp_raw_1fps_faces_expand_40_aligned_metric_pipeline` is a English model originally trained by hchcsuim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ffpp_raw_1fps_faces_expand_40_aligned_metric_pipeline_en_5.5.1_3.0_1737889001331.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ffpp_raw_1fps_faces_expand_40_aligned_metric_pipeline_en_5.5.1_3.0_1737889001331.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ffpp_raw_1fps_faces_expand_40_aligned_metric_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ffpp_raw_1fps_faces_expand_40_aligned_metric_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ffpp_raw_1fps_faces_expand_40_aligned_metric_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/hchcsuim/FFPP-Raw_1FPS_faces-expand-40-aligned_metric
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-fierro_3_en.md b/docs/_posts/ahmedlone127/2025-01-26-fierro_3_en.md
new file mode 100644
index 00000000000000..cdc0dcd4111dcc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-fierro_3_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English fierro_3 GPT2Transformer from Kinga1BK
+author: John Snow Labs
+name: fierro_3
+date: 2025-01-26
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fierro_3` is a English model originally trained by Kinga1BK.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fierro_3_en_5.5.1_3.0_1737868005109.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fierro_3_en_5.5.1_3.0_1737868005109.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("fierro_3","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("fierro_3","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fierro_3|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/Kinga1BK/FIERRO_3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-fierro_3_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-fierro_3_pipeline_en.md
new file mode 100644
index 00000000000000..1dd4498aef2f09
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-fierro_3_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English fierro_3_pipeline pipeline GPT2Transformer from Kinga1BK
+author: John Snow Labs
+name: fierro_3_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fierro_3_pipeline` is a English model originally trained by Kinga1BK.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fierro_3_pipeline_en_5.5.1_3.0_1737868032824.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fierro_3_pipeline_en_5.5.1_3.0_1737868032824.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fierro_3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fierro_3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fierro_3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/Kinga1BK/FIERRO_3
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-finance_distilbert_sentiment_en.md b/docs/_posts/ahmedlone127/2025-01-26-finance_distilbert_sentiment_en.md
new file mode 100644
index 00000000000000..06c6eb6431003a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-finance_distilbert_sentiment_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finance_distilbert_sentiment DistilBertForSequenceClassification from Sharpaxis
+author: John Snow Labs
+name: finance_distilbert_sentiment
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finance_distilbert_sentiment` is a English model originally trained by Sharpaxis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finance_distilbert_sentiment_en_5.5.1_3.0_1737929279033.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finance_distilbert_sentiment_en_5.5.1_3.0_1737929279033.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finance_distilbert_sentiment","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finance_distilbert_sentiment", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finance_distilbert_sentiment|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Sharpaxis/Finance_DistilBERT_sentiment
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-finance_distilbert_sentiment_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-finance_distilbert_sentiment_pipeline_en.md
new file mode 100644
index 00000000000000..91dcb7679115d3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-finance_distilbert_sentiment_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finance_distilbert_sentiment_pipeline pipeline DistilBertForSequenceClassification from Sharpaxis
+author: John Snow Labs
+name: finance_distilbert_sentiment_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finance_distilbert_sentiment_pipeline` is a English model originally trained by Sharpaxis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finance_distilbert_sentiment_pipeline_en_5.5.1_3.0_1737929294629.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finance_distilbert_sentiment_pipeline_en_5.5.1_3.0_1737929294629.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finance_distilbert_sentiment_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finance_distilbert_sentiment_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finance_distilbert_sentiment_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Sharpaxis/Finance_DistilBERT_sentiment
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-fine_tuned_xlm_roberta_for_mgtd2_en.md b/docs/_posts/ahmedlone127/2025-01-26-fine_tuned_xlm_roberta_for_mgtd2_en.md
new file mode 100644
index 00000000000000..481cfa08c8ef2d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-fine_tuned_xlm_roberta_for_mgtd2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English fine_tuned_xlm_roberta_for_mgtd2 XlmRoBertaForSequenceClassification from keles
+author: John Snow Labs
+name: fine_tuned_xlm_roberta_for_mgtd2
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_xlm_roberta_for_mgtd2` is a English model originally trained by keles.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_xlm_roberta_for_mgtd2_en_5.5.1_3.0_1737880055548.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_xlm_roberta_for_mgtd2_en_5.5.1_3.0_1737880055548.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("fine_tuned_xlm_roberta_for_mgtd2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("fine_tuned_xlm_roberta_for_mgtd2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_xlm_roberta_for_mgtd2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|936.9 MB|
+
+## References
+
+https://huggingface.co/keles/fine_tuned_xlm_roberta_for_mgtd2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-fine_tuned_xlm_roberta_for_mgtd2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-fine_tuned_xlm_roberta_for_mgtd2_pipeline_en.md
new file mode 100644
index 00000000000000..6d822ac7340239
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-fine_tuned_xlm_roberta_for_mgtd2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English fine_tuned_xlm_roberta_for_mgtd2_pipeline pipeline XlmRoBertaForSequenceClassification from keles
+author: John Snow Labs
+name: fine_tuned_xlm_roberta_for_mgtd2_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_xlm_roberta_for_mgtd2_pipeline` is a English model originally trained by keles.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_xlm_roberta_for_mgtd2_pipeline_en_5.5.1_3.0_1737880133693.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_xlm_roberta_for_mgtd2_pipeline_en_5.5.1_3.0_1737880133693.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fine_tuned_xlm_roberta_for_mgtd2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fine_tuned_xlm_roberta_for_mgtd2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_xlm_roberta_for_mgtd2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|936.9 MB|
+
+## References
+
+https://huggingface.co/keles/fine_tuned_xlm_roberta_for_mgtd2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-finetuned3_en.md b/docs/_posts/ahmedlone127/2025-01-26-finetuned3_en.md
new file mode 100644
index 00000000000000..219c61c244af78
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-finetuned3_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English finetuned3 GPT2Transformer from Toflamus
+author: John Snow Labs
+name: finetuned3
+date: 2025-01-26
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned3` is a English model originally trained by Toflamus.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned3_en_5.5.1_3.0_1737867880652.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned3_en_5.5.1_3.0_1737867880652.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("finetuned3","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("finetuned3","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned3|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|14.4 MB|
+
+## References
+
+https://huggingface.co/Toflamus/Finetuned3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-finetuned3_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-finetuned3_pipeline_en.md
new file mode 100644
index 00000000000000..c358a5d3f8077f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-finetuned3_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English finetuned3_pipeline pipeline GPT2Transformer from Toflamus
+author: John Snow Labs
+name: finetuned3_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned3_pipeline` is a English model originally trained by Toflamus.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned3_pipeline_en_5.5.1_3.0_1737867882022.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned3_pipeline_en_5.5.1_3.0_1737867882022.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuned3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuned3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|14.4 MB|
+
+## References
+
+https://huggingface.co/Toflamus/Finetuned3
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-finetuned_ai_real_swin_en.md b/docs/_posts/ahmedlone127/2025-01-26-finetuned_ai_real_swin_en.md
new file mode 100644
index 00000000000000..7bfc4d112ccfde
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-finetuned_ai_real_swin_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuned_ai_real_swin SwinForImageClassification from vikas117
+author: John Snow Labs
+name: finetuned_ai_real_swin
+date: 2025-01-26
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_ai_real_swin` is a English model originally trained by vikas117.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_ai_real_swin_en_5.5.1_3.0_1737888809615.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_ai_real_swin_en_5.5.1_3.0_1737888809615.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""finetuned_ai_real_swin","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("finetuned_ai_real_swin","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_ai_real_swin|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/vikas117/finetuned-ai-real-swin
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-finetuned_ai_real_swin_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-finetuned_ai_real_swin_pipeline_en.md
new file mode 100644
index 00000000000000..9f7d32cd51b697
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-finetuned_ai_real_swin_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English finetuned_ai_real_swin_pipeline pipeline SwinForImageClassification from vikas117
+author: John Snow Labs
+name: finetuned_ai_real_swin_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_ai_real_swin_pipeline` is a English model originally trained by vikas117.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_ai_real_swin_pipeline_en_5.5.1_3.0_1737888820271.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_ai_real_swin_pipeline_en_5.5.1_3.0_1737888820271.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuned_ai_real_swin_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuned_ai_real_swin_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_ai_real_swin_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/vikas117/finetuned-ai-real-swin
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-finetuned_deberta_carer_4isear_4_en.md b/docs/_posts/ahmedlone127/2025-01-26-finetuned_deberta_carer_4isear_4_en.md
new file mode 100644
index 00000000000000..de9b1daaa9737e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-finetuned_deberta_carer_4isear_4_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuned_deberta_carer_4isear_4 DeBertaForSequenceClassification from UO282436
+author: John Snow Labs
+name: finetuned_deberta_carer_4isear_4
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_deberta_carer_4isear_4` is a English model originally trained by UO282436.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_deberta_carer_4isear_4_en_5.5.1_3.0_1737917697543.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_deberta_carer_4isear_4_en_5.5.1_3.0_1737917697543.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("finetuned_deberta_carer_4isear_4","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("finetuned_deberta_carer_4isear_4", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_deberta_carer_4isear_4|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|582.6 MB|
+
+## References
+
+https://huggingface.co/UO282436/finetuned-deberta-carer_4isear_4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-finetuned_deberta_carer_4isear_4_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-finetuned_deberta_carer_4isear_4_pipeline_en.md
new file mode 100644
index 00000000000000..ca757b0f64dcce
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-finetuned_deberta_carer_4isear_4_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuned_deberta_carer_4isear_4_pipeline pipeline DeBertaForSequenceClassification from UO282436
+author: John Snow Labs
+name: finetuned_deberta_carer_4isear_4_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_deberta_carer_4isear_4_pipeline` is a English model originally trained by UO282436.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_deberta_carer_4isear_4_pipeline_en_5.5.1_3.0_1737917770918.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_deberta_carer_4isear_4_pipeline_en_5.5.1_3.0_1737917770918.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuned_deberta_carer_4isear_4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuned_deberta_carer_4isear_4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_deberta_carer_4isear_4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|582.6 MB|
+
+## References
+
+https://huggingface.co/UO282436/finetuned-deberta-carer_4isear_4
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-finetuned_ner_model_en.md b/docs/_posts/ahmedlone127/2025-01-26-finetuned_ner_model_en.md
new file mode 100644
index 00000000000000..e5f4de67fdedf4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-finetuned_ner_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuned_ner_model BertForTokenClassification from a-n-a-n-y-a-123
+author: John Snow Labs
+name: finetuned_ner_model
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_ner_model` is a English model originally trained by a-n-a-n-y-a-123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_ner_model_en_5.5.1_3.0_1737934977477.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_ner_model_en_5.5.1_3.0_1737934977477.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("finetuned_ner_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("finetuned_ner_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_ner_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/a-n-a-n-y-a-123/finetuned_ner_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-finetuned_ner_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-finetuned_ner_model_pipeline_en.md
new file mode 100644
index 00000000000000..2355858a24bb96
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-finetuned_ner_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuned_ner_model_pipeline pipeline BertForTokenClassification from a-n-a-n-y-a-123
+author: John Snow Labs
+name: finetuned_ner_model_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_ner_model_pipeline` is a English model originally trained by a-n-a-n-y-a-123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_ner_model_pipeline_en_5.5.1_3.0_1737935009864.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_ner_model_pipeline_en_5.5.1_3.0_1737935009864.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuned_ner_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuned_ner_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_ner_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/a-n-a-n-y-a-123/finetuned_ner_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-finetuning_amazon_sample100000_text_distilmodel_en.md b/docs/_posts/ahmedlone127/2025-01-26-finetuning_amazon_sample100000_text_distilmodel_en.md
new file mode 100644
index 00000000000000..8d3597fe42580e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-finetuning_amazon_sample100000_text_distilmodel_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuning_amazon_sample100000_text_distilmodel DistilBertForSequenceClassification from hsiuping
+author: John Snow Labs
+name: finetuning_amazon_sample100000_text_distilmodel
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_amazon_sample100000_text_distilmodel` is a English model originally trained by hsiuping.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_amazon_sample100000_text_distilmodel_en_5.5.1_3.0_1737904991280.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_amazon_sample100000_text_distilmodel_en_5.5.1_3.0_1737904991280.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuning_amazon_sample100000_text_distilmodel","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_amazon_sample100000_text_distilmodel", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_amazon_sample100000_text_distilmodel|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/hsiuping/finetuning-amazon-sample100000-text-Distilmodel
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-finetuning_amazon_sample100000_text_distilmodel_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-finetuning_amazon_sample100000_text_distilmodel_pipeline_en.md
new file mode 100644
index 00000000000000..bb141474194754
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-finetuning_amazon_sample100000_text_distilmodel_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuning_amazon_sample100000_text_distilmodel_pipeline pipeline DistilBertForSequenceClassification from hsiuping
+author: John Snow Labs
+name: finetuning_amazon_sample100000_text_distilmodel_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_amazon_sample100000_text_distilmodel_pipeline` is a English model originally trained by hsiuping.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_amazon_sample100000_text_distilmodel_pipeline_en_5.5.1_3.0_1737905004369.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_amazon_sample100000_text_distilmodel_pipeline_en_5.5.1_3.0_1737905004369.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuning_amazon_sample100000_text_distilmodel_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuning_amazon_sample100000_text_distilmodel_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_amazon_sample100000_text_distilmodel_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/hsiuping/finetuning-amazon-sample100000-text-Distilmodel
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-finetuning_covidsenti_distilbert_model_en.md b/docs/_posts/ahmedlone127/2025-01-26-finetuning_covidsenti_distilbert_model_en.md
new file mode 100644
index 00000000000000..34b3c409ace60d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-finetuning_covidsenti_distilbert_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuning_covidsenti_distilbert_model DistilBertForSequenceClassification from Letrica
+author: John Snow Labs
+name: finetuning_covidsenti_distilbert_model
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_covidsenti_distilbert_model` is a English model originally trained by Letrica.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_covidsenti_distilbert_model_en_5.5.1_3.0_1737905085914.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_covidsenti_distilbert_model_en_5.5.1_3.0_1737905085914.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuning_covidsenti_distilbert_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_covidsenti_distilbert_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_covidsenti_distilbert_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Letrica/finetuning-COVIDSenti-distilbert-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-finetuning_covidsenti_distilbert_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-finetuning_covidsenti_distilbert_model_pipeline_en.md
new file mode 100644
index 00000000000000..a83e6ed880660d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-finetuning_covidsenti_distilbert_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuning_covidsenti_distilbert_model_pipeline pipeline DistilBertForSequenceClassification from Letrica
+author: John Snow Labs
+name: finetuning_covidsenti_distilbert_model_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_covidsenti_distilbert_model_pipeline` is a English model originally trained by Letrica.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_covidsenti_distilbert_model_pipeline_en_5.5.1_3.0_1737905098703.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_covidsenti_distilbert_model_pipeline_en_5.5.1_3.0_1737905098703.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuning_covidsenti_distilbert_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuning_covidsenti_distilbert_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_covidsenti_distilbert_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Letrica/finetuning-COVIDSenti-distilbert-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-finetuning_sentiment_model_1000_samples_asheba_en.md b/docs/_posts/ahmedlone127/2025-01-26-finetuning_sentiment_model_1000_samples_asheba_en.md
new file mode 100644
index 00000000000000..31a95d9c54d2cb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-finetuning_sentiment_model_1000_samples_asheba_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuning_sentiment_model_1000_samples_asheba DistilBertForSequenceClassification from AshEba
+author: John Snow Labs
+name: finetuning_sentiment_model_1000_samples_asheba
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_1000_samples_asheba` is a English model originally trained by AshEba.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_1000_samples_asheba_en_5.5.1_3.0_1737928715324.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_1000_samples_asheba_en_5.5.1_3.0_1737928715324.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_1000_samples_asheba","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_1000_samples_asheba", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_1000_samples_asheba|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/AshEba/finetuning-sentiment-model-1000-samples
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-finetuning_sentiment_model_1000_samples_asheba_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-finetuning_sentiment_model_1000_samples_asheba_pipeline_en.md
new file mode 100644
index 00000000000000..77478bd3015718
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-finetuning_sentiment_model_1000_samples_asheba_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuning_sentiment_model_1000_samples_asheba_pipeline pipeline DistilBertForSequenceClassification from AshEba
+author: John Snow Labs
+name: finetuning_sentiment_model_1000_samples_asheba_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_1000_samples_asheba_pipeline` is a English model originally trained by AshEba.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_1000_samples_asheba_pipeline_en_5.5.1_3.0_1737928730374.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_1000_samples_asheba_pipeline_en_5.5.1_3.0_1737928730374.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuning_sentiment_model_1000_samples_asheba_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuning_sentiment_model_1000_samples_asheba_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_1000_samples_asheba_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/AshEba/finetuning-sentiment-model-1000-samples
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-finetuning_sentiment_model_3000_samples_gmmaalouf_en.md b/docs/_posts/ahmedlone127/2025-01-26-finetuning_sentiment_model_3000_samples_gmmaalouf_en.md
new file mode 100644
index 00000000000000..e5ca27f0ca75ee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-finetuning_sentiment_model_3000_samples_gmmaalouf_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_gmmaalouf DistilBertForSequenceClassification from gmmaalouf
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_gmmaalouf
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_gmmaalouf` is a English model originally trained by gmmaalouf.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_gmmaalouf_en_5.5.1_3.0_1737873572580.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_gmmaalouf_en_5.5.1_3.0_1737873572580.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_gmmaalouf","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_gmmaalouf", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_gmmaalouf|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/gmmaalouf/finetuning-sentiment-model-3000-samples
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-finetuning_sentiment_model_3000_samples_gmmaalouf_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-finetuning_sentiment_model_3000_samples_gmmaalouf_pipeline_en.md
new file mode 100644
index 00000000000000..29cc6fad5dbc3e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-finetuning_sentiment_model_3000_samples_gmmaalouf_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_gmmaalouf_pipeline pipeline DistilBertForSequenceClassification from gmmaalouf
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_gmmaalouf_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_gmmaalouf_pipeline` is a English model originally trained by gmmaalouf.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_gmmaalouf_pipeline_en_5.5.1_3.0_1737873589313.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_gmmaalouf_pipeline_en_5.5.1_3.0_1737873589313.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuning_sentiment_model_3000_samples_gmmaalouf_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuning_sentiment_model_3000_samples_gmmaalouf_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_gmmaalouf_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/gmmaalouf/finetuning-sentiment-model-3000-samples
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-finetuning_sentiment_model_3000_samples_pettemae_en.md b/docs/_posts/ahmedlone127/2025-01-26-finetuning_sentiment_model_3000_samples_pettemae_en.md
new file mode 100644
index 00000000000000..99151e2a5dac26
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-finetuning_sentiment_model_3000_samples_pettemae_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_pettemae DistilBertForSequenceClassification from pettemae
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_pettemae
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_pettemae` is a English model originally trained by pettemae.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_pettemae_en_5.5.1_3.0_1737929479660.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_pettemae_en_5.5.1_3.0_1737929479660.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_pettemae","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_pettemae", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_pettemae|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/pettemae/finetuning-sentiment-model-3000-samples
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-finetuning_sentiment_model_3000_samples_pettemae_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-finetuning_sentiment_model_3000_samples_pettemae_pipeline_en.md
new file mode 100644
index 00000000000000..5f62e452b8279f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-finetuning_sentiment_model_3000_samples_pettemae_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_pettemae_pipeline pipeline DistilBertForSequenceClassification from pettemae
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_pettemae_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_pettemae_pipeline` is a English model originally trained by pettemae.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_pettemae_pipeline_en_5.5.1_3.0_1737929493494.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_pettemae_pipeline_en_5.5.1_3.0_1737929493494.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuning_sentiment_model_3000_samples_pettemae_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuning_sentiment_model_3000_samples_pettemae_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_pettemae_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/pettemae/finetuning-sentiment-model-3000-samples
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-finetuning_sentiment_model_3000_samples_swapnil7777_en.md b/docs/_posts/ahmedlone127/2025-01-26-finetuning_sentiment_model_3000_samples_swapnil7777_en.md
new file mode 100644
index 00000000000000..bc840a8060d22f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-finetuning_sentiment_model_3000_samples_swapnil7777_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_swapnil7777 DistilBertForSequenceClassification from swapnil7777
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_swapnil7777
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_swapnil7777` is a English model originally trained by swapnil7777.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_swapnil7777_en_5.5.1_3.0_1737873864195.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_swapnil7777_en_5.5.1_3.0_1737873864195.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_swapnil7777","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_swapnil7777", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_swapnil7777|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/swapnil7777/finetuning-sentiment-model-3000-samples
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-finetuning_sentiment_model_3000_samples_swapnil7777_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-finetuning_sentiment_model_3000_samples_swapnil7777_pipeline_en.md
new file mode 100644
index 00000000000000..37cc08a974804f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-finetuning_sentiment_model_3000_samples_swapnil7777_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_swapnil7777_pipeline pipeline DistilBertForSequenceClassification from swapnil7777
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_swapnil7777_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_swapnil7777_pipeline` is a English model originally trained by swapnil7777.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_swapnil7777_pipeline_en_5.5.1_3.0_1737873879099.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_swapnil7777_pipeline_en_5.5.1_3.0_1737873879099.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuning_sentiment_model_3000_samples_swapnil7777_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuning_sentiment_model_3000_samples_swapnil7777_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_swapnil7777_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/swapnil7777/finetuning-sentiment-model-3000-samples
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-finetuning_sentiment_model_3000_samples_taimoor_ahmed1_en.md b/docs/_posts/ahmedlone127/2025-01-26-finetuning_sentiment_model_3000_samples_taimoor_ahmed1_en.md
new file mode 100644
index 00000000000000..215e07a4eead18
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-finetuning_sentiment_model_3000_samples_taimoor_ahmed1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_taimoor_ahmed1 DistilBertForSequenceClassification from taimoor-ahmed1
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_taimoor_ahmed1
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_taimoor_ahmed1` is a English model originally trained by taimoor-ahmed1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_taimoor_ahmed1_en_5.5.1_3.0_1737929377477.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_taimoor_ahmed1_en_5.5.1_3.0_1737929377477.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_taimoor_ahmed1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_taimoor_ahmed1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_taimoor_ahmed1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/taimoor-ahmed1/finetuning-sentiment-model-3000-samples
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-finetuning_sentiment_model_3000_samples_taimoor_ahmed1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-finetuning_sentiment_model_3000_samples_taimoor_ahmed1_pipeline_en.md
new file mode 100644
index 00000000000000..48dd1907f5507b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-finetuning_sentiment_model_3000_samples_taimoor_ahmed1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_taimoor_ahmed1_pipeline pipeline DistilBertForSequenceClassification from taimoor-ahmed1
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_taimoor_ahmed1_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_taimoor_ahmed1_pipeline` is a English model originally trained by taimoor-ahmed1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_taimoor_ahmed1_pipeline_en_5.5.1_3.0_1737929390562.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_taimoor_ahmed1_pipeline_en_5.5.1_3.0_1737929390562.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuning_sentiment_model_3000_samples_taimoor_ahmed1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuning_sentiment_model_3000_samples_taimoor_ahmed1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_taimoor_ahmed1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/taimoor-ahmed1/finetuning-sentiment-model-3000-samples
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-finetuning_sentiment_model_tec_en.md b/docs/_posts/ahmedlone127/2025-01-26-finetuning_sentiment_model_tec_en.md
new file mode 100644
index 00000000000000..d174b635337944
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-finetuning_sentiment_model_tec_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuning_sentiment_model_tec DistilBertForSequenceClassification from greyngs
+author: John Snow Labs
+name: finetuning_sentiment_model_tec
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_tec` is a English model originally trained by greyngs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_tec_en_5.5.1_3.0_1737929176322.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_tec_en_5.5.1_3.0_1737929176322.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_tec","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_tec", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_tec|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/greyngs/finetuning-sentiment-model-tec
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-finetuning_sentiment_model_tec_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-finetuning_sentiment_model_tec_pipeline_en.md
new file mode 100644
index 00000000000000..094d35666e545a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-finetuning_sentiment_model_tec_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuning_sentiment_model_tec_pipeline pipeline DistilBertForSequenceClassification from greyngs
+author: John Snow Labs
+name: finetuning_sentiment_model_tec_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_tec_pipeline` is a English model originally trained by greyngs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_tec_pipeline_en_5.5.1_3.0_1737929190184.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_tec_pipeline_en_5.5.1_3.0_1737929190184.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuning_sentiment_model_tec_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuning_sentiment_model_tec_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_tec_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/greyngs/finetuning-sentiment-model-tec
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-flan_t5_base_educational_question_generate_en.md b/docs/_posts/ahmedlone127/2025-01-26-flan_t5_base_educational_question_generate_en.md
new file mode 100644
index 00000000000000..607f4755ed415e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-flan_t5_base_educational_question_generate_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English flan_t5_base_educational_question_generate T5Transformer from danielfdev
+author: John Snow Labs
+name: flan_t5_base_educational_question_generate
+date: 2025-01-26
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_base_educational_question_generate` is a English model originally trained by danielfdev.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_base_educational_question_generate_en_5.5.1_3.0_1737851790951.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_base_educational_question_generate_en_5.5.1_3.0_1737851790951.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("flan_t5_base_educational_question_generate","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("flan_t5_base_educational_question_generate", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_base_educational_question_generate|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/danielfdev/flan-t5-base-educational-question-generate
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-flan_t5_base_educational_question_generate_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-flan_t5_base_educational_question_generate_pipeline_en.md
new file mode 100644
index 00000000000000..b4cb91d187bc47
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-flan_t5_base_educational_question_generate_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English flan_t5_base_educational_question_generate_pipeline pipeline T5Transformer from danielfdev
+author: John Snow Labs
+name: flan_t5_base_educational_question_generate_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_base_educational_question_generate_pipeline` is a English model originally trained by danielfdev.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_base_educational_question_generate_pipeline_en_5.5.1_3.0_1737851844089.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_base_educational_question_generate_pipeline_en_5.5.1_3.0_1737851844089.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("flan_t5_base_educational_question_generate_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("flan_t5_base_educational_question_generate_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_base_educational_question_generate_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/danielfdev/flan-t5-base-educational-question-generate
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-flant5_paraphrase_en.md b/docs/_posts/ahmedlone127/2025-01-26-flant5_paraphrase_en.md
new file mode 100644
index 00000000000000..ac6a8b202ae76c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-flant5_paraphrase_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English flant5_paraphrase T5Transformer from debjitp452
+author: John Snow Labs
+name: flant5_paraphrase
+date: 2025-01-26
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flant5_paraphrase` is a English model originally trained by debjitp452.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flant5_paraphrase_en_5.5.1_3.0_1737850260845.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flant5_paraphrase_en_5.5.1_3.0_1737850260845.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("flant5_paraphrase","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("flant5_paraphrase", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flant5_paraphrase|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|3.1 GB|
+
+## References
+
+https://huggingface.co/debjitp452/flant5_paraphrase
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-flant5_paraphrase_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-flant5_paraphrase_pipeline_en.md
new file mode 100644
index 00000000000000..1189c7dc64df27
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-flant5_paraphrase_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English flant5_paraphrase_pipeline pipeline T5Transformer from debjitp452
+author: John Snow Labs
+name: flant5_paraphrase_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flant5_paraphrase_pipeline` is a English model originally trained by debjitp452.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flant5_paraphrase_pipeline_en_5.5.1_3.0_1737850400480.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flant5_paraphrase_pipeline_en_5.5.1_3.0_1737850400480.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("flant5_paraphrase_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("flant5_paraphrase_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flant5_paraphrase_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|3.1 GB|
+
+## References
+
+https://huggingface.co/debjitp452/flant5_paraphrase
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-flashcard_generator_en.md b/docs/_posts/ahmedlone127/2025-01-26-flashcard_generator_en.md
new file mode 100644
index 00000000000000..8ec6645d99e81d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-flashcard_generator_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English flashcard_generator T5Transformer from wailalrahbi
+author: John Snow Labs
+name: flashcard_generator
+date: 2025-01-26
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flashcard_generator` is a English model originally trained by wailalrahbi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flashcard_generator_en_5.5.1_3.0_1737851027581.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flashcard_generator_en_5.5.1_3.0_1737851027581.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("flashcard_generator","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("flashcard_generator", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flashcard_generator|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/wailalrahbi/flashcard-generator
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-flashcard_generator_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-flashcard_generator_pipeline_en.md
new file mode 100644
index 00000000000000..daf13c559126a9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-flashcard_generator_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English flashcard_generator_pipeline pipeline T5Transformer from wailalrahbi
+author: John Snow Labs
+name: flashcard_generator_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flashcard_generator_pipeline` is a English model originally trained by wailalrahbi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flashcard_generator_pipeline_en_5.5.1_3.0_1737851078886.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flashcard_generator_pipeline_en_5.5.1_3.0_1737851078886.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("flashcard_generator_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("flashcard_generator_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flashcard_generator_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/wailalrahbi/flashcard-generator
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-flipped_5e_5_igbo_en.md b/docs/_posts/ahmedlone127/2025-01-26-flipped_5e_5_igbo_en.md
new file mode 100644
index 00000000000000..c6a61ba7f0d2bc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-flipped_5e_5_igbo_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English flipped_5e_5_igbo XlmRoBertaForTokenClassification from grace-pro
+author: John Snow Labs
+name: flipped_5e_5_igbo
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flipped_5e_5_igbo` is a English model originally trained by grace-pro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flipped_5e_5_igbo_en_5.5.1_3.0_1737853487704.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flipped_5e_5_igbo_en_5.5.1_3.0_1737853487704.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("flipped_5e_5_igbo","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("flipped_5e_5_igbo", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flipped_5e_5_igbo|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/grace-pro/flipped_5e-5_igbo
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-flipped_5e_5_igbo_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-flipped_5e_5_igbo_pipeline_en.md
new file mode 100644
index 00000000000000..d79de073adafb9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-flipped_5e_5_igbo_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English flipped_5e_5_igbo_pipeline pipeline XlmRoBertaForTokenClassification from grace-pro
+author: John Snow Labs
+name: flipped_5e_5_igbo_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flipped_5e_5_igbo_pipeline` is a English model originally trained by grace-pro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flipped_5e_5_igbo_pipeline_en_5.5.1_3.0_1737853542397.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flipped_5e_5_igbo_pipeline_en_5.5.1_3.0_1737853542397.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("flipped_5e_5_igbo_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("flipped_5e_5_igbo_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flipped_5e_5_igbo_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/grace-pro/flipped_5e-5_igbo
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-gate_reranker_v1_ar.md b/docs/_posts/ahmedlone127/2025-01-26-gate_reranker_v1_ar.md
new file mode 100644
index 00000000000000..17dc322b7a1a88
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-gate_reranker_v1_ar.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Arabic gate_reranker_v1 BertForSequenceClassification from NAMAA-Space
+author: John Snow Labs
+name: gate_reranker_v1
+date: 2025-01-26
+tags: [ar, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: ar
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gate_reranker_v1` is a Arabic model originally trained by NAMAA-Space.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gate_reranker_v1_ar_5.5.1_3.0_1737921203024.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gate_reranker_v1_ar_5.5.1_3.0_1737921203024.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("gate_reranker_v1","ar") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("gate_reranker_v1", "ar")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gate_reranker_v1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|ar|
+|Size:|507.3 MB|
+
+## References
+
+https://huggingface.co/NAMAA-Space/GATE-Reranker-V1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-gate_reranker_v1_pipeline_ar.md b/docs/_posts/ahmedlone127/2025-01-26-gate_reranker_v1_pipeline_ar.md
new file mode 100644
index 00000000000000..a5ccbbcd0cd751
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-gate_reranker_v1_pipeline_ar.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Arabic gate_reranker_v1_pipeline pipeline BertForSequenceClassification from NAMAA-Space
+author: John Snow Labs
+name: gate_reranker_v1_pipeline
+date: 2025-01-26
+tags: [ar, open_source, pipeline, onnx]
+task: Text Classification
+language: ar
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gate_reranker_v1_pipeline` is a Arabic model originally trained by NAMAA-Space.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gate_reranker_v1_pipeline_ar_5.5.1_3.0_1737921229288.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gate_reranker_v1_pipeline_ar_5.5.1_3.0_1737921229288.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gate_reranker_v1_pipeline", lang = "ar")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gate_reranker_v1_pipeline", lang = "ar")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gate_reranker_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ar|
+|Size:|507.3 MB|
+
+## References
+
+https://huggingface.co/NAMAA-Space/GATE-Reranker-V1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-gay_en.md b/docs/_posts/ahmedlone127/2025-01-26-gay_en.md
new file mode 100644
index 00000000000000..5e0432f657cff8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-gay_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English gay BertForQuestionAnswering from sinos11
+author: John Snow Labs
+name: gay
+date: 2025-01-26
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gay` is a English model originally trained by sinos11.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gay_en_5.5.1_3.0_1737919159574.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gay_en_5.5.1_3.0_1737919159574.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("gay","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("gay", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gay|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/sinos11/gay
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-gay_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-gay_pipeline_en.md
new file mode 100644
index 00000000000000..9b4376dba6a1c4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-gay_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English gay_pipeline pipeline BertForQuestionAnswering from sinos11
+author: John Snow Labs
+name: gay_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gay_pipeline` is a English model originally trained by sinos11.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gay_pipeline_en_5.5.1_3.0_1737919181226.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gay_pipeline_en_5.5.1_3.0_1737919181226.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gay_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gay_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gay_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/sinos11/gay
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-gbert_job_extended_en.md b/docs/_posts/ahmedlone127/2025-01-26-gbert_job_extended_en.md
new file mode 100644
index 00000000000000..262b4bab95faed
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-gbert_job_extended_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English gbert_job_extended BertEmbeddings from dathi103
+author: John Snow Labs
+name: gbert_job_extended
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gbert_job_extended` is a English model originally trained by dathi103.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gbert_job_extended_en_5.5.1_3.0_1737861518851.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gbert_job_extended_en_5.5.1_3.0_1737861518851.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("gbert_job_extended","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("gbert_job_extended","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gbert_job_extended|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|420.0 MB|
+
+## References
+
+https://huggingface.co/dathi103/gbert-job-extended
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-gbert_job_extended_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-gbert_job_extended_pipeline_en.md
new file mode 100644
index 00000000000000..e5032e4f750be4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-gbert_job_extended_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English gbert_job_extended_pipeline pipeline BertEmbeddings from dathi103
+author: John Snow Labs
+name: gbert_job_extended_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gbert_job_extended_pipeline` is a English model originally trained by dathi103.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gbert_job_extended_pipeline_en_5.5.1_3.0_1737861543868.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gbert_job_extended_pipeline_en_5.5.1_3.0_1737861543868.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gbert_job_extended_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gbert_job_extended_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gbert_job_extended_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|420.0 MB|
+
+## References
+
+https://huggingface.co/dathi103/gbert-job-extended
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-gender_class_en.md b/docs/_posts/ahmedlone127/2025-01-26-gender_class_en.md
new file mode 100644
index 00000000000000..a3d23e7cfd5fbd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-gender_class_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English gender_class ViTForImageClassification from Leilab
+author: John Snow Labs
+name: gender_class
+date: 2025-01-26
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gender_class` is a English model originally trained by Leilab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gender_class_en_5.5.1_3.0_1737926457581.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gender_class_en_5.5.1_3.0_1737926457581.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""gender_class","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("gender_class","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gender_class|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/Leilab/gender_class
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-gender_class_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-gender_class_pipeline_en.md
new file mode 100644
index 00000000000000..b27bc759daee2a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-gender_class_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English gender_class_pipeline pipeline ViTForImageClassification from Leilab
+author: John Snow Labs
+name: gender_class_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gender_class_pipeline` is a English model originally trained by Leilab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gender_class_pipeline_en_5.5.1_3.0_1737926474493.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gender_class_pipeline_en_5.5.1_3.0_1737926474493.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gender_class_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gender_class_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gender_class_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/Leilab/gender_class
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-gpt2023_en.md b/docs/_posts/ahmedlone127/2025-01-26-gpt2023_en.md
new file mode 100644
index 00000000000000..101c72ed3f4a9b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-gpt2023_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English gpt2023 GPT2Transformer from crumb
+author: John Snow Labs
+name: gpt2023
+date: 2025-01-26
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2023` is a English model originally trained by crumb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2023_en_5.5.1_3.0_1737867158653.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2023_en_5.5.1_3.0_1737867158653.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("gpt2023","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("gpt2023","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2023|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|237.5 MB|
+
+## References
+
+https://huggingface.co/crumb/gpt2023
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-gpt2023_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-gpt2023_pipeline_en.md
new file mode 100644
index 00000000000000..4f290b87cf6eca
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-gpt2023_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English gpt2023_pipeline pipeline GPT2Transformer from crumb
+author: John Snow Labs
+name: gpt2023_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2023_pipeline` is a English model originally trained by crumb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2023_pipeline_en_5.5.1_3.0_1737867244303.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2023_pipeline_en_5.5.1_3.0_1737867244303.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpt2023_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpt2023_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2023_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|237.5 MB|
+
+## References
+
+https://huggingface.co/crumb/gpt2023
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-gpt2_94m_en.md b/docs/_posts/ahmedlone127/2025-01-26-gpt2_94m_en.md
new file mode 100644
index 00000000000000..f4238cf2ddb191
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-gpt2_94m_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English gpt2_94m GPT2Transformer from distributed
+author: John Snow Labs
+name: gpt2_94m
+date: 2025-01-26
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_94m` is a English model originally trained by distributed.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_94m_en_5.5.1_3.0_1737869222846.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_94m_en_5.5.1_3.0_1737869222846.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("gpt2_94m","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("gpt2_94m","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_94m|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|354.8 MB|
+
+## References
+
+https://huggingface.co/distributed/gpt2-94m
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-gpt2_94m_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-gpt2_94m_pipeline_en.md
new file mode 100644
index 00000000000000..9171f5bf67d15b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-gpt2_94m_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English gpt2_94m_pipeline pipeline GPT2Transformer from distributed
+author: John Snow Labs
+name: gpt2_94m_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_94m_pipeline` is a English model originally trained by distributed.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_94m_pipeline_en_5.5.1_3.0_1737869242183.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_94m_pipeline_en_5.5.1_3.0_1737869242183.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpt2_94m_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpt2_94m_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_94m_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|354.8 MB|
+
+## References
+
+https://huggingface.co/distributed/gpt2-94m
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-gpt2_bio_portuguese_pipeline_pt.md b/docs/_posts/ahmedlone127/2025-01-26-gpt2_bio_portuguese_pipeline_pt.md
new file mode 100644
index 00000000000000..b4f1a68bb2bb81
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-gpt2_bio_portuguese_pipeline_pt.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Portuguese gpt2_bio_portuguese_pipeline pipeline GPT2Transformer from pucpr
+author: John Snow Labs
+name: gpt2_bio_portuguese_pipeline
+date: 2025-01-26
+tags: [pt, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: pt
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_bio_portuguese_pipeline` is a Portuguese model originally trained by pucpr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_bio_portuguese_pipeline_pt_5.5.1_3.0_1737913866208.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_bio_portuguese_pipeline_pt_5.5.1_3.0_1737913866208.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpt2_bio_portuguese_pipeline", lang = "pt")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpt2_bio_portuguese_pipeline", lang = "pt")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_bio_portuguese_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|pt|
+|Size:|467.1 MB|
+
+## References
+
+https://huggingface.co/pucpr/gpt2-bio-pt
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-gpt2_bio_portuguese_pt.md b/docs/_posts/ahmedlone127/2025-01-26-gpt2_bio_portuguese_pt.md
new file mode 100644
index 00000000000000..b97edd39efd9d3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-gpt2_bio_portuguese_pt.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Portuguese gpt2_bio_portuguese GPT2Transformer from pucpr
+author: John Snow Labs
+name: gpt2_bio_portuguese
+date: 2025-01-26
+tags: [pt, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: pt
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_bio_portuguese` is a Portuguese model originally trained by pucpr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_bio_portuguese_pt_5.5.1_3.0_1737913842348.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_bio_portuguese_pt_5.5.1_3.0_1737913842348.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("gpt2_bio_portuguese","pt") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("gpt2_bio_portuguese","pt") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_bio_portuguese|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|pt|
+|Size:|467.1 MB|
+
+## References
+
+https://huggingface.co/pucpr/gpt2-bio-pt
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-gpt2_demo_en.md b/docs/_posts/ahmedlone127/2025-01-26-gpt2_demo_en.md
new file mode 100644
index 00000000000000..d6af0b5eb6d82c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-gpt2_demo_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English gpt2_demo GPT2Transformer from demo-leaderboard
+author: John Snow Labs
+name: gpt2_demo
+date: 2025-01-26
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_demo` is a English model originally trained by demo-leaderboard.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_demo_en_5.5.1_3.0_1737911013905.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_demo_en_5.5.1_3.0_1737911013905.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("gpt2_demo","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("gpt2_demo","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_demo|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/demo-leaderboard/gpt2-demo
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-gpt2_demo_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-gpt2_demo_pipeline_en.md
new file mode 100644
index 00000000000000..04b2236b6231b3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-gpt2_demo_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English gpt2_demo_pipeline pipeline GPT2Transformer from demo-leaderboard
+author: John Snow Labs
+name: gpt2_demo_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_demo_pipeline` is a English model originally trained by demo-leaderboard.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_demo_pipeline_en_5.5.1_3.0_1737911041588.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_demo_pipeline_en_5.5.1_3.0_1737911041588.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpt2_demo_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpt2_demo_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_demo_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/demo-leaderboard/gpt2-demo
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-gpt2_french_small_fr.md b/docs/_posts/ahmedlone127/2025-01-26-gpt2_french_small_fr.md
new file mode 100644
index 00000000000000..b77a1c902fb601
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-gpt2_french_small_fr.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: French gpt2_french_small GPT2Transformer from dbddv01
+author: John Snow Labs
+name: gpt2_french_small
+date: 2025-01-26
+tags: [fr, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: fr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_french_small` is a French model originally trained by dbddv01.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_french_small_fr_5.5.1_3.0_1737913961251.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_french_small_fr_5.5.1_3.0_1737913961251.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("gpt2_french_small","fr") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("gpt2_french_small","fr") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_french_small|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|fr|
+|Size:|467.9 MB|
+
+## References
+
+https://huggingface.co/dbddv01/gpt2-french-small
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-gpt2_french_small_pipeline_fr.md b/docs/_posts/ahmedlone127/2025-01-26-gpt2_french_small_pipeline_fr.md
new file mode 100644
index 00000000000000..40c857ec8c1c09
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-gpt2_french_small_pipeline_fr.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: French gpt2_french_small_pipeline pipeline GPT2Transformer from dbddv01
+author: John Snow Labs
+name: gpt2_french_small_pipeline
+date: 2025-01-26
+tags: [fr, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: fr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_french_small_pipeline` is a French model originally trained by dbddv01.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_french_small_pipeline_fr_5.5.1_3.0_1737913984974.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_french_small_pipeline_fr_5.5.1_3.0_1737913984974.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpt2_french_small_pipeline", lang = "fr")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpt2_french_small_pipeline", lang = "fr")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_french_small_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|fr|
+|Size:|467.9 MB|
+
+## References
+
+https://huggingface.co/dbddv01/gpt2-french-small
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-gpt2_medium_dutch_nl.md b/docs/_posts/ahmedlone127/2025-01-26-gpt2_medium_dutch_nl.md
new file mode 100644
index 00000000000000..306497515d3513
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-gpt2_medium_dutch_nl.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Dutch, Flemish gpt2_medium_dutch GPT2Transformer from yhavinga
+author: John Snow Labs
+name: gpt2_medium_dutch
+date: 2025-01-26
+tags: [nl, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: nl
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_medium_dutch` is a Dutch, Flemish model originally trained by yhavinga.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_medium_dutch_nl_5.5.1_3.0_1737867122415.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_medium_dutch_nl_5.5.1_3.0_1737867122415.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("gpt2_medium_dutch","nl") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("gpt2_medium_dutch","nl") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_medium_dutch|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|nl|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/yhavinga/gpt2-medium-dutch
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-gpt2_medium_dutch_pipeline_nl.md b/docs/_posts/ahmedlone127/2025-01-26-gpt2_medium_dutch_pipeline_nl.md
new file mode 100644
index 00000000000000..42eb96ff5a04d5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-gpt2_medium_dutch_pipeline_nl.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Dutch, Flemish gpt2_medium_dutch_pipeline pipeline GPT2Transformer from yhavinga
+author: John Snow Labs
+name: gpt2_medium_dutch_pipeline
+date: 2025-01-26
+tags: [nl, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: nl
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_medium_dutch_pipeline` is a Dutch, Flemish model originally trained by yhavinga.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_medium_dutch_pipeline_nl_5.5.1_3.0_1737867199836.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_medium_dutch_pipeline_nl_5.5.1_3.0_1737867199836.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpt2_medium_dutch_pipeline", lang = "nl")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpt2_medium_dutch_pipeline", lang = "nl")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_medium_dutch_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|nl|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/yhavinga/gpt2-medium-dutch
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-gpt2_small_spanish_es.md b/docs/_posts/ahmedlone127/2025-01-26-gpt2_small_spanish_es.md
new file mode 100644
index 00000000000000..094ef86342c30b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-gpt2_small_spanish_es.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Castilian, Spanish gpt2_small_spanish GPT2Transformer from datificate
+author: John Snow Labs
+name: gpt2_small_spanish
+date: 2025-01-26
+tags: [es, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: es
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_small_spanish` is a Castilian, Spanish model originally trained by datificate.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_small_spanish_es_5.5.1_3.0_1737913414420.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_small_spanish_es_5.5.1_3.0_1737913414420.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("gpt2_small_spanish","es") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("gpt2_small_spanish","es") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_small_spanish|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|es|
+|Size:|298.5 MB|
+
+## References
+
+https://huggingface.co/datificate/gpt2-small-spanish
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-gpt2_small_spanish_pipeline_es.md b/docs/_posts/ahmedlone127/2025-01-26-gpt2_small_spanish_pipeline_es.md
new file mode 100644
index 00000000000000..a88b4102656d43
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-gpt2_small_spanish_pipeline_es.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Castilian, Spanish gpt2_small_spanish_pipeline pipeline GPT2Transformer from datificate
+author: John Snow Labs
+name: gpt2_small_spanish_pipeline
+date: 2025-01-26
+tags: [es, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: es
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_small_spanish_pipeline` is a Castilian, Spanish model originally trained by datificate.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_small_spanish_pipeline_es_5.5.1_3.0_1737913498566.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_small_spanish_pipeline_es_5.5.1_3.0_1737913498566.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpt2_small_spanish_pipeline", lang = "es")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpt2_small_spanish_pipeline", lang = "es")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_small_spanish_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|es|
+|Size:|298.5 MB|
+
+## References
+
+https://huggingface.co/datificate/gpt2-small-spanish
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-gpt2_small_turkish_pipeline_tr.md b/docs/_posts/ahmedlone127/2025-01-26-gpt2_small_turkish_pipeline_tr.md
new file mode 100644
index 00000000000000..0eedbfdafd9be0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-gpt2_small_turkish_pipeline_tr.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Turkish gpt2_small_turkish_pipeline pipeline GPT2Transformer from gorkemgoknar
+author: John Snow Labs
+name: gpt2_small_turkish_pipeline
+date: 2025-01-26
+tags: [tr, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: tr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_small_turkish_pipeline` is a Turkish model originally trained by gorkemgoknar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_small_turkish_pipeline_tr_5.5.1_3.0_1737868691307.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_small_turkish_pipeline_tr_5.5.1_3.0_1737868691307.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpt2_small_turkish_pipeline", lang = "tr")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpt2_small_turkish_pipeline", lang = "tr")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_small_turkish_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|tr|
+|Size:|299.4 MB|
+
+## References
+
+https://huggingface.co/gorkemgoknar/gpt2-small-turkish
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-gpt2_small_turkish_tr.md b/docs/_posts/ahmedlone127/2025-01-26-gpt2_small_turkish_tr.md
new file mode 100644
index 00000000000000..d9304d86ed0cf6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-gpt2_small_turkish_tr.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Turkish gpt2_small_turkish GPT2Transformer from gorkemgoknar
+author: John Snow Labs
+name: gpt2_small_turkish
+date: 2025-01-26
+tags: [tr, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: tr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_small_turkish` is a Turkish model originally trained by gorkemgoknar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_small_turkish_tr_5.5.1_3.0_1737868602982.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_small_turkish_tr_5.5.1_3.0_1737868602982.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("gpt2_small_turkish","tr") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("gpt2_small_turkish","tr") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_small_turkish|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|tr|
+|Size:|299.4 MB|
+
+## References
+
+https://huggingface.co/gorkemgoknar/gpt2-small-turkish
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-gpt2_turkish_256_token_pipeline_tr.md b/docs/_posts/ahmedlone127/2025-01-26-gpt2_turkish_256_token_pipeline_tr.md
new file mode 100644
index 00000000000000..2141e484fd0913
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-gpt2_turkish_256_token_pipeline_tr.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Turkish gpt2_turkish_256_token_pipeline pipeline GPT2Transformer from cenkersisman
+author: John Snow Labs
+name: gpt2_turkish_256_token_pipeline
+date: 2025-01-26
+tags: [tr, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: tr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_turkish_256_token_pipeline` is a Turkish model originally trained by cenkersisman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_turkish_256_token_pipeline_tr_5.5.1_3.0_1737914004563.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_turkish_256_token_pipeline_tr_5.5.1_3.0_1737914004563.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpt2_turkish_256_token_pipeline", lang = "tr")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpt2_turkish_256_token_pipeline", lang = "tr")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_turkish_256_token_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|tr|
+|Size:|467.1 MB|
+
+## References
+
+https://huggingface.co/cenkersisman/gpt2-turkish-256-token
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-gpt2_turkish_256_token_tr.md b/docs/_posts/ahmedlone127/2025-01-26-gpt2_turkish_256_token_tr.md
new file mode 100644
index 00000000000000..a504ac5a8d6788
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-gpt2_turkish_256_token_tr.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Turkish gpt2_turkish_256_token GPT2Transformer from cenkersisman
+author: John Snow Labs
+name: gpt2_turkish_256_token
+date: 2025-01-26
+tags: [tr, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: tr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_turkish_256_token` is a Turkish model originally trained by cenkersisman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_turkish_256_token_tr_5.5.1_3.0_1737913980332.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_turkish_256_token_tr_5.5.1_3.0_1737913980332.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("gpt2_turkish_256_token","tr") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("gpt2_turkish_256_token","tr") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_turkish_256_token|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|tr|
+|Size:|467.1 MB|
+
+## References
+
+https://huggingface.co/cenkersisman/gpt2-turkish-256-token
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-gpt2_turkish_900m_pipeline_tr.md b/docs/_posts/ahmedlone127/2025-01-26-gpt2_turkish_900m_pipeline_tr.md
new file mode 100644
index 00000000000000..c178f349f49057
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-gpt2_turkish_900m_pipeline_tr.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Turkish gpt2_turkish_900m_pipeline pipeline GPT2Transformer from cenkersisman
+author: John Snow Labs
+name: gpt2_turkish_900m_pipeline
+date: 2025-01-26
+tags: [tr, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: tr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_turkish_900m_pipeline` is a Turkish model originally trained by cenkersisman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_turkish_900m_pipeline_tr_5.5.1_3.0_1737913373026.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_turkish_900m_pipeline_tr_5.5.1_3.0_1737913373026.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpt2_turkish_900m_pipeline", lang = "tr")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpt2_turkish_900m_pipeline", lang = "tr")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_turkish_900m_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|tr|
+|Size:|467.1 MB|
+
+## References
+
+https://huggingface.co/cenkersisman/gpt2-turkish-900m
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-gpt2_turkish_900m_tr.md b/docs/_posts/ahmedlone127/2025-01-26-gpt2_turkish_900m_tr.md
new file mode 100644
index 00000000000000..76d26e109f38fc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-gpt2_turkish_900m_tr.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Turkish gpt2_turkish_900m GPT2Transformer from cenkersisman
+author: John Snow Labs
+name: gpt2_turkish_900m
+date: 2025-01-26
+tags: [tr, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: tr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_turkish_900m` is a Turkish model originally trained by cenkersisman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_turkish_900m_tr_5.5.1_3.0_1737913349255.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_turkish_900m_tr_5.5.1_3.0_1737913349255.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("gpt2_turkish_900m","tr") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("gpt2_turkish_900m","tr") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_turkish_900m|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|tr|
+|Size:|467.1 MB|
+
+## References
+
+https://huggingface.co/cenkersisman/gpt2-turkish-900m
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-gpt2gptq_en.md b/docs/_posts/ahmedlone127/2025-01-26-gpt2gptq_en.md
new file mode 100644
index 00000000000000..d52ad867981d5e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-gpt2gptq_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English gpt2gptq GPT2Transformer from pavfi-at-m
+author: John Snow Labs
+name: gpt2gptq
+date: 2025-01-26
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2gptq` is a English model originally trained by pavfi-at-m.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2gptq_en_5.5.1_3.0_1737867365328.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2gptq_en_5.5.1_3.0_1737867365328.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("gpt2gptq","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("gpt2gptq","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2gptq|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|412.7 MB|
+
+## References
+
+https://huggingface.co/pavfi-at-m/gpt2GPTQ
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-gpt2gptq_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-gpt2gptq_pipeline_en.md
new file mode 100644
index 00000000000000..91229dd032430b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-gpt2gptq_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English gpt2gptq_pipeline pipeline GPT2Transformer from pavfi-at-m
+author: John Snow Labs
+name: gpt2gptq_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2gptq_pipeline` is a English model originally trained by pavfi-at-m.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2gptq_pipeline_en_5.5.1_3.0_1737867413462.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2gptq_pipeline_en_5.5.1_3.0_1737867413462.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpt2gptq_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpt2gptq_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2gptq_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|412.7 MB|
+
+## References
+
+https://huggingface.co/pavfi-at-m/gpt2GPTQ
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-gpt_prompt_expansion_fooocus_v2_en.md b/docs/_posts/ahmedlone127/2025-01-26-gpt_prompt_expansion_fooocus_v2_en.md
new file mode 100644
index 00000000000000..d19ec1f4edfc50
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-gpt_prompt_expansion_fooocus_v2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English gpt_prompt_expansion_fooocus_v2 GPT2Transformer from LykosAI
+author: John Snow Labs
+name: gpt_prompt_expansion_fooocus_v2
+date: 2025-01-26
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt_prompt_expansion_fooocus_v2` is a English model originally trained by LykosAI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt_prompt_expansion_fooocus_v2_en_5.5.1_3.0_1737868205179.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt_prompt_expansion_fooocus_v2_en_5.5.1_3.0_1737868205179.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("gpt_prompt_expansion_fooocus_v2","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("gpt_prompt_expansion_fooocus_v2","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt_prompt_expansion_fooocus_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|298.8 MB|
+
+## References
+
+https://huggingface.co/LykosAI/GPT-Prompt-Expansion-Fooocus-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-gpt_prompt_expansion_fooocus_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-gpt_prompt_expansion_fooocus_v2_pipeline_en.md
new file mode 100644
index 00000000000000..73504b67ce134d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-gpt_prompt_expansion_fooocus_v2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English gpt_prompt_expansion_fooocus_v2_pipeline pipeline GPT2Transformer from LykosAI
+author: John Snow Labs
+name: gpt_prompt_expansion_fooocus_v2_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt_prompt_expansion_fooocus_v2_pipeline` is a English model originally trained by LykosAI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt_prompt_expansion_fooocus_v2_pipeline_en_5.5.1_3.0_1737868294642.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt_prompt_expansion_fooocus_v2_pipeline_en_5.5.1_3.0_1737868294642.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpt_prompt_expansion_fooocus_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpt_prompt_expansion_fooocus_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt_prompt_expansion_fooocus_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|298.8 MB|
+
+## References
+
+https://huggingface.co/LykosAI/GPT-Prompt-Expansion-Fooocus-v2
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-gujarati_hatespeech_extension_pipeline_xx.md b/docs/_posts/ahmedlone127/2025-01-26-gujarati_hatespeech_extension_pipeline_xx.md
new file mode 100644
index 00000000000000..46e9811994bc29
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-gujarati_hatespeech_extension_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual gujarati_hatespeech_extension_pipeline pipeline XlmRoBertaForSequenceClassification from Jayveersinh-Raj
+author: John Snow Labs
+name: gujarati_hatespeech_extension_pipeline
+date: 2025-01-26
+tags: [xx, open_source, pipeline, onnx]
+task: Text Classification
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gujarati_hatespeech_extension_pipeline` is a Multilingual model originally trained by Jayveersinh-Raj.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gujarati_hatespeech_extension_pipeline_xx_5.5.1_3.0_1737883040227.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gujarati_hatespeech_extension_pipeline_xx_5.5.1_3.0_1737883040227.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gujarati_hatespeech_extension_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gujarati_hatespeech_extension_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gujarati_hatespeech_extension_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|860.9 MB|
+
+## References
+
+https://huggingface.co/Jayveersinh-Raj/Gujarati_hatespeech_extension
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-gujarati_hatespeech_extension_xx.md b/docs/_posts/ahmedlone127/2025-01-26-gujarati_hatespeech_extension_xx.md
new file mode 100644
index 00000000000000..d02e5a0b00dc58
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-gujarati_hatespeech_extension_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual gujarati_hatespeech_extension XlmRoBertaForSequenceClassification from Jayveersinh-Raj
+author: John Snow Labs
+name: gujarati_hatespeech_extension
+date: 2025-01-26
+tags: [xx, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gujarati_hatespeech_extension` is a Multilingual model originally trained by Jayveersinh-Raj.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gujarati_hatespeech_extension_xx_5.5.1_3.0_1737882956285.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gujarati_hatespeech_extension_xx_5.5.1_3.0_1737882956285.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("gujarati_hatespeech_extension","xx") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("gujarati_hatespeech_extension", "xx")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gujarati_hatespeech_extension|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|xx|
+|Size:|860.9 MB|
+
+## References
+
+https://huggingface.co/Jayveersinh-Raj/Gujarati_hatespeech_extension
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-hand_gestures_image_detection_en.md b/docs/_posts/ahmedlone127/2025-01-26-hand_gestures_image_detection_en.md
new file mode 100644
index 00000000000000..4372d671d75a7c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-hand_gestures_image_detection_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English hand_gestures_image_detection ViTForImageClassification from dima806
+author: John Snow Labs
+name: hand_gestures_image_detection
+date: 2025-01-26
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hand_gestures_image_detection` is a English model originally trained by dima806.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hand_gestures_image_detection_en_5.5.1_3.0_1737925928685.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hand_gestures_image_detection_en_5.5.1_3.0_1737925928685.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""hand_gestures_image_detection","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("hand_gestures_image_detection","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hand_gestures_image_detection|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.4 MB|
+
+## References
+
+https://huggingface.co/dima806/hand_gestures_image_detection
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-hand_gestures_image_detection_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-hand_gestures_image_detection_pipeline_en.md
new file mode 100644
index 00000000000000..d95a89384266e8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-hand_gestures_image_detection_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English hand_gestures_image_detection_pipeline pipeline ViTForImageClassification from dima806
+author: John Snow Labs
+name: hand_gestures_image_detection_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hand_gestures_image_detection_pipeline` is a English model originally trained by dima806.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hand_gestures_image_detection_pipeline_en_5.5.1_3.0_1737925946521.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hand_gestures_image_detection_pipeline_en_5.5.1_3.0_1737925946521.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("hand_gestures_image_detection_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hand_gestures_image_detection_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hand_gestures_image_detection_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.4 MB|
+
+## References
+
+https://huggingface.co/dima806/hand_gestures_image_detection
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-headache_misinformation_detect_en.md b/docs/_posts/ahmedlone127/2025-01-26-headache_misinformation_detect_en.md
new file mode 100644
index 00000000000000..b5b3459da21015
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-headache_misinformation_detect_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English headache_misinformation_detect DistilBertForSequenceClassification from PrachiPatel
+author: John Snow Labs
+name: headache_misinformation_detect
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`headache_misinformation_detect` is a English model originally trained by PrachiPatel.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/headache_misinformation_detect_en_5.5.1_3.0_1737928947035.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/headache_misinformation_detect_en_5.5.1_3.0_1737928947035.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("headache_misinformation_detect","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("headache_misinformation_detect", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|headache_misinformation_detect|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/PrachiPatel/Headache_misinformation_detect
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-headache_misinformation_detect_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-headache_misinformation_detect_pipeline_en.md
new file mode 100644
index 00000000000000..43132afd79ea44
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-headache_misinformation_detect_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English headache_misinformation_detect_pipeline pipeline DistilBertForSequenceClassification from PrachiPatel
+author: John Snow Labs
+name: headache_misinformation_detect_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`headache_misinformation_detect_pipeline` is a English model originally trained by PrachiPatel.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/headache_misinformation_detect_pipeline_en_5.5.1_3.0_1737928960375.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/headache_misinformation_detect_pipeline_en_5.5.1_3.0_1737928960375.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("headache_misinformation_detect_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("headache_misinformation_detect_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|headache_misinformation_detect_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/PrachiPatel/Headache_misinformation_detect
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-helping_agent_classification_en.md b/docs/_posts/ahmedlone127/2025-01-26-helping_agent_classification_en.md
new file mode 100644
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+---
+layout: model
+title: English helping_agent_classification DistilBertForSequenceClassification from Mr-Vicky-01
+author: John Snow Labs
+name: helping_agent_classification
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`helping_agent_classification` is a English model originally trained by Mr-Vicky-01.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/helping_agent_classification_en_5.5.1_3.0_1737929367614.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/helping_agent_classification_en_5.5.1_3.0_1737929367614.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("helping_agent_classification","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("helping_agent_classification", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|helping_agent_classification|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Mr-Vicky-01/helping_agent_classification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-helping_agent_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-helping_agent_classification_pipeline_en.md
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@@ -0,0 +1,70 @@
+---
+layout: model
+title: English helping_agent_classification_pipeline pipeline DistilBertForSequenceClassification from Mr-Vicky-01
+author: John Snow Labs
+name: helping_agent_classification_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`helping_agent_classification_pipeline` is a English model originally trained by Mr-Vicky-01.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/helping_agent_classification_pipeline_en_5.5.1_3.0_1737929381166.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/helping_agent_classification_pipeline_en_5.5.1_3.0_1737929381166.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("helping_agent_classification_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("helping_agent_classification_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|helping_agent_classification_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.6 MB|
+
+## References
+
+https://huggingface.co/Mr-Vicky-01/helping_agent_classification
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-hf_cvcourse_foodclassifier_en.md b/docs/_posts/ahmedlone127/2025-01-26-hf_cvcourse_foodclassifier_en.md
new file mode 100644
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--- /dev/null
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@@ -0,0 +1,94 @@
+---
+layout: model
+title: English hf_cvcourse_foodclassifier SwinForImageClassification from Moreza009
+author: John Snow Labs
+name: hf_cvcourse_foodclassifier
+date: 2025-01-26
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hf_cvcourse_foodclassifier` is a English model originally trained by Moreza009.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hf_cvcourse_foodclassifier_en_5.5.1_3.0_1737889462176.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hf_cvcourse_foodclassifier_en_5.5.1_3.0_1737889462176.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""hf_cvcourse_foodclassifier","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("hf_cvcourse_foodclassifier","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hf_cvcourse_foodclassifier|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.9 MB|
+
+## References
+
+https://huggingface.co/Moreza009/HF_CVcourse_FoodClassifier
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-hf_cvcourse_foodclassifier_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-hf_cvcourse_foodclassifier_pipeline_en.md
new file mode 100644
index 00000000000000..334979b1658fde
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-hf_cvcourse_foodclassifier_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English hf_cvcourse_foodclassifier_pipeline pipeline SwinForImageClassification from Moreza009
+author: John Snow Labs
+name: hf_cvcourse_foodclassifier_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hf_cvcourse_foodclassifier_pipeline` is a English model originally trained by Moreza009.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hf_cvcourse_foodclassifier_pipeline_en_5.5.1_3.0_1737889472752.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hf_cvcourse_foodclassifier_pipeline_en_5.5.1_3.0_1737889472752.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("hf_cvcourse_foodclassifier_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hf_cvcourse_foodclassifier_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hf_cvcourse_foodclassifier_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.9 MB|
+
+## References
+
+https://huggingface.co/Moreza009/HF_CVcourse_FoodClassifier
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-icebert_ic3_is.md b/docs/_posts/ahmedlone127/2025-01-26-icebert_ic3_is.md
new file mode 100644
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--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-icebert_ic3_is.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Icelandic icebert_ic3 RoBertaEmbeddings from mideind
+author: John Snow Labs
+name: icebert_ic3
+date: 2025-01-26
+tags: [is, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: is
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`icebert_ic3` is a Icelandic model originally trained by mideind.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/icebert_ic3_is_5.5.1_3.0_1737906192807.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/icebert_ic3_is_5.5.1_3.0_1737906192807.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("icebert_ic3","is") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("icebert_ic3","is") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|icebert_ic3|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|is|
+|Size:|297.1 MB|
+
+## References
+
+https://huggingface.co/mideind/IceBERT-ic3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-icebert_ic3_pipeline_is.md b/docs/_posts/ahmedlone127/2025-01-26-icebert_ic3_pipeline_is.md
new file mode 100644
index 00000000000000..b5e39d6d0937bd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-icebert_ic3_pipeline_is.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Icelandic icebert_ic3_pipeline pipeline RoBertaEmbeddings from mideind
+author: John Snow Labs
+name: icebert_ic3_pipeline
+date: 2025-01-26
+tags: [is, open_source, pipeline, onnx]
+task: Embeddings
+language: is
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`icebert_ic3_pipeline` is a Icelandic model originally trained by mideind.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/icebert_ic3_pipeline_is_5.5.1_3.0_1737906277908.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/icebert_ic3_pipeline_is_5.5.1_3.0_1737906277908.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("icebert_ic3_pipeline", lang = "is")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("icebert_ic3_pipeline", lang = "is")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|icebert_ic3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|is|
+|Size:|297.2 MB|
+
+## References
+
+https://huggingface.co/mideind/IceBERT-ic3
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-idt5_base_qaqg_v3_en.md b/docs/_posts/ahmedlone127/2025-01-26-idt5_base_qaqg_v3_en.md
new file mode 100644
index 00000000000000..17398785212cd1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-idt5_base_qaqg_v3_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English idt5_base_qaqg_v3 T5Transformer from hawalurahman
+author: John Snow Labs
+name: idt5_base_qaqg_v3
+date: 2025-01-26
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`idt5_base_qaqg_v3` is a English model originally trained by hawalurahman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/idt5_base_qaqg_v3_en_5.5.1_3.0_1737851736052.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/idt5_base_qaqg_v3_en_5.5.1_3.0_1737851736052.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("idt5_base_qaqg_v3","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("idt5_base_qaqg_v3", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|idt5_base_qaqg_v3|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|986.9 MB|
+
+## References
+
+https://huggingface.co/hawalurahman/idt5-base-qaqg_v3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-idt5_base_qaqg_v3_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-idt5_base_qaqg_v3_pipeline_en.md
new file mode 100644
index 00000000000000..37671a5b9401a2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-idt5_base_qaqg_v3_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English idt5_base_qaqg_v3_pipeline pipeline T5Transformer from hawalurahman
+author: John Snow Labs
+name: idt5_base_qaqg_v3_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`idt5_base_qaqg_v3_pipeline` is a English model originally trained by hawalurahman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/idt5_base_qaqg_v3_pipeline_en_5.5.1_3.0_1737851786253.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/idt5_base_qaqg_v3_pipeline_en_5.5.1_3.0_1737851786253.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("idt5_base_qaqg_v3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("idt5_base_qaqg_v3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|idt5_base_qaqg_v3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|986.9 MB|
+
+## References
+
+https://huggingface.co/hawalurahman/idt5-base-qaqg_v3
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-ifoodie_menu_v3_1_en.md b/docs/_posts/ahmedlone127/2025-01-26-ifoodie_menu_v3_1_en.md
new file mode 100644
index 00000000000000..29bd7160e39769
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-ifoodie_menu_v3_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ifoodie_menu_v3_1 SwinForImageClassification from sainteye
+author: John Snow Labs
+name: ifoodie_menu_v3_1
+date: 2025-01-26
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ifoodie_menu_v3_1` is a English model originally trained by sainteye.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ifoodie_menu_v3_1_en_5.5.1_3.0_1737888954746.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ifoodie_menu_v3_1_en_5.5.1_3.0_1737888954746.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""ifoodie_menu_v3_1","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("ifoodie_menu_v3_1","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ifoodie_menu_v3_1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/sainteye/ifoodie-menu-v3.1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-ifoodie_menu_v3_1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-ifoodie_menu_v3_1_pipeline_en.md
new file mode 100644
index 00000000000000..8049166eb093a2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-ifoodie_menu_v3_1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English ifoodie_menu_v3_1_pipeline pipeline SwinForImageClassification from sainteye
+author: John Snow Labs
+name: ifoodie_menu_v3_1_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ifoodie_menu_v3_1_pipeline` is a English model originally trained by sainteye.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ifoodie_menu_v3_1_pipeline_en_5.5.1_3.0_1737888967979.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ifoodie_menu_v3_1_pipeline_en_5.5.1_3.0_1737888967979.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ifoodie_menu_v3_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ifoodie_menu_v3_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ifoodie_menu_v3_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/sainteye/ifoodie-menu-v3.1
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-incel_mbert_en.md b/docs/_posts/ahmedlone127/2025-01-26-incel_mbert_en.md
new file mode 100644
index 00000000000000..df0a31a2a92686
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-incel_mbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English incel_mbert BertEmbeddings from pgajo
+author: John Snow Labs
+name: incel_mbert
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`incel_mbert` is a English model originally trained by pgajo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/incel_mbert_en_5.5.1_3.0_1737862148722.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/incel_mbert_en_5.5.1_3.0_1737862148722.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("incel_mbert","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("incel_mbert","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|incel_mbert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/pgajo/incel-mbert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-incel_mbert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-incel_mbert_pipeline_en.md
new file mode 100644
index 00000000000000..ad8e67e5150e43
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-incel_mbert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English incel_mbert_pipeline pipeline BertEmbeddings from pgajo
+author: John Snow Labs
+name: incel_mbert_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`incel_mbert_pipeline` is a English model originally trained by pgajo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/incel_mbert_pipeline_en_5.5.1_3.0_1737862181467.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/incel_mbert_pipeline_en_5.5.1_3.0_1737862181467.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("incel_mbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("incel_mbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|incel_mbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/pgajo/incel-mbert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-indo_sentiment_indobertweet_almaran_en.md b/docs/_posts/ahmedlone127/2025-01-26-indo_sentiment_indobertweet_almaran_en.md
new file mode 100644
index 00000000000000..ffd5d099bdac21
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-indo_sentiment_indobertweet_almaran_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English indo_sentiment_indobertweet_almaran BertForSequenceClassification from almaran
+author: John Snow Labs
+name: indo_sentiment_indobertweet_almaran
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indo_sentiment_indobertweet_almaran` is a English model originally trained by almaran.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indo_sentiment_indobertweet_almaran_en_5.5.1_3.0_1737921006458.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indo_sentiment_indobertweet_almaran_en_5.5.1_3.0_1737921006458.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("indo_sentiment_indobertweet_almaran","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("indo_sentiment_indobertweet_almaran", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|indo_sentiment_indobertweet_almaran|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|414.0 MB|
+
+## References
+
+https://huggingface.co/almaran/indo_sentiment_indobertweet
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-indo_sentiment_indobertweet_almaran_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-indo_sentiment_indobertweet_almaran_pipeline_en.md
new file mode 100644
index 00000000000000..f6ed7a92f13cfe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-indo_sentiment_indobertweet_almaran_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English indo_sentiment_indobertweet_almaran_pipeline pipeline BertForSequenceClassification from almaran
+author: John Snow Labs
+name: indo_sentiment_indobertweet_almaran_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indo_sentiment_indobertweet_almaran_pipeline` is a English model originally trained by almaran.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indo_sentiment_indobertweet_almaran_pipeline_en_5.5.1_3.0_1737921027999.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indo_sentiment_indobertweet_almaran_pipeline_en_5.5.1_3.0_1737921027999.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("indo_sentiment_indobertweet_almaran_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("indo_sentiment_indobertweet_almaran_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|indo_sentiment_indobertweet_almaran_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|414.1 MB|
+
+## References
+
+https://huggingface.co/almaran/indo_sentiment_indobertweet
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-indobert_large_p2_finetuned_sayula_popoluca_id.md b/docs/_posts/ahmedlone127/2025-01-26-indobert_large_p2_finetuned_sayula_popoluca_id.md
new file mode 100644
index 00000000000000..cdef10cf646a08
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-indobert_large_p2_finetuned_sayula_popoluca_id.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Indonesian indobert_large_p2_finetuned_sayula_popoluca BertForTokenClassification from ageng-anugrah
+author: John Snow Labs
+name: indobert_large_p2_finetuned_sayula_popoluca
+date: 2025-01-26
+tags: [id, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: id
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indobert_large_p2_finetuned_sayula_popoluca` is a Indonesian model originally trained by ageng-anugrah.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indobert_large_p2_finetuned_sayula_popoluca_id_5.5.1_3.0_1737934240877.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indobert_large_p2_finetuned_sayula_popoluca_id_5.5.1_3.0_1737934240877.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("indobert_large_p2_finetuned_sayula_popoluca","id") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("indobert_large_p2_finetuned_sayula_popoluca", "id")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|indobert_large_p2_finetuned_sayula_popoluca|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|id|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/ageng-anugrah/indobert-large-p2-finetuned-pos
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-indobert_large_p2_finetuned_sayula_popoluca_pipeline_id.md b/docs/_posts/ahmedlone127/2025-01-26-indobert_large_p2_finetuned_sayula_popoluca_pipeline_id.md
new file mode 100644
index 00000000000000..5caa864376ae45
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-indobert_large_p2_finetuned_sayula_popoluca_pipeline_id.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Indonesian indobert_large_p2_finetuned_sayula_popoluca_pipeline pipeline BertForTokenClassification from ageng-anugrah
+author: John Snow Labs
+name: indobert_large_p2_finetuned_sayula_popoluca_pipeline
+date: 2025-01-26
+tags: [id, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: id
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indobert_large_p2_finetuned_sayula_popoluca_pipeline` is a Indonesian model originally trained by ageng-anugrah.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indobert_large_p2_finetuned_sayula_popoluca_pipeline_id_5.5.1_3.0_1737934303921.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indobert_large_p2_finetuned_sayula_popoluca_pipeline_id_5.5.1_3.0_1737934303921.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("indobert_large_p2_finetuned_sayula_popoluca_pipeline", lang = "id")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("indobert_large_p2_finetuned_sayula_popoluca_pipeline", lang = "id")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|indobert_large_p2_finetuned_sayula_popoluca_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|id|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/ageng-anugrah/indobert-large-p2-finetuned-pos
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-indonesian_extractive_bert_squad_en.md b/docs/_posts/ahmedlone127/2025-01-26-indonesian_extractive_bert_squad_en.md
new file mode 100644
index 00000000000000..c44a50080fd2e4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-indonesian_extractive_bert_squad_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English indonesian_extractive_bert_squad BertForQuestionAnswering from bstds
+author: John Snow Labs
+name: indonesian_extractive_bert_squad
+date: 2025-01-26
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indonesian_extractive_bert_squad` is a English model originally trained by bstds.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indonesian_extractive_bert_squad_en_5.5.1_3.0_1737918425856.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indonesian_extractive_bert_squad_en_5.5.1_3.0_1737918425856.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("indonesian_extractive_bert_squad","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("indonesian_extractive_bert_squad", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|indonesian_extractive_bert_squad|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|411.7 MB|
+
+## References
+
+https://huggingface.co/bstds/id-extractive-bert-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-indonesian_extractive_bert_squad_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-indonesian_extractive_bert_squad_pipeline_en.md
new file mode 100644
index 00000000000000..0392f23164a6df
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-indonesian_extractive_bert_squad_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English indonesian_extractive_bert_squad_pipeline pipeline BertForQuestionAnswering from bstds
+author: John Snow Labs
+name: indonesian_extractive_bert_squad_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indonesian_extractive_bert_squad_pipeline` is a English model originally trained by bstds.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indonesian_extractive_bert_squad_pipeline_en_5.5.1_3.0_1737918447158.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indonesian_extractive_bert_squad_pipeline_en_5.5.1_3.0_1737918447158.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("indonesian_extractive_bert_squad_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("indonesian_extractive_bert_squad_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|indonesian_extractive_bert_squad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|411.7 MB|
+
+## References
+
+https://huggingface.co/bstds/id-extractive-bert-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-inisw08_robert_mlm_sgd_en.md b/docs/_posts/ahmedlone127/2025-01-26-inisw08_robert_mlm_sgd_en.md
new file mode 100644
index 00000000000000..aba8aa86118aea
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-inisw08_robert_mlm_sgd_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English inisw08_robert_mlm_sgd RoBertaEmbeddings from ugiugi
+author: John Snow Labs
+name: inisw08_robert_mlm_sgd
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`inisw08_robert_mlm_sgd` is a English model originally trained by ugiugi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/inisw08_robert_mlm_sgd_en_5.5.1_3.0_1737866283997.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/inisw08_robert_mlm_sgd_en_5.5.1_3.0_1737866283997.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("inisw08_robert_mlm_sgd","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("inisw08_robert_mlm_sgd","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|inisw08_robert_mlm_sgd|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|433.3 MB|
+
+## References
+
+https://huggingface.co/ugiugi/inisw08-RoBERT-mlm-sgd
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-inisw08_robert_mlm_sgd_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-inisw08_robert_mlm_sgd_pipeline_en.md
new file mode 100644
index 00000000000000..b2152fdb2048a0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-inisw08_robert_mlm_sgd_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English inisw08_robert_mlm_sgd_pipeline pipeline RoBertaEmbeddings from ugiugi
+author: John Snow Labs
+name: inisw08_robert_mlm_sgd_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`inisw08_robert_mlm_sgd_pipeline` is a English model originally trained by ugiugi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/inisw08_robert_mlm_sgd_pipeline_en_5.5.1_3.0_1737866339844.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/inisw08_robert_mlm_sgd_pipeline_en_5.5.1_3.0_1737866339844.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("inisw08_robert_mlm_sgd_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("inisw08_robert_mlm_sgd_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|inisw08_robert_mlm_sgd_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|433.3 MB|
+
+## References
+
+https://huggingface.co/ugiugi/inisw08-RoBERT-mlm-sgd
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-kidlm_en.md b/docs/_posts/ahmedlone127/2025-01-26-kidlm_en.md
new file mode 100644
index 00000000000000..00a5022044ba55
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-kidlm_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English kidlm RoBertaEmbeddings from tafseer-nayeem
+author: John Snow Labs
+name: kidlm
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kidlm` is a English model originally trained by tafseer-nayeem.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kidlm_en_5.5.1_3.0_1737865386467.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kidlm_en_5.5.1_3.0_1737865386467.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("kidlm","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("kidlm","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|kidlm|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|465.5 MB|
+
+## References
+
+https://huggingface.co/tafseer-nayeem/KidLM
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-kidlm_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-kidlm_pipeline_en.md
new file mode 100644
index 00000000000000..45ebc4db46e76b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-kidlm_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English kidlm_pipeline pipeline RoBertaEmbeddings from tafseer-nayeem
+author: John Snow Labs
+name: kidlm_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kidlm_pipeline` is a English model originally trained by tafseer-nayeem.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kidlm_pipeline_en_5.5.1_3.0_1737865410850.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kidlm_pipeline_en_5.5.1_3.0_1737865410850.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("kidlm_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("kidlm_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|kidlm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|465.5 MB|
+
+## References
+
+https://huggingface.co/tafseer-nayeem/KidLM
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-kidlm_plus_en.md b/docs/_posts/ahmedlone127/2025-01-26-kidlm_plus_en.md
new file mode 100644
index 00000000000000..7ed83560641916
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-kidlm_plus_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English kidlm_plus RoBertaEmbeddings from tafseer-nayeem
+author: John Snow Labs
+name: kidlm_plus
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kidlm_plus` is a English model originally trained by tafseer-nayeem.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kidlm_plus_en_5.5.1_3.0_1737906917266.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kidlm_plus_en_5.5.1_3.0_1737906917266.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("kidlm_plus","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("kidlm_plus","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|kidlm_plus|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|465.5 MB|
+
+## References
+
+https://huggingface.co/tafseer-nayeem/KidLM-plus
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-kidlm_plus_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-kidlm_plus_pipeline_en.md
new file mode 100644
index 00000000000000..8175f3ba1ae235
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-kidlm_plus_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English kidlm_plus_pipeline pipeline RoBertaEmbeddings from tafseer-nayeem
+author: John Snow Labs
+name: kidlm_plus_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kidlm_plus_pipeline` is a English model originally trained by tafseer-nayeem.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kidlm_plus_pipeline_en_5.5.1_3.0_1737906941332.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kidlm_plus_pipeline_en_5.5.1_3.0_1737906941332.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("kidlm_plus_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("kidlm_plus_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|kidlm_plus_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|465.5 MB|
+
+## References
+
+https://huggingface.co/tafseer-nayeem/KidLM-plus
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-klue_mrc_bert_hjh_test001_en.md b/docs/_posts/ahmedlone127/2025-01-26-klue_mrc_bert_hjh_test001_en.md
new file mode 100644
index 00000000000000..683b12f74154d7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-klue_mrc_bert_hjh_test001_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English klue_mrc_bert_hjh_test001 BertForQuestionAnswering from cooler8
+author: John Snow Labs
+name: klue_mrc_bert_hjh_test001
+date: 2025-01-26
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`klue_mrc_bert_hjh_test001` is a English model originally trained by cooler8.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/klue_mrc_bert_hjh_test001_en_5.5.1_3.0_1737918781590.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/klue_mrc_bert_hjh_test001_en_5.5.1_3.0_1737918781590.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("klue_mrc_bert_hjh_test001","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("klue_mrc_bert_hjh_test001", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|klue_mrc_bert_hjh_test001|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|412.4 MB|
+
+## References
+
+https://huggingface.co/cooler8/klue-mrc-bert-hjh-test001
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-klue_mrc_bert_hjh_test001_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-klue_mrc_bert_hjh_test001_pipeline_en.md
new file mode 100644
index 00000000000000..c67608a38a36a9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-klue_mrc_bert_hjh_test001_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English klue_mrc_bert_hjh_test001_pipeline pipeline BertForQuestionAnswering from cooler8
+author: John Snow Labs
+name: klue_mrc_bert_hjh_test001_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`klue_mrc_bert_hjh_test001_pipeline` is a English model originally trained by cooler8.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/klue_mrc_bert_hjh_test001_pipeline_en_5.5.1_3.0_1737918803178.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/klue_mrc_bert_hjh_test001_pipeline_en_5.5.1_3.0_1737918803178.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("klue_mrc_bert_hjh_test001_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("klue_mrc_bert_hjh_test001_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|klue_mrc_bert_hjh_test001_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|412.4 MB|
+
+## References
+
+https://huggingface.co/cooler8/klue-mrc-bert-hjh-test001
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-latin_italian_translatorv6_en.md b/docs/_posts/ahmedlone127/2025-01-26-latin_italian_translatorv6_en.md
new file mode 100644
index 00000000000000..7f742f86ee597b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-latin_italian_translatorv6_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English latin_italian_translatorv6 MarianTransformer from Dddixyy
+author: John Snow Labs
+name: latin_italian_translatorv6
+date: 2025-01-26
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`latin_italian_translatorv6` is a English model originally trained by Dddixyy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/latin_italian_translatorv6_en_5.5.1_3.0_1737863263150.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/latin_italian_translatorv6_en_5.5.1_3.0_1737863263150.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("latin_italian_translatorv6","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("latin_italian_translatorv6","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|latin_italian_translatorv6|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|475.7 MB|
+
+## References
+
+https://huggingface.co/Dddixyy/latin-italian-translatorV6
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-latin_italian_translatorv6_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-latin_italian_translatorv6_pipeline_en.md
new file mode 100644
index 00000000000000..8d4b823bedd738
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-latin_italian_translatorv6_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English latin_italian_translatorv6_pipeline pipeline MarianTransformer from Dddixyy
+author: John Snow Labs
+name: latin_italian_translatorv6_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`latin_italian_translatorv6_pipeline` is a English model originally trained by Dddixyy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/latin_italian_translatorv6_pipeline_en_5.5.1_3.0_1737863287698.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/latin_italian_translatorv6_pipeline_en_5.5.1_3.0_1737863287698.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("latin_italian_translatorv6_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("latin_italian_translatorv6_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|latin_italian_translatorv6_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|476.3 MB|
+
+## References
+
+https://huggingface.co/Dddixyy/latin-italian-translatorV6
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-learning_path_t5_model_en.md b/docs/_posts/ahmedlone127/2025-01-26-learning_path_t5_model_en.md
new file mode 100644
index 00000000000000..dd800ad6932d79
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-learning_path_t5_model_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English learning_path_t5_model T5Transformer from pranayvadla17
+author: John Snow Labs
+name: learning_path_t5_model
+date: 2025-01-26
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`learning_path_t5_model` is a English model originally trained by pranayvadla17.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/learning_path_t5_model_en_5.5.1_3.0_1737849709206.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/learning_path_t5_model_en_5.5.1_3.0_1737849709206.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("learning_path_t5_model","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("learning_path_t5_model", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|learning_path_t5_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|894.3 MB|
+
+## References
+
+https://huggingface.co/pranayvadla17/learning_path_t5_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-learning_path_t5_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-learning_path_t5_model_pipeline_en.md
new file mode 100644
index 00000000000000..91679e0de23128
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-learning_path_t5_model_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English learning_path_t5_model_pipeline pipeline T5Transformer from pranayvadla17
+author: John Snow Labs
+name: learning_path_t5_model_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`learning_path_t5_model_pipeline` is a English model originally trained by pranayvadla17.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/learning_path_t5_model_pipeline_en_5.5.1_3.0_1737849758512.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/learning_path_t5_model_pipeline_en_5.5.1_3.0_1737849758512.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("learning_path_t5_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("learning_path_t5_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|learning_path_t5_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|894.3 MB|
+
+## References
+
+https://huggingface.co/pranayvadla17/learning_path_t5_model
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-len_pruned_90_model_en.md b/docs/_posts/ahmedlone127/2025-01-26-len_pruned_90_model_en.md
new file mode 100644
index 00000000000000..41d1ffb091c17f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-len_pruned_90_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English len_pruned_90_model DistilBertForSequenceClassification from andygoh5
+author: John Snow Labs
+name: len_pruned_90_model
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`len_pruned_90_model` is a English model originally trained by andygoh5.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/len_pruned_90_model_en_5.5.1_3.0_1737928795964.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/len_pruned_90_model_en_5.5.1_3.0_1737928795964.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("len_pruned_90_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("len_pruned_90_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|len_pruned_90_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/andygoh5/len-pruned-90-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-len_pruned_90_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-len_pruned_90_model_pipeline_en.md
new file mode 100644
index 00000000000000..bc8a02daebdea6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-len_pruned_90_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English len_pruned_90_model_pipeline pipeline DistilBertForSequenceClassification from andygoh5
+author: John Snow Labs
+name: len_pruned_90_model_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`len_pruned_90_model_pipeline` is a English model originally trained by andygoh5.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/len_pruned_90_model_pipeline_en_5.5.1_3.0_1737928809785.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/len_pruned_90_model_pipeline_en_5.5.1_3.0_1737928809785.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("len_pruned_90_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("len_pruned_90_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|len_pruned_90_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/andygoh5/len-pruned-90-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-llm_data_2_base_run2_1000_en.md b/docs/_posts/ahmedlone127/2025-01-26-llm_data_2_base_run2_1000_en.md
new file mode 100644
index 00000000000000..e2236808c864e5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-llm_data_2_base_run2_1000_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English llm_data_2_base_run2_1000 XlmRoBertaForSequenceClassification from sreddy109
+author: John Snow Labs
+name: llm_data_2_base_run2_1000
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`llm_data_2_base_run2_1000` is a English model originally trained by sreddy109.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/llm_data_2_base_run2_1000_en_5.5.1_3.0_1737880956507.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/llm_data_2_base_run2_1000_en_5.5.1_3.0_1737880956507.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("llm_data_2_base_run2_1000","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("llm_data_2_base_run2_1000", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|llm_data_2_base_run2_1000|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|994.0 MB|
+
+## References
+
+https://huggingface.co/sreddy109/llm-data-2-base-run2-1000
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-llm_data_2_base_run2_1000_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-llm_data_2_base_run2_1000_pipeline_en.md
new file mode 100644
index 00000000000000..b2bf55f342bcc6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-llm_data_2_base_run2_1000_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English llm_data_2_base_run2_1000_pipeline pipeline XlmRoBertaForSequenceClassification from sreddy109
+author: John Snow Labs
+name: llm_data_2_base_run2_1000_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`llm_data_2_base_run2_1000_pipeline` is a English model originally trained by sreddy109.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/llm_data_2_base_run2_1000_pipeline_en_5.5.1_3.0_1737881014595.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/llm_data_2_base_run2_1000_pipeline_en_5.5.1_3.0_1737881014595.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("llm_data_2_base_run2_1000_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("llm_data_2_base_run2_1000_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|llm_data_2_base_run2_1000_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|994.0 MB|
+
+## References
+
+https://huggingface.co/sreddy109/llm-data-2-base-run2-1000
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-llm_data_2_base_run2_100_en.md b/docs/_posts/ahmedlone127/2025-01-26-llm_data_2_base_run2_100_en.md
new file mode 100644
index 00000000000000..93b05f29b950ad
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-llm_data_2_base_run2_100_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English llm_data_2_base_run2_100 XlmRoBertaForSequenceClassification from sreddy109
+author: John Snow Labs
+name: llm_data_2_base_run2_100
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`llm_data_2_base_run2_100` is a English model originally trained by sreddy109.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/llm_data_2_base_run2_100_en_5.5.1_3.0_1737886151266.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/llm_data_2_base_run2_100_en_5.5.1_3.0_1737886151266.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("llm_data_2_base_run2_100","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("llm_data_2_base_run2_100", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|llm_data_2_base_run2_100|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|993.9 MB|
+
+## References
+
+https://huggingface.co/sreddy109/llm-data-2-base-run2-100
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-llm_data_2_base_run2_100_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-llm_data_2_base_run2_100_pipeline_en.md
new file mode 100644
index 00000000000000..7fcf9cf4a445f0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-llm_data_2_base_run2_100_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English llm_data_2_base_run2_100_pipeline pipeline XlmRoBertaForSequenceClassification from sreddy109
+author: John Snow Labs
+name: llm_data_2_base_run2_100_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`llm_data_2_base_run2_100_pipeline` is a English model originally trained by sreddy109.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/llm_data_2_base_run2_100_pipeline_en_5.5.1_3.0_1737886206804.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/llm_data_2_base_run2_100_pipeline_en_5.5.1_3.0_1737886206804.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("llm_data_2_base_run2_100_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("llm_data_2_base_run2_100_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|llm_data_2_base_run2_100_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|994.0 MB|
+
+## References
+
+https://huggingface.co/sreddy109/llm-data-2-base-run2-100
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-llmparser_flan_en.md b/docs/_posts/ahmedlone127/2025-01-26-llmparser_flan_en.md
new file mode 100644
index 00000000000000..830f4cbc1d59a9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-llmparser_flan_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English llmparser_flan T5Transformer from oussamachaouki
+author: John Snow Labs
+name: llmparser_flan
+date: 2025-01-26
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`llmparser_flan` is a English model originally trained by oussamachaouki.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/llmparser_flan_en_5.5.1_3.0_1737851086688.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/llmparser_flan_en_5.5.1_3.0_1737851086688.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("llmparser_flan","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("llmparser_flan", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|llmparser_flan|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/oussamachaouki/LLMParser_Flan
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-llmparser_flan_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-llmparser_flan_pipeline_en.md
new file mode 100644
index 00000000000000..225dca9f4519e1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-llmparser_flan_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English llmparser_flan_pipeline pipeline T5Transformer from oussamachaouki
+author: John Snow Labs
+name: llmparser_flan_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`llmparser_flan_pipeline` is a English model originally trained by oussamachaouki.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/llmparser_flan_pipeline_en_5.5.1_3.0_1737851143322.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/llmparser_flan_pipeline_en_5.5.1_3.0_1737851143322.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("llmparser_flan_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("llmparser_flan_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|llmparser_flan_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/oussamachaouki/LLMParser_Flan
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-malayalam_document_classification_en.md b/docs/_posts/ahmedlone127/2025-01-26-malayalam_document_classification_en.md
new file mode 100644
index 00000000000000..681c524f0a7f22
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-malayalam_document_classification_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English malayalam_document_classification DistilBertForSequenceClassification from Bigheadjoshy
+author: John Snow Labs
+name: malayalam_document_classification
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`malayalam_document_classification` is a English model originally trained by Bigheadjoshy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/malayalam_document_classification_en_5.5.1_3.0_1737904915367.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/malayalam_document_classification_en_5.5.1_3.0_1737904915367.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("malayalam_document_classification","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("malayalam_document_classification", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|malayalam_document_classification|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.7 MB|
+
+## References
+
+https://huggingface.co/Bigheadjoshy/ml_document_classification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-malayalam_document_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-malayalam_document_classification_pipeline_en.md
new file mode 100644
index 00000000000000..94e6e2cef8adc5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-malayalam_document_classification_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English malayalam_document_classification_pipeline pipeline DistilBertForSequenceClassification from Bigheadjoshy
+author: John Snow Labs
+name: malayalam_document_classification_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`malayalam_document_classification_pipeline` is a English model originally trained by Bigheadjoshy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/malayalam_document_classification_pipeline_en_5.5.1_3.0_1737904928436.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/malayalam_document_classification_pipeline_en_5.5.1_3.0_1737904928436.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("malayalam_document_classification_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("malayalam_document_classification_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|malayalam_document_classification_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.8 MB|
+
+## References
+
+https://huggingface.co/Bigheadjoshy/ml_document_classification
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-marianmt_nepali_tonga_tonga_islands_english_en.md b/docs/_posts/ahmedlone127/2025-01-26-marianmt_nepali_tonga_tonga_islands_english_en.md
new file mode 100644
index 00000000000000..00ce58b750f89e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-marianmt_nepali_tonga_tonga_islands_english_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English marianmt_nepali_tonga_tonga_islands_english MarianTransformer from iamTangsang
+author: John Snow Labs
+name: marianmt_nepali_tonga_tonga_islands_english
+date: 2025-01-26
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marianmt_nepali_tonga_tonga_islands_english` is a English model originally trained by iamTangsang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marianmt_nepali_tonga_tonga_islands_english_en_5.5.1_3.0_1737863731930.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marianmt_nepali_tonga_tonga_islands_english_en_5.5.1_3.0_1737863731930.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("marianmt_nepali_tonga_tonga_islands_english","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("marianmt_nepali_tonga_tonga_islands_english","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marianmt_nepali_tonga_tonga_islands_english|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|414.6 MB|
+
+## References
+
+https://huggingface.co/iamTangsang/MarianMT-Nepali-to-English
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-marianmt_nepali_tonga_tonga_islands_english_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-marianmt_nepali_tonga_tonga_islands_english_pipeline_en.md
new file mode 100644
index 00000000000000..ab3f4249bcd2ba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-marianmt_nepali_tonga_tonga_islands_english_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English marianmt_nepali_tonga_tonga_islands_english_pipeline pipeline MarianTransformer from iamTangsang
+author: John Snow Labs
+name: marianmt_nepali_tonga_tonga_islands_english_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marianmt_nepali_tonga_tonga_islands_english_pipeline` is a English model originally trained by iamTangsang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marianmt_nepali_tonga_tonga_islands_english_pipeline_en_5.5.1_3.0_1737863753850.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marianmt_nepali_tonga_tonga_islands_english_pipeline_en_5.5.1_3.0_1737863753850.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("marianmt_nepali_tonga_tonga_islands_english_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("marianmt_nepali_tonga_tonga_islands_english_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marianmt_nepali_tonga_tonga_islands_english_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|415.1 MB|
+
+## References
+
+https://huggingface.co/iamTangsang/MarianMT-Nepali-to-English
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-mbert_bengali_qa_squad_bengali_finetuned_en.md b/docs/_posts/ahmedlone127/2025-01-26-mbert_bengali_qa_squad_bengali_finetuned_en.md
new file mode 100644
index 00000000000000..691efde32f1098
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-mbert_bengali_qa_squad_bengali_finetuned_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mbert_bengali_qa_squad_bengali_finetuned BertForQuestionAnswering from AsifAbrar6
+author: John Snow Labs
+name: mbert_bengali_qa_squad_bengali_finetuned
+date: 2025-01-26
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mbert_bengali_qa_squad_bengali_finetuned` is a English model originally trained by AsifAbrar6.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mbert_bengali_qa_squad_bengali_finetuned_en_5.5.1_3.0_1737918729018.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mbert_bengali_qa_squad_bengali_finetuned_en_5.5.1_3.0_1737918729018.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("mbert_bengali_qa_squad_bengali_finetuned","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("mbert_bengali_qa_squad_bengali_finetuned", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mbert_bengali_qa_squad_bengali_finetuned|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|625.5 MB|
+
+## References
+
+https://huggingface.co/AsifAbrar6/mbert-bengali-qa-squad_bn-finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-mbert_bengali_qa_squad_bengali_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-mbert_bengali_qa_squad_bengali_finetuned_pipeline_en.md
new file mode 100644
index 00000000000000..49533012ea09a8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-mbert_bengali_qa_squad_bengali_finetuned_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mbert_bengali_qa_squad_bengali_finetuned_pipeline pipeline BertForQuestionAnswering from AsifAbrar6
+author: John Snow Labs
+name: mbert_bengali_qa_squad_bengali_finetuned_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mbert_bengali_qa_squad_bengali_finetuned_pipeline` is a English model originally trained by AsifAbrar6.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mbert_bengali_qa_squad_bengali_finetuned_pipeline_en_5.5.1_3.0_1737918761767.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mbert_bengali_qa_squad_bengali_finetuned_pipeline_en_5.5.1_3.0_1737918761767.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mbert_bengali_qa_squad_bengali_finetuned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mbert_bengali_qa_squad_bengali_finetuned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mbert_bengali_qa_squad_bengali_finetuned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|625.5 MB|
+
+## References
+
+https://huggingface.co/AsifAbrar6/mbert-bengali-qa-squad_bn-finetuned
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-mbert_kmeans_0_05_mmarco_l_all_english_s_all_30k_distill_test_mt5_base_mmarco_v2_30k_en.md b/docs/_posts/ahmedlone127/2025-01-26-mbert_kmeans_0_05_mmarco_l_all_english_s_all_30k_distill_test_mt5_base_mmarco_v2_30k_en.md
new file mode 100644
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--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-mbert_kmeans_0_05_mmarco_l_all_english_s_all_30k_distill_test_mt5_base_mmarco_v2_30k_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mbert_kmeans_0_05_mmarco_l_all_english_s_all_30k_distill_test_mt5_base_mmarco_v2_30k BertEmbeddings from spear-model
+author: John Snow Labs
+name: mbert_kmeans_0_05_mmarco_l_all_english_s_all_30k_distill_test_mt5_base_mmarco_v2_30k
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mbert_kmeans_0_05_mmarco_l_all_english_s_all_30k_distill_test_mt5_base_mmarco_v2_30k` is a English model originally trained by spear-model.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mbert_kmeans_0_05_mmarco_l_all_english_s_all_30k_distill_test_mt5_base_mmarco_v2_30k_en_5.5.1_3.0_1737861537254.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mbert_kmeans_0_05_mmarco_l_all_english_s_all_30k_distill_test_mt5_base_mmarco_v2_30k_en_5.5.1_3.0_1737861537254.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("mbert_kmeans_0_05_mmarco_l_all_english_s_all_30k_distill_test_mt5_base_mmarco_v2_30k","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("mbert_kmeans_0_05_mmarco_l_all_english_s_all_30k_distill_test_mt5_base_mmarco_v2_30k","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mbert_kmeans_0_05_mmarco_l_all_english_s_all_30k_distill_test_mt5_base_mmarco_v2_30k|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|665.0 MB|
+
+## References
+
+https://huggingface.co/spear-model/mbert-kmeans-0.05.mmarco.L-all-en.S-all.30K.distill-test.mt5-base-mmarco-v2.30K
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-mbert_kmeans_0_05_mmarco_l_all_english_s_all_30k_distill_test_mt5_base_mmarco_v2_30k_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-mbert_kmeans_0_05_mmarco_l_all_english_s_all_30k_distill_test_mt5_base_mmarco_v2_30k_pipeline_en.md
new file mode 100644
index 00000000000000..10102fd83ec10f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-mbert_kmeans_0_05_mmarco_l_all_english_s_all_30k_distill_test_mt5_base_mmarco_v2_30k_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mbert_kmeans_0_05_mmarco_l_all_english_s_all_30k_distill_test_mt5_base_mmarco_v2_30k_pipeline pipeline BertEmbeddings from spear-model
+author: John Snow Labs
+name: mbert_kmeans_0_05_mmarco_l_all_english_s_all_30k_distill_test_mt5_base_mmarco_v2_30k_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mbert_kmeans_0_05_mmarco_l_all_english_s_all_30k_distill_test_mt5_base_mmarco_v2_30k_pipeline` is a English model originally trained by spear-model.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mbert_kmeans_0_05_mmarco_l_all_english_s_all_30k_distill_test_mt5_base_mmarco_v2_30k_pipeline_en_5.5.1_3.0_1737861576563.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mbert_kmeans_0_05_mmarco_l_all_english_s_all_30k_distill_test_mt5_base_mmarco_v2_30k_pipeline_en_5.5.1_3.0_1737861576563.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mbert_kmeans_0_05_mmarco_l_all_english_s_all_30k_distill_test_mt5_base_mmarco_v2_30k_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mbert_kmeans_0_05_mmarco_l_all_english_s_all_30k_distill_test_mt5_base_mmarco_v2_30k_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mbert_kmeans_0_05_mmarco_l_all_english_s_all_30k_distill_test_mt5_base_mmarco_v2_30k_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/spear-model/mbert-kmeans-0.05.mmarco.L-all-en.S-all.30K.distill-test.mt5-base-mmarco-v2.30K
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-mbti16_en.md b/docs/_posts/ahmedlone127/2025-01-26-mbti16_en.md
new file mode 100644
index 00000000000000..360daa00ee7664
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-mbti16_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mbti16 AlbertForSequenceClassification from StormyCreeper
+author: John Snow Labs
+name: mbti16
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, albert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mbti16` is a English model originally trained by StormyCreeper.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mbti16_en_5.5.1_3.0_1737934716748.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mbti16_en_5.5.1_3.0_1737934716748.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = AlbertForSequenceClassification.pretrained("mbti16","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = AlbertForSequenceClassification.pretrained("mbti16", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mbti16|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|44.3 MB|
+
+## References
+
+https://huggingface.co/StormyCreeper/mbti16
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-mbti16_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-mbti16_pipeline_en.md
new file mode 100644
index 00000000000000..4cfb79f727959f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-mbti16_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mbti16_pipeline pipeline AlbertForSequenceClassification from StormyCreeper
+author: John Snow Labs
+name: mbti16_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mbti16_pipeline` is a English model originally trained by StormyCreeper.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mbti16_pipeline_en_5.5.1_3.0_1737934719012.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mbti16_pipeline_en_5.5.1_3.0_1737934719012.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mbti16_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mbti16_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mbti16_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|44.3 MB|
+
+## References
+
+https://huggingface.co/StormyCreeper/mbti16
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-megatron_gpt2_345m_evol_instruct_v2_en.md b/docs/_posts/ahmedlone127/2025-01-26-megatron_gpt2_345m_evol_instruct_v2_en.md
new file mode 100644
index 00000000000000..6b24adce40448f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-megatron_gpt2_345m_evol_instruct_v2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English megatron_gpt2_345m_evol_instruct_v2 GPT2Transformer from KnutJaegersberg
+author: John Snow Labs
+name: megatron_gpt2_345m_evol_instruct_v2
+date: 2025-01-26
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`megatron_gpt2_345m_evol_instruct_v2` is a English model originally trained by KnutJaegersberg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/megatron_gpt2_345m_evol_instruct_v2_en_5.5.1_3.0_1737911013856.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/megatron_gpt2_345m_evol_instruct_v2_en_5.5.1_3.0_1737911013856.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("megatron_gpt2_345m_evol_instruct_v2","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("megatron_gpt2_345m_evol_instruct_v2","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|megatron_gpt2_345m_evol_instruct_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/KnutJaegersberg/megatron-gpt2-345m-evol_instruct_v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-megatron_gpt2_345m_evol_instruct_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-megatron_gpt2_345m_evol_instruct_v2_pipeline_en.md
new file mode 100644
index 00000000000000..0755915bb00c06
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-megatron_gpt2_345m_evol_instruct_v2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English megatron_gpt2_345m_evol_instruct_v2_pipeline pipeline GPT2Transformer from KnutJaegersberg
+author: John Snow Labs
+name: megatron_gpt2_345m_evol_instruct_v2_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`megatron_gpt2_345m_evol_instruct_v2_pipeline` is a English model originally trained by KnutJaegersberg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/megatron_gpt2_345m_evol_instruct_v2_pipeline_en_5.5.1_3.0_1737911081435.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/megatron_gpt2_345m_evol_instruct_v2_pipeline_en_5.5.1_3.0_1737911081435.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("megatron_gpt2_345m_evol_instruct_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("megatron_gpt2_345m_evol_instruct_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|megatron_gpt2_345m_evol_instruct_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/KnutJaegersberg/megatron-gpt2-345m-evol_instruct_v2
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-megatron_gpt_2_345m_evolinstruct_en.md b/docs/_posts/ahmedlone127/2025-01-26-megatron_gpt_2_345m_evolinstruct_en.md
new file mode 100644
index 00000000000000..6e7d7a0fe714c8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-megatron_gpt_2_345m_evolinstruct_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English megatron_gpt_2_345m_evolinstruct GPT2Transformer from KnutJaegersberg
+author: John Snow Labs
+name: megatron_gpt_2_345m_evolinstruct
+date: 2025-01-26
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`megatron_gpt_2_345m_evolinstruct` is a English model originally trained by KnutJaegersberg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/megatron_gpt_2_345m_evolinstruct_en_5.5.1_3.0_1737910815810.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/megatron_gpt_2_345m_evolinstruct_en_5.5.1_3.0_1737910815810.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("megatron_gpt_2_345m_evolinstruct","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("megatron_gpt_2_345m_evolinstruct","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|megatron_gpt_2_345m_evolinstruct|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/KnutJaegersberg/megatron-GPT-2-345m-EvolInstruct
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-megatron_gpt_2_345m_evolinstruct_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-megatron_gpt_2_345m_evolinstruct_pipeline_en.md
new file mode 100644
index 00000000000000..ddfbea36def1e2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-megatron_gpt_2_345m_evolinstruct_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English megatron_gpt_2_345m_evolinstruct_pipeline pipeline GPT2Transformer from KnutJaegersberg
+author: John Snow Labs
+name: megatron_gpt_2_345m_evolinstruct_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`megatron_gpt_2_345m_evolinstruct_pipeline` is a English model originally trained by KnutJaegersberg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/megatron_gpt_2_345m_evolinstruct_pipeline_en_5.5.1_3.0_1737910881394.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/megatron_gpt_2_345m_evolinstruct_pipeline_en_5.5.1_3.0_1737910881394.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("megatron_gpt_2_345m_evolinstruct_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("megatron_gpt_2_345m_evolinstruct_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|megatron_gpt_2_345m_evolinstruct_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/KnutJaegersberg/megatron-GPT-2-345m-EvolInstruct
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-memobert3_ed_en.md b/docs/_posts/ahmedlone127/2025-01-26-memobert3_ed_en.md
new file mode 100644
index 00000000000000..ebe4767d44320c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-memobert3_ed_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English memobert3_ed XlmRoBertaForSequenceClassification from yemen2016
+author: John Snow Labs
+name: memobert3_ed
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`memobert3_ed` is a English model originally trained by yemen2016.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/memobert3_ed_en_5.5.1_3.0_1737883097881.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/memobert3_ed_en_5.5.1_3.0_1737883097881.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("memobert3_ed","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("memobert3_ed", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|memobert3_ed|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|466.6 MB|
+
+## References
+
+https://huggingface.co/yemen2016/memobert3_ED
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-memobert3_ed_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-memobert3_ed_pipeline_en.md
new file mode 100644
index 00000000000000..cfd2cd1bdc1487
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-memobert3_ed_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English memobert3_ed_pipeline pipeline XlmRoBertaForSequenceClassification from yemen2016
+author: John Snow Labs
+name: memobert3_ed_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`memobert3_ed_pipeline` is a English model originally trained by yemen2016.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/memobert3_ed_pipeline_en_5.5.1_3.0_1737883121547.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/memobert3_ed_pipeline_en_5.5.1_3.0_1737883121547.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("memobert3_ed_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("memobert3_ed_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|memobert3_ed_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.6 MB|
+
+## References
+
+https://huggingface.co/yemen2016/memobert3_ED
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-memobert_ncst_en.md b/docs/_posts/ahmedlone127/2025-01-26-memobert_ncst_en.md
new file mode 100644
index 00000000000000..e34f487cfe8b1b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-memobert_ncst_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English memobert_ncst XlmRoBertaForSequenceClassification from yemen2016
+author: John Snow Labs
+name: memobert_ncst
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`memobert_ncst` is a English model originally trained by yemen2016.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/memobert_ncst_en_5.5.1_3.0_1737882953531.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/memobert_ncst_en_5.5.1_3.0_1737882953531.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("memobert_ncst","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("memobert_ncst", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|memobert_ncst|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|466.6 MB|
+
+## References
+
+https://huggingface.co/yemen2016/memobert_NCST
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-memobert_ncst_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-memobert_ncst_pipeline_en.md
new file mode 100644
index 00000000000000..b1df46dcb981c0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-memobert_ncst_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English memobert_ncst_pipeline pipeline XlmRoBertaForSequenceClassification from yemen2016
+author: John Snow Labs
+name: memobert_ncst_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`memobert_ncst_pipeline` is a English model originally trained by yemen2016.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/memobert_ncst_pipeline_en_5.5.1_3.0_1737882977547.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/memobert_ncst_pipeline_en_5.5.1_3.0_1737882977547.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("memobert_ncst_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("memobert_ncst_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|memobert_ncst_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.6 MB|
+
+## References
+
+https://huggingface.co/yemen2016/memobert_NCST
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-mentalroberta_empai_final_en.md b/docs/_posts/ahmedlone127/2025-01-26-mentalroberta_empai_final_en.md
new file mode 100644
index 00000000000000..6af96fc9f6537f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-mentalroberta_empai_final_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mentalroberta_empai_final RoBertaEmbeddings from LuangMV97
+author: John Snow Labs
+name: mentalroberta_empai_final
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mentalroberta_empai_final` is a English model originally trained by LuangMV97.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mentalroberta_empai_final_en_5.5.1_3.0_1737866071177.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mentalroberta_empai_final_en_5.5.1_3.0_1737866071177.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("mentalroberta_empai_final","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("mentalroberta_empai_final","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mentalroberta_empai_final|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|466.0 MB|
+
+## References
+
+https://huggingface.co/LuangMV97/MentalRoBERTa_EmpAI_final
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-mentalroberta_empai_final_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-mentalroberta_empai_final_pipeline_en.md
new file mode 100644
index 00000000000000..ac4a69b9908067
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-mentalroberta_empai_final_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mentalroberta_empai_final_pipeline pipeline RoBertaEmbeddings from LuangMV97
+author: John Snow Labs
+name: mentalroberta_empai_final_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mentalroberta_empai_final_pipeline` is a English model originally trained by LuangMV97.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mentalroberta_empai_final_pipeline_en_5.5.1_3.0_1737866101194.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mentalroberta_empai_final_pipeline_en_5.5.1_3.0_1737866101194.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mentalroberta_empai_final_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mentalroberta_empai_final_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mentalroberta_empai_final_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.1 MB|
+
+## References
+
+https://huggingface.co/LuangMV97/MentalRoBERTa_EmpAI_final
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-mentalrobertoo_en.md b/docs/_posts/ahmedlone127/2025-01-26-mentalrobertoo_en.md
new file mode 100644
index 00000000000000..15d55cb0e24faa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-mentalrobertoo_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mentalrobertoo RoBertaEmbeddings from crabone123
+author: John Snow Labs
+name: mentalrobertoo
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mentalrobertoo` is a English model originally trained by crabone123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mentalrobertoo_en_5.5.1_3.0_1737866000042.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mentalrobertoo_en_5.5.1_3.0_1737866000042.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("mentalrobertoo","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("mentalrobertoo","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mentalrobertoo|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|466.0 MB|
+
+## References
+
+https://huggingface.co/crabone123/mentalrobertoo
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-mentalrobertoo_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-mentalrobertoo_pipeline_en.md
new file mode 100644
index 00000000000000..73ad8347c00761
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-mentalrobertoo_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mentalrobertoo_pipeline pipeline RoBertaEmbeddings from crabone123
+author: John Snow Labs
+name: mentalrobertoo_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mentalrobertoo_pipeline` is a English model originally trained by crabone123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mentalrobertoo_pipeline_en_5.5.1_3.0_1737866029993.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mentalrobertoo_pipeline_en_5.5.1_3.0_1737866029993.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mentalrobertoo_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mentalrobertoo_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mentalrobertoo_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.1 MB|
+
+## References
+
+https://huggingface.co/crabone123/mentalrobertoo
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-merged_distillbert_sst2_model_lora_en.md b/docs/_posts/ahmedlone127/2025-01-26-merged_distillbert_sst2_model_lora_en.md
new file mode 100644
index 00000000000000..929f02e094e3dc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-merged_distillbert_sst2_model_lora_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English merged_distillbert_sst2_model_lora DistilBertForSequenceClassification from asm3515
+author: John Snow Labs
+name: merged_distillbert_sst2_model_lora
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`merged_distillbert_sst2_model_lora` is a English model originally trained by asm3515.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/merged_distillbert_sst2_model_lora_en_5.5.1_3.0_1737873305866.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/merged_distillbert_sst2_model_lora_en_5.5.1_3.0_1737873305866.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("merged_distillbert_sst2_model_lora","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("merged_distillbert_sst2_model_lora", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|merged_distillbert_sst2_model_lora|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/asm3515/merged-distillbert-sst2-model-lora
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-merged_distillbert_sst2_model_lora_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-merged_distillbert_sst2_model_lora_pipeline_en.md
new file mode 100644
index 00000000000000..818259b536fe8e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-merged_distillbert_sst2_model_lora_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English merged_distillbert_sst2_model_lora_pipeline pipeline DistilBertForSequenceClassification from asm3515
+author: John Snow Labs
+name: merged_distillbert_sst2_model_lora_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`merged_distillbert_sst2_model_lora_pipeline` is a English model originally trained by asm3515.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/merged_distillbert_sst2_model_lora_pipeline_en_5.5.1_3.0_1737873320786.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/merged_distillbert_sst2_model_lora_pipeline_en_5.5.1_3.0_1737873320786.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("merged_distillbert_sst2_model_lora_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("merged_distillbert_sst2_model_lora_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|merged_distillbert_sst2_model_lora_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/asm3515/merged-distillbert-sst2-model-lora
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-mergedistill_maltese_english_128_en.md b/docs/_posts/ahmedlone127/2025-01-26-mergedistill_maltese_english_128_en.md
new file mode 100644
index 00000000000000..37d886cb59e01c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-mergedistill_maltese_english_128_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mergedistill_maltese_english_128 BertEmbeddings from amitness
+author: John Snow Labs
+name: mergedistill_maltese_english_128
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mergedistill_maltese_english_128` is a English model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_english_128_en_5.5.1_3.0_1737891013152.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_english_128_en_5.5.1_3.0_1737891013152.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("mergedistill_maltese_english_128","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("mergedistill_maltese_english_128","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mergedistill_maltese_english_128|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|532.6 MB|
+
+## References
+
+https://huggingface.co/amitness/mergedistill-mt-en-128
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-mergedistill_maltese_english_128_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-mergedistill_maltese_english_128_pipeline_en.md
new file mode 100644
index 00000000000000..e8857746e58d0b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-mergedistill_maltese_english_128_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mergedistill_maltese_english_128_pipeline pipeline BertEmbeddings from amitness
+author: John Snow Labs
+name: mergedistill_maltese_english_128_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mergedistill_maltese_english_128_pipeline` is a English model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_english_128_pipeline_en_5.5.1_3.0_1737891040626.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_english_128_pipeline_en_5.5.1_3.0_1737891040626.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mergedistill_maltese_english_128_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mergedistill_maltese_english_128_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mergedistill_maltese_english_128_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|532.6 MB|
+
+## References
+
+https://huggingface.co/amitness/mergedistill-mt-en-128
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-mergedistill_maltese_english_en.md b/docs/_posts/ahmedlone127/2025-01-26-mergedistill_maltese_english_en.md
new file mode 100644
index 00000000000000..61d120054aba6d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-mergedistill_maltese_english_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mergedistill_maltese_english BertEmbeddings from amitness
+author: John Snow Labs
+name: mergedistill_maltese_english
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mergedistill_maltese_english` is a English model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_english_en_5.5.1_3.0_1737861879962.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_english_en_5.5.1_3.0_1737861879962.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("mergedistill_maltese_english","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("mergedistill_maltese_english","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mergedistill_maltese_english|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|532.5 MB|
+
+## References
+
+https://huggingface.co/amitness/mergedistill-mt-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-mergedistill_maltese_english_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-mergedistill_maltese_english_pipeline_en.md
new file mode 100644
index 00000000000000..e5b6ad3635e5d0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-mergedistill_maltese_english_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mergedistill_maltese_english_pipeline pipeline BertEmbeddings from amitness
+author: John Snow Labs
+name: mergedistill_maltese_english_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mergedistill_maltese_english_pipeline` is a English model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_english_pipeline_en_5.5.1_3.0_1737861909379.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_english_pipeline_en_5.5.1_3.0_1737861909379.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mergedistill_maltese_english_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mergedistill_maltese_english_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mergedistill_maltese_english_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|532.5 MB|
+
+## References
+
+https://huggingface.co/amitness/mergedistill-mt-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-mergedistill_maltese_italian_512_en.md b/docs/_posts/ahmedlone127/2025-01-26-mergedistill_maltese_italian_512_en.md
new file mode 100644
index 00000000000000..535affe12da07a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-mergedistill_maltese_italian_512_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mergedistill_maltese_italian_512 BertEmbeddings from amitness
+author: John Snow Labs
+name: mergedistill_maltese_italian_512
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mergedistill_maltese_italian_512` is a English model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_italian_512_en_5.5.1_3.0_1737890551982.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_italian_512_en_5.5.1_3.0_1737890551982.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("mergedistill_maltese_italian_512","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("mergedistill_maltese_italian_512","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mergedistill_maltese_italian_512|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|538.7 MB|
+
+## References
+
+https://huggingface.co/amitness/mergedistill-mt-it-512
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-mergedistill_maltese_italian_512_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-mergedistill_maltese_italian_512_pipeline_en.md
new file mode 100644
index 00000000000000..f8cb75b330a516
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-mergedistill_maltese_italian_512_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mergedistill_maltese_italian_512_pipeline pipeline BertEmbeddings from amitness
+author: John Snow Labs
+name: mergedistill_maltese_italian_512_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mergedistill_maltese_italian_512_pipeline` is a English model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_italian_512_pipeline_en_5.5.1_3.0_1737890580092.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_italian_512_pipeline_en_5.5.1_3.0_1737890580092.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mergedistill_maltese_italian_512_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mergedistill_maltese_italian_512_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mergedistill_maltese_italian_512_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|538.7 MB|
+
+## References
+
+https://huggingface.co/amitness/mergedistill-mt-it-512
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-mergedistill_maltese_italian_english_128_en.md b/docs/_posts/ahmedlone127/2025-01-26-mergedistill_maltese_italian_english_128_en.md
new file mode 100644
index 00000000000000..df70c690250a31
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-mergedistill_maltese_italian_english_128_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mergedistill_maltese_italian_english_128 BertEmbeddings from amitness
+author: John Snow Labs
+name: mergedistill_maltese_italian_english_128
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mergedistill_maltese_italian_english_128` is a English model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_italian_english_128_en_5.5.1_3.0_1737861084115.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_italian_english_128_en_5.5.1_3.0_1737861084115.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("mergedistill_maltese_italian_english_128","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("mergedistill_maltese_italian_english_128","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mergedistill_maltese_italian_english_128|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|595.7 MB|
+
+## References
+
+https://huggingface.co/amitness/mergedistill-mt-it-en-128
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-mergedistill_maltese_italian_english_128_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-mergedistill_maltese_italian_english_128_pipeline_en.md
new file mode 100644
index 00000000000000..9deb65274f5c4a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-mergedistill_maltese_italian_english_128_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mergedistill_maltese_italian_english_128_pipeline pipeline BertEmbeddings from amitness
+author: John Snow Labs
+name: mergedistill_maltese_italian_english_128_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mergedistill_maltese_italian_english_128_pipeline` is a English model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_italian_english_128_pipeline_en_5.5.1_3.0_1737861114348.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_italian_english_128_pipeline_en_5.5.1_3.0_1737861114348.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mergedistill_maltese_italian_english_128_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mergedistill_maltese_italian_english_128_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mergedistill_maltese_italian_english_128_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|595.7 MB|
+
+## References
+
+https://huggingface.co/amitness/mergedistill-mt-it-en-128
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-mlm_drugcl_descreption_epochs_5_en.md b/docs/_posts/ahmedlone127/2025-01-26-mlm_drugcl_descreption_epochs_5_en.md
new file mode 100644
index 00000000000000..f9495246ff6091
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-mlm_drugcl_descreption_epochs_5_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mlm_drugcl_descreption_epochs_5 BertEmbeddings from Milad1b
+author: John Snow Labs
+name: mlm_drugcl_descreption_epochs_5
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mlm_drugcl_descreption_epochs_5` is a English model originally trained by Milad1b.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mlm_drugcl_descreption_epochs_5_en_5.5.1_3.0_1737861713147.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mlm_drugcl_descreption_epochs_5_en_5.5.1_3.0_1737861713147.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("mlm_drugcl_descreption_epochs_5","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("mlm_drugcl_descreption_epochs_5","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mlm_drugcl_descreption_epochs_5|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|403.5 MB|
+
+## References
+
+https://huggingface.co/Milad1b/MLM_drugcl_descreption_epochs-5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-mlm_drugcl_descreption_epochs_5_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-mlm_drugcl_descreption_epochs_5_pipeline_en.md
new file mode 100644
index 00000000000000..a6c572c8737adb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-mlm_drugcl_descreption_epochs_5_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mlm_drugcl_descreption_epochs_5_pipeline pipeline BertEmbeddings from Milad1b
+author: John Snow Labs
+name: mlm_drugcl_descreption_epochs_5_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mlm_drugcl_descreption_epochs_5_pipeline` is a English model originally trained by Milad1b.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mlm_drugcl_descreption_epochs_5_pipeline_en_5.5.1_3.0_1737861737664.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mlm_drugcl_descreption_epochs_5_pipeline_en_5.5.1_3.0_1737861737664.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mlm_drugcl_descreption_epochs_5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mlm_drugcl_descreption_epochs_5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mlm_drugcl_descreption_epochs_5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/Milad1b/MLM_drugcl_descreption_epochs-5
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-mlm_jennndexter_en.md b/docs/_posts/ahmedlone127/2025-01-26-mlm_jennndexter_en.md
new file mode 100644
index 00000000000000..acd3dc1ba44863
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-mlm_jennndexter_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mlm_jennndexter RoBertaEmbeddings from JennnDexter
+author: John Snow Labs
+name: mlm_jennndexter
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mlm_jennndexter` is a English model originally trained by JennnDexter.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mlm_jennndexter_en_5.5.1_3.0_1737866423465.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mlm_jennndexter_en_5.5.1_3.0_1737866423465.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("mlm_jennndexter","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("mlm_jennndexter","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mlm_jennndexter|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|466.3 MB|
+
+## References
+
+https://huggingface.co/JennnDexter/mlm
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-mlm_jennndexter_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-mlm_jennndexter_pipeline_en.md
new file mode 100644
index 00000000000000..c42eb3712d63bc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-mlm_jennndexter_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mlm_jennndexter_pipeline pipeline RoBertaEmbeddings from JennnDexter
+author: John Snow Labs
+name: mlm_jennndexter_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mlm_jennndexter_pipeline` is a English model originally trained by JennnDexter.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mlm_jennndexter_pipeline_en_5.5.1_3.0_1737866453212.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mlm_jennndexter_pipeline_en_5.5.1_3.0_1737866453212.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mlm_jennndexter_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mlm_jennndexter_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mlm_jennndexter_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.3 MB|
+
+## References
+
+https://huggingface.co/JennnDexter/mlm
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-model_epoch_11_v3_lowercase_en.md b/docs/_posts/ahmedlone127/2025-01-26-model_epoch_11_v3_lowercase_en.md
new file mode 100644
index 00000000000000..fc92116dfffe1b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-model_epoch_11_v3_lowercase_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English model_epoch_11_v3_lowercase XlmRoBertaForSequenceClassification from vjprav33n
+author: John Snow Labs
+name: model_epoch_11_v3_lowercase
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_epoch_11_v3_lowercase` is a English model originally trained by vjprav33n.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_epoch_11_v3_lowercase_en_5.5.1_3.0_1737884453437.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_epoch_11_v3_lowercase_en_5.5.1_3.0_1737884453437.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("model_epoch_11_v3_lowercase","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("model_epoch_11_v3_lowercase", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|model_epoch_11_v3_lowercase|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|915.1 MB|
+
+## References
+
+https://huggingface.co/vjprav33n/model_epoch_11_v3_lowercase
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-model_epoch_11_v3_lowercase_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-model_epoch_11_v3_lowercase_pipeline_en.md
new file mode 100644
index 00000000000000..f554d29b68193e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-model_epoch_11_v3_lowercase_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English model_epoch_11_v3_lowercase_pipeline pipeline XlmRoBertaForSequenceClassification from vjprav33n
+author: John Snow Labs
+name: model_epoch_11_v3_lowercase_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_epoch_11_v3_lowercase_pipeline` is a English model originally trained by vjprav33n.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_epoch_11_v3_lowercase_pipeline_en_5.5.1_3.0_1737884543977.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_epoch_11_v3_lowercase_pipeline_en_5.5.1_3.0_1737884543977.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("model_epoch_11_v3_lowercase_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("model_epoch_11_v3_lowercase_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|model_epoch_11_v3_lowercase_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|915.1 MB|
+
+## References
+
+https://huggingface.co/vjprav33n/model_epoch_11_v3_lowercase
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-model_hf_vizwiz_bert_uncased_en.md b/docs/_posts/ahmedlone127/2025-01-26-model_hf_vizwiz_bert_uncased_en.md
new file mode 100644
index 00000000000000..3cb19d90ee8362
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-model_hf_vizwiz_bert_uncased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English model_hf_vizwiz_bert_uncased BertEmbeddings from nanom
+author: John Snow Labs
+name: model_hf_vizwiz_bert_uncased
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_hf_vizwiz_bert_uncased` is a English model originally trained by nanom.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_hf_vizwiz_bert_uncased_en_5.5.1_3.0_1737861694143.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_hf_vizwiz_bert_uncased_en_5.5.1_3.0_1737861694143.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("model_hf_vizwiz_bert_uncased","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("model_hf_vizwiz_bert_uncased","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|model_hf_vizwiz_bert_uncased|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/nanom/model-hf-vizwiz-bert-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-model_hf_vizwiz_bert_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-model_hf_vizwiz_bert_uncased_pipeline_en.md
new file mode 100644
index 00000000000000..4ae9cf9ee403e6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-model_hf_vizwiz_bert_uncased_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English model_hf_vizwiz_bert_uncased_pipeline pipeline BertEmbeddings from nanom
+author: John Snow Labs
+name: model_hf_vizwiz_bert_uncased_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_hf_vizwiz_bert_uncased_pipeline` is a English model originally trained by nanom.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_hf_vizwiz_bert_uncased_pipeline_en_5.5.1_3.0_1737861716762.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_hf_vizwiz_bert_uncased_pipeline_en_5.5.1_3.0_1737861716762.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("model_hf_vizwiz_bert_uncased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("model_hf_vizwiz_bert_uncased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|model_hf_vizwiz_bert_uncased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/nanom/model-hf-vizwiz-bert-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-modeldir_squad_en.md b/docs/_posts/ahmedlone127/2025-01-26-modeldir_squad_en.md
new file mode 100644
index 00000000000000..f4cdfc33468f59
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-modeldir_squad_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English modeldir_squad BertForQuestionAnswering from deeshlby
+author: John Snow Labs
+name: modeldir_squad
+date: 2025-01-26
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`modeldir_squad` is a English model originally trained by deeshlby.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/modeldir_squad_en_5.5.1_3.0_1737919575780.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/modeldir_squad_en_5.5.1_3.0_1737919575780.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("modeldir_squad","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("modeldir_squad", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|modeldir_squad|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/deeshlby/ModelDir_squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-modeldir_squad_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-modeldir_squad_pipeline_en.md
new file mode 100644
index 00000000000000..9b122fa83bb60d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-modeldir_squad_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English modeldir_squad_pipeline pipeline BertForQuestionAnswering from deeshlby
+author: John Snow Labs
+name: modeldir_squad_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`modeldir_squad_pipeline` is a English model originally trained by deeshlby.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/modeldir_squad_pipeline_en_5.5.1_3.0_1737919596305.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/modeldir_squad_pipeline_en_5.5.1_3.0_1737919596305.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("modeldir_squad_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("modeldir_squad_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|modeldir_squad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/deeshlby/ModelDir_squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-modello_1_en.md b/docs/_posts/ahmedlone127/2025-01-26-modello_1_en.md
new file mode 100644
index 00000000000000..5dc6c0a6d7c84c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-modello_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English modello_1 DistilBertForSequenceClassification from fede0211
+author: John Snow Labs
+name: modello_1
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`modello_1` is a English model originally trained by fede0211.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/modello_1_en_5.5.1_3.0_1737929174672.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/modello_1_en_5.5.1_3.0_1737929174672.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("modello_1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("modello_1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|modello_1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|246.0 MB|
+
+## References
+
+https://huggingface.co/fede0211/modello_1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-modello_1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-modello_1_pipeline_en.md
new file mode 100644
index 00000000000000..61adf6c6575623
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-modello_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English modello_1_pipeline pipeline DistilBertForSequenceClassification from fede0211
+author: John Snow Labs
+name: modello_1_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`modello_1_pipeline` is a English model originally trained by fede0211.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/modello_1_pipeline_en_5.5.1_3.0_1737929187449.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/modello_1_pipeline_en_5.5.1_3.0_1737929187449.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("modello_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("modello_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|modello_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|246.0 MB|
+
+## References
+
+https://huggingface.co/fede0211/modello_1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-modelo_qa_beto_pdqa_en.md b/docs/_posts/ahmedlone127/2025-01-26-modelo_qa_beto_pdqa_en.md
new file mode 100644
index 00000000000000..edb0f879eaae24
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-modelo_qa_beto_pdqa_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English modelo_qa_beto_pdqa BertForQuestionAnswering from Lisibonny
+author: John Snow Labs
+name: modelo_qa_beto_pdqa
+date: 2025-01-26
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`modelo_qa_beto_pdqa` is a English model originally trained by Lisibonny.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/modelo_qa_beto_pdqa_en_5.5.1_3.0_1737918696064.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/modelo_qa_beto_pdqa_en_5.5.1_3.0_1737918696064.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("modelo_qa_beto_pdqa","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("modelo_qa_beto_pdqa", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|modelo_qa_beto_pdqa|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/Lisibonny/modelo_qa_beto_pdqa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-modelo_qa_beto_pdqa_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-modelo_qa_beto_pdqa_pipeline_en.md
new file mode 100644
index 00000000000000..9a1fd1444478a7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-modelo_qa_beto_pdqa_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English modelo_qa_beto_pdqa_pipeline pipeline BertForQuestionAnswering from Lisibonny
+author: John Snow Labs
+name: modelo_qa_beto_pdqa_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`modelo_qa_beto_pdqa_pipeline` is a English model originally trained by Lisibonny.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/modelo_qa_beto_pdqa_pipeline_en_5.5.1_3.0_1737918717491.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/modelo_qa_beto_pdqa_pipeline_en_5.5.1_3.0_1737918717491.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("modelo_qa_beto_pdqa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("modelo_qa_beto_pdqa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|modelo_qa_beto_pdqa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/Lisibonny/modelo_qa_beto_pdqa
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-mt5_base_english_thai_sch_wiki_thai_spider_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-mt5_base_english_thai_sch_wiki_thai_spider_pipeline_en.md
new file mode 100644
index 00000000000000..0199b2482ebe8e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-mt5_base_english_thai_sch_wiki_thai_spider_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mt5_base_english_thai_sch_wiki_thai_spider_pipeline pipeline T5Transformer from e22vvb
+author: John Snow Labs
+name: mt5_base_english_thai_sch_wiki_thai_spider_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_base_english_thai_sch_wiki_thai_spider_pipeline` is a English model originally trained by e22vvb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_base_english_thai_sch_wiki_thai_spider_pipeline_en_5.5.1_3.0_1737849850909.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_base_english_thai_sch_wiki_thai_spider_pipeline_en_5.5.1_3.0_1737849850909.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mt5_base_english_thai_sch_wiki_thai_spider_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mt5_base_english_thai_sch_wiki_thai_spider_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_base_english_thai_sch_wiki_thai_spider_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/e22vvb/mt5-base_EN_TH_sch_wiki_TH_spider
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-mt5_base_sft_english_vietnamese_alpaca_en.md b/docs/_posts/ahmedlone127/2025-01-26-mt5_base_sft_english_vietnamese_alpaca_en.md
new file mode 100644
index 00000000000000..1b3b2016f26e20
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-mt5_base_sft_english_vietnamese_alpaca_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mt5_base_sft_english_vietnamese_alpaca T5Transformer from vietnqw
+author: John Snow Labs
+name: mt5_base_sft_english_vietnamese_alpaca
+date: 2025-01-26
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_base_sft_english_vietnamese_alpaca` is a English model originally trained by vietnqw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_base_sft_english_vietnamese_alpaca_en_5.5.1_3.0_1737851648734.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_base_sft_english_vietnamese_alpaca_en_5.5.1_3.0_1737851648734.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("mt5_base_sft_english_vietnamese_alpaca","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("mt5_base_sft_english_vietnamese_alpaca", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_base_sft_english_vietnamese_alpaca|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|2.4 GB|
+
+## References
+
+https://huggingface.co/vietnqw/mt5_base-sft-en_vi_alpaca
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-mt5_base_sft_english_vietnamese_alpaca_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-mt5_base_sft_english_vietnamese_alpaca_pipeline_en.md
new file mode 100644
index 00000000000000..030bf55043bf8e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-mt5_base_sft_english_vietnamese_alpaca_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mt5_base_sft_english_vietnamese_alpaca_pipeline pipeline T5Transformer from vietnqw
+author: John Snow Labs
+name: mt5_base_sft_english_vietnamese_alpaca_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_base_sft_english_vietnamese_alpaca_pipeline` is a English model originally trained by vietnqw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_base_sft_english_vietnamese_alpaca_pipeline_en_5.5.1_3.0_1737851913354.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_base_sft_english_vietnamese_alpaca_pipeline_en_5.5.1_3.0_1737851913354.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mt5_base_sft_english_vietnamese_alpaca_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mt5_base_sft_english_vietnamese_alpaca_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_base_sft_english_vietnamese_alpaca_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|2.4 GB|
+
+## References
+
+https://huggingface.co/vietnqw/mt5_base-sft-en_vi_alpaca
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-mt5_base_spanish_yoremnokki_en.md b/docs/_posts/ahmedlone127/2025-01-26-mt5_base_spanish_yoremnokki_en.md
new file mode 100644
index 00000000000000..8417f8360036b2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-mt5_base_spanish_yoremnokki_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mt5_base_spanish_yoremnokki T5Transformer from alfsnd
+author: John Snow Labs
+name: mt5_base_spanish_yoremnokki
+date: 2025-01-26
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_base_spanish_yoremnokki` is a English model originally trained by alfsnd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_base_spanish_yoremnokki_en_5.5.1_3.0_1737850612581.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_base_spanish_yoremnokki_en_5.5.1_3.0_1737850612581.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("mt5_base_spanish_yoremnokki","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("mt5_base_spanish_yoremnokki", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_base_spanish_yoremnokki|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|2.3 GB|
+
+## References
+
+https://huggingface.co/alfsnd/mt5-base-spanish-yoremnokki
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-mt5_base_spanish_yoremnokki_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-mt5_base_spanish_yoremnokki_pipeline_en.md
new file mode 100644
index 00000000000000..f0566a42c2a79f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-mt5_base_spanish_yoremnokki_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mt5_base_spanish_yoremnokki_pipeline pipeline T5Transformer from alfsnd
+author: John Snow Labs
+name: mt5_base_spanish_yoremnokki_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_base_spanish_yoremnokki_pipeline` is a English model originally trained by alfsnd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_base_spanish_yoremnokki_pipeline_en_5.5.1_3.0_1737850817890.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_base_spanish_yoremnokki_pipeline_en_5.5.1_3.0_1737850817890.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mt5_base_spanish_yoremnokki_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mt5_base_spanish_yoremnokki_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_base_spanish_yoremnokki_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|2.3 GB|
+
+## References
+
+https://huggingface.co/alfsnd/mt5-base-spanish-yoremnokki
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-multilbinsclass_available_securities_17june_student_xlmr_en.md b/docs/_posts/ahmedlone127/2025-01-26-multilbinsclass_available_securities_17june_student_xlmr_en.md
new file mode 100644
index 00000000000000..d57200631be238
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-multilbinsclass_available_securities_17june_student_xlmr_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English multilbinsclass_available_securities_17june_student_xlmr XlmRoBertaForSequenceClassification from slimaneMakh
+author: John Snow Labs
+name: multilbinsclass_available_securities_17june_student_xlmr
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multilbinsclass_available_securities_17june_student_xlmr` is a English model originally trained by slimaneMakh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multilbinsclass_available_securities_17june_student_xlmr_en_5.5.1_3.0_1737881018775.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multilbinsclass_available_securities_17june_student_xlmr_en_5.5.1_3.0_1737881018775.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("multilbinsclass_available_securities_17june_student_xlmr","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("multilbinsclass_available_securities_17june_student_xlmr", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|multilbinsclass_available_securities_17june_student_xlmr|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|818.2 MB|
+
+## References
+
+https://huggingface.co/slimaneMakh/MultiLBinSClass_Available_securities_17june_student_XLMR
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-multilbinsclass_available_securities_17june_student_xlmr_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-multilbinsclass_available_securities_17june_student_xlmr_pipeline_en.md
new file mode 100644
index 00000000000000..c5803730425c76
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-multilbinsclass_available_securities_17june_student_xlmr_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English multilbinsclass_available_securities_17june_student_xlmr_pipeline pipeline XlmRoBertaForSequenceClassification from slimaneMakh
+author: John Snow Labs
+name: multilbinsclass_available_securities_17june_student_xlmr_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multilbinsclass_available_securities_17june_student_xlmr_pipeline` is a English model originally trained by slimaneMakh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multilbinsclass_available_securities_17june_student_xlmr_pipeline_en_5.5.1_3.0_1737881143555.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multilbinsclass_available_securities_17june_student_xlmr_pipeline_en_5.5.1_3.0_1737881143555.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("multilbinsclass_available_securities_17june_student_xlmr_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("multilbinsclass_available_securities_17june_student_xlmr_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|multilbinsclass_available_securities_17june_student_xlmr_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|818.2 MB|
+
+## References
+
+https://huggingface.co/slimaneMakh/MultiLBinSClass_Available_securities_17june_student_XLMR
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-multilingual_xlm_roberta_for_ner_altayneset_pipeline_xx.md b/docs/_posts/ahmedlone127/2025-01-26-multilingual_xlm_roberta_for_ner_altayneset_pipeline_xx.md
new file mode 100644
index 00000000000000..9172bf4a5b3387
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-multilingual_xlm_roberta_for_ner_altayneset_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual multilingual_xlm_roberta_for_ner_altayneset_pipeline pipeline XlmRoBertaForTokenClassification from AltayNeset
+author: John Snow Labs
+name: multilingual_xlm_roberta_for_ner_altayneset_pipeline
+date: 2025-01-26
+tags: [xx, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multilingual_xlm_roberta_for_ner_altayneset_pipeline` is a Multilingual model originally trained by AltayNeset.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multilingual_xlm_roberta_for_ner_altayneset_pipeline_xx_5.5.1_3.0_1737855091739.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multilingual_xlm_roberta_for_ner_altayneset_pipeline_xx_5.5.1_3.0_1737855091739.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("multilingual_xlm_roberta_for_ner_altayneset_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("multilingual_xlm_roberta_for_ner_altayneset_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|multilingual_xlm_roberta_for_ner_altayneset_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/AltayNeset/multilingual-xlm-roberta-for-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-multilingual_xlm_roberta_for_ner_altayneset_xx.md b/docs/_posts/ahmedlone127/2025-01-26-multilingual_xlm_roberta_for_ner_altayneset_xx.md
new file mode 100644
index 00000000000000..7f046d56e28950
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-multilingual_xlm_roberta_for_ner_altayneset_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual multilingual_xlm_roberta_for_ner_altayneset XlmRoBertaForTokenClassification from AltayNeset
+author: John Snow Labs
+name: multilingual_xlm_roberta_for_ner_altayneset
+date: 2025-01-26
+tags: [xx, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multilingual_xlm_roberta_for_ner_altayneset` is a Multilingual model originally trained by AltayNeset.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multilingual_xlm_roberta_for_ner_altayneset_xx_5.5.1_3.0_1737855005643.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multilingual_xlm_roberta_for_ner_altayneset_xx_5.5.1_3.0_1737855005643.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("multilingual_xlm_roberta_for_ner_altayneset","xx") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("multilingual_xlm_roberta_for_ner_altayneset", "xx")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|multilingual_xlm_roberta_for_ner_altayneset|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|xx|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/AltayNeset/multilingual-xlm-roberta-for-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-multilingual_xlm_roberta_for_ner_turkish_pipeline_xx.md b/docs/_posts/ahmedlone127/2025-01-26-multilingual_xlm_roberta_for_ner_turkish_pipeline_xx.md
new file mode 100644
index 00000000000000..4b4b51e219f941
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-multilingual_xlm_roberta_for_ner_turkish_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual multilingual_xlm_roberta_for_ner_turkish_pipeline pipeline XlmRoBertaForTokenClassification from tuhanasinan
+author: John Snow Labs
+name: multilingual_xlm_roberta_for_ner_turkish_pipeline
+date: 2025-01-26
+tags: [xx, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multilingual_xlm_roberta_for_ner_turkish_pipeline` is a Multilingual model originally trained by tuhanasinan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multilingual_xlm_roberta_for_ner_turkish_pipeline_xx_5.5.1_3.0_1737854334737.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multilingual_xlm_roberta_for_ner_turkish_pipeline_xx_5.5.1_3.0_1737854334737.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("multilingual_xlm_roberta_for_ner_turkish_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("multilingual_xlm_roberta_for_ner_turkish_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|multilingual_xlm_roberta_for_ner_turkish_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|839.7 MB|
+
+## References
+
+https://huggingface.co/tuhanasinan/multilingual-xlm-roberta-for-ner-tr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-multilingual_xlm_roberta_for_ner_turkish_xx.md b/docs/_posts/ahmedlone127/2025-01-26-multilingual_xlm_roberta_for_ner_turkish_xx.md
new file mode 100644
index 00000000000000..fc3cc0a477632a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-multilingual_xlm_roberta_for_ner_turkish_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual multilingual_xlm_roberta_for_ner_turkish XlmRoBertaForTokenClassification from tuhanasinan
+author: John Snow Labs
+name: multilingual_xlm_roberta_for_ner_turkish
+date: 2025-01-26
+tags: [xx, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multilingual_xlm_roberta_for_ner_turkish` is a Multilingual model originally trained by tuhanasinan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multilingual_xlm_roberta_for_ner_turkish_xx_5.5.1_3.0_1737854246460.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multilingual_xlm_roberta_for_ner_turkish_xx_5.5.1_3.0_1737854246460.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("multilingual_xlm_roberta_for_ner_turkish","xx") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("multilingual_xlm_roberta_for_ner_turkish", "xx")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|multilingual_xlm_roberta_for_ner_turkish|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|xx|
+|Size:|839.7 MB|
+
+## References
+
+https://huggingface.co/tuhanasinan/multilingual-xlm-roberta-for-ner-tr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-mysportsreviewsummarizationmodel_en.md b/docs/_posts/ahmedlone127/2025-01-26-mysportsreviewsummarizationmodel_en.md
new file mode 100644
index 00000000000000..3e2c0afceed3c5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-mysportsreviewsummarizationmodel_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mysportsreviewsummarizationmodel T5Transformer from TastySoup
+author: John Snow Labs
+name: mysportsreviewsummarizationmodel
+date: 2025-01-26
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mysportsreviewsummarizationmodel` is a English model originally trained by TastySoup.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mysportsreviewsummarizationmodel_en_5.5.1_3.0_1737851239901.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mysportsreviewsummarizationmodel_en_5.5.1_3.0_1737851239901.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("mysportsreviewsummarizationmodel","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("mysportsreviewsummarizationmodel", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mysportsreviewsummarizationmodel|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|148.0 MB|
+
+## References
+
+https://huggingface.co/TastySoup/mySportsReviewSummarizationModel
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-mysportsreviewsummarizationmodel_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-mysportsreviewsummarizationmodel_pipeline_en.md
new file mode 100644
index 00000000000000..f07cfa6dbfd1da
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-mysportsreviewsummarizationmodel_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mysportsreviewsummarizationmodel_pipeline pipeline T5Transformer from TastySoup
+author: John Snow Labs
+name: mysportsreviewsummarizationmodel_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mysportsreviewsummarizationmodel_pipeline` is a English model originally trained by TastySoup.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mysportsreviewsummarizationmodel_pipeline_en_5.5.1_3.0_1737851288663.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mysportsreviewsummarizationmodel_pipeline_en_5.5.1_3.0_1737851288663.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mysportsreviewsummarizationmodel_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mysportsreviewsummarizationmodel_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mysportsreviewsummarizationmodel_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|148.0 MB|
+
+## References
+
+https://huggingface.co/TastySoup/mySportsReviewSummarizationModel
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-nepal_bhasa_phishing_email_detection_en.md b/docs/_posts/ahmedlone127/2025-01-26-nepal_bhasa_phishing_email_detection_en.md
new file mode 100644
index 00000000000000..eaa211c02c02e3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-nepal_bhasa_phishing_email_detection_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English nepal_bhasa_phishing_email_detection DistilBertForSequenceClassification from kamikaze20
+author: John Snow Labs
+name: nepal_bhasa_phishing_email_detection
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nepal_bhasa_phishing_email_detection` is a English model originally trained by kamikaze20.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nepal_bhasa_phishing_email_detection_en_5.5.1_3.0_1737929148409.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nepal_bhasa_phishing_email_detection_en_5.5.1_3.0_1737929148409.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("nepal_bhasa_phishing_email_detection","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("nepal_bhasa_phishing_email_detection", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nepal_bhasa_phishing_email_detection|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|246.0 MB|
+
+## References
+
+https://huggingface.co/kamikaze20/new_phishing-email-detection
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-nepal_bhasa_phishing_email_detection_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-nepal_bhasa_phishing_email_detection_pipeline_en.md
new file mode 100644
index 00000000000000..c8311c9d79f41e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-nepal_bhasa_phishing_email_detection_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English nepal_bhasa_phishing_email_detection_pipeline pipeline DistilBertForSequenceClassification from kamikaze20
+author: John Snow Labs
+name: nepal_bhasa_phishing_email_detection_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nepal_bhasa_phishing_email_detection_pipeline` is a English model originally trained by kamikaze20.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nepal_bhasa_phishing_email_detection_pipeline_en_5.5.1_3.0_1737929162520.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nepal_bhasa_phishing_email_detection_pipeline_en_5.5.1_3.0_1737929162520.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("nepal_bhasa_phishing_email_detection_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("nepal_bhasa_phishing_email_detection_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nepal_bhasa_phishing_email_detection_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|246.0 MB|
+
+## References
+
+https://huggingface.co/kamikaze20/new_phishing-email-detection
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-ner_advance_en.md b/docs/_posts/ahmedlone127/2025-01-26-ner_advance_en.md
new file mode 100644
index 00000000000000..cb16c527c44c96
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-ner_advance_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ner_advance XlmRoBertaForTokenClassification from neel-jotaniya
+author: John Snow Labs
+name: ner_advance
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_advance` is a English model originally trained by neel-jotaniya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_advance_en_5.5.1_3.0_1737899088616.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_advance_en_5.5.1_3.0_1737899088616.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("ner_advance","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("ner_advance", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_advance|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/neel-jotaniya/NER-advance
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-ner_advance_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-ner_advance_pipeline_en.md
new file mode 100644
index 00000000000000..3de78b357b0905
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-ner_advance_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ner_advance_pipeline pipeline XlmRoBertaForTokenClassification from neel-jotaniya
+author: John Snow Labs
+name: ner_advance_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_advance_pipeline` is a English model originally trained by neel-jotaniya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_advance_pipeline_en_5.5.1_3.0_1737899174627.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_advance_pipeline_en_5.5.1_3.0_1737899174627.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ner_advance_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ner_advance_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_advance_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/neel-jotaniya/NER-advance
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-news_classification_distilbert_en.md b/docs/_posts/ahmedlone127/2025-01-26-news_classification_distilbert_en.md
new file mode 100644
index 00000000000000..dcceeaa325773b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-news_classification_distilbert_en.md
@@ -0,0 +1,96 @@
+---
+layout: model
+title: English news_classification_distilbert DistilBertForSequenceClassification from Laurie
+author: John Snow Labs
+name: news_classification_distilbert
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`news_classification_distilbert` is a English model originally trained by Laurie.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/news_classification_distilbert_en_5.5.1_3.0_1737872999147.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/news_classification_distilbert_en_5.5.1_3.0_1737872999147.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("news_classification_distilbert","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("news_classification_distilbert", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|news_classification_distilbert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+References
+
+https://huggingface.co/Laurie/news_classification_distilbert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-news_classification_distilbert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-news_classification_distilbert_pipeline_en.md
new file mode 100644
index 00000000000000..cd1e17d2a09375
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-news_classification_distilbert_pipeline_en.md
@@ -0,0 +1,72 @@
+---
+layout: model
+title: English news_classification_distilbert_pipeline pipeline DistilBertForSequenceClassification from Laurie
+author: John Snow Labs
+name: news_classification_distilbert_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`news_classification_distilbert_pipeline` is a English model originally trained by Laurie.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/news_classification_distilbert_pipeline_en_5.5.1_3.0_1737873016175.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/news_classification_distilbert_pipeline_en_5.5.1_3.0_1737873016175.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("news_classification_distilbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("news_classification_distilbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|news_classification_distilbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+References
+
+https://huggingface.co/Laurie/news_classification_distilbert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-nlp_intent_classifier_model_en.md b/docs/_posts/ahmedlone127/2025-01-26-nlp_intent_classifier_model_en.md
new file mode 100644
index 00000000000000..bad0327f5eefcb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-nlp_intent_classifier_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English nlp_intent_classifier_model BertForSequenceClassification from Degnon
+author: John Snow Labs
+name: nlp_intent_classifier_model
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nlp_intent_classifier_model` is a English model originally trained by Degnon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nlp_intent_classifier_model_en_5.5.1_3.0_1737920837161.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nlp_intent_classifier_model_en_5.5.1_3.0_1737920837161.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("nlp_intent_classifier_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("nlp_intent_classifier_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nlp_intent_classifier_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|414.5 MB|
+
+## References
+
+https://huggingface.co/Degnon/nlp-intent-classifier-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-nlp_intent_classifier_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-nlp_intent_classifier_model_pipeline_en.md
new file mode 100644
index 00000000000000..a03771f1e6debb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-nlp_intent_classifier_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English nlp_intent_classifier_model_pipeline pipeline BertForSequenceClassification from Degnon
+author: John Snow Labs
+name: nlp_intent_classifier_model_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nlp_intent_classifier_model_pipeline` is a English model originally trained by Degnon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nlp_intent_classifier_model_pipeline_en_5.5.1_3.0_1737920858285.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nlp_intent_classifier_model_pipeline_en_5.5.1_3.0_1737920858285.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("nlp_intent_classifier_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("nlp_intent_classifier_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nlp_intent_classifier_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|414.6 MB|
+
+## References
+
+https://huggingface.co/Degnon/nlp-intent-classifier-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-nuner_finetuned_conll_ler_en.md b/docs/_posts/ahmedlone127/2025-01-26-nuner_finetuned_conll_ler_en.md
new file mode 100644
index 00000000000000..5401af2113be36
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-nuner_finetuned_conll_ler_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English nuner_finetuned_conll_ler BertForTokenClassification from fktime
+author: John Snow Labs
+name: nuner_finetuned_conll_ler
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nuner_finetuned_conll_ler` is a English model originally trained by fktime.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nuner_finetuned_conll_ler_en_5.5.1_3.0_1737934966891.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nuner_finetuned_conll_ler_en_5.5.1_3.0_1737934966891.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("nuner_finetuned_conll_ler","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("nuner_finetuned_conll_ler", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nuner_finetuned_conll_ler|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|665.2 MB|
+
+## References
+
+https://huggingface.co/fktime/nuner-finetuned-conll-ler
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-nuner_finetuned_conll_ler_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-nuner_finetuned_conll_ler_pipeline_en.md
new file mode 100644
index 00000000000000..f8816307e1a619
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-nuner_finetuned_conll_ler_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English nuner_finetuned_conll_ler_pipeline pipeline BertForTokenClassification from fktime
+author: John Snow Labs
+name: nuner_finetuned_conll_ler_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nuner_finetuned_conll_ler_pipeline` is a English model originally trained by fktime.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nuner_finetuned_conll_ler_pipeline_en_5.5.1_3.0_1737935000919.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nuner_finetuned_conll_ler_pipeline_en_5.5.1_3.0_1737935000919.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("nuner_finetuned_conll_ler_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("nuner_finetuned_conll_ler_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nuner_finetuned_conll_ler_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|665.2 MB|
+
+## References
+
+https://huggingface.co/fktime/nuner-finetuned-conll-ler
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-ontochem_biobert_1e_5_10epochs_en.md b/docs/_posts/ahmedlone127/2025-01-26-ontochem_biobert_1e_5_10epochs_en.md
new file mode 100644
index 00000000000000..7f0f4d6913f3db
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-ontochem_biobert_1e_5_10epochs_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ontochem_biobert_1e_5_10epochs BertForTokenClassification from oleshy
+author: John Snow Labs
+name: ontochem_biobert_1e_5_10epochs
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ontochem_biobert_1e_5_10epochs` is a English model originally trained by oleshy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ontochem_biobert_1e_5_10epochs_en_5.5.1_3.0_1737935343959.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ontochem_biobert_1e_5_10epochs_en_5.5.1_3.0_1737935343959.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("ontochem_biobert_1e_5_10epochs","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("ontochem_biobert_1e_5_10epochs", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ontochem_biobert_1e_5_10epochs|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.1 MB|
+
+## References
+
+https://huggingface.co/oleshy/ontochem_biobert_1e-5_10epochs
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-ontochem_biobert_1e_5_10epochs_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-ontochem_biobert_1e_5_10epochs_pipeline_en.md
new file mode 100644
index 00000000000000..e48aeb591d95d4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-ontochem_biobert_1e_5_10epochs_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ontochem_biobert_1e_5_10epochs_pipeline pipeline BertForTokenClassification from oleshy
+author: John Snow Labs
+name: ontochem_biobert_1e_5_10epochs_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ontochem_biobert_1e_5_10epochs_pipeline` is a English model originally trained by oleshy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ontochem_biobert_1e_5_10epochs_pipeline_en_5.5.1_3.0_1737935364750.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ontochem_biobert_1e_5_10epochs_pipeline_en_5.5.1_3.0_1737935364750.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ontochem_biobert_1e_5_10epochs_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ontochem_biobert_1e_5_10epochs_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ontochem_biobert_1e_5_10epochs_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.1 MB|
+
+## References
+
+https://huggingface.co/oleshy/ontochem_biobert_1e-5_10epochs
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-ontochem_biobert_1e_5_10epochs_v2_en.md b/docs/_posts/ahmedlone127/2025-01-26-ontochem_biobert_1e_5_10epochs_v2_en.md
new file mode 100644
index 00000000000000..b5fe24989dca86
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-ontochem_biobert_1e_5_10epochs_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ontochem_biobert_1e_5_10epochs_v2 BertForTokenClassification from oleshy
+author: John Snow Labs
+name: ontochem_biobert_1e_5_10epochs_v2
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ontochem_biobert_1e_5_10epochs_v2` is a English model originally trained by oleshy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ontochem_biobert_1e_5_10epochs_v2_en_5.5.1_3.0_1737935842042.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ontochem_biobert_1e_5_10epochs_v2_en_5.5.1_3.0_1737935842042.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("ontochem_biobert_1e_5_10epochs_v2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("ontochem_biobert_1e_5_10epochs_v2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ontochem_biobert_1e_5_10epochs_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.1 MB|
+
+## References
+
+https://huggingface.co/oleshy/ontochem_biobert_1e-5_10epochs_v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-ontochem_biobert_1e_5_10epochs_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-ontochem_biobert_1e_5_10epochs_v2_pipeline_en.md
new file mode 100644
index 00000000000000..2dbd2939fb3ffc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-ontochem_biobert_1e_5_10epochs_v2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ontochem_biobert_1e_5_10epochs_v2_pipeline pipeline BertForTokenClassification from oleshy
+author: John Snow Labs
+name: ontochem_biobert_1e_5_10epochs_v2_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ontochem_biobert_1e_5_10epochs_v2_pipeline` is a English model originally trained by oleshy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ontochem_biobert_1e_5_10epochs_v2_pipeline_en_5.5.1_3.0_1737935863594.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ontochem_biobert_1e_5_10epochs_v2_pipeline_en_5.5.1_3.0_1737935863594.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ontochem_biobert_1e_5_10epochs_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ontochem_biobert_1e_5_10epochs_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ontochem_biobert_1e_5_10epochs_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.1 MB|
+
+## References
+
+https://huggingface.co/oleshy/ontochem_biobert_1e-5_10epochs_v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-ontochem_biobert_1e_5_10epochs_v4_en.md b/docs/_posts/ahmedlone127/2025-01-26-ontochem_biobert_1e_5_10epochs_v4_en.md
new file mode 100644
index 00000000000000..fd3f8194a0e3b6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-ontochem_biobert_1e_5_10epochs_v4_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ontochem_biobert_1e_5_10epochs_v4 BertForTokenClassification from oleshy
+author: John Snow Labs
+name: ontochem_biobert_1e_5_10epochs_v4
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ontochem_biobert_1e_5_10epochs_v4` is a English model originally trained by oleshy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ontochem_biobert_1e_5_10epochs_v4_en_5.5.1_3.0_1737935849727.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ontochem_biobert_1e_5_10epochs_v4_en_5.5.1_3.0_1737935849727.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("ontochem_biobert_1e_5_10epochs_v4","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("ontochem_biobert_1e_5_10epochs_v4", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ontochem_biobert_1e_5_10epochs_v4|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.1 MB|
+
+## References
+
+https://huggingface.co/oleshy/ontochem_biobert_1e-5_10epochs_v4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-ontochem_biobert_1e_5_10epochs_v4_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-ontochem_biobert_1e_5_10epochs_v4_pipeline_en.md
new file mode 100644
index 00000000000000..1e3c9be2c4f5fe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-ontochem_biobert_1e_5_10epochs_v4_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ontochem_biobert_1e_5_10epochs_v4_pipeline pipeline BertForTokenClassification from oleshy
+author: John Snow Labs
+name: ontochem_biobert_1e_5_10epochs_v4_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ontochem_biobert_1e_5_10epochs_v4_pipeline` is a English model originally trained by oleshy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ontochem_biobert_1e_5_10epochs_v4_pipeline_en_5.5.1_3.0_1737935871055.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ontochem_biobert_1e_5_10epochs_v4_pipeline_en_5.5.1_3.0_1737935871055.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ontochem_biobert_1e_5_10epochs_v4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ontochem_biobert_1e_5_10epochs_v4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ontochem_biobert_1e_5_10epochs_v4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.1 MB|
+
+## References
+
+https://huggingface.co/oleshy/ontochem_biobert_1e-5_10epochs_v4
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-opus_maltese_english_chinese_finetuned_audio_product_en.md b/docs/_posts/ahmedlone127/2025-01-26-opus_maltese_english_chinese_finetuned_audio_product_en.md
new file mode 100644
index 00000000000000..94c000f112b238
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-opus_maltese_english_chinese_finetuned_audio_product_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_english_chinese_finetuned_audio_product MarianTransformer from nananatsu
+author: John Snow Labs
+name: opus_maltese_english_chinese_finetuned_audio_product
+date: 2025-01-26
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_chinese_finetuned_audio_product` is a English model originally trained by nananatsu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_chinese_finetuned_audio_product_en_5.5.1_3.0_1737864446978.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_chinese_finetuned_audio_product_en_5.5.1_3.0_1737864446978.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_english_chinese_finetuned_audio_product","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_english_chinese_finetuned_audio_product","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_chinese_finetuned_audio_product|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|418.3 MB|
+
+## References
+
+https://huggingface.co/nananatsu/opus-mt-en-zh-finetuned-audio-product
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-opus_maltese_english_chinese_finetuned_audio_product_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-opus_maltese_english_chinese_finetuned_audio_product_pipeline_en.md
new file mode 100644
index 00000000000000..6869e27bf4e522
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-opus_maltese_english_chinese_finetuned_audio_product_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_english_chinese_finetuned_audio_product_pipeline pipeline MarianTransformer from nananatsu
+author: John Snow Labs
+name: opus_maltese_english_chinese_finetuned_audio_product_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_chinese_finetuned_audio_product_pipeline` is a English model originally trained by nananatsu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_chinese_finetuned_audio_product_pipeline_en_5.5.1_3.0_1737864468456.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_chinese_finetuned_audio_product_pipeline_en_5.5.1_3.0_1737864468456.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("opus_maltese_english_chinese_finetuned_audio_product_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_english_chinese_finetuned_audio_product_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_chinese_finetuned_audio_product_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|418.8 MB|
+
+## References
+
+https://huggingface.co/nananatsu/opus-mt-en-zh-finetuned-audio-product
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_treen_en.md b/docs/_posts/ahmedlone127/2025-01-26-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_treen_en.md
new file mode 100644
index 00000000000000..9fc86f9e8b2d94
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_treen_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_treen MarianTransformer from Treen
+author: John Snow Labs
+name: opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_treen
+date: 2025-01-26
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_treen` is a English model originally trained by Treen.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_treen_en_5.5.1_3.0_1737863527336.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_treen_en_5.5.1_3.0_1737863527336.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_treen","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_treen","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_treen|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|397.0 MB|
+
+## References
+
+https://huggingface.co/Treen/opus-mt-en-ro-finetuned-en-to-ro
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_treen_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_treen_pipeline_en.md
new file mode 100644
index 00000000000000..4e7660eab1bed5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_treen_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_treen_pipeline pipeline MarianTransformer from Treen
+author: John Snow Labs
+name: opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_treen_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_treen_pipeline` is a English model originally trained by Treen.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_treen_pipeline_en_5.5.1_3.0_1737863547990.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_treen_pipeline_en_5.5.1_3.0_1737863547990.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_treen_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_treen_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_treen_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|397.6 MB|
+
+## References
+
+https://huggingface.co/Treen/opus-mt-en-ro-finetuned-en-to-ro
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-opus_maltese_english_swahili_finetuned_english_tonga_tonga_islands_swahili_en.md b/docs/_posts/ahmedlone127/2025-01-26-opus_maltese_english_swahili_finetuned_english_tonga_tonga_islands_swahili_en.md
new file mode 100644
index 00000000000000..ceccc0569401c9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-opus_maltese_english_swahili_finetuned_english_tonga_tonga_islands_swahili_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_english_swahili_finetuned_english_tonga_tonga_islands_swahili MarianTransformer from Chituyi
+author: John Snow Labs
+name: opus_maltese_english_swahili_finetuned_english_tonga_tonga_islands_swahili
+date: 2025-01-26
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_swahili_finetuned_english_tonga_tonga_islands_swahili` is a English model originally trained by Chituyi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_swahili_finetuned_english_tonga_tonga_islands_swahili_en_5.5.1_3.0_1737864431878.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_swahili_finetuned_english_tonga_tonga_islands_swahili_en_5.5.1_3.0_1737864431878.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_english_swahili_finetuned_english_tonga_tonga_islands_swahili","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_english_swahili_finetuned_english_tonga_tonga_islands_swahili","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_swahili_finetuned_english_tonga_tonga_islands_swahili|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|394.5 MB|
+
+## References
+
+https://huggingface.co/Chituyi/opus-mt-english-swahili-finetuned-en-to-sw
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-opus_maltese_english_swahili_finetuned_english_tonga_tonga_islands_swahili_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-opus_maltese_english_swahili_finetuned_english_tonga_tonga_islands_swahili_pipeline_en.md
new file mode 100644
index 00000000000000..5ef7bb3c48ec6b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-opus_maltese_english_swahili_finetuned_english_tonga_tonga_islands_swahili_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_english_swahili_finetuned_english_tonga_tonga_islands_swahili_pipeline pipeline MarianTransformer from Chituyi
+author: John Snow Labs
+name: opus_maltese_english_swahili_finetuned_english_tonga_tonga_islands_swahili_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_swahili_finetuned_english_tonga_tonga_islands_swahili_pipeline` is a English model originally trained by Chituyi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_maltese_english_swahili_finetuned_english_tonga_tonga_islands_swahili_pipeline_en_5.5.1_3.0_1737864451457.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_swahili_finetuned_english_tonga_tonga_islands_swahili_pipeline_en_5.5.1_3.0_1737864451457.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("opus_maltese_english_swahili_finetuned_english_tonga_tonga_islands_swahili_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_english_swahili_finetuned_english_tonga_tonga_islands_swahili_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_swahili_finetuned_english_tonga_tonga_islands_swahili_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|395.0 MB|
+
+## References
+
+https://huggingface.co/Chituyi/opus-mt-english-swahili-finetuned-en-to-sw
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-osf_swin_base_patch4_window7_cifar10_en.md b/docs/_posts/ahmedlone127/2025-01-26-osf_swin_base_patch4_window7_cifar10_en.md
new file mode 100644
index 00000000000000..a1a4bcbf4aa47b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-osf_swin_base_patch4_window7_cifar10_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English osf_swin_base_patch4_window7_cifar10 SwinForImageClassification from anonymous-429
+author: John Snow Labs
+name: osf_swin_base_patch4_window7_cifar10
+date: 2025-01-26
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`osf_swin_base_patch4_window7_cifar10` is a English model originally trained by anonymous-429.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/osf_swin_base_patch4_window7_cifar10_en_5.5.1_3.0_1737889188406.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/osf_swin_base_patch4_window7_cifar10_en_5.5.1_3.0_1737889188406.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""osf_swin_base_patch4_window7_cifar10","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("osf_swin_base_patch4_window7_cifar10","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|osf_swin_base_patch4_window7_cifar10|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|649.4 MB|
+
+## References
+
+https://huggingface.co/anonymous-429/osf-swin-base-patch4-window7-cifar10
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-osf_swin_base_patch4_window7_cifar10_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-osf_swin_base_patch4_window7_cifar10_pipeline_en.md
new file mode 100644
index 00000000000000..6bb0248e352464
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-osf_swin_base_patch4_window7_cifar10_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English osf_swin_base_patch4_window7_cifar10_pipeline pipeline SwinForImageClassification from anonymous-429
+author: John Snow Labs
+name: osf_swin_base_patch4_window7_cifar10_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`osf_swin_base_patch4_window7_cifar10_pipeline` is a English model originally trained by anonymous-429.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/osf_swin_base_patch4_window7_cifar10_pipeline_en_5.5.1_3.0_1737889224824.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/osf_swin_base_patch4_window7_cifar10_pipeline_en_5.5.1_3.0_1737889224824.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("osf_swin_base_patch4_window7_cifar10_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("osf_swin_base_patch4_window7_cifar10_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|osf_swin_base_patch4_window7_cifar10_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|649.4 MB|
+
+## References
+
+https://huggingface.co/anonymous-429/osf-swin-base-patch4-window7-cifar10
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-ottoman_berturk_milliyet_ner_en.md b/docs/_posts/ahmedlone127/2025-01-26-ottoman_berturk_milliyet_ner_en.md
new file mode 100644
index 00000000000000..899f4662c8b4e5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-ottoman_berturk_milliyet_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ottoman_berturk_milliyet_ner BertForTokenClassification from onurkeles
+author: John Snow Labs
+name: ottoman_berturk_milliyet_ner
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ottoman_berturk_milliyet_ner` is a English model originally trained by onurkeles.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ottoman_berturk_milliyet_ner_en_5.5.1_3.0_1737935107478.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ottoman_berturk_milliyet_ner_en_5.5.1_3.0_1737935107478.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("ottoman_berturk_milliyet_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("ottoman_berturk_milliyet_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ottoman_berturk_milliyet_ner|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|412.3 MB|
+
+## References
+
+https://huggingface.co/onurkeles/ottoman_berturk_milliyet_ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-ottoman_berturk_milliyet_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-ottoman_berturk_milliyet_ner_pipeline_en.md
new file mode 100644
index 00000000000000..70f84d067887e9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-ottoman_berturk_milliyet_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ottoman_berturk_milliyet_ner_pipeline pipeline BertForTokenClassification from onurkeles
+author: John Snow Labs
+name: ottoman_berturk_milliyet_ner_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ottoman_berturk_milliyet_ner_pipeline` is a English model originally trained by onurkeles.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ottoman_berturk_milliyet_ner_pipeline_en_5.5.1_3.0_1737935129316.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ottoman_berturk_milliyet_ner_pipeline_en_5.5.1_3.0_1737935129316.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ottoman_berturk_milliyet_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ottoman_berturk_milliyet_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ottoman_berturk_milliyet_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|412.3 MB|
+
+## References
+
+https://huggingface.co/onurkeles/ottoman_berturk_milliyet_ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-partyclim_hp_norwegian_processing_at_all_adjusted_tonga_tonga_islands_justify_en.md b/docs/_posts/ahmedlone127/2025-01-26-partyclim_hp_norwegian_processing_at_all_adjusted_tonga_tonga_islands_justify_en.md
new file mode 100644
index 00000000000000..8e1a6ad330bb41
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-partyclim_hp_norwegian_processing_at_all_adjusted_tonga_tonga_islands_justify_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English partyclim_hp_norwegian_processing_at_all_adjusted_tonga_tonga_islands_justify XlmRoBertaForSequenceClassification from julitudo
+author: John Snow Labs
+name: partyclim_hp_norwegian_processing_at_all_adjusted_tonga_tonga_islands_justify
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`partyclim_hp_norwegian_processing_at_all_adjusted_tonga_tonga_islands_justify` is a English model originally trained by julitudo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/partyclim_hp_norwegian_processing_at_all_adjusted_tonga_tonga_islands_justify_en_5.5.1_3.0_1737881775143.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/partyclim_hp_norwegian_processing_at_all_adjusted_tonga_tonga_islands_justify_en_5.5.1_3.0_1737881775143.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("partyclim_hp_norwegian_processing_at_all_adjusted_tonga_tonga_islands_justify","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("partyclim_hp_norwegian_processing_at_all_adjusted_tonga_tonga_islands_justify", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|partyclim_hp_norwegian_processing_at_all_adjusted_tonga_tonga_islands_justify|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|812.4 MB|
+
+## References
+
+https://huggingface.co/julitudo/partyclim_HP_no_processing_at_all_adjusted_to_justify
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-partyclim_hp_norwegian_processing_at_all_adjusted_tonga_tonga_islands_justify_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-partyclim_hp_norwegian_processing_at_all_adjusted_tonga_tonga_islands_justify_pipeline_en.md
new file mode 100644
index 00000000000000..f0be08a82203c9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-partyclim_hp_norwegian_processing_at_all_adjusted_tonga_tonga_islands_justify_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English partyclim_hp_norwegian_processing_at_all_adjusted_tonga_tonga_islands_justify_pipeline pipeline XlmRoBertaForSequenceClassification from julitudo
+author: John Snow Labs
+name: partyclim_hp_norwegian_processing_at_all_adjusted_tonga_tonga_islands_justify_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`partyclim_hp_norwegian_processing_at_all_adjusted_tonga_tonga_islands_justify_pipeline` is a English model originally trained by julitudo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/partyclim_hp_norwegian_processing_at_all_adjusted_tonga_tonga_islands_justify_pipeline_en_5.5.1_3.0_1737881907473.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/partyclim_hp_norwegian_processing_at_all_adjusted_tonga_tonga_islands_justify_pipeline_en_5.5.1_3.0_1737881907473.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("partyclim_hp_norwegian_processing_at_all_adjusted_tonga_tonga_islands_justify_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("partyclim_hp_norwegian_processing_at_all_adjusted_tonga_tonga_islands_justify_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|partyclim_hp_norwegian_processing_at_all_adjusted_tonga_tonga_islands_justify_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|812.4 MB|
+
+## References
+
+https://huggingface.co/julitudo/partyclim_HP_no_processing_at_all_adjusted_to_justify
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-persian_ner_parsbert_fa.md b/docs/_posts/ahmedlone127/2025-01-26-persian_ner_parsbert_fa.md
new file mode 100644
index 00000000000000..c2f402fbbabb35
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-persian_ner_parsbert_fa.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Persian persian_ner_parsbert BertForTokenClassification from PardisSzah
+author: John Snow Labs
+name: persian_ner_parsbert
+date: 2025-01-26
+tags: [fa, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: fa
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`persian_ner_parsbert` is a Persian model originally trained by PardisSzah.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/persian_ner_parsbert_fa_5.5.1_3.0_1737933774214.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/persian_ner_parsbert_fa_5.5.1_3.0_1737933774214.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("persian_ner_parsbert","fa") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("persian_ner_parsbert", "fa")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|persian_ner_parsbert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|fa|
+|Size:|606.5 MB|
+
+## References
+
+https://huggingface.co/PardisSzah/Persian_NER_parsbert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-persian_ner_parsbert_pipeline_fa.md b/docs/_posts/ahmedlone127/2025-01-26-persian_ner_parsbert_pipeline_fa.md
new file mode 100644
index 00000000000000..826eb6965ad131
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-persian_ner_parsbert_pipeline_fa.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Persian persian_ner_parsbert_pipeline pipeline BertForTokenClassification from PardisSzah
+author: John Snow Labs
+name: persian_ner_parsbert_pipeline
+date: 2025-01-26
+tags: [fa, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: fa
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`persian_ner_parsbert_pipeline` is a Persian model originally trained by PardisSzah.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/persian_ner_parsbert_pipeline_fa_5.5.1_3.0_1737933806768.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/persian_ner_parsbert_pipeline_fa_5.5.1_3.0_1737933806768.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("persian_ner_parsbert_pipeline", lang = "fa")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("persian_ner_parsbert_pipeline", lang = "fa")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|persian_ner_parsbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|fa|
+|Size:|606.5 MB|
+
+## References
+
+https://huggingface.co/PardisSzah/Persian_NER_parsbert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-playpart_ai_personal_trainer_en.md b/docs/_posts/ahmedlone127/2025-01-26-playpart_ai_personal_trainer_en.md
new file mode 100644
index 00000000000000..18cbb46f90a6ea
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-playpart_ai_personal_trainer_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English playpart_ai_personal_trainer GPT2Transformer from Lukamac
+author: John Snow Labs
+name: playpart_ai_personal_trainer
+date: 2025-01-26
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`playpart_ai_personal_trainer` is a English model originally trained by Lukamac.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/playpart_ai_personal_trainer_en_5.5.1_3.0_1737867764118.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/playpart_ai_personal_trainer_en_5.5.1_3.0_1737867764118.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("playpart_ai_personal_trainer","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("playpart_ai_personal_trainer","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|playpart_ai_personal_trainer|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/Lukamac/PlayPart-AI-Personal-Trainer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-playpart_ai_personal_trainer_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-playpart_ai_personal_trainer_pipeline_en.md
new file mode 100644
index 00000000000000..b63e808d9e4a7e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-playpart_ai_personal_trainer_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English playpart_ai_personal_trainer_pipeline pipeline GPT2Transformer from Lukamac
+author: John Snow Labs
+name: playpart_ai_personal_trainer_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`playpart_ai_personal_trainer_pipeline` is a English model originally trained by Lukamac.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/playpart_ai_personal_trainer_pipeline_en_5.5.1_3.0_1737867788973.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/playpart_ai_personal_trainer_pipeline_en_5.5.1_3.0_1737867788973.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("playpart_ai_personal_trainer_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("playpart_ai_personal_trainer_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|playpart_ai_personal_trainer_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.9 MB|
+
+## References
+
+https://huggingface.co/Lukamac/PlayPart-AI-Personal-Trainer
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-plue_ppbert_en.md b/docs/_posts/ahmedlone127/2025-01-26-plue_ppbert_en.md
new file mode 100644
index 00000000000000..c2ec3af62d7101
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-plue_ppbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English plue_ppbert BertEmbeddings from arvyz
+author: John Snow Labs
+name: plue_ppbert
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`plue_ppbert` is a English model originally trained by arvyz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/plue_ppbert_en_5.5.1_3.0_1737862132085.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/plue_ppbert_en_5.5.1_3.0_1737862132085.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("plue_ppbert","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("plue_ppbert","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|plue_ppbert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.0 MB|
+
+## References
+
+https://huggingface.co/arvyz/plue-ppbert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-plue_ppbert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-plue_ppbert_pipeline_en.md
new file mode 100644
index 00000000000000..c2908a87cfbcd2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-plue_ppbert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English plue_ppbert_pipeline pipeline BertEmbeddings from arvyz
+author: John Snow Labs
+name: plue_ppbert_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`plue_ppbert_pipeline` is a English model originally trained by arvyz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/plue_ppbert_pipeline_en_5.5.1_3.0_1737862153981.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/plue_ppbert_pipeline_en_5.5.1_3.0_1737862153981.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("plue_ppbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("plue_ppbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|plue_ppbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.0 MB|
+
+## References
+
+https://huggingface.co/arvyz/plue-ppbert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-polite_bert_en.md b/docs/_posts/ahmedlone127/2025-01-26-polite_bert_en.md
new file mode 100644
index 00000000000000..eaf60e30bad41b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-polite_bert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English polite_bert BertForSequenceClassification from NOVA-vision-language
+author: John Snow Labs
+name: polite_bert
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`polite_bert` is a English model originally trained by NOVA-vision-language.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/polite_bert_en_5.5.1_3.0_1737921195926.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/polite_bert_en_5.5.1_3.0_1737921195926.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("polite_bert","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("polite_bert", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|polite_bert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/NOVA-vision-language/polite_bert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-polite_bert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-polite_bert_pipeline_en.md
new file mode 100644
index 00000000000000..344f50cd66d797
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-polite_bert_pipeline_en.md
@@ -0,0 +1,72 @@
+---
+layout: model
+title: English polite_bert_pipeline pipeline BertForSequenceClassification from NOVA-vision-language
+author: John Snow Labs
+name: polite_bert_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`polite_bert_pipeline` is a English model originally trained by NOVA-vision-language.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/polite_bert_pipeline_en_5.5.1_3.0_1737921217656.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/polite_bert_pipeline_en_5.5.1_3.0_1737921217656.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("polite_bert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("polite_bert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|polite_bert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+References
+
+https://huggingface.co/NOVA-vision-language/polite_bert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-pre_deberta_v3_large_finetuned_augmentation_en.md b/docs/_posts/ahmedlone127/2025-01-26-pre_deberta_v3_large_finetuned_augmentation_en.md
new file mode 100644
index 00000000000000..007d81311ec5e7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-pre_deberta_v3_large_finetuned_augmentation_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English pre_deberta_v3_large_finetuned_augmentation DeBertaForSequenceClassification from sercetexam9
+author: John Snow Labs
+name: pre_deberta_v3_large_finetuned_augmentation
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pre_deberta_v3_large_finetuned_augmentation` is a English model originally trained by sercetexam9.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pre_deberta_v3_large_finetuned_augmentation_en_5.5.1_3.0_1737917851127.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pre_deberta_v3_large_finetuned_augmentation_en_5.5.1_3.0_1737917851127.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("pre_deberta_v3_large_finetuned_augmentation","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("pre_deberta_v3_large_finetuned_augmentation", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pre_deberta_v3_large_finetuned_augmentation|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/sercetexam9/PRE-deberta-v3-large-finetuned-augmentation
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-pre_deberta_v3_large_finetuned_augmentation_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-pre_deberta_v3_large_finetuned_augmentation_pipeline_en.md
new file mode 100644
index 00000000000000..9ce97a9c1d9440
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-pre_deberta_v3_large_finetuned_augmentation_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English pre_deberta_v3_large_finetuned_augmentation_pipeline pipeline DeBertaForSequenceClassification from sercetexam9
+author: John Snow Labs
+name: pre_deberta_v3_large_finetuned_augmentation_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pre_deberta_v3_large_finetuned_augmentation_pipeline` is a English model originally trained by sercetexam9.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pre_deberta_v3_large_finetuned_augmentation_pipeline_en_5.5.1_3.0_1737917971925.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pre_deberta_v3_large_finetuned_augmentation_pipeline_en_5.5.1_3.0_1737917971925.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("pre_deberta_v3_large_finetuned_augmentation_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("pre_deberta_v3_large_finetuned_augmentation_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pre_deberta_v3_large_finetuned_augmentation_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/sercetexam9/PRE-deberta-v3-large-finetuned-augmentation
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-promptgen_majinai_safe_en.md b/docs/_posts/ahmedlone127/2025-01-26-promptgen_majinai_safe_en.md
new file mode 100644
index 00000000000000..2953109b5bf001
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-promptgen_majinai_safe_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English promptgen_majinai_safe GPT2Transformer from AUTOMATIC
+author: John Snow Labs
+name: promptgen_majinai_safe
+date: 2025-01-26
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`promptgen_majinai_safe` is a English model originally trained by AUTOMATIC.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/promptgen_majinai_safe_en_5.5.1_3.0_1737869154752.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/promptgen_majinai_safe_en_5.5.1_3.0_1737869154752.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("promptgen_majinai_safe","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("promptgen_majinai_safe","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|promptgen_majinai_safe|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|308.4 MB|
+
+## References
+
+https://huggingface.co/AUTOMATIC/promptgen-majinai-safe
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-promptgen_majinai_safe_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-promptgen_majinai_safe_pipeline_en.md
new file mode 100644
index 00000000000000..e082d9c0fe7744
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-promptgen_majinai_safe_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English promptgen_majinai_safe_pipeline pipeline GPT2Transformer from AUTOMATIC
+author: John Snow Labs
+name: promptgen_majinai_safe_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`promptgen_majinai_safe_pipeline` is a English model originally trained by AUTOMATIC.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/promptgen_majinai_safe_pipeline_en_5.5.1_3.0_1737869170907.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/promptgen_majinai_safe_pipeline_en_5.5.1_3.0_1737869170907.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("promptgen_majinai_safe_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("promptgen_majinai_safe_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|promptgen_majinai_safe_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|308.4 MB|
+
+## References
+
+https://huggingface.co/AUTOMATIC/promptgen-majinai-safe
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-pruned_99_model_en.md b/docs/_posts/ahmedlone127/2025-01-26-pruned_99_model_en.md
new file mode 100644
index 00000000000000..3c4dcad0cf0f77
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-pruned_99_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English pruned_99_model DistilBertForSequenceClassification from andygoh5
+author: John Snow Labs
+name: pruned_99_model
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pruned_99_model` is a English model originally trained by andygoh5.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pruned_99_model_en_5.5.1_3.0_1737904685952.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pruned_99_model_en_5.5.1_3.0_1737904685952.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("pruned_99_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("pruned_99_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pruned_99_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/andygoh5/pruned-99-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-pruned_99_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-pruned_99_model_pipeline_en.md
new file mode 100644
index 00000000000000..46dc4018016da6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-pruned_99_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English pruned_99_model_pipeline pipeline DistilBertForSequenceClassification from andygoh5
+author: John Snow Labs
+name: pruned_99_model_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pruned_99_model_pipeline` is a English model originally trained by andygoh5.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pruned_99_model_pipeline_en_5.5.1_3.0_1737904698948.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pruned_99_model_pipeline_en_5.5.1_3.0_1737904698948.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("pruned_99_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("pruned_99_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pruned_99_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/andygoh5/pruned-99-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-ptcrawl_base_v2_5__checkpoint_3_52000_en.md b/docs/_posts/ahmedlone127/2025-01-26-ptcrawl_base_v2_5__checkpoint_3_52000_en.md
new file mode 100644
index 00000000000000..8d56a973fe2a7f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-ptcrawl_base_v2_5__checkpoint_3_52000_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ptcrawl_base_v2_5__checkpoint_3_52000 RoBertaEmbeddings from eduagarcia-temp
+author: John Snow Labs
+name: ptcrawl_base_v2_5__checkpoint_3_52000
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ptcrawl_base_v2_5__checkpoint_3_52000` is a English model originally trained by eduagarcia-temp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ptcrawl_base_v2_5__checkpoint_3_52000_en_5.5.1_3.0_1737906547503.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ptcrawl_base_v2_5__checkpoint_3_52000_en_5.5.1_3.0_1737906547503.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("ptcrawl_base_v2_5__checkpoint_3_52000","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("ptcrawl_base_v2_5__checkpoint_3_52000","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ptcrawl_base_v2_5__checkpoint_3_52000|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|296.7 MB|
+
+## References
+
+https://huggingface.co/eduagarcia-temp/ptcrawl_base-v2_5__checkpoint_3_52000
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-ptcrawl_base_v2_5__checkpoint_3_52000_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-ptcrawl_base_v2_5__checkpoint_3_52000_pipeline_en.md
new file mode 100644
index 00000000000000..0b209102ff0f36
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-ptcrawl_base_v2_5__checkpoint_3_52000_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ptcrawl_base_v2_5__checkpoint_3_52000_pipeline pipeline RoBertaEmbeddings from eduagarcia-temp
+author: John Snow Labs
+name: ptcrawl_base_v2_5__checkpoint_3_52000_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ptcrawl_base_v2_5__checkpoint_3_52000_pipeline` is a English model originally trained by eduagarcia-temp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ptcrawl_base_v2_5__checkpoint_3_52000_pipeline_en_5.5.1_3.0_1737906635599.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ptcrawl_base_v2_5__checkpoint_3_52000_pipeline_en_5.5.1_3.0_1737906635599.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ptcrawl_base_v2_5__checkpoint_3_52000_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ptcrawl_base_v2_5__checkpoint_3_52000_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ptcrawl_base_v2_5__checkpoint_3_52000_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|296.7 MB|
+
+## References
+
+https://huggingface.co/eduagarcia-temp/ptcrawl_base-v2_5__checkpoint_3_52000
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-ptcrawl_base_v2_5__checkpoint_last_en.md b/docs/_posts/ahmedlone127/2025-01-26-ptcrawl_base_v2_5__checkpoint_last_en.md
new file mode 100644
index 00000000000000..b6d6ecbfce773d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-ptcrawl_base_v2_5__checkpoint_last_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ptcrawl_base_v2_5__checkpoint_last RoBertaEmbeddings from eduagarcia-temp
+author: John Snow Labs
+name: ptcrawl_base_v2_5__checkpoint_last
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ptcrawl_base_v2_5__checkpoint_last` is a English model originally trained by eduagarcia-temp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ptcrawl_base_v2_5__checkpoint_last_en_5.5.1_3.0_1737866377972.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ptcrawl_base_v2_5__checkpoint_last_en_5.5.1_3.0_1737866377972.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("ptcrawl_base_v2_5__checkpoint_last","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("ptcrawl_base_v2_5__checkpoint_last","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ptcrawl_base_v2_5__checkpoint_last|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|296.7 MB|
+
+## References
+
+https://huggingface.co/eduagarcia-temp/ptcrawl_base-v2_5__checkpoint_last
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-ptcrawl_base_v2_5__checkpoint_last_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-ptcrawl_base_v2_5__checkpoint_last_pipeline_en.md
new file mode 100644
index 00000000000000..a19901146b6921
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-ptcrawl_base_v2_5__checkpoint_last_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ptcrawl_base_v2_5__checkpoint_last_pipeline pipeline RoBertaEmbeddings from eduagarcia-temp
+author: John Snow Labs
+name: ptcrawl_base_v2_5__checkpoint_last_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ptcrawl_base_v2_5__checkpoint_last_pipeline` is a English model originally trained by eduagarcia-temp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ptcrawl_base_v2_5__checkpoint_last_pipeline_en_5.5.1_3.0_1737866470854.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ptcrawl_base_v2_5__checkpoint_last_pipeline_en_5.5.1_3.0_1737866470854.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ptcrawl_base_v2_5__checkpoint_last_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ptcrawl_base_v2_5__checkpoint_last_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ptcrawl_base_v2_5__checkpoint_last_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|296.7 MB|
+
+## References
+
+https://huggingface.co/eduagarcia-temp/ptcrawl_base-v2_5__checkpoint_last
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-ptcrawl_plus_legal_base_v3_5__checkpoint_1_40000_en.md b/docs/_posts/ahmedlone127/2025-01-26-ptcrawl_plus_legal_base_v3_5__checkpoint_1_40000_en.md
new file mode 100644
index 00000000000000..042839bcd48b01
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-ptcrawl_plus_legal_base_v3_5__checkpoint_1_40000_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ptcrawl_plus_legal_base_v3_5__checkpoint_1_40000 RoBertaEmbeddings from eduagarcia-temp
+author: John Snow Labs
+name: ptcrawl_plus_legal_base_v3_5__checkpoint_1_40000
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ptcrawl_plus_legal_base_v3_5__checkpoint_1_40000` is a English model originally trained by eduagarcia-temp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ptcrawl_plus_legal_base_v3_5__checkpoint_1_40000_en_5.5.1_3.0_1737865339652.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ptcrawl_plus_legal_base_v3_5__checkpoint_1_40000_en_5.5.1_3.0_1737865339652.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("ptcrawl_plus_legal_base_v3_5__checkpoint_1_40000","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("ptcrawl_plus_legal_base_v3_5__checkpoint_1_40000","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ptcrawl_plus_legal_base_v3_5__checkpoint_1_40000|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|296.8 MB|
+
+## References
+
+https://huggingface.co/eduagarcia-temp/ptcrawl_plus_legal_base_v3_5__checkpoint_1_40000
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-ptcrawl_plus_legal_base_v3_5__checkpoint_1_40000_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-ptcrawl_plus_legal_base_v3_5__checkpoint_1_40000_pipeline_en.md
new file mode 100644
index 00000000000000..8562474f70edf6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-ptcrawl_plus_legal_base_v3_5__checkpoint_1_40000_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ptcrawl_plus_legal_base_v3_5__checkpoint_1_40000_pipeline pipeline RoBertaEmbeddings from eduagarcia-temp
+author: John Snow Labs
+name: ptcrawl_plus_legal_base_v3_5__checkpoint_1_40000_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ptcrawl_plus_legal_base_v3_5__checkpoint_1_40000_pipeline` is a English model originally trained by eduagarcia-temp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ptcrawl_plus_legal_base_v3_5__checkpoint_1_40000_pipeline_en_5.5.1_3.0_1737865435637.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ptcrawl_plus_legal_base_v3_5__checkpoint_1_40000_pipeline_en_5.5.1_3.0_1737865435637.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ptcrawl_plus_legal_base_v3_5__checkpoint_1_40000_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ptcrawl_plus_legal_base_v3_5__checkpoint_1_40000_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ptcrawl_plus_legal_base_v3_5__checkpoint_1_40000_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|296.8 MB|
+
+## References
+
+https://huggingface.co/eduagarcia-temp/ptcrawl_plus_legal_base_v3_5__checkpoint_1_40000
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-qa_model2_en.md b/docs/_posts/ahmedlone127/2025-01-26-qa_model2_en.md
new file mode 100644
index 00000000000000..3125de5620aec9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-qa_model2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English qa_model2 BertForQuestionAnswering from sinos11
+author: John Snow Labs
+name: qa_model2
+date: 2025-01-26
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_model2` is a English model originally trained by sinos11.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_model2_en_5.5.1_3.0_1737919318582.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_model2_en_5.5.1_3.0_1737919318582.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("qa_model2","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("qa_model2", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_model2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/sinos11/qa_model2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-qa_model2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-qa_model2_pipeline_en.md
new file mode 100644
index 00000000000000..2fe65a21554b00
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-qa_model2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English qa_model2_pipeline pipeline BertForQuestionAnswering from sinos11
+author: John Snow Labs
+name: qa_model2_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_model2_pipeline` is a English model originally trained by sinos11.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_model2_pipeline_en_5.5.1_3.0_1737919340426.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_model2_pipeline_en_5.5.1_3.0_1737919340426.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("qa_model2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("qa_model2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_model2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/sinos11/qa_model2
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-qa_model_sinos11_en.md b/docs/_posts/ahmedlone127/2025-01-26-qa_model_sinos11_en.md
new file mode 100644
index 00000000000000..0f38c8b0da24b0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-qa_model_sinos11_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English qa_model_sinos11 BertForQuestionAnswering from sinos11
+author: John Snow Labs
+name: qa_model_sinos11
+date: 2025-01-26
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_model_sinos11` is a English model originally trained by sinos11.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_model_sinos11_en_5.5.1_3.0_1737919040190.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_model_sinos11_en_5.5.1_3.0_1737919040190.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("qa_model_sinos11","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("qa_model_sinos11", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_model_sinos11|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/sinos11/qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-qa_model_sinos11_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-qa_model_sinos11_pipeline_en.md
new file mode 100644
index 00000000000000..16859c95f24b22
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-qa_model_sinos11_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English qa_model_sinos11_pipeline pipeline BertForQuestionAnswering from sinos11
+author: John Snow Labs
+name: qa_model_sinos11_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_model_sinos11_pipeline` is a English model originally trained by sinos11.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_model_sinos11_pipeline_en_5.5.1_3.0_1737919061417.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_model_sinos11_pipeline_en_5.5.1_3.0_1737919061417.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("qa_model_sinos11_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("qa_model_sinos11_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_model_sinos11_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/sinos11/qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-qurantafsir_gpt2_en.md b/docs/_posts/ahmedlone127/2025-01-26-qurantafsir_gpt2_en.md
new file mode 100644
index 00000000000000..7dfa6be7d0fafe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-qurantafsir_gpt2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English qurantafsir_gpt2 GPT2Transformer from kaiest
+author: John Snow Labs
+name: qurantafsir_gpt2
+date: 2025-01-26
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qurantafsir_gpt2` is a English model originally trained by kaiest.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qurantafsir_gpt2_en_5.5.1_3.0_1737914159223.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qurantafsir_gpt2_en_5.5.1_3.0_1737914159223.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("qurantafsir_gpt2","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("qurantafsir_gpt2","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qurantafsir_gpt2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/kaiest/QuranTafsir_gpt2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-qurantafsir_gpt2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-qurantafsir_gpt2_pipeline_en.md
new file mode 100644
index 00000000000000..2d78aa567c2158
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-qurantafsir_gpt2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English qurantafsir_gpt2_pipeline pipeline GPT2Transformer from kaiest
+author: John Snow Labs
+name: qurantafsir_gpt2_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qurantafsir_gpt2_pipeline` is a English model originally trained by kaiest.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qurantafsir_gpt2_pipeline_en_5.5.1_3.0_1737914183067.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qurantafsir_gpt2_pipeline_en_5.5.1_3.0_1737914183067.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("qurantafsir_gpt2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("qurantafsir_gpt2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qurantafsir_gpt2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/kaiest/QuranTafsir_gpt2
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-qwen_textgen_model15_en.md b/docs/_posts/ahmedlone127/2025-01-26-qwen_textgen_model15_en.md
new file mode 100644
index 00000000000000..2f38748e74de2b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-qwen_textgen_model15_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English qwen_textgen_model15 BertEmbeddings from JeloH
+author: John Snow Labs
+name: qwen_textgen_model15
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qwen_textgen_model15` is a English model originally trained by JeloH.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qwen_textgen_model15_en_5.5.1_3.0_1737861108831.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qwen_textgen_model15_en_5.5.1_3.0_1737861108831.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("qwen_textgen_model15","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("qwen_textgen_model15","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qwen_textgen_model15|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/JeloH/qwen-textgen-model15
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-qwen_textgen_model15_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-qwen_textgen_model15_pipeline_en.md
new file mode 100644
index 00000000000000..2020101bb91d48
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-qwen_textgen_model15_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English qwen_textgen_model15_pipeline pipeline BertEmbeddings from JeloH
+author: John Snow Labs
+name: qwen_textgen_model15_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qwen_textgen_model15_pipeline` is a English model originally trained by JeloH.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qwen_textgen_model15_pipeline_en_5.5.1_3.0_1737861130601.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qwen_textgen_model15_pipeline_en_5.5.1_3.0_1737861130601.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("qwen_textgen_model15_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("qwen_textgen_model15_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qwen_textgen_model15_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/JeloH/qwen-textgen-model15
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-regression_xlm_roberta_divemt_vietnamese_en.md b/docs/_posts/ahmedlone127/2025-01-26-regression_xlm_roberta_divemt_vietnamese_en.md
new file mode 100644
index 00000000000000..0bed966d21114a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-regression_xlm_roberta_divemt_vietnamese_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English regression_xlm_roberta_divemt_vietnamese XlmRoBertaForSequenceClassification from iknlpt3
+author: John Snow Labs
+name: regression_xlm_roberta_divemt_vietnamese
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`regression_xlm_roberta_divemt_vietnamese` is a English model originally trained by iknlpt3.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/regression_xlm_roberta_divemt_vietnamese_en_5.5.1_3.0_1737885353298.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/regression_xlm_roberta_divemt_vietnamese_en_5.5.1_3.0_1737885353298.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("regression_xlm_roberta_divemt_vietnamese","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("regression_xlm_roberta_divemt_vietnamese", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|regression_xlm_roberta_divemt_vietnamese|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|774.2 MB|
+
+## References
+
+https://huggingface.co/iknlpt3/regression_xlm_roberta_divemt_vie
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-regression_xlm_roberta_divemt_vietnamese_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-regression_xlm_roberta_divemt_vietnamese_pipeline_en.md
new file mode 100644
index 00000000000000..d1ba6f1c6ef176
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-regression_xlm_roberta_divemt_vietnamese_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English regression_xlm_roberta_divemt_vietnamese_pipeline pipeline XlmRoBertaForSequenceClassification from iknlpt3
+author: John Snow Labs
+name: regression_xlm_roberta_divemt_vietnamese_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`regression_xlm_roberta_divemt_vietnamese_pipeline` is a English model originally trained by iknlpt3.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/regression_xlm_roberta_divemt_vietnamese_pipeline_en_5.5.1_3.0_1737885496714.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/regression_xlm_roberta_divemt_vietnamese_pipeline_en_5.5.1_3.0_1737885496714.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("regression_xlm_roberta_divemt_vietnamese_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("regression_xlm_roberta_divemt_vietnamese_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|regression_xlm_roberta_divemt_vietnamese_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|774.2 MB|
+
+## References
+
+https://huggingface.co/iknlpt3/regression_xlm_roberta_divemt_vie
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-results_h_gandomi_en.md b/docs/_posts/ahmedlone127/2025-01-26-results_h_gandomi_en.md
new file mode 100644
index 00000000000000..c07bf510d5e76f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-results_h_gandomi_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English results_h_gandomi DistilBertForTokenClassification from h-gandomi
+author: John Snow Labs
+name: results_h_gandomi
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_h_gandomi` is a English model originally trained by h-gandomi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_h_gandomi_en_5.5.1_3.0_1737909659687.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_h_gandomi_en_5.5.1_3.0_1737909659687.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("results_h_gandomi","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("results_h_gandomi", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_h_gandomi|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/h-gandomi/results
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-results_h_gandomi_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-results_h_gandomi_pipeline_en.md
new file mode 100644
index 00000000000000..647cf3cab6c63f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-results_h_gandomi_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English results_h_gandomi_pipeline pipeline DistilBertForTokenClassification from h-gandomi
+author: John Snow Labs
+name: results_h_gandomi_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_h_gandomi_pipeline` is a English model originally trained by h-gandomi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_h_gandomi_pipeline_en_5.5.1_3.0_1737909673735.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_h_gandomi_pipeline_en_5.5.1_3.0_1737909673735.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("results_h_gandomi_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("results_h_gandomi_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_h_gandomi_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/h-gandomi/results
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-robbert_2023_dutch_large_ft_lcn_en.md b/docs/_posts/ahmedlone127/2025-01-26-robbert_2023_dutch_large_ft_lcn_en.md
new file mode 100644
index 00000000000000..4ee9331e444842
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-robbert_2023_dutch_large_ft_lcn_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English robbert_2023_dutch_large_ft_lcn RoBertaEmbeddings from btamm12
+author: John Snow Labs
+name: robbert_2023_dutch_large_ft_lcn
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`robbert_2023_dutch_large_ft_lcn` is a English model originally trained by btamm12.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/robbert_2023_dutch_large_ft_lcn_en_5.5.1_3.0_1737907696111.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/robbert_2023_dutch_large_ft_lcn_en_5.5.1_3.0_1737907696111.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("robbert_2023_dutch_large_ft_lcn","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("robbert_2023_dutch_large_ft_lcn","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|robbert_2023_dutch_large_ft_lcn|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/btamm12/robbert-2023-dutch-large-ft-lcn
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-robbert_2023_dutch_large_ft_lcn_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-robbert_2023_dutch_large_ft_lcn_pipeline_en.md
new file mode 100644
index 00000000000000..b268d3c464e1e4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-robbert_2023_dutch_large_ft_lcn_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English robbert_2023_dutch_large_ft_lcn_pipeline pipeline RoBertaEmbeddings from btamm12
+author: John Snow Labs
+name: robbert_2023_dutch_large_ft_lcn_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`robbert_2023_dutch_large_ft_lcn_pipeline` is a English model originally trained by btamm12.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/robbert_2023_dutch_large_ft_lcn_pipeline_en_5.5.1_3.0_1737907763079.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/robbert_2023_dutch_large_ft_lcn_pipeline_en_5.5.1_3.0_1737907763079.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("robbert_2023_dutch_large_ft_lcn_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("robbert_2023_dutch_large_ft_lcn_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|robbert_2023_dutch_large_ft_lcn_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/btamm12/robbert-2023-dutch-large-ft-lcn
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-roberta_base_bne_finetuned_tass2020_en.md b/docs/_posts/ahmedlone127/2025-01-26-roberta_base_bne_finetuned_tass2020_en.md
new file mode 100644
index 00000000000000..45eca250d3896e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-roberta_base_bne_finetuned_tass2020_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_base_bne_finetuned_tass2020 RoBertaEmbeddings from helenpy
+author: John Snow Labs
+name: roberta_base_bne_finetuned_tass2020
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_bne_finetuned_tass2020` is a English model originally trained by helenpy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_bne_finetuned_tass2020_en_5.5.1_3.0_1737865204125.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_bne_finetuned_tass2020_en_5.5.1_3.0_1737865204125.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("roberta_base_bne_finetuned_tass2020","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("roberta_base_bne_finetuned_tass2020","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_bne_finetuned_tass2020|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|463.7 MB|
+
+## References
+
+https://huggingface.co/helenpy/roberta-base-bne-finetuned-Tass2020
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-roberta_base_bne_finetuned_tass2020_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-roberta_base_bne_finetuned_tass2020_pipeline_en.md
new file mode 100644
index 00000000000000..0593d421cbef15
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-roberta_base_bne_finetuned_tass2020_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_base_bne_finetuned_tass2020_pipeline pipeline RoBertaEmbeddings from helenpy
+author: John Snow Labs
+name: roberta_base_bne_finetuned_tass2020_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_bne_finetuned_tass2020_pipeline` is a English model originally trained by helenpy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_bne_finetuned_tass2020_pipeline_en_5.5.1_3.0_1737865236549.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_bne_finetuned_tass2020_pipeline_en_5.5.1_3.0_1737865236549.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_base_bne_finetuned_tass2020_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_bne_finetuned_tass2020_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_bne_finetuned_tass2020_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|463.7 MB|
+
+## References
+
+https://huggingface.co/helenpy/roberta-base-bne-finetuned-Tass2020
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-roberta_base_ecom_qa_en.md b/docs/_posts/ahmedlone127/2025-01-26-roberta_base_ecom_qa_en.md
new file mode 100644
index 00000000000000..900c324e048d6e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-roberta_base_ecom_qa_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English roberta_base_ecom_qa RoBertaForQuestionAnswering from Vinayak1699
+author: John Snow Labs
+name: roberta_base_ecom_qa
+date: 2025-01-26
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_ecom_qa` is a English model originally trained by Vinayak1699.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_ecom_qa_en_5.5.1_3.0_1737884114666.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_ecom_qa_en_5.5.1_3.0_1737884114666.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_base_ecom_qa","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_base_ecom_qa", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_ecom_qa|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|440.2 MB|
+
+## References
+
+https://huggingface.co/Vinayak1699/roberta-base-ecom-qa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-roberta_base_ecom_qa_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-roberta_base_ecom_qa_pipeline_en.md
new file mode 100644
index 00000000000000..ae3b3b8219d944
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-roberta_base_ecom_qa_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_base_ecom_qa_pipeline pipeline RoBertaForQuestionAnswering from Vinayak1699
+author: John Snow Labs
+name: roberta_base_ecom_qa_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_ecom_qa_pipeline` is a English model originally trained by Vinayak1699.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_ecom_qa_pipeline_en_5.5.1_3.0_1737884144195.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_ecom_qa_pipeline_en_5.5.1_3.0_1737884144195.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_base_ecom_qa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_ecom_qa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_ecom_qa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|440.2 MB|
+
+## References
+
+https://huggingface.co/Vinayak1699/roberta-base-ecom-qa
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-roberta_based_enron_mlm_pretrained_en.md b/docs/_posts/ahmedlone127/2025-01-26-roberta_based_enron_mlm_pretrained_en.md
new file mode 100644
index 00000000000000..0e12fe0d44b72a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-roberta_based_enron_mlm_pretrained_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_based_enron_mlm_pretrained RoBertaEmbeddings from uladzislauk
+author: John Snow Labs
+name: roberta_based_enron_mlm_pretrained
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_based_enron_mlm_pretrained` is a English model originally trained by uladzislauk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_based_enron_mlm_pretrained_en_5.5.1_3.0_1737865786404.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_based_enron_mlm_pretrained_en_5.5.1_3.0_1737865786404.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("roberta_based_enron_mlm_pretrained","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("roberta_based_enron_mlm_pretrained","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_based_enron_mlm_pretrained|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|466.3 MB|
+
+## References
+
+https://huggingface.co/uladzislauk/roberta-based-enron-mlm-pretrained
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-roberta_based_enron_mlm_pretrained_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-roberta_based_enron_mlm_pretrained_pipeline_en.md
new file mode 100644
index 00000000000000..5b786830abaea4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-roberta_based_enron_mlm_pretrained_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_based_enron_mlm_pretrained_pipeline pipeline RoBertaEmbeddings from uladzislauk
+author: John Snow Labs
+name: roberta_based_enron_mlm_pretrained_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_based_enron_mlm_pretrained_pipeline` is a English model originally trained by uladzislauk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_based_enron_mlm_pretrained_pipeline_en_5.5.1_3.0_1737865813764.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_based_enron_mlm_pretrained_pipeline_en_5.5.1_3.0_1737865813764.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_based_enron_mlm_pretrained_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_based_enron_mlm_pretrained_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_based_enron_mlm_pretrained_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.3 MB|
+
+## References
+
+https://huggingface.co/uladzislauk/roberta-based-enron-mlm-pretrained
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-roberta_imdb_en.md b/docs/_posts/ahmedlone127/2025-01-26-roberta_imdb_en.md
new file mode 100644
index 00000000000000..3900d7f58c483c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-roberta_imdb_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_imdb RoBertaEmbeddings from jmarcosh
+author: John Snow Labs
+name: roberta_imdb
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_imdb` is a English model originally trained by jmarcosh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_imdb_en_5.5.1_3.0_1737865868120.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_imdb_en_5.5.1_3.0_1737865868120.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("roberta_imdb","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("roberta_imdb","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_imdb|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|466.0 MB|
+
+## References
+
+https://huggingface.co/jmarcosh/roberta-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-roberta_imdb_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-roberta_imdb_pipeline_en.md
new file mode 100644
index 00000000000000..1b3e76a8f81e94
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-roberta_imdb_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_imdb_pipeline pipeline RoBertaEmbeddings from jmarcosh
+author: John Snow Labs
+name: roberta_imdb_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_imdb_pipeline` is a English model originally trained by jmarcosh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_imdb_pipeline_en_5.5.1_3.0_1737865893885.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_imdb_pipeline_en_5.5.1_3.0_1737865893885.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_imdb_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_imdb_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_imdb_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.1 MB|
+
+## References
+
+https://huggingface.co/jmarcosh/roberta-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-roberta_large_finetuned_wallisian_en.md b/docs/_posts/ahmedlone127/2025-01-26-roberta_large_finetuned_wallisian_en.md
new file mode 100644
index 00000000000000..5d0e61736f9511
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-roberta_large_finetuned_wallisian_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_large_finetuned_wallisian RoBertaEmbeddings from btamm12
+author: John Snow Labs
+name: roberta_large_finetuned_wallisian
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_finetuned_wallisian` is a English model originally trained by btamm12.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_finetuned_wallisian_en_5.5.1_3.0_1737906327070.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_finetuned_wallisian_en_5.5.1_3.0_1737906327070.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("roberta_large_finetuned_wallisian","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("roberta_large_finetuned_wallisian","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_large_finetuned_wallisian|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/btamm12/roberta-large-finetuned-wls
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-roberta_large_finetuned_wallisian_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-roberta_large_finetuned_wallisian_pipeline_en.md
new file mode 100644
index 00000000000000..ffac0a0c47512a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-roberta_large_finetuned_wallisian_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_large_finetuned_wallisian_pipeline pipeline RoBertaEmbeddings from btamm12
+author: John Snow Labs
+name: roberta_large_finetuned_wallisian_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_finetuned_wallisian_pipeline` is a English model originally trained by btamm12.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_finetuned_wallisian_pipeline_en_5.5.1_3.0_1737906393676.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_finetuned_wallisian_pipeline_en_5.5.1_3.0_1737906393676.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_large_finetuned_wallisian_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_large_finetuned_wallisian_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_large_finetuned_wallisian_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/btamm12/roberta-large-finetuned-wls
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-roberta_pretrained_litcov10k_en.md b/docs/_posts/ahmedlone127/2025-01-26-roberta_pretrained_litcov10k_en.md
new file mode 100644
index 00000000000000..f20bd47a3ce3cb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-roberta_pretrained_litcov10k_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_pretrained_litcov10k RoBertaEmbeddings from IneG
+author: John Snow Labs
+name: roberta_pretrained_litcov10k
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_pretrained_litcov10k` is a English model originally trained by IneG.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_pretrained_litcov10k_en_5.5.1_3.0_1737865794161.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_pretrained_litcov10k_en_5.5.1_3.0_1737865794161.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("roberta_pretrained_litcov10k","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("roberta_pretrained_litcov10k","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_pretrained_litcov10k|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/IneG/RoBERTa_pretrained_litcov10K
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-roberta_pretrained_litcov10k_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-roberta_pretrained_litcov10k_pipeline_en.md
new file mode 100644
index 00000000000000..ff3f92e4d092ef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-roberta_pretrained_litcov10k_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_pretrained_litcov10k_pipeline pipeline RoBertaEmbeddings from IneG
+author: John Snow Labs
+name: roberta_pretrained_litcov10k_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_pretrained_litcov10k_pipeline` is a English model originally trained by IneG.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_pretrained_litcov10k_pipeline_en_5.5.1_3.0_1737865873015.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_pretrained_litcov10k_pipeline_en_5.5.1_3.0_1737865873015.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_pretrained_litcov10k_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_pretrained_litcov10k_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_pretrained_litcov10k_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/IneG/RoBERTa_pretrained_litcov10K
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-roberta_pretrained_litcov200_en.md b/docs/_posts/ahmedlone127/2025-01-26-roberta_pretrained_litcov200_en.md
new file mode 100644
index 00000000000000..f1c089594f1f9a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-roberta_pretrained_litcov200_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_pretrained_litcov200 RoBertaEmbeddings from IneG
+author: John Snow Labs
+name: roberta_pretrained_litcov200
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_pretrained_litcov200` is a English model originally trained by IneG.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_pretrained_litcov200_en_5.5.1_3.0_1737907098399.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_pretrained_litcov200_en_5.5.1_3.0_1737907098399.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("roberta_pretrained_litcov200","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("roberta_pretrained_litcov200","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_pretrained_litcov200|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/IneG/RoBERTa_pretrained_litcov200
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-roberta_pretrained_litcov200_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-roberta_pretrained_litcov200_pipeline_en.md
new file mode 100644
index 00000000000000..caae81ee1a4979
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-roberta_pretrained_litcov200_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_pretrained_litcov200_pipeline pipeline RoBertaEmbeddings from IneG
+author: John Snow Labs
+name: roberta_pretrained_litcov200_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_pretrained_litcov200_pipeline` is a English model originally trained by IneG.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_pretrained_litcov200_pipeline_en_5.5.1_3.0_1737907173128.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_pretrained_litcov200_pipeline_en_5.5.1_3.0_1737907173128.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_pretrained_litcov200_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_pretrained_litcov200_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_pretrained_litcov200_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/IneG/RoBERTa_pretrained_litcov200
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-roberta_trained_mlm_en.md b/docs/_posts/ahmedlone127/2025-01-26-roberta_trained_mlm_en.md
new file mode 100644
index 00000000000000..065053347fc1db
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-roberta_trained_mlm_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_trained_mlm RoBertaEmbeddings from YaBoyBigPat
+author: John Snow Labs
+name: roberta_trained_mlm
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_trained_mlm` is a English model originally trained by YaBoyBigPat.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_trained_mlm_en_5.5.1_3.0_1737907126036.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_trained_mlm_en_5.5.1_3.0_1737907126036.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("roberta_trained_mlm","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("roberta_trained_mlm","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_trained_mlm|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/YaBoyBigPat/roberta_trained_mlm
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-roberta_trained_mlm_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-roberta_trained_mlm_pipeline_en.md
new file mode 100644
index 00000000000000..1cdc74b161c789
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-roberta_trained_mlm_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_trained_mlm_pipeline pipeline RoBertaEmbeddings from YaBoyBigPat
+author: John Snow Labs
+name: roberta_trained_mlm_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_trained_mlm_pipeline` is a English model originally trained by YaBoyBigPat.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_trained_mlm_pipeline_en_5.5.1_3.0_1737907141679.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_trained_mlm_pipeline_en_5.5.1_3.0_1737907141679.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_trained_mlm_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_trained_mlm_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_trained_mlm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/YaBoyBigPat/roberta_trained_mlm
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-rogpt2_base_en.md b/docs/_posts/ahmedlone127/2025-01-26-rogpt2_base_en.md
new file mode 100644
index 00000000000000..4cee403a566b1e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-rogpt2_base_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English rogpt2_base GPT2Transformer from readerbench
+author: John Snow Labs
+name: rogpt2_base
+date: 2025-01-26
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rogpt2_base` is a English model originally trained by readerbench.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rogpt2_base_en_5.5.1_3.0_1737868148498.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rogpt2_base_en_5.5.1_3.0_1737868148498.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("rogpt2_base","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("rogpt2_base","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rogpt2_base|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.5 MB|
+
+## References
+
+https://huggingface.co/readerbench/RoGPT2-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-rogpt2_base_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-rogpt2_base_pipeline_en.md
new file mode 100644
index 00000000000000..210fd545f72f54
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-rogpt2_base_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English rogpt2_base_pipeline pipeline GPT2Transformer from readerbench
+author: John Snow Labs
+name: rogpt2_base_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rogpt2_base_pipeline` is a English model originally trained by readerbench.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rogpt2_base_pipeline_en_5.5.1_3.0_1737868175312.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rogpt2_base_pipeline_en_5.5.1_3.0_1737868175312.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("rogpt2_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("rogpt2_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rogpt2_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.5 MB|
+
+## References
+
+https://huggingface.co/readerbench/RoGPT2-base
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-rogpt2_medium_en.md b/docs/_posts/ahmedlone127/2025-01-26-rogpt2_medium_en.md
new file mode 100644
index 00000000000000..dd94d8f8f5cdda
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-rogpt2_medium_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English rogpt2_medium GPT2Transformer from readerbench
+author: John Snow Labs
+name: rogpt2_medium
+date: 2025-01-26
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rogpt2_medium` is a English model originally trained by readerbench.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rogpt2_medium_en_5.5.1_3.0_1737912933958.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rogpt2_medium_en_5.5.1_3.0_1737912933958.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("rogpt2_medium","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("rogpt2_medium","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rogpt2_medium|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/readerbench/RoGPT2-medium
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-rogpt2_medium_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-rogpt2_medium_pipeline_en.md
new file mode 100644
index 00000000000000..7ab12cbe194cbd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-rogpt2_medium_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English rogpt2_medium_pipeline pipeline GPT2Transformer from readerbench
+author: John Snow Labs
+name: rogpt2_medium_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rogpt2_medium_pipeline` is a English model originally trained by readerbench.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rogpt2_medium_pipeline_en_5.5.1_3.0_1737913008170.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rogpt2_medium_pipeline_en_5.5.1_3.0_1737913008170.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("rogpt2_medium_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("rogpt2_medium_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rogpt2_medium_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/readerbench/RoGPT2-medium
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-rubert_base_cased_neg_en.md b/docs/_posts/ahmedlone127/2025-01-26-rubert_base_cased_neg_en.md
new file mode 100644
index 00000000000000..d01463508ff41d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-rubert_base_cased_neg_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English rubert_base_cased_neg BertForTokenClassification from DimasikKurd
+author: John Snow Labs
+name: rubert_base_cased_neg
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_base_cased_neg` is a English model originally trained by DimasikKurd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_base_cased_neg_en_5.5.1_3.0_1737935677007.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_base_cased_neg_en_5.5.1_3.0_1737935677007.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("rubert_base_cased_neg","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("rubert_base_cased_neg", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rubert_base_cased_neg|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|664.3 MB|
+
+## References
+
+https://huggingface.co/DimasikKurd/rubert-base-cased_neg
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-rubert_base_cased_neg_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-rubert_base_cased_neg_pipeline_en.md
new file mode 100644
index 00000000000000..597027145528d0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-rubert_base_cased_neg_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English rubert_base_cased_neg_pipeline pipeline BertForTokenClassification from DimasikKurd
+author: John Snow Labs
+name: rubert_base_cased_neg_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_base_cased_neg_pipeline` is a English model originally trained by DimasikKurd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_base_cased_neg_pipeline_en_5.5.1_3.0_1737935712192.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_base_cased_neg_pipeline_en_5.5.1_3.0_1737935712192.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("rubert_base_cased_neg_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("rubert_base_cased_neg_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rubert_base_cased_neg_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|664.3 MB|
+
+## References
+
+https://huggingface.co/DimasikKurd/rubert-base-cased_neg
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-s2_en.md b/docs/_posts/ahmedlone127/2025-01-26-s2_en.md
new file mode 100644
index 00000000000000..7da5476a268e27
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-s2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English s2 BertForQuestionAnswering from ShynBui
+author: John Snow Labs
+name: s2
+date: 2025-01-26
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`s2` is a English model originally trained by ShynBui.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/s2_en_5.5.1_3.0_1737919467851.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/s2_en_5.5.1_3.0_1737919467851.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("s2","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("s2", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|s2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/ShynBui/s2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-s2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-s2_pipeline_en.md
new file mode 100644
index 00000000000000..828493f73b6892
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-s2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English s2_pipeline pipeline BertForQuestionAnswering from ShynBui
+author: John Snow Labs
+name: s2_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`s2_pipeline` is a English model originally trained by ShynBui.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/s2_pipeline_en_5.5.1_3.0_1737919491102.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/s2_pipeline_en_5.5.1_3.0_1737919491102.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("s2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("s2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|s2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/ShynBui/s2
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-s4_en.md b/docs/_posts/ahmedlone127/2025-01-26-s4_en.md
new file mode 100644
index 00000000000000..599e13c31cc728
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-s4_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English s4 BertForQuestionAnswering from ShynBui
+author: John Snow Labs
+name: s4
+date: 2025-01-26
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`s4` is a English model originally trained by ShynBui.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/s4_en_5.5.1_3.0_1737919371711.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/s4_en_5.5.1_3.0_1737919371711.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("s4","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("s4", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|s4|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/ShynBui/s4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-s4_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-s4_pipeline_en.md
new file mode 100644
index 00000000000000..cb3711d979c237
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-s4_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English s4_pipeline pipeline BertForQuestionAnswering from ShynBui
+author: John Snow Labs
+name: s4_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`s4_pipeline` is a English model originally trained by ShynBui.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/s4_pipeline_en_5.5.1_3.0_1737919395044.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/s4_pipeline_en_5.5.1_3.0_1737919395044.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("s4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("s4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|s4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/ShynBui/s4
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-samolet_pipeline_ru.md b/docs/_posts/ahmedlone127/2025-01-26-samolet_pipeline_ru.md
new file mode 100644
index 00000000000000..4ae32f1f3672d4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-samolet_pipeline_ru.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Russian samolet_pipeline pipeline BertForTokenClassification from Shakhovak
+author: John Snow Labs
+name: samolet_pipeline
+date: 2025-01-26
+tags: [ru, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: ru
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`samolet_pipeline` is a Russian model originally trained by Shakhovak.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/samolet_pipeline_ru_5.5.1_3.0_1737935395042.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/samolet_pipeline_ru_5.5.1_3.0_1737935395042.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("samolet_pipeline", lang = "ru")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("samolet_pipeline", lang = "ru")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|samolet_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ru|
+|Size:|667.1 MB|
+
+## References
+
+https://huggingface.co/Shakhovak/samolet
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-samolet_ru.md b/docs/_posts/ahmedlone127/2025-01-26-samolet_ru.md
new file mode 100644
index 00000000000000..542e32cdd063a6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-samolet_ru.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Russian samolet BertForTokenClassification from Shakhovak
+author: John Snow Labs
+name: samolet
+date: 2025-01-26
+tags: [ru, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: ru
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`samolet` is a Russian model originally trained by Shakhovak.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/samolet_ru_5.5.1_3.0_1737935360185.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/samolet_ru_5.5.1_3.0_1737935360185.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("samolet","ru") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("samolet", "ru")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|samolet|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|ru|
+|Size:|667.1 MB|
+
+## References
+
+https://huggingface.co/Shakhovak/samolet
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-san_bert_en.md b/docs/_posts/ahmedlone127/2025-01-26-san_bert_en.md
new file mode 100644
index 00000000000000..31e0ecf5ef339f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-san_bert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English san_bert BertEmbeddings from sampathlonka
+author: John Snow Labs
+name: san_bert
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`san_bert` is a English model originally trained by sampathlonka.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/san_bert_en_5.5.1_3.0_1737890731067.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/san_bert_en_5.5.1_3.0_1737890731067.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("san_bert","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("san_bert","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|san_bert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.9 MB|
+
+## References
+
+https://huggingface.co/sampathlonka/San-BERT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-san_bert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-san_bert_pipeline_en.md
new file mode 100644
index 00000000000000..8a2ff974434f7a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-san_bert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English san_bert_pipeline pipeline BertEmbeddings from sampathlonka
+author: John Snow Labs
+name: san_bert_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`san_bert_pipeline` is a English model originally trained by sampathlonka.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/san_bert_pipeline_en_5.5.1_3.0_1737890752111.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/san_bert_pipeline_en_5.5.1_3.0_1737890752111.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("san_bert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("san_bert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|san_bert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.9 MB|
+
+## References
+
+https://huggingface.co/sampathlonka/San-BERT
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sarcasm_classifier_en.md b/docs/_posts/ahmedlone127/2025-01-26-sarcasm_classifier_en.md
new file mode 100644
index 00000000000000..f8887e1c85cc6c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sarcasm_classifier_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sarcasm_classifier BertForSequenceClassification from Hexye
+author: John Snow Labs
+name: sarcasm_classifier
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sarcasm_classifier` is a English model originally trained by Hexye.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sarcasm_classifier_en_5.5.1_3.0_1737920947739.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sarcasm_classifier_en_5.5.1_3.0_1737920947739.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("sarcasm_classifier","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("sarcasm_classifier", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sarcasm_classifier|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/Hexye/sarcasm-classifier
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sarcasm_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sarcasm_classifier_pipeline_en.md
new file mode 100644
index 00000000000000..3b68c74de881b6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sarcasm_classifier_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English sarcasm_classifier_pipeline pipeline BertForSequenceClassification from Hexye
+author: John Snow Labs
+name: sarcasm_classifier_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sarcasm_classifier_pipeline` is a English model originally trained by Hexye.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sarcasm_classifier_pipeline_en_5.5.1_3.0_1737920968439.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sarcasm_classifier_pipeline_en_5.5.1_3.0_1737920968439.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sarcasm_classifier_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sarcasm_classifier_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sarcasm_classifier_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/Hexye/sarcasm-classifier
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-scibertner_en.md b/docs/_posts/ahmedlone127/2025-01-26-scibertner_en.md
new file mode 100644
index 00000000000000..62f74fa6a43374
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-scibertner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English scibertner BertForTokenClassification from Kashob
+author: John Snow Labs
+name: scibertner
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scibertner` is a English model originally trained by Kashob.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/scibertner_en_5.5.1_3.0_1737933621141.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scibertner_en_5.5.1_3.0_1737933621141.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("scibertner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("scibertner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|scibertner|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|410.0 MB|
+
+## References
+
+https://huggingface.co/Kashob/SciBERTNER
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-scibertner_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-scibertner_pipeline_en.md
new file mode 100644
index 00000000000000..818da3e911841b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-scibertner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English scibertner_pipeline pipeline BertForTokenClassification from Kashob
+author: John Snow Labs
+name: scibertner_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scibertner_pipeline` is a English model originally trained by Kashob.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/scibertner_pipeline_en_5.5.1_3.0_1737933643351.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scibertner_pipeline_en_5.5.1_3.0_1737933643351.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("scibertner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("scibertner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|scibertner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.1 MB|
+
+## References
+
+https://huggingface.co/Kashob/SciBERTNER
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_agriculture_bert_finetuned_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_agriculture_bert_finetuned_en.md
new file mode 100644
index 00000000000000..bf050935410059
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_agriculture_bert_finetuned_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_agriculture_bert_finetuned BertSentenceEmbeddings from YMEA
+author: John Snow Labs
+name: sent_agriculture_bert_finetuned
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_agriculture_bert_finetuned` is a English model originally trained by YMEA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_agriculture_bert_finetuned_en_5.5.1_3.0_1737860586533.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_agriculture_bert_finetuned_en_5.5.1_3.0_1737860586533.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_agriculture_bert_finetuned","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_agriculture_bert_finetuned","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_agriculture_bert_finetuned|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|409.9 MB|
+
+## References
+
+https://huggingface.co/YMEA/agriculture-bert-finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_agriculture_bert_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_agriculture_bert_finetuned_pipeline_en.md
new file mode 100644
index 00000000000000..13620de14da8f3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_agriculture_bert_finetuned_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_agriculture_bert_finetuned_pipeline pipeline BertSentenceEmbeddings from YMEA
+author: John Snow Labs
+name: sent_agriculture_bert_finetuned_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_agriculture_bert_finetuned_pipeline` is a English model originally trained by YMEA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_agriculture_bert_finetuned_pipeline_en_5.5.1_3.0_1737860611675.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_agriculture_bert_finetuned_pipeline_en_5.5.1_3.0_1737860611675.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_agriculture_bert_finetuned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_agriculture_bert_finetuned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_agriculture_bert_finetuned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.4 MB|
+
+## References
+
+https://huggingface.co/YMEA/agriculture-bert-finetuned
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_alephbertgimmel_small_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_alephbertgimmel_small_en.md
new file mode 100644
index 00000000000000..700487fab046e9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_alephbertgimmel_small_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_alephbertgimmel_small BertSentenceEmbeddings from dicta-il
+author: John Snow Labs
+name: sent_alephbertgimmel_small
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_alephbertgimmel_small` is a English model originally trained by dicta-il.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_alephbertgimmel_small_en_5.5.1_3.0_1737856656630.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_alephbertgimmel_small_en_5.5.1_3.0_1737856656630.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_alephbertgimmel_small","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_alephbertgimmel_small","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_alephbertgimmel_small|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|295.6 MB|
+
+## References
+
+https://huggingface.co/dicta-il/alephbertgimmel-small
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_alephbertgimmel_small_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_alephbertgimmel_small_pipeline_en.md
new file mode 100644
index 00000000000000..3d5762a01ce548
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_alephbertgimmel_small_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_alephbertgimmel_small_pipeline pipeline BertSentenceEmbeddings from dicta-il
+author: John Snow Labs
+name: sent_alephbertgimmel_small_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_alephbertgimmel_small_pipeline` is a English model originally trained by dicta-il.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_alephbertgimmel_small_pipeline_en_5.5.1_3.0_1737856672446.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_alephbertgimmel_small_pipeline_en_5.5.1_3.0_1737856672446.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_alephbertgimmel_small_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_alephbertgimmel_small_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_alephbertgimmel_small_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|296.1 MB|
+
+## References
+
+https://huggingface.co/dicta-il/alephbertgimmel-small
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_all_minilm_l6_v2_personal_project_default_2024_06_12_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_all_minilm_l6_v2_personal_project_default_2024_06_12_en.md
new file mode 100644
index 00000000000000..2b59b486f4643a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_all_minilm_l6_v2_personal_project_default_2024_06_12_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_all_minilm_l6_v2_personal_project_default_2024_06_12 BertSentenceEmbeddings from brugmark
+author: John Snow Labs
+name: sent_all_minilm_l6_v2_personal_project_default_2024_06_12
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_all_minilm_l6_v2_personal_project_default_2024_06_12` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_default_2024_06_12_en_5.5.1_3.0_1737900777551.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_default_2024_06_12_en_5.5.1_3.0_1737900777551.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_all_minilm_l6_v2_personal_project_default_2024_06_12","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_all_minilm_l6_v2_personal_project_default_2024_06_12","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_all_minilm_l6_v2_personal_project_default_2024_06_12|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|83.9 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-default-2024-06-12
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_all_minilm_l6_v2_personal_project_default_2024_06_12_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_all_minilm_l6_v2_personal_project_default_2024_06_12_pipeline_en.md
new file mode 100644
index 00000000000000..64bbce3d33f7d5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_all_minilm_l6_v2_personal_project_default_2024_06_12_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_all_minilm_l6_v2_personal_project_default_2024_06_12_pipeline pipeline BertSentenceEmbeddings from brugmark
+author: John Snow Labs
+name: sent_all_minilm_l6_v2_personal_project_default_2024_06_12_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_all_minilm_l6_v2_personal_project_default_2024_06_12_pipeline` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_default_2024_06_12_pipeline_en_5.5.1_3.0_1737900781834.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_default_2024_06_12_pipeline_en_5.5.1_3.0_1737900781834.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_all_minilm_l6_v2_personal_project_default_2024_06_12_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_all_minilm_l6_v2_personal_project_default_2024_06_12_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_all_minilm_l6_v2_personal_project_default_2024_06_12_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|84.5 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-default-2024-06-12
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_07_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_07_en.md
new file mode 100644
index 00000000000000..c5c28f524bd9b7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_07_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_07 BertSentenceEmbeddings from brugmark
+author: John Snow Labs
+name: sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_07
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_07` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_07_en_5.5.1_3.0_1737900631971.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_07_en_5.5.1_3.0_1737900631971.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_07","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_07","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_07|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|84.8 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-finetuned-2024-06-07
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_07_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_07_pipeline_en.md
new file mode 100644
index 00000000000000..9b277657e8283f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_07_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_07_pipeline pipeline BertSentenceEmbeddings from brugmark
+author: John Snow Labs
+name: sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_07_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_07_pipeline` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_07_pipeline_en_5.5.1_3.0_1737900636125.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_07_pipeline_en_5.5.1_3.0_1737900636125.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_07_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_07_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_07_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|85.3 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-finetuned-2024-06-07
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_bert_adaptation_martin_fierro_caraboy_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_adaptation_martin_fierro_caraboy_en.md
new file mode 100644
index 00000000000000..7eca51f5aebdb4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_adaptation_martin_fierro_caraboy_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_adaptation_martin_fierro_caraboy BertSentenceEmbeddings from caraboy
+author: John Snow Labs
+name: sent_bert_adaptation_martin_fierro_caraboy
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_adaptation_martin_fierro_caraboy` is a English model originally trained by caraboy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_martin_fierro_caraboy_en_5.5.1_3.0_1737900301687.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_martin_fierro_caraboy_en_5.5.1_3.0_1737900301687.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_adaptation_martin_fierro_caraboy","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_adaptation_martin_fierro_caraboy","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_adaptation_martin_fierro_caraboy|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/caraboy/bert_adaptation_martin_fierro
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_bert_adaptation_martin_fierro_caraboy_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_adaptation_martin_fierro_caraboy_pipeline_en.md
new file mode 100644
index 00000000000000..2f1f2494ec041b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_adaptation_martin_fierro_caraboy_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_adaptation_martin_fierro_caraboy_pipeline pipeline BertSentenceEmbeddings from caraboy
+author: John Snow Labs
+name: sent_bert_adaptation_martin_fierro_caraboy_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_adaptation_martin_fierro_caraboy_pipeline` is a English model originally trained by caraboy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_martin_fierro_caraboy_pipeline_en_5.5.1_3.0_1737900326056.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_martin_fierro_caraboy_pipeline_en_5.5.1_3.0_1737900326056.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_adaptation_martin_fierro_caraboy_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_adaptation_martin_fierro_caraboy_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_adaptation_martin_fierro_caraboy_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.2 MB|
+
+## References
+
+https://huggingface.co/caraboy/bert_adaptation_martin_fierro
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_bert_adaptation_martin_fierro_guntherfrager_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_adaptation_martin_fierro_guntherfrager_en.md
new file mode 100644
index 00000000000000..91e7383cc4a5cc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_adaptation_martin_fierro_guntherfrager_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_adaptation_martin_fierro_guntherfrager BertSentenceEmbeddings from GuntherFrager
+author: John Snow Labs
+name: sent_bert_adaptation_martin_fierro_guntherfrager
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_adaptation_martin_fierro_guntherfrager` is a English model originally trained by GuntherFrager.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_martin_fierro_guntherfrager_en_5.5.1_3.0_1737900912065.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_martin_fierro_guntherfrager_en_5.5.1_3.0_1737900912065.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_adaptation_martin_fierro_guntherfrager","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_adaptation_martin_fierro_guntherfrager","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_adaptation_martin_fierro_guntherfrager|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/GuntherFrager/bert_adaptation_martin_fierro
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_bert_adaptation_martin_fierro_guntherfrager_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_adaptation_martin_fierro_guntherfrager_pipeline_en.md
new file mode 100644
index 00000000000000..f2a58ee29a50ca
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_adaptation_martin_fierro_guntherfrager_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_adaptation_martin_fierro_guntherfrager_pipeline pipeline BertSentenceEmbeddings from GuntherFrager
+author: John Snow Labs
+name: sent_bert_adaptation_martin_fierro_guntherfrager_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_adaptation_martin_fierro_guntherfrager_pipeline` is a English model originally trained by GuntherFrager.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_martin_fierro_guntherfrager_pipeline_en_5.5.1_3.0_1737900933468.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_martin_fierro_guntherfrager_pipeline_en_5.5.1_3.0_1737900933468.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_adaptation_martin_fierro_guntherfrager_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_adaptation_martin_fierro_guntherfrager_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_adaptation_martin_fierro_guntherfrager_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.2 MB|
+
+## References
+
+https://huggingface.co/GuntherFrager/bert_adaptation_martin_fierro
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_bert_adaptation_peppa_pig_federidos_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_adaptation_peppa_pig_federidos_en.md
new file mode 100644
index 00000000000000..31d9f390f48f20
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_adaptation_peppa_pig_federidos_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_adaptation_peppa_pig_federidos BertSentenceEmbeddings from federidos
+author: John Snow Labs
+name: sent_bert_adaptation_peppa_pig_federidos
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_adaptation_peppa_pig_federidos` is a English model originally trained by federidos.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_peppa_pig_federidos_en_5.5.1_3.0_1737900277929.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_peppa_pig_federidos_en_5.5.1_3.0_1737900277929.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_adaptation_peppa_pig_federidos","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_adaptation_peppa_pig_federidos","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_adaptation_peppa_pig_federidos|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/federidos/bert_adaptation_peppa_pig
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_bert_adaptation_peppa_pig_federidos_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_adaptation_peppa_pig_federidos_pipeline_en.md
new file mode 100644
index 00000000000000..51b342153aa9b2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_adaptation_peppa_pig_federidos_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_adaptation_peppa_pig_federidos_pipeline pipeline BertSentenceEmbeddings from federidos
+author: John Snow Labs
+name: sent_bert_adaptation_peppa_pig_federidos_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_adaptation_peppa_pig_federidos_pipeline` is a English model originally trained by federidos.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_peppa_pig_federidos_pipeline_en_5.5.1_3.0_1737900299996.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_peppa_pig_federidos_pipeline_en_5.5.1_3.0_1737900299996.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_adaptation_peppa_pig_federidos_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_adaptation_peppa_pig_federidos_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_adaptation_peppa_pig_federidos_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.2 MB|
+
+## References
+
+https://huggingface.co/federidos/bert_adaptation_peppa_pig
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_bert_adaptation_peppa_pig_juanph_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_adaptation_peppa_pig_juanph_en.md
new file mode 100644
index 00000000000000..fb1cd1507e30a1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_adaptation_peppa_pig_juanph_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_adaptation_peppa_pig_juanph BertSentenceEmbeddings from JuanPH
+author: John Snow Labs
+name: sent_bert_adaptation_peppa_pig_juanph
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_adaptation_peppa_pig_juanph` is a English model originally trained by JuanPH.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_peppa_pig_juanph_en_5.5.1_3.0_1737855954052.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_peppa_pig_juanph_en_5.5.1_3.0_1737855954052.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_adaptation_peppa_pig_juanph","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_adaptation_peppa_pig_juanph","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_adaptation_peppa_pig_juanph|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/JuanPH/bert_adaptation_peppa_pig
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_bert_adaptation_peppa_pig_juanph_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_adaptation_peppa_pig_juanph_pipeline_en.md
new file mode 100644
index 00000000000000..97cd144afe6163
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_adaptation_peppa_pig_juanph_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_adaptation_peppa_pig_juanph_pipeline pipeline BertSentenceEmbeddings from JuanPH
+author: John Snow Labs
+name: sent_bert_adaptation_peppa_pig_juanph_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_adaptation_peppa_pig_juanph_pipeline` is a English model originally trained by JuanPH.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_peppa_pig_juanph_pipeline_en_5.5.1_3.0_1737855976748.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_peppa_pig_juanph_pipeline_en_5.5.1_3.0_1737855976748.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_adaptation_peppa_pig_juanph_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_adaptation_peppa_pig_juanph_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_adaptation_peppa_pig_juanph_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.2 MB|
+
+## References
+
+https://huggingface.co/JuanPH/bert_adaptation_peppa_pig
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_bert_adaptation_referencias_german_vinos_fabiogrigorjev_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_adaptation_referencias_german_vinos_fabiogrigorjev_en.md
new file mode 100644
index 00000000000000..ab06ab5468d4ec
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_adaptation_referencias_german_vinos_fabiogrigorjev_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_adaptation_referencias_german_vinos_fabiogrigorjev BertSentenceEmbeddings from FabioGrigorjev
+author: John Snow Labs
+name: sent_bert_adaptation_referencias_german_vinos_fabiogrigorjev
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_adaptation_referencias_german_vinos_fabiogrigorjev` is a English model originally trained by FabioGrigorjev.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_referencias_german_vinos_fabiogrigorjev_en_5.5.1_3.0_1737860573201.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_referencias_german_vinos_fabiogrigorjev_en_5.5.1_3.0_1737860573201.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_adaptation_referencias_german_vinos_fabiogrigorjev","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_adaptation_referencias_german_vinos_fabiogrigorjev","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_adaptation_referencias_german_vinos_fabiogrigorjev|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/FabioGrigorjev/bert_adaptation_referencias_de_vinos
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_bert_adaptation_referencias_german_vinos_fabiogrigorjev_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_adaptation_referencias_german_vinos_fabiogrigorjev_pipeline_en.md
new file mode 100644
index 00000000000000..992c97dda9a40d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_adaptation_referencias_german_vinos_fabiogrigorjev_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_adaptation_referencias_german_vinos_fabiogrigorjev_pipeline pipeline BertSentenceEmbeddings from FabioGrigorjev
+author: John Snow Labs
+name: sent_bert_adaptation_referencias_german_vinos_fabiogrigorjev_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_adaptation_referencias_german_vinos_fabiogrigorjev_pipeline` is a English model originally trained by FabioGrigorjev.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_referencias_german_vinos_fabiogrigorjev_pipeline_en_5.5.1_3.0_1737860595824.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_referencias_german_vinos_fabiogrigorjev_pipeline_en_5.5.1_3.0_1737860595824.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_adaptation_referencias_german_vinos_fabiogrigorjev_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_adaptation_referencias_german_vinos_fabiogrigorjev_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_adaptation_referencias_german_vinos_fabiogrigorjev_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.2 MB|
+
+## References
+
+https://huggingface.co/FabioGrigorjev/bert_adaptation_referencias_de_vinos
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_96_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_96_en.md
new file mode 100644
index 00000000000000..461fbbf6784a57
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_96_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_base_96 BertSentenceEmbeddings from gokuls
+author: John Snow Labs
+name: sent_bert_base_96
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_96` is a English model originally trained by gokuls.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_96_en_5.5.1_3.0_1737900879495.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_96_en_5.5.1_3.0_1737900879495.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_96","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_96","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_96|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|408.1 MB|
+
+## References
+
+https://huggingface.co/gokuls/bert_base_96
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_96_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_96_pipeline_en.md
new file mode 100644
index 00000000000000..70b370bce2a593
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_96_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_base_96_pipeline pipeline BertSentenceEmbeddings from gokuls
+author: John Snow Labs
+name: sent_bert_base_96_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_96_pipeline` is a English model originally trained by gokuls.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_96_pipeline_en_5.5.1_3.0_1737900900852.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_96_pipeline_en_5.5.1_3.0_1737900900852.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_base_96_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_96_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_96_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|408.6 MB|
+
+## References
+
+https://huggingface.co/gokuls/bert_base_96
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_buddhist_sanskrit_v2_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_buddhist_sanskrit_v2_en.md
new file mode 100644
index 00000000000000..b8d4b833fc4df3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_buddhist_sanskrit_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_base_buddhist_sanskrit_v2 BertSentenceEmbeddings from Matej
+author: John Snow Labs
+name: sent_bert_base_buddhist_sanskrit_v2
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_buddhist_sanskrit_v2` is a English model originally trained by Matej.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_buddhist_sanskrit_v2_en_5.5.1_3.0_1737900261760.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_buddhist_sanskrit_v2_en_5.5.1_3.0_1737900261760.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_buddhist_sanskrit_v2","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_buddhist_sanskrit_v2","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_buddhist_sanskrit_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|408.3 MB|
+
+## References
+
+https://huggingface.co/Matej/bert-base-buddhist-sanskrit-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_buddhist_sanskrit_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_buddhist_sanskrit_v2_pipeline_en.md
new file mode 100644
index 00000000000000..e5072bed302fed
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_buddhist_sanskrit_v2_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_base_buddhist_sanskrit_v2_pipeline pipeline BertSentenceEmbeddings from Matej
+author: John Snow Labs
+name: sent_bert_base_buddhist_sanskrit_v2_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_buddhist_sanskrit_v2_pipeline` is a English model originally trained by Matej.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_buddhist_sanskrit_v2_pipeline_en_5.5.1_3.0_1737900283019.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_buddhist_sanskrit_v2_pipeline_en_5.5.1_3.0_1737900283019.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_base_buddhist_sanskrit_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_buddhist_sanskrit_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_buddhist_sanskrit_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|408.9 MB|
+
+## References
+
+https://huggingface.co/Matej/bert-base-buddhist-sanskrit-v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_cased_conversational_finetuned_wallisian_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_cased_conversational_finetuned_wallisian_en.md
new file mode 100644
index 00000000000000..5dd078bd288e51
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_cased_conversational_finetuned_wallisian_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_base_cased_conversational_finetuned_wallisian BertSentenceEmbeddings from btamm12
+author: John Snow Labs
+name: sent_bert_base_cased_conversational_finetuned_wallisian
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_cased_conversational_finetuned_wallisian` is a English model originally trained by btamm12.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_cased_conversational_finetuned_wallisian_en_5.5.1_3.0_1737860320682.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_cased_conversational_finetuned_wallisian_en_5.5.1_3.0_1737860320682.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_cased_conversational_finetuned_wallisian","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_cased_conversational_finetuned_wallisian","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_cased_conversational_finetuned_wallisian|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|402.8 MB|
+
+## References
+
+https://huggingface.co/btamm12/bert-base-cased-conversational-finetuned-wls
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_cased_conversational_finetuned_wallisian_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_cased_conversational_finetuned_wallisian_pipeline_en.md
new file mode 100644
index 00000000000000..7b786e12576cf9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_cased_conversational_finetuned_wallisian_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_base_cased_conversational_finetuned_wallisian_pipeline pipeline BertSentenceEmbeddings from btamm12
+author: John Snow Labs
+name: sent_bert_base_cased_conversational_finetuned_wallisian_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_cased_conversational_finetuned_wallisian_pipeline` is a English model originally trained by btamm12.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_cased_conversational_finetuned_wallisian_pipeline_en_5.5.1_3.0_1737860341329.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_cased_conversational_finetuned_wallisian_pipeline_en_5.5.1_3.0_1737860341329.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_base_cased_conversational_finetuned_wallisian_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_cased_conversational_finetuned_wallisian_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_cased_conversational_finetuned_wallisian_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.4 MB|
+
+## References
+
+https://huggingface.co/btamm12/bert-base-cased-conversational-finetuned-wls
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_cased_finetuned_bible_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_cased_finetuned_bible_en.md
new file mode 100644
index 00000000000000..a5161c7811b50c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_cased_finetuned_bible_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_base_cased_finetuned_bible BertSentenceEmbeddings from Pragash-Mohanarajah
+author: John Snow Labs
+name: sent_bert_base_cased_finetuned_bible
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_cased_finetuned_bible` is a English model originally trained by Pragash-Mohanarajah.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_cased_finetuned_bible_en_5.5.1_3.0_1737900253943.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_cased_finetuned_bible_en_5.5.1_3.0_1737900253943.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_cased_finetuned_bible","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_cased_finetuned_bible","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_cased_finetuned_bible|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/Pragash-Mohanarajah/bert-base-cased-finetuned-bible
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_cased_finetuned_bible_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_cased_finetuned_bible_pipeline_en.md
new file mode 100644
index 00000000000000..df34f00dec657b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_cased_finetuned_bible_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_base_cased_finetuned_bible_pipeline pipeline BertSentenceEmbeddings from Pragash-Mohanarajah
+author: John Snow Labs
+name: sent_bert_base_cased_finetuned_bible_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_cased_finetuned_bible_pipeline` is a English model originally trained by Pragash-Mohanarajah.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_cased_finetuned_bible_pipeline_en_5.5.1_3.0_1737900274848.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_cased_finetuned_bible_pipeline_en_5.5.1_3.0_1737900274848.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_base_cased_finetuned_bible_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_cased_finetuned_bible_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_cased_finetuned_bible_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|404.2 MB|
+
+## References
+
+https://huggingface.co/Pragash-Mohanarajah/bert-base-cased-finetuned-bible
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_cased_wikitext2_agkelly_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_cased_wikitext2_agkelly_en.md
new file mode 100644
index 00000000000000..89f1ffe6dc0d05
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_cased_wikitext2_agkelly_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_base_cased_wikitext2_agkelly BertSentenceEmbeddings from agkelly
+author: John Snow Labs
+name: sent_bert_base_cased_wikitext2_agkelly
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_cased_wikitext2_agkelly` is a English model originally trained by agkelly.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_cased_wikitext2_agkelly_en_5.5.1_3.0_1737855900396.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_cased_wikitext2_agkelly_en_5.5.1_3.0_1737855900396.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_cased_wikitext2_agkelly","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_cased_wikitext2_agkelly","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_cased_wikitext2_agkelly|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|403.4 MB|
+
+## References
+
+https://huggingface.co/agkelly/bert-base-cased-wikitext2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_cased_wikitext2_agkelly_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_cased_wikitext2_agkelly_pipeline_en.md
new file mode 100644
index 00000000000000..ceeb4b5930f94c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_cased_wikitext2_agkelly_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_base_cased_wikitext2_agkelly_pipeline pipeline BertSentenceEmbeddings from agkelly
+author: John Snow Labs
+name: sent_bert_base_cased_wikitext2_agkelly_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_cased_wikitext2_agkelly_pipeline` is a English model originally trained by agkelly.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_cased_wikitext2_agkelly_pipeline_en_5.5.1_3.0_1737855922204.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_cased_wikitext2_agkelly_pipeline_en_5.5.1_3.0_1737855922204.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_base_cased_wikitext2_agkelly_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_cased_wikitext2_agkelly_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_cased_wikitext2_agkelly_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|404.0 MB|
+
+## References
+
+https://huggingface.co/agkelly/bert-base-cased-wikitext2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_greek_uncased_v1_finetuned_polylex_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_greek_uncased_v1_finetuned_polylex_en.md
new file mode 100644
index 00000000000000..ff2d3184ae9e3f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_greek_uncased_v1_finetuned_polylex_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_base_greek_uncased_v1_finetuned_polylex BertSentenceEmbeddings from snousias
+author: John Snow Labs
+name: sent_bert_base_greek_uncased_v1_finetuned_polylex
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_greek_uncased_v1_finetuned_polylex` is a English model originally trained by snousias.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_greek_uncased_v1_finetuned_polylex_en_5.5.1_3.0_1737859440601.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_greek_uncased_v1_finetuned_polylex_en_5.5.1_3.0_1737859440601.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_greek_uncased_v1_finetuned_polylex","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_greek_uncased_v1_finetuned_polylex","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_greek_uncased_v1_finetuned_polylex|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|421.1 MB|
+
+## References
+
+https://huggingface.co/snousias/bert-base-greek-uncased-v1-finetuned-polylex
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_greek_uncased_v1_finetuned_polylex_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_greek_uncased_v1_finetuned_polylex_pipeline_en.md
new file mode 100644
index 00000000000000..0b2499392bf6e4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_greek_uncased_v1_finetuned_polylex_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_base_greek_uncased_v1_finetuned_polylex_pipeline pipeline BertSentenceEmbeddings from snousias
+author: John Snow Labs
+name: sent_bert_base_greek_uncased_v1_finetuned_polylex_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_greek_uncased_v1_finetuned_polylex_pipeline` is a English model originally trained by snousias.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_greek_uncased_v1_finetuned_polylex_pipeline_en_5.5.1_3.0_1737859465925.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_greek_uncased_v1_finetuned_polylex_pipeline_en_5.5.1_3.0_1737859465925.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_base_greek_uncased_v1_finetuned_polylex_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_greek_uncased_v1_finetuned_polylex_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_greek_uncased_v1_finetuned_polylex_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|421.7 MB|
+
+## References
+
+https://huggingface.co/snousias/bert-base-greek-uncased-v1-finetuned-polylex
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_turkish_cased_offensive_mlm_pipeline_tr.md b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_turkish_cased_offensive_mlm_pipeline_tr.md
new file mode 100644
index 00000000000000..ee1d4de6817d9e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_turkish_cased_offensive_mlm_pipeline_tr.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Turkish sent_bert_base_turkish_cased_offensive_mlm_pipeline pipeline BertSentenceEmbeddings from Overfit-GM
+author: John Snow Labs
+name: sent_bert_base_turkish_cased_offensive_mlm_pipeline
+date: 2025-01-26
+tags: [tr, open_source, pipeline, onnx]
+task: Embeddings
+language: tr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_turkish_cased_offensive_mlm_pipeline` is a Turkish model originally trained by Overfit-GM.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_turkish_cased_offensive_mlm_pipeline_tr_5.5.1_3.0_1737859969099.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_turkish_cased_offensive_mlm_pipeline_tr_5.5.1_3.0_1737859969099.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_base_turkish_cased_offensive_mlm_pipeline", lang = "tr")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_turkish_cased_offensive_mlm_pipeline", lang = "tr")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_turkish_cased_offensive_mlm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|tr|
+|Size:|412.8 MB|
+
+## References
+
+https://huggingface.co/Overfit-GM/bert-base-turkish-cased-offensive-mlm
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_turkish_cased_offensive_mlm_tr.md b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_turkish_cased_offensive_mlm_tr.md
new file mode 100644
index 00000000000000..87b19c608041cc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_turkish_cased_offensive_mlm_tr.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Turkish sent_bert_base_turkish_cased_offensive_mlm BertSentenceEmbeddings from Overfit-GM
+author: John Snow Labs
+name: sent_bert_base_turkish_cased_offensive_mlm
+date: 2025-01-26
+tags: [tr, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: tr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_turkish_cased_offensive_mlm` is a Turkish model originally trained by Overfit-GM.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_turkish_cased_offensive_mlm_tr_5.5.1_3.0_1737859945681.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_turkish_cased_offensive_mlm_tr_5.5.1_3.0_1737859945681.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_turkish_cased_offensive_mlm","tr") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_turkish_cased_offensive_mlm","tr") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_turkish_cased_offensive_mlm|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|tr|
+|Size:|412.3 MB|
+
+## References
+
+https://huggingface.co/Overfit-GM/bert-base-turkish-cased-offensive-mlm
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_uncased_ancient_greek_v1_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_uncased_ancient_greek_v1_en.md
new file mode 100644
index 00000000000000..5639c2529f8e9d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_uncased_ancient_greek_v1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_base_uncased_ancient_greek_v1 BertSentenceEmbeddings from Sonnenblume
+author: John Snow Labs
+name: sent_bert_base_uncased_ancient_greek_v1
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_uncased_ancient_greek_v1` is a English model originally trained by Sonnenblume.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_ancient_greek_v1_en_5.5.1_3.0_1737860208001.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_ancient_greek_v1_en_5.5.1_3.0_1737860208001.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_uncased_ancient_greek_v1","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_uncased_ancient_greek_v1","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_uncased_ancient_greek_v1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|421.0 MB|
+
+## References
+
+https://huggingface.co/Sonnenblume/bert-base-uncased-ancient-greek-v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_uncased_ancient_greek_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_uncased_ancient_greek_v1_pipeline_en.md
new file mode 100644
index 00000000000000..0cad2a9e1596f6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_uncased_ancient_greek_v1_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_base_uncased_ancient_greek_v1_pipeline pipeline BertSentenceEmbeddings from Sonnenblume
+author: John Snow Labs
+name: sent_bert_base_uncased_ancient_greek_v1_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_uncased_ancient_greek_v1_pipeline` is a English model originally trained by Sonnenblume.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_ancient_greek_v1_pipeline_en_5.5.1_3.0_1737860233677.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_ancient_greek_v1_pipeline_en_5.5.1_3.0_1737860233677.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_base_uncased_ancient_greek_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_uncased_ancient_greek_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_uncased_ancient_greek_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|421.6 MB|
+
+## References
+
+https://huggingface.co/Sonnenblume/bert-base-uncased-ancient-greek-v1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_uncased_finetuned_imdb_jasheu_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_uncased_finetuned_imdb_jasheu_en.md
new file mode 100644
index 00000000000000..e74e1e411489fe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_uncased_finetuned_imdb_jasheu_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_base_uncased_finetuned_imdb_jasheu BertSentenceEmbeddings from jasheu
+author: John Snow Labs
+name: sent_bert_base_uncased_finetuned_imdb_jasheu
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_uncased_finetuned_imdb_jasheu` is a English model originally trained by jasheu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_finetuned_imdb_jasheu_en_5.5.1_3.0_1737859444479.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_finetuned_imdb_jasheu_en_5.5.1_3.0_1737859444479.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_uncased_finetuned_imdb_jasheu","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_uncased_finetuned_imdb_jasheu","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_uncased_finetuned_imdb_jasheu|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/jasheu/bert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_uncased_finetuned_imdb_jasheu_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_uncased_finetuned_imdb_jasheu_pipeline_en.md
new file mode 100644
index 00000000000000..6d0b0507e08f54
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_uncased_finetuned_imdb_jasheu_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_base_uncased_finetuned_imdb_jasheu_pipeline pipeline BertSentenceEmbeddings from jasheu
+author: John Snow Labs
+name: sent_bert_base_uncased_finetuned_imdb_jasheu_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_uncased_finetuned_imdb_jasheu_pipeline` is a English model originally trained by jasheu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_finetuned_imdb_jasheu_pipeline_en_5.5.1_3.0_1737859470970.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_finetuned_imdb_jasheu_pipeline_en_5.5.1_3.0_1737859470970.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_base_uncased_finetuned_imdb_jasheu_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_uncased_finetuned_imdb_jasheu_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_uncased_finetuned_imdb_jasheu_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.7 MB|
+
+## References
+
+https://huggingface.co/jasheu/bert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_uncased_issues_128_synpjh_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_uncased_issues_128_synpjh_en.md
new file mode 100644
index 00000000000000..ef3a07cc972744
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_uncased_issues_128_synpjh_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_base_uncased_issues_128_synpjh BertSentenceEmbeddings from synpjh
+author: John Snow Labs
+name: sent_bert_base_uncased_issues_128_synpjh
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_uncased_issues_128_synpjh` is a English model originally trained by synpjh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_issues_128_synpjh_en_5.5.1_3.0_1737860237319.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_issues_128_synpjh_en_5.5.1_3.0_1737860237319.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_uncased_issues_128_synpjh","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_uncased_issues_128_synpjh","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_uncased_issues_128_synpjh|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/synpjh/bert-base-uncased-issues-128
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_uncased_issues_128_synpjh_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_uncased_issues_128_synpjh_pipeline_en.md
new file mode 100644
index 00000000000000..270b7f7a21898d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_uncased_issues_128_synpjh_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_base_uncased_issues_128_synpjh_pipeline pipeline BertSentenceEmbeddings from synpjh
+author: John Snow Labs
+name: sent_bert_base_uncased_issues_128_synpjh_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_uncased_issues_128_synpjh_pipeline` is a English model originally trained by synpjh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_issues_128_synpjh_pipeline_en_5.5.1_3.0_1737860260096.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_issues_128_synpjh_pipeline_en_5.5.1_3.0_1737860260096.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_base_uncased_issues_128_synpjh_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_uncased_issues_128_synpjh_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_uncased_issues_128_synpjh_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.7 MB|
+
+## References
+
+https://huggingface.co/synpjh/bert-base-uncased-issues-128
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_uncased_m_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_uncased_m_en.md
new file mode 100644
index 00000000000000..760568b695c9c8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_uncased_m_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_base_uncased_m BertSentenceEmbeddings from ivanxia1988
+author: John Snow Labs
+name: sent_bert_base_uncased_m
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_uncased_m` is a English model originally trained by ivanxia1988.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_m_en_5.5.1_3.0_1737855837187.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_m_en_5.5.1_3.0_1737855837187.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_uncased_m","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_uncased_m","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_uncased_m|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/ivanxia1988/bert-base-uncased-m
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_uncased_m_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_uncased_m_pipeline_en.md
new file mode 100644
index 00000000000000..6badc545325b5a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_base_uncased_m_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_base_uncased_m_pipeline pipeline BertSentenceEmbeddings from ivanxia1988
+author: John Snow Labs
+name: sent_bert_base_uncased_m_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_uncased_m_pipeline` is a English model originally trained by ivanxia1988.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_m_pipeline_en_5.5.1_3.0_1737855857553.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_m_pipeline_en_5.5.1_3.0_1737855857553.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_base_uncased_m_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_uncased_m_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_uncased_m_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.7 MB|
+
+## References
+
+https://huggingface.co/ivanxia1988/bert-base-uncased-m
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_bert_large_mnr_mlm_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_large_mnr_mlm_en.md
new file mode 100644
index 00000000000000..9af7fe11a947ef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_large_mnr_mlm_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_large_mnr_mlm BertSentenceEmbeddings from omarelsayeed
+author: John Snow Labs
+name: sent_bert_large_mnr_mlm
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_large_mnr_mlm` is a English model originally trained by omarelsayeed.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_large_mnr_mlm_en_5.5.1_3.0_1737860446857.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_large_mnr_mlm_en_5.5.1_3.0_1737860446857.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_large_mnr_mlm","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_large_mnr_mlm","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_large_mnr_mlm|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.4 GB|
+
+## References
+
+https://huggingface.co/omarelsayeed/bert_large_mnr_mlm
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_bert_large_mnr_mlm_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_large_mnr_mlm_pipeline_en.md
new file mode 100644
index 00000000000000..ca0e70be8ace3e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_large_mnr_mlm_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_large_mnr_mlm_pipeline pipeline BertSentenceEmbeddings from omarelsayeed
+author: John Snow Labs
+name: sent_bert_large_mnr_mlm_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_large_mnr_mlm_pipeline` is a English model originally trained by omarelsayeed.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_large_mnr_mlm_pipeline_en_5.5.1_3.0_1737860530545.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_large_mnr_mlm_pipeline_en_5.5.1_3.0_1737860530545.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_large_mnr_mlm_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_large_mnr_mlm_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_large_mnr_mlm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.4 GB|
+
+## References
+
+https://huggingface.co/omarelsayeed/bert_large_mnr_mlm
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_bert_large_uncased_finetuned_clinc150_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_large_uncased_finetuned_clinc150_en.md
new file mode 100644
index 00000000000000..c55d8df9ff163e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_large_uncased_finetuned_clinc150_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_large_uncased_finetuned_clinc150 BertSentenceEmbeddings from FilippoComastri
+author: John Snow Labs
+name: sent_bert_large_uncased_finetuned_clinc150
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_large_uncased_finetuned_clinc150` is a English model originally trained by FilippoComastri.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_large_uncased_finetuned_clinc150_en_5.5.1_3.0_1737860824303.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_large_uncased_finetuned_clinc150_en_5.5.1_3.0_1737860824303.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_large_uncased_finetuned_clinc150","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_large_uncased_finetuned_clinc150","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_large_uncased_finetuned_clinc150|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/FilippoComastri/bert-large-uncased-finetuned-clinc150
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_bert_large_uncased_finetuned_clinc150_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_large_uncased_finetuned_clinc150_pipeline_en.md
new file mode 100644
index 00000000000000..cb4aa9c8497a85
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_large_uncased_finetuned_clinc150_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_large_uncased_finetuned_clinc150_pipeline pipeline BertSentenceEmbeddings from FilippoComastri
+author: John Snow Labs
+name: sent_bert_large_uncased_finetuned_clinc150_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_large_uncased_finetuned_clinc150_pipeline` is a English model originally trained by FilippoComastri.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_large_uncased_finetuned_clinc150_pipeline_en_5.5.1_3.0_1737860884244.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_large_uncased_finetuned_clinc150_pipeline_en_5.5.1_3.0_1737860884244.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_large_uncased_finetuned_clinc150_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_large_uncased_finetuned_clinc150_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_large_uncased_finetuned_clinc150_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/FilippoComastri/bert-large-uncased-finetuned-clinc150
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_bert_pretrained_litcov10k_paraphrased_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_pretrained_litcov10k_paraphrased_en.md
new file mode 100644
index 00000000000000..e046f04ed6733b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_pretrained_litcov10k_paraphrased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_pretrained_litcov10k_paraphrased BertSentenceEmbeddings from IneG
+author: John Snow Labs
+name: sent_bert_pretrained_litcov10k_paraphrased
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_pretrained_litcov10k_paraphrased` is a English model originally trained by IneG.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_pretrained_litcov10k_paraphrased_en_5.5.1_3.0_1737859902928.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_pretrained_litcov10k_paraphrased_en_5.5.1_3.0_1737859902928.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_pretrained_litcov10k_paraphrased","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_pretrained_litcov10k_paraphrased","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_pretrained_litcov10k_paraphrased|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/IneG/BERT_pretrained_litcov10K_paraphrased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_bert_pretrained_litcov10k_paraphrased_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_pretrained_litcov10k_paraphrased_pipeline_en.md
new file mode 100644
index 00000000000000..e3e94717bb9fde
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_pretrained_litcov10k_paraphrased_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_pretrained_litcov10k_paraphrased_pipeline pipeline BertSentenceEmbeddings from IneG
+author: John Snow Labs
+name: sent_bert_pretrained_litcov10k_paraphrased_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_pretrained_litcov10k_paraphrased_pipeline` is a English model originally trained by IneG.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_pretrained_litcov10k_paraphrased_pipeline_en_5.5.1_3.0_1737859923703.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_pretrained_litcov10k_paraphrased_pipeline_en_5.5.1_3.0_1737859923703.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_pretrained_litcov10k_paraphrased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_pretrained_litcov10k_paraphrased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_pretrained_litcov10k_paraphrased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.7 MB|
+
+## References
+
+https://huggingface.co/IneG/BERT_pretrained_litcov10K_paraphrased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_bert_small_finetuned_legal_contracts_larger4010_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_small_finetuned_legal_contracts_larger4010_en.md
new file mode 100644
index 00000000000000..a185da42954397
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_small_finetuned_legal_contracts_larger4010_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_small_finetuned_legal_contracts_larger4010 BertSentenceEmbeddings from muhtasham
+author: John Snow Labs
+name: sent_bert_small_finetuned_legal_contracts_larger4010
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_small_finetuned_legal_contracts_larger4010` is a English model originally trained by muhtasham.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_small_finetuned_legal_contracts_larger4010_en_5.5.1_3.0_1737900397320.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_small_finetuned_legal_contracts_larger4010_en_5.5.1_3.0_1737900397320.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_small_finetuned_legal_contracts_larger4010","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_small_finetuned_legal_contracts_larger4010","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_small_finetuned_legal_contracts_larger4010|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|107.0 MB|
+
+## References
+
+https://huggingface.co/muhtasham/bert-small-finetuned-legal-contracts-larger4010
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_bert_small_finetuned_legal_contracts_larger4010_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_small_finetuned_legal_contracts_larger4010_pipeline_en.md
new file mode 100644
index 00000000000000..fd04b671bbd31e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_small_finetuned_legal_contracts_larger4010_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_small_finetuned_legal_contracts_larger4010_pipeline pipeline BertSentenceEmbeddings from muhtasham
+author: John Snow Labs
+name: sent_bert_small_finetuned_legal_contracts_larger4010_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_small_finetuned_legal_contracts_larger4010_pipeline` is a English model originally trained by muhtasham.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_small_finetuned_legal_contracts_larger4010_pipeline_en_5.5.1_3.0_1737900402361.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_small_finetuned_legal_contracts_larger4010_pipeline_en_5.5.1_3.0_1737900402361.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_small_finetuned_legal_contracts_larger4010_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_small_finetuned_legal_contracts_larger4010_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_small_finetuned_legal_contracts_larger4010_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|107.5 MB|
+
+## References
+
+https://huggingface.co/muhtasham/bert-small-finetuned-legal-contracts-larger4010
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_bert_small_finetuned_legal_definitions_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_small_finetuned_legal_definitions_en.md
new file mode 100644
index 00000000000000..5ae008c1a8cd8c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_small_finetuned_legal_definitions_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_small_finetuned_legal_definitions BertSentenceEmbeddings from muhtasham
+author: John Snow Labs
+name: sent_bert_small_finetuned_legal_definitions
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_small_finetuned_legal_definitions` is a English model originally trained by muhtasham.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_small_finetuned_legal_definitions_en_5.5.1_3.0_1737856026849.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_small_finetuned_legal_definitions_en_5.5.1_3.0_1737856026849.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_small_finetuned_legal_definitions","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_small_finetuned_legal_definitions","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_small_finetuned_legal_definitions|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|107.0 MB|
+
+## References
+
+https://huggingface.co/muhtasham/bert-small-finetuned-legal-definitions
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_bert_small_finetuned_legal_definitions_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_small_finetuned_legal_definitions_pipeline_en.md
new file mode 100644
index 00000000000000..996391257e54d1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_small_finetuned_legal_definitions_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_small_finetuned_legal_definitions_pipeline pipeline BertSentenceEmbeddings from muhtasham
+author: John Snow Labs
+name: sent_bert_small_finetuned_legal_definitions_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_small_finetuned_legal_definitions_pipeline` is a English model originally trained by muhtasham.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_small_finetuned_legal_definitions_pipeline_en_5.5.1_3.0_1737856032676.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_small_finetuned_legal_definitions_pipeline_en_5.5.1_3.0_1737856032676.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_small_finetuned_legal_definitions_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_small_finetuned_legal_definitions_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_small_finetuned_legal_definitions_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|107.5 MB|
+
+## References
+
+https://huggingface.co/muhtasham/bert-small-finetuned-legal-definitions
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_bert_uncased_l_2_h_256_a_4_mlm_multi_emails_hq_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_uncased_l_2_h_256_a_4_mlm_multi_emails_hq_en.md
new file mode 100644
index 00000000000000..0dfd8ac997bb99
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_uncased_l_2_h_256_a_4_mlm_multi_emails_hq_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_uncased_l_2_h_256_a_4_mlm_multi_emails_hq BertSentenceEmbeddings from postbot
+author: John Snow Labs
+name: sent_bert_uncased_l_2_h_256_a_4_mlm_multi_emails_hq
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_uncased_l_2_h_256_a_4_mlm_multi_emails_hq` is a English model originally trained by postbot.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_uncased_l_2_h_256_a_4_mlm_multi_emails_hq_en_5.5.1_3.0_1737855948286.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_uncased_l_2_h_256_a_4_mlm_multi_emails_hq_en_5.5.1_3.0_1737855948286.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_uncased_l_2_h_256_a_4_mlm_multi_emails_hq","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_uncased_l_2_h_256_a_4_mlm_multi_emails_hq","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_uncased_l_2_h_256_a_4_mlm_multi_emails_hq|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|35.9 MB|
+
+## References
+
+https://huggingface.co/postbot/bert_uncased_L-2_H-256_A-4-mlm-multi-emails-hq
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_bert_uncased_l_2_h_256_a_4_mlm_multi_emails_hq_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_uncased_l_2_h_256_a_4_mlm_multi_emails_hq_pipeline_en.md
new file mode 100644
index 00000000000000..27d23c92a92b49
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_bert_uncased_l_2_h_256_a_4_mlm_multi_emails_hq_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_uncased_l_2_h_256_a_4_mlm_multi_emails_hq_pipeline pipeline BertSentenceEmbeddings from postbot
+author: John Snow Labs
+name: sent_bert_uncased_l_2_h_256_a_4_mlm_multi_emails_hq_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_uncased_l_2_h_256_a_4_mlm_multi_emails_hq_pipeline` is a English model originally trained by postbot.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_uncased_l_2_h_256_a_4_mlm_multi_emails_hq_pipeline_en_5.5.1_3.0_1737855950368.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_uncased_l_2_h_256_a_4_mlm_multi_emails_hq_pipeline_en_5.5.1_3.0_1737855950368.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_uncased_l_2_h_256_a_4_mlm_multi_emails_hq_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_uncased_l_2_h_256_a_4_mlm_multi_emails_hq_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_uncased_l_2_h_256_a_4_mlm_multi_emails_hq_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|36.5 MB|
+
+## References
+
+https://huggingface.co/postbot/bert_uncased_L-2_H-256_A-4-mlm-multi-emails-hq
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_bertskill_relative_key_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_bertskill_relative_key_en.md
new file mode 100644
index 00000000000000..a721baa85657d4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_bertskill_relative_key_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bertskill_relative_key BertSentenceEmbeddings from meilanynonsitentua
+author: John Snow Labs
+name: sent_bertskill_relative_key
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bertskill_relative_key` is a English model originally trained by meilanynonsitentua.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bertskill_relative_key_en_5.5.1_3.0_1737856076342.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bertskill_relative_key_en_5.5.1_3.0_1737856076342.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bertskill_relative_key","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bertskill_relative_key","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bertskill_relative_key|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|413.8 MB|
+
+## References
+
+https://huggingface.co/meilanynonsitentua/bertskill-relative-key
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_bertskill_relative_key_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_bertskill_relative_key_pipeline_en.md
new file mode 100644
index 00000000000000..4de2c946608a70
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_bertskill_relative_key_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bertskill_relative_key_pipeline pipeline BertSentenceEmbeddings from meilanynonsitentua
+author: John Snow Labs
+name: sent_bertskill_relative_key_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bertskill_relative_key_pipeline` is a English model originally trained by meilanynonsitentua.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bertskill_relative_key_pipeline_en_5.5.1_3.0_1737856098122.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bertskill_relative_key_pipeline_en_5.5.1_3.0_1737856098122.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bertskill_relative_key_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bertskill_relative_key_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bertskill_relative_key_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|414.3 MB|
+
+## References
+
+https://huggingface.co/meilanynonsitentua/bertskill-relative-key
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_bertturk_ottoman_raw_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_bertturk_ottoman_raw_en.md
new file mode 100644
index 00000000000000..027e006280d696
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_bertturk_ottoman_raw_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bertturk_ottoman_raw BertSentenceEmbeddings from onurkeles
+author: John Snow Labs
+name: sent_bertturk_ottoman_raw
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bertturk_ottoman_raw` is a English model originally trained by onurkeles.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bertturk_ottoman_raw_en_5.5.1_3.0_1737855781935.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bertturk_ottoman_raw_en_5.5.1_3.0_1737855781935.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bertturk_ottoman_raw","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bertturk_ottoman_raw","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bertturk_ottoman_raw|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|412.0 MB|
+
+## References
+
+https://huggingface.co/onurkeles/bertturk-ottoman-raw
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_bertturk_ottoman_raw_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_bertturk_ottoman_raw_pipeline_en.md
new file mode 100644
index 00000000000000..f2262206180e76
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_bertturk_ottoman_raw_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bertturk_ottoman_raw_pipeline pipeline BertSentenceEmbeddings from onurkeles
+author: John Snow Labs
+name: sent_bertturk_ottoman_raw_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bertturk_ottoman_raw_pipeline` is a English model originally trained by onurkeles.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bertturk_ottoman_raw_pipeline_en_5.5.1_3.0_1737855802346.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bertturk_ottoman_raw_pipeline_en_5.5.1_3.0_1737855802346.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bertturk_ottoman_raw_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bertturk_ottoman_raw_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bertturk_ottoman_raw_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|412.5 MB|
+
+## References
+
+https://huggingface.co/onurkeles/bertturk-ottoman-raw
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_cardiobertpt_pipeline_pt.md b/docs/_posts/ahmedlone127/2025-01-26-sent_cardiobertpt_pipeline_pt.md
new file mode 100644
index 00000000000000..8f73d8db2f645e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_cardiobertpt_pipeline_pt.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Portuguese sent_cardiobertpt_pipeline pipeline BertSentenceEmbeddings from pucpr-br
+author: John Snow Labs
+name: sent_cardiobertpt_pipeline
+date: 2025-01-26
+tags: [pt, open_source, pipeline, onnx]
+task: Embeddings
+language: pt
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_cardiobertpt_pipeline` is a Portuguese model originally trained by pucpr-br.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_cardiobertpt_pipeline_pt_5.5.1_3.0_1737856693438.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_cardiobertpt_pipeline_pt_5.5.1_3.0_1737856693438.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_cardiobertpt_pipeline", lang = "pt")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_cardiobertpt_pipeline", lang = "pt")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_cardiobertpt_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|pt|
+|Size:|663.3 MB|
+
+## References
+
+https://huggingface.co/pucpr-br/cardiobertpt
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_cardiobertpt_pt.md b/docs/_posts/ahmedlone127/2025-01-26-sent_cardiobertpt_pt.md
new file mode 100644
index 00000000000000..b3ce5a49c8bcd9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_cardiobertpt_pt.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Portuguese sent_cardiobertpt BertSentenceEmbeddings from pucpr-br
+author: John Snow Labs
+name: sent_cardiobertpt
+date: 2025-01-26
+tags: [pt, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: pt
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_cardiobertpt` is a Portuguese model originally trained by pucpr-br.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_cardiobertpt_pt_5.5.1_3.0_1737856660089.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_cardiobertpt_pt_5.5.1_3.0_1737856660089.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_cardiobertpt","pt") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_cardiobertpt","pt") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_cardiobertpt|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|pt|
+|Size:|662.7 MB|
+
+## References
+
+https://huggingface.co/pucpr-br/cardiobertpt
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_chungli_ao_mbert_news_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_chungli_ao_mbert_news_en.md
new file mode 100644
index 00000000000000..8ef293f5ab7ca1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_chungli_ao_mbert_news_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_chungli_ao_mbert_news BertSentenceEmbeddings from N1ch0
+author: John Snow Labs
+name: sent_chungli_ao_mbert_news
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_chungli_ao_mbert_news` is a English model originally trained by N1ch0.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_chungli_ao_mbert_news_en_5.5.1_3.0_1737860045217.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_chungli_ao_mbert_news_en_5.5.1_3.0_1737860045217.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_chungli_ao_mbert_news","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_chungli_ao_mbert_news","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_chungli_ao_mbert_news|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|665.0 MB|
+
+## References
+
+https://huggingface.co/N1ch0/chungli-ao-mBERT-news
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_chungli_ao_mbert_news_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_chungli_ao_mbert_news_pipeline_en.md
new file mode 100644
index 00000000000000..15318e59943b80
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_chungli_ao_mbert_news_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_chungli_ao_mbert_news_pipeline pipeline BertSentenceEmbeddings from N1ch0
+author: John Snow Labs
+name: sent_chungli_ao_mbert_news_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_chungli_ao_mbert_news_pipeline` is a English model originally trained by N1ch0.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_chungli_ao_mbert_news_pipeline_en_5.5.1_3.0_1737860079335.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_chungli_ao_mbert_news_pipeline_en_5.5.1_3.0_1737860079335.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_chungli_ao_mbert_news_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_chungli_ao_mbert_news_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_chungli_ao_mbert_news_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|665.6 MB|
+
+## References
+
+https://huggingface.co/N1ch0/chungli-ao-mBERT-news
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_colbert_bertnsp_600_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_colbert_bertnsp_600_en.md
new file mode 100644
index 00000000000000..f48a59c089ec8e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_colbert_bertnsp_600_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_colbert_bertnsp_600 BertSentenceEmbeddings from approach0
+author: John Snow Labs
+name: sent_colbert_bertnsp_600
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_colbert_bertnsp_600` is a English model originally trained by approach0.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_colbert_bertnsp_600_en_5.5.1_3.0_1737860193874.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_colbert_bertnsp_600_en_5.5.1_3.0_1737860193874.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_colbert_bertnsp_600","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_colbert_bertnsp_600","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_colbert_bertnsp_600|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|409.8 MB|
+
+## References
+
+https://huggingface.co/approach0/colbert-bertnsp-600
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_colbert_bertnsp_600_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_colbert_bertnsp_600_pipeline_en.md
new file mode 100644
index 00000000000000..a6a5aaf8e36ead
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_colbert_bertnsp_600_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_colbert_bertnsp_600_pipeline pipeline BertSentenceEmbeddings from approach0
+author: John Snow Labs
+name: sent_colbert_bertnsp_600_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_colbert_bertnsp_600_pipeline` is a English model originally trained by approach0.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_colbert_bertnsp_600_pipeline_en_5.5.1_3.0_1737860216591.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_colbert_bertnsp_600_pipeline_en_5.5.1_3.0_1737860216591.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_colbert_bertnsp_600_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_colbert_bertnsp_600_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_colbert_bertnsp_600_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.4 MB|
+
+## References
+
+https://huggingface.co/approach0/colbert-bertnsp-600
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_colbertgecko_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_colbertgecko_en.md
new file mode 100644
index 00000000000000..0fcef5b7150145
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_colbertgecko_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_colbertgecko BertSentenceEmbeddings from JoniJoniAl
+author: John Snow Labs
+name: sent_colbertgecko
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_colbertgecko` is a English model originally trained by JoniJoniAl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_colbertgecko_en_5.5.1_3.0_1737860066966.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_colbertgecko_en_5.5.1_3.0_1737860066966.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_colbertgecko","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_colbertgecko","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_colbertgecko|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/JoniJoniAl/ColBERTGecko
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_colbertgecko_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_colbertgecko_pipeline_en.md
new file mode 100644
index 00000000000000..ae29b4c10a4c9c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_colbertgecko_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_colbertgecko_pipeline pipeline BertSentenceEmbeddings from JoniJoniAl
+author: John Snow Labs
+name: sent_colbertgecko_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_colbertgecko_pipeline` is a English model originally trained by JoniJoniAl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_colbertgecko_pipeline_en_5.5.1_3.0_1737860088376.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_colbertgecko_pipeline_en_5.5.1_3.0_1737860088376.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_colbertgecko_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_colbertgecko_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_colbertgecko_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.3 MB|
+
+## References
+
+https://huggingface.co/JoniJoniAl/ColBERTGecko
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_convbert_base_turkish_cased_offensive_mlm_pipeline_tr.md b/docs/_posts/ahmedlone127/2025-01-26-sent_convbert_base_turkish_cased_offensive_mlm_pipeline_tr.md
new file mode 100644
index 00000000000000..bb9cdabcceacfc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_convbert_base_turkish_cased_offensive_mlm_pipeline_tr.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Turkish sent_convbert_base_turkish_cased_offensive_mlm_pipeline pipeline BertSentenceEmbeddings from Overfit-GM
+author: John Snow Labs
+name: sent_convbert_base_turkish_cased_offensive_mlm_pipeline
+date: 2025-01-26
+tags: [tr, open_source, pipeline, onnx]
+task: Embeddings
+language: tr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_convbert_base_turkish_cased_offensive_mlm_pipeline` is a Turkish model originally trained by Overfit-GM.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_convbert_base_turkish_cased_offensive_mlm_pipeline_tr_5.5.1_3.0_1737900470737.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_convbert_base_turkish_cased_offensive_mlm_pipeline_tr_5.5.1_3.0_1737900470737.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_convbert_base_turkish_cased_offensive_mlm_pipeline", lang = "tr")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_convbert_base_turkish_cased_offensive_mlm_pipeline", lang = "tr")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_convbert_base_turkish_cased_offensive_mlm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|tr|
+|Size:|400.6 MB|
+
+## References
+
+https://huggingface.co/Overfit-GM/convbert-base-turkish-cased-offensive-mlm
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_convbert_base_turkish_cased_offensive_mlm_tr.md b/docs/_posts/ahmedlone127/2025-01-26-sent_convbert_base_turkish_cased_offensive_mlm_tr.md
new file mode 100644
index 00000000000000..38e563c356883d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_convbert_base_turkish_cased_offensive_mlm_tr.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Turkish sent_convbert_base_turkish_cased_offensive_mlm BertSentenceEmbeddings from Overfit-GM
+author: John Snow Labs
+name: sent_convbert_base_turkish_cased_offensive_mlm
+date: 2025-01-26
+tags: [tr, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: tr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_convbert_base_turkish_cased_offensive_mlm` is a Turkish model originally trained by Overfit-GM.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_convbert_base_turkish_cased_offensive_mlm_tr_5.5.1_3.0_1737900449651.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_convbert_base_turkish_cased_offensive_mlm_tr_5.5.1_3.0_1737900449651.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_convbert_base_turkish_cased_offensive_mlm","tr") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_convbert_base_turkish_cased_offensive_mlm","tr") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_convbert_base_turkish_cased_offensive_mlm|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|tr|
+|Size:|400.1 MB|
+
+## References
+
+https://huggingface.co/Overfit-GM/convbert-base-turkish-cased-offensive-mlm
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_dpr_bertnsp_520_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_dpr_bertnsp_520_en.md
new file mode 100644
index 00000000000000..b76417df0fd3cb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_dpr_bertnsp_520_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_dpr_bertnsp_520 BertSentenceEmbeddings from approach0
+author: John Snow Labs
+name: sent_dpr_bertnsp_520
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_dpr_bertnsp_520` is a English model originally trained by approach0.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_dpr_bertnsp_520_en_5.5.1_3.0_1737859679588.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_dpr_bertnsp_520_en_5.5.1_3.0_1737859679588.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_dpr_bertnsp_520","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_dpr_bertnsp_520","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_dpr_bertnsp_520|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|409.8 MB|
+
+## References
+
+https://huggingface.co/approach0/dpr-bertnsp-520
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_dpr_bertnsp_520_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_dpr_bertnsp_520_pipeline_en.md
new file mode 100644
index 00000000000000..ce15d5f7b3a86e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_dpr_bertnsp_520_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_dpr_bertnsp_520_pipeline pipeline BertSentenceEmbeddings from approach0
+author: John Snow Labs
+name: sent_dpr_bertnsp_520_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_dpr_bertnsp_520_pipeline` is a English model originally trained by approach0.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_dpr_bertnsp_520_pipeline_en_5.5.1_3.0_1737859701606.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_dpr_bertnsp_520_pipeline_en_5.5.1_3.0_1737859701606.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_dpr_bertnsp_520_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_dpr_bertnsp_520_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_dpr_bertnsp_520_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.4 MB|
+
+## References
+
+https://huggingface.co/approach0/dpr-bertnsp-520
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_dpr_cotbert_320_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_dpr_cotbert_320_en.md
new file mode 100644
index 00000000000000..6d0d45865f427c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_dpr_cotbert_320_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_dpr_cotbert_320 BertSentenceEmbeddings from approach0
+author: John Snow Labs
+name: sent_dpr_cotbert_320
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_dpr_cotbert_320` is a English model originally trained by approach0.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_dpr_cotbert_320_en_5.5.1_3.0_1737860663964.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_dpr_cotbert_320_en_5.5.1_3.0_1737860663964.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_dpr_cotbert_320","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_dpr_cotbert_320","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_dpr_cotbert_320|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|409.8 MB|
+
+## References
+
+https://huggingface.co/approach0/dpr-cotbert-320
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_dpr_cotbert_320_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_dpr_cotbert_320_pipeline_en.md
new file mode 100644
index 00000000000000..1655cc9c1bdaf6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_dpr_cotbert_320_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_dpr_cotbert_320_pipeline pipeline BertSentenceEmbeddings from approach0
+author: John Snow Labs
+name: sent_dpr_cotbert_320_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_dpr_cotbert_320_pipeline` is a English model originally trained by approach0.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_dpr_cotbert_320_pipeline_en_5.5.1_3.0_1737860687460.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_dpr_cotbert_320_pipeline_en_5.5.1_3.0_1737860687460.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_dpr_cotbert_320_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_dpr_cotbert_320_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_dpr_cotbert_320_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.3 MB|
+
+## References
+
+https://huggingface.co/approach0/dpr-cotbert-320
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_dummy_model_xbb123456_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_dummy_model_xbb123456_en.md
new file mode 100644
index 00000000000000..463b396d2b60b9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_dummy_model_xbb123456_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_dummy_model_xbb123456 BertSentenceEmbeddings from xbb123456
+author: John Snow Labs
+name: sent_dummy_model_xbb123456
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_dummy_model_xbb123456` is a English model originally trained by xbb123456.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_dummy_model_xbb123456_en_5.5.1_3.0_1737860585974.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_dummy_model_xbb123456_en_5.5.1_3.0_1737860585974.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_dummy_model_xbb123456","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_dummy_model_xbb123456","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_dummy_model_xbb123456|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/xbb123456/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_dummy_model_xbb123456_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_dummy_model_xbb123456_pipeline_en.md
new file mode 100644
index 00000000000000..0303fb3502b974
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_dummy_model_xbb123456_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_dummy_model_xbb123456_pipeline pipeline BertSentenceEmbeddings from xbb123456
+author: John Snow Labs
+name: sent_dummy_model_xbb123456_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_dummy_model_xbb123456_pipeline` is a English model originally trained by xbb123456.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_dummy_model_xbb123456_pipeline_en_5.5.1_3.0_1737860611824.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_dummy_model_xbb123456_pipeline_en_5.5.1_3.0_1737860611824.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_dummy_model_xbb123456_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_dummy_model_xbb123456_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_dummy_model_xbb123456_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.7 MB|
+
+## References
+
+https://huggingface.co/xbb123456/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_extended_mbert_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_extended_mbert_en.md
new file mode 100644
index 00000000000000..0197dfe1f9bb28
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_extended_mbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_extended_mbert BertSentenceEmbeddings from mehdie
+author: John Snow Labs
+name: sent_extended_mbert
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_extended_mbert` is a English model originally trained by mehdie.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_extended_mbert_en_5.5.1_3.0_1737856483661.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_extended_mbert_en_5.5.1_3.0_1737856483661.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_extended_mbert","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_extended_mbert","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_extended_mbert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|625.5 MB|
+
+## References
+
+https://huggingface.co/mehdie/Extended-mBERT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_extended_mbert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_extended_mbert_pipeline_en.md
new file mode 100644
index 00000000000000..5533f138050fac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_extended_mbert_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_extended_mbert_pipeline pipeline BertSentenceEmbeddings from mehdie
+author: John Snow Labs
+name: sent_extended_mbert_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_extended_mbert_pipeline` is a English model originally trained by mehdie.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_extended_mbert_pipeline_en_5.5.1_3.0_1737856514462.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_extended_mbert_pipeline_en_5.5.1_3.0_1737856514462.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_extended_mbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_extended_mbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_extended_mbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|626.1 MB|
+
+## References
+
+https://huggingface.co/mehdie/Extended-mBERT
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_fine_tuned_bert_for_liquidity_q_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_fine_tuned_bert_for_liquidity_q_en.md
new file mode 100644
index 00000000000000..fa3c88a468b193
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_fine_tuned_bert_for_liquidity_q_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_fine_tuned_bert_for_liquidity_q BertSentenceEmbeddings from punchnami
+author: John Snow Labs
+name: sent_fine_tuned_bert_for_liquidity_q
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_fine_tuned_bert_for_liquidity_q` is a English model originally trained by punchnami.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_fine_tuned_bert_for_liquidity_q_en_5.5.1_3.0_1737900467684.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_fine_tuned_bert_for_liquidity_q_en_5.5.1_3.0_1737900467684.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_fine_tuned_bert_for_liquidity_q","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_fine_tuned_bert_for_liquidity_q","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_fine_tuned_bert_for_liquidity_q|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/punchnami/fine-tuned-BERT-for-liquidity-q
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_fine_tuned_bert_for_liquidity_q_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_fine_tuned_bert_for_liquidity_q_pipeline_en.md
new file mode 100644
index 00000000000000..1fde21437a6eca
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_fine_tuned_bert_for_liquidity_q_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_fine_tuned_bert_for_liquidity_q_pipeline pipeline BertSentenceEmbeddings from punchnami
+author: John Snow Labs
+name: sent_fine_tuned_bert_for_liquidity_q_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_fine_tuned_bert_for_liquidity_q_pipeline` is a English model originally trained by punchnami.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_fine_tuned_bert_for_liquidity_q_pipeline_en_5.5.1_3.0_1737900489091.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_fine_tuned_bert_for_liquidity_q_pipeline_en_5.5.1_3.0_1737900489091.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_fine_tuned_bert_for_liquidity_q_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_fine_tuned_bert_for_liquidity_q_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_fine_tuned_bert_for_liquidity_q_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.7 MB|
+
+## References
+
+https://huggingface.co/punchnami/fine-tuned-BERT-for-liquidity-q
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_finetuned_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_finetuned_en.md
new file mode 100644
index 00000000000000..70ddccc1c3c0a7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_finetuned_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_finetuned BertSentenceEmbeddings from PaawanPurdhani
+author: John Snow Labs
+name: sent_finetuned
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_finetuned` is a English model originally trained by PaawanPurdhani.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_finetuned_en_5.5.1_3.0_1737856379338.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_finetuned_en_5.5.1_3.0_1737856379338.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_finetuned","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_finetuned","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_finetuned|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/PaawanPurdhani/Finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_finetuned_pipeline_en.md
new file mode 100644
index 00000000000000..d9e0551f18be89
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_finetuned_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_finetuned_pipeline pipeline BertSentenceEmbeddings from PaawanPurdhani
+author: John Snow Labs
+name: sent_finetuned_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_finetuned_pipeline` is a English model originally trained by PaawanPurdhani.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_finetuned_pipeline_en_5.5.1_3.0_1737856400765.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_finetuned_pipeline_en_5.5.1_3.0_1737856400765.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_finetuned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_finetuned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_finetuned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.7 MB|
+
+## References
+
+https://huggingface.co/PaawanPurdhani/Finetuned
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_google_bert_base_uncased_finetuned_yelp_accelerate_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_google_bert_base_uncased_finetuned_yelp_accelerate_en.md
new file mode 100644
index 00000000000000..696001acc0d153
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_google_bert_base_uncased_finetuned_yelp_accelerate_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_google_bert_base_uncased_finetuned_yelp_accelerate BertSentenceEmbeddings from adheebhussain
+author: John Snow Labs
+name: sent_google_bert_base_uncased_finetuned_yelp_accelerate
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_google_bert_base_uncased_finetuned_yelp_accelerate` is a English model originally trained by adheebhussain.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_google_bert_base_uncased_finetuned_yelp_accelerate_en_5.5.1_3.0_1737859848905.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_google_bert_base_uncased_finetuned_yelp_accelerate_en_5.5.1_3.0_1737859848905.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_google_bert_base_uncased_finetuned_yelp_accelerate","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_google_bert_base_uncased_finetuned_yelp_accelerate","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_google_bert_base_uncased_finetuned_yelp_accelerate|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/adheebhussain/google-bert-base-uncased-finetuned-yelp-accelerate
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_google_bert_base_uncased_finetuned_yelp_accelerate_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_google_bert_base_uncased_finetuned_yelp_accelerate_pipeline_en.md
new file mode 100644
index 00000000000000..fc926e74a9e4f5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_google_bert_base_uncased_finetuned_yelp_accelerate_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_google_bert_base_uncased_finetuned_yelp_accelerate_pipeline pipeline BertSentenceEmbeddings from adheebhussain
+author: John Snow Labs
+name: sent_google_bert_base_uncased_finetuned_yelp_accelerate_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_google_bert_base_uncased_finetuned_yelp_accelerate_pipeline` is a English model originally trained by adheebhussain.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_google_bert_base_uncased_finetuned_yelp_accelerate_pipeline_en_5.5.1_3.0_1737859868980.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_google_bert_base_uncased_finetuned_yelp_accelerate_pipeline_en_5.5.1_3.0_1737859868980.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_google_bert_base_uncased_finetuned_yelp_accelerate_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_google_bert_base_uncased_finetuned_yelp_accelerate_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_google_bert_base_uncased_finetuned_yelp_accelerate_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.7 MB|
+
+## References
+
+https://huggingface.co/adheebhussain/google-bert-base-uncased-finetuned-yelp-accelerate
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_incel_bert_base_multilingual_cased_627k_italian_pipeline_xx.md b/docs/_posts/ahmedlone127/2025-01-26-sent_incel_bert_base_multilingual_cased_627k_italian_pipeline_xx.md
new file mode 100644
index 00000000000000..6d72c41b6f7d84
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_incel_bert_base_multilingual_cased_627k_italian_pipeline_xx.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Multilingual sent_incel_bert_base_multilingual_cased_627k_italian_pipeline pipeline BertSentenceEmbeddings from pgajo
+author: John Snow Labs
+name: sent_incel_bert_base_multilingual_cased_627k_italian_pipeline
+date: 2025-01-26
+tags: [xx, open_source, pipeline, onnx]
+task: Embeddings
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_incel_bert_base_multilingual_cased_627k_italian_pipeline` is a Multilingual model originally trained by pgajo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_incel_bert_base_multilingual_cased_627k_italian_pipeline_xx_5.5.1_3.0_1737859706180.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_incel_bert_base_multilingual_cased_627k_italian_pipeline_xx_5.5.1_3.0_1737859706180.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_incel_bert_base_multilingual_cased_627k_italian_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_incel_bert_base_multilingual_cased_627k_italian_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_incel_bert_base_multilingual_cased_627k_italian_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|665.6 MB|
+
+## References
+
+https://huggingface.co/pgajo/incel-bert-base-multilingual-cased-627k_italian
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_incel_bert_base_multilingual_cased_627k_italian_xx.md b/docs/_posts/ahmedlone127/2025-01-26-sent_incel_bert_base_multilingual_cased_627k_italian_xx.md
new file mode 100644
index 00000000000000..33a9899385bd15
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_incel_bert_base_multilingual_cased_627k_italian_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual sent_incel_bert_base_multilingual_cased_627k_italian BertSentenceEmbeddings from pgajo
+author: John Snow Labs
+name: sent_incel_bert_base_multilingual_cased_627k_italian
+date: 2025-01-26
+tags: [xx, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_incel_bert_base_multilingual_cased_627k_italian` is a Multilingual model originally trained by pgajo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_incel_bert_base_multilingual_cased_627k_italian_xx_5.5.1_3.0_1737859669634.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_incel_bert_base_multilingual_cased_627k_italian_xx_5.5.1_3.0_1737859669634.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_incel_bert_base_multilingual_cased_627k_italian","xx") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_incel_bert_base_multilingual_cased_627k_italian","xx") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_incel_bert_base_multilingual_cased_627k_italian|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|xx|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/pgajo/incel-bert-base-multilingual-cased-627k_italian
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_incel_mbert_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_incel_mbert_en.md
new file mode 100644
index 00000000000000..40d98e81e1044a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_incel_mbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_incel_mbert BertSentenceEmbeddings from pgajo
+author: John Snow Labs
+name: sent_incel_mbert
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_incel_mbert` is a English model originally trained by pgajo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_incel_mbert_en_5.5.1_3.0_1737860494037.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_incel_mbert_en_5.5.1_3.0_1737860494037.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_incel_mbert","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_incel_mbert","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_incel_mbert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/pgajo/incel-mbert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_incel_mbert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_incel_mbert_pipeline_en.md
new file mode 100644
index 00000000000000..67a62b2778abf2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_incel_mbert_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_incel_mbert_pipeline pipeline BertSentenceEmbeddings from pgajo
+author: John Snow Labs
+name: sent_incel_mbert_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_incel_mbert_pipeline` is a English model originally trained by pgajo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_incel_mbert_pipeline_en_5.5.1_3.0_1737860527391.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_incel_mbert_pipeline_en_5.5.1_3.0_1737860527391.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_incel_mbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_incel_mbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_incel_mbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|665.6 MB|
+
+## References
+
+https://huggingface.co/pgajo/incel-mbert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_itd_bert_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_itd_bert_en.md
new file mode 100644
index 00000000000000..9518a16cd09c31
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_itd_bert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_itd_bert BertSentenceEmbeddings from melll-uff
+author: John Snow Labs
+name: sent_itd_bert
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_itd_bert` is a English model originally trained by melll-uff.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_itd_bert_en_5.5.1_3.0_1737860100875.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_itd_bert_en_5.5.1_3.0_1737860100875.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_itd_bert","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_itd_bert","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_itd_bert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|405.3 MB|
+
+## References
+
+https://huggingface.co/melll-uff/itd_bert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_itd_bert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_itd_bert_pipeline_en.md
new file mode 100644
index 00000000000000..bb0b5055275e1e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_itd_bert_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_itd_bert_pipeline pipeline BertSentenceEmbeddings from melll-uff
+author: John Snow Labs
+name: sent_itd_bert_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_itd_bert_pipeline` is a English model originally trained by melll-uff.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_itd_bert_pipeline_en_5.5.1_3.0_1737860122509.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_itd_bert_pipeline_en_5.5.1_3.0_1737860122509.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_itd_bert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_itd_bert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_itd_bert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|405.9 MB|
+
+## References
+
+https://huggingface.co/melll-uff/itd_bert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_kinyabert_small_pretrained_kinyarwanda_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_kinyabert_small_pretrained_kinyarwanda_en.md
new file mode 100644
index 00000000000000..64b6151be79d04
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_kinyabert_small_pretrained_kinyarwanda_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_kinyabert_small_pretrained_kinyarwanda BertSentenceEmbeddings from RogerB
+author: John Snow Labs
+name: sent_kinyabert_small_pretrained_kinyarwanda
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_kinyabert_small_pretrained_kinyarwanda` is a English model originally trained by RogerB.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_kinyabert_small_pretrained_kinyarwanda_en_5.5.1_3.0_1737859965084.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_kinyabert_small_pretrained_kinyarwanda_en_5.5.1_3.0_1737859965084.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_kinyabert_small_pretrained_kinyarwanda","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_kinyabert_small_pretrained_kinyarwanda","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_kinyabert_small_pretrained_kinyarwanda|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|247.4 MB|
+
+## References
+
+https://huggingface.co/RogerB/KinyaBERT-small-pretrained-kinyarwanda
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_kinyabert_small_pretrained_kinyarwanda_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_kinyabert_small_pretrained_kinyarwanda_pipeline_en.md
new file mode 100644
index 00000000000000..b1c3dd768d86b3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_kinyabert_small_pretrained_kinyarwanda_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_kinyabert_small_pretrained_kinyarwanda_pipeline pipeline BertSentenceEmbeddings from RogerB
+author: John Snow Labs
+name: sent_kinyabert_small_pretrained_kinyarwanda_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_kinyabert_small_pretrained_kinyarwanda_pipeline` is a English model originally trained by RogerB.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_kinyabert_small_pretrained_kinyarwanda_pipeline_en_5.5.1_3.0_1737859978428.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_kinyabert_small_pretrained_kinyarwanda_pipeline_en_5.5.1_3.0_1737859978428.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_kinyabert_small_pretrained_kinyarwanda_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_kinyabert_small_pretrained_kinyarwanda_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_kinyabert_small_pretrained_kinyarwanda_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|248.0 MB|
+
+## References
+
+https://huggingface.co/RogerB/KinyaBERT-small-pretrained-kinyarwanda
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_legal_indobert_pytorch_v2_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_legal_indobert_pytorch_v2_en.md
new file mode 100644
index 00000000000000..1d434e06c1b44d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_legal_indobert_pytorch_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_legal_indobert_pytorch_v2 BertSentenceEmbeddings from kapanjagocoding
+author: John Snow Labs
+name: sent_legal_indobert_pytorch_v2
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_legal_indobert_pytorch_v2` is a English model originally trained by kapanjagocoding.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_legal_indobert_pytorch_v2_en_5.5.1_3.0_1737859443825.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_legal_indobert_pytorch_v2_en_5.5.1_3.0_1737859443825.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_legal_indobert_pytorch_v2","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_legal_indobert_pytorch_v2","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_legal_indobert_pytorch_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/kapanjagocoding/legal-indobert-pytorch-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_legal_indobert_pytorch_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_legal_indobert_pytorch_v2_pipeline_en.md
new file mode 100644
index 00000000000000..19c7a33d046356
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_legal_indobert_pytorch_v2_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_legal_indobert_pytorch_v2_pipeline pipeline BertSentenceEmbeddings from kapanjagocoding
+author: John Snow Labs
+name: sent_legal_indobert_pytorch_v2_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_legal_indobert_pytorch_v2_pipeline` is a English model originally trained by kapanjagocoding.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_legal_indobert_pytorch_v2_pipeline_en_5.5.1_3.0_1737859470505.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_legal_indobert_pytorch_v2_pipeline_en_5.5.1_3.0_1737859470505.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_legal_indobert_pytorch_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_legal_indobert_pytorch_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_legal_indobert_pytorch_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|404.2 MB|
+
+## References
+
+https://huggingface.co/kapanjagocoding/legal-indobert-pytorch-v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_mergedistill_maltese_128_v2_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_mergedistill_maltese_128_v2_en.md
new file mode 100644
index 00000000000000..189b47304b4297
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_mergedistill_maltese_128_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_mergedistill_maltese_128_v2 BertSentenceEmbeddings from amitness
+author: John Snow Labs
+name: sent_mergedistill_maltese_128_v2
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_mergedistill_maltese_128_v2` is a English model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_mergedistill_maltese_128_v2_en_5.5.1_3.0_1737860075021.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_mergedistill_maltese_128_v2_en_5.5.1_3.0_1737860075021.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_mergedistill_maltese_128_v2","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_mergedistill_maltese_128_v2","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_mergedistill_maltese_128_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|470.4 MB|
+
+## References
+
+https://huggingface.co/amitness/mergedistill-mt-128-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_mergedistill_maltese_128_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_mergedistill_maltese_128_v2_pipeline_en.md
new file mode 100644
index 00000000000000..4b05f3a457e8e2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_mergedistill_maltese_128_v2_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_mergedistill_maltese_128_v2_pipeline pipeline BertSentenceEmbeddings from amitness
+author: John Snow Labs
+name: sent_mergedistill_maltese_128_v2_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_mergedistill_maltese_128_v2_pipeline` is a English model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_mergedistill_maltese_128_v2_pipeline_en_5.5.1_3.0_1737860105221.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_mergedistill_maltese_128_v2_pipeline_en_5.5.1_3.0_1737860105221.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_mergedistill_maltese_128_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_mergedistill_maltese_128_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_mergedistill_maltese_128_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|470.9 MB|
+
+## References
+
+https://huggingface.co/amitness/mergedistill-mt-128-v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_mergedistill_maltese_arabic_512_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_mergedistill_maltese_arabic_512_en.md
new file mode 100644
index 00000000000000..8f53d56060a80e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_mergedistill_maltese_arabic_512_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_mergedistill_maltese_arabic_512 BertSentenceEmbeddings from amitness
+author: John Snow Labs
+name: sent_mergedistill_maltese_arabic_512
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_mergedistill_maltese_arabic_512` is a English model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_mergedistill_maltese_arabic_512_en_5.5.1_3.0_1737859522052.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_mergedistill_maltese_arabic_512_en_5.5.1_3.0_1737859522052.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_mergedistill_maltese_arabic_512","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_mergedistill_maltese_arabic_512","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_mergedistill_maltese_arabic_512|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|647.0 MB|
+
+## References
+
+https://huggingface.co/amitness/mergedistill-mt-ar-512
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_mergedistill_maltese_arabic_512_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_mergedistill_maltese_arabic_512_pipeline_en.md
new file mode 100644
index 00000000000000..c5eed8fda3cacd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_mergedistill_maltese_arabic_512_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_mergedistill_maltese_arabic_512_pipeline pipeline BertSentenceEmbeddings from amitness
+author: John Snow Labs
+name: sent_mergedistill_maltese_arabic_512_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_mergedistill_maltese_arabic_512_pipeline` is a English model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_mergedistill_maltese_arabic_512_pipeline_en_5.5.1_3.0_1737859556523.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_mergedistill_maltese_arabic_512_pipeline_en_5.5.1_3.0_1737859556523.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_mergedistill_maltese_arabic_512_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_mergedistill_maltese_arabic_512_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_mergedistill_maltese_arabic_512_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|647.5 MB|
+
+## References
+
+https://huggingface.co/amitness/mergedistill-mt-ar-512
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_mergedistill_maltese_english_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_mergedistill_maltese_english_en.md
new file mode 100644
index 00000000000000..e5886ea09af085
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_mergedistill_maltese_english_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_mergedistill_maltese_english BertSentenceEmbeddings from amitness
+author: John Snow Labs
+name: sent_mergedistill_maltese_english
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_mergedistill_maltese_english` is a English model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_mergedistill_maltese_english_en_5.5.1_3.0_1737860155669.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_mergedistill_maltese_english_en_5.5.1_3.0_1737860155669.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_mergedistill_maltese_english","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_mergedistill_maltese_english","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_mergedistill_maltese_english|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|532.5 MB|
+
+## References
+
+https://huggingface.co/amitness/mergedistill-mt-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_mergedistill_maltese_english_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_mergedistill_maltese_english_pipeline_en.md
new file mode 100644
index 00000000000000..c9bc47fa788b65
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_mergedistill_maltese_english_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_mergedistill_maltese_english_pipeline pipeline BertSentenceEmbeddings from amitness
+author: John Snow Labs
+name: sent_mergedistill_maltese_english_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_mergedistill_maltese_english_pipeline` is a English model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_mergedistill_maltese_english_pipeline_en_5.5.1_3.0_1737860188595.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_mergedistill_maltese_english_pipeline_en_5.5.1_3.0_1737860188595.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_mergedistill_maltese_english_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_mergedistill_maltese_english_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_mergedistill_maltese_english_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|533.1 MB|
+
+## References
+
+https://huggingface.co/amitness/mergedistill-mt-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_mergedistill_maltese_italian_128_v2_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_mergedistill_maltese_italian_128_v2_en.md
new file mode 100644
index 00000000000000..3e3ca5c5e203d2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_mergedistill_maltese_italian_128_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_mergedistill_maltese_italian_128_v2 BertSentenceEmbeddings from amitness
+author: John Snow Labs
+name: sent_mergedistill_maltese_italian_128_v2
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_mergedistill_maltese_italian_128_v2` is a English model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_mergedistill_maltese_italian_128_v2_en_5.5.1_3.0_1737860247708.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_mergedistill_maltese_italian_128_v2_en_5.5.1_3.0_1737860247708.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_mergedistill_maltese_italian_128_v2","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_mergedistill_maltese_italian_128_v2","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_mergedistill_maltese_italian_128_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|538.7 MB|
+
+## References
+
+https://huggingface.co/amitness/mergedistill-mt-it-128-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_mergedistill_maltese_italian_128_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_mergedistill_maltese_italian_128_v2_pipeline_en.md
new file mode 100644
index 00000000000000..cbeafcd2f01f1c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_mergedistill_maltese_italian_128_v2_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_mergedistill_maltese_italian_128_v2_pipeline pipeline BertSentenceEmbeddings from amitness
+author: John Snow Labs
+name: sent_mergedistill_maltese_italian_128_v2_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_mergedistill_maltese_italian_128_v2_pipeline` is a English model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_mergedistill_maltese_italian_128_v2_pipeline_en_5.5.1_3.0_1737860278429.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_mergedistill_maltese_italian_128_v2_pipeline_en_5.5.1_3.0_1737860278429.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_mergedistill_maltese_italian_128_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_mergedistill_maltese_italian_128_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_mergedistill_maltese_italian_128_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|539.2 MB|
+
+## References
+
+https://huggingface.co/amitness/mergedistill-mt-it-128-v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_mergedistill_maltese_italian_english_128_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_mergedistill_maltese_italian_english_128_en.md
new file mode 100644
index 00000000000000..697a9fb705e8df
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_mergedistill_maltese_italian_english_128_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_mergedistill_maltese_italian_english_128 BertSentenceEmbeddings from amitness
+author: John Snow Labs
+name: sent_mergedistill_maltese_italian_english_128
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_mergedistill_maltese_italian_english_128` is a English model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_mergedistill_maltese_italian_english_128_en_5.5.1_3.0_1737860429508.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_mergedistill_maltese_italian_english_128_en_5.5.1_3.0_1737860429508.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_mergedistill_maltese_italian_english_128","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_mergedistill_maltese_italian_english_128","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_mergedistill_maltese_italian_english_128|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|595.7 MB|
+
+## References
+
+https://huggingface.co/amitness/mergedistill-mt-it-en-128
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_mergedistill_maltese_italian_english_128_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_mergedistill_maltese_italian_english_128_pipeline_en.md
new file mode 100644
index 00000000000000..ceca3cccc1606b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_mergedistill_maltese_italian_english_128_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_mergedistill_maltese_italian_english_128_pipeline pipeline BertSentenceEmbeddings from amitness
+author: John Snow Labs
+name: sent_mergedistill_maltese_italian_english_128_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_mergedistill_maltese_italian_english_128_pipeline` is a English model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_mergedistill_maltese_italian_english_128_pipeline_en_5.5.1_3.0_1737860464438.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_mergedistill_maltese_italian_english_128_pipeline_en_5.5.1_3.0_1737860464438.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_mergedistill_maltese_italian_english_128_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_mergedistill_maltese_italian_english_128_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_mergedistill_maltese_italian_english_128_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|596.3 MB|
+
+## References
+
+https://huggingface.co/amitness/mergedistill-mt-it-en-128
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_mlm_20230405_002_3_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_mlm_20230405_002_3_en.md
new file mode 100644
index 00000000000000..c066dc38da539b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_mlm_20230405_002_3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_mlm_20230405_002_3 BertSentenceEmbeddings from intanm
+author: John Snow Labs
+name: sent_mlm_20230405_002_3
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_mlm_20230405_002_3` is a English model originally trained by intanm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_mlm_20230405_002_3_en_5.5.1_3.0_1737859736135.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_mlm_20230405_002_3_en_5.5.1_3.0_1737859736135.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_mlm_20230405_002_3","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_mlm_20230405_002_3","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_mlm_20230405_002_3|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|464.2 MB|
+
+## References
+
+https://huggingface.co/intanm/mlm-20230405-002-3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_mlm_20230405_002_3_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_mlm_20230405_002_3_pipeline_en.md
new file mode 100644
index 00000000000000..29767c5edcc7a0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_mlm_20230405_002_3_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_mlm_20230405_002_3_pipeline pipeline BertSentenceEmbeddings from intanm
+author: John Snow Labs
+name: sent_mlm_20230405_002_3_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_mlm_20230405_002_3_pipeline` is a English model originally trained by intanm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_mlm_20230405_002_3_pipeline_en_5.5.1_3.0_1737859762122.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_mlm_20230405_002_3_pipeline_en_5.5.1_3.0_1737859762122.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_mlm_20230405_002_3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_mlm_20230405_002_3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_mlm_20230405_002_3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|464.8 MB|
+
+## References
+
+https://huggingface.co/intanm/mlm-20230405-002-3
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_mlm_20230503_indobert_base_p2_002_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_mlm_20230503_indobert_base_p2_002_en.md
new file mode 100644
index 00000000000000..f469c6e21e7711
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_mlm_20230503_indobert_base_p2_002_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_mlm_20230503_indobert_base_p2_002 BertSentenceEmbeddings from intanm
+author: John Snow Labs
+name: sent_mlm_20230503_indobert_base_p2_002
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_mlm_20230503_indobert_base_p2_002` is a English model originally trained by intanm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_mlm_20230503_indobert_base_p2_002_en_5.5.1_3.0_1737859518932.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_mlm_20230503_indobert_base_p2_002_en_5.5.1_3.0_1737859518932.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_mlm_20230503_indobert_base_p2_002","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_mlm_20230503_indobert_base_p2_002","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_mlm_20230503_indobert_base_p2_002|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|464.3 MB|
+
+## References
+
+https://huggingface.co/intanm/mlm-20230503-indobert-base-p2-002
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_mlm_20230503_indobert_base_p2_002_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_mlm_20230503_indobert_base_p2_002_pipeline_en.md
new file mode 100644
index 00000000000000..dacc89695ea2f2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_mlm_20230503_indobert_base_p2_002_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_mlm_20230503_indobert_base_p2_002_pipeline pipeline BertSentenceEmbeddings from intanm
+author: John Snow Labs
+name: sent_mlm_20230503_indobert_base_p2_002_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_mlm_20230503_indobert_base_p2_002_pipeline` is a English model originally trained by intanm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_mlm_20230503_indobert_base_p2_002_pipeline_en_5.5.1_3.0_1737859542022.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_mlm_20230503_indobert_base_p2_002_pipeline_en_5.5.1_3.0_1737859542022.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_mlm_20230503_indobert_base_p2_002_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_mlm_20230503_indobert_base_p2_002_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_mlm_20230503_indobert_base_p2_002_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|464.8 MB|
+
+## References
+
+https://huggingface.co/intanm/mlm-20230503-indobert-base-p2-002
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_mytoken_model_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_mytoken_model_en.md
new file mode 100644
index 00000000000000..c6c0feca416635
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_mytoken_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_mytoken_model BertSentenceEmbeddings from kumarme072
+author: John Snow Labs
+name: sent_mytoken_model
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_mytoken_model` is a English model originally trained by kumarme072.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_mytoken_model_en_5.5.1_3.0_1737856200637.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_mytoken_model_en_5.5.1_3.0_1737856200637.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_mytoken_model","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_mytoken_model","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_mytoken_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/kumarme072/mytoken_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_mytoken_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_mytoken_model_pipeline_en.md
new file mode 100644
index 00000000000000..8bee77ef40e3ab
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_mytoken_model_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_mytoken_model_pipeline pipeline BertSentenceEmbeddings from kumarme072
+author: John Snow Labs
+name: sent_mytoken_model_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_mytoken_model_pipeline` is a English model originally trained by kumarme072.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_mytoken_model_pipeline_en_5.5.1_3.0_1737856224861.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_mytoken_model_pipeline_en_5.5.1_3.0_1737856224861.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_mytoken_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_mytoken_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_mytoken_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.3 MB|
+
+## References
+
+https://huggingface.co/kumarme072/mytoken_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_plue_ppbert_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_plue_ppbert_en.md
new file mode 100644
index 00000000000000..f2df705e3109a6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_plue_ppbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_plue_ppbert BertSentenceEmbeddings from arvyz
+author: John Snow Labs
+name: sent_plue_ppbert
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_plue_ppbert` is a English model originally trained by arvyz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_plue_ppbert_en_5.5.1_3.0_1737859709047.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_plue_ppbert_en_5.5.1_3.0_1737859709047.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_plue_ppbert","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_plue_ppbert","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_plue_ppbert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.0 MB|
+
+## References
+
+https://huggingface.co/arvyz/plue-ppbert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_plue_ppbert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_plue_ppbert_pipeline_en.md
new file mode 100644
index 00000000000000..5ead2a1bef4102
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_plue_ppbert_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_plue_ppbert_pipeline pipeline BertSentenceEmbeddings from arvyz
+author: John Snow Labs
+name: sent_plue_ppbert_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_plue_ppbert_pipeline` is a English model originally trained by arvyz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_plue_ppbert_pipeline_en_5.5.1_3.0_1737859733643.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_plue_ppbert_pipeline_en_5.5.1_3.0_1737859733643.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_plue_ppbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_plue_ppbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_plue_ppbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.5 MB|
+
+## References
+
+https://huggingface.co/arvyz/plue-ppbert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_retromae_beir_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_retromae_beir_en.md
new file mode 100644
index 00000000000000..7bb6ecde82b568
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_retromae_beir_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_retromae_beir BertSentenceEmbeddings from Shitao
+author: John Snow Labs
+name: sent_retromae_beir
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_retromae_beir` is a English model originally trained by Shitao.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_retromae_beir_en_5.5.1_3.0_1737901095667.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_retromae_beir_en_5.5.1_3.0_1737901095667.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_retromae_beir","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_retromae_beir","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_retromae_beir|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.6 MB|
+
+## References
+
+https://huggingface.co/Shitao/RetroMAE_BEIR
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_retromae_beir_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_retromae_beir_pipeline_en.md
new file mode 100644
index 00000000000000..974eee246e3251
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_retromae_beir_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_retromae_beir_pipeline pipeline BertSentenceEmbeddings from Shitao
+author: John Snow Labs
+name: sent_retromae_beir_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_retromae_beir_pipeline` is a English model originally trained by Shitao.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_retromae_beir_pipeline_en_5.5.1_3.0_1737901116303.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_retromae_beir_pipeline_en_5.5.1_3.0_1737901116303.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_retromae_beir_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_retromae_beir_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_retromae_beir_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|408.1 MB|
+
+## References
+
+https://huggingface.co/Shitao/RetroMAE_BEIR
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_scholarbert_100_64bit_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_scholarbert_100_64bit_en.md
new file mode 100644
index 00000000000000..cfee33f55bc535
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_scholarbert_100_64bit_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_scholarbert_100_64bit BertSentenceEmbeddings from globuslabs
+author: John Snow Labs
+name: sent_scholarbert_100_64bit
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_scholarbert_100_64bit` is a English model originally trained by globuslabs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_scholarbert_100_64bit_en_5.5.1_3.0_1737855924250.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_scholarbert_100_64bit_en_5.5.1_3.0_1737855924250.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_scholarbert_100_64bit","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_scholarbert_100_64bit","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_scholarbert_100_64bit|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|842.4 MB|
+
+## References
+
+https://huggingface.co/globuslabs/ScholarBERT_100_64bit
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_scholarbert_100_64bit_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_scholarbert_100_64bit_pipeline_en.md
new file mode 100644
index 00000000000000..1a3b1ceddb7a53
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_scholarbert_100_64bit_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_scholarbert_100_64bit_pipeline pipeline BertSentenceEmbeddings from globuslabs
+author: John Snow Labs
+name: sent_scholarbert_100_64bit_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_scholarbert_100_64bit_pipeline` is a English model originally trained by globuslabs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_scholarbert_100_64bit_pipeline_en_5.5.1_3.0_1737856173623.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_scholarbert_100_64bit_pipeline_en_5.5.1_3.0_1737856173623.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_scholarbert_100_64bit_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_scholarbert_100_64bit_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_scholarbert_100_64bit_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|842.9 MB|
+
+## References
+
+https://huggingface.co/globuslabs/ScholarBERT_100_64bit
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_splade_all_cocomae_220_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_splade_all_cocomae_220_en.md
new file mode 100644
index 00000000000000..30deb27b2997b6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_splade_all_cocomae_220_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_splade_all_cocomae_220 BertSentenceEmbeddings from approach0
+author: John Snow Labs
+name: sent_splade_all_cocomae_220
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_splade_all_cocomae_220` is a English model originally trained by approach0.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_splade_all_cocomae_220_en_5.5.1_3.0_1737859593134.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_splade_all_cocomae_220_en_5.5.1_3.0_1737859593134.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_splade_all_cocomae_220","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_splade_all_cocomae_220","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_splade_all_cocomae_220|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|409.9 MB|
+
+## References
+
+https://huggingface.co/approach0/splade_all-cocomae-220
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_splade_all_cocomae_220_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_splade_all_cocomae_220_pipeline_en.md
new file mode 100644
index 00000000000000..163055426c65a6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_splade_all_cocomae_220_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_splade_all_cocomae_220_pipeline pipeline BertSentenceEmbeddings from approach0
+author: John Snow Labs
+name: sent_splade_all_cocomae_220_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_splade_all_cocomae_220_pipeline` is a English model originally trained by approach0.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_splade_all_cocomae_220_pipeline_en_5.5.1_3.0_1737859617508.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_splade_all_cocomae_220_pipeline_en_5.5.1_3.0_1737859617508.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_splade_all_cocomae_220_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_splade_all_cocomae_220_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_splade_all_cocomae_220_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.4 MB|
+
+## References
+
+https://huggingface.co/approach0/splade_all-cocomae-220
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_squeezebert_finetuned_better_daily_dialog_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_squeezebert_finetuned_better_daily_dialog_en.md
new file mode 100644
index 00000000000000..c29ee386bf37e9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_squeezebert_finetuned_better_daily_dialog_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_squeezebert_finetuned_better_daily_dialog BertSentenceEmbeddings from BaioSbubens
+author: John Snow Labs
+name: sent_squeezebert_finetuned_better_daily_dialog
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_squeezebert_finetuned_better_daily_dialog` is a English model originally trained by BaioSbubens.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_squeezebert_finetuned_better_daily_dialog_en_5.5.1_3.0_1737900727517.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_squeezebert_finetuned_better_daily_dialog_en_5.5.1_3.0_1737900727517.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_squeezebert_finetuned_better_daily_dialog","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_squeezebert_finetuned_better_daily_dialog","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_squeezebert_finetuned_better_daily_dialog|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|189.0 MB|
+
+## References
+
+https://huggingface.co/BaioSbubens/squeezebert-finetuned-better_daily_dialog
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_squeezebert_finetuned_better_daily_dialog_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_squeezebert_finetuned_better_daily_dialog_pipeline_en.md
new file mode 100644
index 00000000000000..5c6179934dd7a3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_squeezebert_finetuned_better_daily_dialog_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_squeezebert_finetuned_better_daily_dialog_pipeline pipeline BertSentenceEmbeddings from BaioSbubens
+author: John Snow Labs
+name: sent_squeezebert_finetuned_better_daily_dialog_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_squeezebert_finetuned_better_daily_dialog_pipeline` is a English model originally trained by BaioSbubens.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_squeezebert_finetuned_better_daily_dialog_pipeline_en_5.5.1_3.0_1737900737633.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_squeezebert_finetuned_better_daily_dialog_pipeline_en_5.5.1_3.0_1737900737633.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_squeezebert_finetuned_better_daily_dialog_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_squeezebert_finetuned_better_daily_dialog_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_squeezebert_finetuned_better_daily_dialog_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|189.5 MB|
+
+## References
+
+https://huggingface.co/BaioSbubens/squeezebert-finetuned-better_daily_dialog
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_ugmultbert_e1_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_ugmultbert_e1_en.md
new file mode 100644
index 00000000000000..208bcf2aa9a187
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_ugmultbert_e1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_ugmultbert_e1 BertSentenceEmbeddings from TurkLangsTeamURFU
+author: John Snow Labs
+name: sent_ugmultbert_e1
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_ugmultbert_e1` is a English model originally trained by TurkLangsTeamURFU.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_ugmultbert_e1_en_5.5.1_3.0_1737859840103.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_ugmultbert_e1_en_5.5.1_3.0_1737859840103.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_ugmultbert_e1","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_ugmultbert_e1","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_ugmultbert_e1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|494.4 MB|
+
+## References
+
+https://huggingface.co/TurkLangsTeamURFU/UgMultBERT_e1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_ugmultbert_e1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_ugmultbert_e1_pipeline_en.md
new file mode 100644
index 00000000000000..505ef84550dd2f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_ugmultbert_e1_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_ugmultbert_e1_pipeline pipeline BertSentenceEmbeddings from TurkLangsTeamURFU
+author: John Snow Labs
+name: sent_ugmultbert_e1_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_ugmultbert_e1_pipeline` is a English model originally trained by TurkLangsTeamURFU.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_ugmultbert_e1_pipeline_en_5.5.1_3.0_1737859864716.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_ugmultbert_e1_pipeline_en_5.5.1_3.0_1737859864716.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_ugmultbert_e1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_ugmultbert_e1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_ugmultbert_e1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|494.9 MB|
+
+## References
+
+https://huggingface.co/TurkLangsTeamURFU/UgMultBERT_e1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_ugmultmtokbert_3e_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_ugmultmtokbert_3e_en.md
new file mode 100644
index 00000000000000..f5b940362e86ae
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_ugmultmtokbert_3e_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_ugmultmtokbert_3e BertSentenceEmbeddings from TurkLangsTeamURFU
+author: John Snow Labs
+name: sent_ugmultmtokbert_3e
+date: 2025-01-26
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_ugmultmtokbert_3e` is a English model originally trained by TurkLangsTeamURFU.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_ugmultmtokbert_3e_en_5.5.1_3.0_1737859748405.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_ugmultmtokbert_3e_en_5.5.1_3.0_1737859748405.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_ugmultmtokbert_3e","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_ugmultmtokbert_3e","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_ugmultmtokbert_3e|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|742.7 MB|
+
+## References
+
+https://huggingface.co/TurkLangsTeamURFU/UgMultMTokBERT_3e
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sent_ugmultmtokbert_3e_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sent_ugmultmtokbert_3e_pipeline_en.md
new file mode 100644
index 00000000000000..b62d10a600cd27
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sent_ugmultmtokbert_3e_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_ugmultmtokbert_3e_pipeline pipeline BertSentenceEmbeddings from TurkLangsTeamURFU
+author: John Snow Labs
+name: sent_ugmultmtokbert_3e_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_ugmultmtokbert_3e_pipeline` is a English model originally trained by TurkLangsTeamURFU.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_ugmultmtokbert_3e_pipeline_en_5.5.1_3.0_1737859789065.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_ugmultmtokbert_3e_pipeline_en_5.5.1_3.0_1737859789065.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_ugmultmtokbert_3e_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_ugmultmtokbert_3e_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_ugmultmtokbert_3e_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|743.2 MB|
+
+## References
+
+https://huggingface.co/TurkLangsTeamURFU/UgMultMTokBERT_3e
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sentiment_model_on_imdb_dataset_en.md b/docs/_posts/ahmedlone127/2025-01-26-sentiment_model_on_imdb_dataset_en.md
new file mode 100644
index 00000000000000..e4974327171caa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sentiment_model_on_imdb_dataset_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sentiment_model_on_imdb_dataset DistilBertForSequenceClassification from uppaluru
+author: John Snow Labs
+name: sentiment_model_on_imdb_dataset
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentiment_model_on_imdb_dataset` is a English model originally trained by uppaluru.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentiment_model_on_imdb_dataset_en_5.5.1_3.0_1737929054678.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentiment_model_on_imdb_dataset_en_5.5.1_3.0_1737929054678.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("sentiment_model_on_imdb_dataset","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("sentiment_model_on_imdb_dataset", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sentiment_model_on_imdb_dataset|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/uppaluru/sentiment-model-on-imdb-dataset
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sentiment_model_on_imdb_dataset_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sentiment_model_on_imdb_dataset_pipeline_en.md
new file mode 100644
index 00000000000000..057d509489f7ed
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sentiment_model_on_imdb_dataset_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English sentiment_model_on_imdb_dataset_pipeline pipeline DistilBertForSequenceClassification from uppaluru
+author: John Snow Labs
+name: sentiment_model_on_imdb_dataset_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentiment_model_on_imdb_dataset_pipeline` is a English model originally trained by uppaluru.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentiment_model_on_imdb_dataset_pipeline_en_5.5.1_3.0_1737929069438.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentiment_model_on_imdb_dataset_pipeline_en_5.5.1_3.0_1737929069438.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sentiment_model_on_imdb_dataset_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sentiment_model_on_imdb_dataset_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sentiment_model_on_imdb_dataset_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/uppaluru/sentiment-model-on-imdb-dataset
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sentiment_review_en.md b/docs/_posts/ahmedlone127/2025-01-26-sentiment_review_en.md
new file mode 100644
index 00000000000000..9c5d23e8837d15
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sentiment_review_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sentiment_review DistilBertForSequenceClassification from rxh1
+author: John Snow Labs
+name: sentiment_review
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentiment_review` is a English model originally trained by rxh1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentiment_review_en_5.5.1_3.0_1737928735461.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentiment_review_en_5.5.1_3.0_1737928735461.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("sentiment_review","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("sentiment_review", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sentiment_review|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|507.6 MB|
+
+## References
+
+https://huggingface.co/rxh1/sentiment-review
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sentiment_review_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sentiment_review_pipeline_en.md
new file mode 100644
index 00000000000000..86e9ae66c6e45f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sentiment_review_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English sentiment_review_pipeline pipeline DistilBertForSequenceClassification from rxh1
+author: John Snow Labs
+name: sentiment_review_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentiment_review_pipeline` is a English model originally trained by rxh1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentiment_review_pipeline_en_5.5.1_3.0_1737928761995.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentiment_review_pipeline_en_5.5.1_3.0_1737928761995.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sentiment_review_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sentiment_review_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sentiment_review_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|507.6 MB|
+
+## References
+
+https://huggingface.co/rxh1/sentiment-review
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sharq_model_uzb_en.md b/docs/_posts/ahmedlone127/2025-01-26-sharq_model_uzb_en.md
new file mode 100644
index 00000000000000..0e0fbe13acb815
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sharq_model_uzb_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sharq_model_uzb DistilBertForSequenceClassification from blackhole33
+author: John Snow Labs
+name: sharq_model_uzb
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sharq_model_uzb` is a English model originally trained by blackhole33.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sharq_model_uzb_en_5.5.1_3.0_1737929081073.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sharq_model_uzb_en_5.5.1_3.0_1737929081073.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("sharq_model_uzb","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("sharq_model_uzb", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sharq_model_uzb|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/blackhole33/sharq-model-uzb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sharq_model_uzb_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sharq_model_uzb_pipeline_en.md
new file mode 100644
index 00000000000000..fa8ae0ed782a44
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sharq_model_uzb_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English sharq_model_uzb_pipeline pipeline DistilBertForSequenceClassification from blackhole33
+author: John Snow Labs
+name: sharq_model_uzb_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sharq_model_uzb_pipeline` is a English model originally trained by blackhole33.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sharq_model_uzb_pipeline_en_5.5.1_3.0_1737929094781.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sharq_model_uzb_pipeline_en_5.5.1_3.0_1737929094781.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sharq_model_uzb_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sharq_model_uzb_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sharq_model_uzb_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/blackhole33/sharq-model-uzb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sinhala_roberta_large_en.md b/docs/_posts/ahmedlone127/2025-01-26-sinhala_roberta_large_en.md
new file mode 100644
index 00000000000000..e8c85567856159
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sinhala_roberta_large_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sinhala_roberta_large RoBertaEmbeddings from 9wimu9
+author: John Snow Labs
+name: sinhala_roberta_large
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sinhala_roberta_large` is a English model originally trained by 9wimu9.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sinhala_roberta_large_en_5.5.1_3.0_1737907253091.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sinhala_roberta_large_en_5.5.1_3.0_1737907253091.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("sinhala_roberta_large","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("sinhala_roberta_large","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sinhala_roberta_large|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/9wimu9/sinhala-roberta-large
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sinhala_roberta_large_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sinhala_roberta_large_pipeline_en.md
new file mode 100644
index 00000000000000..072fe32086ad00
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sinhala_roberta_large_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English sinhala_roberta_large_pipeline pipeline RoBertaEmbeddings from 9wimu9
+author: John Snow Labs
+name: sinhala_roberta_large_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sinhala_roberta_large_pipeline` is a English model originally trained by 9wimu9.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sinhala_roberta_large_pipeline_en_5.5.1_3.0_1737907326579.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sinhala_roberta_large_pipeline_en_5.5.1_3.0_1737907326579.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sinhala_roberta_large_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sinhala_roberta_large_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sinhala_roberta_large_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/9wimu9/sinhala-roberta-large
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-skin_cancer_image_classification_en.md b/docs/_posts/ahmedlone127/2025-01-26-skin_cancer_image_classification_en.md
new file mode 100644
index 00000000000000..0e6c7069782375
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-skin_cancer_image_classification_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English skin_cancer_image_classification ViTForImageClassification from Anwarkh1
+author: John Snow Labs
+name: skin_cancer_image_classification
+date: 2025-01-26
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`skin_cancer_image_classification` is a English model originally trained by Anwarkh1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/skin_cancer_image_classification_en_5.5.1_3.0_1737926387801.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/skin_cancer_image_classification_en_5.5.1_3.0_1737926387801.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""skin_cancer_image_classification","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("skin_cancer_image_classification","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|skin_cancer_image_classification|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/Anwarkh1/Skin_Cancer-Image_Classification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-skin_cancer_image_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-skin_cancer_image_classification_pipeline_en.md
new file mode 100644
index 00000000000000..2a30cd860ddbef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-skin_cancer_image_classification_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English skin_cancer_image_classification_pipeline pipeline ViTForImageClassification from Anwarkh1
+author: John Snow Labs
+name: skin_cancer_image_classification_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`skin_cancer_image_classification_pipeline` is a English model originally trained by Anwarkh1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/skin_cancer_image_classification_pipeline_en_5.5.1_3.0_1737926404768.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/skin_cancer_image_classification_pipeline_en_5.5.1_3.0_1737926404768.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("skin_cancer_image_classification_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("skin_cancer_image_classification_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|skin_cancer_image_classification_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/Anwarkh1/Skin_Cancer-Image_Classification
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-skin_types_image_detection_en.md b/docs/_posts/ahmedlone127/2025-01-26-skin_types_image_detection_en.md
new file mode 100644
index 00000000000000..837f0adaf67228
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-skin_types_image_detection_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English skin_types_image_detection ViTForImageClassification from dima806
+author: John Snow Labs
+name: skin_types_image_detection
+date: 2025-01-26
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`skin_types_image_detection` is a English model originally trained by dima806.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/skin_types_image_detection_en_5.5.1_3.0_1737926046736.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/skin_types_image_detection_en_5.5.1_3.0_1737926046736.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""skin_types_image_detection","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("skin_types_image_detection","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|skin_types_image_detection|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/dima806/skin_types_image_detection
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-skin_types_image_detection_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-skin_types_image_detection_pipeline_en.md
new file mode 100644
index 00000000000000..b414cf193b3011
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-skin_types_image_detection_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English skin_types_image_detection_pipeline pipeline ViTForImageClassification from dima806
+author: John Snow Labs
+name: skin_types_image_detection_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`skin_types_image_detection_pipeline` is a English model originally trained by dima806.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/skin_types_image_detection_pipeline_en_5.5.1_3.0_1737926064119.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/skin_types_image_detection_pipeline_en_5.5.1_3.0_1737926064119.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("skin_types_image_detection_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("skin_types_image_detection_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|skin_types_image_detection_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/dima806/skin_types_image_detection
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-slovak_bpe_blm_pipeline_sk.md b/docs/_posts/ahmedlone127/2025-01-26-slovak_bpe_blm_pipeline_sk.md
new file mode 100644
index 00000000000000..a91e58073828c4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-slovak_bpe_blm_pipeline_sk.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Slovak slovak_bpe_blm_pipeline pipeline RoBertaEmbeddings from daviddrzik
+author: John Snow Labs
+name: slovak_bpe_blm_pipeline
+date: 2025-01-26
+tags: [sk, open_source, pipeline, onnx]
+task: Embeddings
+language: sk
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`slovak_bpe_blm_pipeline` is a Slovak model originally trained by daviddrzik.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/slovak_bpe_blm_pipeline_sk_5.5.1_3.0_1737906668267.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/slovak_bpe_blm_pipeline_sk_5.5.1_3.0_1737906668267.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("slovak_bpe_blm_pipeline", lang = "sk")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("slovak_bpe_blm_pipeline", lang = "sk")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|slovak_bpe_blm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|sk|
+|Size:|219.6 MB|
+
+## References
+
+https://huggingface.co/daviddrzik/SK_BPE_BLM
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-slovak_bpe_blm_sk.md b/docs/_posts/ahmedlone127/2025-01-26-slovak_bpe_blm_sk.md
new file mode 100644
index 00000000000000..2f639aace2ead9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-slovak_bpe_blm_sk.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Slovak slovak_bpe_blm RoBertaEmbeddings from daviddrzik
+author: John Snow Labs
+name: slovak_bpe_blm
+date: 2025-01-26
+tags: [sk, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: sk
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`slovak_bpe_blm` is a Slovak model originally trained by daviddrzik.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/slovak_bpe_blm_sk_5.5.1_3.0_1737906656757.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/slovak_bpe_blm_sk_5.5.1_3.0_1737906656757.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("slovak_bpe_blm","sk") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("slovak_bpe_blm","sk") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|slovak_bpe_blm|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|sk|
+|Size:|219.6 MB|
+
+## References
+
+https://huggingface.co/daviddrzik/SK_BPE_BLM
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-spaceroberta_en.md b/docs/_posts/ahmedlone127/2025-01-26-spaceroberta_en.md
new file mode 100644
index 00000000000000..81eea9e22fbdf9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-spaceroberta_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English spaceroberta RoBertaEmbeddings from icelab
+author: John Snow Labs
+name: spaceroberta
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`spaceroberta` is a English model originally trained by icelab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/spaceroberta_en_5.5.1_3.0_1737906769872.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/spaceroberta_en_5.5.1_3.0_1737906769872.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("spaceroberta","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("spaceroberta","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|spaceroberta|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|466.2 MB|
+
+## References
+
+https://huggingface.co/icelab/spaceroberta
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-spaceroberta_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-spaceroberta_pipeline_en.md
new file mode 100644
index 00000000000000..6f64f3c34baa54
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-spaceroberta_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English spaceroberta_pipeline pipeline RoBertaEmbeddings from icelab
+author: John Snow Labs
+name: spaceroberta_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`spaceroberta_pipeline` is a English model originally trained by icelab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/spaceroberta_pipeline_en_5.5.1_3.0_1737906795001.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/spaceroberta_pipeline_en_5.5.1_3.0_1737906795001.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("spaceroberta_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("spaceroberta_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|spaceroberta_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.3 MB|
+
+## References
+
+https://huggingface.co/icelab/spaceroberta
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-student_alpha0_25kd_en.md b/docs/_posts/ahmedlone127/2025-01-26-student_alpha0_25kd_en.md
new file mode 100644
index 00000000000000..b9c98c8a6fc2ad
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-student_alpha0_25kd_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English student_alpha0_25kd DistilBertForTokenClassification from pmpmp74832
+author: John Snow Labs
+name: student_alpha0_25kd
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`student_alpha0_25kd` is a English model originally trained by pmpmp74832.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/student_alpha0_25kd_en_5.5.1_3.0_1737909901172.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/student_alpha0_25kd_en_5.5.1_3.0_1737909901172.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("student_alpha0_25kd","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("student_alpha0_25kd", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|student_alpha0_25kd|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|329.4 MB|
+
+## References
+
+https://huggingface.co/pmpmp74832/student-alpha0.25KD
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-student_alpha0_25kd_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-student_alpha0_25kd_pipeline_en.md
new file mode 100644
index 00000000000000..57c848ea5c9c19
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-student_alpha0_25kd_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English student_alpha0_25kd_pipeline pipeline DistilBertForTokenClassification from pmpmp74832
+author: John Snow Labs
+name: student_alpha0_25kd_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`student_alpha0_25kd_pipeline` is a English model originally trained by pmpmp74832.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/student_alpha0_25kd_pipeline_en_5.5.1_3.0_1737909920409.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/student_alpha0_25kd_pipeline_en_5.5.1_3.0_1737909920409.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("student_alpha0_25kd_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("student_alpha0_25kd_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|student_alpha0_25kd_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|329.4 MB|
+
+## References
+
+https://huggingface.co/pmpmp74832/student-alpha0.25KD
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-substitution_cipher_text_turkish_pipeline_tr.md b/docs/_posts/ahmedlone127/2025-01-26-substitution_cipher_text_turkish_pipeline_tr.md
new file mode 100644
index 00000000000000..46012fc5e2569e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-substitution_cipher_text_turkish_pipeline_tr.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Turkish substitution_cipher_text_turkish_pipeline pipeline T5Transformer from Cipher-AI
+author: John Snow Labs
+name: substitution_cipher_text_turkish_pipeline
+date: 2025-01-26
+tags: [tr, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: tr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`substitution_cipher_text_turkish_pipeline` is a Turkish model originally trained by Cipher-AI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/substitution_cipher_text_turkish_pipeline_tr_5.5.1_3.0_1737850240910.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/substitution_cipher_text_turkish_pipeline_tr_5.5.1_3.0_1737850240910.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("substitution_cipher_text_turkish_pipeline", lang = "tr")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("substitution_cipher_text_turkish_pipeline", lang = "tr")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|substitution_cipher_text_turkish_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|tr|
+|Size:|927.2 MB|
+
+## References
+
+https://huggingface.co/Cipher-AI/Substitution-Cipher-Text-Turkish
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-substitution_cipher_text_turkish_tr.md b/docs/_posts/ahmedlone127/2025-01-26-substitution_cipher_text_turkish_tr.md
new file mode 100644
index 00000000000000..d01ea4a9896f03
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-substitution_cipher_text_turkish_tr.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Turkish substitution_cipher_text_turkish T5Transformer from Cipher-AI
+author: John Snow Labs
+name: substitution_cipher_text_turkish
+date: 2025-01-26
+tags: [tr, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: tr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`substitution_cipher_text_turkish` is a Turkish model originally trained by Cipher-AI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/substitution_cipher_text_turkish_tr_5.5.1_3.0_1737850194250.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/substitution_cipher_text_turkish_tr_5.5.1_3.0_1737850194250.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("substitution_cipher_text_turkish","tr") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("substitution_cipher_text_turkish", "tr")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|substitution_cipher_text_turkish|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|tr|
+|Size:|927.2 MB|
+
+## References
+
+https://huggingface.co/Cipher-AI/Substitution-Cipher-Text-Turkish
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-superclass_multilang_tableclf_21may_xlm_roberta_base_baseline_en.md b/docs/_posts/ahmedlone127/2025-01-26-superclass_multilang_tableclf_21may_xlm_roberta_base_baseline_en.md
new file mode 100644
index 00000000000000..ce6bd87db83fa8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-superclass_multilang_tableclf_21may_xlm_roberta_base_baseline_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English superclass_multilang_tableclf_21may_xlm_roberta_base_baseline XlmRoBertaForSequenceClassification from slimaneMakh
+author: John Snow Labs
+name: superclass_multilang_tableclf_21may_xlm_roberta_base_baseline
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`superclass_multilang_tableclf_21may_xlm_roberta_base_baseline` is a English model originally trained by slimaneMakh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/superclass_multilang_tableclf_21may_xlm_roberta_base_baseline_en_5.5.1_3.0_1737881194277.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/superclass_multilang_tableclf_21may_xlm_roberta_base_baseline_en_5.5.1_3.0_1737881194277.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("superclass_multilang_tableclf_21may_xlm_roberta_base_baseline","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("superclass_multilang_tableclf_21may_xlm_roberta_base_baseline", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|superclass_multilang_tableclf_21may_xlm_roberta_base_baseline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|861.3 MB|
+
+## References
+
+https://huggingface.co/slimaneMakh/superClass_multiLang_tableClf_21may_xlm-roberta-base_BASELINE
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-superclass_multilang_tableclf_21may_xlm_roberta_base_baseline_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-superclass_multilang_tableclf_21may_xlm_roberta_base_baseline_pipeline_en.md
new file mode 100644
index 00000000000000..4873cba89a9b16
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-superclass_multilang_tableclf_21may_xlm_roberta_base_baseline_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English superclass_multilang_tableclf_21may_xlm_roberta_base_baseline_pipeline pipeline XlmRoBertaForSequenceClassification from slimaneMakh
+author: John Snow Labs
+name: superclass_multilang_tableclf_21may_xlm_roberta_base_baseline_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`superclass_multilang_tableclf_21may_xlm_roberta_base_baseline_pipeline` is a English model originally trained by slimaneMakh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/superclass_multilang_tableclf_21may_xlm_roberta_base_baseline_pipeline_en_5.5.1_3.0_1737881283365.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/superclass_multilang_tableclf_21may_xlm_roberta_base_baseline_pipeline_en_5.5.1_3.0_1737881283365.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("superclass_multilang_tableclf_21may_xlm_roberta_base_baseline_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("superclass_multilang_tableclf_21may_xlm_roberta_base_baseline_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|superclass_multilang_tableclf_21may_xlm_roberta_base_baseline_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|861.4 MB|
+
+## References
+
+https://huggingface.co/slimaneMakh/superClass_multiLang_tableClf_21may_xlm-roberta-base_BASELINE
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sweng25_3_en.md b/docs/_posts/ahmedlone127/2025-01-26-sweng25_3_en.md
new file mode 100644
index 00000000000000..e259ed792484af
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sweng25_3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sweng25_3 BertForTokenClassification from kavans25
+author: John Snow Labs
+name: sweng25_3
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sweng25_3` is a English model originally trained by kavans25.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sweng25_3_en_5.5.1_3.0_1737933967191.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sweng25_3_en_5.5.1_3.0_1737933967191.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("sweng25_3","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("sweng25_3", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sweng25_3|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/kavans25/Sweng25_3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-sweng25_3_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-sweng25_3_pipeline_en.md
new file mode 100644
index 00000000000000..586dee945d9527
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-sweng25_3_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English sweng25_3_pipeline pipeline BertForTokenClassification from kavans25
+author: John Snow Labs
+name: sweng25_3_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sweng25_3_pipeline` is a English model originally trained by kavans25.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sweng25_3_pipeline_en_5.5.1_3.0_1737933988319.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sweng25_3_pipeline_en_5.5.1_3.0_1737933988319.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sweng25_3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sweng25_3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sweng25_3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/kavans25/Sweng25_3
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_05_en.md b/docs/_posts/ahmedlone127/2025-01-26-swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_05_en.md
new file mode 100644
index 00000000000000..2939892e039560
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_05_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_05 SwinForImageClassification from amjadfqs
+author: John Snow Labs
+name: swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_05
+date: 2025-01-26
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_05` is a English model originally trained by amjadfqs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_05_en_5.5.1_3.0_1737889081905.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_05_en_5.5.1_3.0_1737889081905.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_05","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_05","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_05|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|649.8 MB|
+
+## References
+
+https://huggingface.co/amjadfqs/swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-final_05
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_05_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_05_pipeline_en.md
new file mode 100644
index 00000000000000..44322d0886ae7a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_05_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_05_pipeline pipeline SwinForImageClassification from amjadfqs
+author: John Snow Labs
+name: swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_05_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_05_pipeline` is a English model originally trained by amjadfqs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_05_pipeline_en_5.5.1_3.0_1737889116004.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_05_pipeline_en_5.5.1_3.0_1737889116004.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_05_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_05_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_final_05_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|649.8 MB|
+
+## References
+
+https://huggingface.co/amjadfqs/swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-final_05
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_02_en.md b/docs/_posts/ahmedlone127/2025-01-26-swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_02_en.md
new file mode 100644
index 00000000000000..fd963d80916ef0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_02_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_02 SwinForImageClassification from amjadfqs
+author: John Snow Labs
+name: swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_02
+date: 2025-01-26
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_02` is a English model originally trained by amjadfqs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_02_en_5.5.1_3.0_1737888862950.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_02_en_5.5.1_3.0_1737888862950.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_02","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_02","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_02|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|649.8 MB|
+
+## References
+
+https://huggingface.co/amjadfqs/swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-skullStrippded_02
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_02_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_02_pipeline_en.md
new file mode 100644
index 00000000000000..6e5b0f5f7e9376
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_02_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_02_pipeline pipeline SwinForImageClassification from amjadfqs
+author: John Snow Labs
+name: swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_02_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_02_pipeline` is a English model originally trained by amjadfqs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_02_pipeline_en_5.5.1_3.0_1737888896894.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_02_pipeline_en_5.5.1_3.0_1737888896894.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_02_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_02_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_02_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|649.8 MB|
+
+## References
+
+https://huggingface.co/amjadfqs/swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-skullStrippded_02
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-swin_base_patch4_window7_224_in22k_finetuned_ct_zen45_en.md b/docs/_posts/ahmedlone127/2025-01-26-swin_base_patch4_window7_224_in22k_finetuned_ct_zen45_en.md
new file mode 100644
index 00000000000000..80339bc260620d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-swin_base_patch4_window7_224_in22k_finetuned_ct_zen45_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_base_patch4_window7_224_in22k_finetuned_ct_zen45 SwinForImageClassification from zen45
+author: John Snow Labs
+name: swin_base_patch4_window7_224_in22k_finetuned_ct_zen45
+date: 2025-01-26
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_base_patch4_window7_224_in22k_finetuned_ct_zen45` is a English model originally trained by zen45.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_in22k_finetuned_ct_zen45_en_5.5.1_3.0_1737889480445.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_in22k_finetuned_ct_zen45_en_5.5.1_3.0_1737889480445.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_base_patch4_window7_224_in22k_finetuned_ct_zen45","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_base_patch4_window7_224_in22k_finetuned_ct_zen45","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_base_patch4_window7_224_in22k_finetuned_ct_zen45|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|649.8 MB|
+
+## References
+
+https://huggingface.co/zen45/swin-base-patch4-window7-224-in22k-finetuned-CT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-swin_base_patch4_window7_224_in22k_finetuned_ct_zen45_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-swin_base_patch4_window7_224_in22k_finetuned_ct_zen45_pipeline_en.md
new file mode 100644
index 00000000000000..7a3961941e7737
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-swin_base_patch4_window7_224_in22k_finetuned_ct_zen45_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_base_patch4_window7_224_in22k_finetuned_ct_zen45_pipeline pipeline SwinForImageClassification from zen45
+author: John Snow Labs
+name: swin_base_patch4_window7_224_in22k_finetuned_ct_zen45_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_base_patch4_window7_224_in22k_finetuned_ct_zen45_pipeline` is a English model originally trained by zen45.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_in22k_finetuned_ct_zen45_pipeline_en_5.5.1_3.0_1737889513978.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_in22k_finetuned_ct_zen45_pipeline_en_5.5.1_3.0_1737889513978.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_base_patch4_window7_224_in22k_finetuned_ct_zen45_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_base_patch4_window7_224_in22k_finetuned_ct_zen45_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_base_patch4_window7_224_in22k_finetuned_ct_zen45_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|649.8 MB|
+
+## References
+
+https://huggingface.co/zen45/swin-base-patch4-window7-224-in22k-finetuned-CT
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_alzheimers_en.md b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_alzheimers_en.md
new file mode 100644
index 00000000000000..7a8b236aeac85f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_alzheimers_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_alzheimers SwinForImageClassification from rhlc
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_alzheimers
+date: 2025-01-26
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_alzheimers` is a English model originally trained by rhlc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_alzheimers_en_5.5.1_3.0_1737888728398.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_alzheimers_en_5.5.1_3.0_1737888728398.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_alzheimers","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_alzheimers","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_alzheimers|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/rhlc/swin-tiny-patch4-window7-224-finetuned-alzheimers
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_alzheimers_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_alzheimers_pipeline_en.md
new file mode 100644
index 00000000000000..30bcc87dc2b7c2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_alzheimers_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_alzheimers_pipeline pipeline SwinForImageClassification from rhlc
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_alzheimers_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_alzheimers_pipeline` is a English model originally trained by rhlc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_alzheimers_pipeline_en_5.5.1_3.0_1737888741685.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_alzheimers_pipeline_en_5.5.1_3.0_1737888741685.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_alzheimers_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_alzheimers_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_alzheimers_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/rhlc/swin-tiny-patch4-window7-224-finetuned-alzheimers
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_amiqinayat_en.md b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_amiqinayat_en.md
new file mode 100644
index 00000000000000..e6e38f0aabef63
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_amiqinayat_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_amiqinayat SwinForImageClassification from amiqinayat
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_amiqinayat
+date: 2025-01-26
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_amiqinayat` is a English model originally trained by amiqinayat.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_amiqinayat_en_5.5.1_3.0_1737889105468.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_amiqinayat_en_5.5.1_3.0_1737889105468.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_amiqinayat","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_amiqinayat","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_amiqinayat|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/amiqinayat/swin-tiny-patch4-window7-224-finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_amiqinayat_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_amiqinayat_pipeline_en.md
new file mode 100644
index 00000000000000..d7f9f5201674ca
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_amiqinayat_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_amiqinayat_pipeline pipeline SwinForImageClassification from amiqinayat
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_amiqinayat_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_amiqinayat_pipeline` is a English model originally trained by amiqinayat.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_amiqinayat_pipeline_en_5.5.1_3.0_1737889116533.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_amiqinayat_pipeline_en_5.5.1_3.0_1737889116533.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_amiqinayat_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_amiqinayat_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_amiqinayat_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/amiqinayat/swin-tiny-patch4-window7-224-finetuned
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_artucathur_en.md b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_artucathur_en.md
new file mode 100644
index 00000000000000..207eda285c55aa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_artucathur_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_artucathur SwinForImageClassification from artucathur
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_artucathur
+date: 2025-01-26
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_artucathur` is a English model originally trained by artucathur.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_artucathur_en_5.5.1_3.0_1737889222373.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_artucathur_en_5.5.1_3.0_1737889222373.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_artucathur","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_artucathur","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_artucathur|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/artucathur/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_artucathur_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_artucathur_pipeline_en.md
new file mode 100644
index 00000000000000..e5815cd5dec8be
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_artucathur_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_artucathur_pipeline pipeline SwinForImageClassification from artucathur
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_artucathur_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_artucathur_pipeline` is a English model originally trained by artucathur.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_artucathur_pipeline_en_5.5.1_3.0_1737889233107.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_artucathur_pipeline_en_5.5.1_3.0_1737889233107.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_artucathur_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_artucathur_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_artucathur_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/artucathur/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_axion004_en.md b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_axion004_en.md
new file mode 100644
index 00000000000000..d7a5f3fd8ba9dc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_axion004_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_axion004 SwinForImageClassification from Axion004
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_axion004
+date: 2025-01-26
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_axion004` is a English model originally trained by Axion004.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_axion004_en_5.5.1_3.0_1737889318191.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_axion004_en_5.5.1_3.0_1737889318191.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_axion004","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_axion004","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_axion004|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/Axion004/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_axion004_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_axion004_pipeline_en.md
new file mode 100644
index 00000000000000..ce0002d6a766a2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_axion004_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_axion004_pipeline pipeline SwinForImageClassification from Axion004
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_axion004_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_axion004_pipeline` is a English model originally trained by Axion004.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_axion004_pipeline_en_5.5.1_3.0_1737889329894.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_axion004_pipeline_en_5.5.1_3.0_1737889329894.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_axion004_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_axion004_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_axion004_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/Axion004/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_danggoryo_en.md b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_danggoryo_en.md
new file mode 100644
index 00000000000000..4dcf2a96a8cc07
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_danggoryo_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_danggoryo SwinForImageClassification from DanggoRyo
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_danggoryo
+date: 2025-01-26
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_danggoryo` is a English model originally trained by DanggoRyo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_danggoryo_en_5.5.1_3.0_1737889340872.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_danggoryo_en_5.5.1_3.0_1737889340872.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_danggoryo","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_danggoryo","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_danggoryo|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/DanggoRyo/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_danggoryo_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_danggoryo_pipeline_en.md
new file mode 100644
index 00000000000000..a58c030103d10f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_danggoryo_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_danggoryo_pipeline pipeline SwinForImageClassification from DanggoRyo
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_danggoryo_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_danggoryo_pipeline` is a English model originally trained by DanggoRyo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_danggoryo_pipeline_en_5.5.1_3.0_1737889351883.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_danggoryo_pipeline_en_5.5.1_3.0_1737889351883.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_danggoryo_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_danggoryo_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_danggoryo_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/DanggoRyo/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_digitalpath_en.md b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_digitalpath_en.md
new file mode 100644
index 00000000000000..779fcd0a62c488
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_digitalpath_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_digitalpath SwinForImageClassification from DigitalPath
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_digitalpath
+date: 2025-01-26
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_digitalpath` is a English model originally trained by DigitalPath.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_digitalpath_en_5.5.1_3.0_1737888637777.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_digitalpath_en_5.5.1_3.0_1737888637777.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_digitalpath","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_digitalpath","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_digitalpath|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/DigitalPath/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_digitalpath_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_digitalpath_pipeline_en.md
new file mode 100644
index 00000000000000..1670a78f063767
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_digitalpath_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_digitalpath_pipeline pipeline SwinForImageClassification from DigitalPath
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_digitalpath_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_digitalpath_pipeline` is a English model originally trained by DigitalPath.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_digitalpath_pipeline_en_5.5.1_3.0_1737888648775.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_digitalpath_pipeline_en_5.5.1_3.0_1737888648775.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_digitalpath_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_digitalpath_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_digitalpath_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/DigitalPath/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_felipecordeiiro_en.md b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_felipecordeiiro_en.md
new file mode 100644
index 00000000000000..b8492f3b1d6c92
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_felipecordeiiro_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_felipecordeiiro SwinForImageClassification from Felipecordeiiro
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_felipecordeiiro
+date: 2025-01-26
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_felipecordeiiro` is a English model originally trained by Felipecordeiiro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_felipecordeiiro_en_5.5.1_3.0_1737889346438.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_felipecordeiiro_en_5.5.1_3.0_1737889346438.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_felipecordeiiro","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_felipecordeiiro","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_felipecordeiiro|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/Felipecordeiiro/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_felipecordeiiro_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_felipecordeiiro_pipeline_en.md
new file mode 100644
index 00000000000000..26f9d34016a2e3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_felipecordeiiro_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_felipecordeiiro_pipeline pipeline SwinForImageClassification from Felipecordeiiro
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_felipecordeiiro_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_felipecordeiiro_pipeline` is a English model originally trained by Felipecordeiiro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_felipecordeiiro_pipeline_en_5.5.1_3.0_1737889357577.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_felipecordeiiro_pipeline_en_5.5.1_3.0_1737889357577.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_felipecordeiiro_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_felipecordeiiro_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_felipecordeiiro_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/Felipecordeiiro/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_flavioferlin_en.md b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_flavioferlin_en.md
new file mode 100644
index 00000000000000..503c2291046d0d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_flavioferlin_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_flavioferlin SwinForImageClassification from flavioferlin
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_flavioferlin
+date: 2025-01-26
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_flavioferlin` is a English model originally trained by flavioferlin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_flavioferlin_en_5.5.1_3.0_1737889308572.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_flavioferlin_en_5.5.1_3.0_1737889308572.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_flavioferlin","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_flavioferlin","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_flavioferlin|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/flavioferlin/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_flavioferlin_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_flavioferlin_pipeline_en.md
new file mode 100644
index 00000000000000..2150cc0e2ad147
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_flavioferlin_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_flavioferlin_pipeline pipeline SwinForImageClassification from flavioferlin
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_flavioferlin_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_flavioferlin_pipeline` is a English model originally trained by flavioferlin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_flavioferlin_pipeline_en_5.5.1_3.0_1737889319258.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_flavioferlin_pipeline_en_5.5.1_3.0_1737889319258.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_flavioferlin_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_flavioferlin_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_flavioferlin_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/flavioferlin/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_hoanbklucky_en.md b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_hoanbklucky_en.md
new file mode 100644
index 00000000000000..f8686cbb72e53c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_hoanbklucky_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_hoanbklucky SwinForImageClassification from hoanbklucky
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_hoanbklucky
+date: 2025-01-26
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_hoanbklucky` is a English model originally trained by hoanbklucky.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_hoanbklucky_en_5.5.1_3.0_1737888634226.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_hoanbklucky_en_5.5.1_3.0_1737888634226.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_hoanbklucky","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_hoanbklucky","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_hoanbklucky|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.5 MB|
+
+## References
+
+https://huggingface.co/hoanbklucky/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_hoanbklucky_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_hoanbklucky_pipeline_en.md
new file mode 100644
index 00000000000000..2d488f185c2465
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_hoanbklucky_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_hoanbklucky_pipeline pipeline SwinForImageClassification from hoanbklucky
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_hoanbklucky_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_hoanbklucky_pipeline` is a English model originally trained by hoanbklucky.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_hoanbklucky_pipeline_en_5.5.1_3.0_1737888645234.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_hoanbklucky_pipeline_en_5.5.1_3.0_1737888645234.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_hoanbklucky_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_hoanbklucky_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_hoanbklucky_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.5 MB|
+
+## References
+
+https://huggingface.co/hoanbklucky/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_pankajgharai_en.md b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_pankajgharai_en.md
new file mode 100644
index 00000000000000..06d14896b351d5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_pankajgharai_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_pankajgharai SwinForImageClassification from pankajgharai
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_pankajgharai
+date: 2025-01-26
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_pankajgharai` is a English model originally trained by pankajgharai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_pankajgharai_en_5.5.1_3.0_1737889018703.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_pankajgharai_en_5.5.1_3.0_1737889018703.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_pankajgharai","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_pankajgharai","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_pankajgharai|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/pankajgharai/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_pankajgharai_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_pankajgharai_pipeline_en.md
new file mode 100644
index 00000000000000..89eaa45f7252e9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_pankajgharai_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_pankajgharai_pipeline pipeline SwinForImageClassification from pankajgharai
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_pankajgharai_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_pankajgharai_pipeline` is a English model originally trained by pankajgharai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_pankajgharai_pipeline_en_5.5.1_3.0_1737889029308.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_pankajgharai_pipeline_en_5.5.1_3.0_1737889029308.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_pankajgharai_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_pankajgharai_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_pankajgharai_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/pankajgharai/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_phvk1611_en.md b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_phvk1611_en.md
new file mode 100644
index 00000000000000..b358d1cdd6f14a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_phvk1611_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_phvk1611 SwinForImageClassification from PHVK1611
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_phvk1611
+date: 2025-01-26
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_phvk1611` is a English model originally trained by PHVK1611.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_phvk1611_en_5.5.1_3.0_1737889195457.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_phvk1611_en_5.5.1_3.0_1737889195457.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_phvk1611","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_phvk1611","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_phvk1611|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/PHVK1611/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_phvk1611_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_phvk1611_pipeline_en.md
new file mode 100644
index 00000000000000..2a2a0df2056829
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_phvk1611_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_phvk1611_pipeline pipeline SwinForImageClassification from PHVK1611
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_phvk1611_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_phvk1611_pipeline` is a English model originally trained by PHVK1611.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_phvk1611_pipeline_en_5.5.1_3.0_1737889207009.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_phvk1611_pipeline_en_5.5.1_3.0_1737889207009.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_phvk1611_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_phvk1611_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_phvk1611_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/PHVK1611/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_travellerio_en.md b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_travellerio_en.md
new file mode 100644
index 00000000000000..dcce620f068125
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_travellerio_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_travellerio SwinForImageClassification from travellerio
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_travellerio
+date: 2025-01-26
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_travellerio` is a English model originally trained by travellerio.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_travellerio_en_5.5.1_3.0_1737888617690.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_travellerio_en_5.5.1_3.0_1737888617690.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_travellerio","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_travellerio","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_travellerio|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/travellerio/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_travellerio_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_travellerio_pipeline_en.md
new file mode 100644
index 00000000000000..905ac82a412442
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_eurosat_travellerio_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_travellerio_pipeline pipeline SwinForImageClassification from travellerio
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_travellerio_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_travellerio_pipeline` is a English model originally trained by travellerio.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_travellerio_pipeline_en_5.5.1_3.0_1737888629357.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_travellerio_pipeline_en_5.5.1_3.0_1737888629357.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_travellerio_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_travellerio_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_travellerio_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/travellerio/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_landscape_en.md b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_landscape_en.md
new file mode 100644
index 00000000000000..4cca241307a500
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_landscape_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_landscape SwinForImageClassification from vintage-lavender619
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_landscape
+date: 2025-01-26
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_landscape` is a English model originally trained by vintage-lavender619.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_landscape_en_5.5.1_3.0_1737889233090.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_landscape_en_5.5.1_3.0_1737889233090.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_landscape","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_landscape","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_landscape|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|212.1 MB|
+
+## References
+
+https://huggingface.co/vintage-lavender619/swin-tiny-patch4-window7-224-finetuned-landscape
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_landscape_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_landscape_pipeline_en.md
new file mode 100644
index 00000000000000..47edc5749cff16
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_landscape_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_landscape_pipeline pipeline SwinForImageClassification from vintage-lavender619
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_landscape_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_landscape_pipeline` is a English model originally trained by vintage-lavender619.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_landscape_pipeline_en_5.5.1_3.0_1737889244878.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_landscape_pipeline_en_5.5.1_3.0_1737889244878.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_landscape_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_landscape_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_landscape_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|212.1 MB|
+
+## References
+
+https://huggingface.co/vintage-lavender619/swin-tiny-patch4-window7-224-finetuned-landscape
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_lungs_disease_en.md b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_lungs_disease_en.md
new file mode 100644
index 00000000000000..ca93fbf051959f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_lungs_disease_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_lungs_disease SwinForImageClassification from luciana
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_lungs_disease
+date: 2025-01-26
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_lungs_disease` is a English model originally trained by luciana.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_lungs_disease_en_5.5.1_3.0_1737889408527.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_lungs_disease_en_5.5.1_3.0_1737889408527.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_lungs_disease","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_lungs_disease","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_lungs_disease|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/luciana/swin-tiny-patch4-window7-224-finetuned-lungs-disease
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_lungs_disease_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_lungs_disease_pipeline_en.md
new file mode 100644
index 00000000000000..7bedff30aeb91d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_lungs_disease_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_lungs_disease_pipeline pipeline SwinForImageClassification from luciana
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_lungs_disease_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_lungs_disease_pipeline` is a English model originally trained by luciana.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_lungs_disease_pipeline_en_5.5.1_3.0_1737889419346.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_lungs_disease_pipeline_en_5.5.1_3.0_1737889419346.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_lungs_disease_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_lungs_disease_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_lungs_disease_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/luciana/swin-tiny-patch4-window7-224-finetuned-lungs-disease
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_wuqinhao_en.md b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_wuqinhao_en.md
new file mode 100644
index 00000000000000..359cc8a955462e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_wuqinhao_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_wuqinhao SwinForImageClassification from wuqinhao
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_wuqinhao
+date: 2025-01-26
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_wuqinhao` is a English model originally trained by wuqinhao.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_wuqinhao_en_5.5.1_3.0_1737888641478.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_wuqinhao_en_5.5.1_3.0_1737888641478.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_wuqinhao","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_wuqinhao","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_wuqinhao|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/wuqinhao/swin-tiny-patch4-window7-224-finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_wuqinhao_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_wuqinhao_pipeline_en.md
new file mode 100644
index 00000000000000..fe4f8c3537b99a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_finetuned_wuqinhao_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_wuqinhao_pipeline pipeline SwinForImageClassification from wuqinhao
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_wuqinhao_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_wuqinhao_pipeline` is a English model originally trained by wuqinhao.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_wuqinhao_pipeline_en_5.5.1_3.0_1737888652313.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_wuqinhao_pipeline_en_5.5.1_3.0_1737888652313.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_wuqinhao_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_wuqinhao_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_wuqinhao_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/wuqinhao/swin-tiny-patch4-window7-224-finetuned
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_for_pre_evaluation_en.md b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_for_pre_evaluation_en.md
new file mode 100644
index 00000000000000..03ed3aafde397c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_for_pre_evaluation_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_for_pre_evaluation SwinForImageClassification from Prot10
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_for_pre_evaluation
+date: 2025-01-26
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_for_pre_evaluation` is a English model originally trained by Prot10.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_for_pre_evaluation_en_5.5.1_3.0_1737889314150.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_for_pre_evaluation_en_5.5.1_3.0_1737889314150.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_for_pre_evaluation","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_for_pre_evaluation","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_for_pre_evaluation|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/Prot10/swin-tiny-patch4-window7-224-for-pre_evaluation
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_for_pre_evaluation_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_for_pre_evaluation_pipeline_en.md
new file mode 100644
index 00000000000000..9f0ed522f5e217
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_for_pre_evaluation_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_for_pre_evaluation_pipeline pipeline SwinForImageClassification from Prot10
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_for_pre_evaluation_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_for_pre_evaluation_pipeline` is a English model originally trained by Prot10.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_for_pre_evaluation_pipeline_en_5.5.1_3.0_1737889324929.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_for_pre_evaluation_pipeline_en_5.5.1_3.0_1737889324929.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_for_pre_evaluation_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_for_pre_evaluation_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_for_pre_evaluation_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/Prot10/swin-tiny-patch4-window7-224-for-pre_evaluation
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_kontur_competition_52k_en.md b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_kontur_competition_52k_en.md
new file mode 100644
index 00000000000000..ac0ea03395f75a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_kontur_competition_52k_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_kontur_competition_52k SwinForImageClassification from t1msan
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_kontur_competition_52k
+date: 2025-01-26
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_kontur_competition_52k` is a English model originally trained by t1msan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_kontur_competition_52k_en_5.5.1_3.0_1737888861803.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_kontur_competition_52k_en_5.5.1_3.0_1737888861803.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_kontur_competition_52k","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_kontur_competition_52k","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_kontur_competition_52k|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/t1msan/swin-tiny-patch4-window7-224-Kontur-competition-52K
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_kontur_competition_52k_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_kontur_competition_52k_pipeline_en.md
new file mode 100644
index 00000000000000..09cec79ece370e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_kontur_competition_52k_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_kontur_competition_52k_pipeline pipeline SwinForImageClassification from t1msan
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_kontur_competition_52k_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_kontur_competition_52k_pipeline` is a English model originally trained by t1msan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_kontur_competition_52k_pipeline_en_5.5.1_3.0_1737888872823.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_kontur_competition_52k_pipeline_en_5.5.1_3.0_1737888872823.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_kontur_competition_52k_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_kontur_competition_52k_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_kontur_competition_52k_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/t1msan/swin-tiny-patch4-window7-224-Kontur-competition-52K
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_pueba1_en.md b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_pueba1_en.md
new file mode 100644
index 00000000000000..ac60e49ee4564d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_pueba1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_pueba1 SwinForImageClassification from Angy309
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_pueba1
+date: 2025-01-26
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_pueba1` is a English model originally trained by Angy309.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_pueba1_en_5.5.1_3.0_1737888909845.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_pueba1_en_5.5.1_3.0_1737888909845.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_pueba1","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_pueba1","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_pueba1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/Angy309/swin-tiny-patch4-window7-224-pueba1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_pueba1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_pueba1_pipeline_en.md
new file mode 100644
index 00000000000000..be5113c7019e90
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_pueba1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_pueba1_pipeline pipeline SwinForImageClassification from Angy309
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_pueba1_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_pueba1_pipeline` is a English model originally trained by Angy309.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_pueba1_pipeline_en_5.5.1_3.0_1737888920719.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_pueba1_pipeline_en_5.5.1_3.0_1737888920719.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_pueba1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_pueba1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_pueba1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/Angy309/swin-tiny-patch4-window7-224-pueba1
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_venda_u13_b_24_en.md b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_venda_u13_b_24_en.md
new file mode 100644
index 00000000000000..d72efd73e05c83
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_venda_u13_b_24_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_venda_u13_b_24 SwinForImageClassification from Augusto777
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_venda_u13_b_24
+date: 2025-01-26
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_venda_u13_b_24` is a English model originally trained by Augusto777.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_venda_u13_b_24_en_5.5.1_3.0_1737889412575.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_venda_u13_b_24_en_5.5.1_3.0_1737889412575.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_venda_u13_b_24","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_venda_u13_b_24","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_venda_u13_b_24|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/Augusto777/swin-tiny-patch4-window7-224-ve-U13-b-24
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_venda_u13_b_24_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_venda_u13_b_24_pipeline_en.md
new file mode 100644
index 00000000000000..d9afec58fa10bf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-swin_tiny_patch4_window7_224_venda_u13_b_24_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_venda_u13_b_24_pipeline pipeline SwinForImageClassification from Augusto777
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_venda_u13_b_24_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_venda_u13_b_24_pipeline` is a English model originally trained by Augusto777.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_venda_u13_b_24_pipeline_en_5.5.1_3.0_1737889423136.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_venda_u13_b_24_pipeline_en_5.5.1_3.0_1737889423136.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_venda_u13_b_24_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_venda_u13_b_24_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_venda_u13_b_24_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/Augusto777/swin-tiny-patch4-window7-224-ve-U13-b-24
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-t5_base_for2inf_family_en.md b/docs/_posts/ahmedlone127/2025-01-26-t5_base_for2inf_family_en.md
new file mode 100644
index 00000000000000..475f03c032cd95
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-t5_base_for2inf_family_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_base_for2inf_family T5Transformer from ggallipoli
+author: John Snow Labs
+name: t5_base_for2inf_family
+date: 2025-01-26
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_base_for2inf_family` is a English model originally trained by ggallipoli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_base_for2inf_family_en_5.5.1_3.0_1737849602703.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_base_for2inf_family_en_5.5.1_3.0_1737849602703.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_base_for2inf_family","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_base_for2inf_family", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_base_for2inf_family|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|925.8 MB|
+
+## References
+
+https://huggingface.co/ggallipoli/t5-base_for2inf_family
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-t5_base_for2inf_family_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-t5_base_for2inf_family_pipeline_en.md
new file mode 100644
index 00000000000000..bfff9f3458de52
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-t5_base_for2inf_family_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_base_for2inf_family_pipeline pipeline T5Transformer from ggallipoli
+author: John Snow Labs
+name: t5_base_for2inf_family_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_base_for2inf_family_pipeline` is a English model originally trained by ggallipoli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_base_for2inf_family_pipeline_en_5.5.1_3.0_1737849652985.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_base_for2inf_family_pipeline_en_5.5.1_3.0_1737849652985.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_base_for2inf_family_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_base_for2inf_family_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_base_for2inf_family_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|925.8 MB|
+
+## References
+
+https://huggingface.co/ggallipoli/t5-base_for2inf_family
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-t5_base_inf2for_family_en.md b/docs/_posts/ahmedlone127/2025-01-26-t5_base_inf2for_family_en.md
new file mode 100644
index 00000000000000..5d4cf0d74930c1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-t5_base_inf2for_family_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_base_inf2for_family T5Transformer from ggallipoli
+author: John Snow Labs
+name: t5_base_inf2for_family
+date: 2025-01-26
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_base_inf2for_family` is a English model originally trained by ggallipoli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_base_inf2for_family_en_5.5.1_3.0_1737849755906.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_base_inf2for_family_en_5.5.1_3.0_1737849755906.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_base_inf2for_family","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_base_inf2for_family", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_base_inf2for_family|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|925.6 MB|
+
+## References
+
+https://huggingface.co/ggallipoli/t5-base_inf2for_family
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-t5_base_inf2for_family_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-t5_base_inf2for_family_pipeline_en.md
new file mode 100644
index 00000000000000..c7c92b110f74e3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-t5_base_inf2for_family_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_base_inf2for_family_pipeline pipeline T5Transformer from ggallipoli
+author: John Snow Labs
+name: t5_base_inf2for_family_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_base_inf2for_family_pipeline` is a English model originally trained by ggallipoli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_base_inf2for_family_pipeline_en_5.5.1_3.0_1737849805933.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_base_inf2for_family_pipeline_en_5.5.1_3.0_1737849805933.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_base_inf2for_family_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_base_inf2for_family_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_base_inf2for_family_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|925.6 MB|
+
+## References
+
+https://huggingface.co/ggallipoli/t5-base_inf2for_family
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-t5_large_inf2for_family_en.md b/docs/_posts/ahmedlone127/2025-01-26-t5_large_inf2for_family_en.md
new file mode 100644
index 00000000000000..becf1d15cf686a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-t5_large_inf2for_family_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_large_inf2for_family T5Transformer from ggallipoli
+author: John Snow Labs
+name: t5_large_inf2for_family
+date: 2025-01-26
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_large_inf2for_family` is a English model originally trained by ggallipoli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_large_inf2for_family_en_5.5.1_3.0_1737852437559.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_large_inf2for_family_en_5.5.1_3.0_1737852437559.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_large_inf2for_family","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_large_inf2for_family", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_large_inf2for_family|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|2.9 GB|
+
+## References
+
+https://huggingface.co/ggallipoli/t5-large_inf2for_family
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-t5_large_inf2for_family_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-t5_large_inf2for_family_pipeline_en.md
new file mode 100644
index 00000000000000..ab5fc1a49430ba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-t5_large_inf2for_family_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_large_inf2for_family_pipeline pipeline T5Transformer from ggallipoli
+author: John Snow Labs
+name: t5_large_inf2for_family_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_large_inf2for_family_pipeline` is a English model originally trained by ggallipoli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_large_inf2for_family_pipeline_en_5.5.1_3.0_1737852568337.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_large_inf2for_family_pipeline_en_5.5.1_3.0_1737852568337.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_large_inf2for_family_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_large_inf2for_family_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_large_inf2for_family_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|2.9 GB|
+
+## References
+
+https://huggingface.co/ggallipoli/t5-large_inf2for_family
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-t5_qa_model_newsqa_en.md b/docs/_posts/ahmedlone127/2025-01-26-t5_qa_model_newsqa_en.md
new file mode 100644
index 00000000000000..42d919f6fd7c0f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-t5_qa_model_newsqa_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_qa_model_newsqa T5Transformer from Pavan48
+author: John Snow Labs
+name: t5_qa_model_newsqa
+date: 2025-01-26
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_qa_model_newsqa` is a English model originally trained by Pavan48.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_qa_model_newsqa_en_5.5.1_3.0_1737851566837.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_qa_model_newsqa_en_5.5.1_3.0_1737851566837.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_qa_model_newsqa","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_qa_model_newsqa", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_qa_model_newsqa|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|902.7 MB|
+
+## References
+
+https://huggingface.co/Pavan48/T5-QA_model-NEWSQA
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-t5_qa_model_newsqa_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-t5_qa_model_newsqa_pipeline_en.md
new file mode 100644
index 00000000000000..21b8bce7c70869
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-t5_qa_model_newsqa_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_qa_model_newsqa_pipeline pipeline T5Transformer from Pavan48
+author: John Snow Labs
+name: t5_qa_model_newsqa_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_qa_model_newsqa_pipeline` is a English model originally trained by Pavan48.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_qa_model_newsqa_pipeline_en_5.5.1_3.0_1737851615945.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_qa_model_newsqa_pipeline_en_5.5.1_3.0_1737851615945.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_qa_model_newsqa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_qa_model_newsqa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_qa_model_newsqa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|902.7 MB|
+
+## References
+
+https://huggingface.co/Pavan48/T5-QA_model-NEWSQA
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-t5_small_sum_dpo_10k_1_1ep_en.md b/docs/_posts/ahmedlone127/2025-01-26-t5_small_sum_dpo_10k_1_1ep_en.md
new file mode 100644
index 00000000000000..7aae844b915e8d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-t5_small_sum_dpo_10k_1_1ep_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_small_sum_dpo_10k_1_1ep T5Transformer from Muadil
+author: John Snow Labs
+name: t5_small_sum_dpo_10k_1_1ep
+date: 2025-01-26
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_sum_dpo_10k_1_1ep` is a English model originally trained by Muadil.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_10k_1_1ep_en_5.5.1_3.0_1737851793319.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_10k_1_1ep_en_5.5.1_3.0_1737851793319.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_small_sum_dpo_10k_1_1ep","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_small_sum_dpo_10k_1_1ep", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_sum_dpo_10k_1_1ep|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|155.8 MB|
+
+## References
+
+https://huggingface.co/Muadil/t5-small_sum_DPO_10k_1_1ep
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-t5_small_sum_dpo_10k_1_1ep_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-t5_small_sum_dpo_10k_1_1ep_pipeline_en.md
new file mode 100644
index 00000000000000..f2a5bafdc2de05
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-t5_small_sum_dpo_10k_1_1ep_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_small_sum_dpo_10k_1_1ep_pipeline pipeline T5Transformer from Muadil
+author: John Snow Labs
+name: t5_small_sum_dpo_10k_1_1ep_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_sum_dpo_10k_1_1ep_pipeline` is a English model originally trained by Muadil.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_10k_1_1ep_pipeline_en_5.5.1_3.0_1737851844973.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_10k_1_1ep_pipeline_en_5.5.1_3.0_1737851844973.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_small_sum_dpo_10k_1_1ep_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_small_sum_dpo_10k_1_1ep_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_sum_dpo_10k_1_1ep_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|155.8 MB|
+
+## References
+
+https://huggingface.co/Muadil/t5-small_sum_DPO_10k_1_1ep
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-tamil_legacy_roman_classifier_v2_en.md b/docs/_posts/ahmedlone127/2025-01-26-tamil_legacy_roman_classifier_v2_en.md
new file mode 100644
index 00000000000000..5659afa4c17ed8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-tamil_legacy_roman_classifier_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English tamil_legacy_roman_classifier_v2 BertForSequenceClassification from sanujen
+author: John Snow Labs
+name: tamil_legacy_roman_classifier_v2
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tamil_legacy_roman_classifier_v2` is a English model originally trained by sanujen.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tamil_legacy_roman_classifier_v2_en_5.5.1_3.0_1737921575313.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tamil_legacy_roman_classifier_v2_en_5.5.1_3.0_1737921575313.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("tamil_legacy_roman_classifier_v2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("tamil_legacy_roman_classifier_v2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tamil_legacy_roman_classifier_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/sanujen/Tamil_Legacy_Roman_Classifier_V2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-tamil_legacy_roman_classifier_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-tamil_legacy_roman_classifier_v2_pipeline_en.md
new file mode 100644
index 00000000000000..c9b6403b7cebe8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-tamil_legacy_roman_classifier_v2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English tamil_legacy_roman_classifier_v2_pipeline pipeline BertForSequenceClassification from sanujen
+author: John Snow Labs
+name: tamil_legacy_roman_classifier_v2_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tamil_legacy_roman_classifier_v2_pipeline` is a English model originally trained by sanujen.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tamil_legacy_roman_classifier_v2_pipeline_en_5.5.1_3.0_1737921595978.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tamil_legacy_roman_classifier_v2_pipeline_en_5.5.1_3.0_1737921595978.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("tamil_legacy_roman_classifier_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("tamil_legacy_roman_classifier_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tamil_legacy_roman_classifier_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/sanujen/Tamil_Legacy_Roman_Classifier_V2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-tesla81_pipeline_sr.md b/docs/_posts/ahmedlone127/2025-01-26-tesla81_pipeline_sr.md
new file mode 100644
index 00000000000000..088155a1180e7d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-tesla81_pipeline_sr.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Serbian tesla81_pipeline pipeline RoBertaEmbeddings from te-sla
+author: John Snow Labs
+name: tesla81_pipeline
+date: 2025-01-26
+tags: [sr, open_source, pipeline, onnx]
+task: Embeddings
+language: sr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tesla81_pipeline` is a Serbian model originally trained by te-sla.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tesla81_pipeline_sr_5.5.1_3.0_1737866411329.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tesla81_pipeline_sr_5.5.1_3.0_1737866411329.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("tesla81_pipeline", lang = "sr")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("tesla81_pipeline", lang = "sr")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tesla81_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|sr|
+|Size:|290.5 MB|
+
+## References
+
+https://huggingface.co/te-sla/Tesla81
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-tesla81_sr.md b/docs/_posts/ahmedlone127/2025-01-26-tesla81_sr.md
new file mode 100644
index 00000000000000..faa5fb2de58b7f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-tesla81_sr.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Serbian tesla81 RoBertaEmbeddings from te-sla
+author: John Snow Labs
+name: tesla81
+date: 2025-01-26
+tags: [sr, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: sr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tesla81` is a Serbian model originally trained by te-sla.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tesla81_sr_5.5.1_3.0_1737866392471.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tesla81_sr_5.5.1_3.0_1737866392471.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("tesla81","sr") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("tesla81","sr") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tesla81|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|sr|
+|Size:|290.5 MB|
+
+## References
+
+https://huggingface.co/te-sla/Tesla81
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-test1_isom5240grp21_en.md b/docs/_posts/ahmedlone127/2025-01-26-test1_isom5240grp21_en.md
new file mode 100644
index 00000000000000..a2d15ae1c36b5b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-test1_isom5240grp21_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English test1_isom5240grp21 DistilBertForSequenceClassification from isom5240grp21
+author: John Snow Labs
+name: test1_isom5240grp21
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test1_isom5240grp21` is a English model originally trained by isom5240grp21.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test1_isom5240grp21_en_5.5.1_3.0_1737929560944.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test1_isom5240grp21_en_5.5.1_3.0_1737929560944.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("test1_isom5240grp21","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("test1_isom5240grp21", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test1_isom5240grp21|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/isom5240grp21/test1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-test1_isom5240grp21_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-test1_isom5240grp21_pipeline_en.md
new file mode 100644
index 00000000000000..be3eb9b9f21a84
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-test1_isom5240grp21_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English test1_isom5240grp21_pipeline pipeline DistilBertForSequenceClassification from isom5240grp21
+author: John Snow Labs
+name: test1_isom5240grp21_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test1_isom5240grp21_pipeline` is a English model originally trained by isom5240grp21.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test1_isom5240grp21_pipeline_en_5.5.1_3.0_1737929574032.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test1_isom5240grp21_pipeline_en_5.5.1_3.0_1737929574032.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("test1_isom5240grp21_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("test1_isom5240grp21_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test1_isom5240grp21_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/isom5240grp21/test1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-test_gpt2_naul_en.md b/docs/_posts/ahmedlone127/2025-01-26-test_gpt2_naul_en.md
new file mode 100644
index 00000000000000..893ec2f5ef9e97
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-test_gpt2_naul_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English test_gpt2_naul GPT2Transformer from naul
+author: John Snow Labs
+name: test_gpt2_naul
+date: 2025-01-26
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_gpt2_naul` is a English model originally trained by naul.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_gpt2_naul_en_5.5.1_3.0_1737915883508.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_gpt2_naul_en_5.5.1_3.0_1737915883508.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("test_gpt2_naul","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("test_gpt2_naul","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_gpt2_naul|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|465.7 MB|
+
+## References
+
+https://huggingface.co/naul/test-gpt2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-test_gpt2_naul_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-test_gpt2_naul_pipeline_en.md
new file mode 100644
index 00000000000000..896b0b71961e04
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-test_gpt2_naul_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English test_gpt2_naul_pipeline pipeline GPT2Transformer from naul
+author: John Snow Labs
+name: test_gpt2_naul_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_gpt2_naul_pipeline` is a English model originally trained by naul.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_gpt2_naul_pipeline_en_5.5.1_3.0_1737915906987.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_gpt2_naul_pipeline_en_5.5.1_3.0_1737915906987.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("test_gpt2_naul_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("test_gpt2_naul_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_gpt2_naul_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|465.7 MB|
+
+## References
+
+https://huggingface.co/naul/test-gpt2
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-test_ner_boghdadyjr_en.md b/docs/_posts/ahmedlone127/2025-01-26-test_ner_boghdadyjr_en.md
new file mode 100644
index 00000000000000..529ef116fe9c1d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-test_ner_boghdadyjr_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English test_ner_boghdadyjr BertForTokenClassification from BoghdadyJR
+author: John Snow Labs
+name: test_ner_boghdadyjr
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_ner_boghdadyjr` is a English model originally trained by BoghdadyJR.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_ner_boghdadyjr_en_5.5.1_3.0_1737933322704.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_ner_boghdadyjr_en_5.5.1_3.0_1737933322704.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("test_ner_boghdadyjr","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("test_ner_boghdadyjr", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_ner_boghdadyjr|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/BoghdadyJR/test-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-test_ner_boghdadyjr_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-test_ner_boghdadyjr_pipeline_en.md
new file mode 100644
index 00000000000000..4fe662a0fd3525
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-test_ner_boghdadyjr_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English test_ner_boghdadyjr_pipeline pipeline BertForTokenClassification from BoghdadyJR
+author: John Snow Labs
+name: test_ner_boghdadyjr_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_ner_boghdadyjr_pipeline` is a English model originally trained by BoghdadyJR.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_ner_boghdadyjr_pipeline_en_5.5.1_3.0_1737933349365.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_ner_boghdadyjr_pipeline_en_5.5.1_3.0_1737933349365.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("test_ner_boghdadyjr_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("test_ner_boghdadyjr_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_ner_boghdadyjr_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/BoghdadyJR/test-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-test_ner_hr_wesbeaver_en.md b/docs/_posts/ahmedlone127/2025-01-26-test_ner_hr_wesbeaver_en.md
new file mode 100644
index 00000000000000..eb4d48a700112e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-test_ner_hr_wesbeaver_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English test_ner_hr_wesbeaver BertForTokenClassification from hr-wesbeaver
+author: John Snow Labs
+name: test_ner_hr_wesbeaver
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_ner_hr_wesbeaver` is a English model originally trained by hr-wesbeaver.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_ner_hr_wesbeaver_en_5.5.1_3.0_1737935263293.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_ner_hr_wesbeaver_en_5.5.1_3.0_1737935263293.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("test_ner_hr_wesbeaver","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("test_ner_hr_wesbeaver", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_ner_hr_wesbeaver|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/hr-wesbeaver/test-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-test_ner_hr_wesbeaver_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-test_ner_hr_wesbeaver_pipeline_en.md
new file mode 100644
index 00000000000000..32879b32016fca
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-test_ner_hr_wesbeaver_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English test_ner_hr_wesbeaver_pipeline pipeline BertForTokenClassification from hr-wesbeaver
+author: John Snow Labs
+name: test_ner_hr_wesbeaver_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_ner_hr_wesbeaver_pipeline` is a English model originally trained by hr-wesbeaver.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_ner_hr_wesbeaver_pipeline_en_5.5.1_3.0_1737935287211.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_ner_hr_wesbeaver_pipeline_en_5.5.1_3.0_1737935287211.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("test_ner_hr_wesbeaver_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("test_ner_hr_wesbeaver_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_ner_hr_wesbeaver_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/hr-wesbeaver/test-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-test_qa_en.md b/docs/_posts/ahmedlone127/2025-01-26-test_qa_en.md
new file mode 100644
index 00000000000000..e1646fcae03742
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-test_qa_en.md
@@ -0,0 +1,92 @@
+---
+layout: model
+title: English test_qa DistilBertForQuestionAnswering from hoang14
+author: John Snow Labs
+name: test_qa
+date: 2025-01-26
+tags: [distilbert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_qa` is a English model originally trained by hoang14.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_qa_en_5.5.1_3.0_1737918991828.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_qa_en_5.5.1_3.0_1737918991828.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("test_qa","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering  
+    .pretrained("test_qa", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_qa|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+References
+
+https://huggingface.co/hoang14/test_qa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-test_qa_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-test_qa_pipeline_en.md
new file mode 100644
index 00000000000000..b130f2a89e0304
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-test_qa_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English test_qa_pipeline pipeline BertForQuestionAnswering from nathantablang
+author: John Snow Labs
+name: test_qa_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_qa_pipeline` is a English model originally trained by nathantablang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_qa_pipeline_en_5.5.1_3.0_1737919064764.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_qa_pipeline_en_5.5.1_3.0_1737919064764.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("test_qa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("test_qa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_qa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/nathantablang/test-qa
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-test_trainer_ashed00_en.md b/docs/_posts/ahmedlone127/2025-01-26-test_trainer_ashed00_en.md
new file mode 100644
index 00000000000000..1aa62410ded3a5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-test_trainer_ashed00_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English test_trainer_ashed00 DistilBertForSequenceClassification from Ashed00
+author: John Snow Labs
+name: test_trainer_ashed00
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_trainer_ashed00` is a English model originally trained by Ashed00.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_trainer_ashed00_en_5.5.1_3.0_1737929166393.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_trainer_ashed00_en_5.5.1_3.0_1737929166393.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("test_trainer_ashed00","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("test_trainer_ashed00", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_trainer_ashed00|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Ashed00/test_trainer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-test_trainer_ashed00_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-test_trainer_ashed00_pipeline_en.md
new file mode 100644
index 00000000000000..f700ef0dee5786
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-test_trainer_ashed00_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English test_trainer_ashed00_pipeline pipeline DistilBertForSequenceClassification from Ashed00
+author: John Snow Labs
+name: test_trainer_ashed00_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_trainer_ashed00_pipeline` is a English model originally trained by Ashed00.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_trainer_ashed00_pipeline_en_5.5.1_3.0_1737929180517.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_trainer_ashed00_pipeline_en_5.5.1_3.0_1737929180517.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("test_trainer_ashed00_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("test_trainer_ashed00_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_trainer_ashed00_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Ashed00/test_trainer
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-title_generation1_for_yt_videos_en.md b/docs/_posts/ahmedlone127/2025-01-26-title_generation1_for_yt_videos_en.md
new file mode 100644
index 00000000000000..d763833b4d841c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-title_generation1_for_yt_videos_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English title_generation1_for_yt_videos T5Transformer from michc
+author: John Snow Labs
+name: title_generation1_for_yt_videos
+date: 2025-01-26
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`title_generation1_for_yt_videos` is a English model originally trained by michc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/title_generation1_for_yt_videos_en_5.5.1_3.0_1737850527229.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/title_generation1_for_yt_videos_en_5.5.1_3.0_1737850527229.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("title_generation1_for_yt_videos","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("title_generation1_for_yt_videos", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|title_generation1_for_yt_videos|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/michc/title-generation1-for-YT-videos
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-title_generation1_for_yt_videos_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-title_generation1_for_yt_videos_pipeline_en.md
new file mode 100644
index 00000000000000..16d47a6e3965c8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-title_generation1_for_yt_videos_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English title_generation1_for_yt_videos_pipeline pipeline T5Transformer from michc
+author: John Snow Labs
+name: title_generation1_for_yt_videos_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`title_generation1_for_yt_videos_pipeline` is a English model originally trained by michc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/title_generation1_for_yt_videos_pipeline_en_5.5.1_3.0_1737850576143.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/title_generation1_for_yt_videos_pipeline_en_5.5.1_3.0_1737850576143.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("title_generation1_for_yt_videos_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("title_generation1_for_yt_videos_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|title_generation1_for_yt_videos_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/michc/title-generation1-for-YT-videos
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-title_instruction_pipeline_uk.md b/docs/_posts/ahmedlone127/2025-01-26-title_instruction_pipeline_uk.md
new file mode 100644
index 00000000000000..a78bf97ba29247
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-title_instruction_pipeline_uk.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Ukrainian title_instruction_pipeline pipeline XlmRoBertaForSequenceClassification from zeusfsx
+author: John Snow Labs
+name: title_instruction_pipeline
+date: 2025-01-26
+tags: [uk, open_source, pipeline, onnx]
+task: Text Classification
+language: uk
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`title_instruction_pipeline` is a Ukrainian model originally trained by zeusfsx.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/title_instruction_pipeline_uk_5.5.1_3.0_1737881431559.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/title_instruction_pipeline_uk_5.5.1_3.0_1737881431559.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("title_instruction_pipeline", lang = "uk")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("title_instruction_pipeline", lang = "uk")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|title_instruction_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|uk|
+|Size:|390.4 MB|
+
+## References
+
+https://huggingface.co/zeusfsx/title-instruction
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-title_instruction_uk.md b/docs/_posts/ahmedlone127/2025-01-26-title_instruction_uk.md
new file mode 100644
index 00000000000000..3b3fbc4224c193
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-title_instruction_uk.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Ukrainian title_instruction XlmRoBertaForSequenceClassification from zeusfsx
+author: John Snow Labs
+name: title_instruction
+date: 2025-01-26
+tags: [uk, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: uk
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`title_instruction` is a Ukrainian model originally trained by zeusfsx.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/title_instruction_uk_5.5.1_3.0_1737881401246.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/title_instruction_uk_5.5.1_3.0_1737881401246.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("title_instruction","uk") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("title_instruction", "uk")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|title_instruction|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|uk|
+|Size:|390.3 MB|
+
+## References
+
+https://huggingface.co/zeusfsx/title-instruction
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-tr20m_gpt2tok_en.md b/docs/_posts/ahmedlone127/2025-01-26-tr20m_gpt2tok_en.md
new file mode 100644
index 00000000000000..72ad8919ca81a1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-tr20m_gpt2tok_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English tr20m_gpt2tok GPT2Transformer from clio-ai
+author: John Snow Labs
+name: tr20m_gpt2tok
+date: 2025-01-26
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tr20m_gpt2tok` is a English model originally trained by clio-ai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tr20m_gpt2tok_en_5.5.1_3.0_1737874414480.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tr20m_gpt2tok_en_5.5.1_3.0_1737874414480.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("tr20m_gpt2tok","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("tr20m_gpt2tok","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tr20m_gpt2tok|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|77.6 MB|
+
+## References
+
+https://huggingface.co/clio-ai/tr20m_gpt2tok
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-tr20m_gpt2tok_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-tr20m_gpt2tok_pipeline_en.md
new file mode 100644
index 00000000000000..1817f3a7c4c486
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-tr20m_gpt2tok_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English tr20m_gpt2tok_pipeline pipeline GPT2Transformer from clio-ai
+author: John Snow Labs
+name: tr20m_gpt2tok_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tr20m_gpt2tok_pipeline` is a English model originally trained by clio-ai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tr20m_gpt2tok_pipeline_en_5.5.1_3.0_1737874418454.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tr20m_gpt2tok_pipeline_en_5.5.1_3.0_1737874418454.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("tr20m_gpt2tok_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("tr20m_gpt2tok_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tr20m_gpt2tok_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|77.6 MB|
+
+## References
+
+https://huggingface.co/clio-ai/tr20m_gpt2tok
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-trained_distilbert_indonesia_presidential_election_balanced_dataset_id.md b/docs/_posts/ahmedlone127/2025-01-26-trained_distilbert_indonesia_presidential_election_balanced_dataset_id.md
new file mode 100644
index 00000000000000..b3b6fdb65ff757
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-trained_distilbert_indonesia_presidential_election_balanced_dataset_id.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Indonesian trained_distilbert_indonesia_presidential_election_balanced_dataset DistilBertForSequenceClassification from Rendika
+author: John Snow Labs
+name: trained_distilbert_indonesia_presidential_election_balanced_dataset
+date: 2025-01-26
+tags: [id, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: id
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`trained_distilbert_indonesia_presidential_election_balanced_dataset` is a Indonesian model originally trained by Rendika.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/trained_distilbert_indonesia_presidential_election_balanced_dataset_id_5.5.1_3.0_1737873866436.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/trained_distilbert_indonesia_presidential_election_balanced_dataset_id_5.5.1_3.0_1737873866436.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("trained_distilbert_indonesia_presidential_election_balanced_dataset","id") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("trained_distilbert_indonesia_presidential_election_balanced_dataset", "id")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|trained_distilbert_indonesia_presidential_election_balanced_dataset|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|id|
+|Size:|255.3 MB|
+
+## References
+
+https://huggingface.co/Rendika/Trained-DistilBERT-Indonesia-Presidential-Election-Balanced-Dataset
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-trained_distilbert_indonesia_presidential_election_balanced_dataset_pipeline_id.md b/docs/_posts/ahmedlone127/2025-01-26-trained_distilbert_indonesia_presidential_election_balanced_dataset_pipeline_id.md
new file mode 100644
index 00000000000000..6fe4b60512f78a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-trained_distilbert_indonesia_presidential_election_balanced_dataset_pipeline_id.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Indonesian trained_distilbert_indonesia_presidential_election_balanced_dataset_pipeline pipeline DistilBertForSequenceClassification from Rendika
+author: John Snow Labs
+name: trained_distilbert_indonesia_presidential_election_balanced_dataset_pipeline
+date: 2025-01-26
+tags: [id, open_source, pipeline, onnx]
+task: Text Classification
+language: id
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`trained_distilbert_indonesia_presidential_election_balanced_dataset_pipeline` is a Indonesian model originally trained by Rendika.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/trained_distilbert_indonesia_presidential_election_balanced_dataset_pipeline_id_5.5.1_3.0_1737873881596.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/trained_distilbert_indonesia_presidential_election_balanced_dataset_pipeline_id_5.5.1_3.0_1737873881596.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("trained_distilbert_indonesia_presidential_election_balanced_dataset_pipeline", lang = "id")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("trained_distilbert_indonesia_presidential_election_balanced_dataset_pipeline", lang = "id")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|trained_distilbert_indonesia_presidential_election_balanced_dataset_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|id|
+|Size:|255.3 MB|
+
+## References
+
+https://huggingface.co/Rendika/Trained-DistilBERT-Indonesia-Presidential-Election-Balanced-Dataset
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-training_dir_en.md b/docs/_posts/ahmedlone127/2025-01-26-training_dir_en.md
new file mode 100644
index 00000000000000..620937f480ad09
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-training_dir_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English training_dir XlmRoBertaForSequenceClassification from sahil-zzzz
+author: John Snow Labs
+name: training_dir
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`training_dir` is a English model originally trained by sahil-zzzz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/training_dir_en_5.5.1_3.0_1737884600769.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/training_dir_en_5.5.1_3.0_1737884600769.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("training_dir","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("training_dir", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|training_dir|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|834.8 MB|
+
+## References
+
+https://huggingface.co/sahil-zzzz/training_dir
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-training_dir_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-training_dir_pipeline_en.md
new file mode 100644
index 00000000000000..8b1c1848cc5238
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-training_dir_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English training_dir_pipeline pipeline XlmRoBertaForSequenceClassification from sahil-zzzz
+author: John Snow Labs
+name: training_dir_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`training_dir_pipeline` is a English model originally trained by sahil-zzzz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/training_dir_pipeline_en_5.5.1_3.0_1737884690526.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/training_dir_pipeline_en_5.5.1_3.0_1737884690526.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("training_dir_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("training_dir_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|training_dir_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|834.8 MB|
+
+## References
+
+https://huggingface.co/sahil-zzzz/training_dir
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-trial_project_en.md b/docs/_posts/ahmedlone127/2025-01-26-trial_project_en.md
new file mode 100644
index 00000000000000..c4e49abc19f9ce
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-trial_project_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English trial_project DistilBertForSequenceClassification from aurielwish
+author: John Snow Labs
+name: trial_project
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`trial_project` is a English model originally trained by aurielwish.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/trial_project_en_5.5.1_3.0_1737928936906.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/trial_project_en_5.5.1_3.0_1737928936906.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("trial_project","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("trial_project", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|trial_project|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/aurielwish/trial-project
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-trial_project_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-trial_project_pipeline_en.md
new file mode 100644
index 00000000000000..00beb0cc4ea5d1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-trial_project_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English trial_project_pipeline pipeline DistilBertForSequenceClassification from aurielwish
+author: John Snow Labs
+name: trial_project_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`trial_project_pipeline` is a English model originally trained by aurielwish.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/trial_project_pipeline_en_5.5.1_3.0_1737928950436.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/trial_project_pipeline_en_5.5.1_3.0_1737928950436.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("trial_project_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("trial_project_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|trial_project_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/aurielwish/trial-project
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-twitter_financial_sentiment_en.md b/docs/_posts/ahmedlone127/2025-01-26-twitter_financial_sentiment_en.md
new file mode 100644
index 00000000000000..b0a763521b221c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-twitter_financial_sentiment_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English twitter_financial_sentiment DistilBertForSequenceClassification from alcatere
+author: John Snow Labs
+name: twitter_financial_sentiment
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_financial_sentiment` is a English model originally trained by alcatere.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twitter_financial_sentiment_en_5.5.1_3.0_1737905426425.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_financial_sentiment_en_5.5.1_3.0_1737905426425.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("twitter_financial_sentiment","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("twitter_financial_sentiment", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|twitter_financial_sentiment|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/alcatere/twitter_financial_sentiment
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-twitter_financial_sentiment_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-twitter_financial_sentiment_pipeline_en.md
new file mode 100644
index 00000000000000..64f18cff9121b7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-twitter_financial_sentiment_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English twitter_financial_sentiment_pipeline pipeline DistilBertForSequenceClassification from alcatere
+author: John Snow Labs
+name: twitter_financial_sentiment_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_financial_sentiment_pipeline` is a English model originally trained by alcatere.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twitter_financial_sentiment_pipeline_en_5.5.1_3.0_1737905440030.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_financial_sentiment_pipeline_en_5.5.1_3.0_1737905440030.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("twitter_financial_sentiment_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("twitter_financial_sentiment_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|twitter_financial_sentiment_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/alcatere/twitter_financial_sentiment
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-twitter_xlm_roberta_base_sentiment_deletion_multiclass_gr_en.md b/docs/_posts/ahmedlone127/2025-01-26-twitter_xlm_roberta_base_sentiment_deletion_multiclass_gr_en.md
new file mode 100644
index 00000000000000..0625e681dd1c74
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-twitter_xlm_roberta_base_sentiment_deletion_multiclass_gr_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English twitter_xlm_roberta_base_sentiment_deletion_multiclass_gr XlmRoBertaForSequenceClassification from research-dump
+author: John Snow Labs
+name: twitter_xlm_roberta_base_sentiment_deletion_multiclass_gr
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_xlm_roberta_base_sentiment_deletion_multiclass_gr` is a English model originally trained by research-dump.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twitter_xlm_roberta_base_sentiment_deletion_multiclass_gr_en_5.5.1_3.0_1737885537970.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_xlm_roberta_base_sentiment_deletion_multiclass_gr_en_5.5.1_3.0_1737885537970.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("twitter_xlm_roberta_base_sentiment_deletion_multiclass_gr","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("twitter_xlm_roberta_base_sentiment_deletion_multiclass_gr", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|twitter_xlm_roberta_base_sentiment_deletion_multiclass_gr|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/research-dump/twitter-xlm-roberta-base-sentiment_deletion_multiclass_gr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-twitter_xlm_roberta_base_sentiment_deletion_multiclass_gr_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-twitter_xlm_roberta_base_sentiment_deletion_multiclass_gr_pipeline_en.md
new file mode 100644
index 00000000000000..4581be4e388c3a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-twitter_xlm_roberta_base_sentiment_deletion_multiclass_gr_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English twitter_xlm_roberta_base_sentiment_deletion_multiclass_gr_pipeline pipeline XlmRoBertaForSequenceClassification from research-dump
+author: John Snow Labs
+name: twitter_xlm_roberta_base_sentiment_deletion_multiclass_gr_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_xlm_roberta_base_sentiment_deletion_multiclass_gr_pipeline` is a English model originally trained by research-dump.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twitter_xlm_roberta_base_sentiment_deletion_multiclass_gr_pipeline_en_5.5.1_3.0_1737885591344.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_xlm_roberta_base_sentiment_deletion_multiclass_gr_pipeline_en_5.5.1_3.0_1737885591344.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("twitter_xlm_roberta_base_sentiment_deletion_multiclass_gr_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("twitter_xlm_roberta_base_sentiment_deletion_multiclass_gr_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|twitter_xlm_roberta_base_sentiment_deletion_multiclass_gr_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/research-dump/twitter-xlm-roberta-base-sentiment_deletion_multiclass_gr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-twitter_xlm_roberta_base_sentiment_deletion_multiclass_spanish_masked_en.md b/docs/_posts/ahmedlone127/2025-01-26-twitter_xlm_roberta_base_sentiment_deletion_multiclass_spanish_masked_en.md
new file mode 100644
index 00000000000000..6388ac64623cde
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-twitter_xlm_roberta_base_sentiment_deletion_multiclass_spanish_masked_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English twitter_xlm_roberta_base_sentiment_deletion_multiclass_spanish_masked XlmRoBertaForSequenceClassification from research-dump
+author: John Snow Labs
+name: twitter_xlm_roberta_base_sentiment_deletion_multiclass_spanish_masked
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_xlm_roberta_base_sentiment_deletion_multiclass_spanish_masked` is a English model originally trained by research-dump.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twitter_xlm_roberta_base_sentiment_deletion_multiclass_spanish_masked_en_5.5.1_3.0_1737884716148.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_xlm_roberta_base_sentiment_deletion_multiclass_spanish_masked_en_5.5.1_3.0_1737884716148.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("twitter_xlm_roberta_base_sentiment_deletion_multiclass_spanish_masked","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("twitter_xlm_roberta_base_sentiment_deletion_multiclass_spanish_masked", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|twitter_xlm_roberta_base_sentiment_deletion_multiclass_spanish_masked|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/research-dump/twitter-xlm-roberta-base-sentiment_deletion_multiclass_es_masked
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-twitter_xlm_roberta_base_sentiment_deletion_multiclass_spanish_masked_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-twitter_xlm_roberta_base_sentiment_deletion_multiclass_spanish_masked_pipeline_en.md
new file mode 100644
index 00000000000000..1f0103c9735457
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-twitter_xlm_roberta_base_sentiment_deletion_multiclass_spanish_masked_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English twitter_xlm_roberta_base_sentiment_deletion_multiclass_spanish_masked_pipeline pipeline XlmRoBertaForSequenceClassification from research-dump
+author: John Snow Labs
+name: twitter_xlm_roberta_base_sentiment_deletion_multiclass_spanish_masked_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_xlm_roberta_base_sentiment_deletion_multiclass_spanish_masked_pipeline` is a English model originally trained by research-dump.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twitter_xlm_roberta_base_sentiment_deletion_multiclass_spanish_masked_pipeline_en_5.5.1_3.0_1737884769605.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_xlm_roberta_base_sentiment_deletion_multiclass_spanish_masked_pipeline_en_5.5.1_3.0_1737884769605.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("twitter_xlm_roberta_base_sentiment_deletion_multiclass_spanish_masked_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("twitter_xlm_roberta_base_sentiment_deletion_multiclass_spanish_masked_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|twitter_xlm_roberta_base_sentiment_deletion_multiclass_spanish_masked_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/research-dump/twitter-xlm-roberta-base-sentiment_deletion_multiclass_es_masked
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-visual_emotion_classification_en.md b/docs/_posts/ahmedlone127/2025-01-26-visual_emotion_classification_en.md
new file mode 100644
index 00000000000000..426dcbe771f656
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-visual_emotion_classification_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English visual_emotion_classification ViTForImageClassification from yangswei
+author: John Snow Labs
+name: visual_emotion_classification
+date: 2025-01-26
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`visual_emotion_classification` is a English model originally trained by yangswei.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/visual_emotion_classification_en_5.5.1_3.0_1737926061863.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/visual_emotion_classification_en_5.5.1_3.0_1737926061863.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""visual_emotion_classification","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("visual_emotion_classification","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|visual_emotion_classification|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/yangswei/visual-emotion-classification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-visual_emotion_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-visual_emotion_classification_pipeline_en.md
new file mode 100644
index 00000000000000..7fd6513fae89bc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-visual_emotion_classification_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English visual_emotion_classification_pipeline pipeline ViTForImageClassification from yangswei
+author: John Snow Labs
+name: visual_emotion_classification_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`visual_emotion_classification_pipeline` is a English model originally trained by yangswei.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/visual_emotion_classification_pipeline_en_5.5.1_3.0_1737926080910.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/visual_emotion_classification_pipeline_en_5.5.1_3.0_1737926080910.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("visual_emotion_classification_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("visual_emotion_classification_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|visual_emotion_classification_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/yangswei/visual-emotion-classification
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-vit_base_patch16_224_glrh11_en.md b/docs/_posts/ahmedlone127/2025-01-26-vit_base_patch16_224_glrh11_en.md
new file mode 100644
index 00000000000000..044df1de81ad65
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-vit_base_patch16_224_glrh11_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_base_patch16_224_glrh11 ViTForImageClassification from glrh11
+author: John Snow Labs
+name: vit_base_patch16_224_glrh11
+date: 2025-01-26
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_patch16_224_glrh11` is a English model originally trained by glrh11.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_glrh11_en_5.5.1_3.0_1737925925101.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_glrh11_en_5.5.1_3.0_1737925925101.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vit_base_patch16_224_glrh11","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vit_base_patch16_224_glrh11","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_patch16_224_glrh11|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|324.2 MB|
+
+## References
+
+https://huggingface.co/glrh11/vit-base-patch16-224
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-vit_base_patch16_224_glrh11_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-vit_base_patch16_224_glrh11_pipeline_en.md
new file mode 100644
index 00000000000000..f40d3eccead508
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-vit_base_patch16_224_glrh11_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_base_patch16_224_glrh11_pipeline pipeline ViTForImageClassification from glrh11
+author: John Snow Labs
+name: vit_base_patch16_224_glrh11_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_patch16_224_glrh11_pipeline` is a English model originally trained by glrh11.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_glrh11_pipeline_en_5.5.1_3.0_1737925941989.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_glrh11_pipeline_en_5.5.1_3.0_1737925941989.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_base_patch16_224_glrh11_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_base_patch16_224_glrh11_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_patch16_224_glrh11_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|324.2 MB|
+
+## References
+
+https://huggingface.co/glrh11/vit-base-patch16-224
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-vit_base_patch16_384_en.md b/docs/_posts/ahmedlone127/2025-01-26-vit_base_patch16_384_en.md
new file mode 100644
index 00000000000000..7ee31cd15478af
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-vit_base_patch16_384_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_base_patch16_384 ViTForImageClassification from google
+author: John Snow Labs
+name: vit_base_patch16_384
+date: 2025-01-26
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_patch16_384` is a English model originally trained by google.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_patch16_384_en_5.5.1_3.0_1737926233936.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_patch16_384_en_5.5.1_3.0_1737926233936.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vit_base_patch16_384","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vit_base_patch16_384","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_patch16_384|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|325.3 MB|
+
+## References
+
+https://huggingface.co/google/vit-base-patch16-384
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-vit_base_patch16_384_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-vit_base_patch16_384_pipeline_en.md
new file mode 100644
index 00000000000000..ec102c350681fb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-vit_base_patch16_384_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_base_patch16_384_pipeline pipeline ViTForImageClassification from google
+author: John Snow Labs
+name: vit_base_patch16_384_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_patch16_384_pipeline` is a English model originally trained by google.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_patch16_384_pipeline_en_5.5.1_3.0_1737926252600.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_patch16_384_pipeline_en_5.5.1_3.0_1737926252600.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_base_patch16_384_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_base_patch16_384_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_patch16_384_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|325.3 MB|
+
+## References
+
+https://huggingface.co/google/vit-base-patch16-384
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-vit_finetuned_chest_xray_pneumonia_en.md b/docs/_posts/ahmedlone127/2025-01-26-vit_finetuned_chest_xray_pneumonia_en.md
new file mode 100644
index 00000000000000..d19261bb476a9d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-vit_finetuned_chest_xray_pneumonia_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_finetuned_chest_xray_pneumonia ViTForImageClassification from nickmuchi
+author: John Snow Labs
+name: vit_finetuned_chest_xray_pneumonia
+date: 2025-01-26
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_finetuned_chest_xray_pneumonia` is a English model originally trained by nickmuchi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_finetuned_chest_xray_pneumonia_en_5.5.1_3.0_1737926205932.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_finetuned_chest_xray_pneumonia_en_5.5.1_3.0_1737926205932.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vit_finetuned_chest_xray_pneumonia","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vit_finetuned_chest_xray_pneumonia","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_finetuned_chest_xray_pneumonia|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/nickmuchi/vit-finetuned-chest-xray-pneumonia
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-vit_finetuned_chest_xray_pneumonia_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-vit_finetuned_chest_xray_pneumonia_pipeline_en.md
new file mode 100644
index 00000000000000..89aeaf79976b6b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-vit_finetuned_chest_xray_pneumonia_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_finetuned_chest_xray_pneumonia_pipeline pipeline ViTForImageClassification from nickmuchi
+author: John Snow Labs
+name: vit_finetuned_chest_xray_pneumonia_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_finetuned_chest_xray_pneumonia_pipeline` is a English model originally trained by nickmuchi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_finetuned_chest_xray_pneumonia_pipeline_en_5.5.1_3.0_1737926224296.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_finetuned_chest_xray_pneumonia_pipeline_en_5.5.1_3.0_1737926224296.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_finetuned_chest_xray_pneumonia_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_finetuned_chest_xray_pneumonia_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_finetuned_chest_xray_pneumonia_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/nickmuchi/vit-finetuned-chest-xray-pneumonia
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-viz_wiz_bert_base_uncased_f32_en.md b/docs/_posts/ahmedlone127/2025-01-26-viz_wiz_bert_base_uncased_f32_en.md
new file mode 100644
index 00000000000000..d9c2d1b9cdb3c2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-viz_wiz_bert_base_uncased_f32_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English viz_wiz_bert_base_uncased_f32 BertEmbeddings from eisenjulian
+author: John Snow Labs
+name: viz_wiz_bert_base_uncased_f32
+date: 2025-01-26
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`viz_wiz_bert_base_uncased_f32` is a English model originally trained by eisenjulian.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/viz_wiz_bert_base_uncased_f32_en_5.5.1_3.0_1737908361156.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/viz_wiz_bert_base_uncased_f32_en_5.5.1_3.0_1737908361156.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("viz_wiz_bert_base_uncased_f32","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("viz_wiz_bert_base_uncased_f32","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|viz_wiz_bert_base_uncased_f32|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/eisenjulian/viz-wiz-bert-base-uncased_f32
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-viz_wiz_bert_base_uncased_f32_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-viz_wiz_bert_base_uncased_f32_pipeline_en.md
new file mode 100644
index 00000000000000..a34a099194c423
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-viz_wiz_bert_base_uncased_f32_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English viz_wiz_bert_base_uncased_f32_pipeline pipeline BertEmbeddings from eisenjulian
+author: John Snow Labs
+name: viz_wiz_bert_base_uncased_f32_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`viz_wiz_bert_base_uncased_f32_pipeline` is a English model originally trained by eisenjulian.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/viz_wiz_bert_base_uncased_f32_pipeline_en_5.5.1_3.0_1737908382855.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/viz_wiz_bert_base_uncased_f32_pipeline_en_5.5.1_3.0_1737908382855.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("viz_wiz_bert_base_uncased_f32_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("viz_wiz_bert_base_uncased_f32_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|viz_wiz_bert_base_uncased_f32_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/eisenjulian/viz-wiz-bert-base-uncased_f32
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-vlsp_en.md b/docs/_posts/ahmedlone127/2025-01-26-vlsp_en.md
new file mode 100644
index 00000000000000..b19df0c9a190e5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-vlsp_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vlsp XlmRoBertaForSequenceClassification from mecoaoge2
+author: John Snow Labs
+name: vlsp
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vlsp` is a English model originally trained by mecoaoge2.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vlsp_en_5.5.1_3.0_1737882239719.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vlsp_en_5.5.1_3.0_1737882239719.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("vlsp","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("vlsp", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vlsp|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|365.9 MB|
+
+## References
+
+https://huggingface.co/mecoaoge2/VLSP
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-vlsp_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-vlsp_pipeline_en.md
new file mode 100644
index 00000000000000..2da29d6267b6f6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-vlsp_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English vlsp_pipeline pipeline XlmRoBertaForSequenceClassification from mecoaoge2
+author: John Snow Labs
+name: vlsp_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vlsp_pipeline` is a English model originally trained by mecoaoge2.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vlsp_pipeline_en_5.5.1_3.0_1737882258819.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vlsp_pipeline_en_5.5.1_3.0_1737882258819.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vlsp_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vlsp_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vlsp_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|365.9 MB|
+
+## References
+
+https://huggingface.co/mecoaoge2/VLSP
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-vsmec1_en.md b/docs/_posts/ahmedlone127/2025-01-26-vsmec1_en.md
new file mode 100644
index 00000000000000..bcabdc62348e4c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-vsmec1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vsmec1 XlmRoBertaForSequenceClassification from mecoaoge2
+author: John Snow Labs
+name: vsmec1
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vsmec1` is a English model originally trained by mecoaoge2.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vsmec1_en_5.5.1_3.0_1737885584067.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vsmec1_en_5.5.1_3.0_1737885584067.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("vsmec1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("vsmec1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vsmec1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|365.9 MB|
+
+## References
+
+https://huggingface.co/mecoaoge2/VSMEC1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-vsmec1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-vsmec1_pipeline_en.md
new file mode 100644
index 00000000000000..d5f845f1e290ee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-vsmec1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English vsmec1_pipeline pipeline XlmRoBertaForSequenceClassification from mecoaoge2
+author: John Snow Labs
+name: vsmec1_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vsmec1_pipeline` is a English model originally trained by mecoaoge2.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vsmec1_pipeline_en_5.5.1_3.0_1737885602864.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vsmec1_pipeline_en_5.5.1_3.0_1737885602864.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vsmec1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vsmec1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vsmec1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|365.9 MB|
+
+## References
+
+https://huggingface.co/mecoaoge2/VSMEC1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-vsmec_en.md b/docs/_posts/ahmedlone127/2025-01-26-vsmec_en.md
new file mode 100644
index 00000000000000..a73aa5af1bb0d1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-vsmec_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vsmec XlmRoBertaForSequenceClassification from mecoaoge2
+author: John Snow Labs
+name: vsmec
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vsmec` is a English model originally trained by mecoaoge2.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vsmec_en_5.5.1_3.0_1737885078260.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vsmec_en_5.5.1_3.0_1737885078260.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("vsmec","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("vsmec", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vsmec|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|365.9 MB|
+
+## References
+
+https://huggingface.co/mecoaoge2/VSMEC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-vsmec_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-vsmec_pipeline_en.md
new file mode 100644
index 00000000000000..c4941e18f2fa23
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-vsmec_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English vsmec_pipeline pipeline XlmRoBertaForSequenceClassification from mecoaoge2
+author: John Snow Labs
+name: vsmec_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vsmec_pipeline` is a English model originally trained by mecoaoge2.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vsmec_pipeline_en_5.5.1_3.0_1737885096924.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vsmec_pipeline_en_5.5.1_3.0_1737885096924.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vsmec_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vsmec_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vsmec_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|365.9 MB|
+
+## References
+
+https://huggingface.co/mecoaoge2/VSMEC
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_r_base_finetuned_after_mrp_v2_denim_sound_4_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_r_base_finetuned_after_mrp_v2_denim_sound_4_en.md
new file mode 100644
index 00000000000000..a3ac0769f2bded
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_r_base_finetuned_after_mrp_v2_denim_sound_4_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_r_base_finetuned_after_mrp_v2_denim_sound_4 XlmRoBertaForSequenceClassification from haturusinghe
+author: John Snow Labs
+name: xlm_r_base_finetuned_after_mrp_v2_denim_sound_4
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_r_base_finetuned_after_mrp_v2_denim_sound_4` is a English model originally trained by haturusinghe.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_r_base_finetuned_after_mrp_v2_denim_sound_4_en_5.5.1_3.0_1737879057763.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_r_base_finetuned_after_mrp_v2_denim_sound_4_en_5.5.1_3.0_1737879057763.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_r_base_finetuned_after_mrp_v2_denim_sound_4","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_r_base_finetuned_after_mrp_v2_denim_sound_4", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_r_base_finetuned_after_mrp_v2_denim_sound_4|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|783.1 MB|
+
+## References
+
+https://huggingface.co/haturusinghe/xlm_r_base-finetuned_after_mrp-v2-denim-sound-4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_r_base_finetuned_after_mrp_v2_denim_sound_4_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_r_base_finetuned_after_mrp_v2_denim_sound_4_pipeline_en.md
new file mode 100644
index 00000000000000..884e3c8f22bcfa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_r_base_finetuned_after_mrp_v2_denim_sound_4_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_r_base_finetuned_after_mrp_v2_denim_sound_4_pipeline pipeline XlmRoBertaForSequenceClassification from haturusinghe
+author: John Snow Labs
+name: xlm_r_base_finetuned_after_mrp_v2_denim_sound_4_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_r_base_finetuned_after_mrp_v2_denim_sound_4_pipeline` is a English model originally trained by haturusinghe.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_r_base_finetuned_after_mrp_v2_denim_sound_4_pipeline_en_5.5.1_3.0_1737879199660.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_r_base_finetuned_after_mrp_v2_denim_sound_4_pipeline_en_5.5.1_3.0_1737879199660.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_r_base_finetuned_after_mrp_v2_denim_sound_4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_r_base_finetuned_after_mrp_v2_denim_sound_4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_r_base_finetuned_after_mrp_v2_denim_sound_4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|783.1 MB|
+
+## References
+
+https://huggingface.co/haturusinghe/xlm_r_base-finetuned_after_mrp-v2-denim-sound-4
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_r_base_finetuned_after_mrp_v2_different_deluge_11_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_r_base_finetuned_after_mrp_v2_different_deluge_11_en.md
new file mode 100644
index 00000000000000..57fb6d741b2274
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_r_base_finetuned_after_mrp_v2_different_deluge_11_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_r_base_finetuned_after_mrp_v2_different_deluge_11 XlmRoBertaForSequenceClassification from haturusinghe
+author: John Snow Labs
+name: xlm_r_base_finetuned_after_mrp_v2_different_deluge_11
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_r_base_finetuned_after_mrp_v2_different_deluge_11` is a English model originally trained by haturusinghe.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_r_base_finetuned_after_mrp_v2_different_deluge_11_en_5.5.1_3.0_1737886564942.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_r_base_finetuned_after_mrp_v2_different_deluge_11_en_5.5.1_3.0_1737886564942.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_r_base_finetuned_after_mrp_v2_different_deluge_11","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_r_base_finetuned_after_mrp_v2_different_deluge_11", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_r_base_finetuned_after_mrp_v2_different_deluge_11|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|782.7 MB|
+
+## References
+
+https://huggingface.co/haturusinghe/xlm_r_base-finetuned_after_mrp-v2-different-deluge-11
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_r_base_finetuned_after_mrp_v2_different_deluge_11_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_r_base_finetuned_after_mrp_v2_different_deluge_11_pipeline_en.md
new file mode 100644
index 00000000000000..c4855f5ff2ff15
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_r_base_finetuned_after_mrp_v2_different_deluge_11_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_r_base_finetuned_after_mrp_v2_different_deluge_11_pipeline pipeline XlmRoBertaForSequenceClassification from haturusinghe
+author: John Snow Labs
+name: xlm_r_base_finetuned_after_mrp_v2_different_deluge_11_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_r_base_finetuned_after_mrp_v2_different_deluge_11_pipeline` is a English model originally trained by haturusinghe.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_r_base_finetuned_after_mrp_v2_different_deluge_11_pipeline_en_5.5.1_3.0_1737886702727.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_r_base_finetuned_after_mrp_v2_different_deluge_11_pipeline_en_5.5.1_3.0_1737886702727.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_r_base_finetuned_after_mrp_v2_different_deluge_11_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_r_base_finetuned_after_mrp_v2_different_deluge_11_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_r_base_finetuned_after_mrp_v2_different_deluge_11_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|782.7 MB|
+
+## References
+
+https://huggingface.co/haturusinghe/xlm_r_base-finetuned_after_mrp-v2-different-deluge-11
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_r_base_finetuned_after_mrp_v2_lucky_cloud_13_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_r_base_finetuned_after_mrp_v2_lucky_cloud_13_en.md
new file mode 100644
index 00000000000000..0be26753811094
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_r_base_finetuned_after_mrp_v2_lucky_cloud_13_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_r_base_finetuned_after_mrp_v2_lucky_cloud_13 XlmRoBertaForSequenceClassification from haturusinghe
+author: John Snow Labs
+name: xlm_r_base_finetuned_after_mrp_v2_lucky_cloud_13
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_r_base_finetuned_after_mrp_v2_lucky_cloud_13` is a English model originally trained by haturusinghe.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_r_base_finetuned_after_mrp_v2_lucky_cloud_13_en_5.5.1_3.0_1737886362245.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_r_base_finetuned_after_mrp_v2_lucky_cloud_13_en_5.5.1_3.0_1737886362245.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_r_base_finetuned_after_mrp_v2_lucky_cloud_13","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_r_base_finetuned_after_mrp_v2_lucky_cloud_13", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_r_base_finetuned_after_mrp_v2_lucky_cloud_13|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|782.7 MB|
+
+## References
+
+https://huggingface.co/haturusinghe/xlm_r_base-finetuned_after_mrp-v2-lucky-cloud-13
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_r_base_finetuned_after_mrp_v2_lucky_cloud_13_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_r_base_finetuned_after_mrp_v2_lucky_cloud_13_pipeline_en.md
new file mode 100644
index 00000000000000..1a104a7a6345a3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_r_base_finetuned_after_mrp_v2_lucky_cloud_13_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_r_base_finetuned_after_mrp_v2_lucky_cloud_13_pipeline pipeline XlmRoBertaForSequenceClassification from haturusinghe
+author: John Snow Labs
+name: xlm_r_base_finetuned_after_mrp_v2_lucky_cloud_13_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_r_base_finetuned_after_mrp_v2_lucky_cloud_13_pipeline` is a English model originally trained by haturusinghe.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_r_base_finetuned_after_mrp_v2_lucky_cloud_13_pipeline_en_5.5.1_3.0_1737886501683.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_r_base_finetuned_after_mrp_v2_lucky_cloud_13_pipeline_en_5.5.1_3.0_1737886501683.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_r_base_finetuned_after_mrp_v2_lucky_cloud_13_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_r_base_finetuned_after_mrp_v2_lucky_cloud_13_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_r_base_finetuned_after_mrp_v2_lucky_cloud_13_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|782.7 MB|
+
+## References
+
+https://huggingface.co/haturusinghe/xlm_r_base-finetuned_after_mrp-v2-lucky-cloud-13
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_r_base_finetuned_after_mrp_v2_ruby_galaxy_10_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_r_base_finetuned_after_mrp_v2_ruby_galaxy_10_en.md
new file mode 100644
index 00000000000000..0d0812855d9267
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_r_base_finetuned_after_mrp_v2_ruby_galaxy_10_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_r_base_finetuned_after_mrp_v2_ruby_galaxy_10 XlmRoBertaForSequenceClassification from haturusinghe
+author: John Snow Labs
+name: xlm_r_base_finetuned_after_mrp_v2_ruby_galaxy_10
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_r_base_finetuned_after_mrp_v2_ruby_galaxy_10` is a English model originally trained by haturusinghe.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_r_base_finetuned_after_mrp_v2_ruby_galaxy_10_en_5.5.1_3.0_1737881044491.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_r_base_finetuned_after_mrp_v2_ruby_galaxy_10_en_5.5.1_3.0_1737881044491.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_r_base_finetuned_after_mrp_v2_ruby_galaxy_10","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_r_base_finetuned_after_mrp_v2_ruby_galaxy_10", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_r_base_finetuned_after_mrp_v2_ruby_galaxy_10|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|782.7 MB|
+
+## References
+
+https://huggingface.co/haturusinghe/xlm_r_base-finetuned_after_mrp-v2-ruby-galaxy-10
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_r_base_finetuned_after_mrp_v2_ruby_galaxy_10_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_r_base_finetuned_after_mrp_v2_ruby_galaxy_10_pipeline_en.md
new file mode 100644
index 00000000000000..d7e6c5153a48e2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_r_base_finetuned_after_mrp_v2_ruby_galaxy_10_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_r_base_finetuned_after_mrp_v2_ruby_galaxy_10_pipeline pipeline XlmRoBertaForSequenceClassification from haturusinghe
+author: John Snow Labs
+name: xlm_r_base_finetuned_after_mrp_v2_ruby_galaxy_10_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_r_base_finetuned_after_mrp_v2_ruby_galaxy_10_pipeline` is a English model originally trained by haturusinghe.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_r_base_finetuned_after_mrp_v2_ruby_galaxy_10_pipeline_en_5.5.1_3.0_1737881188317.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_r_base_finetuned_after_mrp_v2_ruby_galaxy_10_pipeline_en_5.5.1_3.0_1737881188317.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_r_base_finetuned_after_mrp_v2_ruby_galaxy_10_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_r_base_finetuned_after_mrp_v2_ruby_galaxy_10_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_r_base_finetuned_after_mrp_v2_ruby_galaxy_10_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|782.7 MB|
+
+## References
+
+https://huggingface.co/haturusinghe/xlm_r_base-finetuned_after_mrp-v2-ruby-galaxy-10
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_afr_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_afr_en.md
new file mode 100644
index 00000000000000..3517e5747148a7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_afr_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_afr XlmRoBertaForSequenceClassification from FrinzTheCoder
+author: John Snow Labs
+name: xlm_roberta_base_afr
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_afr` is a English model originally trained by FrinzTheCoder.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_afr_en_5.5.1_3.0_1737878392762.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_afr_en_5.5.1_3.0_1737878392762.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_afr","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_afr", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_afr|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|775.6 MB|
+
+## References
+
+https://huggingface.co/FrinzTheCoder/xlm-roberta-base-afr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_afr_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_afr_pipeline_en.md
new file mode 100644
index 00000000000000..7426e86e2d8011
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_afr_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_afr_pipeline pipeline XlmRoBertaForSequenceClassification from FrinzTheCoder
+author: John Snow Labs
+name: xlm_roberta_base_afr_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_afr_pipeline` is a English model originally trained by FrinzTheCoder.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_afr_pipeline_en_5.5.1_3.0_1737878537567.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_afr_pipeline_en_5.5.1_3.0_1737878537567.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_afr_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_afr_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_afr_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|775.6 MB|
+
+## References
+
+https://huggingface.co/FrinzTheCoder/xlm-roberta-base-afr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_autext2024_04_12_2024_detection_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_autext2024_04_12_2024_detection_en.md
new file mode 100644
index 00000000000000..6017f6ec975632
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_autext2024_04_12_2024_detection_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_autext2024_04_12_2024_detection XlmRoBertaForSequenceClassification from ISEGURA
+author: John Snow Labs
+name: xlm_roberta_base_autext2024_04_12_2024_detection
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_autext2024_04_12_2024_detection` is a English model originally trained by ISEGURA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_autext2024_04_12_2024_detection_en_5.5.1_3.0_1737880060702.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_autext2024_04_12_2024_detection_en_5.5.1_3.0_1737880060702.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_autext2024_04_12_2024_detection","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_autext2024_04_12_2024_detection", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_autext2024_04_12_2024_detection|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|817.7 MB|
+
+## References
+
+https://huggingface.co/ISEGURA/xlm-roberta-base-autext2024_04-12-2024_detection
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_autext2024_04_12_2024_detection_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_autext2024_04_12_2024_detection_pipeline_en.md
new file mode 100644
index 00000000000000..66172374e7008a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_autext2024_04_12_2024_detection_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_autext2024_04_12_2024_detection_pipeline pipeline XlmRoBertaForSequenceClassification from ISEGURA
+author: John Snow Labs
+name: xlm_roberta_base_autext2024_04_12_2024_detection_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_autext2024_04_12_2024_detection_pipeline` is a English model originally trained by ISEGURA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_autext2024_04_12_2024_detection_pipeline_en_5.5.1_3.0_1737880185251.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_autext2024_04_12_2024_detection_pipeline_en_5.5.1_3.0_1737880185251.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_autext2024_04_12_2024_detection_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_autext2024_04_12_2024_detection_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_autext2024_04_12_2024_detection_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|817.7 MB|
+
+## References
+
+https://huggingface.co/ISEGURA/xlm-roberta-base-autext2024_04-12-2024_detection
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_final_mixed_aug_insert_synonym_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_final_mixed_aug_insert_synonym_en.md
new file mode 100644
index 00000000000000..f3d204fd4ed194
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_final_mixed_aug_insert_synonym_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_final_mixed_aug_insert_synonym XlmRoBertaForSequenceClassification from ThuyNT03
+author: John Snow Labs
+name: xlm_roberta_base_final_mixed_aug_insert_synonym
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_final_mixed_aug_insert_synonym` is a English model originally trained by ThuyNT03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_final_mixed_aug_insert_synonym_en_5.5.1_3.0_1737879183182.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_final_mixed_aug_insert_synonym_en_5.5.1_3.0_1737879183182.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_final_mixed_aug_insert_synonym","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_final_mixed_aug_insert_synonym", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_final_mixed_aug_insert_synonym|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|795.2 MB|
+
+## References
+
+https://huggingface.co/ThuyNT03/xlm-roberta-base-Final_Mixed-aug_insert_synonym
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_final_mixed_aug_insert_synonym_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_final_mixed_aug_insert_synonym_pipeline_en.md
new file mode 100644
index 00000000000000..a726d691bf037d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_final_mixed_aug_insert_synonym_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_final_mixed_aug_insert_synonym_pipeline pipeline XlmRoBertaForSequenceClassification from ThuyNT03
+author: John Snow Labs
+name: xlm_roberta_base_final_mixed_aug_insert_synonym_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_final_mixed_aug_insert_synonym_pipeline` is a English model originally trained by ThuyNT03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_final_mixed_aug_insert_synonym_pipeline_en_5.5.1_3.0_1737879311696.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_final_mixed_aug_insert_synonym_pipeline_en_5.5.1_3.0_1737879311696.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_final_mixed_aug_insert_synonym_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_final_mixed_aug_insert_synonym_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_final_mixed_aug_insert_synonym_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|795.3 MB|
+
+## References
+
+https://huggingface.co/ThuyNT03/xlm-roberta-base-Final_Mixed-aug_insert_synonym
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_final_mixed_aug_replace_tfidf_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_final_mixed_aug_replace_tfidf_en.md
new file mode 100644
index 00000000000000..2efb03169a8bd7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_final_mixed_aug_replace_tfidf_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_final_mixed_aug_replace_tfidf XlmRoBertaForSequenceClassification from ThuyNT03
+author: John Snow Labs
+name: xlm_roberta_base_final_mixed_aug_replace_tfidf
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_final_mixed_aug_replace_tfidf` is a English model originally trained by ThuyNT03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_final_mixed_aug_replace_tfidf_en_5.5.1_3.0_1737882293372.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_final_mixed_aug_replace_tfidf_en_5.5.1_3.0_1737882293372.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_final_mixed_aug_replace_tfidf","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_final_mixed_aug_replace_tfidf", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_final_mixed_aug_replace_tfidf|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|794.9 MB|
+
+## References
+
+https://huggingface.co/ThuyNT03/xlm-roberta-base-Final_Mixed-aug_replace_tfidf
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_final_mixed_aug_replace_tfidf_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_final_mixed_aug_replace_tfidf_pipeline_en.md
new file mode 100644
index 00000000000000..96e4f2660192d6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_final_mixed_aug_replace_tfidf_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_final_mixed_aug_replace_tfidf_pipeline pipeline XlmRoBertaForSequenceClassification from ThuyNT03
+author: John Snow Labs
+name: xlm_roberta_base_final_mixed_aug_replace_tfidf_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_final_mixed_aug_replace_tfidf_pipeline` is a English model originally trained by ThuyNT03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_final_mixed_aug_replace_tfidf_pipeline_en_5.5.1_3.0_1737882417323.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_final_mixed_aug_replace_tfidf_pipeline_en_5.5.1_3.0_1737882417323.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_final_mixed_aug_replace_tfidf_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_final_mixed_aug_replace_tfidf_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_final_mixed_aug_replace_tfidf_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|794.9 MB|
+
+## References
+
+https://huggingface.co/ThuyNT03/xlm-roberta-base-Final_Mixed-aug_replace_tfidf
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_final_vietnam_aug_insert_tfidf_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_final_vietnam_aug_insert_tfidf_en.md
new file mode 100644
index 00000000000000..a2932445d699b9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_final_vietnam_aug_insert_tfidf_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_final_vietnam_aug_insert_tfidf XlmRoBertaForSequenceClassification from ThuyNT03
+author: John Snow Labs
+name: xlm_roberta_base_final_vietnam_aug_insert_tfidf
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_final_vietnam_aug_insert_tfidf` is a English model originally trained by ThuyNT03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_final_vietnam_aug_insert_tfidf_en_5.5.1_3.0_1737884709655.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_final_vietnam_aug_insert_tfidf_en_5.5.1_3.0_1737884709655.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_final_vietnam_aug_insert_tfidf","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_final_vietnam_aug_insert_tfidf", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_final_vietnam_aug_insert_tfidf|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|793.7 MB|
+
+## References
+
+https://huggingface.co/ThuyNT03/xlm-roberta-base-Final_VietNam-aug_insert_tfidf
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_final_vietnam_aug_insert_tfidf_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_final_vietnam_aug_insert_tfidf_pipeline_en.md
new file mode 100644
index 00000000000000..4839886a9dd3a8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_final_vietnam_aug_insert_tfidf_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_final_vietnam_aug_insert_tfidf_pipeline pipeline XlmRoBertaForSequenceClassification from ThuyNT03
+author: John Snow Labs
+name: xlm_roberta_base_final_vietnam_aug_insert_tfidf_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_final_vietnam_aug_insert_tfidf_pipeline` is a English model originally trained by ThuyNT03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_final_vietnam_aug_insert_tfidf_pipeline_en_5.5.1_3.0_1737884840959.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_final_vietnam_aug_insert_tfidf_pipeline_en_5.5.1_3.0_1737884840959.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_final_vietnam_aug_insert_tfidf_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_final_vietnam_aug_insert_tfidf_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_final_vietnam_aug_insert_tfidf_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|793.7 MB|
+
+## References
+
+https://huggingface.co/ThuyNT03/xlm-roberta-base-Final_VietNam-aug_insert_tfidf
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_iberautextification2024_5fcv_2epo_task2_v1_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_iberautextification2024_5fcv_2epo_task2_v1_en.md
new file mode 100644
index 00000000000000..2e9b7d90fdef44
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_iberautextification2024_5fcv_2epo_task2_v1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_iberautextification2024_5fcv_2epo_task2_v1 XlmRoBertaForSequenceClassification from vg055
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_iberautextification2024_5fcv_2epo_task2_v1
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_iberautextification2024_5fcv_2epo_task2_v1` is a English model originally trained by vg055.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_iberautextification2024_5fcv_2epo_task2_v1_en_5.5.1_3.0_1737882053671.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_iberautextification2024_5fcv_2epo_task2_v1_en_5.5.1_3.0_1737882053671.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_finetuned_iberautextification2024_5fcv_2epo_task2_v1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_finetuned_iberautextification2024_5fcv_2epo_task2_v1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_iberautextification2024_5fcv_2epo_task2_v1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|888.0 MB|
+
+## References
+
+https://huggingface.co/vg055/xlm-roberta-base-finetuned-IberAuTexTification2024-5fCV-2epo-task2-v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_iberautextification2024_5fcv_2epo_task2_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_iberautextification2024_5fcv_2epo_task2_v1_pipeline_en.md
new file mode 100644
index 00000000000000..27ee08df365e36
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_iberautextification2024_5fcv_2epo_task2_v1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_iberautextification2024_5fcv_2epo_task2_v1_pipeline pipeline XlmRoBertaForSequenceClassification from vg055
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_iberautextification2024_5fcv_2epo_task2_v1_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_iberautextification2024_5fcv_2epo_task2_v1_pipeline` is a English model originally trained by vg055.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_iberautextification2024_5fcv_2epo_task2_v1_pipeline_en_5.5.1_3.0_1737882115558.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_iberautextification2024_5fcv_2epo_task2_v1_pipeline_en_5.5.1_3.0_1737882115558.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_iberautextification2024_5fcv_2epo_task2_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_iberautextification2024_5fcv_2epo_task2_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_iberautextification2024_5fcv_2epo_task2_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|888.0 MB|
+
+## References
+
+https://huggingface.co/vg055/xlm-roberta-base-finetuned-IberAuTexTification2024-5fCV-2epo-task2-v1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_iberautextification2024_7030_task1_v2_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_iberautextification2024_7030_task1_v2_en.md
new file mode 100644
index 00000000000000..5f219423787aa7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_iberautextification2024_7030_task1_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_iberautextification2024_7030_task1_v2 XlmRoBertaForSequenceClassification from vg055
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_iberautextification2024_7030_task1_v2
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_iberautextification2024_7030_task1_v2` is a English model originally trained by vg055.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_iberautextification2024_7030_task1_v2_en_5.5.1_3.0_1737879665152.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_iberautextification2024_7030_task1_v2_en_5.5.1_3.0_1737879665152.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_finetuned_iberautextification2024_7030_task1_v2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_finetuned_iberautextification2024_7030_task1_v2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_iberautextification2024_7030_task1_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|894.5 MB|
+
+## References
+
+https://huggingface.co/vg055/xlm-roberta-base-finetuned-IberAuTexTification2024-7030-task1-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_iberautextification2024_7030_task1_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_iberautextification2024_7030_task1_v2_pipeline_en.md
new file mode 100644
index 00000000000000..6bcc0dc0afd2af
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_iberautextification2024_7030_task1_v2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_iberautextification2024_7030_task1_v2_pipeline pipeline XlmRoBertaForSequenceClassification from vg055
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_iberautextification2024_7030_task1_v2_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_iberautextification2024_7030_task1_v2_pipeline` is a English model originally trained by vg055.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_iberautextification2024_7030_task1_v2_pipeline_en_5.5.1_3.0_1737879730327.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_iberautextification2024_7030_task1_v2_pipeline_en_5.5.1_3.0_1737879730327.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_iberautextification2024_7030_task1_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_iberautextification2024_7030_task1_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_iberautextification2024_7030_task1_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|894.5 MB|
+
+## References
+
+https://huggingface.co/vg055/xlm-roberta-base-finetuned-IberAuTexTification2024-7030-task1-v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_marc_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_marc_en.md
new file mode 100644
index 00000000000000..8521fe1a5e4a52
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_marc_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_marc XlmRoBertaForSequenceClassification from PGCaptain
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_marc
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_marc` is a English model originally trained by PGCaptain.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_marc_en_5.5.1_3.0_1737885904525.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_marc_en_5.5.1_3.0_1737885904525.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_finetuned_marc","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_finetuned_marc", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_marc|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|829.8 MB|
+
+## References
+
+https://huggingface.co/PGCaptain/xlm-roberta-base-finetuned-marc
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_marc_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_marc_pipeline_en.md
new file mode 100644
index 00000000000000..0f666fff4b67dc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_marc_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_marc_pipeline pipeline XlmRoBertaForSequenceClassification from PGCaptain
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_marc_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_marc_pipeline` is a English model originally trained by PGCaptain.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_marc_pipeline_en_5.5.1_3.0_1737885999506.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_marc_pipeline_en_5.5.1_3.0_1737885999506.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_marc_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_marc_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_marc_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|829.8 MB|
+
+## References
+
+https://huggingface.co/PGCaptain/xlm-roberta-base-finetuned-marc
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_all_haoj1_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_all_haoj1_en.md
new file mode 100644
index 00000000000000..33cdeca1026d3e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_all_haoj1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_haoj1 XlmRoBertaForTokenClassification from haoj1
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_haoj1
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_haoj1` is a English model originally trained by haoj1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_haoj1_en_5.5.1_3.0_1737854854771.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_haoj1_en_5.5.1_3.0_1737854854771.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_haoj1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_haoj1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_haoj1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/haoj1/xlm-roberta-base-finetuned-panx-all
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_all_haoj1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_all_haoj1_pipeline_en.md
new file mode 100644
index 00000000000000..2a6860c55009d3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_all_haoj1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_haoj1_pipeline pipeline XlmRoBertaForTokenClassification from haoj1
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_haoj1_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_haoj1_pipeline` is a English model originally trained by haoj1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_haoj1_pipeline_en_5.5.1_3.0_1737854938156.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_haoj1_pipeline_en_5.5.1_3.0_1737854938156.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_haoj1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_haoj1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_haoj1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/haoj1/xlm-roberta-base-finetuned-panx-all
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_all_imaditya123_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_all_imaditya123_en.md
new file mode 100644
index 00000000000000..4546c1b7d8403e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_all_imaditya123_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_imaditya123 XlmRoBertaForTokenClassification from imaditya123
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_imaditya123
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_imaditya123` is a English model originally trained by imaditya123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_imaditya123_en_5.5.1_3.0_1737854843303.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_imaditya123_en_5.5.1_3.0_1737854843303.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_imaditya123","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_imaditya123", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_imaditya123|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/imaditya123/xlm-roberta-base-finetuned-panx-all
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_all_imaditya123_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_all_imaditya123_pipeline_en.md
new file mode 100644
index 00000000000000..75ae59134ff4fe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_all_imaditya123_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_imaditya123_pipeline pipeline XlmRoBertaForTokenClassification from imaditya123
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_imaditya123_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_imaditya123_pipeline` is a English model originally trained by imaditya123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_imaditya123_pipeline_en_5.5.1_3.0_1737854926823.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_imaditya123_pipeline_en_5.5.1_3.0_1737854926823.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_imaditya123_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_imaditya123_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_imaditya123_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/imaditya123/xlm-roberta-base-finetuned-panx-all
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_all_leesihyun_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_all_leesihyun_en.md
new file mode 100644
index 00000000000000..d299a9350f7b9f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_all_leesihyun_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_leesihyun XlmRoBertaForTokenClassification from LEESIHYUN
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_leesihyun
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_leesihyun` is a English model originally trained by LEESIHYUN.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_leesihyun_en_5.5.1_3.0_1737899318347.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_leesihyun_en_5.5.1_3.0_1737899318347.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_leesihyun","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_leesihyun", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_leesihyun|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/LEESIHYUN/xlm-roberta-base-finetuned-panx-all
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_all_leesihyun_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_all_leesihyun_pipeline_en.md
new file mode 100644
index 00000000000000..4b39fc83a6deec
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_all_leesihyun_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_leesihyun_pipeline pipeline XlmRoBertaForTokenClassification from LEESIHYUN
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_leesihyun_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_leesihyun_pipeline` is a English model originally trained by LEESIHYUN.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_leesihyun_pipeline_en_5.5.1_3.0_1737899401845.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_leesihyun_pipeline_en_5.5.1_3.0_1737899401845.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_leesihyun_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_leesihyun_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_leesihyun_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/LEESIHYUN/xlm-roberta-base-finetuned-panx-all
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_all_mohamedalaa00_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_all_mohamedalaa00_en.md
new file mode 100644
index 00000000000000..1cb3cab2aafffa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_all_mohamedalaa00_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_mohamedalaa00 XlmRoBertaForTokenClassification from MohamedAlaa00
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_mohamedalaa00
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_mohamedalaa00` is a English model originally trained by MohamedAlaa00.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_mohamedalaa00_en_5.5.1_3.0_1737854422950.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_mohamedalaa00_en_5.5.1_3.0_1737854422950.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_mohamedalaa00","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_mohamedalaa00", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_mohamedalaa00|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|863.7 MB|
+
+## References
+
+https://huggingface.co/MohamedAlaa00/xlm-roberta-base-finetuned-panx-all
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_all_mohamedalaa00_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_all_mohamedalaa00_pipeline_en.md
new file mode 100644
index 00000000000000..0e4cb24b00c0e5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_all_mohamedalaa00_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_mohamedalaa00_pipeline pipeline XlmRoBertaForTokenClassification from MohamedAlaa00
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_mohamedalaa00_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_mohamedalaa00_pipeline` is a English model originally trained by MohamedAlaa00.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_mohamedalaa00_pipeline_en_5.5.1_3.0_1737854501969.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_mohamedalaa00_pipeline_en_5.5.1_3.0_1737854501969.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_mohamedalaa00_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_mohamedalaa00_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_mohamedalaa00_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|863.7 MB|
+
+## References
+
+https://huggingface.co/MohamedAlaa00/xlm-roberta-base-finetuned-panx-all
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_all_usmanyaqoob_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_all_usmanyaqoob_en.md
new file mode 100644
index 00000000000000..a71c8a000ebf75
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_all_usmanyaqoob_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_usmanyaqoob XlmRoBertaForTokenClassification from usmanyaqoob
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_usmanyaqoob
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_usmanyaqoob` is a English model originally trained by usmanyaqoob.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_usmanyaqoob_en_5.5.1_3.0_1737898297122.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_usmanyaqoob_en_5.5.1_3.0_1737898297122.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_usmanyaqoob","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_usmanyaqoob", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_usmanyaqoob|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|847.9 MB|
+
+## References
+
+https://huggingface.co/usmanyaqoob/xlm-roberta-base-finetuned-panx-all
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_all_usmanyaqoob_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_all_usmanyaqoob_pipeline_en.md
new file mode 100644
index 00000000000000..db50b3b9852ce5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_all_usmanyaqoob_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_usmanyaqoob_pipeline pipeline XlmRoBertaForTokenClassification from usmanyaqoob
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_usmanyaqoob_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_usmanyaqoob_pipeline` is a English model originally trained by usmanyaqoob.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_usmanyaqoob_pipeline_en_5.5.1_3.0_1737898380136.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_usmanyaqoob_pipeline_en_5.5.1_3.0_1737898380136.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_usmanyaqoob_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_usmanyaqoob_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_usmanyaqoob_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/usmanyaqoob/xlm-roberta-base-finetuned-panx-all
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_english_ahid1_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_english_ahid1_en.md
new file mode 100644
index 00000000000000..3f5030267a176d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_english_ahid1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_ahid1 XlmRoBertaForTokenClassification from ahid1
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_ahid1
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_ahid1` is a English model originally trained by ahid1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_ahid1_en_5.5.1_3.0_1737899245341.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_ahid1_en_5.5.1_3.0_1737899245341.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_ahid1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_ahid1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_ahid1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/ahid1/xlm-roberta-base-finetuned-panx-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_english_ahid1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_english_ahid1_pipeline_en.md
new file mode 100644
index 00000000000000..40e4302e3e6344
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_english_ahid1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_ahid1_pipeline pipeline XlmRoBertaForTokenClassification from ahid1
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_ahid1_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_ahid1_pipeline` is a English model originally trained by ahid1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_ahid1_pipeline_en_5.5.1_3.0_1737899354184.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_ahid1_pipeline_en_5.5.1_3.0_1737899354184.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_ahid1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_ahid1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_ahid1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/ahid1/xlm-roberta-base-finetuned-panx-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_english_k4west_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_english_k4west_en.md
new file mode 100644
index 00000000000000..42275d90b06a14
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_english_k4west_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_k4west XlmRoBertaForTokenClassification from k4west
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_k4west
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_k4west` is a English model originally trained by k4west.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_k4west_en_5.5.1_3.0_1737854616190.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_k4west_en_5.5.1_3.0_1737854616190.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_k4west","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_k4west", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_k4west|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/k4west/xlm-roberta-base-finetuned-panx-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_english_k4west_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_english_k4west_pipeline_en.md
new file mode 100644
index 00000000000000..2955d87a16eabf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_english_k4west_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_k4west_pipeline pipeline XlmRoBertaForTokenClassification from k4west
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_k4west_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_k4west_pipeline` is a English model originally trained by k4west.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_k4west_pipeline_en_5.5.1_3.0_1737854723532.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_k4west_pipeline_en_5.5.1_3.0_1737854723532.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_k4west_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_k4west_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_k4west_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/k4west/xlm-roberta-base-finetuned-panx-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_english_rlawltjd_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_english_rlawltjd_en.md
new file mode 100644
index 00000000000000..9e4a113867b828
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_english_rlawltjd_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_rlawltjd XlmRoBertaForTokenClassification from rlawltjd
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_rlawltjd
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_rlawltjd` is a English model originally trained by rlawltjd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_rlawltjd_en_5.5.1_3.0_1737853796576.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_rlawltjd_en_5.5.1_3.0_1737853796576.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_rlawltjd","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_rlawltjd", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_rlawltjd|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/rlawltjd/xlm-roberta-base-finetuned-panx-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_english_rlawltjd_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_english_rlawltjd_pipeline_en.md
new file mode 100644
index 00000000000000..8c8dec79eeb962
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_english_rlawltjd_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_rlawltjd_pipeline pipeline XlmRoBertaForTokenClassification from rlawltjd
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_rlawltjd_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_rlawltjd_pipeline` is a English model originally trained by rlawltjd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_rlawltjd_pipeline_en_5.5.1_3.0_1737853906620.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_rlawltjd_pipeline_en_5.5.1_3.0_1737853906620.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_rlawltjd_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_rlawltjd_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_rlawltjd_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/rlawltjd/xlm-roberta-base-finetuned-panx-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_english_usmanyaqoob_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_english_usmanyaqoob_en.md
new file mode 100644
index 00000000000000..0877ee4b566f11
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_english_usmanyaqoob_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_usmanyaqoob XlmRoBertaForTokenClassification from usmanyaqoob
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_usmanyaqoob
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_usmanyaqoob` is a English model originally trained by usmanyaqoob.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_usmanyaqoob_en_5.5.1_3.0_1737897370184.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_usmanyaqoob_en_5.5.1_3.0_1737897370184.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_usmanyaqoob","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_usmanyaqoob", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_usmanyaqoob|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/usmanyaqoob/xlm-roberta-base-finetuned-panx-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_english_usmanyaqoob_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_english_usmanyaqoob_pipeline_en.md
new file mode 100644
index 00000000000000..54befee444d6ff
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_english_usmanyaqoob_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_usmanyaqoob_pipeline pipeline XlmRoBertaForTokenClassification from usmanyaqoob
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_usmanyaqoob_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_usmanyaqoob_pipeline` is a English model originally trained by usmanyaqoob.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_usmanyaqoob_pipeline_en_5.5.1_3.0_1737897477709.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_usmanyaqoob_pipeline_en_5.5.1_3.0_1737897477709.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_usmanyaqoob_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_usmanyaqoob_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_usmanyaqoob_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/usmanyaqoob/xlm-roberta-base-finetuned-panx-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_french_ahid1_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_french_ahid1_en.md
new file mode 100644
index 00000000000000..798b95e66c488f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_french_ahid1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_ahid1 XlmRoBertaForTokenClassification from ahid1
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_ahid1
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_ahid1` is a English model originally trained by ahid1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_ahid1_en_5.5.1_3.0_1737898443239.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_ahid1_en_5.5.1_3.0_1737898443239.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_ahid1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_ahid1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_ahid1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/ahid1/xlm-roberta-base-finetuned-panx-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_french_ahid1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_french_ahid1_pipeline_en.md
new file mode 100644
index 00000000000000..cfe71abb27de89
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_french_ahid1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_ahid1_pipeline pipeline XlmRoBertaForTokenClassification from ahid1
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_ahid1_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_ahid1_pipeline` is a English model originally trained by ahid1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_ahid1_pipeline_en_5.5.1_3.0_1737898535914.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_ahid1_pipeline_en_5.5.1_3.0_1737898535914.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_ahid1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_ahid1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_ahid1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/ahid1/xlm-roberta-base-finetuned-panx-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_french_july_tokyo_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_french_july_tokyo_en.md
new file mode 100644
index 00000000000000..71e71e8e0f8168
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_french_july_tokyo_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_july_tokyo XlmRoBertaForTokenClassification from July-Tokyo
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_july_tokyo
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_july_tokyo` is a English model originally trained by July-Tokyo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_july_tokyo_en_5.5.1_3.0_1737897414925.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_july_tokyo_en_5.5.1_3.0_1737897414925.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_july_tokyo","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_july_tokyo", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_july_tokyo|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/July-Tokyo/xlm-roberta-base-finetuned-panx-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_french_july_tokyo_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_french_july_tokyo_pipeline_en.md
new file mode 100644
index 00000000000000..8dece6c043a5c2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_french_july_tokyo_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_july_tokyo_pipeline pipeline XlmRoBertaForTokenClassification from July-Tokyo
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_july_tokyo_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_july_tokyo_pipeline` is a English model originally trained by July-Tokyo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_july_tokyo_pipeline_en_5.5.1_3.0_1737897517105.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_july_tokyo_pipeline_en_5.5.1_3.0_1737897517105.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_july_tokyo_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_july_tokyo_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_july_tokyo_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/July-Tokyo/xlm-roberta-base-finetuned-panx-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_french_msrisrujan_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_french_msrisrujan_en.md
new file mode 100644
index 00000000000000..02cc1ff3e58c47
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_french_msrisrujan_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_msrisrujan XlmRoBertaForTokenClassification from Msrisrujan
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_msrisrujan
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_msrisrujan` is a English model originally trained by Msrisrujan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_msrisrujan_en_5.5.1_3.0_1737899357767.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_msrisrujan_en_5.5.1_3.0_1737899357767.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_msrisrujan","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_msrisrujan", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_msrisrujan|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.9 MB|
+
+## References
+
+https://huggingface.co/Msrisrujan/xlm-roberta-base-finetuned-panx-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_french_msrisrujan_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_french_msrisrujan_pipeline_en.md
new file mode 100644
index 00000000000000..db90fdc6d0ede2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_french_msrisrujan_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_msrisrujan_pipeline pipeline XlmRoBertaForTokenClassification from Msrisrujan
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_msrisrujan_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_msrisrujan_pipeline` is a English model originally trained by Msrisrujan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_msrisrujan_pipeline_en_5.5.1_3.0_1737899442552.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_msrisrujan_pipeline_en_5.5.1_3.0_1737899442552.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_msrisrujan_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_msrisrujan_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_msrisrujan_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.9 MB|
+
+## References
+
+https://huggingface.co/Msrisrujan/xlm-roberta-base-finetuned-panx-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_french_rlawltjd_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_french_rlawltjd_en.md
new file mode 100644
index 00000000000000..412bce8ab64709
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_french_rlawltjd_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_rlawltjd XlmRoBertaForTokenClassification from rlawltjd
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_rlawltjd
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_rlawltjd` is a English model originally trained by rlawltjd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_rlawltjd_en_5.5.1_3.0_1737855068512.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_rlawltjd_en_5.5.1_3.0_1737855068512.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_rlawltjd","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_rlawltjd", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_rlawltjd|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/rlawltjd/xlm-roberta-base-finetuned-panx-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_french_rlawltjd_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_french_rlawltjd_pipeline_en.md
new file mode 100644
index 00000000000000..82ee14541ab506
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_french_rlawltjd_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_rlawltjd_pipeline pipeline XlmRoBertaForTokenClassification from rlawltjd
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_rlawltjd_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_rlawltjd_pipeline` is a English model originally trained by rlawltjd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_rlawltjd_pipeline_en_5.5.1_3.0_1737855159968.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_rlawltjd_pipeline_en_5.5.1_3.0_1737855159968.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_rlawltjd_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_rlawltjd_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_rlawltjd_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/rlawltjd/xlm-roberta-base-finetuned-panx-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_french_usmanyaqoob_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_french_usmanyaqoob_en.md
new file mode 100644
index 00000000000000..1ec653d26e06c8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_french_usmanyaqoob_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_usmanyaqoob XlmRoBertaForTokenClassification from usmanyaqoob
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_usmanyaqoob
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_usmanyaqoob` is a English model originally trained by usmanyaqoob.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_usmanyaqoob_en_5.5.1_3.0_1737897587962.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_usmanyaqoob_en_5.5.1_3.0_1737897587962.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_usmanyaqoob","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_usmanyaqoob", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_usmanyaqoob|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|828.0 MB|
+
+## References
+
+https://huggingface.co/usmanyaqoob/xlm-roberta-base-finetuned-panx-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_french_usmanyaqoob_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_french_usmanyaqoob_pipeline_en.md
new file mode 100644
index 00000000000000..ad88858f09cb76
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_french_usmanyaqoob_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_usmanyaqoob_pipeline pipeline XlmRoBertaForTokenClassification from usmanyaqoob
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_usmanyaqoob_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_usmanyaqoob_pipeline` is a English model originally trained by usmanyaqoob.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_usmanyaqoob_pipeline_en_5.5.1_3.0_1737897679566.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_usmanyaqoob_pipeline_en_5.5.1_3.0_1737897679566.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_usmanyaqoob_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_usmanyaqoob_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_usmanyaqoob_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|828.0 MB|
+
+## References
+
+https://huggingface.co/usmanyaqoob/xlm-roberta-base-finetuned-panx-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_ahid1_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_ahid1_en.md
new file mode 100644
index 00000000000000..b56154cf66e46d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_ahid1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_ahid1 XlmRoBertaForTokenClassification from ahid1
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_ahid1
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_ahid1` is a English model originally trained by ahid1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_ahid1_en_5.5.1_3.0_1737899519121.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_ahid1_en_5.5.1_3.0_1737899519121.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_ahid1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_ahid1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_ahid1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/ahid1/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_ahid1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_ahid1_pipeline_en.md
new file mode 100644
index 00000000000000..f80f646a93193b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_ahid1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_ahid1_pipeline pipeline XlmRoBertaForTokenClassification from ahid1
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_ahid1_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_ahid1_pipeline` is a English model originally trained by ahid1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_ahid1_pipeline_en_5.5.1_3.0_1737899611788.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_ahid1_pipeline_en_5.5.1_3.0_1737899611788.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_ahid1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_ahid1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_ahid1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/ahid1/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_danielbyiringiro_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_danielbyiringiro_en.md
new file mode 100644
index 00000000000000..8c770b19a86a85
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_danielbyiringiro_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_danielbyiringiro XlmRoBertaForTokenClassification from danielbyiringiro
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_danielbyiringiro
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_danielbyiringiro` is a English model originally trained by danielbyiringiro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_danielbyiringiro_en_5.5.1_3.0_1737854274120.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_danielbyiringiro_en_5.5.1_3.0_1737854274120.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_danielbyiringiro","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_danielbyiringiro", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_danielbyiringiro|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/danielbyiringiro/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_danielbyiringiro_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_danielbyiringiro_pipeline_en.md
new file mode 100644
index 00000000000000..2d75f147534305
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_danielbyiringiro_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_danielbyiringiro_pipeline pipeline XlmRoBertaForTokenClassification from danielbyiringiro
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_danielbyiringiro_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_danielbyiringiro_pipeline` is a English model originally trained by danielbyiringiro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_danielbyiringiro_pipeline_en_5.5.1_3.0_1737854360779.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_danielbyiringiro_pipeline_en_5.5.1_3.0_1737854360779.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_danielbyiringiro_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_danielbyiringiro_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_danielbyiringiro_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/danielbyiringiro/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_francois2511_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_francois2511_en.md
new file mode 100644
index 00000000000000..6635851a49e3da
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_francois2511_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_francois2511 XlmRoBertaForTokenClassification from Francois2511
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_francois2511
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_francois2511` is a English model originally trained by Francois2511.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_francois2511_en_5.5.1_3.0_1737853772396.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_francois2511_en_5.5.1_3.0_1737853772396.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_francois2511","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_francois2511", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_francois2511|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/Francois2511/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_francois2511_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_francois2511_pipeline_en.md
new file mode 100644
index 00000000000000..e83f48eb54a8c5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_francois2511_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_francois2511_pipeline pipeline XlmRoBertaForTokenClassification from Francois2511
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_francois2511_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_francois2511_pipeline` is a English model originally trained by Francois2511.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_francois2511_pipeline_en_5.5.1_3.0_1737853859818.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_francois2511_pipeline_en_5.5.1_3.0_1737853859818.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_francois2511_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_francois2511_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_francois2511_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/Francois2511/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_french_ahid1_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_french_ahid1_en.md
new file mode 100644
index 00000000000000..3783e544296812
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_french_ahid1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_ahid1 XlmRoBertaForTokenClassification from ahid1
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_ahid1
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_ahid1` is a English model originally trained by ahid1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_ahid1_en_5.5.1_3.0_1737898758278.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_ahid1_en_5.5.1_3.0_1737898758278.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_ahid1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_ahid1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_ahid1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/ahid1/xlm-roberta-base-finetuned-panx-de-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_french_ahid1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_french_ahid1_pipeline_en.md
new file mode 100644
index 00000000000000..374e132931ffff
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_french_ahid1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_ahid1_pipeline pipeline XlmRoBertaForTokenClassification from ahid1
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_ahid1_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_ahid1_pipeline` is a English model originally trained by ahid1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_ahid1_pipeline_en_5.5.1_3.0_1737898845740.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_ahid1_pipeline_en_5.5.1_3.0_1737898845740.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_ahid1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_ahid1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_ahid1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/ahid1/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_french_danielbyiringiro_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_french_danielbyiringiro_en.md
new file mode 100644
index 00000000000000..2fa329c7ad749b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_french_danielbyiringiro_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_danielbyiringiro XlmRoBertaForTokenClassification from danielbyiringiro
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_danielbyiringiro
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_danielbyiringiro` is a English model originally trained by danielbyiringiro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_danielbyiringiro_en_5.5.1_3.0_1737855161287.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_danielbyiringiro_en_5.5.1_3.0_1737855161287.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_danielbyiringiro","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_danielbyiringiro", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_danielbyiringiro|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/danielbyiringiro/xlm-roberta-base-finetuned-panx-de-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_french_danielbyiringiro_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_french_danielbyiringiro_pipeline_en.md
new file mode 100644
index 00000000000000..74b82c7c9a82a4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_french_danielbyiringiro_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_danielbyiringiro_pipeline pipeline XlmRoBertaForTokenClassification from danielbyiringiro
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_danielbyiringiro_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_danielbyiringiro_pipeline` is a English model originally trained by danielbyiringiro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_danielbyiringiro_pipeline_en_5.5.1_3.0_1737855251443.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_danielbyiringiro_pipeline_en_5.5.1_3.0_1737855251443.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_danielbyiringiro_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_danielbyiringiro_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_danielbyiringiro_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/danielbyiringiro/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_french_italian_english_hebrew_modern_arabic_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_french_italian_english_hebrew_modern_arabic_en.md
new file mode 100644
index 00000000000000..c6ae6ddd36b6ac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_french_italian_english_hebrew_modern_arabic_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_italian_english_hebrew_modern_arabic XlmRoBertaForTokenClassification from GV05
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_italian_english_hebrew_modern_arabic
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_italian_english_hebrew_modern_arabic` is a English model originally trained by GV05.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_italian_english_hebrew_modern_arabic_en_5.5.1_3.0_1737897864866.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_italian_english_hebrew_modern_arabic_en_5.5.1_3.0_1737897864866.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_italian_english_hebrew_modern_arabic","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_italian_english_hebrew_modern_arabic", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_italian_english_hebrew_modern_arabic|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|875.3 MB|
+
+## References
+
+https://huggingface.co/GV05/xlm-roberta-base-finetuned-panx-de-fr-it-en-he-ar
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_french_italian_english_hebrew_modern_arabic_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_french_italian_english_hebrew_modern_arabic_pipeline_en.md
new file mode 100644
index 00000000000000..54eae64eef4879
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_french_italian_english_hebrew_modern_arabic_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_italian_english_hebrew_modern_arabic_pipeline pipeline XlmRoBertaForTokenClassification from GV05
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_italian_english_hebrew_modern_arabic_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_italian_english_hebrew_modern_arabic_pipeline` is a English model originally trained by GV05.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_italian_english_hebrew_modern_arabic_pipeline_en_5.5.1_3.0_1737897929250.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_italian_english_hebrew_modern_arabic_pipeline_en_5.5.1_3.0_1737897929250.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_italian_english_hebrew_modern_arabic_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_italian_english_hebrew_modern_arabic_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_italian_english_hebrew_modern_arabic_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|875.4 MB|
+
+## References
+
+https://huggingface.co/GV05/xlm-roberta-base-finetuned-panx-de-fr-it-en-he-ar
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_french_july_tokyo_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_french_july_tokyo_en.md
new file mode 100644
index 00000000000000..8a7e13b1c83965
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_french_july_tokyo_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_july_tokyo XlmRoBertaForTokenClassification from July-Tokyo
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_july_tokyo
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_july_tokyo` is a English model originally trained by July-Tokyo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_july_tokyo_en_5.5.1_3.0_1737897959614.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_july_tokyo_en_5.5.1_3.0_1737897959614.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_july_tokyo","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_july_tokyo", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_july_tokyo|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/July-Tokyo/xlm-roberta-base-finetuned-panx-de-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_french_july_tokyo_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_french_july_tokyo_pipeline_en.md
new file mode 100644
index 00000000000000..bab9f8f9305be0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_french_july_tokyo_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_july_tokyo_pipeline pipeline XlmRoBertaForTokenClassification from July-Tokyo
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_july_tokyo_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_july_tokyo_pipeline` is a English model originally trained by July-Tokyo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_july_tokyo_pipeline_en_5.5.1_3.0_1737898047595.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_july_tokyo_pipeline_en_5.5.1_3.0_1737898047595.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_july_tokyo_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_july_tokyo_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_july_tokyo_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/July-Tokyo/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_french_leesihyun_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_french_leesihyun_en.md
new file mode 100644
index 00000000000000..3506af07da91a4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_french_leesihyun_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_leesihyun XlmRoBertaForTokenClassification from LEESIHYUN
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_leesihyun
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_leesihyun` is a English model originally trained by LEESIHYUN.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_leesihyun_en_5.5.1_3.0_1737898365515.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_leesihyun_en_5.5.1_3.0_1737898365515.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_leesihyun","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_leesihyun", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_leesihyun|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/LEESIHYUN/xlm-roberta-base-finetuned-panx-de-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_french_leesihyun_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_french_leesihyun_pipeline_en.md
new file mode 100644
index 00000000000000..e990faf4151863
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_french_leesihyun_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_leesihyun_pipeline pipeline XlmRoBertaForTokenClassification from LEESIHYUN
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_leesihyun_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_leesihyun_pipeline` is a English model originally trained by LEESIHYUN.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_leesihyun_pipeline_en_5.5.1_3.0_1737898452667.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_leesihyun_pipeline_en_5.5.1_3.0_1737898452667.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_leesihyun_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_leesihyun_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_leesihyun_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/LEESIHYUN/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_french_loki47_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_french_loki47_en.md
new file mode 100644
index 00000000000000..9aabada6b48195
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_french_loki47_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_loki47 XlmRoBertaForTokenClassification from loki47
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_loki47
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_loki47` is a English model originally trained by loki47.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_loki47_en_5.5.1_3.0_1737853777042.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_loki47_en_5.5.1_3.0_1737853777042.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_loki47","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_loki47", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_loki47|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/loki47/xlm-roberta-base-finetuned-panx-de-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_french_loki47_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_french_loki47_pipeline_en.md
new file mode 100644
index 00000000000000..1e6e8b863d07e8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_french_loki47_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_loki47_pipeline pipeline XlmRoBertaForTokenClassification from loki47
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_loki47_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_loki47_pipeline` is a English model originally trained by loki47.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_loki47_pipeline_en_5.5.1_3.0_1737853870630.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_loki47_pipeline_en_5.5.1_3.0_1737853870630.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_loki47_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_loki47_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_loki47_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/loki47/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_french_rlawltjd_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_french_rlawltjd_en.md
new file mode 100644
index 00000000000000..89e7ee9f62a246
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_french_rlawltjd_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_rlawltjd XlmRoBertaForTokenClassification from rlawltjd
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_rlawltjd
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_rlawltjd` is a English model originally trained by rlawltjd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_rlawltjd_en_5.5.1_3.0_1737854095781.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_rlawltjd_en_5.5.1_3.0_1737854095781.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_rlawltjd","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_rlawltjd", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_rlawltjd|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/rlawltjd/xlm-roberta-base-finetuned-panx-de-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_french_rlawltjd_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_french_rlawltjd_pipeline_en.md
new file mode 100644
index 00000000000000..a7aaaa6f8d3491
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_french_rlawltjd_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_rlawltjd_pipeline pipeline XlmRoBertaForTokenClassification from rlawltjd
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_rlawltjd_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_rlawltjd_pipeline` is a English model originally trained by rlawltjd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_rlawltjd_pipeline_en_5.5.1_3.0_1737854182746.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_rlawltjd_pipeline_en_5.5.1_3.0_1737854182746.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_rlawltjd_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_rlawltjd_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_rlawltjd_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/rlawltjd/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_french_usmanyaqoob_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_french_usmanyaqoob_en.md
new file mode 100644
index 00000000000000..9869705bd5e41e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_french_usmanyaqoob_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_usmanyaqoob XlmRoBertaForTokenClassification from usmanyaqoob
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_usmanyaqoob
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_usmanyaqoob` is a English model originally trained by usmanyaqoob.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_usmanyaqoob_en_5.5.1_3.0_1737898570848.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_usmanyaqoob_en_5.5.1_3.0_1737898570848.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_usmanyaqoob","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_usmanyaqoob", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_usmanyaqoob|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|843.3 MB|
+
+## References
+
+https://huggingface.co/usmanyaqoob/xlm-roberta-base-finetuned-panx-de-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_french_usmanyaqoob_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_french_usmanyaqoob_pipeline_en.md
new file mode 100644
index 00000000000000..6d6ba1f433f718
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_french_usmanyaqoob_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_usmanyaqoob_pipeline pipeline XlmRoBertaForTokenClassification from usmanyaqoob
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_usmanyaqoob_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_usmanyaqoob_pipeline` is a English model originally trained by usmanyaqoob.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_usmanyaqoob_pipeline_en_5.5.1_3.0_1737898658747.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_usmanyaqoob_pipeline_en_5.5.1_3.0_1737898658747.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_usmanyaqoob_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_usmanyaqoob_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_usmanyaqoob_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|843.3 MB|
+
+## References
+
+https://huggingface.co/usmanyaqoob/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_iwantmorebugs_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_iwantmorebugs_en.md
new file mode 100644
index 00000000000000..b604c853840329
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_iwantmorebugs_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_iwantmorebugs XlmRoBertaForTokenClassification from iwantmorebugs
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_iwantmorebugs
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_iwantmorebugs` is a English model originally trained by iwantmorebugs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_iwantmorebugs_en_5.5.1_3.0_1737898829908.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_iwantmorebugs_en_5.5.1_3.0_1737898829908.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_iwantmorebugs","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_iwantmorebugs", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_iwantmorebugs|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/iwantmorebugs/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_iwantmorebugs_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_iwantmorebugs_pipeline_en.md
new file mode 100644
index 00000000000000..18073c378db997
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_iwantmorebugs_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_iwantmorebugs_pipeline pipeline XlmRoBertaForTokenClassification from iwantmorebugs
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_iwantmorebugs_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_iwantmorebugs_pipeline` is a English model originally trained by iwantmorebugs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_iwantmorebugs_pipeline_en_5.5.1_3.0_1737898915928.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_iwantmorebugs_pipeline_en_5.5.1_3.0_1737898915928.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_iwantmorebugs_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_iwantmorebugs_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_iwantmorebugs_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/iwantmorebugs/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_july_tokyo_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_july_tokyo_en.md
new file mode 100644
index 00000000000000..1b76eff8c1ee52
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_july_tokyo_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_july_tokyo XlmRoBertaForTokenClassification from July-Tokyo
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_july_tokyo
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_july_tokyo` is a English model originally trained by July-Tokyo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_july_tokyo_en_5.5.1_3.0_1737897820076.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_july_tokyo_en_5.5.1_3.0_1737897820076.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_july_tokyo","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_july_tokyo", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_july_tokyo|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/July-Tokyo/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_july_tokyo_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_july_tokyo_pipeline_en.md
new file mode 100644
index 00000000000000..21d7f5841b596f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_july_tokyo_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_july_tokyo_pipeline pipeline XlmRoBertaForTokenClassification from July-Tokyo
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_july_tokyo_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_july_tokyo_pipeline` is a English model originally trained by July-Tokyo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_july_tokyo_pipeline_en_5.5.1_3.0_1737897906841.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_july_tokyo_pipeline_en_5.5.1_3.0_1737897906841.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_july_tokyo_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_july_tokyo_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_july_tokyo_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/July-Tokyo/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_longma98_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_longma98_en.md
new file mode 100644
index 00000000000000..c231ab9970ac87
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_longma98_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_longma98 XlmRoBertaForTokenClassification from longma98
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_longma98
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_longma98` is a English model originally trained by longma98.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_longma98_en_5.5.1_3.0_1737899143720.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_longma98_en_5.5.1_3.0_1737899143720.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_longma98","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_longma98", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_longma98|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/longma98/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_longma98_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_longma98_pipeline_en.md
new file mode 100644
index 00000000000000..42acdf053fbdd6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_longma98_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_longma98_pipeline pipeline XlmRoBertaForTokenClassification from longma98
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_longma98_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_longma98_pipeline` is a English model originally trained by longma98.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_longma98_pipeline_en_5.5.1_3.0_1737899230263.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_longma98_pipeline_en_5.5.1_3.0_1737899230263.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_longma98_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_longma98_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_longma98_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/longma98/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_lortigas_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_lortigas_en.md
new file mode 100644
index 00000000000000..c0af82fcde278a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_lortigas_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_lortigas XlmRoBertaForTokenClassification from lortigas
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_lortigas
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_lortigas` is a English model originally trained by lortigas.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_lortigas_en_5.5.1_3.0_1737899454877.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_lortigas_en_5.5.1_3.0_1737899454877.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_lortigas","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_lortigas", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_lortigas|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/lortigas/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_lortigas_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_lortigas_pipeline_en.md
new file mode 100644
index 00000000000000..793118fb927eb9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_lortigas_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_lortigas_pipeline pipeline XlmRoBertaForTokenClassification from lortigas
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_lortigas_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_lortigas_pipeline` is a English model originally trained by lortigas.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_lortigas_pipeline_en_5.5.1_3.0_1737899523573.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_lortigas_pipeline_en_5.5.1_3.0_1737899523573.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_lortigas_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_lortigas_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_lortigas_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/lortigas/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_mkanare_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_mkanare_en.md
new file mode 100644
index 00000000000000..1b449a54d1b064
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_mkanare_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_mkanare XlmRoBertaForTokenClassification from mkanare
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_mkanare
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_mkanare` is a English model originally trained by mkanare.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_mkanare_en_5.5.1_3.0_1737854057052.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_mkanare_en_5.5.1_3.0_1737854057052.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_mkanare","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_mkanare", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_mkanare|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/mkanare/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_mkanare_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_mkanare_pipeline_en.md
new file mode 100644
index 00000000000000..7201acfc755186
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_mkanare_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_mkanare_pipeline pipeline XlmRoBertaForTokenClassification from mkanare
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_mkanare_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_mkanare_pipeline` is a English model originally trained by mkanare.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_mkanare_pipeline_en_5.5.1_3.0_1737854143890.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_mkanare_pipeline_en_5.5.1_3.0_1737854143890.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_mkanare_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_mkanare_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_mkanare_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/mkanare/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_nik135_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_nik135_en.md
new file mode 100644
index 00000000000000..40f871bf3bb1df
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_nik135_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_nik135 XlmRoBertaForTokenClassification from nik135
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_nik135
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_nik135` is a English model originally trained by nik135.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_nik135_en_5.5.1_3.0_1737898175370.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_nik135_en_5.5.1_3.0_1737898175370.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_nik135","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_nik135", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_nik135|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|841.2 MB|
+
+## References
+
+https://huggingface.co/nik135/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_nik135_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_nik135_pipeline_en.md
new file mode 100644
index 00000000000000..0f19f52fc6ce72
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_nik135_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_nik135_pipeline pipeline XlmRoBertaForTokenClassification from nik135
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_nik135_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_nik135_pipeline` is a English model originally trained by nik135.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_nik135_pipeline_en_5.5.1_3.0_1737898261940.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_nik135_pipeline_en_5.5.1_3.0_1737898261940.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_nik135_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_nik135_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_nik135_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|841.2 MB|
+
+## References
+
+https://huggingface.co/nik135/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_obong_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_obong_en.md
new file mode 100644
index 00000000000000..c18cc7660b5c1d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_obong_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_obong XlmRoBertaForTokenClassification from obong
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_obong
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_obong` is a English model originally trained by obong.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_obong_en_5.5.1_3.0_1737898004611.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_obong_en_5.5.1_3.0_1737898004611.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_obong","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_obong", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_obong|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/obong/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_obong_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_obong_pipeline_en.md
new file mode 100644
index 00000000000000..ef239c8f730114
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_obong_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_obong_pipeline pipeline XlmRoBertaForTokenClassification from obong
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_obong_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_obong_pipeline` is a English model originally trained by obong.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_obong_pipeline_en_5.5.1_3.0_1737898075052.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_obong_pipeline_en_5.5.1_3.0_1737898075052.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_obong_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_obong_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_obong_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/obong/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_psardinha_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_psardinha_en.md
new file mode 100644
index 00000000000000..778c3928ad8e37
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_psardinha_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_psardinha XlmRoBertaForTokenClassification from psardinha
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_psardinha
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_psardinha` is a English model originally trained by psardinha.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_psardinha_en_5.5.1_3.0_1737898523972.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_psardinha_en_5.5.1_3.0_1737898523972.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_psardinha","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_psardinha", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_psardinha|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|837.8 MB|
+
+## References
+
+https://huggingface.co/psardinha/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_psardinha_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_psardinha_pipeline_en.md
new file mode 100644
index 00000000000000..1b9e8ca60c3716
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_psardinha_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_psardinha_pipeline pipeline XlmRoBertaForTokenClassification from psardinha
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_psardinha_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_psardinha_pipeline` is a English model originally trained by psardinha.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_psardinha_pipeline_en_5.5.1_3.0_1737898617758.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_psardinha_pipeline_en_5.5.1_3.0_1737898617758.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_psardinha_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_psardinha_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_psardinha_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|837.8 MB|
+
+## References
+
+https://huggingface.co/psardinha/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_radamshi_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_radamshi_en.md
new file mode 100644
index 00000000000000..7f90cd0c424ce6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_radamshi_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_radamshi XlmRoBertaForTokenClassification from RADAMSHI
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_radamshi
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_radamshi` is a English model originally trained by RADAMSHI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_radamshi_en_5.5.1_3.0_1737898908308.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_radamshi_en_5.5.1_3.0_1737898908308.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_radamshi","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_radamshi", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_radamshi|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|841.2 MB|
+
+## References
+
+https://huggingface.co/RADAMSHI/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_radamshi_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_radamshi_pipeline_en.md
new file mode 100644
index 00000000000000..46650ce5176135
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_radamshi_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_radamshi_pipeline pipeline XlmRoBertaForTokenClassification from RADAMSHI
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_radamshi_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_radamshi_pipeline` is a English model originally trained by RADAMSHI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_radamshi_pipeline_en_5.5.1_3.0_1737898994837.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_radamshi_pipeline_en_5.5.1_3.0_1737898994837.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_radamshi_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_radamshi_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_radamshi_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|841.2 MB|
+
+## References
+
+https://huggingface.co/RADAMSHI/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_shawki11_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_shawki11_en.md
new file mode 100644
index 00000000000000..4350f668946e8e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_shawki11_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_shawki11 XlmRoBertaForTokenClassification from Shawki11
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_shawki11
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_shawki11` is a English model originally trained by Shawki11.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_shawki11_en_5.5.1_3.0_1737854284591.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_shawki11_en_5.5.1_3.0_1737854284591.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_shawki11","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_shawki11", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_shawki11|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|845.0 MB|
+
+## References
+
+https://huggingface.co/Shawki11/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_shawki11_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_shawki11_pipeline_en.md
new file mode 100644
index 00000000000000..b52cfeb4fcc3e3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_shawki11_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_shawki11_pipeline pipeline XlmRoBertaForTokenClassification from Shawki11
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_shawki11_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_shawki11_pipeline` is a English model originally trained by Shawki11.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_shawki11_pipeline_en_5.5.1_3.0_1737854370820.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_shawki11_pipeline_en_5.5.1_3.0_1737854370820.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_shawki11_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_shawki11_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_shawki11_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|845.0 MB|
+
+## References
+
+https://huggingface.co/Shawki11/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_sreek_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_sreek_en.md
new file mode 100644
index 00000000000000..7b9b50156715a1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_sreek_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_sreek XlmRoBertaForTokenClassification from Sreek
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_sreek
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_sreek` is a English model originally trained by Sreek.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_sreek_en_5.5.1_3.0_1737853824369.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_sreek_en_5.5.1_3.0_1737853824369.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_sreek","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_sreek", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_sreek|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/Sreek/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_sreek_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_sreek_pipeline_en.md
new file mode 100644
index 00000000000000..3f162ac33d25c4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_sreek_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_sreek_pipeline pipeline XlmRoBertaForTokenClassification from Sreek
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_sreek_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_sreek_pipeline` is a English model originally trained by Sreek.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_sreek_pipeline_en_5.5.1_3.0_1737853894322.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_sreek_pipeline_en_5.5.1_3.0_1737853894322.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_sreek_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_sreek_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_sreek_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/Sreek/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_usmanyaqoob_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_usmanyaqoob_en.md
new file mode 100644
index 00000000000000..d6f97ed8794c8b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_usmanyaqoob_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_usmanyaqoob XlmRoBertaForTokenClassification from usmanyaqoob
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_usmanyaqoob
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_usmanyaqoob` is a English model originally trained by usmanyaqoob.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_usmanyaqoob_en_5.5.1_3.0_1737897415539.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_usmanyaqoob_en_5.5.1_3.0_1737897415539.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_usmanyaqoob","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_usmanyaqoob", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_usmanyaqoob|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.6 MB|
+
+## References
+
+https://huggingface.co/usmanyaqoob/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_usmanyaqoob_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_usmanyaqoob_pipeline_en.md
new file mode 100644
index 00000000000000..b8458e9970ecee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_german_usmanyaqoob_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_usmanyaqoob_pipeline pipeline XlmRoBertaForTokenClassification from usmanyaqoob
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_usmanyaqoob_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_usmanyaqoob_pipeline` is a English model originally trained by usmanyaqoob.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_usmanyaqoob_pipeline_en_5.5.1_3.0_1737897510963.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_usmanyaqoob_pipeline_en_5.5.1_3.0_1737897510963.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_usmanyaqoob_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_usmanyaqoob_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_usmanyaqoob_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.6 MB|
+
+## References
+
+https://huggingface.co/usmanyaqoob/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_italian_ahid1_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_italian_ahid1_en.md
new file mode 100644
index 00000000000000..c384847804670c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_italian_ahid1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_ahid1 XlmRoBertaForTokenClassification from ahid1
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_ahid1
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_ahid1` is a English model originally trained by ahid1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_ahid1_en_5.5.1_3.0_1737898695381.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_ahid1_en_5.5.1_3.0_1737898695381.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_ahid1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_ahid1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_ahid1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|816.7 MB|
+
+## References
+
+https://huggingface.co/ahid1/xlm-roberta-base-finetuned-panx-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_italian_ahid1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_italian_ahid1_pipeline_en.md
new file mode 100644
index 00000000000000..d734ef3ee0d8f2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_italian_ahid1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_ahid1_pipeline pipeline XlmRoBertaForTokenClassification from ahid1
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_ahid1_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_ahid1_pipeline` is a English model originally trained by ahid1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_ahid1_pipeline_en_5.5.1_3.0_1737898793836.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_ahid1_pipeline_en_5.5.1_3.0_1737898793836.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_ahid1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_ahid1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_ahid1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|816.8 MB|
+
+## References
+
+https://huggingface.co/ahid1/xlm-roberta-base-finetuned-panx-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_italian_july_tokyo_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_italian_july_tokyo_en.md
new file mode 100644
index 00000000000000..7b8ccef57ea20e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_italian_july_tokyo_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_july_tokyo XlmRoBertaForTokenClassification from July-Tokyo
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_july_tokyo
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_july_tokyo` is a English model originally trained by July-Tokyo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_july_tokyo_en_5.5.1_3.0_1737854474488.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_july_tokyo_en_5.5.1_3.0_1737854474488.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_july_tokyo","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_july_tokyo", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_july_tokyo|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|816.7 MB|
+
+## References
+
+https://huggingface.co/July-Tokyo/xlm-roberta-base-finetuned-panx-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_italian_july_tokyo_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_italian_july_tokyo_pipeline_en.md
new file mode 100644
index 00000000000000..e1b826b0364250
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_italian_july_tokyo_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_july_tokyo_pipeline pipeline XlmRoBertaForTokenClassification from July-Tokyo
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_july_tokyo_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_july_tokyo_pipeline` is a English model originally trained by July-Tokyo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_july_tokyo_pipeline_en_5.5.1_3.0_1737854573317.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_july_tokyo_pipeline_en_5.5.1_3.0_1737854573317.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_july_tokyo_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_july_tokyo_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_july_tokyo_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|816.8 MB|
+
+## References
+
+https://huggingface.co/July-Tokyo/xlm-roberta-base-finetuned-panx-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_italian_leesihyun_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_italian_leesihyun_en.md
new file mode 100644
index 00000000000000..d8ebda5ebdd1b9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_italian_leesihyun_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_leesihyun XlmRoBertaForTokenClassification from LEESIHYUN
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_leesihyun
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_leesihyun` is a English model originally trained by LEESIHYUN.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_leesihyun_en_5.5.1_3.0_1737897556514.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_leesihyun_en_5.5.1_3.0_1737897556514.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_leesihyun","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_leesihyun", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_leesihyun|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|816.7 MB|
+
+## References
+
+https://huggingface.co/LEESIHYUN/xlm-roberta-base-finetuned-panx-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_italian_leesihyun_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_italian_leesihyun_pipeline_en.md
new file mode 100644
index 00000000000000..588ab7351ad812
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_italian_leesihyun_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_leesihyun_pipeline pipeline XlmRoBertaForTokenClassification from LEESIHYUN
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_leesihyun_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_leesihyun_pipeline` is a English model originally trained by LEESIHYUN.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_leesihyun_pipeline_en_5.5.1_3.0_1737897654431.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_leesihyun_pipeline_en_5.5.1_3.0_1737897654431.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_leesihyun_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_leesihyun_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_leesihyun_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|816.8 MB|
+
+## References
+
+https://huggingface.co/LEESIHYUN/xlm-roberta-base-finetuned-panx-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_italian_mcguiver_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_italian_mcguiver_en.md
new file mode 100644
index 00000000000000..a943a28fc18467
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_italian_mcguiver_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_mcguiver XlmRoBertaForTokenClassification from mcguiver
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_mcguiver
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_mcguiver` is a English model originally trained by mcguiver.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_mcguiver_en_5.5.1_3.0_1737854675227.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_mcguiver_en_5.5.1_3.0_1737854675227.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_mcguiver","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_mcguiver", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_mcguiver|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|816.7 MB|
+
+## References
+
+https://huggingface.co/mcguiver/xlm-roberta-base-finetuned-panx-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_italian_mcguiver_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_italian_mcguiver_pipeline_en.md
new file mode 100644
index 00000000000000..d232363f8a0c6e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_italian_mcguiver_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_mcguiver_pipeline pipeline XlmRoBertaForTokenClassification from mcguiver
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_mcguiver_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_mcguiver_pipeline` is a English model originally trained by mcguiver.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_mcguiver_pipeline_en_5.5.1_3.0_1737854774477.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_mcguiver_pipeline_en_5.5.1_3.0_1737854774477.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_mcguiver_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_mcguiver_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_mcguiver_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|816.8 MB|
+
+## References
+
+https://huggingface.co/mcguiver/xlm-roberta-base-finetuned-panx-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_italian_soumilj_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_italian_soumilj_en.md
new file mode 100644
index 00000000000000..6d5ee04511fc8d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_italian_soumilj_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_soumilj XlmRoBertaForTokenClassification from soumilj
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_soumilj
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_soumilj` is a English model originally trained by soumilj.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_soumilj_en_5.5.1_3.0_1737853734144.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_soumilj_en_5.5.1_3.0_1737853734144.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_soumilj","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_soumilj", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_soumilj|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|813.8 MB|
+
+## References
+
+https://huggingface.co/soumilj/xlm-roberta-base-finetuned-panx-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_italian_soumilj_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_italian_soumilj_pipeline_en.md
new file mode 100644
index 00000000000000..144e0d0dd462d2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_italian_soumilj_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_soumilj_pipeline pipeline XlmRoBertaForTokenClassification from soumilj
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_soumilj_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_soumilj_pipeline` is a English model originally trained by soumilj.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_soumilj_pipeline_en_5.5.1_3.0_1737853835037.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_soumilj_pipeline_en_5.5.1_3.0_1737853835037.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_soumilj_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_soumilj_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_soumilj_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|813.8 MB|
+
+## References
+
+https://huggingface.co/soumilj/xlm-roberta-base-finetuned-panx-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_italian_usmanyaqoob_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_italian_usmanyaqoob_en.md
new file mode 100644
index 00000000000000..caefb457ee0e7a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_italian_usmanyaqoob_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_usmanyaqoob XlmRoBertaForTokenClassification from usmanyaqoob
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_usmanyaqoob
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_usmanyaqoob` is a English model originally trained by usmanyaqoob.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_usmanyaqoob_en_5.5.1_3.0_1737899007726.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_usmanyaqoob_en_5.5.1_3.0_1737899007726.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_usmanyaqoob","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_usmanyaqoob", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_usmanyaqoob|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|816.8 MB|
+
+## References
+
+https://huggingface.co/usmanyaqoob/xlm-roberta-base-finetuned-panx-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_italian_usmanyaqoob_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_italian_usmanyaqoob_pipeline_en.md
new file mode 100644
index 00000000000000..139d3e2313e6c2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_panx_italian_usmanyaqoob_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_usmanyaqoob_pipeline pipeline XlmRoBertaForTokenClassification from usmanyaqoob
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_usmanyaqoob_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_usmanyaqoob_pipeline` is a English model originally trained by usmanyaqoob.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_usmanyaqoob_pipeline_en_5.5.1_3.0_1737899106801.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_usmanyaqoob_pipeline_en_5.5.1_3.0_1737899106801.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_usmanyaqoob_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_usmanyaqoob_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_usmanyaqoob_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|816.8 MB|
+
+## References
+
+https://huggingface.co/usmanyaqoob/xlm-roberta-base-finetuned-panx-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_t_price_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_t_price_en.md
new file mode 100644
index 00000000000000..5b80bdd995f539
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_t_price_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_t_price XlmRoBertaForSequenceClassification from Gregorig
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_t_price
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_t_price` is a English model originally trained by Gregorig.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_t_price_en_5.5.1_3.0_1737879193368.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_t_price_en_5.5.1_3.0_1737879193368.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_finetuned_t_price","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_finetuned_t_price", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_t_price|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|796.4 MB|
+
+## References
+
+https://huggingface.co/Gregorig/xlm-roberta-base-finetuned-t_price
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_t_price_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_t_price_pipeline_en.md
new file mode 100644
index 00000000000000..0d6f189a90719e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_finetuned_t_price_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_t_price_pipeline pipeline XlmRoBertaForSequenceClassification from Gregorig
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_t_price_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_t_price_pipeline` is a English model originally trained by Gregorig.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_t_price_pipeline_en_5.5.1_3.0_1737879337103.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_t_price_pipeline_en_5.5.1_3.0_1737879337103.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_t_price_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_t_price_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_t_price_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|796.4 MB|
+
+## References
+
+https://huggingface.co/Gregorig/xlm-roberta-base-finetuned-t_price
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_ft_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_ft_en.md
new file mode 100644
index 00000000000000..dd90db81532f9c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_ft_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_ft XlmRoBertaForSequenceClassification from jgilhuly16
+author: John Snow Labs
+name: xlm_roberta_base_ft
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_ft` is a English model originally trained by jgilhuly16.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_ft_en_5.5.1_3.0_1737878769860.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_ft_en_5.5.1_3.0_1737878769860.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_ft","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_ft", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_ft|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|795.6 MB|
+
+## References
+
+https://huggingface.co/jgilhuly16/xlm-roberta-base-ft
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_ft_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_ft_pipeline_en.md
new file mode 100644
index 00000000000000..f7bc2422f6a902
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_ft_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_ft_pipeline pipeline XlmRoBertaForSequenceClassification from jgilhuly16
+author: John Snow Labs
+name: xlm_roberta_base_ft_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_ft_pipeline` is a English model originally trained by jgilhuly16.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_ft_pipeline_en_5.5.1_3.0_1737878908352.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_ft_pipeline_en_5.5.1_3.0_1737878908352.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_ft_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_ft_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_ft_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|795.6 MB|
+
+## References
+
+https://huggingface.co/jgilhuly16/xlm-roberta-base-ft
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_latin_intertextuality_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_latin_intertextuality_en.md
new file mode 100644
index 00000000000000..edf936833ebc93
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_latin_intertextuality_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_latin_intertextuality XlmRoBertaForSequenceClassification from julian-schelb
+author: John Snow Labs
+name: xlm_roberta_base_latin_intertextuality
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_latin_intertextuality` is a English model originally trained by julian-schelb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_latin_intertextuality_en_5.5.1_3.0_1737881484393.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_latin_intertextuality_en_5.5.1_3.0_1737881484393.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_latin_intertextuality","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_latin_intertextuality", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_latin_intertextuality|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|797.1 MB|
+
+## References
+
+https://huggingface.co/julian-schelb/xlm-roberta-base-latin-intertextuality
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_latin_intertextuality_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_latin_intertextuality_pipeline_en.md
new file mode 100644
index 00000000000000..a31f69ccbd678f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_latin_intertextuality_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_latin_intertextuality_pipeline pipeline XlmRoBertaForSequenceClassification from julian-schelb
+author: John Snow Labs
+name: xlm_roberta_base_latin_intertextuality_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_latin_intertextuality_pipeline` is a English model originally trained by julian-schelb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_latin_intertextuality_pipeline_en_5.5.1_3.0_1737881617922.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_latin_intertextuality_pipeline_en_5.5.1_3.0_1737881617922.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_latin_intertextuality_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_latin_intertextuality_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_latin_intertextuality_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|797.1 MB|
+
+## References
+
+https://huggingface.co/julian-schelb/xlm-roberta-base-latin-intertextuality
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_qp_1e5_r_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_qp_1e5_r_en.md
new file mode 100644
index 00000000000000..90cbb93e018051
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_qp_1e5_r_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_qp_1e5_r XlmRoBertaForSequenceClassification from ngwgsang
+author: John Snow Labs
+name: xlm_roberta_base_qp_1e5_r
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_qp_1e5_r` is a English model originally trained by ngwgsang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_qp_1e5_r_en_5.5.1_3.0_1737883270563.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_qp_1e5_r_en_5.5.1_3.0_1737883270563.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_qp_1e5_r","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_qp_1e5_r", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_qp_1e5_r|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|845.6 MB|
+
+## References
+
+https://huggingface.co/ngwgsang/xlm-roberta-base-qp-1e5-r
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_qp_1e5_r_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_qp_1e5_r_pipeline_en.md
new file mode 100644
index 00000000000000..e168850dcdaa21
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_qp_1e5_r_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_qp_1e5_r_pipeline pipeline XlmRoBertaForSequenceClassification from ngwgsang
+author: John Snow Labs
+name: xlm_roberta_base_qp_1e5_r_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_qp_1e5_r_pipeline` is a English model originally trained by ngwgsang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_qp_1e5_r_pipeline_en_5.5.1_3.0_1737883343020.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_qp_1e5_r_pipeline_en_5.5.1_3.0_1737883343020.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_qp_1e5_r_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_qp_1e5_r_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_qp_1e5_r_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|845.7 MB|
+
+## References
+
+https://huggingface.co/ngwgsang/xlm-roberta-base-qp-1e5-r
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_trans_finetuned_pearsonr_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_trans_finetuned_pearsonr_en.md
new file mode 100644
index 00000000000000..fb1234b353d498
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_trans_finetuned_pearsonr_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_trans_finetuned_pearsonr XlmRoBertaForSequenceClassification from aabid123
+author: John Snow Labs
+name: xlm_roberta_base_trans_finetuned_pearsonr
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_trans_finetuned_pearsonr` is a English model originally trained by aabid123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_trans_finetuned_pearsonr_en_5.5.1_3.0_1737881765136.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_trans_finetuned_pearsonr_en_5.5.1_3.0_1737881765136.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_trans_finetuned_pearsonr","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_trans_finetuned_pearsonr", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_trans_finetuned_pearsonr|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|808.1 MB|
+
+## References
+
+https://huggingface.co/aabid123/xlm-roberta-base-trans-finetuned-pearsonr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_trans_finetuned_pearsonr_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_trans_finetuned_pearsonr_pipeline_en.md
new file mode 100644
index 00000000000000..52a44354b91a92
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_trans_finetuned_pearsonr_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_trans_finetuned_pearsonr_pipeline pipeline XlmRoBertaForSequenceClassification from aabid123
+author: John Snow Labs
+name: xlm_roberta_base_trans_finetuned_pearsonr_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_trans_finetuned_pearsonr_pipeline` is a English model originally trained by aabid123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_trans_finetuned_pearsonr_pipeline_en_5.5.1_3.0_1737881888055.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_trans_finetuned_pearsonr_pipeline_en_5.5.1_3.0_1737881888055.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_trans_finetuned_pearsonr_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_trans_finetuned_pearsonr_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_trans_finetuned_pearsonr_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|808.1 MB|
+
+## References
+
+https://huggingface.co/aabid123/xlm-roberta-base-trans-finetuned-pearsonr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_vietnam_aug_replace_w2v_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_vietnam_aug_replace_w2v_en.md
new file mode 100644
index 00000000000000..733177f87ab42e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_vietnam_aug_replace_w2v_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_vietnam_aug_replace_w2v XlmRoBertaForSequenceClassification from ThuyNT03
+author: John Snow Labs
+name: xlm_roberta_base_vietnam_aug_replace_w2v
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_vietnam_aug_replace_w2v` is a English model originally trained by ThuyNT03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_vietnam_aug_replace_w2v_en_5.5.1_3.0_1737887002125.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_vietnam_aug_replace_w2v_en_5.5.1_3.0_1737887002125.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_vietnam_aug_replace_w2v","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_vietnam_aug_replace_w2v", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_vietnam_aug_replace_w2v|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|794.8 MB|
+
+## References
+
+https://huggingface.co/ThuyNT03/xlm-roberta-base-VietNam-aug_replace_w2v
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_vietnam_aug_replace_w2v_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_vietnam_aug_replace_w2v_pipeline_en.md
new file mode 100644
index 00000000000000..4a346e39244014
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_vietnam_aug_replace_w2v_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_vietnam_aug_replace_w2v_pipeline pipeline XlmRoBertaForSequenceClassification from ThuyNT03
+author: John Snow Labs
+name: xlm_roberta_base_vietnam_aug_replace_w2v_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_vietnam_aug_replace_w2v_pipeline` is a English model originally trained by ThuyNT03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_vietnam_aug_replace_w2v_pipeline_en_5.5.1_3.0_1737887131216.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_vietnam_aug_replace_w2v_pipeline_en_5.5.1_3.0_1737887131216.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_vietnam_aug_replace_w2v_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_vietnam_aug_replace_w2v_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_vietnam_aug_replace_w2v_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|794.9 MB|
+
+## References
+
+https://huggingface.co/ThuyNT03/xlm-roberta-base-VietNam-aug_replace_w2v
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_vsmec_100_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_vsmec_100_en.md
new file mode 100644
index 00000000000000..4936f9bdfafd8a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_vsmec_100_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_vsmec_100 XlmRoBertaForSequenceClassification from tmnam20
+author: John Snow Labs
+name: xlm_roberta_base_vsmec_100
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_vsmec_100` is a English model originally trained by tmnam20.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_vsmec_100_en_5.5.1_3.0_1737882340397.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_vsmec_100_en_5.5.1_3.0_1737882340397.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_vsmec_100","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_vsmec_100", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_vsmec_100|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|774.5 MB|
+
+## References
+
+https://huggingface.co/tmnam20/xlm-roberta-base-vsmec-100
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_vsmec_100_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_vsmec_100_pipeline_en.md
new file mode 100644
index 00000000000000..e093bd71c5cbf4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_base_vsmec_100_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_vsmec_100_pipeline pipeline XlmRoBertaForSequenceClassification from tmnam20
+author: John Snow Labs
+name: xlm_roberta_base_vsmec_100_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_vsmec_100_pipeline` is a English model originally trained by tmnam20.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_vsmec_100_pipeline_en_5.5.1_3.0_1737882482942.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_vsmec_100_pipeline_en_5.5.1_3.0_1737882482942.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_vsmec_100_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_vsmec_100_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_vsmec_100_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|774.5 MB|
+
+## References
+
+https://huggingface.co/tmnam20/xlm-roberta-base-vsmec-100
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_hausa_sentiment_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_hausa_sentiment_en.md
new file mode 100644
index 00000000000000..3d339c5ea13dfb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_hausa_sentiment_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_hausa_sentiment XlmRoBertaForSequenceClassification from lukmanaj
+author: John Snow Labs
+name: xlm_roberta_hausa_sentiment
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_hausa_sentiment` is a English model originally trained by lukmanaj.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_hausa_sentiment_en_5.5.1_3.0_1737883444844.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_hausa_sentiment_en_5.5.1_3.0_1737883444844.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_hausa_sentiment","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_hausa_sentiment", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_hausa_sentiment|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|819.0 MB|
+
+## References
+
+https://huggingface.co/lukmanaj/xlm-roberta-hausa-sentiment
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_hausa_sentiment_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_hausa_sentiment_pipeline_en.md
new file mode 100644
index 00000000000000..68c09aa0e80b15
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlm_roberta_hausa_sentiment_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_hausa_sentiment_pipeline pipeline XlmRoBertaForSequenceClassification from lukmanaj
+author: John Snow Labs
+name: xlm_roberta_hausa_sentiment_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_hausa_sentiment_pipeline` is a English model originally trained by lukmanaj.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_hausa_sentiment_pipeline_en_5.5.1_3.0_1737883544685.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_hausa_sentiment_pipeline_en_5.5.1_3.0_1737883544685.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_hausa_sentiment_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_hausa_sentiment_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_hausa_sentiment_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|819.0 MB|
+
+## References
+
+https://huggingface.co/lukmanaj/xlm-roberta-hausa-sentiment
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlmr_drug_classifier_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlmr_drug_classifier_en.md
new file mode 100644
index 00000000000000..260f3c87561424
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlmr_drug_classifier_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlmr_drug_classifier XlmRoBertaForSequenceClassification from aaaksenova
+author: John Snow Labs
+name: xlmr_drug_classifier
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmr_drug_classifier` is a English model originally trained by aaaksenova.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmr_drug_classifier_en_5.5.1_3.0_1737886466089.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmr_drug_classifier_en_5.5.1_3.0_1737886466089.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlmr_drug_classifier","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlmr_drug_classifier", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmr_drug_classifier|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/aaaksenova/xlmr_drug_classifier
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlmr_drug_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlmr_drug_classifier_pipeline_en.md
new file mode 100644
index 00000000000000..f3ef2fa1f5a622
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlmr_drug_classifier_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlmr_drug_classifier_pipeline pipeline XlmRoBertaForSequenceClassification from aaaksenova
+author: John Snow Labs
+name: xlmr_drug_classifier_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmr_drug_classifier_pipeline` is a English model originally trained by aaaksenova.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmr_drug_classifier_pipeline_en_5.5.1_3.0_1737886519188.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmr_drug_classifier_pipeline_en_5.5.1_3.0_1737886519188.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlmr_drug_classifier_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmr_drug_classifier_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmr_drug_classifier_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/aaaksenova/xlmr_drug_classifier
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlmr_roberta_base_finetuned_panx_all_ajit_transformer_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlmr_roberta_base_finetuned_panx_all_ajit_transformer_en.md
new file mode 100644
index 00000000000000..650ec826a88f63
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlmr_roberta_base_finetuned_panx_all_ajit_transformer_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlmr_roberta_base_finetuned_panx_all_ajit_transformer XlmRoBertaForTokenClassification from ajit-transformer
+author: John Snow Labs
+name: xlmr_roberta_base_finetuned_panx_all_ajit_transformer
+date: 2025-01-26
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmr_roberta_base_finetuned_panx_all_ajit_transformer` is a English model originally trained by ajit-transformer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmr_roberta_base_finetuned_panx_all_ajit_transformer_en_5.5.1_3.0_1737898138352.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmr_roberta_base_finetuned_panx_all_ajit_transformer_en_5.5.1_3.0_1737898138352.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlmr_roberta_base_finetuned_panx_all_ajit_transformer","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlmr_roberta_base_finetuned_panx_all_ajit_transformer", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmr_roberta_base_finetuned_panx_all_ajit_transformer|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|837.4 MB|
+
+## References
+
+https://huggingface.co/ajit-transformer/xlmr-roberta-base-finetuned-panx-all
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xlmr_roberta_base_finetuned_panx_all_ajit_transformer_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xlmr_roberta_base_finetuned_panx_all_ajit_transformer_pipeline_en.md
new file mode 100644
index 00000000000000..c2f265c5120697
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xlmr_roberta_base_finetuned_panx_all_ajit_transformer_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlmr_roberta_base_finetuned_panx_all_ajit_transformer_pipeline pipeline XlmRoBertaForTokenClassification from ajit-transformer
+author: John Snow Labs
+name: xlmr_roberta_base_finetuned_panx_all_ajit_transformer_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmr_roberta_base_finetuned_panx_all_ajit_transformer_pipeline` is a English model originally trained by ajit-transformer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmr_roberta_base_finetuned_panx_all_ajit_transformer_pipeline_en_5.5.1_3.0_1737898222705.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmr_roberta_base_finetuned_panx_all_ajit_transformer_pipeline_en_5.5.1_3.0_1737898222705.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlmr_roberta_base_finetuned_panx_all_ajit_transformer_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmr_roberta_base_finetuned_panx_all_ajit_transformer_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmr_roberta_base_finetuned_panx_all_ajit_transformer_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|837.4 MB|
+
+## References
+
+https://huggingface.co/ajit-transformer/xlmr-roberta-base-finetuned-panx-all
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xtc2_en.md b/docs/_posts/ahmedlone127/2025-01-26-xtc2_en.md
new file mode 100644
index 00000000000000..b2fce39dc7e0e1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xtc2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xtc2 XlmRoBertaForSequenceClassification from iproskurina
+author: John Snow Labs
+name: xtc2
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xtc2` is a English model originally trained by iproskurina.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xtc2_en_5.5.1_3.0_1737885397227.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xtc2_en_5.5.1_3.0_1737885397227.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xtc2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xtc2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xtc2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/iproskurina/xtc2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-xtc2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-xtc2_pipeline_en.md
new file mode 100644
index 00000000000000..2d856f8de42cf4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-xtc2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xtc2_pipeline pipeline XlmRoBertaForSequenceClassification from iproskurina
+author: John Snow Labs
+name: xtc2_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xtc2_pipeline` is a English model originally trained by iproskurina.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xtc2_pipeline_en_5.5.1_3.0_1737885450834.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xtc2_pipeline_en_5.5.1_3.0_1737885450834.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xtc2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xtc2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xtc2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/iproskurina/xtc2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-yelp_classification_distilbert_en.md b/docs/_posts/ahmedlone127/2025-01-26-yelp_classification_distilbert_en.md
new file mode 100644
index 00000000000000..72bca8f8271f15
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-yelp_classification_distilbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English yelp_classification_distilbert DistilBertForSequenceClassification from dfelorza
+author: John Snow Labs
+name: yelp_classification_distilbert
+date: 2025-01-26
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`yelp_classification_distilbert` is a English model originally trained by dfelorza.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/yelp_classification_distilbert_en_5.5.1_3.0_1737873049054.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/yelp_classification_distilbert_en_5.5.1_3.0_1737873049054.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("yelp_classification_distilbert","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("yelp_classification_distilbert", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|yelp_classification_distilbert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/dfelorza/Yelp_classification_distilbert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-yelp_classification_distilbert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-yelp_classification_distilbert_pipeline_en.md
new file mode 100644
index 00000000000000..522c8558bf1462
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-yelp_classification_distilbert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English yelp_classification_distilbert_pipeline pipeline DistilBertForSequenceClassification from dfelorza
+author: John Snow Labs
+name: yelp_classification_distilbert_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`yelp_classification_distilbert_pipeline` is a English model originally trained by dfelorza.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/yelp_classification_distilbert_pipeline_en_5.5.1_3.0_1737873063169.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/yelp_classification_distilbert_pipeline_en_5.5.1_3.0_1737873063169.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("yelp_classification_distilbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("yelp_classification_distilbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|yelp_classification_distilbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/dfelorza/Yelp_classification_distilbert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-yolo_testing_en.md b/docs/_posts/ahmedlone127/2025-01-26-yolo_testing_en.md
new file mode 100644
index 00000000000000..2534edcdca69f1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-yolo_testing_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English yolo_testing SwinForImageClassification from Tushar86
+author: John Snow Labs
+name: yolo_testing
+date: 2025-01-26
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`yolo_testing` is a English model originally trained by Tushar86.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/yolo_testing_en_5.5.1_3.0_1737888765677.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/yolo_testing_en_5.5.1_3.0_1737888765677.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""yolo_testing","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("yolo_testing","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|yolo_testing|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|650.5 MB|
+
+## References
+
+https://huggingface.co/Tushar86/yolo-testing
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-26-yolo_testing_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-26-yolo_testing_pipeline_en.md
new file mode 100644
index 00000000000000..1485344fb13449
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-26-yolo_testing_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English yolo_testing_pipeline pipeline SwinForImageClassification from Tushar86
+author: John Snow Labs
+name: yolo_testing_pipeline
+date: 2025-01-26
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`yolo_testing_pipeline` is a English model originally trained by Tushar86.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/yolo_testing_pipeline_en_5.5.1_3.0_1737888798932.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/yolo_testing_pipeline_en_5.5.1_3.0_1737888798932.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("yolo_testing_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("yolo_testing_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|yolo_testing_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|650.5 MB|
+
+## References
+
+https://huggingface.co/Tushar86/yolo-testing
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-100_butterfly_types_image_detection_en.md b/docs/_posts/ahmedlone127/2025-01-27-100_butterfly_types_image_detection_en.md
new file mode 100644
index 00000000000000..052e64f6b24d65
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-100_butterfly_types_image_detection_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English 100_butterfly_types_image_detection ViTForImageClassification from dima806
+author: John Snow Labs
+name: 100_butterfly_types_image_detection
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`100_butterfly_types_image_detection` is a English model originally trained by dima806.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/100_butterfly_types_image_detection_en_5.5.1_3.0_1737974258400.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/100_butterfly_types_image_detection_en_5.5.1_3.0_1737974258400.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""100_butterfly_types_image_detection","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("100_butterfly_types_image_detection","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|100_butterfly_types_image_detection|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.6 MB|
+
+## References
+
+https://huggingface.co/dima806/100_butterfly_types_image_detection
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-100_butterfly_types_image_detection_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-100_butterfly_types_image_detection_pipeline_en.md
new file mode 100644
index 00000000000000..bcacf1a80e95eb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-100_butterfly_types_image_detection_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English 100_butterfly_types_image_detection_pipeline pipeline ViTForImageClassification from dima806
+author: John Snow Labs
+name: 100_butterfly_types_image_detection_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`100_butterfly_types_image_detection_pipeline` is a English model originally trained by dima806.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/100_butterfly_types_image_detection_pipeline_en_5.5.1_3.0_1737974276455.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/100_butterfly_types_image_detection_pipeline_en_5.5.1_3.0_1737974276455.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("100_butterfly_types_image_detection_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("100_butterfly_types_image_detection_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|100_butterfly_types_image_detection_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.6 MB|
+
+## References
+
+https://huggingface.co/dima806/100_butterfly_types_image_detection
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-10dimensions_similarity_en.md b/docs/_posts/ahmedlone127/2025-01-27-10dimensions_similarity_en.md
new file mode 100644
index 00000000000000..7b923c2cee60b4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-10dimensions_similarity_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English 10dimensions_similarity BertForSequenceClassification from Blablablab
+author: John Snow Labs
+name: 10dimensions_similarity
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`10dimensions_similarity` is a English model originally trained by Blablablab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/10dimensions_similarity_en_5.5.1_3.0_1737950018988.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/10dimensions_similarity_en_5.5.1_3.0_1737950018988.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("10dimensions_similarity","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("10dimensions_similarity", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|10dimensions_similarity|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|405.9 MB|
+
+## References
+
+https://huggingface.co/Blablablab/10dimensions-similarity
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-10dimensions_similarity_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-10dimensions_similarity_pipeline_en.md
new file mode 100644
index 00000000000000..de23c5f8ecd844
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-10dimensions_similarity_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English 10dimensions_similarity_pipeline pipeline BertForSequenceClassification from Blablablab
+author: John Snow Labs
+name: 10dimensions_similarity_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`10dimensions_similarity_pipeline` is a English model originally trained by Blablablab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/10dimensions_similarity_pipeline_en_5.5.1_3.0_1737950039455.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/10dimensions_similarity_pipeline_en_5.5.1_3.0_1737950039455.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("10dimensions_similarity_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("10dimensions_similarity_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|10dimensions_similarity_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|405.9 MB|
+
+## References
+
+https://huggingface.co/Blablablab/10dimensions-similarity
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-133_dog_breeds_image_detection_en.md b/docs/_posts/ahmedlone127/2025-01-27-133_dog_breeds_image_detection_en.md
new file mode 100644
index 00000000000000..d2318b9c548245
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-133_dog_breeds_image_detection_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English 133_dog_breeds_image_detection ViTForImageClassification from dima806
+author: John Snow Labs
+name: 133_dog_breeds_image_detection
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`133_dog_breeds_image_detection` is a English model originally trained by dima806.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/133_dog_breeds_image_detection_en_5.5.1_3.0_1737974273592.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/133_dog_breeds_image_detection_en_5.5.1_3.0_1737974273592.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""133_dog_breeds_image_detection","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("133_dog_breeds_image_detection","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|133_dog_breeds_image_detection|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.7 MB|
+
+## References
+
+https://huggingface.co/dima806/133_dog_breeds_image_detection
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-133_dog_breeds_image_detection_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-133_dog_breeds_image_detection_pipeline_en.md
new file mode 100644
index 00000000000000..331c6f0f8fbd6c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-133_dog_breeds_image_detection_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English 133_dog_breeds_image_detection_pipeline pipeline ViTForImageClassification from dima806
+author: John Snow Labs
+name: 133_dog_breeds_image_detection_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`133_dog_breeds_image_detection_pipeline` is a English model originally trained by dima806.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/133_dog_breeds_image_detection_pipeline_en_5.5.1_3.0_1737974290914.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/133_dog_breeds_image_detection_pipeline_en_5.5.1_3.0_1737974290914.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("133_dog_breeds_image_detection_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("133_dog_breeds_image_detection_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|133_dog_breeds_image_detection_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.7 MB|
+
+## References
+
+https://huggingface.co/dima806/133_dog_breeds_image_detection
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-2020_q2_90p_filtered_en.md b/docs/_posts/ahmedlone127/2025-01-27-2020_q2_90p_filtered_en.md
new file mode 100644
index 00000000000000..cbe470afdaaacc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-2020_q2_90p_filtered_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English 2020_q2_90p_filtered RoBertaEmbeddings from DouglasPontes
+author: John Snow Labs
+name: 2020_q2_90p_filtered
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`2020_q2_90p_filtered` is a English model originally trained by DouglasPontes.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/2020_q2_90p_filtered_en_5.5.1_3.0_1738020163156.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/2020_q2_90p_filtered_en_5.5.1_3.0_1738020163156.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("2020_q2_90p_filtered","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("2020_q2_90p_filtered","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|2020_q2_90p_filtered|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|466.1 MB|
+
+## References
+
+https://huggingface.co/DouglasPontes/2020-Q2-90p-filtered
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-2020_q2_90p_filtered_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-2020_q2_90p_filtered_pipeline_en.md
new file mode 100644
index 00000000000000..fdc71cc5bc2824
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-2020_q2_90p_filtered_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English 2020_q2_90p_filtered_pipeline pipeline RoBertaEmbeddings from DouglasPontes
+author: John Snow Labs
+name: 2020_q2_90p_filtered_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`2020_q2_90p_filtered_pipeline` is a English model originally trained by DouglasPontes.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/2020_q2_90p_filtered_pipeline_en_5.5.1_3.0_1738020186499.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/2020_q2_90p_filtered_pipeline_en_5.5.1_3.0_1738020186499.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("2020_q2_90p_filtered_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("2020_q2_90p_filtered_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|2020_q2_90p_filtered_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.1 MB|
+
+## References
+
+https://huggingface.co/DouglasPontes/2020-Q2-90p-filtered
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-2020_q2_filtered_tweets_tok_prog_en.md b/docs/_posts/ahmedlone127/2025-01-27-2020_q2_filtered_tweets_tok_prog_en.md
new file mode 100644
index 00000000000000..d6734911c52d34
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-2020_q2_filtered_tweets_tok_prog_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English 2020_q2_filtered_tweets_tok_prog RoBertaEmbeddings from DouglasPontes
+author: John Snow Labs
+name: 2020_q2_filtered_tweets_tok_prog
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`2020_q2_filtered_tweets_tok_prog` is a English model originally trained by DouglasPontes.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/2020_q2_filtered_tweets_tok_prog_en_5.5.1_3.0_1737965768594.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/2020_q2_filtered_tweets_tok_prog_en_5.5.1_3.0_1737965768594.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("2020_q2_filtered_tweets_tok_prog","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("2020_q2_filtered_tweets_tok_prog","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|2020_q2_filtered_tweets_tok_prog|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|470.1 MB|
+
+## References
+
+https://huggingface.co/DouglasPontes/2020-Q2-filtered_tweets_tok_prog
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-2020_q2_filtered_tweets_tok_prog_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-2020_q2_filtered_tweets_tok_prog_pipeline_en.md
new file mode 100644
index 00000000000000..974738c508f465
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-2020_q2_filtered_tweets_tok_prog_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English 2020_q2_filtered_tweets_tok_prog_pipeline pipeline RoBertaEmbeddings from DouglasPontes
+author: John Snow Labs
+name: 2020_q2_filtered_tweets_tok_prog_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`2020_q2_filtered_tweets_tok_prog_pipeline` is a English model originally trained by DouglasPontes.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/2020_q2_filtered_tweets_tok_prog_pipeline_en_5.5.1_3.0_1737965792721.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/2020_q2_filtered_tweets_tok_prog_pipeline_en_5.5.1_3.0_1737965792721.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("2020_q2_filtered_tweets_tok_prog_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("2020_q2_filtered_tweets_tok_prog_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|2020_q2_filtered_tweets_tok_prog_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|470.1 MB|
+
+## References
+
+https://huggingface.co/DouglasPontes/2020-Q2-filtered_tweets_tok_prog
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-2020_q3_50p_filtered_en.md b/docs/_posts/ahmedlone127/2025-01-27-2020_q3_50p_filtered_en.md
new file mode 100644
index 00000000000000..2056719df5ecdd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-2020_q3_50p_filtered_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English 2020_q3_50p_filtered RoBertaEmbeddings from DouglasPontes
+author: John Snow Labs
+name: 2020_q3_50p_filtered
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`2020_q3_50p_filtered` is a English model originally trained by DouglasPontes.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/2020_q3_50p_filtered_en_5.5.1_3.0_1737966368457.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/2020_q3_50p_filtered_en_5.5.1_3.0_1737966368457.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("2020_q3_50p_filtered","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("2020_q3_50p_filtered","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|2020_q3_50p_filtered|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|466.1 MB|
+
+## References
+
+https://huggingface.co/DouglasPontes/2020-Q3-50p-filtered
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-2020_q3_50p_filtered_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-2020_q3_50p_filtered_pipeline_en.md
new file mode 100644
index 00000000000000..08cb3750d5ac47
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-2020_q3_50p_filtered_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English 2020_q3_50p_filtered_pipeline pipeline RoBertaEmbeddings from DouglasPontes
+author: John Snow Labs
+name: 2020_q3_50p_filtered_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`2020_q3_50p_filtered_pipeline` is a English model originally trained by DouglasPontes.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/2020_q3_50p_filtered_pipeline_en_5.5.1_3.0_1737966399134.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/2020_q3_50p_filtered_pipeline_en_5.5.1_3.0_1737966399134.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("2020_q3_50p_filtered_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("2020_q3_50p_filtered_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|2020_q3_50p_filtered_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.1 MB|
+
+## References
+
+https://huggingface.co/DouglasPontes/2020-Q3-50p-filtered
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-20k_token_model_en.md b/docs/_posts/ahmedlone127/2025-01-27-20k_token_model_en.md
new file mode 100644
index 00000000000000..320bc5acdfa68d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-20k_token_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English 20k_token_model BertEmbeddings from kumarme072
+author: John Snow Labs
+name: 20k_token_model
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`20k_token_model` is a English model originally trained by kumarme072.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/20k_token_model_en_5.5.1_3.0_1737953533995.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/20k_token_model_en_5.5.1_3.0_1737953533995.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("20k_token_model","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("20k_token_model","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|20k_token_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|409.8 MB|
+
+## References
+
+https://huggingface.co/kumarme072/20k_token_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-20k_token_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-20k_token_model_pipeline_en.md
new file mode 100644
index 00000000000000..ac529242ef1bc7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-20k_token_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English 20k_token_model_pipeline pipeline BertEmbeddings from kumarme072
+author: John Snow Labs
+name: 20k_token_model_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`20k_token_model_pipeline` is a English model originally trained by kumarme072.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/20k_token_model_pipeline_en_5.5.1_3.0_1737953555986.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/20k_token_model_pipeline_en_5.5.1_3.0_1737953555986.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("20k_token_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("20k_token_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|20k_token_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.8 MB|
+
+## References
+
+https://huggingface.co/kumarme072/20k_token_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-adapter_model_en.md b/docs/_posts/ahmedlone127/2025-01-27-adapter_model_en.md
new file mode 100644
index 00000000000000..416e0560922bf5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-adapter_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English adapter_model BertEmbeddings from asalmsk
+author: John Snow Labs
+name: adapter_model
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`adapter_model` is a English model originally trained by asalmsk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/adapter_model_en_5.5.1_3.0_1737985033288.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/adapter_model_en_5.5.1_3.0_1737985033288.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("adapter_model","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("adapter_model","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|adapter_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|624.4 MB|
+
+## References
+
+https://huggingface.co/asalmsk/adapter_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-adapter_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-adapter_model_pipeline_en.md
new file mode 100644
index 00000000000000..8af63531e886c4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-adapter_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English adapter_model_pipeline pipeline BertEmbeddings from asalmsk
+author: John Snow Labs
+name: adapter_model_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`adapter_model_pipeline` is a English model originally trained by asalmsk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/adapter_model_pipeline_en_5.5.1_3.0_1737985064963.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/adapter_model_pipeline_en_5.5.1_3.0_1737985064963.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("adapter_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("adapter_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|adapter_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|624.4 MB|
+
+## References
+
+https://huggingface.co/asalmsk/adapter_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-affilgood_affilroberta_en.md b/docs/_posts/ahmedlone127/2025-01-27-affilgood_affilroberta_en.md
new file mode 100644
index 00000000000000..81b7ca31c81f96
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-affilgood_affilroberta_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English affilgood_affilroberta RoBertaEmbeddings from SIRIS-Lab
+author: John Snow Labs
+name: affilgood_affilroberta
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`affilgood_affilroberta` is a English model originally trained by SIRIS-Lab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/affilgood_affilroberta_en_5.5.1_3.0_1737965662725.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/affilgood_affilroberta_en_5.5.1_3.0_1737965662725.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("affilgood_affilroberta","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("affilgood_affilroberta","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|affilgood_affilroberta|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|466.0 MB|
+
+## References
+
+https://huggingface.co/SIRIS-Lab/affilgood-affilroberta
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-affilgood_affilroberta_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-affilgood_affilroberta_pipeline_en.md
new file mode 100644
index 00000000000000..5a248361767caa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-affilgood_affilroberta_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English affilgood_affilroberta_pipeline pipeline RoBertaEmbeddings from SIRIS-Lab
+author: John Snow Labs
+name: affilgood_affilroberta_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`affilgood_affilroberta_pipeline` is a English model originally trained by SIRIS-Lab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/affilgood_affilroberta_pipeline_en_5.5.1_3.0_1737965686660.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/affilgood_affilroberta_pipeline_en_5.5.1_3.0_1737965686660.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("affilgood_affilroberta_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("affilgood_affilroberta_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|affilgood_affilroberta_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.0 MB|
+
+## References
+
+https://huggingface.co/SIRIS-Lab/affilgood-affilroberta
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-age_classify_v001_en.md b/docs/_posts/ahmedlone127/2025-01-27-age_classify_v001_en.md
new file mode 100644
index 00000000000000..2fccd77b143240
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-age_classify_v001_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English age_classify_v001 ViTForImageClassification from cledoux42
+author: John Snow Labs
+name: age_classify_v001
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`age_classify_v001` is a English model originally trained by cledoux42.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/age_classify_v001_en_5.5.1_3.0_1738021664453.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/age_classify_v001_en_5.5.1_3.0_1738021664453.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""age_classify_v001","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("age_classify_v001","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|age_classify_v001|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/cledoux42/Age_Classify_v001
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-age_classify_v001_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-age_classify_v001_pipeline_en.md
new file mode 100644
index 00000000000000..53037ae48a8119
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-age_classify_v001_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English age_classify_v001_pipeline pipeline ViTForImageClassification from cledoux42
+author: John Snow Labs
+name: age_classify_v001_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`age_classify_v001_pipeline` is a English model originally trained by cledoux42.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/age_classify_v001_pipeline_en_5.5.1_3.0_1738021681223.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/age_classify_v001_pipeline_en_5.5.1_3.0_1738021681223.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("age_classify_v001_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("age_classify_v001_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|age_classify_v001_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.4 MB|
+
+## References
+
+https://huggingface.co/cledoux42/Age_Classify_v001
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-aglm_en.md b/docs/_posts/ahmedlone127/2025-01-27-aglm_en.md
new file mode 100644
index 00000000000000..3156cf113aeb29
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-aglm_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English aglm RoBertaEmbeddings from ongm
+author: John Snow Labs
+name: aglm
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`aglm` is a English model originally trained by ongm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/aglm_en_5.5.1_3.0_1738020152764.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/aglm_en_5.5.1_3.0_1738020152764.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("aglm","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("aglm","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|aglm|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|310.9 MB|
+
+## References
+
+https://huggingface.co/ongm/AGLM
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-aglm_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-aglm_pipeline_en.md
new file mode 100644
index 00000000000000..1d871a65e1e0a6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-aglm_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English aglm_pipeline pipeline RoBertaEmbeddings from ongm
+author: John Snow Labs
+name: aglm_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`aglm_pipeline` is a English model originally trained by ongm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/aglm_pipeline_en_5.5.1_3.0_1738020168391.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/aglm_pipeline_en_5.5.1_3.0_1738020168391.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("aglm_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("aglm_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|aglm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|311.0 MB|
+
+## References
+
+https://huggingface.co/ongm/AGLM
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-ai_reminder_model_en.md b/docs/_posts/ahmedlone127/2025-01-27-ai_reminder_model_en.md
new file mode 100644
index 00000000000000..8e9dc77b7abd80
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-ai_reminder_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ai_reminder_model DistilBertForTokenClassification from syaha
+author: John Snow Labs
+name: ai_reminder_model
+date: 2025-01-27
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ai_reminder_model` is a English model originally trained by syaha.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ai_reminder_model_en_5.5.1_3.0_1737988474008.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ai_reminder_model_en_5.5.1_3.0_1737988474008.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("ai_reminder_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("ai_reminder_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ai_reminder_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/syaha/ai-reminder-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-ai_reminder_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-ai_reminder_model_pipeline_en.md
new file mode 100644
index 00000000000000..f51261c44cb468
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-ai_reminder_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ai_reminder_model_pipeline pipeline DistilBertForTokenClassification from syaha
+author: John Snow Labs
+name: ai_reminder_model_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ai_reminder_model_pipeline` is a English model originally trained by syaha.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ai_reminder_model_pipeline_en_5.5.1_3.0_1737988488450.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ai_reminder_model_pipeline_en_5.5.1_3.0_1737988488450.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ai_reminder_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ai_reminder_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ai_reminder_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/syaha/ai-reminder-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-albert_twitter_sentiment_en.md b/docs/_posts/ahmedlone127/2025-01-27-albert_twitter_sentiment_en.md
new file mode 100644
index 00000000000000..6efbc0f782a176
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-albert_twitter_sentiment_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English albert_twitter_sentiment AlbertForSequenceClassification from halvion
+author: John Snow Labs
+name: albert_twitter_sentiment
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, albert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_twitter_sentiment` is a English model originally trained by halvion.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_twitter_sentiment_en_5.5.1_3.0_1737988738139.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_twitter_sentiment_en_5.5.1_3.0_1737988738139.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = AlbertForSequenceClassification.pretrained("albert_twitter_sentiment","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = AlbertForSequenceClassification.pretrained("albert_twitter_sentiment", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_twitter_sentiment|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/halvion/albert-twitter-sentiment
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-albert_twitter_sentiment_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-albert_twitter_sentiment_pipeline_en.md
new file mode 100644
index 00000000000000..0bf668fb77e2f6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-albert_twitter_sentiment_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English albert_twitter_sentiment_pipeline pipeline AlbertForSequenceClassification from halvion
+author: John Snow Labs
+name: albert_twitter_sentiment_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_twitter_sentiment_pipeline` is a English model originally trained by halvion.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_twitter_sentiment_pipeline_en_5.5.1_3.0_1737988740428.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_twitter_sentiment_pipeline_en_5.5.1_3.0_1737988740428.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("albert_twitter_sentiment_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("albert_twitter_sentiment_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_twitter_sentiment_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/halvion/albert-twitter-sentiment
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-all_minilm_l6_v2_personal_project_default_2024_06_05_en.md b/docs/_posts/ahmedlone127/2025-01-27-all_minilm_l6_v2_personal_project_default_2024_06_05_en.md
new file mode 100644
index 00000000000000..8385e8a8c0f96f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-all_minilm_l6_v2_personal_project_default_2024_06_05_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English all_minilm_l6_v2_personal_project_default_2024_06_05 BertEmbeddings from brugmark
+author: John Snow Labs
+name: all_minilm_l6_v2_personal_project_default_2024_06_05
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_minilm_l6_v2_personal_project_default_2024_06_05` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_default_2024_06_05_en_5.5.1_3.0_1737954075958.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_default_2024_06_05_en_5.5.1_3.0_1737954075958.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("all_minilm_l6_v2_personal_project_default_2024_06_05","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("all_minilm_l6_v2_personal_project_default_2024_06_05","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_minilm_l6_v2_personal_project_default_2024_06_05|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|83.9 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-default-2024-06-05
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-all_minilm_l6_v2_personal_project_default_2024_06_05_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-all_minilm_l6_v2_personal_project_default_2024_06_05_pipeline_en.md
new file mode 100644
index 00000000000000..6868383ea74596
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-all_minilm_l6_v2_personal_project_default_2024_06_05_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English all_minilm_l6_v2_personal_project_default_2024_06_05_pipeline pipeline BertEmbeddings from brugmark
+author: John Snow Labs
+name: all_minilm_l6_v2_personal_project_default_2024_06_05_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_minilm_l6_v2_personal_project_default_2024_06_05_pipeline` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_default_2024_06_05_pipeline_en_5.5.1_3.0_1737954080378.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_default_2024_06_05_pipeline_en_5.5.1_3.0_1737954080378.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("all_minilm_l6_v2_personal_project_default_2024_06_05_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("all_minilm_l6_v2_personal_project_default_2024_06_05_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_minilm_l6_v2_personal_project_default_2024_06_05_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|83.9 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-default-2024-06-05
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-all_minilm_l6_v2_personal_project_finetuned_2024_03_22_en.md b/docs/_posts/ahmedlone127/2025-01-27-all_minilm_l6_v2_personal_project_finetuned_2024_03_22_en.md
new file mode 100644
index 00000000000000..21b9445463d746
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-all_minilm_l6_v2_personal_project_finetuned_2024_03_22_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English all_minilm_l6_v2_personal_project_finetuned_2024_03_22 BertEmbeddings from brugmark
+author: John Snow Labs
+name: all_minilm_l6_v2_personal_project_finetuned_2024_03_22
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_minilm_l6_v2_personal_project_finetuned_2024_03_22` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_finetuned_2024_03_22_en_5.5.1_3.0_1737954231492.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_finetuned_2024_03_22_en_5.5.1_3.0_1737954231492.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("all_minilm_l6_v2_personal_project_finetuned_2024_03_22","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("all_minilm_l6_v2_personal_project_finetuned_2024_03_22","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_minilm_l6_v2_personal_project_finetuned_2024_03_22|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|84.6 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-finetuned-2024-03-22
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-all_minilm_l6_v2_personal_project_finetuned_2024_03_22_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-all_minilm_l6_v2_personal_project_finetuned_2024_03_22_pipeline_en.md
new file mode 100644
index 00000000000000..4e20e3fe469972
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-all_minilm_l6_v2_personal_project_finetuned_2024_03_22_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English all_minilm_l6_v2_personal_project_finetuned_2024_03_22_pipeline pipeline BertEmbeddings from brugmark
+author: John Snow Labs
+name: all_minilm_l6_v2_personal_project_finetuned_2024_03_22_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_minilm_l6_v2_personal_project_finetuned_2024_03_22_pipeline` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_finetuned_2024_03_22_pipeline_en_5.5.1_3.0_1737954235694.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_finetuned_2024_03_22_pipeline_en_5.5.1_3.0_1737954235694.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("all_minilm_l6_v2_personal_project_finetuned_2024_03_22_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("all_minilm_l6_v2_personal_project_finetuned_2024_03_22_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_minilm_l6_v2_personal_project_finetuned_2024_03_22_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|84.6 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-finetuned-2024-03-22
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-alzheimer_vit_classifier_en.md b/docs/_posts/ahmedlone127/2025-01-27-alzheimer_vit_classifier_en.md
new file mode 100644
index 00000000000000..d17e31e29fd079
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-alzheimer_vit_classifier_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English alzheimer_vit_classifier ViTForImageClassification from skshmjn
+author: John Snow Labs
+name: alzheimer_vit_classifier
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`alzheimer_vit_classifier` is a English model originally trained by skshmjn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/alzheimer_vit_classifier_en_5.5.1_3.0_1738021693892.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/alzheimer_vit_classifier_en_5.5.1_3.0_1738021693892.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""alzheimer_vit_classifier","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("alzheimer_vit_classifier","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|alzheimer_vit_classifier|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/skshmjn/Alzheimer-vit-classifier
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-alzheimer_vit_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-alzheimer_vit_classifier_pipeline_en.md
new file mode 100644
index 00000000000000..2de8bc778de9c4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-alzheimer_vit_classifier_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English alzheimer_vit_classifier_pipeline pipeline ViTForImageClassification from skshmjn
+author: John Snow Labs
+name: alzheimer_vit_classifier_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`alzheimer_vit_classifier_pipeline` is a English model originally trained by skshmjn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/alzheimer_vit_classifier_pipeline_en_5.5.1_3.0_1738021709963.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/alzheimer_vit_classifier_pipeline_en_5.5.1_3.0_1738021709963.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("alzheimer_vit_classifier_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("alzheimer_vit_classifier_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|alzheimer_vit_classifier_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/skshmjn/Alzheimer-vit-classifier
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-ameertelbani_en.md b/docs/_posts/ahmedlone127/2025-01-27-ameertelbani_en.md
new file mode 100644
index 00000000000000..eeaed67b425fb1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-ameertelbani_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ameertelbani ViTForImageClassification from ameerTelbani
+author: John Snow Labs
+name: ameertelbani
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ameertelbani` is a English model originally trained by ameerTelbani.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ameertelbani_en_5.5.1_3.0_1737974183492.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ameertelbani_en_5.5.1_3.0_1737974183492.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""ameertelbani","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("ameertelbani","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ameertelbani|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/ameerTelbani/ameerTelbani
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-ameertelbani_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-ameertelbani_pipeline_en.md
new file mode 100644
index 00000000000000..57b1803dce2986
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-ameertelbani_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English ameertelbani_pipeline pipeline ViTForImageClassification from ameerTelbani
+author: John Snow Labs
+name: ameertelbani_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ameertelbani_pipeline` is a English model originally trained by ameerTelbani.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ameertelbani_pipeline_en_5.5.1_3.0_1737974240697.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ameertelbani_pipeline_en_5.5.1_3.0_1737974240697.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ameertelbani_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ameertelbani_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ameertelbani_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/ameerTelbani/ameerTelbani
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-amharicnewsnoncleanednonweighted_en.md b/docs/_posts/ahmedlone127/2025-01-27-amharicnewsnoncleanednonweighted_en.md
new file mode 100644
index 00000000000000..4025bc3f1e3465
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-amharicnewsnoncleanednonweighted_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English amharicnewsnoncleanednonweighted XlmRoBertaForSequenceClassification from akiseid
+author: John Snow Labs
+name: amharicnewsnoncleanednonweighted
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`amharicnewsnoncleanednonweighted` is a English model originally trained by akiseid.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/amharicnewsnoncleanednonweighted_en_5.5.1_3.0_1737959598088.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/amharicnewsnoncleanednonweighted_en_5.5.1_3.0_1737959598088.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("amharicnewsnoncleanednonweighted","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("amharicnewsnoncleanednonweighted", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|amharicnewsnoncleanednonweighted|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|840.7 MB|
+
+## References
+
+https://huggingface.co/akiseid/AmharicNewsNonCleanedNonWeighted
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-amharicnewsnoncleanednonweighted_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-amharicnewsnoncleanednonweighted_pipeline_en.md
new file mode 100644
index 00000000000000..d5b880da7018c2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-amharicnewsnoncleanednonweighted_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English amharicnewsnoncleanednonweighted_pipeline pipeline XlmRoBertaForSequenceClassification from akiseid
+author: John Snow Labs
+name: amharicnewsnoncleanednonweighted_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`amharicnewsnoncleanednonweighted_pipeline` is a English model originally trained by akiseid.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/amharicnewsnoncleanednonweighted_pipeline_en_5.5.1_3.0_1737959681833.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/amharicnewsnoncleanednonweighted_pipeline_en_5.5.1_3.0_1737959681833.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("amharicnewsnoncleanednonweighted_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("amharicnewsnoncleanednonweighted_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|amharicnewsnoncleanednonweighted_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/akiseid/AmharicNewsNonCleanedNonWeighted
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-angmodel_finetune_3_finalversion_en.md b/docs/_posts/ahmedlone127/2025-01-27-angmodel_finetune_3_finalversion_en.md
new file mode 100644
index 00000000000000..e27d9e121cb212
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-angmodel_finetune_3_finalversion_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English angmodel_finetune_3_finalversion XlmRoBertaForSequenceClassification from chengeorge
+author: John Snow Labs
+name: angmodel_finetune_3_finalversion
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`angmodel_finetune_3_finalversion` is a English model originally trained by chengeorge.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/angmodel_finetune_3_finalversion_en_5.5.1_3.0_1737960021542.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/angmodel_finetune_3_finalversion_en_5.5.1_3.0_1737960021542.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("angmodel_finetune_3_finalversion","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("angmodel_finetune_3_finalversion", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|angmodel_finetune_3_finalversion|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/chengeorge/AngModel_Finetune_3_FinalVersion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-angmodel_finetune_3_finalversion_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-angmodel_finetune_3_finalversion_pipeline_en.md
new file mode 100644
index 00000000000000..be2f118156513d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-angmodel_finetune_3_finalversion_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English angmodel_finetune_3_finalversion_pipeline pipeline XlmRoBertaForSequenceClassification from chengeorge
+author: John Snow Labs
+name: angmodel_finetune_3_finalversion_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`angmodel_finetune_3_finalversion_pipeline` is a English model originally trained by chengeorge.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/angmodel_finetune_3_finalversion_pipeline_en_5.5.1_3.0_1737960073932.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/angmodel_finetune_3_finalversion_pipeline_en_5.5.1_3.0_1737960073932.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("angmodel_finetune_3_finalversion_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("angmodel_finetune_3_finalversion_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|angmodel_finetune_3_finalversion_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/chengeorge/AngModel_Finetune_3_FinalVersion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-aphasia_t5_normalization_en.md b/docs/_posts/ahmedlone127/2025-01-27-aphasia_t5_normalization_en.md
new file mode 100644
index 00000000000000..0330eb8a5ec26b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-aphasia_t5_normalization_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English aphasia_t5_normalization T5Transformer from LeifsterNYC
+author: John Snow Labs
+name: aphasia_t5_normalization
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`aphasia_t5_normalization` is a English model originally trained by LeifsterNYC.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/aphasia_t5_normalization_en_5.5.1_3.0_1737946079528.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/aphasia_t5_normalization_en_5.5.1_3.0_1737946079528.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("aphasia_t5_normalization","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("aphasia_t5_normalization", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|aphasia_t5_normalization|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|279.5 MB|
+
+## References
+
+https://huggingface.co/LeifsterNYC/aphasia-t5-normalization
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-aphasia_t5_normalization_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-aphasia_t5_normalization_pipeline_en.md
new file mode 100644
index 00000000000000..cccd625027700c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-aphasia_t5_normalization_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English aphasia_t5_normalization_pipeline pipeline T5Transformer from LeifsterNYC
+author: John Snow Labs
+name: aphasia_t5_normalization_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`aphasia_t5_normalization_pipeline` is a English model originally trained by LeifsterNYC.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/aphasia_t5_normalization_pipeline_en_5.5.1_3.0_1737946095954.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/aphasia_t5_normalization_pipeline_en_5.5.1_3.0_1737946095954.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("aphasia_t5_normalization_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("aphasia_t5_normalization_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|aphasia_t5_normalization_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|279.5 MB|
+
+## References
+
+https://huggingface.co/LeifsterNYC/aphasia-t5-normalization
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-ares_bart_cnn_en.md b/docs/_posts/ahmedlone127/2025-01-27-ares_bart_cnn_en.md
new file mode 100644
index 00000000000000..37b8a1b1575e39
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-ares_bart_cnn_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English ares_bart_cnn BartTransformer from prithivMLmods
+author: John Snow Labs
+name: ares_bart_cnn
+date: 2025-01-27
+tags: [en, open_source, onnx, text_generation, bart]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BartTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ares_bart_cnn` is a English model originally trained by prithivMLmods.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ares_bart_cnn_en_5.5.1_3.0_1737987569441.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ares_bart_cnn_en_5.5.1_3.0_1737987569441.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = BartTransformer.pretrained("ares_bart_cnn","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = BartTransformer.pretrained("ares_bart_cnn","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ares_bart_cnn|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/prithivMLmods/Ares-Bart-Cnn
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-ares_bart_cnn_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-ares_bart_cnn_pipeline_en.md
new file mode 100644
index 00000000000000..23b8be1cb7ae77
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-ares_bart_cnn_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English ares_bart_cnn_pipeline pipeline BartTransformer from prithivMLmods
+author: John Snow Labs
+name: ares_bart_cnn_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ares_bart_cnn_pipeline` is a English model originally trained by prithivMLmods.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ares_bart_cnn_pipeline_en_5.5.1_3.0_1737987906712.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ares_bart_cnn_pipeline_en_5.5.1_3.0_1737987906712.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ares_bart_cnn_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ares_bart_cnn_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ares_bart_cnn_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/prithivMLmods/Ares-Bart-Cnn
+
+## Included Models
+
+- DocumentAssembler
+- BartTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-arwen_gpt2_medium_x21_en.md b/docs/_posts/ahmedlone127/2025-01-27-arwen_gpt2_medium_x21_en.md
new file mode 100644
index 00000000000000..8e7200ca9ab545
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-arwen_gpt2_medium_x21_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English arwen_gpt2_medium_x21 GPT2Transformer from stanford-crfm
+author: John Snow Labs
+name: arwen_gpt2_medium_x21
+date: 2025-01-27
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`arwen_gpt2_medium_x21` is a English model originally trained by stanford-crfm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/arwen_gpt2_medium_x21_en_5.5.1_3.0_1737995271901.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/arwen_gpt2_medium_x21_en_5.5.1_3.0_1737995271901.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("arwen_gpt2_medium_x21","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("arwen_gpt2_medium_x21","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|arwen_gpt2_medium_x21|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|852.4 MB|
+
+## References
+
+https://huggingface.co/stanford-crfm/arwen-gpt2-medium-x21
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-arwen_gpt2_medium_x21_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-arwen_gpt2_medium_x21_pipeline_en.md
new file mode 100644
index 00000000000000..3d1bb38765424b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-arwen_gpt2_medium_x21_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English arwen_gpt2_medium_x21_pipeline pipeline GPT2Transformer from stanford-crfm
+author: John Snow Labs
+name: arwen_gpt2_medium_x21_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`arwen_gpt2_medium_x21_pipeline` is a English model originally trained by stanford-crfm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/arwen_gpt2_medium_x21_pipeline_en_5.5.1_3.0_1737995514058.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/arwen_gpt2_medium_x21_pipeline_en_5.5.1_3.0_1737995514058.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("arwen_gpt2_medium_x21_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("arwen_gpt2_medium_x21_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|arwen_gpt2_medium_x21_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|852.4 MB|
+
+## References
+
+https://huggingface.co/stanford-crfm/arwen-gpt2-medium-x21
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-asl_translation_model_en.md b/docs/_posts/ahmedlone127/2025-01-27-asl_translation_model_en.md
new file mode 100644
index 00000000000000..24b27a554e622e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-asl_translation_model_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English asl_translation_model T5Transformer from elpeeee
+author: John Snow Labs
+name: asl_translation_model
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asl_translation_model` is a English model originally trained by elpeeee.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asl_translation_model_en_5.5.1_3.0_1737978179434.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asl_translation_model_en_5.5.1_3.0_1737978179434.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("asl_translation_model","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("asl_translation_model", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|asl_translation_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|285.8 MB|
+
+## References
+
+https://huggingface.co/elpeeee/asl_translation_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-asl_translation_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-asl_translation_model_pipeline_en.md
new file mode 100644
index 00000000000000..29eb0b190d534a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-asl_translation_model_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English asl_translation_model_pipeline pipeline T5Transformer from elpeeee
+author: John Snow Labs
+name: asl_translation_model_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asl_translation_model_pipeline` is a English model originally trained by elpeeee.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asl_translation_model_pipeline_en_5.5.1_3.0_1737978194736.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asl_translation_model_pipeline_en_5.5.1_3.0_1737978194736.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("asl_translation_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("asl_translation_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|asl_translation_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|285.8 MB|
+
+## References
+
+https://huggingface.co/elpeeee/asl_translation_model
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-asl_vit_en.md b/docs/_posts/ahmedlone127/2025-01-27-asl_vit_en.md
new file mode 100644
index 00000000000000..c250229cae9d11
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-asl_vit_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English asl_vit ViTForImageClassification from akahana
+author: John Snow Labs
+name: asl_vit
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asl_vit` is a English model originally trained by akahana.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asl_vit_en_5.5.1_3.0_1738022271832.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asl_vit_en_5.5.1_3.0_1738022271832.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""asl_vit","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("asl_vit","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|asl_vit|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.4 MB|
+
+## References
+
+https://huggingface.co/akahana/asl-vit
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-asl_vit_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-asl_vit_pipeline_en.md
new file mode 100644
index 00000000000000..cb3a17a037fc02
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-asl_vit_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English asl_vit_pipeline pipeline ViTForImageClassification from akahana
+author: John Snow Labs
+name: asl_vit_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asl_vit_pipeline` is a English model originally trained by akahana.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asl_vit_pipeline_en_5.5.1_3.0_1738022287856.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asl_vit_pipeline_en_5.5.1_3.0_1738022287856.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("asl_vit_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("asl_vit_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|asl_vit_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.4 MB|
+
+## References
+
+https://huggingface.co/akahana/asl-vit
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-atharvakanchan_en.md b/docs/_posts/ahmedlone127/2025-01-27-atharvakanchan_en.md
new file mode 100644
index 00000000000000..c95ba8535804de
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-atharvakanchan_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English atharvakanchan T5Transformer from atharvakanchan
+author: John Snow Labs
+name: atharvakanchan
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`atharvakanchan` is a English model originally trained by atharvakanchan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/atharvakanchan_en_5.5.1_3.0_1737991934391.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/atharvakanchan_en_5.5.1_3.0_1737991934391.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("atharvakanchan","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("atharvakanchan", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|atharvakanchan|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|148.0 MB|
+
+## References
+
+https://huggingface.co/atharvakanchan/atharvakanchan
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-atharvakanchan_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-atharvakanchan_pipeline_en.md
new file mode 100644
index 00000000000000..f895f750c5b2b2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-atharvakanchan_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English atharvakanchan_pipeline pipeline T5Transformer from atharvakanchan
+author: John Snow Labs
+name: atharvakanchan_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`atharvakanchan_pipeline` is a English model originally trained by atharvakanchan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/atharvakanchan_pipeline_en_5.5.1_3.0_1737991982636.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/atharvakanchan_pipeline_en_5.5.1_3.0_1737991982636.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("atharvakanchan_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("atharvakanchan_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|atharvakanchan_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|148.0 MB|
+
+## References
+
+https://huggingface.co/atharvakanchan/atharvakanchan
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-atharvakanchane_en.md b/docs/_posts/ahmedlone127/2025-01-27-atharvakanchane_en.md
new file mode 100644
index 00000000000000..b89c541bae3472
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-atharvakanchane_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English atharvakanchane T5Transformer from atharvakanchan
+author: John Snow Labs
+name: atharvakanchane
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`atharvakanchane` is a English model originally trained by atharvakanchan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/atharvakanchane_en_5.5.1_3.0_1737963665509.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/atharvakanchane_en_5.5.1_3.0_1737963665509.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("atharvakanchane","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("atharvakanchane", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|atharvakanchane|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|148.0 MB|
+
+## References
+
+https://huggingface.co/atharvakanchan/atharvakanchane
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-atharvakanchane_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-atharvakanchane_pipeline_en.md
new file mode 100644
index 00000000000000..97648fc669e477
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-atharvakanchane_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English atharvakanchane_pipeline pipeline T5Transformer from atharvakanchan
+author: John Snow Labs
+name: atharvakanchane_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`atharvakanchane_pipeline` is a English model originally trained by atharvakanchan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/atharvakanchane_pipeline_en_5.5.1_3.0_1737963712984.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/atharvakanchane_pipeline_en_5.5.1_3.0_1737963712984.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("atharvakanchane_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("atharvakanchane_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|atharvakanchane_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|148.0 MB|
+
+## References
+
+https://huggingface.co/atharvakanchan/atharvakanchane
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-attractive_faces_celebs_detection_en.md b/docs/_posts/ahmedlone127/2025-01-27-attractive_faces_celebs_detection_en.md
new file mode 100644
index 00000000000000..8769857dc5cb4c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-attractive_faces_celebs_detection_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English attractive_faces_celebs_detection ViTForImageClassification from dima806
+author: John Snow Labs
+name: attractive_faces_celebs_detection
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`attractive_faces_celebs_detection` is a English model originally trained by dima806.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/attractive_faces_celebs_detection_en_5.5.1_3.0_1737974819008.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/attractive_faces_celebs_detection_en_5.5.1_3.0_1737974819008.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""attractive_faces_celebs_detection","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("attractive_faces_celebs_detection","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|attractive_faces_celebs_detection|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/dima806/attractive_faces_celebs_detection
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-attractive_faces_celebs_detection_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-attractive_faces_celebs_detection_pipeline_en.md
new file mode 100644
index 00000000000000..405ef55c8a075e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-attractive_faces_celebs_detection_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English attractive_faces_celebs_detection_pipeline pipeline ViTForImageClassification from dima806
+author: John Snow Labs
+name: attractive_faces_celebs_detection_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`attractive_faces_celebs_detection_pipeline` is a English model originally trained by dima806.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/attractive_faces_celebs_detection_pipeline_en_5.5.1_3.0_1737974835951.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/attractive_faces_celebs_detection_pipeline_en_5.5.1_3.0_1737974835951.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("attractive_faces_celebs_detection_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("attractive_faces_celebs_detection_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|attractive_faces_celebs_detection_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/dima806/attractive_faces_celebs_detection
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-augmented_model_fast_2_en.md b/docs/_posts/ahmedlone127/2025-01-27-augmented_model_fast_2_en.md
new file mode 100644
index 00000000000000..e832048ef737c2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-augmented_model_fast_2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English augmented_model_fast_2 DistilBertForSequenceClassification from LeonardoFettucciari
+author: John Snow Labs
+name: augmented_model_fast_2
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`augmented_model_fast_2` is a English model originally trained by LeonardoFettucciari.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/augmented_model_fast_2_en_5.5.1_3.0_1737939672894.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/augmented_model_fast_2_en_5.5.1_3.0_1737939672894.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("augmented_model_fast_2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("augmented_model_fast_2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|augmented_model_fast_2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/LeonardoFettucciari/augmented_model_fast_2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-augmented_model_fast_2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-augmented_model_fast_2_pipeline_en.md
new file mode 100644
index 00000000000000..9358748139cc7e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-augmented_model_fast_2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English augmented_model_fast_2_pipeline pipeline DistilBertForSequenceClassification from LeonardoFettucciari
+author: John Snow Labs
+name: augmented_model_fast_2_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`augmented_model_fast_2_pipeline` is a English model originally trained by LeonardoFettucciari.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/augmented_model_fast_2_pipeline_en_5.5.1_3.0_1737939686707.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/augmented_model_fast_2_pipeline_en_5.5.1_3.0_1737939686707.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("augmented_model_fast_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("augmented_model_fast_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|augmented_model_fast_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/LeonardoFettucciari/augmented_model_fast_2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-augmented_model_one_norwegian_decay_en.md b/docs/_posts/ahmedlone127/2025-01-27-augmented_model_one_norwegian_decay_en.md
new file mode 100644
index 00000000000000..a060125f0f203a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-augmented_model_one_norwegian_decay_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English augmented_model_one_norwegian_decay DistilBertForSequenceClassification from LeonardoFettucciari
+author: John Snow Labs
+name: augmented_model_one_norwegian_decay
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`augmented_model_one_norwegian_decay` is a English model originally trained by LeonardoFettucciari.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/augmented_model_one_norwegian_decay_en_5.5.1_3.0_1737939947035.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/augmented_model_one_norwegian_decay_en_5.5.1_3.0_1737939947035.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("augmented_model_one_norwegian_decay","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("augmented_model_one_norwegian_decay", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|augmented_model_one_norwegian_decay|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/LeonardoFettucciari/augmented_model_one_no_decay
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-augmented_model_one_norwegian_decay_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-augmented_model_one_norwegian_decay_pipeline_en.md
new file mode 100644
index 00000000000000..ecd4b83bbce3e6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-augmented_model_one_norwegian_decay_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English augmented_model_one_norwegian_decay_pipeline pipeline DistilBertForSequenceClassification from LeonardoFettucciari
+author: John Snow Labs
+name: augmented_model_one_norwegian_decay_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`augmented_model_one_norwegian_decay_pipeline` is a English model originally trained by LeonardoFettucciari.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/augmented_model_one_norwegian_decay_pipeline_en_5.5.1_3.0_1737939960690.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/augmented_model_one_norwegian_decay_pipeline_en_5.5.1_3.0_1737939960690.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("augmented_model_one_norwegian_decay_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("augmented_model_one_norwegian_decay_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|augmented_model_one_norwegian_decay_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/LeonardoFettucciari/augmented_model_one_no_decay
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-autotrain_93gqy_z1clf_jmstadt_en.md b/docs/_posts/ahmedlone127/2025-01-27-autotrain_93gqy_z1clf_jmstadt_en.md
new file mode 100644
index 00000000000000..720a882e14ba20
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-autotrain_93gqy_z1clf_jmstadt_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English autotrain_93gqy_z1clf_jmstadt T5Transformer from jmstadt
+author: John Snow Labs
+name: autotrain_93gqy_z1clf_jmstadt
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_93gqy_z1clf_jmstadt` is a English model originally trained by jmstadt.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_93gqy_z1clf_jmstadt_en_5.5.1_3.0_1738000456011.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_93gqy_z1clf_jmstadt_en_5.5.1_3.0_1738000456011.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("autotrain_93gqy_z1clf_jmstadt","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("autotrain_93gqy_z1clf_jmstadt", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_93gqy_z1clf_jmstadt|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|275.9 MB|
+
+## References
+
+https://huggingface.co/jmstadt/autotrain-93gqy-z1clf
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-autotrain_93gqy_z1clf_jmstadt_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-autotrain_93gqy_z1clf_jmstadt_pipeline_en.md
new file mode 100644
index 00000000000000..fc276dbc54a480
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-autotrain_93gqy_z1clf_jmstadt_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English autotrain_93gqy_z1clf_jmstadt_pipeline pipeline T5Transformer from jmstadt
+author: John Snow Labs
+name: autotrain_93gqy_z1clf_jmstadt_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_93gqy_z1clf_jmstadt_pipeline` is a English model originally trained by jmstadt.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_93gqy_z1clf_jmstadt_pipeline_en_5.5.1_3.0_1738000480470.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_93gqy_z1clf_jmstadt_pipeline_en_5.5.1_3.0_1738000480470.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("autotrain_93gqy_z1clf_jmstadt_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("autotrain_93gqy_z1clf_jmstadt_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_93gqy_z1clf_jmstadt_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|275.9 MB|
+
+## References
+
+https://huggingface.co/jmstadt/autotrain-93gqy-z1clf
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-avarbert_en.md b/docs/_posts/ahmedlone127/2025-01-27-avarbert_en.md
new file mode 100644
index 00000000000000..589fd84fcd5584
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-avarbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English avarbert RoBertaEmbeddings from VolinaMA
+author: John Snow Labs
+name: avarbert
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`avarbert` is a English model originally trained by VolinaMA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/avarbert_en_5.5.1_3.0_1738020393150.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/avarbert_en_5.5.1_3.0_1738020393150.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("avarbert","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("avarbert","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|avarbert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|306.7 MB|
+
+## References
+
+https://huggingface.co/VolinaMA/avarBERT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-avarbert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-avarbert_pipeline_en.md
new file mode 100644
index 00000000000000..7583a5e839bb1a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-avarbert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English avarbert_pipeline pipeline RoBertaEmbeddings from VolinaMA
+author: John Snow Labs
+name: avarbert_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`avarbert_pipeline` is a English model originally trained by VolinaMA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/avarbert_pipeline_en_5.5.1_3.0_1738020409041.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/avarbert_pipeline_en_5.5.1_3.0_1738020409041.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("avarbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("avarbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|avarbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|306.7 MB|
+
+## References
+
+https://huggingface.co/VolinaMA/avarBERT
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-b_ai_fine_tuned_flan_t5_en.md b/docs/_posts/ahmedlone127/2025-01-27-b_ai_fine_tuned_flan_t5_en.md
new file mode 100644
index 00000000000000..ae93167647e5bc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-b_ai_fine_tuned_flan_t5_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English b_ai_fine_tuned_flan_t5 T5Transformer from binhnt20010408
+author: John Snow Labs
+name: b_ai_fine_tuned_flan_t5
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`b_ai_fine_tuned_flan_t5` is a English model originally trained by binhnt20010408.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/b_ai_fine_tuned_flan_t5_en_5.5.1_3.0_1738000062889.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/b_ai_fine_tuned_flan_t5_en_5.5.1_3.0_1738000062889.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("b_ai_fine_tuned_flan_t5","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("b_ai_fine_tuned_flan_t5", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|b_ai_fine_tuned_flan_t5|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/binhnt20010408/b-ai-fine-tuned-flan-t5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-b_ai_fine_tuned_flan_t5_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-b_ai_fine_tuned_flan_t5_pipeline_en.md
new file mode 100644
index 00000000000000..862eb47d1ae59d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-b_ai_fine_tuned_flan_t5_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English b_ai_fine_tuned_flan_t5_pipeline pipeline T5Transformer from binhnt20010408
+author: John Snow Labs
+name: b_ai_fine_tuned_flan_t5_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`b_ai_fine_tuned_flan_t5_pipeline` is a English model originally trained by binhnt20010408.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/b_ai_fine_tuned_flan_t5_pipeline_en_5.5.1_3.0_1738000116112.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/b_ai_fine_tuned_flan_t5_pipeline_en_5.5.1_3.0_1738000116112.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("b_ai_fine_tuned_flan_t5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("b_ai_fine_tuned_flan_t5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|b_ai_fine_tuned_flan_t5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/binhnt20010408/b-ai-fine-tuned-flan-t5
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-babylm_student_gpt2_3_en.md b/docs/_posts/ahmedlone127/2025-01-27-babylm_student_gpt2_3_en.md
new file mode 100644
index 00000000000000..aea8ec541f0096
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-babylm_student_gpt2_3_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English babylm_student_gpt2_3 GPT2Transformer from momergul
+author: John Snow Labs
+name: babylm_student_gpt2_3
+date: 2025-01-27
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`babylm_student_gpt2_3` is a English model originally trained by momergul.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/babylm_student_gpt2_3_en_5.5.1_3.0_1737997454540.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/babylm_student_gpt2_3_en_5.5.1_3.0_1737997454540.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("babylm_student_gpt2_3","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("babylm_student_gpt2_3","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|babylm_student_gpt2_3|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.5 MB|
+
+## References
+
+https://huggingface.co/momergul/babylm-student-gpt2-3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-babylm_student_gpt2_3_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-babylm_student_gpt2_3_pipeline_en.md
new file mode 100644
index 00000000000000..36428bd6e44466
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-babylm_student_gpt2_3_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English babylm_student_gpt2_3_pipeline pipeline GPT2Transformer from momergul
+author: John Snow Labs
+name: babylm_student_gpt2_3_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`babylm_student_gpt2_3_pipeline` is a English model originally trained by momergul.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/babylm_student_gpt2_3_pipeline_en_5.5.1_3.0_1737997479144.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/babylm_student_gpt2_3_pipeline_en_5.5.1_3.0_1737997479144.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("babylm_student_gpt2_3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("babylm_student_gpt2_3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|babylm_student_gpt2_3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.6 MB|
+
+## References
+
+https://huggingface.co/momergul/babylm-student-gpt2-3
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-bacrizzler_en.md b/docs/_posts/ahmedlone127/2025-01-27-bacrizzler_en.md
new file mode 100644
index 00000000000000..0c59dbb022fd27
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-bacrizzler_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bacrizzler T5Transformer from aidanzhou
+author: John Snow Labs
+name: bacrizzler
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bacrizzler` is a English model originally trained by aidanzhou.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bacrizzler_en_5.5.1_3.0_1738007552111.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bacrizzler_en_5.5.1_3.0_1738007552111.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("bacrizzler","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("bacrizzler", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bacrizzler|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|925.8 MB|
+
+## References
+
+https://huggingface.co/aidanzhou/BACRizzler
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-bacrizzler_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-bacrizzler_pipeline_en.md
new file mode 100644
index 00000000000000..073102818f4a6b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-bacrizzler_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bacrizzler_pipeline pipeline T5Transformer from aidanzhou
+author: John Snow Labs
+name: bacrizzler_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bacrizzler_pipeline` is a English model originally trained by aidanzhou.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bacrizzler_pipeline_en_5.5.1_3.0_1738007601946.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bacrizzler_pipeline_en_5.5.1_3.0_1738007601946.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bacrizzler_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bacrizzler_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bacrizzler_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|925.8 MB|
+
+## References
+
+https://huggingface.co/aidanzhou/BACRizzler
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-bart_german_de.md b/docs/_posts/ahmedlone127/2025-01-27-bart_german_de.md
new file mode 100644
index 00000000000000..6dd4c986738af1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-bart_german_de.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: German bart_german BartTransformer from Shahm
+author: John Snow Labs
+name: bart_german
+date: 2025-01-27
+tags: [de, open_source, onnx, text_generation, bart]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: de
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BartTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bart_german` is a German model originally trained by Shahm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bart_german_de_5.5.1_3.0_1737956052928.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bart_german_de_5.5.1_3.0_1737956052928.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = BartTransformer.pretrained("bart_german","de") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = BartTransformer.pretrained("bart_german","de") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bart_german|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|de|
+|Size:|809.5 MB|
+
+## References
+
+https://huggingface.co/Shahm/bart-german
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-bart_german_pipeline_de.md b/docs/_posts/ahmedlone127/2025-01-27-bart_german_pipeline_de.md
new file mode 100644
index 00000000000000..b25f198319123f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-bart_german_pipeline_de.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: German bart_german_pipeline pipeline BartTransformer from Shahm
+author: John Snow Labs
+name: bart_german_pipeline
+date: 2025-01-27
+tags: [de, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: de
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bart_german_pipeline` is a German model originally trained by Shahm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bart_german_pipeline_de_5.5.1_3.0_1737956094435.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bart_german_pipeline_de_5.5.1_3.0_1737956094435.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bart_german_pipeline", lang = "de")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bart_german_pipeline", lang = "de")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bart_german_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|de|
+|Size:|809.5 MB|
+
+## References
+
+https://huggingface.co/Shahm/bart-german
+
+## Included Models
+
+- DocumentAssembler
+- BartTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-bart_large_xsum_samsum_conv_summarizer_yashugupta786_en.md b/docs/_posts/ahmedlone127/2025-01-27-bart_large_xsum_samsum_conv_summarizer_yashugupta786_en.md
new file mode 100644
index 00000000000000..bd7668dbb111f0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-bart_large_xsum_samsum_conv_summarizer_yashugupta786_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bart_large_xsum_samsum_conv_summarizer_yashugupta786 BartTransformer from yashugupta786
+author: John Snow Labs
+name: bart_large_xsum_samsum_conv_summarizer_yashugupta786
+date: 2025-01-27
+tags: [en, open_source, onnx, text_generation, bart]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BartTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bart_large_xsum_samsum_conv_summarizer_yashugupta786` is a English model originally trained by yashugupta786.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bart_large_xsum_samsum_conv_summarizer_yashugupta786_en_5.5.1_3.0_1737955699640.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bart_large_xsum_samsum_conv_summarizer_yashugupta786_en_5.5.1_3.0_1737955699640.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = BartTransformer.pretrained("bart_large_xsum_samsum_conv_summarizer_yashugupta786","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = BartTransformer.pretrained("bart_large_xsum_samsum_conv_summarizer_yashugupta786","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bart_large_xsum_samsum_conv_summarizer_yashugupta786|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.9 GB|
+
+## References
+
+https://huggingface.co/yashugupta786/bart_large_xsum_samsum_conv_summarizer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-bart_large_xsum_samsum_conv_summarizer_yashugupta786_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-bart_large_xsum_samsum_conv_summarizer_yashugupta786_pipeline_en.md
new file mode 100644
index 00000000000000..7b021a90cf255d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-bart_large_xsum_samsum_conv_summarizer_yashugupta786_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bart_large_xsum_samsum_conv_summarizer_yashugupta786_pipeline pipeline BartTransformer from yashugupta786
+author: John Snow Labs
+name: bart_large_xsum_samsum_conv_summarizer_yashugupta786_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bart_large_xsum_samsum_conv_summarizer_yashugupta786_pipeline` is a English model originally trained by yashugupta786.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bart_large_xsum_samsum_conv_summarizer_yashugupta786_pipeline_en_5.5.1_3.0_1737955790735.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bart_large_xsum_samsum_conv_summarizer_yashugupta786_pipeline_en_5.5.1_3.0_1737955790735.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bart_large_xsum_samsum_conv_summarizer_yashugupta786_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bart_large_xsum_samsum_conv_summarizer_yashugupta786_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bart_large_xsum_samsum_conv_summarizer_yashugupta786_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.9 GB|
+
+## References
+
+https://huggingface.co/yashugupta786/bart_large_xsum_samsum_conv_summarizer
+
+## Included Models
+
+- DocumentAssembler
+- BartTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-beard_face_image_detection_en.md b/docs/_posts/ahmedlone127/2025-01-27-beard_face_image_detection_en.md
new file mode 100644
index 00000000000000..0bf899d0e1a9fd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-beard_face_image_detection_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English beard_face_image_detection ViTForImageClassification from dima806
+author: John Snow Labs
+name: beard_face_image_detection
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`beard_face_image_detection` is a English model originally trained by dima806.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/beard_face_image_detection_en_5.5.1_3.0_1738021704581.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/beard_face_image_detection_en_5.5.1_3.0_1738021704581.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""beard_face_image_detection","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("beard_face_image_detection","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|beard_face_image_detection|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/dima806/beard_face_image_detection
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-beard_face_image_detection_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-beard_face_image_detection_pipeline_en.md
new file mode 100644
index 00000000000000..9614e6c9f6c3d4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-beard_face_image_detection_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English beard_face_image_detection_pipeline pipeline ViTForImageClassification from dima806
+author: John Snow Labs
+name: beard_face_image_detection_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`beard_face_image_detection_pipeline` is a English model originally trained by dima806.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/beard_face_image_detection_pipeline_en_5.5.1_3.0_1738021722622.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/beard_face_image_detection_pipeline_en_5.5.1_3.0_1738021722622.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("beard_face_image_detection_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("beard_face_image_detection_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|beard_face_image_detection_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/dima806/beard_face_image_detection
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-beren_gpt2_medium_x49_en.md b/docs/_posts/ahmedlone127/2025-01-27-beren_gpt2_medium_x49_en.md
new file mode 100644
index 00000000000000..a011e6f0ce5632
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-beren_gpt2_medium_x49_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English beren_gpt2_medium_x49 GPT2Transformer from stanford-crfm
+author: John Snow Labs
+name: beren_gpt2_medium_x49
+date: 2025-01-27
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`beren_gpt2_medium_x49` is a English model originally trained by stanford-crfm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/beren_gpt2_medium_x49_en_5.5.1_3.0_1737996293104.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/beren_gpt2_medium_x49_en_5.5.1_3.0_1737996293104.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("beren_gpt2_medium_x49","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("beren_gpt2_medium_x49","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|beren_gpt2_medium_x49|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|852.4 MB|
+
+## References
+
+https://huggingface.co/stanford-crfm/beren-gpt2-medium-x49
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-beren_gpt2_medium_x49_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-beren_gpt2_medium_x49_pipeline_en.md
new file mode 100644
index 00000000000000..fc58152fb32967
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-beren_gpt2_medium_x49_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English beren_gpt2_medium_x49_pipeline pipeline GPT2Transformer from stanford-crfm
+author: John Snow Labs
+name: beren_gpt2_medium_x49_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`beren_gpt2_medium_x49_pipeline` is a English model originally trained by stanford-crfm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/beren_gpt2_medium_x49_pipeline_en_5.5.1_3.0_1737996537672.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/beren_gpt2_medium_x49_pipeline_en_5.5.1_3.0_1737996537672.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("beren_gpt2_medium_x49_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("beren_gpt2_medium_x49_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|beren_gpt2_medium_x49_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|852.4 MB|
+
+## References
+
+https://huggingface.co/stanford-crfm/beren-gpt2-medium-x49
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-bert_adaptation_martin_fierro_didicito_en.md b/docs/_posts/ahmedlone127/2025-01-27-bert_adaptation_martin_fierro_didicito_en.md
new file mode 100644
index 00000000000000..0b60f600c85020
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-bert_adaptation_martin_fierro_didicito_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_adaptation_martin_fierro_didicito BertEmbeddings from didicito
+author: John Snow Labs
+name: bert_adaptation_martin_fierro_didicito
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_martin_fierro_didicito` is a English model originally trained by didicito.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_martin_fierro_didicito_en_5.5.1_3.0_1737985789134.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_martin_fierro_didicito_en_5.5.1_3.0_1737985789134.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_adaptation_martin_fierro_didicito","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_adaptation_martin_fierro_didicito","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_martin_fierro_didicito|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/didicito/bert_adaptation_martin_fierro
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-bert_adaptation_martin_fierro_didicito_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-bert_adaptation_martin_fierro_didicito_pipeline_en.md
new file mode 100644
index 00000000000000..2d3916f4988517
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-bert_adaptation_martin_fierro_didicito_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_adaptation_martin_fierro_didicito_pipeline pipeline BertEmbeddings from didicito
+author: John Snow Labs
+name: bert_adaptation_martin_fierro_didicito_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_martin_fierro_didicito_pipeline` is a English model originally trained by didicito.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_martin_fierro_didicito_pipeline_en_5.5.1_3.0_1737985809601.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_martin_fierro_didicito_pipeline_en_5.5.1_3.0_1737985809601.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_adaptation_martin_fierro_didicito_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_adaptation_martin_fierro_didicito_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_martin_fierro_didicito_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/didicito/bert_adaptation_martin_fierro
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-bert_adaptation_peppa_pig_fcaneri_en.md b/docs/_posts/ahmedlone127/2025-01-27-bert_adaptation_peppa_pig_fcaneri_en.md
new file mode 100644
index 00000000000000..88b355bb658105
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-bert_adaptation_peppa_pig_fcaneri_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_adaptation_peppa_pig_fcaneri BertEmbeddings from fcaneri
+author: John Snow Labs
+name: bert_adaptation_peppa_pig_fcaneri
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_peppa_pig_fcaneri` is a English model originally trained by fcaneri.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_peppa_pig_fcaneri_en_5.5.1_3.0_1737953572695.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_peppa_pig_fcaneri_en_5.5.1_3.0_1737953572695.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_adaptation_peppa_pig_fcaneri","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_adaptation_peppa_pig_fcaneri","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_peppa_pig_fcaneri|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/fcaneri/bert_adaptation_peppa_pig
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-bert_adaptation_peppa_pig_fcaneri_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-bert_adaptation_peppa_pig_fcaneri_pipeline_en.md
new file mode 100644
index 00000000000000..557de601b192e6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-bert_adaptation_peppa_pig_fcaneri_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_adaptation_peppa_pig_fcaneri_pipeline pipeline BertEmbeddings from fcaneri
+author: John Snow Labs
+name: bert_adaptation_peppa_pig_fcaneri_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_peppa_pig_fcaneri_pipeline` is a English model originally trained by fcaneri.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_peppa_pig_fcaneri_pipeline_en_5.5.1_3.0_1737953596359.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_peppa_pig_fcaneri_pipeline_en_5.5.1_3.0_1737953596359.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_adaptation_peppa_pig_fcaneri_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_adaptation_peppa_pig_fcaneri_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_peppa_pig_fcaneri_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/fcaneri/bert_adaptation_peppa_pig
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-bert_adaptation_peppa_pig_mauroandres_en.md b/docs/_posts/ahmedlone127/2025-01-27-bert_adaptation_peppa_pig_mauroandres_en.md
new file mode 100644
index 00000000000000..f98ef8aa3d40ee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-bert_adaptation_peppa_pig_mauroandres_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_adaptation_peppa_pig_mauroandres BertEmbeddings from mauroandres
+author: John Snow Labs
+name: bert_adaptation_peppa_pig_mauroandres
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_peppa_pig_mauroandres` is a English model originally trained by mauroandres.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_peppa_pig_mauroandres_en_5.5.1_3.0_1737985615000.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_peppa_pig_mauroandres_en_5.5.1_3.0_1737985615000.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_adaptation_peppa_pig_mauroandres","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_adaptation_peppa_pig_mauroandres","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_peppa_pig_mauroandres|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/mauroandres/bert_adaptation_peppa_pig
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-bert_adaptation_peppa_pig_mauroandres_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-bert_adaptation_peppa_pig_mauroandres_pipeline_en.md
new file mode 100644
index 00000000000000..1af857563e1298
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-bert_adaptation_peppa_pig_mauroandres_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_adaptation_peppa_pig_mauroandres_pipeline pipeline BertEmbeddings from mauroandres
+author: John Snow Labs
+name: bert_adaptation_peppa_pig_mauroandres_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_peppa_pig_mauroandres_pipeline` is a English model originally trained by mauroandres.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_peppa_pig_mauroandres_pipeline_en_5.5.1_3.0_1737985635733.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_peppa_pig_mauroandres_pipeline_en_5.5.1_3.0_1737985635733.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_adaptation_peppa_pig_mauroandres_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_adaptation_peppa_pig_mauroandres_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_peppa_pig_mauroandres_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/mauroandres/bert_adaptation_peppa_pig
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-bert_base_cased_wikitext2_lucasday17_en.md b/docs/_posts/ahmedlone127/2025-01-27-bert_base_cased_wikitext2_lucasday17_en.md
new file mode 100644
index 00000000000000..700be36c5aa02f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-bert_base_cased_wikitext2_lucasday17_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_cased_wikitext2_lucasday17 BertEmbeddings from LucasDay17
+author: John Snow Labs
+name: bert_base_cased_wikitext2_lucasday17
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_wikitext2_lucasday17` is a English model originally trained by LucasDay17.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_wikitext2_lucasday17_en_5.5.1_3.0_1737953929961.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_wikitext2_lucasday17_en_5.5.1_3.0_1737953929961.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_base_cased_wikitext2_lucasday17","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_base_cased_wikitext2_lucasday17","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_cased_wikitext2_lucasday17|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|403.4 MB|
+
+## References
+
+https://huggingface.co/LucasDay17/bert-base-cased-wikitext2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-bert_base_cased_wikitext2_lucasday17_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-bert_base_cased_wikitext2_lucasday17_pipeline_en.md
new file mode 100644
index 00000000000000..b2dcdaf8c34307
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-bert_base_cased_wikitext2_lucasday17_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_cased_wikitext2_lucasday17_pipeline pipeline BertEmbeddings from LucasDay17
+author: John Snow Labs
+name: bert_base_cased_wikitext2_lucasday17_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_wikitext2_lucasday17_pipeline` is a English model originally trained by LucasDay17.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_wikitext2_lucasday17_pipeline_en_5.5.1_3.0_1737953950699.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_wikitext2_lucasday17_pipeline_en_5.5.1_3.0_1737953950699.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_cased_wikitext2_lucasday17_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_cased_wikitext2_lucasday17_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_cased_wikitext2_lucasday17_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.5 MB|
+
+## References
+
+https://huggingface.co/LucasDay17/bert-base-cased-wikitext2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-bert_base_german_cased_mlm_basque_oriya_ddr_en.md b/docs/_posts/ahmedlone127/2025-01-27-bert_base_german_cased_mlm_basque_oriya_ddr_en.md
new file mode 100644
index 00000000000000..bb13bb05e3ffaf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-bert_base_german_cased_mlm_basque_oriya_ddr_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_german_cased_mlm_basque_oriya_ddr BertEmbeddings from jonas-luehrs
+author: John Snow Labs
+name: bert_base_german_cased_mlm_basque_oriya_ddr
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_german_cased_mlm_basque_oriya_ddr` is a English model originally trained by jonas-luehrs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_german_cased_mlm_basque_oriya_ddr_en_5.5.1_3.0_1737985540082.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_german_cased_mlm_basque_oriya_ddr_en_5.5.1_3.0_1737985540082.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_base_german_cased_mlm_basque_oriya_ddr","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_base_german_cased_mlm_basque_oriya_ddr","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_german_cased_mlm_basque_oriya_ddr|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/jonas-luehrs/bert-base-german-cased-MLM-eu-or-ddr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-bert_base_german_cased_mlm_basque_oriya_ddr_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-bert_base_german_cased_mlm_basque_oriya_ddr_pipeline_en.md
new file mode 100644
index 00000000000000..534b8f052a2aa6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-bert_base_german_cased_mlm_basque_oriya_ddr_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_german_cased_mlm_basque_oriya_ddr_pipeline pipeline BertEmbeddings from jonas-luehrs
+author: John Snow Labs
+name: bert_base_german_cased_mlm_basque_oriya_ddr_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_german_cased_mlm_basque_oriya_ddr_pipeline` is a English model originally trained by jonas-luehrs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_german_cased_mlm_basque_oriya_ddr_pipeline_en_5.5.1_3.0_1737985560818.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_german_cased_mlm_basque_oriya_ddr_pipeline_en_5.5.1_3.0_1737985560818.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_german_cased_mlm_basque_oriya_ddr_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_german_cased_mlm_basque_oriya_ddr_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_german_cased_mlm_basque_oriya_ddr_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/jonas-luehrs/bert-base-german-cased-MLM-eu-or-ddr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-bert_base_uncased_finetuned_negation_scope_en.md b/docs/_posts/ahmedlone127/2025-01-27-bert_base_uncased_finetuned_negation_scope_en.md
new file mode 100644
index 00000000000000..a94b8c407a00fc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-bert_base_uncased_finetuned_negation_scope_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_uncased_finetuned_negation_scope BertForTokenClassification from dannashao
+author: John Snow Labs
+name: bert_base_uncased_finetuned_negation_scope
+date: 2025-01-27
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_negation_scope` is a English model originally trained by dannashao.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_negation_scope_en_5.5.1_3.0_1738017659977.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_negation_scope_en_5.5.1_3.0_1738017659977.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_base_uncased_finetuned_negation_scope","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_base_uncased_finetuned_negation_scope", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetuned_negation_scope|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/dannashao/bert-base-uncased-finetuned-negation_scope
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-bert_base_uncased_finetuned_negation_scope_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-bert_base_uncased_finetuned_negation_scope_pipeline_en.md
new file mode 100644
index 00000000000000..043ca245bccc71
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-bert_base_uncased_finetuned_negation_scope_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_uncased_finetuned_negation_scope_pipeline pipeline BertForTokenClassification from dannashao
+author: John Snow Labs
+name: bert_base_uncased_finetuned_negation_scope_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_negation_scope_pipeline` is a English model originally trained by dannashao.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_negation_scope_pipeline_en_5.5.1_3.0_1738017680509.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_negation_scope_pipeline_en_5.5.1_3.0_1738017680509.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetuned_negation_scope_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_negation_scope_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetuned_negation_scope_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/dannashao/bert-base-uncased-finetuned-negation_scope
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-bert_base_uncased_issues_128_jewoos_en.md b/docs/_posts/ahmedlone127/2025-01-27-bert_base_uncased_issues_128_jewoos_en.md
new file mode 100644
index 00000000000000..e3d75ea99ee349
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-bert_base_uncased_issues_128_jewoos_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_uncased_issues_128_jewoos BertEmbeddings from jewoos
+author: John Snow Labs
+name: bert_base_uncased_issues_128_jewoos
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_issues_128_jewoos` is a English model originally trained by jewoos.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_issues_128_jewoos_en_5.5.1_3.0_1737954286906.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_issues_128_jewoos_en_5.5.1_3.0_1737954286906.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_base_uncased_issues_128_jewoos","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_base_uncased_issues_128_jewoos","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_issues_128_jewoos|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/jewoos/bert-base-uncased-issues-128
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-bert_base_uncased_issues_128_jewoos_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-bert_base_uncased_issues_128_jewoos_pipeline_en.md
new file mode 100644
index 00000000000000..b22c255eeec4cf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-bert_base_uncased_issues_128_jewoos_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_uncased_issues_128_jewoos_pipeline pipeline BertEmbeddings from jewoos
+author: John Snow Labs
+name: bert_base_uncased_issues_128_jewoos_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_issues_128_jewoos_pipeline` is a English model originally trained by jewoos.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_issues_128_jewoos_pipeline_en_5.5.1_3.0_1737954307567.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_issues_128_jewoos_pipeline_en_5.5.1_3.0_1737954307567.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_issues_128_jewoos_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_issues_128_jewoos_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_issues_128_jewoos_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/jewoos/bert-base-uncased-issues-128
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-bert_base_uncased_m_en.md b/docs/_posts/ahmedlone127/2025-01-27-bert_base_uncased_m_en.md
new file mode 100644
index 00000000000000..87b2b30d989724
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-bert_base_uncased_m_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_uncased_m BertEmbeddings from ivanxia1988
+author: John Snow Labs
+name: bert_base_uncased_m
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_m` is a English model originally trained by ivanxia1988.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_m_en_5.5.1_3.0_1737985679657.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_m_en_5.5.1_3.0_1737985679657.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_base_uncased_m","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_base_uncased_m","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_m|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/ivanxia1988/bert-base-uncased-m
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-bert_base_uncased_m_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-bert_base_uncased_m_pipeline_en.md
new file mode 100644
index 00000000000000..c7ea4c48740fe1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-bert_base_uncased_m_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_uncased_m_pipeline pipeline BertEmbeddings from ivanxia1988
+author: John Snow Labs
+name: bert_base_uncased_m_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_m_pipeline` is a English model originally trained by ivanxia1988.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_m_pipeline_en_5.5.1_3.0_1737985700476.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_m_pipeline_en_5.5.1_3.0_1737985700476.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_m_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_m_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_m_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/ivanxia1988/bert-base-uncased-m
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-bert_fair_uncased_en.md b/docs/_posts/ahmedlone127/2025-01-27-bert_fair_uncased_en.md
new file mode 100644
index 00000000000000..6cadea05a794d8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-bert_fair_uncased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_fair_uncased BertEmbeddings from MScDS2023
+author: John Snow Labs
+name: bert_fair_uncased
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_fair_uncased` is a English model originally trained by MScDS2023.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_fair_uncased_en_5.5.1_3.0_1737985177274.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_fair_uncased_en_5.5.1_3.0_1737985177274.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_fair_uncased","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_fair_uncased","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_fair_uncased|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/MScDS2023/bert-fair-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-bert_fair_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-bert_fair_uncased_pipeline_en.md
new file mode 100644
index 00000000000000..74f21a50c115c6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-bert_fair_uncased_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_fair_uncased_pipeline pipeline BertEmbeddings from MScDS2023
+author: John Snow Labs
+name: bert_fair_uncased_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_fair_uncased_pipeline` is a English model originally trained by MScDS2023.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_fair_uncased_pipeline_en_5.5.1_3.0_1737985198004.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_fair_uncased_pipeline_en_5.5.1_3.0_1737985198004.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_fair_uncased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_fair_uncased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_fair_uncased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/MScDS2023/bert-fair-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-bert_finetuned_ner_model_en.md b/docs/_posts/ahmedlone127/2025-01-27-bert_finetuned_ner_model_en.md
new file mode 100644
index 00000000000000..bc11c0b9d4606d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-bert_finetuned_ner_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_finetuned_ner_model BertForTokenClassification from psyonp
+author: John Snow Labs
+name: bert_finetuned_ner_model
+date: 2025-01-27
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_model` is a English model originally trained by psyonp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_model_en_5.5.1_3.0_1738017854793.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_model_en_5.5.1_3.0_1738017854793.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_finetuned_ner_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/psyonp/bert-finetuned-ner-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-bert_finetuned_ner_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-bert_finetuned_ner_model_pipeline_en.md
new file mode 100644
index 00000000000000..8cd7a537f432ba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-bert_finetuned_ner_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_finetuned_ner_model_pipeline pipeline BertForTokenClassification from psyonp
+author: John Snow Labs
+name: bert_finetuned_ner_model_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_model_pipeline` is a English model originally trained by psyonp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_model_pipeline_en_5.5.1_3.0_1738017874805.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_model_pipeline_en_5.5.1_3.0_1738017874805.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_ner_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_ner_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/psyonp/bert-finetuned-ner-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-bert_finetuned_ner_requirements_en.md b/docs/_posts/ahmedlone127/2025-01-27-bert_finetuned_ner_requirements_en.md
new file mode 100644
index 00000000000000..38909b1647ca4e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-bert_finetuned_ner_requirements_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_finetuned_ner_requirements BertForTokenClassification from thescripterr
+author: John Snow Labs
+name: bert_finetuned_ner_requirements
+date: 2025-01-27
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_requirements` is a English model originally trained by thescripterr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_requirements_en_5.5.1_3.0_1738018048731.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_requirements_en_5.5.1_3.0_1738018048731.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_finetuned_ner_requirements","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner_requirements", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_requirements|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/thescripterr/bert-finetuned-ner-requirements
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-bert_finetuned_ner_requirements_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-bert_finetuned_ner_requirements_pipeline_en.md
new file mode 100644
index 00000000000000..11559e5371c039
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-bert_finetuned_ner_requirements_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_finetuned_ner_requirements_pipeline pipeline BertForTokenClassification from thescripterr
+author: John Snow Labs
+name: bert_finetuned_ner_requirements_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_requirements_pipeline` is a English model originally trained by thescripterr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_requirements_pipeline_en_5.5.1_3.0_1738018069623.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_requirements_pipeline_en_5.5.1_3.0_1738018069623.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_ner_requirements_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_ner_requirements_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_requirements_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/thescripterr/bert-finetuned-ner-requirements
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-bert_lorafinetuned_covidqa_en.md b/docs/_posts/ahmedlone127/2025-01-27-bert_lorafinetuned_covidqa_en.md
new file mode 100644
index 00000000000000..4b2827913def08
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-bert_lorafinetuned_covidqa_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_lorafinetuned_covidqa BertEmbeddings from dqduong2003
+author: John Snow Labs
+name: bert_lorafinetuned_covidqa
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_lorafinetuned_covidqa` is a English model originally trained by dqduong2003.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_lorafinetuned_covidqa_en_5.5.1_3.0_1737954097630.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_lorafinetuned_covidqa_en_5.5.1_3.0_1737954097630.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_lorafinetuned_covidqa","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_lorafinetuned_covidqa","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_lorafinetuned_covidqa|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|402.3 MB|
+
+## References
+
+https://huggingface.co/dqduong2003/bert-lorafinetuned-covidqa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-bert_lorafinetuned_covidqa_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-bert_lorafinetuned_covidqa_pipeline_en.md
new file mode 100644
index 00000000000000..febf93081dd1c8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-bert_lorafinetuned_covidqa_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_lorafinetuned_covidqa_pipeline pipeline BertEmbeddings from dqduong2003
+author: John Snow Labs
+name: bert_lorafinetuned_covidqa_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_lorafinetuned_covidqa_pipeline` is a English model originally trained by dqduong2003.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_lorafinetuned_covidqa_pipeline_en_5.5.1_3.0_1737954118383.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_lorafinetuned_covidqa_pipeline_en_5.5.1_3.0_1737954118383.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_lorafinetuned_covidqa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_lorafinetuned_covidqa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_lorafinetuned_covidqa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|402.3 MB|
+
+## References
+
+https://huggingface.co/dqduong2003/bert-lorafinetuned-covidqa
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-bert_pretrained_litcov10k_paraphrased_all_shuffled_en.md b/docs/_posts/ahmedlone127/2025-01-27-bert_pretrained_litcov10k_paraphrased_all_shuffled_en.md
new file mode 100644
index 00000000000000..472318b06d2484
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-bert_pretrained_litcov10k_paraphrased_all_shuffled_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_pretrained_litcov10k_paraphrased_all_shuffled BertEmbeddings from IneG
+author: John Snow Labs
+name: bert_pretrained_litcov10k_paraphrased_all_shuffled
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_pretrained_litcov10k_paraphrased_all_shuffled` is a English model originally trained by IneG.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_pretrained_litcov10k_paraphrased_all_shuffled_en_5.5.1_3.0_1737954109942.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_pretrained_litcov10k_paraphrased_all_shuffled_en_5.5.1_3.0_1737954109942.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_pretrained_litcov10k_paraphrased_all_shuffled","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_pretrained_litcov10k_paraphrased_all_shuffled","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_pretrained_litcov10k_paraphrased_all_shuffled|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/IneG/BERT_pretrained_litcov10K_paraphrased_all-shuffled
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-bert_pretrained_litcov10k_paraphrased_all_shuffled_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-bert_pretrained_litcov10k_paraphrased_all_shuffled_pipeline_en.md
new file mode 100644
index 00000000000000..593783af606021
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-bert_pretrained_litcov10k_paraphrased_all_shuffled_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_pretrained_litcov10k_paraphrased_all_shuffled_pipeline pipeline BertEmbeddings from IneG
+author: John Snow Labs
+name: bert_pretrained_litcov10k_paraphrased_all_shuffled_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_pretrained_litcov10k_paraphrased_all_shuffled_pipeline` is a English model originally trained by IneG.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_pretrained_litcov10k_paraphrased_all_shuffled_pipeline_en_5.5.1_3.0_1737954130754.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_pretrained_litcov10k_paraphrased_all_shuffled_pipeline_en_5.5.1_3.0_1737954130754.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_pretrained_litcov10k_paraphrased_all_shuffled_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_pretrained_litcov10k_paraphrased_all_shuffled_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_pretrained_litcov10k_paraphrased_all_shuffled_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/IneG/BERT_pretrained_litcov10K_paraphrased_all-shuffled
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-bert_tiny_lda_100_v1_mnli_en.md b/docs/_posts/ahmedlone127/2025-01-27-bert_tiny_lda_100_v1_mnli_en.md
new file mode 100644
index 00000000000000..0c9ad105e3dcd2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-bert_tiny_lda_100_v1_mnli_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_tiny_lda_100_v1_mnli DistilBertForSequenceClassification from gokulsrinivasagan
+author: John Snow Labs
+name: bert_tiny_lda_100_v1_mnli
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_tiny_lda_100_v1_mnli` is a English model originally trained by gokulsrinivasagan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_tiny_lda_100_v1_mnli_en_5.5.1_3.0_1737939869644.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_tiny_lda_100_v1_mnli_en_5.5.1_3.0_1737939869644.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("bert_tiny_lda_100_v1_mnli","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("bert_tiny_lda_100_v1_mnli", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_tiny_lda_100_v1_mnli|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|123.9 MB|
+
+## References
+
+https://huggingface.co/gokulsrinivasagan/bert_tiny_lda_100_v1_mnli
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-bert_tiny_lda_100_v1_mnli_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-bert_tiny_lda_100_v1_mnli_pipeline_en.md
new file mode 100644
index 00000000000000..955546d2aa5bb4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-bert_tiny_lda_100_v1_mnli_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_tiny_lda_100_v1_mnli_pipeline pipeline DistilBertForSequenceClassification from gokulsrinivasagan
+author: John Snow Labs
+name: bert_tiny_lda_100_v1_mnli_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_tiny_lda_100_v1_mnli_pipeline` is a English model originally trained by gokulsrinivasagan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_tiny_lda_100_v1_mnli_pipeline_en_5.5.1_3.0_1737939877039.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_tiny_lda_100_v1_mnli_pipeline_en_5.5.1_3.0_1737939877039.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_tiny_lda_100_v1_mnli_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_tiny_lda_100_v1_mnli_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_tiny_lda_100_v1_mnli_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|123.9 MB|
+
+## References
+
+https://huggingface.co/gokulsrinivasagan/bert_tiny_lda_100_v1_mnli
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-billsum_model_z_en.md b/docs/_posts/ahmedlone127/2025-01-27-billsum_model_z_en.md
new file mode 100644
index 00000000000000..894d8369f8c386
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-billsum_model_z_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English billsum_model_z T5Transformer from getallineedeasily
+author: John Snow Labs
+name: billsum_model_z
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`billsum_model_z` is a English model originally trained by getallineedeasily.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/billsum_model_z_en_5.5.1_3.0_1738006558943.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/billsum_model_z_en_5.5.1_3.0_1738006558943.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("billsum_model_z","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("billsum_model_z", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|billsum_model_z|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|905.8 MB|
+
+## References
+
+https://huggingface.co/getallineedeasily/billsum-model-z
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-billsum_model_z_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-billsum_model_z_pipeline_en.md
new file mode 100644
index 00000000000000..6dc7fe816615a2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-billsum_model_z_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English billsum_model_z_pipeline pipeline T5Transformer from getallineedeasily
+author: John Snow Labs
+name: billsum_model_z_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`billsum_model_z_pipeline` is a English model originally trained by getallineedeasily.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/billsum_model_z_pipeline_en_5.5.1_3.0_1738006610530.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/billsum_model_z_pipeline_en_5.5.1_3.0_1738006610530.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("billsum_model_z_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("billsum_model_z_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|billsum_model_z_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|905.9 MB|
+
+## References
+
+https://huggingface.co/getallineedeasily/billsum-model-z
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-biobart_v2_base_en.md b/docs/_posts/ahmedlone127/2025-01-27-biobart_v2_base_en.md
new file mode 100644
index 00000000000000..82ffe3c73f65cc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-biobart_v2_base_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English biobart_v2_base BartTransformer from GanjinZero
+author: John Snow Labs
+name: biobart_v2_base
+date: 2025-01-27
+tags: [en, open_source, onnx, text_generation, bart]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BartTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biobart_v2_base` is a English model originally trained by GanjinZero.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biobart_v2_base_en_5.5.1_3.0_1737987197944.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biobart_v2_base_en_5.5.1_3.0_1737987197944.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = BartTransformer.pretrained("biobart_v2_base","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = BartTransformer.pretrained("biobart_v2_base","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|biobart_v2_base|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|711.7 MB|
+
+## References
+
+https://huggingface.co/GanjinZero/biobart-v2-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-biobart_v2_base_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-biobart_v2_base_pipeline_en.md
new file mode 100644
index 00000000000000..957aecd6cdde92
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-biobart_v2_base_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English biobart_v2_base_pipeline pipeline BartTransformer from GanjinZero
+author: John Snow Labs
+name: biobart_v2_base_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biobart_v2_base_pipeline` is a English model originally trained by GanjinZero.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biobart_v2_base_pipeline_en_5.5.1_3.0_1737987400375.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biobart_v2_base_pipeline_en_5.5.1_3.0_1737987400375.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("biobart_v2_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("biobart_v2_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|biobart_v2_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|711.7 MB|
+
+## References
+
+https://huggingface.co/GanjinZero/biobart-v2-base
+
+## Included Models
+
+- DocumentAssembler
+- BartTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-bone_fracture_detection_using_xray_en.md b/docs/_posts/ahmedlone127/2025-01-27-bone_fracture_detection_using_xray_en.md
new file mode 100644
index 00000000000000..2769658634a252
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-bone_fracture_detection_using_xray_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bone_fracture_detection_using_xray ViTForImageClassification from Heem2
+author: John Snow Labs
+name: bone_fracture_detection_using_xray
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bone_fracture_detection_using_xray` is a English model originally trained by Heem2.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bone_fracture_detection_using_xray_en_5.5.1_3.0_1737957217549.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bone_fracture_detection_using_xray_en_5.5.1_3.0_1737957217549.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""bone_fracture_detection_using_xray","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("bone_fracture_detection_using_xray","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bone_fracture_detection_using_xray|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/Heem2/bone-fracture-detection-using-xray
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-bone_fracture_detection_using_xray_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-bone_fracture_detection_using_xray_pipeline_en.md
new file mode 100644
index 00000000000000..7f915ffa6b0327
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-bone_fracture_detection_using_xray_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bone_fracture_detection_using_xray_pipeline pipeline ViTForImageClassification from Heem2
+author: John Snow Labs
+name: bone_fracture_detection_using_xray_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bone_fracture_detection_using_xray_pipeline` is a English model originally trained by Heem2.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bone_fracture_detection_using_xray_pipeline_en_5.5.1_3.0_1737957234114.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bone_fracture_detection_using_xray_pipeline_en_5.5.1_3.0_1737957234114.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bone_fracture_detection_using_xray_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bone_fracture_detection_using_xray_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bone_fracture_detection_using_xray_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/Heem2/bone-fracture-detection-using-xray
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-brwac_v1_3__checkpoint12_en.md b/docs/_posts/ahmedlone127/2025-01-27-brwac_v1_3__checkpoint12_en.md
new file mode 100644
index 00000000000000..13a29107132ed7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-brwac_v1_3__checkpoint12_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English brwac_v1_3__checkpoint12 RoBertaEmbeddings from eduagarcia-temp
+author: John Snow Labs
+name: brwac_v1_3__checkpoint12
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`brwac_v1_3__checkpoint12` is a English model originally trained by eduagarcia-temp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/brwac_v1_3__checkpoint12_en_5.5.1_3.0_1738020402754.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/brwac_v1_3__checkpoint12_en_5.5.1_3.0_1738020402754.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("brwac_v1_3__checkpoint12","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("brwac_v1_3__checkpoint12","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|brwac_v1_3__checkpoint12|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|298.6 MB|
+
+## References
+
+https://huggingface.co/eduagarcia-temp/brwac_v1_3__checkpoint12
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-brwac_v1_3__checkpoint12_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-brwac_v1_3__checkpoint12_pipeline_en.md
new file mode 100644
index 00000000000000..8aa07a47683aa7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-brwac_v1_3__checkpoint12_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English brwac_v1_3__checkpoint12_pipeline pipeline RoBertaEmbeddings from eduagarcia-temp
+author: John Snow Labs
+name: brwac_v1_3__checkpoint12_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`brwac_v1_3__checkpoint12_pipeline` is a English model originally trained by eduagarcia-temp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/brwac_v1_3__checkpoint12_pipeline_en_5.5.1_3.0_1738020486703.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/brwac_v1_3__checkpoint12_pipeline_en_5.5.1_3.0_1738020486703.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("brwac_v1_3__checkpoint12_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("brwac_v1_3__checkpoint12_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|brwac_v1_3__checkpoint12_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|298.6 MB|
+
+## References
+
+https://huggingface.co/eduagarcia-temp/brwac_v1_3__checkpoint12
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-brwac_v1_5__checkpoint4_en.md b/docs/_posts/ahmedlone127/2025-01-27-brwac_v1_5__checkpoint4_en.md
new file mode 100644
index 00000000000000..bfa43aec1bd4ee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-brwac_v1_5__checkpoint4_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English brwac_v1_5__checkpoint4 RoBertaEmbeddings from eduagarcia-temp
+author: John Snow Labs
+name: brwac_v1_5__checkpoint4
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`brwac_v1_5__checkpoint4` is a English model originally trained by eduagarcia-temp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/brwac_v1_5__checkpoint4_en_5.5.1_3.0_1737965853915.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/brwac_v1_5__checkpoint4_en_5.5.1_3.0_1737965853915.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("brwac_v1_5__checkpoint4","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("brwac_v1_5__checkpoint4","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|brwac_v1_5__checkpoint4|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|296.8 MB|
+
+## References
+
+https://huggingface.co/eduagarcia-temp/brwac_v1_5__checkpoint4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-brwac_v1_5__checkpoint4_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-brwac_v1_5__checkpoint4_pipeline_en.md
new file mode 100644
index 00000000000000..d06a67928228ce
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-brwac_v1_5__checkpoint4_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English brwac_v1_5__checkpoint4_pipeline pipeline RoBertaEmbeddings from eduagarcia-temp
+author: John Snow Labs
+name: brwac_v1_5__checkpoint4_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`brwac_v1_5__checkpoint4_pipeline` is a English model originally trained by eduagarcia-temp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/brwac_v1_5__checkpoint4_pipeline_en_5.5.1_3.0_1737965941245.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/brwac_v1_5__checkpoint4_pipeline_en_5.5.1_3.0_1737965941245.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("brwac_v1_5__checkpoint4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("brwac_v1_5__checkpoint4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|brwac_v1_5__checkpoint4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|296.8 MB|
+
+## References
+
+https://huggingface.co/eduagarcia-temp/brwac_v1_5__checkpoint4
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_billsum_model_antoinesir_en.md b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_billsum_model_antoinesir_en.md
new file mode 100644
index 00000000000000..279c00040b8698
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_billsum_model_antoinesir_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_billsum_model_antoinesir T5Transformer from AntoineSir
+author: John Snow Labs
+name: burmese_awesome_billsum_model_antoinesir
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_billsum_model_antoinesir` is a English model originally trained by AntoineSir.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_billsum_model_antoinesir_en_5.5.1_3.0_1737991441953.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_billsum_model_antoinesir_en_5.5.1_3.0_1737991441953.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("burmese_awesome_billsum_model_antoinesir","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("burmese_awesome_billsum_model_antoinesir", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_billsum_model_antoinesir|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|266.1 MB|
+
+## References
+
+https://huggingface.co/AntoineSir/my_awesome_billsum_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_billsum_model_antoinesir_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_billsum_model_antoinesir_pipeline_en.md
new file mode 100644
index 00000000000000..74595e10ec8e0e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_billsum_model_antoinesir_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_billsum_model_antoinesir_pipeline pipeline T5Transformer from AntoineSir
+author: John Snow Labs
+name: burmese_awesome_billsum_model_antoinesir_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_billsum_model_antoinesir_pipeline` is a English model originally trained by AntoineSir.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_billsum_model_antoinesir_pipeline_en_5.5.1_3.0_1737991460098.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_billsum_model_antoinesir_pipeline_en_5.5.1_3.0_1737991460098.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_billsum_model_antoinesir_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_billsum_model_antoinesir_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_billsum_model_antoinesir_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|266.1 MB|
+
+## References
+
+https://huggingface.co/AntoineSir/my_awesome_billsum_model
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_billsum_model_dmen24_en.md b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_billsum_model_dmen24_en.md
new file mode 100644
index 00000000000000..d56c01bdac6c81
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_billsum_model_dmen24_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_billsum_model_dmen24 T5Transformer from dmen24
+author: John Snow Labs
+name: burmese_awesome_billsum_model_dmen24
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_billsum_model_dmen24` is a English model originally trained by dmen24.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_billsum_model_dmen24_en_5.5.1_3.0_1738001754152.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_billsum_model_dmen24_en_5.5.1_3.0_1738001754152.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("burmese_awesome_billsum_model_dmen24","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("burmese_awesome_billsum_model_dmen24", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_billsum_model_dmen24|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|278.3 MB|
+
+## References
+
+https://huggingface.co/dmen24/my_awesome_billsum_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_billsum_model_dmen24_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_billsum_model_dmen24_pipeline_en.md
new file mode 100644
index 00000000000000..eb3f99fbf8e122
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_billsum_model_dmen24_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_billsum_model_dmen24_pipeline pipeline T5Transformer from dmen24
+author: John Snow Labs
+name: burmese_awesome_billsum_model_dmen24_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_billsum_model_dmen24_pipeline` is a English model originally trained by dmen24.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_billsum_model_dmen24_pipeline_en_5.5.1_3.0_1738001770902.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_billsum_model_dmen24_pipeline_en_5.5.1_3.0_1738001770902.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_billsum_model_dmen24_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_billsum_model_dmen24_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_billsum_model_dmen24_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|278.3 MB|
+
+## References
+
+https://huggingface.co/dmen24/my_awesome_billsum_model
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_billsum_model_tr13_en.md b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_billsum_model_tr13_en.md
new file mode 100644
index 00000000000000..b9d2f2e7c9cd0c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_billsum_model_tr13_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_billsum_model_tr13 T5Transformer from Tr13
+author: John Snow Labs
+name: burmese_awesome_billsum_model_tr13
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_billsum_model_tr13` is a English model originally trained by Tr13.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_billsum_model_tr13_en_5.5.1_3.0_1738007958788.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_billsum_model_tr13_en_5.5.1_3.0_1738007958788.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("burmese_awesome_billsum_model_tr13","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("burmese_awesome_billsum_model_tr13", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_billsum_model_tr13|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|272.3 MB|
+
+## References
+
+https://huggingface.co/Tr13/my_awesome_billsum_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_billsum_model_tr13_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_billsum_model_tr13_pipeline_en.md
new file mode 100644
index 00000000000000..ee03c4de292b1f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_billsum_model_tr13_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_billsum_model_tr13_pipeline pipeline T5Transformer from Tr13
+author: John Snow Labs
+name: burmese_awesome_billsum_model_tr13_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_billsum_model_tr13_pipeline` is a English model originally trained by Tr13.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_billsum_model_tr13_pipeline_en_5.5.1_3.0_1738007977325.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_billsum_model_tr13_pipeline_en_5.5.1_3.0_1738007977325.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_billsum_model_tr13_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_billsum_model_tr13_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_billsum_model_tr13_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|272.3 MB|
+
+## References
+
+https://huggingface.co/Tr13/my_awesome_billsum_model
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_eli5_mlm_model_attempt_2_en.md b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_eli5_mlm_model_attempt_2_en.md
new file mode 100644
index 00000000000000..0324ad45199fd9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_eli5_mlm_model_attempt_2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_eli5_mlm_model_attempt_2 RoBertaEmbeddings from abdiharyadi
+author: John Snow Labs
+name: burmese_awesome_eli5_mlm_model_attempt_2
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_eli5_mlm_model_attempt_2` is a English model originally trained by abdiharyadi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_attempt_2_en_5.5.1_3.0_1737965423599.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_attempt_2_en_5.5.1_3.0_1737965423599.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("burmese_awesome_eli5_mlm_model_attempt_2","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("burmese_awesome_eli5_mlm_model_attempt_2","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_eli5_mlm_model_attempt_2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/abdiharyadi/my_awesome_eli5_mlm_model_attempt_2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_eli5_mlm_model_attempt_2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_eli5_mlm_model_attempt_2_pipeline_en.md
new file mode 100644
index 00000000000000..8da0fe48895123
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_eli5_mlm_model_attempt_2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_eli5_mlm_model_attempt_2_pipeline pipeline RoBertaEmbeddings from abdiharyadi
+author: John Snow Labs
+name: burmese_awesome_eli5_mlm_model_attempt_2_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_eli5_mlm_model_attempt_2_pipeline` is a English model originally trained by abdiharyadi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_attempt_2_pipeline_en_5.5.1_3.0_1737965440364.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_attempt_2_pipeline_en_5.5.1_3.0_1737965440364.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_eli5_mlm_model_attempt_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_eli5_mlm_model_attempt_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_eli5_mlm_model_attempt_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/abdiharyadi/my_awesome_eli5_mlm_model_attempt_2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_eli5_mlm_model_faithyeojw_en.md b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_eli5_mlm_model_faithyeojw_en.md
new file mode 100644
index 00000000000000..eacd78a736e0fe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_eli5_mlm_model_faithyeojw_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_eli5_mlm_model_faithyeojw RoBertaEmbeddings from faithyeojw
+author: John Snow Labs
+name: burmese_awesome_eli5_mlm_model_faithyeojw
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_eli5_mlm_model_faithyeojw` is a English model originally trained by faithyeojw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_faithyeojw_en_5.5.1_3.0_1738020617052.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_faithyeojw_en_5.5.1_3.0_1738020617052.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("burmese_awesome_eli5_mlm_model_faithyeojw","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("burmese_awesome_eli5_mlm_model_faithyeojw","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_eli5_mlm_model_faithyeojw|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/faithyeojw/my_awesome_eli5_mlm_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_eli5_mlm_model_faithyeojw_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_eli5_mlm_model_faithyeojw_pipeline_en.md
new file mode 100644
index 00000000000000..7a1ca96d3ec271
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_eli5_mlm_model_faithyeojw_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_eli5_mlm_model_faithyeojw_pipeline pipeline RoBertaEmbeddings from faithyeojw
+author: John Snow Labs
+name: burmese_awesome_eli5_mlm_model_faithyeojw_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_eli5_mlm_model_faithyeojw_pipeline` is a English model originally trained by faithyeojw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_faithyeojw_pipeline_en_5.5.1_3.0_1738020632382.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_faithyeojw_pipeline_en_5.5.1_3.0_1738020632382.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_eli5_mlm_model_faithyeojw_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_eli5_mlm_model_faithyeojw_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_eli5_mlm_model_faithyeojw_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/faithyeojw/my_awesome_eli5_mlm_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_eli5_mlm_model_heopewl_en.md b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_eli5_mlm_model_heopewl_en.md
new file mode 100644
index 00000000000000..153bda44e80c6d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_eli5_mlm_model_heopewl_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_eli5_mlm_model_heopewl RoBertaEmbeddings from heopewl
+author: John Snow Labs
+name: burmese_awesome_eli5_mlm_model_heopewl
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_eli5_mlm_model_heopewl` is a English model originally trained by heopewl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_heopewl_en_5.5.1_3.0_1738020411801.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_heopewl_en_5.5.1_3.0_1738020411801.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("burmese_awesome_eli5_mlm_model_heopewl","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("burmese_awesome_eli5_mlm_model_heopewl","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_eli5_mlm_model_heopewl|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/heopewl/my_awesome_eli5_mlm_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_eli5_mlm_model_heopewl_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_eli5_mlm_model_heopewl_pipeline_en.md
new file mode 100644
index 00000000000000..abaf9c9a03eee3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_eli5_mlm_model_heopewl_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_eli5_mlm_model_heopewl_pipeline pipeline RoBertaEmbeddings from heopewl
+author: John Snow Labs
+name: burmese_awesome_eli5_mlm_model_heopewl_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_eli5_mlm_model_heopewl_pipeline` is a English model originally trained by heopewl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_heopewl_pipeline_en_5.5.1_3.0_1738020443800.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_heopewl_pipeline_en_5.5.1_3.0_1738020443800.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_eli5_mlm_model_heopewl_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_eli5_mlm_model_heopewl_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_eli5_mlm_model_heopewl_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/heopewl/my_awesome_eli5_mlm_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_eli5_mlm_model_tiaisabel_en.md b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_eli5_mlm_model_tiaisabel_en.md
new file mode 100644
index 00000000000000..afc9c233d71df3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_eli5_mlm_model_tiaisabel_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_eli5_mlm_model_tiaisabel RoBertaEmbeddings from tiaisabel
+author: John Snow Labs
+name: burmese_awesome_eli5_mlm_model_tiaisabel
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_eli5_mlm_model_tiaisabel` is a English model originally trained by tiaisabel.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_tiaisabel_en_5.5.1_3.0_1737965450523.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_tiaisabel_en_5.5.1_3.0_1737965450523.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("burmese_awesome_eli5_mlm_model_tiaisabel","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("burmese_awesome_eli5_mlm_model_tiaisabel","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_eli5_mlm_model_tiaisabel|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/tiaisabel/my_awesome_eli5_mlm_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_eli5_mlm_model_tiaisabel_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_eli5_mlm_model_tiaisabel_pipeline_en.md
new file mode 100644
index 00000000000000..f47e3e4eab46c2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_eli5_mlm_model_tiaisabel_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_eli5_mlm_model_tiaisabel_pipeline pipeline RoBertaEmbeddings from tiaisabel
+author: John Snow Labs
+name: burmese_awesome_eli5_mlm_model_tiaisabel_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_eli5_mlm_model_tiaisabel_pipeline` is a English model originally trained by tiaisabel.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_tiaisabel_pipeline_en_5.5.1_3.0_1737965466959.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_tiaisabel_pipeline_en_5.5.1_3.0_1737965466959.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_eli5_mlm_model_tiaisabel_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_eli5_mlm_model_tiaisabel_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_eli5_mlm_model_tiaisabel_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/tiaisabel/my_awesome_eli5_mlm_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_eli5_mlm_model_toaster123_en.md b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_eli5_mlm_model_toaster123_en.md
new file mode 100644
index 00000000000000..30728eb7105c20
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_eli5_mlm_model_toaster123_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_eli5_mlm_model_toaster123 RoBertaEmbeddings from toaster123
+author: John Snow Labs
+name: burmese_awesome_eli5_mlm_model_toaster123
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_eli5_mlm_model_toaster123` is a English model originally trained by toaster123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_toaster123_en_5.5.1_3.0_1737966242308.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_toaster123_en_5.5.1_3.0_1737966242308.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("burmese_awesome_eli5_mlm_model_toaster123","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("burmese_awesome_eli5_mlm_model_toaster123","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_eli5_mlm_model_toaster123|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/toaster123/my_awesome_eli5_mlm_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_eli5_mlm_model_toaster123_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_eli5_mlm_model_toaster123_pipeline_en.md
new file mode 100644
index 00000000000000..db59a53f2180da
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_eli5_mlm_model_toaster123_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_eli5_mlm_model_toaster123_pipeline pipeline RoBertaEmbeddings from toaster123
+author: John Snow Labs
+name: burmese_awesome_eli5_mlm_model_toaster123_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_eli5_mlm_model_toaster123_pipeline` is a English model originally trained by toaster123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_toaster123_pipeline_en_5.5.1_3.0_1737966257979.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_toaster123_pipeline_en_5.5.1_3.0_1737966257979.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_eli5_mlm_model_toaster123_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_eli5_mlm_model_toaster123_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_eli5_mlm_model_toaster123_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/toaster123/my_awesome_eli5_mlm_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_food_model_blisian_en.md b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_food_model_blisian_en.md
new file mode 100644
index 00000000000000..8c778f1867f26c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_food_model_blisian_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_food_model_blisian ViTForImageClassification from blisian
+author: John Snow Labs
+name: burmese_awesome_food_model_blisian
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_food_model_blisian` is a English model originally trained by blisian.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_food_model_blisian_en_5.5.1_3.0_1737974158647.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_food_model_blisian_en_5.5.1_3.0_1737974158647.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""burmese_awesome_food_model_blisian","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("burmese_awesome_food_model_blisian","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_food_model_blisian|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.6 MB|
+
+## References
+
+https://huggingface.co/blisian/my_awesome_food_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_food_model_blisian_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_food_model_blisian_pipeline_en.md
new file mode 100644
index 00000000000000..1e5eed2278c716
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_food_model_blisian_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_food_model_blisian_pipeline pipeline ViTForImageClassification from blisian
+author: John Snow Labs
+name: burmese_awesome_food_model_blisian_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_food_model_blisian_pipeline` is a English model originally trained by blisian.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_food_model_blisian_pipeline_en_5.5.1_3.0_1737974175516.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_food_model_blisian_pipeline_en_5.5.1_3.0_1737974175516.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_food_model_blisian_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_food_model_blisian_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_food_model_blisian_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.6 MB|
+
+## References
+
+https://huggingface.co/blisian/my_awesome_food_model
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_food_model_josealfonsoaguilar_en.md b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_food_model_josealfonsoaguilar_en.md
new file mode 100644
index 00000000000000..027f1fa48241da
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_food_model_josealfonsoaguilar_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_food_model_josealfonsoaguilar ViTForImageClassification from JoseAlfonsoAguilar
+author: John Snow Labs
+name: burmese_awesome_food_model_josealfonsoaguilar
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_food_model_josealfonsoaguilar` is a English model originally trained by JoseAlfonsoAguilar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_food_model_josealfonsoaguilar_en_5.5.1_3.0_1737973973829.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_food_model_josealfonsoaguilar_en_5.5.1_3.0_1737973973829.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""burmese_awesome_food_model_josealfonsoaguilar","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("burmese_awesome_food_model_josealfonsoaguilar","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_food_model_josealfonsoaguilar|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.6 MB|
+
+## References
+
+https://huggingface.co/JoseAlfonsoAguilar/my_awesome_food_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_food_model_josealfonsoaguilar_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_food_model_josealfonsoaguilar_pipeline_en.md
new file mode 100644
index 00000000000000..624a90c6aef6eb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_food_model_josealfonsoaguilar_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_food_model_josealfonsoaguilar_pipeline pipeline ViTForImageClassification from JoseAlfonsoAguilar
+author: John Snow Labs
+name: burmese_awesome_food_model_josealfonsoaguilar_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_food_model_josealfonsoaguilar_pipeline` is a English model originally trained by JoseAlfonsoAguilar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_food_model_josealfonsoaguilar_pipeline_en_5.5.1_3.0_1737973990235.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_food_model_josealfonsoaguilar_pipeline_en_5.5.1_3.0_1737973990235.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_food_model_josealfonsoaguilar_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_food_model_josealfonsoaguilar_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_food_model_josealfonsoaguilar_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.6 MB|
+
+## References
+
+https://huggingface.co/JoseAlfonsoAguilar/my_awesome_food_model
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_model_abhibarnwal707_en.md b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_model_abhibarnwal707_en.md
new file mode 100644
index 00000000000000..6ca505b85b5b67
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_model_abhibarnwal707_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_abhibarnwal707 DistilBertForSequenceClassification from abhibarnwal707
+author: John Snow Labs
+name: burmese_awesome_model_abhibarnwal707
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_abhibarnwal707` is a English model originally trained by abhibarnwal707.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_abhibarnwal707_en_5.5.1_3.0_1737939465694.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_abhibarnwal707_en_5.5.1_3.0_1737939465694.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_abhibarnwal707","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_abhibarnwal707", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_abhibarnwal707|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/abhibarnwal707/my_awesome_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_model_abhibarnwal707_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_model_abhibarnwal707_pipeline_en.md
new file mode 100644
index 00000000000000..70fa49fa9837a6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_model_abhibarnwal707_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_abhibarnwal707_pipeline pipeline DistilBertForSequenceClassification from abhibarnwal707
+author: John Snow Labs
+name: burmese_awesome_model_abhibarnwal707_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_abhibarnwal707_pipeline` is a English model originally trained by abhibarnwal707.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_abhibarnwal707_pipeline_en_5.5.1_3.0_1737939480712.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_abhibarnwal707_pipeline_en_5.5.1_3.0_1737939480712.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_abhibarnwal707_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_abhibarnwal707_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_abhibarnwal707_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/abhibarnwal707/my_awesome_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_model_goutamnagp123_en.md b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_model_goutamnagp123_en.md
new file mode 100644
index 00000000000000..ec38cc7740e8b7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_model_goutamnagp123_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_goutamnagp123 DistilBertForSequenceClassification from GoutamNagp123
+author: John Snow Labs
+name: burmese_awesome_model_goutamnagp123
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_goutamnagp123` is a English model originally trained by GoutamNagp123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_goutamnagp123_en_5.5.1_3.0_1737939775571.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_goutamnagp123_en_5.5.1_3.0_1737939775571.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_goutamnagp123","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_goutamnagp123", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_goutamnagp123|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/GoutamNagp123/my_awesome_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_model_goutamnagp123_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_model_goutamnagp123_pipeline_en.md
new file mode 100644
index 00000000000000..34ded2f61929f7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_model_goutamnagp123_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_goutamnagp123_pipeline pipeline DistilBertForSequenceClassification from GoutamNagp123
+author: John Snow Labs
+name: burmese_awesome_model_goutamnagp123_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_goutamnagp123_pipeline` is a English model originally trained by GoutamNagp123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_goutamnagp123_pipeline_en_5.5.1_3.0_1737939789162.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_goutamnagp123_pipeline_en_5.5.1_3.0_1737939789162.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_goutamnagp123_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_goutamnagp123_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_goutamnagp123_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/GoutamNagp123/my_awesome_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_model_mohamadreza2002_en.md b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_model_mohamadreza2002_en.md
new file mode 100644
index 00000000000000..bb843fb90559c0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_model_mohamadreza2002_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_mohamadreza2002 DistilBertForSequenceClassification from MohamadReza2002
+author: John Snow Labs
+name: burmese_awesome_model_mohamadreza2002
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_mohamadreza2002` is a English model originally trained by MohamadReza2002.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_mohamadreza2002_en_5.5.1_3.0_1737939681199.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_mohamadreza2002_en_5.5.1_3.0_1737939681199.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_mohamadreza2002","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_mohamadreza2002", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_mohamadreza2002|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/MohamadReza2002/my_awesome_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_model_mohamadreza2002_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_model_mohamadreza2002_pipeline_en.md
new file mode 100644
index 00000000000000..4022f968eafcb2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_model_mohamadreza2002_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_mohamadreza2002_pipeline pipeline DistilBertForSequenceClassification from MohamadReza2002
+author: John Snow Labs
+name: burmese_awesome_model_mohamadreza2002_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_mohamadreza2002_pipeline` is a English model originally trained by MohamadReza2002.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_mohamadreza2002_pipeline_en_5.5.1_3.0_1737939694839.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_mohamadreza2002_pipeline_en_5.5.1_3.0_1737939694839.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_mohamadreza2002_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_mohamadreza2002_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_mohamadreza2002_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/MohamadReza2002/my_awesome_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_model_nsyed_en.md b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_model_nsyed_en.md
new file mode 100644
index 00000000000000..9b3d201b7fd942
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_model_nsyed_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_nsyed DistilBertForSequenceClassification from nsyed
+author: John Snow Labs
+name: burmese_awesome_model_nsyed
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_nsyed` is a English model originally trained by nsyed.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_nsyed_en_5.5.1_3.0_1737939104080.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_nsyed_en_5.5.1_3.0_1737939104080.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_nsyed","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_nsyed", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_nsyed|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/nsyed/my_awesome_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_model_nsyed_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_model_nsyed_pipeline_en.md
new file mode 100644
index 00000000000000..da2e8911f9c780
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_model_nsyed_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_nsyed_pipeline pipeline DistilBertForSequenceClassification from nsyed
+author: John Snow Labs
+name: burmese_awesome_model_nsyed_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_nsyed_pipeline` is a English model originally trained by nsyed.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_nsyed_pipeline_en_5.5.1_3.0_1737939130136.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_nsyed_pipeline_en_5.5.1_3.0_1737939130136.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_nsyed_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_nsyed_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_nsyed_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/nsyed/my_awesome_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_model_walon_en.md b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_model_walon_en.md
new file mode 100644
index 00000000000000..e18170da214f84
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_model_walon_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_walon DistilBertForSequenceClassification from walon
+author: John Snow Labs
+name: burmese_awesome_model_walon
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_walon` is a English model originally trained by walon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_walon_en_5.5.1_3.0_1737939977854.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_walon_en_5.5.1_3.0_1737939977854.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_walon","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_walon", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_walon|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/walon/my_awesome_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_model_walon_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_model_walon_pipeline_en.md
new file mode 100644
index 00000000000000..f5f0c558ab35f0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_model_walon_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_walon_pipeline pipeline DistilBertForSequenceClassification from walon
+author: John Snow Labs
+name: burmese_awesome_model_walon_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_walon_pipeline` is a English model originally trained by walon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_walon_pipeline_en_5.5.1_3.0_1737939991838.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_walon_pipeline_en_5.5.1_3.0_1737939991838.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_walon_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_walon_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_walon_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/walon/my_awesome_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_opus_books_model_ananim30j_en.md b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_opus_books_model_ananim30j_en.md
new file mode 100644
index 00000000000000..659a452cd72eb5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_opus_books_model_ananim30j_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_opus_books_model_ananim30j T5Transformer from ananim30j
+author: John Snow Labs
+name: burmese_awesome_opus_books_model_ananim30j
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_opus_books_model_ananim30j` is a English model originally trained by ananim30j.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_ananim30j_en_5.5.1_3.0_1737961805710.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_ananim30j_en_5.5.1_3.0_1737961805710.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("burmese_awesome_opus_books_model_ananim30j","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("burmese_awesome_opus_books_model_ananim30j", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_opus_books_model_ananim30j|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|279.4 MB|
+
+## References
+
+https://huggingface.co/ananim30j/my_awesome_opus_books_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_opus_books_model_ananim30j_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_opus_books_model_ananim30j_pipeline_en.md
new file mode 100644
index 00000000000000..8e1151938cce86
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_opus_books_model_ananim30j_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_opus_books_model_ananim30j_pipeline pipeline T5Transformer from ananim30j
+author: John Snow Labs
+name: burmese_awesome_opus_books_model_ananim30j_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_opus_books_model_ananim30j_pipeline` is a English model originally trained by ananim30j.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_ananim30j_pipeline_en_5.5.1_3.0_1737961821782.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_ananim30j_pipeline_en_5.5.1_3.0_1737961821782.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_opus_books_model_ananim30j_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_opus_books_model_ananim30j_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_opus_books_model_ananim30j_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|279.4 MB|
+
+## References
+
+https://huggingface.co/ananim30j/my_awesome_opus_books_model
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_opus_books_model_dlwen_en.md b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_opus_books_model_dlwen_en.md
new file mode 100644
index 00000000000000..86ebadd948ec58
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_opus_books_model_dlwen_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_opus_books_model_dlwen MarianTransformer from dlwen
+author: John Snow Labs
+name: burmese_awesome_opus_books_model_dlwen
+date: 2025-01-27
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_opus_books_model_dlwen` is a English model originally trained by dlwen.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_dlwen_en_5.5.1_3.0_1737937416285.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_dlwen_en_5.5.1_3.0_1737937416285.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("burmese_awesome_opus_books_model_dlwen","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("burmese_awesome_opus_books_model_dlwen","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_opus_books_model_dlwen|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|475.9 MB|
+
+## References
+
+https://huggingface.co/dlwen/my_awesome_opus_books_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_opus_books_model_dlwen_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_opus_books_model_dlwen_pipeline_en.md
new file mode 100644
index 00000000000000..0ad8ca0c38ed94
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_opus_books_model_dlwen_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_opus_books_model_dlwen_pipeline pipeline MarianTransformer from dlwen
+author: John Snow Labs
+name: burmese_awesome_opus_books_model_dlwen_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_opus_books_model_dlwen_pipeline` is a English model originally trained by dlwen.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_dlwen_pipeline_en_5.5.1_3.0_1737937445284.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_dlwen_pipeline_en_5.5.1_3.0_1737937445284.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_opus_books_model_dlwen_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_opus_books_model_dlwen_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_opus_books_model_dlwen_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|476.4 MB|
+
+## References
+
+https://huggingface.co/dlwen/my_awesome_opus_books_model
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_opus_books_model_kiranpadi_en.md b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_opus_books_model_kiranpadi_en.md
new file mode 100644
index 00000000000000..df6e3e797933e1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_opus_books_model_kiranpadi_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_opus_books_model_kiranpadi T5Transformer from Kiranpadi
+author: John Snow Labs
+name: burmese_awesome_opus_books_model_kiranpadi
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_opus_books_model_kiranpadi` is a English model originally trained by Kiranpadi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_kiranpadi_en_5.5.1_3.0_1737978390888.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_kiranpadi_en_5.5.1_3.0_1737978390888.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("burmese_awesome_opus_books_model_kiranpadi","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("burmese_awesome_opus_books_model_kiranpadi", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_opus_books_model_kiranpadi|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|246.0 MB|
+
+## References
+
+https://huggingface.co/Kiranpadi/my_awesome_opus_books_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_opus_books_model_kiranpadi_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_opus_books_model_kiranpadi_pipeline_en.md
new file mode 100644
index 00000000000000..3a392347d5d525
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_opus_books_model_kiranpadi_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_opus_books_model_kiranpadi_pipeline pipeline T5Transformer from Kiranpadi
+author: John Snow Labs
+name: burmese_awesome_opus_books_model_kiranpadi_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_opus_books_model_kiranpadi_pipeline` is a English model originally trained by Kiranpadi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_kiranpadi_pipeline_en_5.5.1_3.0_1737978412241.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_kiranpadi_pipeline_en_5.5.1_3.0_1737978412241.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_opus_books_model_kiranpadi_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_opus_books_model_kiranpadi_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_opus_books_model_kiranpadi_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|246.0 MB|
+
+## References
+
+https://huggingface.co/Kiranpadi/my_awesome_opus_books_model
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_opus_books_model_lilyk_en.md b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_opus_books_model_lilyk_en.md
new file mode 100644
index 00000000000000..9e9d3e50df76a9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_opus_books_model_lilyk_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_opus_books_model_lilyk T5Transformer from LilyK
+author: John Snow Labs
+name: burmese_awesome_opus_books_model_lilyk
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_opus_books_model_lilyk` is a English model originally trained by LilyK.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_lilyk_en_5.5.1_3.0_1737991583665.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_lilyk_en_5.5.1_3.0_1737991583665.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("burmese_awesome_opus_books_model_lilyk","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("burmese_awesome_opus_books_model_lilyk", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_opus_books_model_lilyk|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|279.4 MB|
+
+## References
+
+https://huggingface.co/LilyK/my_awesome_opus_books_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_opus_books_model_lilyk_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_opus_books_model_lilyk_pipeline_en.md
new file mode 100644
index 00000000000000..57632d6cbdbb84
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmese_awesome_opus_books_model_lilyk_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_opus_books_model_lilyk_pipeline pipeline T5Transformer from LilyK
+author: John Snow Labs
+name: burmese_awesome_opus_books_model_lilyk_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_opus_books_model_lilyk_pipeline` is a English model originally trained by LilyK.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_lilyk_pipeline_en_5.5.1_3.0_1737991600100.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_lilyk_pipeline_en_5.5.1_3.0_1737991600100.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_opus_books_model_lilyk_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_opus_books_model_lilyk_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_opus_books_model_lilyk_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|279.4 MB|
+
+## References
+
+https://huggingface.co/LilyK/my_awesome_opus_books_model
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmese_cool_trainer_en.md b/docs/_posts/ahmedlone127/2025-01-27-burmese_cool_trainer_en.md
new file mode 100644
index 00000000000000..d2116513289f23
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmese_cool_trainer_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_cool_trainer DistilBertForSequenceClassification from CodeLifeCL
+author: John Snow Labs
+name: burmese_cool_trainer
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_cool_trainer` is a English model originally trained by CodeLifeCL.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_cool_trainer_en_5.5.1_3.0_1737939935807.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_cool_trainer_en_5.5.1_3.0_1737939935807.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_cool_trainer","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_cool_trainer", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_cool_trainer|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|507.6 MB|
+
+## References
+
+https://huggingface.co/CodeLifeCL/my-cool-trainer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmese_cool_trainer_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-burmese_cool_trainer_pipeline_en.md
new file mode 100644
index 00000000000000..3ea82acc618953
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmese_cool_trainer_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_cool_trainer_pipeline pipeline DistilBertForSequenceClassification from CodeLifeCL
+author: John Snow Labs
+name: burmese_cool_trainer_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_cool_trainer_pipeline` is a English model originally trained by CodeLifeCL.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_cool_trainer_pipeline_en_5.5.1_3.0_1737939962783.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_cool_trainer_pipeline_en_5.5.1_3.0_1737939962783.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_cool_trainer_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_cool_trainer_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_cool_trainer_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|507.6 MB|
+
+## References
+
+https://huggingface.co/CodeLifeCL/my-cool-trainer
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmese_fantastic_patent_model_t5_v1_en.md b/docs/_posts/ahmedlone127/2025-01-27-burmese_fantastic_patent_model_t5_v1_en.md
new file mode 100644
index 00000000000000..1a7a90c0cf729f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmese_fantastic_patent_model_t5_v1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_fantastic_patent_model_t5_v1 T5Transformer from dmen24
+author: John Snow Labs
+name: burmese_fantastic_patent_model_t5_v1
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_fantastic_patent_model_t5_v1` is a English model originally trained by dmen24.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_fantastic_patent_model_t5_v1_en_5.5.1_3.0_1737989387896.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_fantastic_patent_model_t5_v1_en_5.5.1_3.0_1737989387896.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("burmese_fantastic_patent_model_t5_v1","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("burmese_fantastic_patent_model_t5_v1", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_fantastic_patent_model_t5_v1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|275.6 MB|
+
+## References
+
+https://huggingface.co/dmen24/my_fantastic_patent_model_T5_V1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmese_fantastic_patent_model_t5_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-burmese_fantastic_patent_model_t5_v1_pipeline_en.md
new file mode 100644
index 00000000000000..15e3a206606496
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmese_fantastic_patent_model_t5_v1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_fantastic_patent_model_t5_v1_pipeline pipeline T5Transformer from dmen24
+author: John Snow Labs
+name: burmese_fantastic_patent_model_t5_v1_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_fantastic_patent_model_t5_v1_pipeline` is a English model originally trained by dmen24.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_fantastic_patent_model_t5_v1_pipeline_en_5.5.1_3.0_1737989404728.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_fantastic_patent_model_t5_v1_pipeline_en_5.5.1_3.0_1737989404728.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_fantastic_patent_model_t5_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_fantastic_patent_model_t5_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_fantastic_patent_model_t5_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|275.6 MB|
+
+## References
+
+https://huggingface.co/dmen24/my_fantastic_patent_model_T5_V1
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmese_food_model_osanseviero_en.md b/docs/_posts/ahmedlone127/2025-01-27-burmese_food_model_osanseviero_en.md
new file mode 100644
index 00000000000000..3cf564f9d18d74
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmese_food_model_osanseviero_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_food_model_osanseviero ViTForImageClassification from osanseviero
+author: John Snow Labs
+name: burmese_food_model_osanseviero
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_food_model_osanseviero` is a English model originally trained by osanseviero.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_food_model_osanseviero_en_5.5.1_3.0_1737974843020.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_food_model_osanseviero_en_5.5.1_3.0_1737974843020.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""burmese_food_model_osanseviero","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("burmese_food_model_osanseviero","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_food_model_osanseviero|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.6 MB|
+
+## References
+
+https://huggingface.co/osanseviero/my_food_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmese_food_model_osanseviero_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-burmese_food_model_osanseviero_pipeline_en.md
new file mode 100644
index 00000000000000..e2af6fda9adedf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmese_food_model_osanseviero_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_food_model_osanseviero_pipeline pipeline ViTForImageClassification from osanseviero
+author: John Snow Labs
+name: burmese_food_model_osanseviero_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_food_model_osanseviero_pipeline` is a English model originally trained by osanseviero.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_food_model_osanseviero_pipeline_en_5.5.1_3.0_1737974862210.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_food_model_osanseviero_pipeline_en_5.5.1_3.0_1737974862210.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_food_model_osanseviero_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_food_model_osanseviero_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_food_model_osanseviero_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.6 MB|
+
+## References
+
+https://huggingface.co/osanseviero/my_food_model
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmese_sports_review_summarization_model_mariika01_en.md b/docs/_posts/ahmedlone127/2025-01-27-burmese_sports_review_summarization_model_mariika01_en.md
new file mode 100644
index 00000000000000..856b70c38f8d8b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmese_sports_review_summarization_model_mariika01_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_sports_review_summarization_model_mariika01 T5Transformer from mariika01
+author: John Snow Labs
+name: burmese_sports_review_summarization_model_mariika01
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_sports_review_summarization_model_mariika01` is a English model originally trained by mariika01.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_sports_review_summarization_model_mariika01_en_5.5.1_3.0_1737961674186.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_sports_review_summarization_model_mariika01_en_5.5.1_3.0_1737961674186.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("burmese_sports_review_summarization_model_mariika01","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("burmese_sports_review_summarization_model_mariika01", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_sports_review_summarization_model_mariika01|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|148.0 MB|
+
+## References
+
+https://huggingface.co/mariika01/my-sports-review-summarization-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmese_sports_review_summarization_model_mariika01_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-burmese_sports_review_summarization_model_mariika01_pipeline_en.md
new file mode 100644
index 00000000000000..c3904f76470074
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmese_sports_review_summarization_model_mariika01_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_sports_review_summarization_model_mariika01_pipeline pipeline T5Transformer from mariika01
+author: John Snow Labs
+name: burmese_sports_review_summarization_model_mariika01_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_sports_review_summarization_model_mariika01_pipeline` is a English model originally trained by mariika01.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_sports_review_summarization_model_mariika01_pipeline_en_5.5.1_3.0_1737961723574.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_sports_review_summarization_model_mariika01_pipeline_en_5.5.1_3.0_1737961723574.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_sports_review_summarization_model_mariika01_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_sports_review_summarization_model_mariika01_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_sports_review_summarization_model_mariika01_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|148.0 MB|
+
+## References
+
+https://huggingface.co/mariika01/my-sports-review-summarization-model
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmese_summarization_model_iamj33l_en.md b/docs/_posts/ahmedlone127/2025-01-27-burmese_summarization_model_iamj33l_en.md
new file mode 100644
index 00000000000000..5f4d9e826eab9e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmese_summarization_model_iamj33l_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_summarization_model_iamj33l T5Transformer from iamj33l
+author: John Snow Labs
+name: burmese_summarization_model_iamj33l
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_summarization_model_iamj33l` is a English model originally trained by iamj33l.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_summarization_model_iamj33l_en_5.5.1_3.0_1737980655008.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_summarization_model_iamj33l_en_5.5.1_3.0_1737980655008.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("burmese_summarization_model_iamj33l","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("burmese_summarization_model_iamj33l", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_summarization_model_iamj33l|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|276.2 MB|
+
+## References
+
+https://huggingface.co/iamj33l/my_summarization_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmese_summarization_model_iamj33l_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-burmese_summarization_model_iamj33l_pipeline_en.md
new file mode 100644
index 00000000000000..a6eda2c4a46468
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmese_summarization_model_iamj33l_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_summarization_model_iamj33l_pipeline pipeline T5Transformer from iamj33l
+author: John Snow Labs
+name: burmese_summarization_model_iamj33l_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_summarization_model_iamj33l_pipeline` is a English model originally trained by iamj33l.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_summarization_model_iamj33l_pipeline_en_5.5.1_3.0_1737980671294.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_summarization_model_iamj33l_pipeline_en_5.5.1_3.0_1737980671294.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_summarization_model_iamj33l_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_summarization_model_iamj33l_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_summarization_model_iamj33l_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|276.2 MB|
+
+## References
+
+https://huggingface.co/iamj33l/my_summarization_model
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmese_t5_summarization_model_en.md b/docs/_posts/ahmedlone127/2025-01-27-burmese_t5_summarization_model_en.md
new file mode 100644
index 00000000000000..7eae7ae12604d2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmese_t5_summarization_model_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_t5_summarization_model T5Transformer from dmen24
+author: John Snow Labs
+name: burmese_t5_summarization_model
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_t5_summarization_model` is a English model originally trained by dmen24.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_t5_summarization_model_en_5.5.1_3.0_1738001045792.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_t5_summarization_model_en_5.5.1_3.0_1738001045792.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("burmese_t5_summarization_model","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("burmese_t5_summarization_model", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_t5_summarization_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|280.1 MB|
+
+## References
+
+https://huggingface.co/dmen24/my_T5_summarization_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmese_t5_summarization_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-burmese_t5_summarization_model_pipeline_en.md
new file mode 100644
index 00000000000000..8e4eab93ddb34d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmese_t5_summarization_model_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_t5_summarization_model_pipeline pipeline T5Transformer from dmen24
+author: John Snow Labs
+name: burmese_t5_summarization_model_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_t5_summarization_model_pipeline` is a English model originally trained by dmen24.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_t5_summarization_model_pipeline_en_5.5.1_3.0_1738001072941.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_t5_summarization_model_pipeline_en_5.5.1_3.0_1738001072941.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_t5_summarization_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_t5_summarization_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_t5_summarization_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|280.1 MB|
+
+## References
+
+https://huggingface.co/dmen24/my_T5_summarization_model
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmesebert_my.md b/docs/_posts/ahmedlone127/2025-01-27-burmesebert_my.md
new file mode 100644
index 00000000000000..5b147ab31df093
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmesebert_my.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Burmese burmesebert BertEmbeddings from jojo-ai-mst
+author: John Snow Labs
+name: burmesebert
+date: 2025-01-27
+tags: [my, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: my
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmesebert` is a Burmese model originally trained by jojo-ai-mst.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmesebert_my_5.5.1_3.0_1737985442477.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmesebert_my_5.5.1_3.0_1737985442477.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("burmesebert","my") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("burmesebert","my") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmesebert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|my|
+|Size:|1.4 GB|
+
+## References
+
+https://huggingface.co/jojo-ai-mst/BurmeseBert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-burmesebert_pipeline_my.md b/docs/_posts/ahmedlone127/2025-01-27-burmesebert_pipeline_my.md
new file mode 100644
index 00000000000000..e94dba5e748951
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-burmesebert_pipeline_my.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Burmese burmesebert_pipeline pipeline BertEmbeddings from jojo-ai-mst
+author: John Snow Labs
+name: burmesebert_pipeline
+date: 2025-01-27
+tags: [my, open_source, pipeline, onnx]
+task: Embeddings
+language: my
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmesebert_pipeline` is a Burmese model originally trained by jojo-ai-mst.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmesebert_pipeline_my_5.5.1_3.0_1737985513688.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmesebert_pipeline_my_5.5.1_3.0_1737985513688.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmesebert_pipeline", lang = "my")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmesebert_pipeline", lang = "my")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmesebert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|my|
+|Size:|1.4 GB|
+
+## References
+
+https://huggingface.co/jojo-ai-mst/BurmeseBert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-car_brands_en.md b/docs/_posts/ahmedlone127/2025-01-27-car_brands_en.md
new file mode 100644
index 00000000000000..60b1ceb65341ca
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-car_brands_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English car_brands ViTForImageClassification from misterawpb
+author: John Snow Labs
+name: car_brands
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`car_brands` is a English model originally trained by misterawpb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/car_brands_en_5.5.1_3.0_1738022276365.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/car_brands_en_5.5.1_3.0_1738022276365.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""car_brands","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("car_brands","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|car_brands|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/misterawpb/car_brands
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-car_brands_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-car_brands_pipeline_en.md
new file mode 100644
index 00000000000000..244a7fcaa7f9b7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-car_brands_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English car_brands_pipeline pipeline ViTForImageClassification from misterawpb
+author: John Snow Labs
+name: car_brands_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`car_brands_pipeline` is a English model originally trained by misterawpb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/car_brands_pipeline_en_5.5.1_3.0_1738022303182.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/car_brands_pipeline_en_5.5.1_3.0_1738022303182.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("car_brands_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("car_brands_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|car_brands_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/misterawpb/car_brands
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-car_damage_detection_en.md b/docs/_posts/ahmedlone127/2025-01-27-car_damage_detection_en.md
new file mode 100644
index 00000000000000..bae687a8c42523
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-car_damage_detection_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English car_damage_detection ViTForImageClassification from beingamit99
+author: John Snow Labs
+name: car_damage_detection
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`car_damage_detection` is a English model originally trained by beingamit99.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/car_damage_detection_en_5.5.1_3.0_1737957461044.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/car_damage_detection_en_5.5.1_3.0_1737957461044.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""car_damage_detection","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("car_damage_detection","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|car_damage_detection|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/beingamit99/car_damage_detection
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-car_damage_detection_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-car_damage_detection_pipeline_en.md
new file mode 100644
index 00000000000000..6330302487c1f7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-car_damage_detection_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English car_damage_detection_pipeline pipeline ViTForImageClassification from beingamit99
+author: John Snow Labs
+name: car_damage_detection_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`car_damage_detection_pipeline` is a English model originally trained by beingamit99.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/car_damage_detection_pipeline_en_5.5.1_3.0_1737957477702.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/car_damage_detection_pipeline_en_5.5.1_3.0_1737957477702.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("car_damage_detection_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("car_damage_detection_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|car_damage_detection_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/beingamit99/car_damage_detection
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-causalbert_en.md b/docs/_posts/ahmedlone127/2025-01-27-causalbert_en.md
new file mode 100644
index 00000000000000..a31d371fc519d7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-causalbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English causalbert BertForTokenClassification from norygano
+author: John Snow Labs
+name: causalbert
+date: 2025-01-27
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`causalbert` is a English model originally trained by norygano.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/causalbert_en_5.5.1_3.0_1738017311511.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/causalbert_en_5.5.1_3.0_1738017311511.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("causalbert","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("causalbert", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|causalbert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/norygano/causalBERT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-causalbert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-causalbert_pipeline_en.md
new file mode 100644
index 00000000000000..9ef286c780b59b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-causalbert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English causalbert_pipeline pipeline BertForTokenClassification from norygano
+author: John Snow Labs
+name: causalbert_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`causalbert_pipeline` is a English model originally trained by norygano.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/causalbert_pipeline_en_5.5.1_3.0_1738017332334.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/causalbert_pipeline_en_5.5.1_3.0_1738017332334.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("causalbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("causalbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|causalbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/norygano/causalBERT
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-ccr_test_en.md b/docs/_posts/ahmedlone127/2025-01-27-ccr_test_en.md
new file mode 100644
index 00000000000000..94fc1ebf4e96d9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-ccr_test_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ccr_test RoBertaEmbeddings from gaodrew
+author: John Snow Labs
+name: ccr_test
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ccr_test` is a English model originally trained by gaodrew.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ccr_test_en_5.5.1_3.0_1738019535795.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ccr_test_en_5.5.1_3.0_1738019535795.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("ccr_test","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("ccr_test","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ccr_test|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|204.7 MB|
+
+## References
+
+https://huggingface.co/gaodrew/CCR-test
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-ccr_test_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-ccr_test_pipeline_en.md
new file mode 100644
index 00000000000000..da97a8b4b0676c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-ccr_test_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ccr_test_pipeline pipeline RoBertaEmbeddings from gaodrew
+author: John Snow Labs
+name: ccr_test_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ccr_test_pipeline` is a English model originally trained by gaodrew.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ccr_test_pipeline_en_5.5.1_3.0_1738019555134.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ccr_test_pipeline_en_5.5.1_3.0_1738019555134.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ccr_test_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ccr_test_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ccr_test_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|204.7 MB|
+
+## References
+
+https://huggingface.co/gaodrew/CCR-test
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-chatot_en.md b/docs/_posts/ahmedlone127/2025-01-27-chatot_en.md
new file mode 100644
index 00000000000000..1a54a6b503793f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-chatot_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English chatot T5Transformer from kraj9173
+author: John Snow Labs
+name: chatot
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`chatot` is a English model originally trained by kraj9173.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/chatot_en_5.5.1_3.0_1737992318424.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/chatot_en_5.5.1_3.0_1737992318424.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("chatot","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("chatot", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|chatot|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|349.8 MB|
+
+## References
+
+https://huggingface.co/kraj9173/chatot
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-chatot_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-chatot_pipeline_en.md
new file mode 100644
index 00000000000000..58bb8f7aa6de43
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-chatot_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English chatot_pipeline pipeline T5Transformer from kraj9173
+author: John Snow Labs
+name: chatot_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`chatot_pipeline` is a English model originally trained by kraj9173.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/chatot_pipeline_en_5.5.1_3.0_1737992336063.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/chatot_pipeline_en_5.5.1_3.0_1737992336063.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("chatot_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("chatot_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|chatot_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|349.8 MB|
+
+## References
+
+https://huggingface.co/kraj9173/chatot
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-chuvash_construction_vehicle_identification_pipeline_zh.md b/docs/_posts/ahmedlone127/2025-01-27-chuvash_construction_vehicle_identification_pipeline_zh.md
new file mode 100644
index 00000000000000..e5504cb20a0848
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-chuvash_construction_vehicle_identification_pipeline_zh.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Chinese chuvash_construction_vehicle_identification_pipeline pipeline ViTForImageClassification from Bazaar
+author: John Snow Labs
+name: chuvash_construction_vehicle_identification_pipeline
+date: 2025-01-27
+tags: [zh, open_source, pipeline, onnx]
+task: Image Classification
+language: zh
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`chuvash_construction_vehicle_identification_pipeline` is a Chinese model originally trained by Bazaar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/chuvash_construction_vehicle_identification_pipeline_zh_5.5.1_3.0_1737974992800.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/chuvash_construction_vehicle_identification_pipeline_zh_5.5.1_3.0_1737974992800.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("chuvash_construction_vehicle_identification_pipeline", lang = "zh")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("chuvash_construction_vehicle_identification_pipeline", lang = "zh")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|chuvash_construction_vehicle_identification_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|zh|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/Bazaar/cv_construction_vehicle_identification
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-chuvash_construction_vehicle_identification_zh.md b/docs/_posts/ahmedlone127/2025-01-27-chuvash_construction_vehicle_identification_zh.md
new file mode 100644
index 00000000000000..0732482dad9bcf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-chuvash_construction_vehicle_identification_zh.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Chinese chuvash_construction_vehicle_identification ViTForImageClassification from Bazaar
+author: John Snow Labs
+name: chuvash_construction_vehicle_identification
+date: 2025-01-27
+tags: [zh, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: zh
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`chuvash_construction_vehicle_identification` is a Chinese model originally trained by Bazaar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/chuvash_construction_vehicle_identification_zh_5.5.1_3.0_1737974972897.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/chuvash_construction_vehicle_identification_zh_5.5.1_3.0_1737974972897.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""chuvash_construction_vehicle_identification","zh")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("chuvash_construction_vehicle_identification","zh") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|chuvash_construction_vehicle_identification|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|zh|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/Bazaar/cv_construction_vehicle_identification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-cifake_vit_generated_d1_20_d2_90_retrainv2_en.md b/docs/_posts/ahmedlone127/2025-01-27-cifake_vit_generated_d1_20_d2_90_retrainv2_en.md
new file mode 100644
index 00000000000000..0e37e8d17963ce
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-cifake_vit_generated_d1_20_d2_90_retrainv2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English cifake_vit_generated_d1_20_d2_90_retrainv2 ViTForImageClassification from dpaul93
+author: John Snow Labs
+name: cifake_vit_generated_d1_20_d2_90_retrainv2
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cifake_vit_generated_d1_20_d2_90_retrainv2` is a English model originally trained by dpaul93.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cifake_vit_generated_d1_20_d2_90_retrainv2_en_5.5.1_3.0_1737974301326.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cifake_vit_generated_d1_20_d2_90_retrainv2_en_5.5.1_3.0_1737974301326.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""cifake_vit_generated_d1_20_d2_90_retrainv2","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("cifake_vit_generated_d1_20_d2_90_retrainv2","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cifake_vit_generated_d1_20_d2_90_retrainv2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.2 MB|
+
+## References
+
+https://huggingface.co/dpaul93/cifake_vit_generated-d1-20-d2-90-retrainv2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-cifake_vit_generated_d1_20_d2_90_retrainv2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-cifake_vit_generated_d1_20_d2_90_retrainv2_pipeline_en.md
new file mode 100644
index 00000000000000..16ed8a314841d7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-cifake_vit_generated_d1_20_d2_90_retrainv2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English cifake_vit_generated_d1_20_d2_90_retrainv2_pipeline pipeline ViTForImageClassification from dpaul93
+author: John Snow Labs
+name: cifake_vit_generated_d1_20_d2_90_retrainv2_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cifake_vit_generated_d1_20_d2_90_retrainv2_pipeline` is a English model originally trained by dpaul93.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cifake_vit_generated_d1_20_d2_90_retrainv2_pipeline_en_5.5.1_3.0_1737974317716.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cifake_vit_generated_d1_20_d2_90_retrainv2_pipeline_en_5.5.1_3.0_1737974317716.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("cifake_vit_generated_d1_20_d2_90_retrainv2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cifake_vit_generated_d1_20_d2_90_retrainv2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cifake_vit_generated_d1_20_d2_90_retrainv2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.2 MB|
+
+## References
+
+https://huggingface.co/dpaul93/cifake_vit_generated-d1-20-d2-90-retrainv2
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-city_austronesian_languages_vit_base_patch16_224_en.md b/docs/_posts/ahmedlone127/2025-01-27-city_austronesian_languages_vit_base_patch16_224_en.md
new file mode 100644
index 00000000000000..9ff4165530716a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-city_austronesian_languages_vit_base_patch16_224_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English city_austronesian_languages_vit_base_patch16_224 ViTForImageClassification from STEM-AI-mtl
+author: John Snow Labs
+name: city_austronesian_languages_vit_base_patch16_224
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`city_austronesian_languages_vit_base_patch16_224` is a English model originally trained by STEM-AI-mtl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/city_austronesian_languages_vit_base_patch16_224_en_5.5.1_3.0_1737974860540.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/city_austronesian_languages_vit_base_patch16_224_en_5.5.1_3.0_1737974860540.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""city_austronesian_languages_vit_base_patch16_224","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("city_austronesian_languages_vit_base_patch16_224","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|city_austronesian_languages_vit_base_patch16_224|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.4 MB|
+
+## References
+
+https://huggingface.co/STEM-AI-mtl/City_map-vit-base-patch16-224
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-city_austronesian_languages_vit_base_patch16_224_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-city_austronesian_languages_vit_base_patch16_224_pipeline_en.md
new file mode 100644
index 00000000000000..bf5b58e594e691
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-city_austronesian_languages_vit_base_patch16_224_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English city_austronesian_languages_vit_base_patch16_224_pipeline pipeline ViTForImageClassification from STEM-AI-mtl
+author: John Snow Labs
+name: city_austronesian_languages_vit_base_patch16_224_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`city_austronesian_languages_vit_base_patch16_224_pipeline` is a English model originally trained by STEM-AI-mtl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/city_austronesian_languages_vit_base_patch16_224_pipeline_en_5.5.1_3.0_1737974883583.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/city_austronesian_languages_vit_base_patch16_224_pipeline_en_5.5.1_3.0_1737974883583.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("city_austronesian_languages_vit_base_patch16_224_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("city_austronesian_languages_vit_base_patch16_224_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|city_austronesian_languages_vit_base_patch16_224_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.4 MB|
+
+## References
+
+https://huggingface.co/STEM-AI-mtl/City_map-vit-base-patch16-224
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-climate_sentiment_model_iqrabatool_en.md b/docs/_posts/ahmedlone127/2025-01-27-climate_sentiment_model_iqrabatool_en.md
new file mode 100644
index 00000000000000..cf30cacd62bd9d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-climate_sentiment_model_iqrabatool_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English climate_sentiment_model_iqrabatool DistilBertForSequenceClassification from iqrabatool
+author: John Snow Labs
+name: climate_sentiment_model_iqrabatool
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`climate_sentiment_model_iqrabatool` is a English model originally trained by iqrabatool.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/climate_sentiment_model_iqrabatool_en_5.5.1_3.0_1737939104075.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/climate_sentiment_model_iqrabatool_en_5.5.1_3.0_1737939104075.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("climate_sentiment_model_iqrabatool","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("climate_sentiment_model_iqrabatool", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|climate_sentiment_model_iqrabatool|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/iqrabatool/climate-sentiment-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-climate_sentiment_model_iqrabatool_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-climate_sentiment_model_iqrabatool_pipeline_en.md
new file mode 100644
index 00000000000000..5eb262d1192546
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-climate_sentiment_model_iqrabatool_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English climate_sentiment_model_iqrabatool_pipeline pipeline DistilBertForSequenceClassification from iqrabatool
+author: John Snow Labs
+name: climate_sentiment_model_iqrabatool_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`climate_sentiment_model_iqrabatool_pipeline` is a English model originally trained by iqrabatool.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/climate_sentiment_model_iqrabatool_pipeline_en_5.5.1_3.0_1737939127488.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/climate_sentiment_model_iqrabatool_pipeline_en_5.5.1_3.0_1737939127488.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("climate_sentiment_model_iqrabatool_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("climate_sentiment_model_iqrabatool_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|climate_sentiment_model_iqrabatool_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/iqrabatool/climate-sentiment-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-clip_vit_small_patch16_224_en.md b/docs/_posts/ahmedlone127/2025-01-27-clip_vit_small_patch16_224_en.md
new file mode 100644
index 00000000000000..63d5baef904262
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-clip_vit_small_patch16_224_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English clip_vit_small_patch16_224 ViTForImageClassification from magicslabnu
+author: John Snow Labs
+name: clip_vit_small_patch16_224
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_small_patch16_224` is a English model originally trained by magicslabnu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_small_patch16_224_en_5.5.1_3.0_1738021951710.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_small_patch16_224_en_5.5.1_3.0_1738021951710.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""clip_vit_small_patch16_224","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("clip_vit_small_patch16_224","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_vit_small_patch16_224|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|82.6 MB|
+
+## References
+
+https://huggingface.co/magicslabnu/clip_vit_small_patch16_224
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-clip_vit_small_patch16_224_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-clip_vit_small_patch16_224_pipeline_en.md
new file mode 100644
index 00000000000000..fd35e1cec35ebd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-clip_vit_small_patch16_224_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English clip_vit_small_patch16_224_pipeline pipeline ViTForImageClassification from magicslabnu
+author: John Snow Labs
+name: clip_vit_small_patch16_224_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_small_patch16_224_pipeline` is a English model originally trained by magicslabnu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_vit_small_patch16_224_pipeline_en_5.5.1_3.0_1738021955599.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_small_patch16_224_pipeline_en_5.5.1_3.0_1738021955599.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("clip_vit_small_patch16_224_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("clip_vit_small_patch16_224_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_vit_small_patch16_224_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|82.7 MB|
+
+## References
+
+https://huggingface.co/magicslabnu/clip_vit_small_patch16_224
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-cnn_dailymail_summarizer_en.md b/docs/_posts/ahmedlone127/2025-01-27-cnn_dailymail_summarizer_en.md
new file mode 100644
index 00000000000000..4d39d2839d906f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-cnn_dailymail_summarizer_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English cnn_dailymail_summarizer T5Transformer from ngchuchi
+author: John Snow Labs
+name: cnn_dailymail_summarizer
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cnn_dailymail_summarizer` is a English model originally trained by ngchuchi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cnn_dailymail_summarizer_en_5.5.1_3.0_1738007575090.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cnn_dailymail_summarizer_en_5.5.1_3.0_1738007575090.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("cnn_dailymail_summarizer","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("cnn_dailymail_summarizer", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cnn_dailymail_summarizer|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|272.6 MB|
+
+## References
+
+https://huggingface.co/ngchuchi/cnn_dailymail_summarizer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-cnn_dailymail_summarizer_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-cnn_dailymail_summarizer_pipeline_en.md
new file mode 100644
index 00000000000000..81da70406caa99
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-cnn_dailymail_summarizer_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English cnn_dailymail_summarizer_pipeline pipeline T5Transformer from ngchuchi
+author: John Snow Labs
+name: cnn_dailymail_summarizer_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cnn_dailymail_summarizer_pipeline` is a English model originally trained by ngchuchi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cnn_dailymail_summarizer_pipeline_en_5.5.1_3.0_1738007592596.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cnn_dailymail_summarizer_pipeline_en_5.5.1_3.0_1738007592596.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("cnn_dailymail_summarizer_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cnn_dailymail_summarizer_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cnn_dailymail_summarizer_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|272.6 MB|
+
+## References
+
+https://huggingface.co/ngchuchi/cnn_dailymail_summarizer
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-colombian_sign_language_small_unbiased_random_20_en.md b/docs/_posts/ahmedlone127/2025-01-27-colombian_sign_language_small_unbiased_random_20_en.md
new file mode 100644
index 00000000000000..27d048fb5ba298
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-colombian_sign_language_small_unbiased_random_20_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English colombian_sign_language_small_unbiased_random_20 RoBertaEmbeddings from PELAB-LiU
+author: John Snow Labs
+name: colombian_sign_language_small_unbiased_random_20
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`colombian_sign_language_small_unbiased_random_20` is a English model originally trained by PELAB-LiU.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/colombian_sign_language_small_unbiased_random_20_en_5.5.1_3.0_1737965612995.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/colombian_sign_language_small_unbiased_random_20_en_5.5.1_3.0_1737965612995.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("colombian_sign_language_small_unbiased_random_20","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("colombian_sign_language_small_unbiased_random_20","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|colombian_sign_language_small_unbiased_random_20|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|470.6 MB|
+
+## References
+
+https://huggingface.co/PELAB-LiU/csn-small-unbiased-random-20
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-colombian_sign_language_small_unbiased_random_20_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-colombian_sign_language_small_unbiased_random_20_pipeline_en.md
new file mode 100644
index 00000000000000..e73f28deb01a9c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-colombian_sign_language_small_unbiased_random_20_pipeline_en.md
@@ -0,0 +1,72 @@
+---
+layout: model
+title: English colombian_sign_language_small_unbiased_random_20_pipeline pipeline RoBertaEmbeddings from antolin
+author: John Snow Labs
+name: colombian_sign_language_small_unbiased_random_20_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`colombian_sign_language_small_unbiased_random_20_pipeline` is a English model originally trained by antolin.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/colombian_sign_language_small_unbiased_random_20_pipeline_en_5.5.1_3.0_1737965648619.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/colombian_sign_language_small_unbiased_random_20_pipeline_en_5.5.1_3.0_1737965648619.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("colombian_sign_language_small_unbiased_random_20_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("colombian_sign_language_small_unbiased_random_20_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|colombian_sign_language_small_unbiased_random_20_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|470.6 MB|
+
+## References
+
+References
+
+https://huggingface.co/antolin/csn-small-unbiased-random-20
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-comparacion_t5_v1_en.md b/docs/_posts/ahmedlone127/2025-01-27-comparacion_t5_v1_en.md
new file mode 100644
index 00000000000000..d95998875be8f0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-comparacion_t5_v1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English comparacion_t5_v1 T5Transformer from MartinElMolon
+author: John Snow Labs
+name: comparacion_t5_v1
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`comparacion_t5_v1` is a English model originally trained by MartinElMolon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/comparacion_t5_v1_en_5.5.1_3.0_1737989201464.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/comparacion_t5_v1_en_5.5.1_3.0_1737989201464.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("comparacion_t5_v1","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("comparacion_t5_v1", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|comparacion_t5_v1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|994.6 MB|
+
+## References
+
+https://huggingface.co/MartinElMolon/comparacion_T5_v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-comparacion_t5_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-comparacion_t5_v1_pipeline_en.md
new file mode 100644
index 00000000000000..a3308ca7a4047e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-comparacion_t5_v1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English comparacion_t5_v1_pipeline pipeline T5Transformer from MartinElMolon
+author: John Snow Labs
+name: comparacion_t5_v1_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`comparacion_t5_v1_pipeline` is a English model originally trained by MartinElMolon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/comparacion_t5_v1_pipeline_en_5.5.1_3.0_1737989253166.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/comparacion_t5_v1_pipeline_en_5.5.1_3.0_1737989253166.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("comparacion_t5_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("comparacion_t5_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|comparacion_t5_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|994.6 MB|
+
+## References
+
+https://huggingface.co/MartinElMolon/comparacion_T5_v1
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-conference_qa_model_en.md b/docs/_posts/ahmedlone127/2025-01-27-conference_qa_model_en.md
new file mode 100644
index 00000000000000..baa7ed74c55cd8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-conference_qa_model_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English conference_qa_model DistilBertForQuestionAnswering from Acavent
+author: John Snow Labs
+name: conference_qa_model
+date: 2025-01-27
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`conference_qa_model` is a English model originally trained by Acavent.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/conference_qa_model_en_5.5.1_3.0_1737973813822.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/conference_qa_model_en_5.5.1_3.0_1737973813822.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("conference_qa_model","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("conference_qa_model", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|conference_qa_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Acavent/conference-qa-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-conference_qa_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-conference_qa_model_pipeline_en.md
new file mode 100644
index 00000000000000..470b5ba3114ef2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-conference_qa_model_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English conference_qa_model_pipeline pipeline DistilBertForQuestionAnswering from Acavent
+author: John Snow Labs
+name: conference_qa_model_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`conference_qa_model_pipeline` is a English model originally trained by Acavent.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/conference_qa_model_pipeline_en_5.5.1_3.0_1737973833442.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/conference_qa_model_pipeline_en_5.5.1_3.0_1737973833442.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("conference_qa_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("conference_qa_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|conference_qa_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Acavent/conference-qa-model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-conflibert_scr_uncased_en.md b/docs/_posts/ahmedlone127/2025-01-27-conflibert_scr_uncased_en.md
new file mode 100644
index 00000000000000..83aff40b3f0132
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-conflibert_scr_uncased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English conflibert_scr_uncased BertEmbeddings from eventdata-utd
+author: John Snow Labs
+name: conflibert_scr_uncased
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`conflibert_scr_uncased` is a English model originally trained by eventdata-utd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/conflibert_scr_uncased_en_5.5.1_3.0_1737984901279.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/conflibert_scr_uncased_en_5.5.1_3.0_1737984901279.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("conflibert_scr_uncased","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("conflibert_scr_uncased","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|conflibert_scr_uncased|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|406.0 MB|
+
+## References
+
+https://huggingface.co/eventdata-utd/ConfliBERT-scr-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-conflibert_scr_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-conflibert_scr_uncased_pipeline_en.md
new file mode 100644
index 00000000000000..5e6994635e7db7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-conflibert_scr_uncased_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English conflibert_scr_uncased_pipeline pipeline BertEmbeddings from eventdata-utd
+author: John Snow Labs
+name: conflibert_scr_uncased_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`conflibert_scr_uncased_pipeline` is a English model originally trained by eventdata-utd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/conflibert_scr_uncased_pipeline_en_5.5.1_3.0_1737984922406.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/conflibert_scr_uncased_pipeline_en_5.5.1_3.0_1737984922406.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("conflibert_scr_uncased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("conflibert_scr_uncased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|conflibert_scr_uncased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.0 MB|
+
+## References
+
+https://huggingface.co/eventdata-utd/ConfliBERT-scr-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-conservation_status_en.md b/docs/_posts/ahmedlone127/2025-01-27-conservation_status_en.md
new file mode 100644
index 00000000000000..c5cfd092280277
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-conservation_status_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English conservation_status ViTForImageClassification from JuanMa360
+author: John Snow Labs
+name: conservation_status
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`conservation_status` is a English model originally trained by JuanMa360.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/conservation_status_en_5.5.1_3.0_1738021523286.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/conservation_status_en_5.5.1_3.0_1738021523286.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""conservation_status","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("conservation_status","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|conservation_status|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/JuanMa360/conservation_status
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-conservation_status_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-conservation_status_pipeline_en.md
new file mode 100644
index 00000000000000..45304955553c92
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-conservation_status_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English conservation_status_pipeline pipeline ViTForImageClassification from JuanMa360
+author: John Snow Labs
+name: conservation_status_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`conservation_status_pipeline` is a English model originally trained by JuanMa360.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/conservation_status_pipeline_en_5.5.1_3.0_1738021539399.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/conservation_status_pipeline_en_5.5.1_3.0_1738021539399.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("conservation_status_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("conservation_status_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|conservation_status_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/JuanMa360/conservation_status
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-cs221_xlm_roberta_base_finetuned_semeval_en.md b/docs/_posts/ahmedlone127/2025-01-27-cs221_xlm_roberta_base_finetuned_semeval_en.md
new file mode 100644
index 00000000000000..79353ff1a967b9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-cs221_xlm_roberta_base_finetuned_semeval_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English cs221_xlm_roberta_base_finetuned_semeval XlmRoBertaForSequenceClassification from Kuongan
+author: John Snow Labs
+name: cs221_xlm_roberta_base_finetuned_semeval
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cs221_xlm_roberta_base_finetuned_semeval` is a English model originally trained by Kuongan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cs221_xlm_roberta_base_finetuned_semeval_en_5.5.1_3.0_1737959180514.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cs221_xlm_roberta_base_finetuned_semeval_en_5.5.1_3.0_1737959180514.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("cs221_xlm_roberta_base_finetuned_semeval","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("cs221_xlm_roberta_base_finetuned_semeval", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cs221_xlm_roberta_base_finetuned_semeval|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|802.9 MB|
+
+## References
+
+https://huggingface.co/Kuongan/CS221-xlm-roberta-base-finetuned-semeval
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-cs221_xlm_roberta_base_finetuned_semeval_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-cs221_xlm_roberta_base_finetuned_semeval_pipeline_en.md
new file mode 100644
index 00000000000000..a6cdd6a5cb7011
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-cs221_xlm_roberta_base_finetuned_semeval_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English cs221_xlm_roberta_base_finetuned_semeval_pipeline pipeline XlmRoBertaForSequenceClassification from Kuongan
+author: John Snow Labs
+name: cs221_xlm_roberta_base_finetuned_semeval_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cs221_xlm_roberta_base_finetuned_semeval_pipeline` is a English model originally trained by Kuongan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cs221_xlm_roberta_base_finetuned_semeval_pipeline_en_5.5.1_3.0_1737959301779.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cs221_xlm_roberta_base_finetuned_semeval_pipeline_en_5.5.1_3.0_1737959301779.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("cs221_xlm_roberta_base_finetuned_semeval_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cs221_xlm_roberta_base_finetuned_semeval_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cs221_xlm_roberta_base_finetuned_semeval_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|802.9 MB|
+
+## References
+
+https://huggingface.co/Kuongan/CS221-xlm-roberta-base-finetuned-semeval
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-danskbert_ncs_en.md b/docs/_posts/ahmedlone127/2025-01-27-danskbert_ncs_en.md
new file mode 100644
index 00000000000000..7d3ad27c3b41f3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-danskbert_ncs_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English danskbert_ncs XlmRoBertaForSequenceClassification from yemen2016
+author: John Snow Labs
+name: danskbert_ncs
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`danskbert_ncs` is a English model originally trained by yemen2016.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/danskbert_ncs_en_5.5.1_3.0_1737959128772.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/danskbert_ncs_en_5.5.1_3.0_1737959128772.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("danskbert_ncs","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("danskbert_ncs", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|danskbert_ncs|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|436.2 MB|
+
+## References
+
+https://huggingface.co/yemen2016/danskbert_NCS
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-danskbert_ncs_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-danskbert_ncs_pipeline_en.md
new file mode 100644
index 00000000000000..12482f6326430f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-danskbert_ncs_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English danskbert_ncs_pipeline pipeline XlmRoBertaForSequenceClassification from yemen2016
+author: John Snow Labs
+name: danskbert_ncs_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`danskbert_ncs_pipeline` is a English model originally trained by yemen2016.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/danskbert_ncs_pipeline_en_5.5.1_3.0_1737959162693.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/danskbert_ncs_pipeline_en_5.5.1_3.0_1737959162693.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("danskbert_ncs_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("danskbert_ncs_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|danskbert_ncs_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|436.3 MB|
+
+## References
+
+https://huggingface.co/yemen2016/danskbert_NCS
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-darkmatter_gpt2_small_x343_en.md b/docs/_posts/ahmedlone127/2025-01-27-darkmatter_gpt2_small_x343_en.md
new file mode 100644
index 00000000000000..48da397d5b3f22
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-darkmatter_gpt2_small_x343_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English darkmatter_gpt2_small_x343 GPT2Transformer from stanford-crfm
+author: John Snow Labs
+name: darkmatter_gpt2_small_x343
+date: 2025-01-27
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`darkmatter_gpt2_small_x343` is a English model originally trained by stanford-crfm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/darkmatter_gpt2_small_x343_en_5.5.1_3.0_1737997685824.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/darkmatter_gpt2_small_x343_en_5.5.1_3.0_1737997685824.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("darkmatter_gpt2_small_x343","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("darkmatter_gpt2_small_x343","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|darkmatter_gpt2_small_x343|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|299.3 MB|
+
+## References
+
+https://huggingface.co/stanford-crfm/darkmatter-gpt2-small-x343
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-darkmatter_gpt2_small_x343_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-darkmatter_gpt2_small_x343_pipeline_en.md
new file mode 100644
index 00000000000000..28d3ae91d60f00
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-darkmatter_gpt2_small_x343_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English darkmatter_gpt2_small_x343_pipeline pipeline GPT2Transformer from stanford-crfm
+author: John Snow Labs
+name: darkmatter_gpt2_small_x343_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`darkmatter_gpt2_small_x343_pipeline` is a English model originally trained by stanford-crfm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/darkmatter_gpt2_small_x343_pipeline_en_5.5.1_3.0_1737997773259.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/darkmatter_gpt2_small_x343_pipeline_en_5.5.1_3.0_1737997773259.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("darkmatter_gpt2_small_x343_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("darkmatter_gpt2_small_x343_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|darkmatter_gpt2_small_x343_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|299.3 MB|
+
+## References
+
+https://huggingface.co/stanford-crfm/darkmatter-gpt2-small-x343
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-deepfake_vs_real_image_detection_dima806_en.md b/docs/_posts/ahmedlone127/2025-01-27-deepfake_vs_real_image_detection_dima806_en.md
new file mode 100644
index 00000000000000..88f6fc14f3dd63
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-deepfake_vs_real_image_detection_dima806_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deepfake_vs_real_image_detection_dima806 ViTForImageClassification from dima806
+author: John Snow Labs
+name: deepfake_vs_real_image_detection_dima806
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deepfake_vs_real_image_detection_dima806` is a English model originally trained by dima806.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deepfake_vs_real_image_detection_dima806_en_5.5.1_3.0_1737957391783.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deepfake_vs_real_image_detection_dima806_en_5.5.1_3.0_1737957391783.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""deepfake_vs_real_image_detection_dima806","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("deepfake_vs_real_image_detection_dima806","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deepfake_vs_real_image_detection_dima806|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/dima806/deepfake_vs_real_image_detection
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-deepfake_vs_real_image_detection_dima806_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-deepfake_vs_real_image_detection_dima806_pipeline_en.md
new file mode 100644
index 00000000000000..153395d0d6f821
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-deepfake_vs_real_image_detection_dima806_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English deepfake_vs_real_image_detection_dima806_pipeline pipeline ViTForImageClassification from dima806
+author: John Snow Labs
+name: deepfake_vs_real_image_detection_dima806_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deepfake_vs_real_image_detection_dima806_pipeline` is a English model originally trained by dima806.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deepfake_vs_real_image_detection_dima806_pipeline_en_5.5.1_3.0_1737957408958.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deepfake_vs_real_image_detection_dima806_pipeline_en_5.5.1_3.0_1737957408958.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deepfake_vs_real_image_detection_dima806_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deepfake_vs_real_image_detection_dima806_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deepfake_vs_real_image_detection_dima806_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/dima806/deepfake_vs_real_image_detection
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-deit_cifar100_en.md b/docs/_posts/ahmedlone127/2025-01-27-deit_cifar100_en.md
new file mode 100644
index 00000000000000..9079b91f7889dd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-deit_cifar100_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deit_cifar100 ViTForImageClassification from tzhao3
+author: John Snow Labs
+name: deit_cifar100
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deit_cifar100` is a English model originally trained by tzhao3.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deit_cifar100_en_5.5.1_3.0_1737974376951.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deit_cifar100_en_5.5.1_3.0_1737974376951.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""deit_cifar100","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("deit_cifar100","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deit_cifar100|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.5 MB|
+
+## References
+
+https://huggingface.co/tzhao3/DeiT-CIFAR100
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-deit_cifar100_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-deit_cifar100_pipeline_en.md
new file mode 100644
index 00000000000000..05f95c08795c09
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-deit_cifar100_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English deit_cifar100_pipeline pipeline ViTForImageClassification from tzhao3
+author: John Snow Labs
+name: deit_cifar100_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deit_cifar100_pipeline` is a English model originally trained by tzhao3.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deit_cifar100_pipeline_en_5.5.1_3.0_1737974393913.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deit_cifar100_pipeline_en_5.5.1_3.0_1737974393913.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deit_cifar100_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deit_cifar100_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deit_cifar100_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.5 MB|
+
+## References
+
+https://huggingface.co/tzhao3/DeiT-CIFAR100
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-devops_log_classifier_en.md b/docs/_posts/ahmedlone127/2025-01-27-devops_log_classifier_en.md
new file mode 100644
index 00000000000000..65e5017caeb079
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-devops_log_classifier_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English devops_log_classifier DistilBertForSequenceClassification from satishgonella
+author: John Snow Labs
+name: devops_log_classifier
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`devops_log_classifier` is a English model originally trained by satishgonella.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/devops_log_classifier_en_5.5.1_3.0_1737939224169.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/devops_log_classifier_en_5.5.1_3.0_1737939224169.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("devops_log_classifier","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("devops_log_classifier", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|devops_log_classifier|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/satishgonella/devops-log-classifier
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-devops_log_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-devops_log_classifier_pipeline_en.md
new file mode 100644
index 00000000000000..abd248e3b83fde
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-devops_log_classifier_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English devops_log_classifier_pipeline pipeline DistilBertForSequenceClassification from satishgonella
+author: John Snow Labs
+name: devops_log_classifier_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`devops_log_classifier_pipeline` is a English model originally trained by satishgonella.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/devops_log_classifier_pipeline_en_5.5.1_3.0_1737939237577.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/devops_log_classifier_pipeline_en_5.5.1_3.0_1737939237577.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("devops_log_classifier_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("devops_log_classifier_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|devops_log_classifier_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/satishgonella/devops-log-classifier
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-dialogpt_rabbiaaa_en.md b/docs/_posts/ahmedlone127/2025-01-27-dialogpt_rabbiaaa_en.md
new file mode 100644
index 00000000000000..ba61a977edaf0d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-dialogpt_rabbiaaa_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English dialogpt_rabbiaaa GPT2Transformer from Rabbiaaa
+author: John Snow Labs
+name: dialogpt_rabbiaaa
+date: 2025-01-27
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dialogpt_rabbiaaa` is a English model originally trained by Rabbiaaa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dialogpt_rabbiaaa_en_5.5.1_3.0_1738003676293.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dialogpt_rabbiaaa_en_5.5.1_3.0_1738003676293.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("dialogpt_rabbiaaa","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("dialogpt_rabbiaaa","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dialogpt_rabbiaaa|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|308.4 MB|
+
+## References
+
+https://huggingface.co/Rabbiaaa/DialoGPT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-dialogpt_rabbiaaa_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-dialogpt_rabbiaaa_pipeline_en.md
new file mode 100644
index 00000000000000..ce532a5228aab6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-dialogpt_rabbiaaa_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English dialogpt_rabbiaaa_pipeline pipeline GPT2Transformer from Rabbiaaa
+author: John Snow Labs
+name: dialogpt_rabbiaaa_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dialogpt_rabbiaaa_pipeline` is a English model originally trained by Rabbiaaa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dialogpt_rabbiaaa_pipeline_en_5.5.1_3.0_1738003692818.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dialogpt_rabbiaaa_pipeline_en_5.5.1_3.0_1738003692818.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dialogpt_rabbiaaa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dialogpt_rabbiaaa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dialogpt_rabbiaaa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|308.4 MB|
+
+## References
+
+https://huggingface.co/Rabbiaaa/DialoGPT
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-diffusion_robustness_20ng_en.md b/docs/_posts/ahmedlone127/2025-01-27-diffusion_robustness_20ng_en.md
new file mode 100644
index 00000000000000..1a86b76ce41886
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-diffusion_robustness_20ng_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English diffusion_robustness_20ng RoBertaEmbeddings from Maybe1407
+author: John Snow Labs
+name: diffusion_robustness_20ng
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`diffusion_robustness_20ng` is a English model originally trained by Maybe1407.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/diffusion_robustness_20ng_en_5.5.1_3.0_1738019850424.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/diffusion_robustness_20ng_en_5.5.1_3.0_1738019850424.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("diffusion_robustness_20ng","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("diffusion_robustness_20ng","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|diffusion_robustness_20ng|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/Maybe1407/diffusion_robustness_20ng
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-diffusion_robustness_20ng_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-diffusion_robustness_20ng_pipeline_en.md
new file mode 100644
index 00000000000000..20b05ec9e95bb0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-diffusion_robustness_20ng_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English diffusion_robustness_20ng_pipeline pipeline RoBertaEmbeddings from Maybe1407
+author: John Snow Labs
+name: diffusion_robustness_20ng_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`diffusion_robustness_20ng_pipeline` is a English model originally trained by Maybe1407.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/diffusion_robustness_20ng_pipeline_en_5.5.1_3.0_1738019914332.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/diffusion_robustness_20ng_pipeline_en_5.5.1_3.0_1738019914332.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("diffusion_robustness_20ng_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("diffusion_robustness_20ng_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|diffusion_robustness_20ng_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/Maybe1407/diffusion_robustness_20ng
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-diffusion_robustness_sst2_en.md b/docs/_posts/ahmedlone127/2025-01-27-diffusion_robustness_sst2_en.md
new file mode 100644
index 00000000000000..a3f9f0ad094672
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-diffusion_robustness_sst2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English diffusion_robustness_sst2 RoBertaEmbeddings from Maybe1407
+author: John Snow Labs
+name: diffusion_robustness_sst2
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`diffusion_robustness_sst2` is a English model originally trained by Maybe1407.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/diffusion_robustness_sst2_en_5.5.1_3.0_1737965601325.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/diffusion_robustness_sst2_en_5.5.1_3.0_1737965601325.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("diffusion_robustness_sst2","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("diffusion_robustness_sst2","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|diffusion_robustness_sst2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/Maybe1407/diffusion_robustness_sst2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-diffusion_robustness_sst2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-diffusion_robustness_sst2_pipeline_en.md
new file mode 100644
index 00000000000000..f39c31b2e9b586
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-diffusion_robustness_sst2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English diffusion_robustness_sst2_pipeline pipeline RoBertaEmbeddings from Maybe1407
+author: John Snow Labs
+name: diffusion_robustness_sst2_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`diffusion_robustness_sst2_pipeline` is a English model originally trained by Maybe1407.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/diffusion_robustness_sst2_pipeline_en_5.5.1_3.0_1737965670551.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/diffusion_robustness_sst2_pipeline_en_5.5.1_3.0_1737965670551.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("diffusion_robustness_sst2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("diffusion_robustness_sst2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|diffusion_robustness_sst2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/Maybe1407/diffusion_robustness_sst2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-diffusion_robustness_trec_en.md b/docs/_posts/ahmedlone127/2025-01-27-diffusion_robustness_trec_en.md
new file mode 100644
index 00000000000000..511a8aec4afd0c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-diffusion_robustness_trec_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English diffusion_robustness_trec RoBertaEmbeddings from Maybe1407
+author: John Snow Labs
+name: diffusion_robustness_trec
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`diffusion_robustness_trec` is a English model originally trained by Maybe1407.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/diffusion_robustness_trec_en_5.5.1_3.0_1737965909675.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/diffusion_robustness_trec_en_5.5.1_3.0_1737965909675.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("diffusion_robustness_trec","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("diffusion_robustness_trec","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|diffusion_robustness_trec|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/Maybe1407/diffusion_robustness_trec
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-diffusion_robustness_trec_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-diffusion_robustness_trec_pipeline_en.md
new file mode 100644
index 00000000000000..6fece9f5ab6fe1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-diffusion_robustness_trec_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English diffusion_robustness_trec_pipeline pipeline RoBertaEmbeddings from Maybe1407
+author: John Snow Labs
+name: diffusion_robustness_trec_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`diffusion_robustness_trec_pipeline` is a English model originally trained by Maybe1407.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/diffusion_robustness_trec_pipeline_en_5.5.1_3.0_1737965976801.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/diffusion_robustness_trec_pipeline_en_5.5.1_3.0_1737965976801.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("diffusion_robustness_trec_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("diffusion_robustness_trec_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|diffusion_robustness_trec_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/Maybe1407/diffusion_robustness_trec
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-dishesqamodel_en.md b/docs/_posts/ahmedlone127/2025-01-27-dishesqamodel_en.md
new file mode 100644
index 00000000000000..54545da0bbbbb6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-dishesqamodel_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English dishesqamodel T5Transformer from Smrfhdl
+author: John Snow Labs
+name: dishesqamodel
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dishesqamodel` is a English model originally trained by Smrfhdl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dishesqamodel_en_5.5.1_3.0_1738000013157.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dishesqamodel_en_5.5.1_3.0_1738000013157.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("dishesqamodel","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("dishesqamodel", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dishesqamodel|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|349.8 MB|
+
+## References
+
+https://huggingface.co/Smrfhdl/DishesQAModel
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-dishesqamodel_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-dishesqamodel_pipeline_en.md
new file mode 100644
index 00000000000000..29e173ffa774cb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-dishesqamodel_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English dishesqamodel_pipeline pipeline T5Transformer from Smrfhdl
+author: John Snow Labs
+name: dishesqamodel_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dishesqamodel_pipeline` is a English model originally trained by Smrfhdl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dishesqamodel_pipeline_en_5.5.1_3.0_1738000032062.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dishesqamodel_pipeline_en_5.5.1_3.0_1738000032062.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dishesqamodel_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dishesqamodel_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dishesqamodel_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|349.8 MB|
+
+## References
+
+https://huggingface.co/Smrfhdl/DishesQAModel
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-disorroberta_en.md b/docs/_posts/ahmedlone127/2025-01-27-disorroberta_en.md
new file mode 100644
index 00000000000000..280c49184c915f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-disorroberta_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English disorroberta RoBertaEmbeddings from citiusLTL
+author: John Snow Labs
+name: disorroberta
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`disorroberta` is a English model originally trained by citiusLTL.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/disorroberta_en_5.5.1_3.0_1737966301610.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/disorroberta_en_5.5.1_3.0_1737966301610.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("disorroberta","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("disorroberta","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|disorroberta|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|466.0 MB|
+
+## References
+
+https://huggingface.co/citiusLTL/DisorRoBERTa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-disorroberta_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-disorroberta_pipeline_en.md
new file mode 100644
index 00000000000000..686f137aad2721
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-disorroberta_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English disorroberta_pipeline pipeline RoBertaEmbeddings from citiusLTL
+author: John Snow Labs
+name: disorroberta_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`disorroberta_pipeline` is a English model originally trained by citiusLTL.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/disorroberta_pipeline_en_5.5.1_3.0_1737966325572.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/disorroberta_pipeline_en_5.5.1_3.0_1737966325572.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("disorroberta_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("disorroberta_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|disorroberta_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.1 MB|
+
+## References
+
+https://huggingface.co/citiusLTL/DisorRoBERTa
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilbart_cnn_6_6_sshleifer_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilbart_cnn_6_6_sshleifer_en.md
new file mode 100644
index 00000000000000..e9565138d5d2e1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilbart_cnn_6_6_sshleifer_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilbart_cnn_6_6_sshleifer BartTransformer from sshleifer
+author: John Snow Labs
+name: distilbart_cnn_6_6_sshleifer
+date: 2025-01-27
+tags: [en, open_source, onnx, text_generation, bart]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BartTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbart_cnn_6_6_sshleifer` is a English model originally trained by sshleifer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbart_cnn_6_6_sshleifer_en_5.5.1_3.0_1737987397451.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbart_cnn_6_6_sshleifer_en_5.5.1_3.0_1737987397451.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = BartTransformer.pretrained("distilbart_cnn_6_6_sshleifer","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = BartTransformer.pretrained("distilbart_cnn_6_6_sshleifer","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbart_cnn_6_6_sshleifer|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|796.3 MB|
+
+## References
+
+https://huggingface.co/sshleifer/distilbart-cnn-6-6
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilbart_cnn_6_6_sshleifer_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilbart_cnn_6_6_sshleifer_pipeline_en.md
new file mode 100644
index 00000000000000..d3ebc2934a110e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilbart_cnn_6_6_sshleifer_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbart_cnn_6_6_sshleifer_pipeline pipeline BartTransformer from sshleifer
+author: John Snow Labs
+name: distilbart_cnn_6_6_sshleifer_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbart_cnn_6_6_sshleifer_pipeline` is a English model originally trained by sshleifer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbart_cnn_6_6_sshleifer_pipeline_en_5.5.1_3.0_1737987625060.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbart_cnn_6_6_sshleifer_pipeline_en_5.5.1_3.0_1737987625060.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbart_cnn_6_6_sshleifer_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbart_cnn_6_6_sshleifer_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbart_cnn_6_6_sshleifer_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|796.3 MB|
+
+## References
+
+https://huggingface.co/sshleifer/distilbart-cnn-6-6
+
+## Included Models
+
+- DocumentAssembler
+- BartTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_cased_rocstories_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_cased_rocstories_en.md
new file mode 100644
index 00000000000000..f0f0dcedec2a31
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_cased_rocstories_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_cased_rocstories DistilBertForSequenceClassification from KeiHeityuu
+author: John Snow Labs
+name: distilbert_base_cased_rocstories
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_cased_rocstories` is a English model originally trained by KeiHeityuu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_cased_rocstories_en_5.5.1_3.0_1737939676077.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_cased_rocstories_en_5.5.1_3.0_1737939676077.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_cased_rocstories","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_cased_rocstories", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_cased_rocstories|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|246.0 MB|
+
+## References
+
+https://huggingface.co/KeiHeityuu/distilbert-base-cased-rocstories
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_cased_rocstories_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_cased_rocstories_pipeline_en.md
new file mode 100644
index 00000000000000..5fd5be5c823d9b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_cased_rocstories_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_cased_rocstories_pipeline pipeline DistilBertForSequenceClassification from KeiHeityuu
+author: John Snow Labs
+name: distilbert_base_cased_rocstories_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_cased_rocstories_pipeline` is a English model originally trained by KeiHeityuu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_cased_rocstories_pipeline_en_5.5.1_3.0_1737939689002.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_cased_rocstories_pipeline_en_5.5.1_3.0_1737939689002.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_cased_rocstories_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_cased_rocstories_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_cased_rocstories_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|246.0 MB|
+
+## References
+
+https://huggingface.co/KeiHeityuu/distilbert-base-cased-rocstories
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_multilingual_cased_classification_finetuned_ptt_adptive_pipeline_xx.md b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_multilingual_cased_classification_finetuned_ptt_adptive_pipeline_xx.md
new file mode 100644
index 00000000000000..8f1f1a6f9e5db7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_multilingual_cased_classification_finetuned_ptt_adptive_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual distilbert_base_multilingual_cased_classification_finetuned_ptt_adptive_pipeline pipeline DistilBertForSequenceClassification from Mou11209203
+author: John Snow Labs
+name: distilbert_base_multilingual_cased_classification_finetuned_ptt_adptive_pipeline
+date: 2025-01-27
+tags: [xx, open_source, pipeline, onnx]
+task: Text Classification
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_multilingual_cased_classification_finetuned_ptt_adptive_pipeline` is a Multilingual model originally trained by Mou11209203.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_multilingual_cased_classification_finetuned_ptt_adptive_pipeline_xx_5.5.1_3.0_1737939281822.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_multilingual_cased_classification_finetuned_ptt_adptive_pipeline_xx_5.5.1_3.0_1737939281822.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_multilingual_cased_classification_finetuned_ptt_adptive_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_multilingual_cased_classification_finetuned_ptt_adptive_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_multilingual_cased_classification_finetuned_ptt_adptive_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|507.6 MB|
+
+## References
+
+https://huggingface.co/Mou11209203/distilbert-base-multilingual-cased_classification_finetuned_ptt_adptive
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_multilingual_cased_classification_finetuned_ptt_adptive_xx.md b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_multilingual_cased_classification_finetuned_ptt_adptive_xx.md
new file mode 100644
index 00000000000000..56137c536ffd46
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_multilingual_cased_classification_finetuned_ptt_adptive_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual distilbert_base_multilingual_cased_classification_finetuned_ptt_adptive DistilBertForSequenceClassification from Mou11209203
+author: John Snow Labs
+name: distilbert_base_multilingual_cased_classification_finetuned_ptt_adptive
+date: 2025-01-27
+tags: [xx, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_multilingual_cased_classification_finetuned_ptt_adptive` is a Multilingual model originally trained by Mou11209203.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_multilingual_cased_classification_finetuned_ptt_adptive_xx_5.5.1_3.0_1737939254800.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_multilingual_cased_classification_finetuned_ptt_adptive_xx_5.5.1_3.0_1737939254800.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_multilingual_cased_classification_finetuned_ptt_adptive","xx") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_multilingual_cased_classification_finetuned_ptt_adptive", "xx")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_multilingual_cased_classification_finetuned_ptt_adptive|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|xx|
+|Size:|507.6 MB|
+
+## References
+
+https://huggingface.co/Mou11209203/distilbert-base-multilingual-cased_classification_finetuned_ptt_adptive
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_emotion_ft_1201_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_emotion_ft_1201_en.md
new file mode 100644
index 00000000000000..8fd7bcc4d47261
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_emotion_ft_1201_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_emotion_ft_1201 DistilBertForSequenceClassification from a3467895898
+author: John Snow Labs
+name: distilbert_base_uncased_emotion_ft_1201
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_emotion_ft_1201` is a English model originally trained by a3467895898.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_emotion_ft_1201_en_5.5.1_3.0_1737939791353.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_emotion_ft_1201_en_5.5.1_3.0_1737939791353.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_emotion_ft_1201","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_emotion_ft_1201", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_emotion_ft_1201|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/a3467895898/distilbert-base-uncased_emotion_ft_1201
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_emotion_ft_1201_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_emotion_ft_1201_pipeline_en.md
new file mode 100644
index 00000000000000..c125e99550e2a2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_emotion_ft_1201_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_emotion_ft_1201_pipeline pipeline DistilBertForSequenceClassification from a3467895898
+author: John Snow Labs
+name: distilbert_base_uncased_emotion_ft_1201_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_emotion_ft_1201_pipeline` is a English model originally trained by a3467895898.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_emotion_ft_1201_pipeline_en_5.5.1_3.0_1737939807463.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_emotion_ft_1201_pipeline_en_5.5.1_3.0_1737939807463.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_emotion_ft_1201_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_emotion_ft_1201_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_emotion_ft_1201_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/a3467895898/distilbert-base-uncased_emotion_ft_1201
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_cola_vegetable_plane_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_cola_vegetable_plane_en.md
new file mode 100644
index 00000000000000..a675c185b98ef2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_cola_vegetable_plane_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_cola_vegetable_plane DistilBertForSequenceClassification from vegetable-plane
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_cola_vegetable_plane
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_cola_vegetable_plane` is a English model originally trained by vegetable-plane.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_cola_vegetable_plane_en_5.5.1_3.0_1737939852583.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_cola_vegetable_plane_en_5.5.1_3.0_1737939852583.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_cola_vegetable_plane","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_cola_vegetable_plane", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_cola_vegetable_plane|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/vegetable-plane/distilbert-base-uncased-finetuned-cola
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_cola_vegetable_plane_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_cola_vegetable_plane_pipeline_en.md
new file mode 100644
index 00000000000000..4d5032249fc5e6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_cola_vegetable_plane_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_cola_vegetable_plane_pipeline pipeline DistilBertForSequenceClassification from vegetable-plane
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_cola_vegetable_plane_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_cola_vegetable_plane_pipeline` is a English model originally trained by vegetable-plane.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_cola_vegetable_plane_pipeline_en_5.5.1_3.0_1737939866646.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_cola_vegetable_plane_pipeline_en_5.5.1_3.0_1737939866646.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_cola_vegetable_plane_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_cola_vegetable_plane_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_cola_vegetable_plane_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/vegetable-plane/distilbert-base-uncased-finetuned-cola
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_emotion_dailab_bitesnail_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_emotion_dailab_bitesnail_en.md
new file mode 100644
index 00000000000000..91311b44115561
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_emotion_dailab_bitesnail_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_dailab_bitesnail DistilBertForSequenceClassification from DAILAB-bitesnail
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_dailab_bitesnail
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_dailab_bitesnail` is a English model originally trained by DAILAB-bitesnail.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_dailab_bitesnail_en_5.5.1_3.0_1737939538080.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_dailab_bitesnail_en_5.5.1_3.0_1737939538080.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_dailab_bitesnail","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_dailab_bitesnail", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_dailab_bitesnail|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/DAILAB-bitesnail/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_emotion_dailab_bitesnail_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_emotion_dailab_bitesnail_pipeline_en.md
new file mode 100644
index 00000000000000..a0659de29d479b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_emotion_dailab_bitesnail_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_dailab_bitesnail_pipeline pipeline DistilBertForSequenceClassification from DAILAB-bitesnail
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_dailab_bitesnail_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_dailab_bitesnail_pipeline` is a English model originally trained by DAILAB-bitesnail.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_dailab_bitesnail_pipeline_en_5.5.1_3.0_1737939553501.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_dailab_bitesnail_pipeline_en_5.5.1_3.0_1737939553501.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_dailab_bitesnail_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_dailab_bitesnail_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_dailab_bitesnail_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/DAILAB-bitesnail/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_emotion_gidong_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_emotion_gidong_en.md
new file mode 100644
index 00000000000000..3b441d8c442bc9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_emotion_gidong_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_gidong DistilBertForSequenceClassification from Gidong
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_gidong
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_gidong` is a English model originally trained by Gidong.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_gidong_en_5.5.1_3.0_1737939450369.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_gidong_en_5.5.1_3.0_1737939450369.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_gidong","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_gidong", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_gidong|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Gidong/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_emotion_gidong_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_emotion_gidong_pipeline_en.md
new file mode 100644
index 00000000000000..f13fd5b63a13d4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_emotion_gidong_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_gidong_pipeline pipeline DistilBertForSequenceClassification from Gidong
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_gidong_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_gidong_pipeline` is a English model originally trained by Gidong.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_gidong_pipeline_en_5.5.1_3.0_1737939463622.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_gidong_pipeline_en_5.5.1_3.0_1737939463622.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_gidong_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_gidong_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_gidong_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Gidong/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_emotion_hongbanjang_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_emotion_hongbanjang_en.md
new file mode 100644
index 00000000000000..843386da1c2b88
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_emotion_hongbanjang_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_hongbanjang DistilBertForSequenceClassification from Hongbanjang
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_hongbanjang
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_hongbanjang` is a English model originally trained by Hongbanjang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_hongbanjang_en_5.5.1_3.0_1737940126416.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_hongbanjang_en_5.5.1_3.0_1737940126416.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_hongbanjang","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_hongbanjang", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_hongbanjang|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Hongbanjang/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_emotion_hongbanjang_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_emotion_hongbanjang_pipeline_en.md
new file mode 100644
index 00000000000000..1284c6c135cefa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_emotion_hongbanjang_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_hongbanjang_pipeline pipeline DistilBertForSequenceClassification from Hongbanjang
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_hongbanjang_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_hongbanjang_pipeline` is a English model originally trained by Hongbanjang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_hongbanjang_pipeline_en_5.5.1_3.0_1737940139544.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_hongbanjang_pipeline_en_5.5.1_3.0_1737940139544.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_hongbanjang_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_hongbanjang_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_hongbanjang_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Hongbanjang/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_emotion_omar22allam_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_emotion_omar22allam_en.md
new file mode 100644
index 00000000000000..644e99fc9af655
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_emotion_omar22allam_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_omar22allam DistilBertForSequenceClassification from omar22allam
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_omar22allam
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_omar22allam` is a English model originally trained by omar22allam.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_omar22allam_en_5.5.1_3.0_1737939227760.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_omar22allam_en_5.5.1_3.0_1737939227760.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_omar22allam","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_omar22allam", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_omar22allam|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/omar22allam/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_emotion_omar22allam_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_emotion_omar22allam_pipeline_en.md
new file mode 100644
index 00000000000000..7397d3c43f38b0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_emotion_omar22allam_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_omar22allam_pipeline pipeline DistilBertForSequenceClassification from omar22allam
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_omar22allam_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_omar22allam_pipeline` is a English model originally trained by omar22allam.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_omar22allam_pipeline_en_5.5.1_3.0_1737939242053.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_omar22allam_pipeline_en_5.5.1_3.0_1737939242053.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_omar22allam_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_omar22allam_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_omar22allam_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/omar22allam/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_emotion_panupanjanin_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_emotion_panupanjanin_en.md
new file mode 100644
index 00000000000000..11c71de8e38065
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_emotion_panupanjanin_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_panupanjanin DistilBertForSequenceClassification from PanupanJanin
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_panupanjanin
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_panupanjanin` is a English model originally trained by PanupanJanin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_panupanjanin_en_5.5.1_3.0_1737939439141.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_panupanjanin_en_5.5.1_3.0_1737939439141.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_panupanjanin","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_panupanjanin", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_panupanjanin|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/PanupanJanin/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_emotion_panupanjanin_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_emotion_panupanjanin_pipeline_en.md
new file mode 100644
index 00000000000000..80ef1cad743e07
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_emotion_panupanjanin_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_panupanjanin_pipeline pipeline DistilBertForSequenceClassification from PanupanJanin
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_panupanjanin_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_panupanjanin_pipeline` is a English model originally trained by PanupanJanin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_panupanjanin_pipeline_en_5.5.1_3.0_1737939453059.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_panupanjanin_pipeline_en_5.5.1_3.0_1737939453059.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_panupanjanin_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_panupanjanin_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_panupanjanin_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/PanupanJanin/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_emotion_paulovsantanas_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_emotion_paulovsantanas_en.md
new file mode 100644
index 00000000000000..ccd56b59fccd1d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_emotion_paulovsantanas_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_paulovsantanas DistilBertForSequenceClassification from paulovsantanas
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_paulovsantanas
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_paulovsantanas` is a English model originally trained by paulovsantanas.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_paulovsantanas_en_5.5.1_3.0_1737939226687.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_paulovsantanas_en_5.5.1_3.0_1737939226687.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_paulovsantanas","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_paulovsantanas", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_paulovsantanas|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/paulovsantanas/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_emotion_paulovsantanas_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_emotion_paulovsantanas_pipeline_en.md
new file mode 100644
index 00000000000000..fe3d0fae2849f3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_emotion_paulovsantanas_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_paulovsantanas_pipeline pipeline DistilBertForSequenceClassification from paulovsantanas
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_paulovsantanas_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_paulovsantanas_pipeline` is a English model originally trained by paulovsantanas.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_paulovsantanas_pipeline_en_5.5.1_3.0_1737939245838.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_paulovsantanas_pipeline_en_5.5.1_3.0_1737939245838.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_paulovsantanas_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_paulovsantanas_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_paulovsantanas_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/paulovsantanas/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_imdb_afazrihady_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_imdb_afazrihady_en.md
new file mode 100644
index 00000000000000..56fd1c421f8e52
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_imdb_afazrihady_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_afazrihady DistilBertEmbeddings from afazrihady
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_afazrihady
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_afazrihady` is a English model originally trained by afazrihady.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_afazrihady_en_5.5.1_3.0_1737976433962.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_afazrihady_en_5.5.1_3.0_1737976433962.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_afazrihady","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_afazrihady","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_afazrihady|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/afazrihady/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_imdb_afazrihady_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_imdb_afazrihady_pipeline_en.md
new file mode 100644
index 00000000000000..6ec38effbbf304
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_imdb_afazrihady_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_afazrihady_pipeline pipeline DistilBertEmbeddings from afazrihady
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_afazrihady_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_afazrihady_pipeline` is a English model originally trained by afazrihady.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_afazrihady_pipeline_en_5.5.1_3.0_1737976448642.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_afazrihady_pipeline_en_5.5.1_3.0_1737976448642.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_afazrihady_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_afazrihady_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_afazrihady_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/afazrihady/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_imdb_dave19_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_imdb_dave19_en.md
new file mode 100644
index 00000000000000..b09d7343e0b56c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_imdb_dave19_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_dave19 DistilBertEmbeddings from dave19
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_dave19
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_dave19` is a English model originally trained by dave19.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_dave19_en_5.5.1_3.0_1737976433794.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_dave19_en_5.5.1_3.0_1737976433794.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_dave19","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_dave19","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_dave19|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/dave19/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_imdb_dave19_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_imdb_dave19_pipeline_en.md
new file mode 100644
index 00000000000000..857f176182908b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_imdb_dave19_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_dave19_pipeline pipeline DistilBertEmbeddings from dave19
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_dave19_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_dave19_pipeline` is a English model originally trained by dave19.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_dave19_pipeline_en_5.5.1_3.0_1737976449722.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_dave19_pipeline_en_5.5.1_3.0_1737976449722.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_dave19_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_dave19_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_dave19_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/dave19/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_ner_roncmic_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_ner_roncmic_en.md
new file mode 100644
index 00000000000000..525d9f8986e876
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_ner_roncmic_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_roncmic DistilBertForTokenClassification from roncmic
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_roncmic
+date: 2025-01-27
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_roncmic` is a English model originally trained by roncmic.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_roncmic_en_5.5.1_3.0_1737988473941.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_roncmic_en_5.5.1_3.0_1737988473941.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_roncmic","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_roncmic", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_roncmic|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/roncmic/distilbert-base-uncased-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_ner_roncmic_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_ner_roncmic_pipeline_en.md
new file mode 100644
index 00000000000000..18f9ca18b32fdf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_ner_roncmic_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_roncmic_pipeline pipeline DistilBertForTokenClassification from roncmic
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_roncmic_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_roncmic_pipeline` is a English model originally trained by roncmic.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_roncmic_pipeline_en_5.5.1_3.0_1737988489169.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_roncmic_pipeline_en_5.5.1_3.0_1737988489169.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_ner_roncmic_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_ner_roncmic_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_roncmic_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/roncmic/distilbert-base-uncased-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_squad_xonic48_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_squad_xonic48_en.md
new file mode 100644
index 00000000000000..f7d5157d8a8a5b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_squad_xonic48_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_xonic48 DistilBertForQuestionAnswering from xonic48
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_xonic48
+date: 2025-01-27
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_xonic48` is a English model originally trained by xonic48.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_xonic48_en_5.5.1_3.0_1737973813771.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_xonic48_en_5.5.1_3.0_1737973813771.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_xonic48","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_xonic48", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_xonic48|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/xonic48/distilbert-base-uncased-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_squad_xonic48_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_squad_xonic48_pipeline_en.md
new file mode 100644
index 00000000000000..36e55596a84de0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_squad_xonic48_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_xonic48_pipeline pipeline DistilBertForQuestionAnswering from xonic48
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_xonic48_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_xonic48_pipeline` is a English model originally trained by xonic48.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_xonic48_pipeline_en_5.5.1_3.0_1737973833399.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_xonic48_pipeline_en_5.5.1_3.0_1737973833399.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_squad_xonic48_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_squad_xonic48_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_xonic48_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/xonic48/distilbert-base-uncased-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_sst_2_english_07112024t125645_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_sst_2_english_07112024t125645_en.md
new file mode 100644
index 00000000000000..4fa9ad846eaeca
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_sst_2_english_07112024t125645_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_sst_2_english_07112024t125645 DistilBertForSequenceClassification from samaksh-khatri-crest-data
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_sst_2_english_07112024t125645
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_sst_2_english_07112024t125645` is a English model originally trained by samaksh-khatri-crest-data.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_sst_2_english_07112024t125645_en_5.5.1_3.0_1737940043675.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_sst_2_english_07112024t125645_en_5.5.1_3.0_1737940043675.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_sst_2_english_07112024t125645","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_sst_2_english_07112024t125645", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_sst_2_english_07112024t125645|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/samaksh-khatri-crest-data/distilbert-base-uncased-finetuned-sst-2-english_07112024T125645
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_sst_2_english_07112024t125645_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_sst_2_english_07112024t125645_pipeline_en.md
new file mode 100644
index 00000000000000..69d011961b7163
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilbert_base_uncased_finetuned_sst_2_english_07112024t125645_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_sst_2_english_07112024t125645_pipeline pipeline DistilBertForSequenceClassification from samaksh-khatri-crest-data
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_sst_2_english_07112024t125645_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_sst_2_english_07112024t125645_pipeline` is a English model originally trained by samaksh-khatri-crest-data.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_sst_2_english_07112024t125645_pipeline_en_5.5.1_3.0_1737940058019.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_sst_2_english_07112024t125645_pipeline_en_5.5.1_3.0_1737940058019.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_sst_2_english_07112024t125645_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_sst_2_english_07112024t125645_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_sst_2_english_07112024t125645_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/samaksh-khatri-crest-data/distilbert-base-uncased-finetuned-sst-2-english_07112024T125645
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilbert_finetuned_lrpxxx_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilbert_finetuned_lrpxxx_en.md
new file mode 100644
index 00000000000000..a1aadc70ca28cf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilbert_finetuned_lrpxxx_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_finetuned_lrpxxx DistilBertForSequenceClassification from LRPxxx
+author: John Snow Labs
+name: distilbert_finetuned_lrpxxx
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetuned_lrpxxx` is a English model originally trained by LRPxxx.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_lrpxxx_en_5.5.1_3.0_1737939763954.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_lrpxxx_en_5.5.1_3.0_1737939763954.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_finetuned_lrpxxx","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_finetuned_lrpxxx", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_finetuned_lrpxxx|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/LRPxxx/DistilBERT_Finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilbert_finetuned_lrpxxx_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilbert_finetuned_lrpxxx_pipeline_en.md
new file mode 100644
index 00000000000000..106db2d3eeaf06
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilbert_finetuned_lrpxxx_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_finetuned_lrpxxx_pipeline pipeline DistilBertForSequenceClassification from LRPxxx
+author: John Snow Labs
+name: distilbert_finetuned_lrpxxx_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetuned_lrpxxx_pipeline` is a English model originally trained by LRPxxx.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_lrpxxx_pipeline_en_5.5.1_3.0_1737939779030.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_lrpxxx_pipeline_en_5.5.1_3.0_1737939779030.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_finetuned_lrpxxx_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_finetuned_lrpxxx_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_finetuned_lrpxxx_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/LRPxxx/DistilBERT_Finetuned
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilbert_finetuned_varadsrivastava_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilbert_finetuned_varadsrivastava_en.md
new file mode 100644
index 00000000000000..b7c8014525cfc3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilbert_finetuned_varadsrivastava_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_finetuned_varadsrivastava DistilBertForSequenceClassification from varadsrivastava
+author: John Snow Labs
+name: distilbert_finetuned_varadsrivastava
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetuned_varadsrivastava` is a English model originally trained by varadsrivastava.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_varadsrivastava_en_5.5.1_3.0_1737939343669.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_varadsrivastava_en_5.5.1_3.0_1737939343669.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_finetuned_varadsrivastava","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_finetuned_varadsrivastava", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_finetuned_varadsrivastava|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/varadsrivastava/distilbert_finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilbert_finetuned_varadsrivastava_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilbert_finetuned_varadsrivastava_pipeline_en.md
new file mode 100644
index 00000000000000..9ddd26d4de170e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilbert_finetuned_varadsrivastava_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_finetuned_varadsrivastava_pipeline pipeline DistilBertForSequenceClassification from varadsrivastava
+author: John Snow Labs
+name: distilbert_finetuned_varadsrivastava_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetuned_varadsrivastava_pipeline` is a English model originally trained by varadsrivastava.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_varadsrivastava_pipeline_en_5.5.1_3.0_1737939356913.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_varadsrivastava_pipeline_en_5.5.1_3.0_1737939356913.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_finetuned_varadsrivastava_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_finetuned_varadsrivastava_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_finetuned_varadsrivastava_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/varadsrivastava/distilbert_finetuned
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilbert_lora_false_adapted_augment_true_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilbert_lora_false_adapted_augment_true_en.md
new file mode 100644
index 00000000000000..6d31139ebfebef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilbert_lora_false_adapted_augment_true_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_lora_false_adapted_augment_true DistilBertForSequenceClassification from EmiMule
+author: John Snow Labs
+name: distilbert_lora_false_adapted_augment_true
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_lora_false_adapted_augment_true` is a English model originally trained by EmiMule.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_lora_false_adapted_augment_true_en_5.5.1_3.0_1737939215233.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_lora_false_adapted_augment_true_en_5.5.1_3.0_1737939215233.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_lora_false_adapted_augment_true","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_lora_false_adapted_augment_true", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_lora_false_adapted_augment_true|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/EmiMule/distilbert-LoRA-False-adapted-augment-True
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilbert_lora_false_adapted_augment_true_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilbert_lora_false_adapted_augment_true_pipeline_en.md
new file mode 100644
index 00000000000000..92d6b1338fc25c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilbert_lora_false_adapted_augment_true_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_lora_false_adapted_augment_true_pipeline pipeline DistilBertForSequenceClassification from EmiMule
+author: John Snow Labs
+name: distilbert_lora_false_adapted_augment_true_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_lora_false_adapted_augment_true_pipeline` is a English model originally trained by EmiMule.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_lora_false_adapted_augment_true_pipeline_en_5.5.1_3.0_1737939228506.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_lora_false_adapted_augment_true_pipeline_en_5.5.1_3.0_1737939228506.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_lora_false_adapted_augment_true_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_lora_false_adapted_augment_true_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_lora_false_adapted_augment_true_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/EmiMule/distilbert-LoRA-False-adapted-augment-True
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilgpt2_distilbert_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilgpt2_distilbert_en.md
new file mode 100644
index 00000000000000..38b22d7ab10ae8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilgpt2_distilbert_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilgpt2_distilbert GPT2Transformer from distilbert
+author: John Snow Labs
+name: distilgpt2_distilbert
+date: 2025-01-27
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilgpt2_distilbert` is a English model originally trained by distilbert.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilgpt2_distilbert_en_5.5.1_3.0_1737994918800.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilgpt2_distilbert_en_5.5.1_3.0_1737994918800.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("distilgpt2_distilbert","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("distilgpt2_distilbert","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilgpt2_distilbert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|308.4 MB|
+
+## References
+
+https://huggingface.co/distilbert/distilgpt2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilgpt2_distilbert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilgpt2_distilbert_pipeline_en.md
new file mode 100644
index 00000000000000..b14c0652279a6a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilgpt2_distilbert_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilgpt2_distilbert_pipeline pipeline GPT2Transformer from distilbert
+author: John Snow Labs
+name: distilgpt2_distilbert_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilgpt2_distilbert_pipeline` is a English model originally trained by distilbert.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilgpt2_distilbert_pipeline_en_5.5.1_3.0_1737994934641.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilgpt2_distilbert_pipeline_en_5.5.1_3.0_1737994934641.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilgpt2_distilbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilgpt2_distilbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilgpt2_distilbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|308.4 MB|
+
+## References
+
+https://huggingface.co/distilbert/distilgpt2
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilgpt2_emailgen_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilgpt2_emailgen_en.md
new file mode 100644
index 00000000000000..146cc2dcb6be05
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilgpt2_emailgen_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilgpt2_emailgen GPT2Transformer from postbot
+author: John Snow Labs
+name: distilgpt2_emailgen
+date: 2025-01-27
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilgpt2_emailgen` is a English model originally trained by postbot.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilgpt2_emailgen_en_5.5.1_3.0_1737995517555.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilgpt2_emailgen_en_5.5.1_3.0_1737995517555.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("distilgpt2_emailgen","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("distilgpt2_emailgen","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilgpt2_emailgen|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|308.4 MB|
+
+## References
+
+https://huggingface.co/postbot/distilgpt2-emailgen
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilgpt2_emailgen_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilgpt2_emailgen_pipeline_en.md
new file mode 100644
index 00000000000000..6c5d7179131712
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilgpt2_emailgen_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilgpt2_emailgen_pipeline pipeline GPT2Transformer from postbot
+author: John Snow Labs
+name: distilgpt2_emailgen_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilgpt2_emailgen_pipeline` is a English model originally trained by postbot.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilgpt2_emailgen_pipeline_en_5.5.1_3.0_1737995536115.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilgpt2_emailgen_pipeline_en_5.5.1_3.0_1737995536115.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilgpt2_emailgen_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilgpt2_emailgen_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilgpt2_emailgen_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|308.4 MB|
+
+## References
+
+https://huggingface.co/postbot/distilgpt2-emailgen
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distillbert_base_sst_myers_briggs_classifier_en.md b/docs/_posts/ahmedlone127/2025-01-27-distillbert_base_sst_myers_briggs_classifier_en.md
new file mode 100644
index 00000000000000..f43b0ca1074e1e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distillbert_base_sst_myers_briggs_classifier_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distillbert_base_sst_myers_briggs_classifier DistilBertForSequenceClassification from jtatman
+author: John Snow Labs
+name: distillbert_base_sst_myers_briggs_classifier
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distillbert_base_sst_myers_briggs_classifier` is a English model originally trained by jtatman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distillbert_base_sst_myers_briggs_classifier_en_5.5.1_3.0_1737939720631.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distillbert_base_sst_myers_briggs_classifier_en_5.5.1_3.0_1737939720631.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distillbert_base_sst_myers_briggs_classifier","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distillbert_base_sst_myers_briggs_classifier", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distillbert_base_sst_myers_briggs_classifier|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/jtatman/distillbert-base-sst-myers-briggs-classifier
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distillbert_base_sst_myers_briggs_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-distillbert_base_sst_myers_briggs_classifier_pipeline_en.md
new file mode 100644
index 00000000000000..714fb82955e3fe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distillbert_base_sst_myers_briggs_classifier_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distillbert_base_sst_myers_briggs_classifier_pipeline pipeline DistilBertForSequenceClassification from jtatman
+author: John Snow Labs
+name: distillbert_base_sst_myers_briggs_classifier_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distillbert_base_sst_myers_briggs_classifier_pipeline` is a English model originally trained by jtatman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distillbert_base_sst_myers_briggs_classifier_pipeline_en_5.5.1_3.0_1737939734716.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distillbert_base_sst_myers_briggs_classifier_pipeline_en_5.5.1_3.0_1737939734716.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distillbert_base_sst_myers_briggs_classifier_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distillbert_base_sst_myers_briggs_classifier_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distillbert_base_sst_myers_briggs_classifier_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/jtatman/distillbert-base-sst-myers-briggs-classifier
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distillbert_base_uncased_squad_v2_en.md b/docs/_posts/ahmedlone127/2025-01-27-distillbert_base_uncased_squad_v2_en.md
new file mode 100644
index 00000000000000..f35804d2dc9749
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distillbert_base_uncased_squad_v2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distillbert_base_uncased_squad_v2 DistilBertForQuestionAnswering from telord
+author: John Snow Labs
+name: distillbert_base_uncased_squad_v2
+date: 2025-01-27
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distillbert_base_uncased_squad_v2` is a English model originally trained by telord.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distillbert_base_uncased_squad_v2_en_5.5.1_3.0_1737973813896.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distillbert_base_uncased_squad_v2_en_5.5.1_3.0_1737973813896.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("distillbert_base_uncased_squad_v2","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("distillbert_base_uncased_squad_v2", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distillbert_base_uncased_squad_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/telord/distillbert-base-uncased-squad-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distillbert_base_uncased_squad_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-distillbert_base_uncased_squad_v2_pipeline_en.md
new file mode 100644
index 00000000000000..1f2643279bd928
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distillbert_base_uncased_squad_v2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distillbert_base_uncased_squad_v2_pipeline pipeline DistilBertForQuestionAnswering from telord
+author: John Snow Labs
+name: distillbert_base_uncased_squad_v2_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distillbert_base_uncased_squad_v2_pipeline` is a English model originally trained by telord.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distillbert_base_uncased_squad_v2_pipeline_en_5.5.1_3.0_1737973835159.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distillbert_base_uncased_squad_v2_pipeline_en_5.5.1_3.0_1737973835159.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distillbert_base_uncased_squad_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distillbert_base_uncased_squad_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distillbert_base_uncased_squad_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/telord/distillbert-base-uncased-squad-v2
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilled_t5_base_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilled_t5_base_en.md
new file mode 100644
index 00000000000000..a64ad135239234
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilled_t5_base_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilled_t5_base T5Transformer from hyunwookim
+author: John Snow Labs
+name: distilled_t5_base
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilled_t5_base` is a English model originally trained by hyunwookim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilled_t5_base_en_5.5.1_3.0_1737945199906.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilled_t5_base_en_5.5.1_3.0_1737945199906.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("distilled_t5_base","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("distilled_t5_base", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilled_t5_base|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/hyunwookim/distilled_t5_base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilled_t5_base_final_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilled_t5_base_final_en.md
new file mode 100644
index 00000000000000..049394f229a43a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilled_t5_base_final_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilled_t5_base_final T5Transformer from hyunwookim
+author: John Snow Labs
+name: distilled_t5_base_final
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilled_t5_base_final` is a English model originally trained by hyunwookim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilled_t5_base_final_en_5.5.1_3.0_1737991944475.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilled_t5_base_final_en_5.5.1_3.0_1737991944475.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("distilled_t5_base_final","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("distilled_t5_base_final", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilled_t5_base_final|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/hyunwookim/distilled_t5_base_final
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilled_t5_base_final_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilled_t5_base_final_pipeline_en.md
new file mode 100644
index 00000000000000..5a0ecd77710cae
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilled_t5_base_final_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilled_t5_base_final_pipeline pipeline T5Transformer from hyunwookim
+author: John Snow Labs
+name: distilled_t5_base_final_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilled_t5_base_final_pipeline` is a English model originally trained by hyunwookim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilled_t5_base_final_pipeline_en_5.5.1_3.0_1737991995525.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilled_t5_base_final_pipeline_en_5.5.1_3.0_1737991995525.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilled_t5_base_final_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilled_t5_base_final_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilled_t5_base_final_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/hyunwookim/distilled_t5_base_final
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilled_t5_base_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilled_t5_base_pipeline_en.md
new file mode 100644
index 00000000000000..98e68b135c6c0d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilled_t5_base_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilled_t5_base_pipeline pipeline T5Transformer from hyunwookim
+author: John Snow Labs
+name: distilled_t5_base_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilled_t5_base_pipeline` is a English model originally trained by hyunwookim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilled_t5_base_pipeline_en_5.5.1_3.0_1737945254619.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilled_t5_base_pipeline_en_5.5.1_3.0_1737945254619.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilled_t5_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilled_t5_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilled_t5_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/hyunwookim/distilled_t5_base
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilroberta_base_finetuned_evm_opcodes_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilroberta_base_finetuned_evm_opcodes_en.md
new file mode 100644
index 00000000000000..866f73f54bde3e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilroberta_base_finetuned_evm_opcodes_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilroberta_base_finetuned_evm_opcodes RoBertaEmbeddings from Fixedbot
+author: John Snow Labs
+name: distilroberta_base_finetuned_evm_opcodes
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_finetuned_evm_opcodes` is a English model originally trained by Fixedbot.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_base_finetuned_evm_opcodes_en_5.5.1_3.0_1737966532721.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_finetuned_evm_opcodes_en_5.5.1_3.0_1737966532721.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("distilroberta_base_finetuned_evm_opcodes","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("distilroberta_base_finetuned_evm_opcodes","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_base_finetuned_evm_opcodes|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/Fixedbot/distilroberta-base-finetuned-evm-opcodes
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilroberta_base_finetuned_evm_opcodes_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilroberta_base_finetuned_evm_opcodes_pipeline_en.md
new file mode 100644
index 00000000000000..e1f8aa34865b9a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilroberta_base_finetuned_evm_opcodes_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilroberta_base_finetuned_evm_opcodes_pipeline pipeline RoBertaEmbeddings from Fixedbot
+author: John Snow Labs
+name: distilroberta_base_finetuned_evm_opcodes_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_finetuned_evm_opcodes_pipeline` is a English model originally trained by Fixedbot.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_base_finetuned_evm_opcodes_pipeline_en_5.5.1_3.0_1737966548672.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_finetuned_evm_opcodes_pipeline_en_5.5.1_3.0_1737966548672.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilroberta_base_finetuned_evm_opcodes_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilroberta_base_finetuned_evm_opcodes_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_base_finetuned_evm_opcodes_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/Fixedbot/distilroberta-base-finetuned-evm-opcodes
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilroberta_base_ft_politics_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilroberta_base_ft_politics_en.md
new file mode 100644
index 00000000000000..37da403655d0df
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilroberta_base_ft_politics_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilroberta_base_ft_politics RoBertaEmbeddings from jkruk
+author: John Snow Labs
+name: distilroberta_base_ft_politics
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_ft_politics` is a English model originally trained by jkruk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_base_ft_politics_en_5.5.1_3.0_1738020538009.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_ft_politics_en_5.5.1_3.0_1738020538009.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("distilroberta_base_ft_politics","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("distilroberta_base_ft_politics","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_base_ft_politics|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/jkruk/distilroberta-base-ft-politics
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilroberta_base_ft_politics_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilroberta_base_ft_politics_pipeline_en.md
new file mode 100644
index 00000000000000..3f57fd30765ba0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilroberta_base_ft_politics_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilroberta_base_ft_politics_pipeline pipeline RoBertaEmbeddings from jkruk
+author: John Snow Labs
+name: distilroberta_base_ft_politics_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_ft_politics_pipeline` is a English model originally trained by jkruk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_base_ft_politics_pipeline_en_5.5.1_3.0_1738020553659.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_ft_politics_pipeline_en_5.5.1_3.0_1738020553659.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilroberta_base_ft_politics_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilroberta_base_ft_politics_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_base_ft_politics_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/jkruk/distilroberta-base-ft-politics
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilroberta_base_ft_relationships_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilroberta_base_ft_relationships_en.md
new file mode 100644
index 00000000000000..08cb6ab78ca9e3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilroberta_base_ft_relationships_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilroberta_base_ft_relationships RoBertaEmbeddings from jkruk
+author: John Snow Labs
+name: distilroberta_base_ft_relationships
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_ft_relationships` is a English model originally trained by jkruk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_base_ft_relationships_en_5.5.1_3.0_1737965889104.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_ft_relationships_en_5.5.1_3.0_1737965889104.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("distilroberta_base_ft_relationships","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("distilroberta_base_ft_relationships","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_base_ft_relationships|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|306.4 MB|
+
+## References
+
+https://huggingface.co/jkruk/distilroberta-base-ft-relationships
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilroberta_base_ft_relationships_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilroberta_base_ft_relationships_pipeline_en.md
new file mode 100644
index 00000000000000..8890b4316666f3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilroberta_base_ft_relationships_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilroberta_base_ft_relationships_pipeline pipeline RoBertaEmbeddings from jkruk
+author: John Snow Labs
+name: distilroberta_base_ft_relationships_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_ft_relationships_pipeline` is a English model originally trained by jkruk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_base_ft_relationships_pipeline_en_5.5.1_3.0_1737965904769.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_ft_relationships_pipeline_en_5.5.1_3.0_1737965904769.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilroberta_base_ft_relationships_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilroberta_base_ft_relationships_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_base_ft_relationships_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/jkruk/distilroberta-base-ft-relationships
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilroberta_base_ft_science_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilroberta_base_ft_science_en.md
new file mode 100644
index 00000000000000..0323ddeef80e8e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilroberta_base_ft_science_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilroberta_base_ft_science RoBertaEmbeddings from jkruk
+author: John Snow Labs
+name: distilroberta_base_ft_science
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_ft_science` is a English model originally trained by jkruk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_base_ft_science_en_5.5.1_3.0_1737965606913.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_ft_science_en_5.5.1_3.0_1737965606913.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("distilroberta_base_ft_science","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("distilroberta_base_ft_science","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_base_ft_science|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|306.4 MB|
+
+## References
+
+https://huggingface.co/jkruk/distilroberta-base-ft-science
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-distilroberta_base_ft_science_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-distilroberta_base_ft_science_pipeline_en.md
new file mode 100644
index 00000000000000..efb1b0bb8c609b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-distilroberta_base_ft_science_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilroberta_base_ft_science_pipeline pipeline RoBertaEmbeddings from jkruk
+author: John Snow Labs
+name: distilroberta_base_ft_science_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_ft_science_pipeline` is a English model originally trained by jkruk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_base_ft_science_pipeline_en_5.5.1_3.0_1737965626486.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_ft_science_pipeline_en_5.5.1_3.0_1737965626486.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilroberta_base_ft_science_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilroberta_base_ft_science_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_base_ft_science_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/jkruk/distilroberta-base-ft-science
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-dobf_mlm_roberta_size_en.md b/docs/_posts/ahmedlone127/2025-01-27-dobf_mlm_roberta_size_en.md
new file mode 100644
index 00000000000000..e42324c06689f7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-dobf_mlm_roberta_size_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dobf_mlm_roberta_size RoBertaEmbeddings from claudios
+author: John Snow Labs
+name: dobf_mlm_roberta_size
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dobf_mlm_roberta_size` is a English model originally trained by claudios.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dobf_mlm_roberta_size_en_5.5.1_3.0_1737966853609.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dobf_mlm_roberta_size_en_5.5.1_3.0_1737966853609.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("dobf_mlm_roberta_size","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("dobf_mlm_roberta_size","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dobf_mlm_roberta_size|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|299.0 MB|
+
+## References
+
+https://huggingface.co/claudios/dobf-mlm-roberta-size
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-dobf_mlm_roberta_size_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-dobf_mlm_roberta_size_pipeline_en.md
new file mode 100644
index 00000000000000..42a769f4297691
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-dobf_mlm_roberta_size_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dobf_mlm_roberta_size_pipeline pipeline RoBertaEmbeddings from claudios
+author: John Snow Labs
+name: dobf_mlm_roberta_size_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dobf_mlm_roberta_size_pipeline` is a English model originally trained by claudios.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dobf_mlm_roberta_size_pipeline_en_5.5.1_3.0_1737966938107.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dobf_mlm_roberta_size_pipeline_en_5.5.1_3.0_1737966938107.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dobf_mlm_roberta_size_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dobf_mlm_roberta_size_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dobf_mlm_roberta_size_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|299.0 MB|
+
+## References
+
+https://huggingface.co/claudios/dobf-mlm-roberta-size
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-dummy_model_abdulkoko_en.md b/docs/_posts/ahmedlone127/2025-01-27-dummy_model_abdulkoko_en.md
new file mode 100644
index 00000000000000..5feebe37196768
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-dummy_model_abdulkoko_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_abdulkoko CamemBertEmbeddings from Abdulkoko
+author: John Snow Labs
+name: dummy_model_abdulkoko
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_abdulkoko` is a English model originally trained by Abdulkoko.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_abdulkoko_en_5.5.1_3.0_1737940722232.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_abdulkoko_en_5.5.1_3.0_1737940722232.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_abdulkoko","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_abdulkoko","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_abdulkoko|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/Abdulkoko/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-dummy_model_abdulkoko_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-dummy_model_abdulkoko_pipeline_en.md
new file mode 100644
index 00000000000000..f1e33ed7ed343a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-dummy_model_abdulkoko_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_abdulkoko_pipeline pipeline CamemBertEmbeddings from Abdulkoko
+author: John Snow Labs
+name: dummy_model_abdulkoko_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_abdulkoko_pipeline` is a English model originally trained by Abdulkoko.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_abdulkoko_pipeline_en_5.5.1_3.0_1737940801528.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_abdulkoko_pipeline_en_5.5.1_3.0_1737940801528.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_abdulkoko_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_abdulkoko_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_abdulkoko_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/Abdulkoko/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-dummy_model_allkkiver_en.md b/docs/_posts/ahmedlone127/2025-01-27-dummy_model_allkkiver_en.md
new file mode 100644
index 00000000000000..c2485e9e6b3ab5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-dummy_model_allkkiver_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_allkkiver CamemBertEmbeddings from allkkiver
+author: John Snow Labs
+name: dummy_model_allkkiver
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_allkkiver` is a English model originally trained by allkkiver.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_allkkiver_en_5.5.1_3.0_1737940639572.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_allkkiver_en_5.5.1_3.0_1737940639572.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_allkkiver","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_allkkiver","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_allkkiver|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/allkkiver/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-dummy_model_allkkiver_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-dummy_model_allkkiver_pipeline_en.md
new file mode 100644
index 00000000000000..696a3ac0ecf203
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-dummy_model_allkkiver_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_allkkiver_pipeline pipeline CamemBertEmbeddings from allkkiver
+author: John Snow Labs
+name: dummy_model_allkkiver_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_allkkiver_pipeline` is a English model originally trained by allkkiver.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_allkkiver_pipeline_en_5.5.1_3.0_1737940720386.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_allkkiver_pipeline_en_5.5.1_3.0_1737940720386.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_allkkiver_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_allkkiver_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_allkkiver_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/allkkiver/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-dummy_model_dimichw_en.md b/docs/_posts/ahmedlone127/2025-01-27-dummy_model_dimichw_en.md
new file mode 100644
index 00000000000000..b056d88e2e8d65
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-dummy_model_dimichw_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_dimichw CamemBertEmbeddings from DimichW
+author: John Snow Labs
+name: dummy_model_dimichw
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_dimichw` is a English model originally trained by DimichW.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_dimichw_en_5.5.1_3.0_1737975769568.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_dimichw_en_5.5.1_3.0_1737975769568.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_dimichw","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_dimichw","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_dimichw|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/DimichW/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-dummy_model_dimichw_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-dummy_model_dimichw_pipeline_en.md
new file mode 100644
index 00000000000000..f95f977f6c21b1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-dummy_model_dimichw_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_dimichw_pipeline pipeline CamemBertEmbeddings from DimichW
+author: John Snow Labs
+name: dummy_model_dimichw_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_dimichw_pipeline` is a English model originally trained by DimichW.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_dimichw_pipeline_en_5.5.1_3.0_1737975844902.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_dimichw_pipeline_en_5.5.1_3.0_1737975844902.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_dimichw_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_dimichw_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_dimichw_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/DimichW/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-dummy_model_hayatoshibahara_en.md b/docs/_posts/ahmedlone127/2025-01-27-dummy_model_hayatoshibahara_en.md
new file mode 100644
index 00000000000000..189166469866d6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-dummy_model_hayatoshibahara_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_hayatoshibahara CamemBertEmbeddings from hayatoshibahara
+author: John Snow Labs
+name: dummy_model_hayatoshibahara
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_hayatoshibahara` is a English model originally trained by hayatoshibahara.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_hayatoshibahara_en_5.5.1_3.0_1737940716220.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_hayatoshibahara_en_5.5.1_3.0_1737940716220.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_hayatoshibahara","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_hayatoshibahara","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_hayatoshibahara|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/hayatoshibahara/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-dummy_model_hayatoshibahara_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-dummy_model_hayatoshibahara_pipeline_en.md
new file mode 100644
index 00000000000000..386374e38ba0a0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-dummy_model_hayatoshibahara_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_hayatoshibahara_pipeline pipeline CamemBertEmbeddings from hayatoshibahara
+author: John Snow Labs
+name: dummy_model_hayatoshibahara_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_hayatoshibahara_pipeline` is a English model originally trained by hayatoshibahara.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_hayatoshibahara_pipeline_en_5.5.1_3.0_1737940792409.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_hayatoshibahara_pipeline_en_5.5.1_3.0_1737940792409.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_hayatoshibahara_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_hayatoshibahara_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_hayatoshibahara_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/hayatoshibahara/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-dummy_model_hieudeptraivcl_en.md b/docs/_posts/ahmedlone127/2025-01-27-dummy_model_hieudeptraivcl_en.md
new file mode 100644
index 00000000000000..0f921181e4ca21
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-dummy_model_hieudeptraivcl_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_hieudeptraivcl CamemBertEmbeddings from hieudeptraivcl
+author: John Snow Labs
+name: dummy_model_hieudeptraivcl
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_hieudeptraivcl` is a English model originally trained by hieudeptraivcl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_hieudeptraivcl_en_5.5.1_3.0_1737975946149.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_hieudeptraivcl_en_5.5.1_3.0_1737975946149.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_hieudeptraivcl","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_hieudeptraivcl","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_hieudeptraivcl|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/hieudeptraivcl/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-dummy_model_hieudeptraivcl_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-dummy_model_hieudeptraivcl_pipeline_en.md
new file mode 100644
index 00000000000000..c316c6d6fde46f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-dummy_model_hieudeptraivcl_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_hieudeptraivcl_pipeline pipeline CamemBertEmbeddings from hieudeptraivcl
+author: John Snow Labs
+name: dummy_model_hieudeptraivcl_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_hieudeptraivcl_pipeline` is a English model originally trained by hieudeptraivcl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_hieudeptraivcl_pipeline_en_5.5.1_3.0_1737976020007.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_hieudeptraivcl_pipeline_en_5.5.1_3.0_1737976020007.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_hieudeptraivcl_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_hieudeptraivcl_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_hieudeptraivcl_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/hieudeptraivcl/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-dummy_model_jackson107_en.md b/docs/_posts/ahmedlone127/2025-01-27-dummy_model_jackson107_en.md
new file mode 100644
index 00000000000000..a503cd78818333
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-dummy_model_jackson107_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_jackson107 CamemBertEmbeddings from Jackson107
+author: John Snow Labs
+name: dummy_model_jackson107
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_jackson107` is a English model originally trained by Jackson107.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_jackson107_en_5.5.1_3.0_1737940639722.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_jackson107_en_5.5.1_3.0_1737940639722.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_jackson107","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_jackson107","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_jackson107|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/Jackson107/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-dummy_model_jackson107_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-dummy_model_jackson107_pipeline_en.md
new file mode 100644
index 00000000000000..d2a0c8cdf9d7f6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-dummy_model_jackson107_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_jackson107_pipeline pipeline CamemBertEmbeddings from Jackson107
+author: John Snow Labs
+name: dummy_model_jackson107_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_jackson107_pipeline` is a English model originally trained by Jackson107.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_jackson107_pipeline_en_5.5.1_3.0_1737940719202.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_jackson107_pipeline_en_5.5.1_3.0_1737940719202.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_jackson107_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_jackson107_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_jackson107_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/Jackson107/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-dummy_model_jhkwon_en.md b/docs/_posts/ahmedlone127/2025-01-27-dummy_model_jhkwon_en.md
new file mode 100644
index 00000000000000..ae886111a9947d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-dummy_model_jhkwon_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_jhkwon CamemBertEmbeddings from jhkwon
+author: John Snow Labs
+name: dummy_model_jhkwon
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_jhkwon` is a English model originally trained by jhkwon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_jhkwon_en_5.5.1_3.0_1737975671146.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_jhkwon_en_5.5.1_3.0_1737975671146.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_jhkwon","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_jhkwon","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_jhkwon|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/jhkwon/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-dummy_model_jhkwon_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-dummy_model_jhkwon_pipeline_en.md
new file mode 100644
index 00000000000000..436dae1e27256a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-dummy_model_jhkwon_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_jhkwon_pipeline pipeline CamemBertEmbeddings from jhkwon
+author: John Snow Labs
+name: dummy_model_jhkwon_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_jhkwon_pipeline` is a English model originally trained by jhkwon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_jhkwon_pipeline_en_5.5.1_3.0_1737975749872.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_jhkwon_pipeline_en_5.5.1_3.0_1737975749872.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_jhkwon_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_jhkwon_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_jhkwon_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/jhkwon/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-dummy_model_ylic204_en.md b/docs/_posts/ahmedlone127/2025-01-27-dummy_model_ylic204_en.md
new file mode 100644
index 00000000000000..d9b86bf861c948
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-dummy_model_ylic204_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_ylic204 CamemBertEmbeddings from ylic204
+author: John Snow Labs
+name: dummy_model_ylic204
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_ylic204` is a English model originally trained by ylic204.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_ylic204_en_5.5.1_3.0_1737975671227.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_ylic204_en_5.5.1_3.0_1737975671227.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_ylic204","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_ylic204","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_ylic204|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/ylic204/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-dummy_model_ylic204_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-dummy_model_ylic204_pipeline_en.md
new file mode 100644
index 00000000000000..1530ce4ccba908
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-dummy_model_ylic204_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_ylic204_pipeline pipeline CamemBertEmbeddings from ylic204
+author: John Snow Labs
+name: dummy_model_ylic204_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_ylic204_pipeline` is a English model originally trained by ylic204.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_ylic204_pipeline_en_5.5.1_3.0_1737975748274.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_ylic204_pipeline_en_5.5.1_3.0_1737975748274.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_ylic204_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_ylic204_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_ylic204_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/ylic204/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-e5_base_german_sentence_similarity_de.md b/docs/_posts/ahmedlone127/2025-01-27-e5_base_german_sentence_similarity_de.md
new file mode 100644
index 00000000000000..c4f50063d49323
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-e5_base_german_sentence_similarity_de.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: German e5_base_german_sentence_similarity E5Embeddings from kaixkhazaki
+author: John Snow Labs
+name: e5_base_german_sentence_similarity
+date: 2025-01-27
+tags: [de, open_source, onnx, embeddings, e5]
+task: Embeddings
+language: de
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: E5Embeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_base_german_sentence_similarity` is a German model originally trained by kaixkhazaki.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_base_german_sentence_similarity_de_5.5.1_3.0_1737949709987.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_base_german_sentence_similarity_de_5.5.1_3.0_1737949709987.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = E5Embeddings.pretrained("e5_base_german_sentence_similarity","de") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = E5Embeddings.pretrained("e5_base_german_sentence_similarity","de") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|e5_base_german_sentence_similarity|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[E5]|
+|Language:|de|
+|Size:|385.6 MB|
+
+## References
+
+https://huggingface.co/kaixkhazaki/e5-base-german-sentence-similarity
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-e5_base_german_sentence_similarity_pipeline_de.md b/docs/_posts/ahmedlone127/2025-01-27-e5_base_german_sentence_similarity_pipeline_de.md
new file mode 100644
index 00000000000000..b80449fa3a74a6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-e5_base_german_sentence_similarity_pipeline_de.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: German e5_base_german_sentence_similarity_pipeline pipeline E5Embeddings from kaixkhazaki
+author: John Snow Labs
+name: e5_base_german_sentence_similarity_pipeline
+date: 2025-01-27
+tags: [de, open_source, pipeline, onnx]
+task: Embeddings
+language: de
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_base_german_sentence_similarity_pipeline` is a German model originally trained by kaixkhazaki.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_base_german_sentence_similarity_pipeline_de_5.5.1_3.0_1737949736057.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_base_german_sentence_similarity_pipeline_de_5.5.1_3.0_1737949736057.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("e5_base_german_sentence_similarity_pipeline", lang = "de")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("e5_base_german_sentence_similarity_pipeline", lang = "de")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|e5_base_german_sentence_similarity_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|de|
+|Size:|385.6 MB|
+
+## References
+
+https://huggingface.co/kaixkhazaki/e5-base-german-sentence-similarity
+
+## Included Models
+
+- DocumentAssembler
+- E5Embeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-electrical_classification_bert_large_en.md b/docs/_posts/ahmedlone127/2025-01-27-electrical_classification_bert_large_en.md
new file mode 100644
index 00000000000000..ad0bd257bfc9ff
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-electrical_classification_bert_large_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English electrical_classification_bert_large BertForSequenceClassification from disham993
+author: John Snow Labs
+name: electrical_classification_bert_large
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`electrical_classification_bert_large` is a English model originally trained by disham993.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electrical_classification_bert_large_en_5.5.1_3.0_1738005711649.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electrical_classification_bert_large_en_5.5.1_3.0_1738005711649.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("electrical_classification_bert_large","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("electrical_classification_bert_large", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electrical_classification_bert_large|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/disham993/electrical-classification-bert-large
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-electrical_classification_bert_large_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-electrical_classification_bert_large_pipeline_en.md
new file mode 100644
index 00000000000000..0dd3c93ba13959
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-electrical_classification_bert_large_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English electrical_classification_bert_large_pipeline pipeline BertForSequenceClassification from disham993
+author: John Snow Labs
+name: electrical_classification_bert_large_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`electrical_classification_bert_large_pipeline` is a English model originally trained by disham993.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electrical_classification_bert_large_pipeline_en_5.5.1_3.0_1738005776079.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electrical_classification_bert_large_pipeline_en_5.5.1_3.0_1738005776079.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("electrical_classification_bert_large_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("electrical_classification_bert_large_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electrical_classification_bert_large_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/disham993/electrical-classification-bert-large
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-emotion_analysis_trans_en.md b/docs/_posts/ahmedlone127/2025-01-27-emotion_analysis_trans_en.md
new file mode 100644
index 00000000000000..a44a1ade9ec17c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-emotion_analysis_trans_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English emotion_analysis_trans DistilBertForSequenceClassification from erlend123
+author: John Snow Labs
+name: emotion_analysis_trans
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`emotion_analysis_trans` is a English model originally trained by erlend123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/emotion_analysis_trans_en_5.5.1_3.0_1737939427901.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/emotion_analysis_trans_en_5.5.1_3.0_1737939427901.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("emotion_analysis_trans","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("emotion_analysis_trans", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|emotion_analysis_trans|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/erlend123/emotion-analysis-trans
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-emotion_analysis_trans_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-emotion_analysis_trans_pipeline_en.md
new file mode 100644
index 00000000000000..823ca1c64d0c60
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-emotion_analysis_trans_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English emotion_analysis_trans_pipeline pipeline DistilBertForSequenceClassification from erlend123
+author: John Snow Labs
+name: emotion_analysis_trans_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`emotion_analysis_trans_pipeline` is a English model originally trained by erlend123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/emotion_analysis_trans_pipeline_en_5.5.1_3.0_1737939441432.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/emotion_analysis_trans_pipeline_en_5.5.1_3.0_1737939441432.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("emotion_analysis_trans_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("emotion_analysis_trans_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|emotion_analysis_trans_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/erlend123/emotion-analysis-trans
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-emubert_en.md b/docs/_posts/ahmedlone127/2025-01-27-emubert_en.md
new file mode 100644
index 00000000000000..185d26941d6f79
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-emubert_en.md
@@ -0,0 +1,96 @@
+---
+layout: model
+title: English emubert RoBertaEmbeddings from umarbutler
+author: John Snow Labs
+name: emubert
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`emubert` is a English model originally trained by umarbutler.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/emubert_en_5.5.1_3.0_1737966091192.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/emubert_en_5.5.1_3.0_1737966091192.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("emubert","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("emubert","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|emubert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|466.5 MB|
+
+## References
+
+References
+
+https://huggingface.co/umarbutler/emubert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-emubert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-emubert_pipeline_en.md
new file mode 100644
index 00000000000000..563faa37b2806a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-emubert_pipeline_en.md
@@ -0,0 +1,72 @@
+---
+layout: model
+title: English emubert_pipeline pipeline RoBertaEmbeddings from umarbutler
+author: John Snow Labs
+name: emubert_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`emubert_pipeline` is a English model originally trained by umarbutler.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/emubert_pipeline_en_5.5.1_3.0_1737966123015.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/emubert_pipeline_en_5.5.1_3.0_1737966123015.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("emubert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("emubert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|emubert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.5 MB|
+
+## References
+
+References
+
+https://huggingface.co/umarbutler/emubert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-eng_japanese_trans_en.md b/docs/_posts/ahmedlone127/2025-01-27-eng_japanese_trans_en.md
new file mode 100644
index 00000000000000..2c12697cb55aa2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-eng_japanese_trans_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English eng_japanese_trans MarianTransformer from Patlu29
+author: John Snow Labs
+name: eng_japanese_trans
+date: 2025-01-27
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`eng_japanese_trans` is a English model originally trained by Patlu29.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/eng_japanese_trans_en_5.5.1_3.0_1737984249210.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/eng_japanese_trans_en_5.5.1_3.0_1737984249210.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("eng_japanese_trans","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("eng_japanese_trans","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|eng_japanese_trans|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|418.7 MB|
+
+## References
+
+https://huggingface.co/Patlu29/eng-jap_trans
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-eng_japanese_trans_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-eng_japanese_trans_pipeline_en.md
new file mode 100644
index 00000000000000..15d2714c085c6e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-eng_japanese_trans_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English eng_japanese_trans_pipeline pipeline MarianTransformer from Patlu29
+author: John Snow Labs
+name: eng_japanese_trans_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`eng_japanese_trans_pipeline` is a English model originally trained by Patlu29.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/eng_japanese_trans_pipeline_en_5.5.1_3.0_1737984276513.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/eng_japanese_trans_pipeline_en_5.5.1_3.0_1737984276513.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("eng_japanese_trans_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("eng_japanese_trans_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|eng_japanese_trans_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|419.2 MB|
+
+## References
+
+https://huggingface.co/Patlu29/eng-jap_trans
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-eng_mar_translator_en.md b/docs/_posts/ahmedlone127/2025-01-27-eng_mar_translator_en.md
new file mode 100644
index 00000000000000..3f743b46516e4c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-eng_mar_translator_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English eng_mar_translator T5Transformer from rautaditya
+author: John Snow Labs
+name: eng_mar_translator
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`eng_mar_translator` is a English model originally trained by rautaditya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/eng_mar_translator_en_5.5.1_3.0_1737961254422.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/eng_mar_translator_en_5.5.1_3.0_1737961254422.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("eng_mar_translator","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("eng_mar_translator", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|eng_mar_translator|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|267.0 MB|
+
+## References
+
+https://huggingface.co/rautaditya/eng-mar-translator
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-eng_mar_translator_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-eng_mar_translator_pipeline_en.md
new file mode 100644
index 00000000000000..78e4b81b77b51a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-eng_mar_translator_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English eng_mar_translator_pipeline pipeline T5Transformer from rautaditya
+author: John Snow Labs
+name: eng_mar_translator_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`eng_mar_translator_pipeline` is a English model originally trained by rautaditya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/eng_mar_translator_pipeline_en_5.5.1_3.0_1737961275044.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/eng_mar_translator_pipeline_en_5.5.1_3.0_1737961275044.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("eng_mar_translator_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("eng_mar_translator_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|eng_mar_translator_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|267.0 MB|
+
+## References
+
+https://huggingface.co/rautaditya/eng-mar-translator
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-english_bert_v0_en.md b/docs/_posts/ahmedlone127/2025-01-27-english_bert_v0_en.md
new file mode 100644
index 00000000000000..2d7e7c8eea6fe6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-english_bert_v0_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English english_bert_v0 BertEmbeddings from dnagpt
+author: John Snow Labs
+name: english_bert_v0
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_bert_v0` is a English model originally trained by dnagpt.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/english_bert_v0_en_5.5.1_3.0_1737985737113.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_bert_v0_en_5.5.1_3.0_1737985737113.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("english_bert_v0","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("english_bert_v0","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|english_bert_v0|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|404.4 MB|
+
+## References
+
+https://huggingface.co/dnagpt/en_bert_v0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-english_bert_v0_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-english_bert_v0_pipeline_en.md
new file mode 100644
index 00000000000000..62c97d503e2599
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-english_bert_v0_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English english_bert_v0_pipeline pipeline BertEmbeddings from dnagpt
+author: John Snow Labs
+name: english_bert_v0_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_bert_v0_pipeline` is a English model originally trained by dnagpt.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/english_bert_v0_pipeline_en_5.5.1_3.0_1737985758052.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_bert_v0_pipeline_en_5.5.1_3.0_1737985758052.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("english_bert_v0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("english_bert_v0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|english_bert_v0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|404.4 MB|
+
+## References
+
+https://huggingface.co/dnagpt/en_bert_v0
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-english_russian_translate_en.md b/docs/_posts/ahmedlone127/2025-01-27-english_russian_translate_en.md
new file mode 100644
index 00000000000000..0dacca0fd8bbc8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-english_russian_translate_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English english_russian_translate T5Transformer from CrimsonRubus
+author: John Snow Labs
+name: english_russian_translate
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_russian_translate` is a English model originally trained by CrimsonRubus.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/english_russian_translate_en_5.5.1_3.0_1737977761575.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_russian_translate_en_5.5.1_3.0_1737977761575.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("english_russian_translate","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("english_russian_translate", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|english_russian_translate|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|266.7 MB|
+
+## References
+
+https://huggingface.co/CrimsonRubus/en_ru_translate
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-english_russian_translate_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-english_russian_translate_pipeline_en.md
new file mode 100644
index 00000000000000..71933d6fc772db
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-english_russian_translate_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English english_russian_translate_pipeline pipeline T5Transformer from CrimsonRubus
+author: John Snow Labs
+name: english_russian_translate_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_russian_translate_pipeline` is a English model originally trained by CrimsonRubus.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/english_russian_translate_pipeline_en_5.5.1_3.0_1737977779347.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_russian_translate_pipeline_en_5.5.1_3.0_1737977779347.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("english_russian_translate_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("english_russian_translate_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|english_russian_translate_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|266.7 MB|
+
+## References
+
+https://huggingface.co/CrimsonRubus/en_ru_translate
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-english_russian_translate_red_en.md b/docs/_posts/ahmedlone127/2025-01-27-english_russian_translate_red_en.md
new file mode 100644
index 00000000000000..58925129a343e7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-english_russian_translate_red_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English english_russian_translate_red T5Transformer from CrimsonRubus
+author: John Snow Labs
+name: english_russian_translate_red
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_russian_translate_red` is a English model originally trained by CrimsonRubus.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/english_russian_translate_red_en_5.5.1_3.0_1738007177843.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_russian_translate_red_en_5.5.1_3.0_1738007177843.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("english_russian_translate_red","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("english_russian_translate_red", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|english_russian_translate_red|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|268.1 MB|
+
+## References
+
+https://huggingface.co/CrimsonRubus/en_ru_translate_red
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-english_russian_translate_red_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-english_russian_translate_red_pipeline_en.md
new file mode 100644
index 00000000000000..9ae605c54b6e82
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-english_russian_translate_red_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English english_russian_translate_red_pipeline pipeline T5Transformer from CrimsonRubus
+author: John Snow Labs
+name: english_russian_translate_red_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_russian_translate_red_pipeline` is a English model originally trained by CrimsonRubus.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/english_russian_translate_red_pipeline_en_5.5.1_3.0_1738007196143.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_russian_translate_red_pipeline_en_5.5.1_3.0_1738007196143.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("english_russian_translate_red_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("english_russian_translate_red_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|english_russian_translate_red_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|268.1 MB|
+
+## References
+
+https://huggingface.co/CrimsonRubus/en_ru_translate_red
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-esgbertv1_access_tonga_tonga_islands_communications_en.md b/docs/_posts/ahmedlone127/2025-01-27-esgbertv1_access_tonga_tonga_islands_communications_en.md
new file mode 100644
index 00000000000000..0afe9de19dc422
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-esgbertv1_access_tonga_tonga_islands_communications_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English esgbertv1_access_tonga_tonga_islands_communications BertForSequenceClassification from ab3223323
+author: John Snow Labs
+name: esgbertv1_access_tonga_tonga_islands_communications
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`esgbertv1_access_tonga_tonga_islands_communications` is a English model originally trained by ab3223323.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/esgbertv1_access_tonga_tonga_islands_communications_en_5.5.1_3.0_1738005361567.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/esgbertv1_access_tonga_tonga_islands_communications_en_5.5.1_3.0_1738005361567.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("esgbertv1_access_tonga_tonga_islands_communications","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("esgbertv1_access_tonga_tonga_islands_communications", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|esgbertv1_access_tonga_tonga_islands_communications|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/ab3223323/esgBERTv1_Access_to_Communications
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-esgbertv1_access_tonga_tonga_islands_communications_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-esgbertv1_access_tonga_tonga_islands_communications_pipeline_en.md
new file mode 100644
index 00000000000000..98fab6115b3bc7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-esgbertv1_access_tonga_tonga_islands_communications_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English esgbertv1_access_tonga_tonga_islands_communications_pipeline pipeline BertForSequenceClassification from ab3223323
+author: John Snow Labs
+name: esgbertv1_access_tonga_tonga_islands_communications_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`esgbertv1_access_tonga_tonga_islands_communications_pipeline` is a English model originally trained by ab3223323.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/esgbertv1_access_tonga_tonga_islands_communications_pipeline_en_5.5.1_3.0_1738005383177.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/esgbertv1_access_tonga_tonga_islands_communications_pipeline_en_5.5.1_3.0_1738005383177.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("esgbertv1_access_tonga_tonga_islands_communications_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("esgbertv1_access_tonga_tonga_islands_communications_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|esgbertv1_access_tonga_tonga_islands_communications_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/ab3223323/esgBERTv1_Access_to_Communications
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-evoker_en.md b/docs/_posts/ahmedlone127/2025-01-27-evoker_en.md
new file mode 100644
index 00000000000000..37973e2a4666f8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-evoker_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English evoker GPT2Transformer from kaj
+author: John Snow Labs
+name: evoker
+date: 2025-01-27
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`evoker` is a English model originally trained by kaj.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/evoker_en_5.5.1_3.0_1738003962231.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/evoker_en_5.5.1_3.0_1738003962231.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("evoker","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("evoker","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|evoker|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|308.5 MB|
+
+## References
+
+https://huggingface.co/kaj/evoker
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-evoker_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-evoker_pipeline_en.md
new file mode 100644
index 00000000000000..d31f6b03d27d2d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-evoker_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English evoker_pipeline pipeline GPT2Transformer from kaj
+author: John Snow Labs
+name: evoker_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`evoker_pipeline` is a English model originally trained by kaj.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/evoker_pipeline_en_5.5.1_3.0_1738003978858.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/evoker_pipeline_en_5.5.1_3.0_1738003978858.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("evoker_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("evoker_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|evoker_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|308.5 MB|
+
+## References
+
+https://huggingface.co/kaj/evoker
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-eyeglasses_detection_en.md b/docs/_posts/ahmedlone127/2025-01-27-eyeglasses_detection_en.md
new file mode 100644
index 00000000000000..4da0d297c4fef5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-eyeglasses_detection_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English eyeglasses_detection ViTForImageClassification from youngp5
+author: John Snow Labs
+name: eyeglasses_detection
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`eyeglasses_detection` is a English model originally trained by youngp5.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/eyeglasses_detection_en_5.5.1_3.0_1737974955679.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/eyeglasses_detection_en_5.5.1_3.0_1737974955679.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""eyeglasses_detection","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("eyeglasses_detection","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|eyeglasses_detection|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/youngp5/eyeglasses_detection
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-eyeglasses_detection_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-eyeglasses_detection_pipeline_en.md
new file mode 100644
index 00000000000000..429d4fecd88dc0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-eyeglasses_detection_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English eyeglasses_detection_pipeline pipeline ViTForImageClassification from youngp5
+author: John Snow Labs
+name: eyeglasses_detection_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`eyeglasses_detection_pipeline` is a English model originally trained by youngp5.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/eyeglasses_detection_pipeline_en_5.5.1_3.0_1737974972781.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/eyeglasses_detection_pipeline_en_5.5.1_3.0_1737974972781.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("eyeglasses_detection_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("eyeglasses_detection_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|eyeglasses_detection_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/youngp5/eyeglasses_detection
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-face_emotion_en.md b/docs/_posts/ahmedlone127/2025-01-27-face_emotion_en.md
new file mode 100644
index 00000000000000..5bd344e0535673
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-face_emotion_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English face_emotion ViTForImageClassification from gerhardien
+author: John Snow Labs
+name: face_emotion
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`face_emotion` is a English model originally trained by gerhardien.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/face_emotion_en_5.5.1_3.0_1737957076874.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/face_emotion_en_5.5.1_3.0_1737957076874.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""face_emotion","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("face_emotion","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|face_emotion|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/gerhardien/face-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-face_emotion_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-face_emotion_pipeline_en.md
new file mode 100644
index 00000000000000..68652586a14472
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-face_emotion_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English face_emotion_pipeline pipeline ViTForImageClassification from gerhardien
+author: John Snow Labs
+name: face_emotion_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`face_emotion_pipeline` is a English model originally trained by gerhardien.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/face_emotion_pipeline_en_5.5.1_3.0_1737957093647.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/face_emotion_pipeline_en_5.5.1_3.0_1737957093647.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("face_emotion_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("face_emotion_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|face_emotion_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/gerhardien/face-emotion
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-face_emotions_image_detection_v3_en.md b/docs/_posts/ahmedlone127/2025-01-27-face_emotions_image_detection_v3_en.md
new file mode 100644
index 00000000000000..29f9af192adb68
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-face_emotions_image_detection_v3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English face_emotions_image_detection_v3 ViTForImageClassification from dpaul93
+author: John Snow Labs
+name: face_emotions_image_detection_v3
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`face_emotions_image_detection_v3` is a English model originally trained by dpaul93.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/face_emotions_image_detection_v3_en_5.5.1_3.0_1737973985387.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/face_emotions_image_detection_v3_en_5.5.1_3.0_1737973985387.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""face_emotions_image_detection_v3","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("face_emotions_image_detection_v3","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|face_emotions_image_detection_v3|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.7 MB|
+
+## References
+
+https://huggingface.co/dpaul93/face_emotions_image_detection-v3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-face_emotions_image_detection_v3_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-face_emotions_image_detection_v3_pipeline_en.md
new file mode 100644
index 00000000000000..8961ab5003601b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-face_emotions_image_detection_v3_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English face_emotions_image_detection_v3_pipeline pipeline ViTForImageClassification from dpaul93
+author: John Snow Labs
+name: face_emotions_image_detection_v3_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`face_emotions_image_detection_v3_pipeline` is a English model originally trained by dpaul93.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/face_emotions_image_detection_v3_pipeline_en_5.5.1_3.0_1737974001261.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/face_emotions_image_detection_v3_pipeline_en_5.5.1_3.0_1737974001261.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("face_emotions_image_detection_v3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("face_emotions_image_detection_v3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|face_emotions_image_detection_v3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.7 MB|
+
+## References
+
+https://huggingface.co/dpaul93/face_emotions_image_detection-v3
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-face_obstruction_image_detection_en.md b/docs/_posts/ahmedlone127/2025-01-27-face_obstruction_image_detection_en.md
new file mode 100644
index 00000000000000..60c01540079ca4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-face_obstruction_image_detection_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English face_obstruction_image_detection ViTForImageClassification from dima806
+author: John Snow Labs
+name: face_obstruction_image_detection
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`face_obstruction_image_detection` is a English model originally trained by dima806.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/face_obstruction_image_detection_en_5.5.1_3.0_1738021117767.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/face_obstruction_image_detection_en_5.5.1_3.0_1738021117767.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""face_obstruction_image_detection","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("face_obstruction_image_detection","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|face_obstruction_image_detection|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/dima806/face_obstruction_image_detection
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-face_obstruction_image_detection_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-face_obstruction_image_detection_pipeline_en.md
new file mode 100644
index 00000000000000..9f84667767ec97
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-face_obstruction_image_detection_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English face_obstruction_image_detection_pipeline pipeline ViTForImageClassification from dima806
+author: John Snow Labs
+name: face_obstruction_image_detection_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`face_obstruction_image_detection_pipeline` is a English model originally trained by dima806.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/face_obstruction_image_detection_pipeline_en_5.5.1_3.0_1738021135988.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/face_obstruction_image_detection_pipeline_en_5.5.1_3.0_1738021135988.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("face_obstruction_image_detection_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("face_obstruction_image_detection_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|face_obstruction_image_detection_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/dima806/face_obstruction_image_detection
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-fashion_images_gender_age_vit_large_patch16_224_in21k_v2_en.md b/docs/_posts/ahmedlone127/2025-01-27-fashion_images_gender_age_vit_large_patch16_224_in21k_v2_en.md
new file mode 100644
index 00000000000000..6c2d14df0e727a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-fashion_images_gender_age_vit_large_patch16_224_in21k_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English fashion_images_gender_age_vit_large_patch16_224_in21k_v2 ViTForImageClassification from touchtech
+author: John Snow Labs
+name: fashion_images_gender_age_vit_large_patch16_224_in21k_v2
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fashion_images_gender_age_vit_large_patch16_224_in21k_v2` is a English model originally trained by touchtech.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fashion_images_gender_age_vit_large_patch16_224_in21k_v2_en_5.5.1_3.0_1737974528294.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fashion_images_gender_age_vit_large_patch16_224_in21k_v2_en_5.5.1_3.0_1737974528294.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""fashion_images_gender_age_vit_large_patch16_224_in21k_v2","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("fashion_images_gender_age_vit_large_patch16_224_in21k_v2","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fashion_images_gender_age_vit_large_patch16_224_in21k_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/touchtech/fashion-images-gender-age-vit-large-patch16-224-in21k-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-fashion_images_gender_age_vit_large_patch16_224_in21k_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-fashion_images_gender_age_vit_large_patch16_224_in21k_v2_pipeline_en.md
new file mode 100644
index 00000000000000..31db26d6866fd7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-fashion_images_gender_age_vit_large_patch16_224_in21k_v2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English fashion_images_gender_age_vit_large_patch16_224_in21k_v2_pipeline pipeline ViTForImageClassification from touchtech
+author: John Snow Labs
+name: fashion_images_gender_age_vit_large_patch16_224_in21k_v2_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fashion_images_gender_age_vit_large_patch16_224_in21k_v2_pipeline` is a English model originally trained by touchtech.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fashion_images_gender_age_vit_large_patch16_224_in21k_v2_pipeline_en_5.5.1_3.0_1737974591959.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fashion_images_gender_age_vit_large_patch16_224_in21k_v2_pipeline_en_5.5.1_3.0_1737974591959.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fashion_images_gender_age_vit_large_patch16_224_in21k_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fashion_images_gender_age_vit_large_patch16_224_in21k_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fashion_images_gender_age_vit_large_patch16_224_in21k_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/touchtech/fashion-images-gender-age-vit-large-patch16-224-in21k-v2
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-fashion_images_perspectives_vit_large_patch16_224_in21k_v4_en.md b/docs/_posts/ahmedlone127/2025-01-27-fashion_images_perspectives_vit_large_patch16_224_in21k_v4_en.md
new file mode 100644
index 00000000000000..a0070c20f6d6c1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-fashion_images_perspectives_vit_large_patch16_224_in21k_v4_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English fashion_images_perspectives_vit_large_patch16_224_in21k_v4 ViTForImageClassification from touchtech
+author: John Snow Labs
+name: fashion_images_perspectives_vit_large_patch16_224_in21k_v4
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fashion_images_perspectives_vit_large_patch16_224_in21k_v4` is a English model originally trained by touchtech.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fashion_images_perspectives_vit_large_patch16_224_in21k_v4_en_5.5.1_3.0_1738021087225.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fashion_images_perspectives_vit_large_patch16_224_in21k_v4_en_5.5.1_3.0_1738021087225.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""fashion_images_perspectives_vit_large_patch16_224_in21k_v4","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("fashion_images_perspectives_vit_large_patch16_224_in21k_v4","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fashion_images_perspectives_vit_large_patch16_224_in21k_v4|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/touchtech/fashion-images-perspectives-vit-large-patch16-224-in21k-v4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-fashion_images_perspectives_vit_large_patch16_224_in21k_v4_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-fashion_images_perspectives_vit_large_patch16_224_in21k_v4_pipeline_en.md
new file mode 100644
index 00000000000000..9ff0988befef31
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-fashion_images_perspectives_vit_large_patch16_224_in21k_v4_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English fashion_images_perspectives_vit_large_patch16_224_in21k_v4_pipeline pipeline ViTForImageClassification from touchtech
+author: John Snow Labs
+name: fashion_images_perspectives_vit_large_patch16_224_in21k_v4_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fashion_images_perspectives_vit_large_patch16_224_in21k_v4_pipeline` is a English model originally trained by touchtech.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fashion_images_perspectives_vit_large_patch16_224_in21k_v4_pipeline_en_5.5.1_3.0_1738021145007.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fashion_images_perspectives_vit_large_patch16_224_in21k_v4_pipeline_en_5.5.1_3.0_1738021145007.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fashion_images_perspectives_vit_large_patch16_224_in21k_v4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fashion_images_perspectives_vit_large_patch16_224_in21k_v4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fashion_images_perspectives_vit_large_patch16_224_in21k_v4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/touchtech/fashion-images-perspectives-vit-large-patch16-224-in21k-v4
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-fast_gpt2_en.md b/docs/_posts/ahmedlone127/2025-01-27-fast_gpt2_en.md
new file mode 100644
index 00000000000000..a7e38d24560d68
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-fast_gpt2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English fast_gpt2 GPT2Transformer from Narsil
+author: John Snow Labs
+name: fast_gpt2
+date: 2025-01-27
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fast_gpt2` is a English model originally trained by Narsil.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fast_gpt2_en_5.5.1_3.0_1737997133105.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fast_gpt2_en_5.5.1_3.0_1737997133105.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("fast_gpt2","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("fast_gpt2","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fast_gpt2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/Narsil/fast_gpt2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-fast_gpt2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-fast_gpt2_pipeline_en.md
new file mode 100644
index 00000000000000..55bf70c660e489
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-fast_gpt2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English fast_gpt2_pipeline pipeline GPT2Transformer from Narsil
+author: John Snow Labs
+name: fast_gpt2_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fast_gpt2_pipeline` is a English model originally trained by Narsil.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fast_gpt2_pipeline_en_5.5.1_3.0_1737997156580.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fast_gpt2_pipeline_en_5.5.1_3.0_1737997156580.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fast_gpt2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fast_gpt2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fast_gpt2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/Narsil/fast_gpt2
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-fewshot_qa_002_20230613_en.md b/docs/_posts/ahmedlone127/2025-01-27-fewshot_qa_002_20230613_en.md
new file mode 100644
index 00000000000000..980e8e41848f2d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-fewshot_qa_002_20230613_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English fewshot_qa_002_20230613 XlmRoBertaForQuestionAnswering from intanm
+author: John Snow Labs
+name: fewshot_qa_002_20230613
+date: 2025-01-27
+tags: [en, open_source, onnx, question_answering, xlm_roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fewshot_qa_002_20230613` is a English model originally trained by intanm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fewshot_qa_002_20230613_en_5.5.1_3.0_1737964826884.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fewshot_qa_002_20230613_en_5.5.1_3.0_1737964826884.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("fewshot_qa_002_20230613","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("fewshot_qa_002_20230613", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fewshot_qa_002_20230613|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|880.3 MB|
+
+## References
+
+https://huggingface.co/intanm/fewshot-qa-002-20230613
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-fewshot_qa_002_20230613_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-fewshot_qa_002_20230613_pipeline_en.md
new file mode 100644
index 00000000000000..56824401b3a0d5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-fewshot_qa_002_20230613_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English fewshot_qa_002_20230613_pipeline pipeline XlmRoBertaForQuestionAnswering from intanm
+author: John Snow Labs
+name: fewshot_qa_002_20230613_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fewshot_qa_002_20230613_pipeline` is a English model originally trained by intanm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fewshot_qa_002_20230613_pipeline_en_5.5.1_3.0_1737964892432.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fewshot_qa_002_20230613_pipeline_en_5.5.1_3.0_1737964892432.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fewshot_qa_002_20230613_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fewshot_qa_002_20230613_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fewshot_qa_002_20230613_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|880.3 MB|
+
+## References
+
+https://huggingface.co/intanm/fewshot-qa-002-20230613
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-final_model_sbazar_en.md b/docs/_posts/ahmedlone127/2025-01-27-final_model_sbazar_en.md
new file mode 100644
index 00000000000000..004ad32aa832a8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-final_model_sbazar_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English final_model_sbazar T5Transformer from Sbazar
+author: John Snow Labs
+name: final_model_sbazar
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`final_model_sbazar` is a English model originally trained by Sbazar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/final_model_sbazar_en_5.5.1_3.0_1737962138247.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/final_model_sbazar_en_5.5.1_3.0_1737962138247.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("final_model_sbazar","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("final_model_sbazar", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|final_model_sbazar|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|182.6 MB|
+
+## References
+
+https://huggingface.co/Sbazar/final-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-final_model_sbazar_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-final_model_sbazar_pipeline_en.md
new file mode 100644
index 00000000000000..49b480a5656a11
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-final_model_sbazar_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English final_model_sbazar_pipeline pipeline T5Transformer from Sbazar
+author: John Snow Labs
+name: final_model_sbazar_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`final_model_sbazar_pipeline` is a English model originally trained by Sbazar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/final_model_sbazar_pipeline_en_5.5.1_3.0_1737962188655.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/final_model_sbazar_pipeline_en_5.5.1_3.0_1737962188655.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("final_model_sbazar_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("final_model_sbazar_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|final_model_sbazar_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|182.6 MB|
+
+## References
+
+https://huggingface.co/Sbazar/final-model
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-final_project_en.md b/docs/_posts/ahmedlone127/2025-01-27-final_project_en.md
new file mode 100644
index 00000000000000..18fa65f5882a6c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-final_project_en.md
@@ -0,0 +1,96 @@
+---
+layout: model
+title: English final_project MarianTransformer from Cosmosplendor
+author: John Snow Labs
+name: final_project
+date: 2025-01-27
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`final_project` is a English model originally trained by Cosmosplendor.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/final_project_en_5.5.1_3.0_1737977688323.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/final_project_en_5.5.1_3.0_1737977688323.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("final_project","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("final_project","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|final_project|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|349.8 MB|
+
+## References
+
+References
+
+https://huggingface.co/Cosmosplendor/final-project
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-final_project_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-final_project_pipeline_en.md
new file mode 100644
index 00000000000000..3488ddc1f9c874
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-final_project_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English final_project_pipeline pipeline MarianTransformer from Cosmosplendor
+author: John Snow Labs
+name: final_project_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`final_project_pipeline` is a English model originally trained by Cosmosplendor.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/final_project_pipeline_en_5.5.1_3.0_1737977706894.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/final_project_pipeline_en_5.5.1_3.0_1737977706894.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("final_project_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("final_project_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|final_project_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|349.8 MB|
+
+## References
+
+References
+
+https://huggingface.co/Cosmosplendor/final-project
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-financial_bert_en.md b/docs/_posts/ahmedlone127/2025-01-27-financial_bert_en.md
new file mode 100644
index 00000000000000..7dd3b7318ef68b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-financial_bert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English financial_bert BertForTokenClassification from whataboutyou-ai
+author: John Snow Labs
+name: financial_bert
+date: 2025-01-27
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`financial_bert` is a English model originally trained by whataboutyou-ai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/financial_bert_en_5.5.1_3.0_1738017197957.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/financial_bert_en_5.5.1_3.0_1738017197957.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("financial_bert","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("financial_bert", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|financial_bert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/whataboutyou-ai/financial_bert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-financial_bert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-financial_bert_pipeline_en.md
new file mode 100644
index 00000000000000..f9eface9d2f31b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-financial_bert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English financial_bert_pipeline pipeline BertForTokenClassification from whataboutyou-ai
+author: John Snow Labs
+name: financial_bert_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`financial_bert_pipeline` is a English model originally trained by whataboutyou-ai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/financial_bert_pipeline_en_5.5.1_3.0_1738017218885.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/financial_bert_pipeline_en_5.5.1_3.0_1738017218885.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("financial_bert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("financial_bert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|financial_bert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/whataboutyou-ai/financial_bert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-financial_qa_t5_en.md b/docs/_posts/ahmedlone127/2025-01-27-financial_qa_t5_en.md
new file mode 100644
index 00000000000000..7c1fdb786a1783
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-financial_qa_t5_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English financial_qa_t5 T5Transformer from vincentkr18
+author: John Snow Labs
+name: financial_qa_t5
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`financial_qa_t5` is a English model originally trained by vincentkr18.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/financial_qa_t5_en_5.5.1_3.0_1737989156141.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/financial_qa_t5_en_5.5.1_3.0_1737989156141.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("financial_qa_t5","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("financial_qa_t5", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|financial_qa_t5|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|246.5 MB|
+
+## References
+
+https://huggingface.co/vincentkr18/financial-qa-t5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-financial_qa_t5_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-financial_qa_t5_pipeline_en.md
new file mode 100644
index 00000000000000..0bcccefca90564
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-financial_qa_t5_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English financial_qa_t5_pipeline pipeline T5Transformer from vincentkr18
+author: John Snow Labs
+name: financial_qa_t5_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`financial_qa_t5_pipeline` is a English model originally trained by vincentkr18.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/financial_qa_t5_pipeline_en_5.5.1_3.0_1737989177645.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/financial_qa_t5_pipeline_en_5.5.1_3.0_1737989177645.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("financial_qa_t5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("financial_qa_t5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|financial_qa_t5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|246.5 MB|
+
+## References
+
+https://huggingface.co/vincentkr18/financial-qa-t5
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-fine_tuned_mt5_trainer_epoch10_en.md b/docs/_posts/ahmedlone127/2025-01-27-fine_tuned_mt5_trainer_epoch10_en.md
new file mode 100644
index 00000000000000..06c45d1569f05a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-fine_tuned_mt5_trainer_epoch10_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English fine_tuned_mt5_trainer_epoch10 T5Transformer from HsuuHsuu
+author: John Snow Labs
+name: fine_tuned_mt5_trainer_epoch10
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_mt5_trainer_epoch10` is a English model originally trained by HsuuHsuu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_mt5_trainer_epoch10_en_5.5.1_3.0_1737964093519.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_mt5_trainer_epoch10_en_5.5.1_3.0_1737964093519.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("fine_tuned_mt5_trainer_epoch10","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("fine_tuned_mt5_trainer_epoch10", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_mt5_trainer_epoch10|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|2.6 MB|
+
+## References
+
+https://huggingface.co/HsuuHsuu/fine-tuned-mt5-trainer-epoch10
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-fine_tuned_mt5_trainer_epoch10_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-fine_tuned_mt5_trainer_epoch10_pipeline_en.md
new file mode 100644
index 00000000000000..867939b28b9e52
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-fine_tuned_mt5_trainer_epoch10_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English fine_tuned_mt5_trainer_epoch10_pipeline pipeline T5Transformer from HsuuHsuu
+author: John Snow Labs
+name: fine_tuned_mt5_trainer_epoch10_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_mt5_trainer_epoch10_pipeline` is a English model originally trained by HsuuHsuu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_mt5_trainer_epoch10_pipeline_en_5.5.1_3.0_1737964099286.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_mt5_trainer_epoch10_pipeline_en_5.5.1_3.0_1737964099286.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fine_tuned_mt5_trainer_epoch10_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fine_tuned_mt5_trainer_epoch10_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_mt5_trainer_epoch10_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|2.6 MB|
+
+## References
+
+https://huggingface.co/HsuuHsuu/fine-tuned-mt5-trainer-epoch10
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-fine_tuned_t5_armaandhande_en.md b/docs/_posts/ahmedlone127/2025-01-27-fine_tuned_t5_armaandhande_en.md
new file mode 100644
index 00000000000000..66842afb9ef2b4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-fine_tuned_t5_armaandhande_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English fine_tuned_t5_armaandhande T5Transformer from ArmaanDhande
+author: John Snow Labs
+name: fine_tuned_t5_armaandhande
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_t5_armaandhande` is a English model originally trained by ArmaanDhande.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_armaandhande_en_5.5.1_3.0_1737989659440.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_armaandhande_en_5.5.1_3.0_1737989659440.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("fine_tuned_t5_armaandhande","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("fine_tuned_t5_armaandhande", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_t5_armaandhande|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|274.4 MB|
+
+## References
+
+https://huggingface.co/ArmaanDhande/fine-tuned-t5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-fine_tuned_t5_armaandhande_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-fine_tuned_t5_armaandhande_pipeline_en.md
new file mode 100644
index 00000000000000..6de8d08d52d7bd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-fine_tuned_t5_armaandhande_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English fine_tuned_t5_armaandhande_pipeline pipeline T5Transformer from ArmaanDhande
+author: John Snow Labs
+name: fine_tuned_t5_armaandhande_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_t5_armaandhande_pipeline` is a English model originally trained by ArmaanDhande.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_armaandhande_pipeline_en_5.5.1_3.0_1737989676385.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_armaandhande_pipeline_en_5.5.1_3.0_1737989676385.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fine_tuned_t5_armaandhande_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fine_tuned_t5_armaandhande_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_t5_armaandhande_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|274.4 MB|
+
+## References
+
+https://huggingface.co/ArmaanDhande/fine-tuned-t5
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-fine_tuned_t5_small_model_naive_approach_en.md b/docs/_posts/ahmedlone127/2025-01-27-fine_tuned_t5_small_model_naive_approach_en.md
new file mode 100644
index 00000000000000..3d8ba5a41d9123
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-fine_tuned_t5_small_model_naive_approach_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English fine_tuned_t5_small_model_naive_approach T5Transformer from ariW
+author: John Snow Labs
+name: fine_tuned_t5_small_model_naive_approach
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_t5_small_model_naive_approach` is a English model originally trained by ariW.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_small_model_naive_approach_en_5.5.1_3.0_1737961973491.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_small_model_naive_approach_en_5.5.1_3.0_1737961973491.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("fine_tuned_t5_small_model_naive_approach","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("fine_tuned_t5_small_model_naive_approach", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_t5_small_model_naive_approach|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|273.2 MB|
+
+## References
+
+https://huggingface.co/ariW/fine_tuned_t5_small_model-naive-approach
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-fine_tuned_t5_small_model_naive_approach_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-fine_tuned_t5_small_model_naive_approach_pipeline_en.md
new file mode 100644
index 00000000000000..40d27163678015
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-fine_tuned_t5_small_model_naive_approach_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English fine_tuned_t5_small_model_naive_approach_pipeline pipeline T5Transformer from ariW
+author: John Snow Labs
+name: fine_tuned_t5_small_model_naive_approach_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_t5_small_model_naive_approach_pipeline` is a English model originally trained by ariW.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_small_model_naive_approach_pipeline_en_5.5.1_3.0_1737961990542.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_small_model_naive_approach_pipeline_en_5.5.1_3.0_1737961990542.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fine_tuned_t5_small_model_naive_approach_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fine_tuned_t5_small_model_naive_approach_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_t5_small_model_naive_approach_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|273.2 MB|
+
+## References
+
+https://huggingface.co/ariW/fine_tuned_t5_small_model-naive-approach
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-fine_tuned_t5_small_model_sec_5_v12_en.md b/docs/_posts/ahmedlone127/2025-01-27-fine_tuned_t5_small_model_sec_5_v12_en.md
new file mode 100644
index 00000000000000..5eb447cc42038d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-fine_tuned_t5_small_model_sec_5_v12_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English fine_tuned_t5_small_model_sec_5_v12 T5Transformer from miasetya
+author: John Snow Labs
+name: fine_tuned_t5_small_model_sec_5_v12
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_t5_small_model_sec_5_v12` is a English model originally trained by miasetya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_small_model_sec_5_v12_en_5.5.1_3.0_1737992328786.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_small_model_sec_5_v12_en_5.5.1_3.0_1737992328786.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("fine_tuned_t5_small_model_sec_5_v12","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("fine_tuned_t5_small_model_sec_5_v12", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_t5_small_model_sec_5_v12|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|268.7 MB|
+
+## References
+
+https://huggingface.co/miasetya/fine_tuned_t5_small_model_sec_5_v12
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-fine_tuned_t5_small_model_sec_5_v12_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-fine_tuned_t5_small_model_sec_5_v12_pipeline_en.md
new file mode 100644
index 00000000000000..aab34d2141a5a1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-fine_tuned_t5_small_model_sec_5_v12_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English fine_tuned_t5_small_model_sec_5_v12_pipeline pipeline T5Transformer from miasetya
+author: John Snow Labs
+name: fine_tuned_t5_small_model_sec_5_v12_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_t5_small_model_sec_5_v12_pipeline` is a English model originally trained by miasetya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_small_model_sec_5_v12_pipeline_en_5.5.1_3.0_1737992346870.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_small_model_sec_5_v12_pipeline_en_5.5.1_3.0_1737992346870.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fine_tuned_t5_small_model_sec_5_v12_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fine_tuned_t5_small_model_sec_5_v12_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_t5_small_model_sec_5_v12_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|268.7 MB|
+
+## References
+
+https://huggingface.co/miasetya/fine_tuned_t5_small_model_sec_5_v12
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-fine_tuned_t5_small_model_sec_5_v2_en.md b/docs/_posts/ahmedlone127/2025-01-27-fine_tuned_t5_small_model_sec_5_v2_en.md
new file mode 100644
index 00000000000000..b2314f6facfa25
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-fine_tuned_t5_small_model_sec_5_v2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English fine_tuned_t5_small_model_sec_5_v2 T5Transformer from miasetya
+author: John Snow Labs
+name: fine_tuned_t5_small_model_sec_5_v2
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_t5_small_model_sec_5_v2` is a English model originally trained by miasetya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_small_model_sec_5_v2_en_5.5.1_3.0_1737999324762.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_small_model_sec_5_v2_en_5.5.1_3.0_1737999324762.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("fine_tuned_t5_small_model_sec_5_v2","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("fine_tuned_t5_small_model_sec_5_v2", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_t5_small_model_sec_5_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|271.7 MB|
+
+## References
+
+https://huggingface.co/miasetya/fine_tuned_t5_small_model_sec_5_v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-fine_tuned_t5_small_model_sec_5_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-fine_tuned_t5_small_model_sec_5_v2_pipeline_en.md
new file mode 100644
index 00000000000000..ed7991280b0597
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-fine_tuned_t5_small_model_sec_5_v2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English fine_tuned_t5_small_model_sec_5_v2_pipeline pipeline T5Transformer from miasetya
+author: John Snow Labs
+name: fine_tuned_t5_small_model_sec_5_v2_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_t5_small_model_sec_5_v2_pipeline` is a English model originally trained by miasetya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_small_model_sec_5_v2_pipeline_en_5.5.1_3.0_1737999343033.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_small_model_sec_5_v2_pipeline_en_5.5.1_3.0_1737999343033.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fine_tuned_t5_small_model_sec_5_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fine_tuned_t5_small_model_sec_5_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_t5_small_model_sec_5_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|271.7 MB|
+
+## References
+
+https://huggingface.co/miasetya/fine_tuned_t5_small_model_sec_5_v2
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-fine_tuned_t5_small_model_sec_5_v4_en.md b/docs/_posts/ahmedlone127/2025-01-27-fine_tuned_t5_small_model_sec_5_v4_en.md
new file mode 100644
index 00000000000000..cb8a9465bc5d3d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-fine_tuned_t5_small_model_sec_5_v4_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English fine_tuned_t5_small_model_sec_5_v4 T5Transformer from miasetya
+author: John Snow Labs
+name: fine_tuned_t5_small_model_sec_5_v4
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_t5_small_model_sec_5_v4` is a English model originally trained by miasetya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_small_model_sec_5_v4_en_5.5.1_3.0_1737961254400.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_small_model_sec_5_v4_en_5.5.1_3.0_1737961254400.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("fine_tuned_t5_small_model_sec_5_v4","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("fine_tuned_t5_small_model_sec_5_v4", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_t5_small_model_sec_5_v4|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|267.1 MB|
+
+## References
+
+https://huggingface.co/miasetya/fine_tuned_t5_small_model_sec_5_v4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-fine_tuned_t5_small_model_sec_5_v4_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-fine_tuned_t5_small_model_sec_5_v4_pipeline_en.md
new file mode 100644
index 00000000000000..00f653ef54a3f3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-fine_tuned_t5_small_model_sec_5_v4_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English fine_tuned_t5_small_model_sec_5_v4_pipeline pipeline T5Transformer from miasetya
+author: John Snow Labs
+name: fine_tuned_t5_small_model_sec_5_v4_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_t5_small_model_sec_5_v4_pipeline` is a English model originally trained by miasetya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_small_model_sec_5_v4_pipeline_en_5.5.1_3.0_1737961273490.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_small_model_sec_5_v4_pipeline_en_5.5.1_3.0_1737961273490.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fine_tuned_t5_small_model_sec_5_v4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fine_tuned_t5_small_model_sec_5_v4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_t5_small_model_sec_5_v4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|267.1 MB|
+
+## References
+
+https://huggingface.co/miasetya/fine_tuned_t5_small_model_sec_5_v4
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-finetuned_kamruzzaman_asif_en.md b/docs/_posts/ahmedlone127/2025-01-27-finetuned_kamruzzaman_asif_en.md
new file mode 100644
index 00000000000000..2e01e1d00b2f59
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-finetuned_kamruzzaman_asif_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English finetuned_kamruzzaman_asif T5Transformer from kamruzzaman-asif
+author: John Snow Labs
+name: finetuned_kamruzzaman_asif
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_kamruzzaman_asif` is a English model originally trained by kamruzzaman-asif.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_kamruzzaman_asif_en_5.5.1_3.0_1737989459733.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_kamruzzaman_asif_en_5.5.1_3.0_1737989459733.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("finetuned_kamruzzaman_asif","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("finetuned_kamruzzaman_asif", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_kamruzzaman_asif|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/kamruzzaman-asif/finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-finetuned_kamruzzaman_asif_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-finetuned_kamruzzaman_asif_pipeline_en.md
new file mode 100644
index 00000000000000..c8e01400660838
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-finetuned_kamruzzaman_asif_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English finetuned_kamruzzaman_asif_pipeline pipeline T5Transformer from kamruzzaman-asif
+author: John Snow Labs
+name: finetuned_kamruzzaman_asif_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_kamruzzaman_asif_pipeline` is a English model originally trained by kamruzzaman-asif.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_kamruzzaman_asif_pipeline_en_5.5.1_3.0_1737989513754.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_kamruzzaman_asif_pipeline_en_5.5.1_3.0_1737989513754.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuned_kamruzzaman_asif_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuned_kamruzzaman_asif_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_kamruzzaman_asif_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/kamruzzaman-asif/finetuned
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-finetuned_mixed_mechanical_data_french_en.md b/docs/_posts/ahmedlone127/2025-01-27-finetuned_mixed_mechanical_data_french_en.md
new file mode 100644
index 00000000000000..120685ffd3e130
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-finetuned_mixed_mechanical_data_french_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English finetuned_mixed_mechanical_data_french T5Transformer from amiraMamdouh
+author: John Snow Labs
+name: finetuned_mixed_mechanical_data_french
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_mixed_mechanical_data_french` is a English model originally trained by amiraMamdouh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_mixed_mechanical_data_french_en_5.5.1_3.0_1737988865580.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_mixed_mechanical_data_french_en_5.5.1_3.0_1737988865580.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("finetuned_mixed_mechanical_data_french","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("finetuned_mixed_mechanical_data_french", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_mixed_mechanical_data_french|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|287.2 MB|
+
+## References
+
+https://huggingface.co/amiraMamdouh/finetuned_mixed_mechanical_data_fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-finetuned_mixed_mechanical_data_french_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-finetuned_mixed_mechanical_data_french_pipeline_en.md
new file mode 100644
index 00000000000000..bed3c41fba2dd4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-finetuned_mixed_mechanical_data_french_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English finetuned_mixed_mechanical_data_french_pipeline pipeline T5Transformer from amiraMamdouh
+author: John Snow Labs
+name: finetuned_mixed_mechanical_data_french_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_mixed_mechanical_data_french_pipeline` is a English model originally trained by amiraMamdouh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_mixed_mechanical_data_french_pipeline_en_5.5.1_3.0_1737988880706.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_mixed_mechanical_data_french_pipeline_en_5.5.1_3.0_1737988880706.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuned_mixed_mechanical_data_french_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuned_mixed_mechanical_data_french_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_mixed_mechanical_data_french_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|287.2 MB|
+
+## References
+
+https://huggingface.co/amiraMamdouh/finetuned_mixed_mechanical_data_fr
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-finetuned_query_general_mixed_mechanical_data_french_en.md b/docs/_posts/ahmedlone127/2025-01-27-finetuned_query_general_mixed_mechanical_data_french_en.md
new file mode 100644
index 00000000000000..61cc3503db0370
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-finetuned_query_general_mixed_mechanical_data_french_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English finetuned_query_general_mixed_mechanical_data_french T5Transformer from amiraMamdouh
+author: John Snow Labs
+name: finetuned_query_general_mixed_mechanical_data_french
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_query_general_mixed_mechanical_data_french` is a English model originally trained by amiraMamdouh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_query_general_mixed_mechanical_data_french_en_5.5.1_3.0_1737978608931.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_query_general_mixed_mechanical_data_french_en_5.5.1_3.0_1737978608931.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("finetuned_query_general_mixed_mechanical_data_french","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("finetuned_query_general_mixed_mechanical_data_french", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_query_general_mixed_mechanical_data_french|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|285.5 MB|
+
+## References
+
+https://huggingface.co/amiraMamdouh/finetuned_query_general_mixed_mechanical_data_fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-finetuned_query_general_mixed_mechanical_data_french_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-finetuned_query_general_mixed_mechanical_data_french_pipeline_en.md
new file mode 100644
index 00000000000000..10acf753ec8462
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-finetuned_query_general_mixed_mechanical_data_french_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English finetuned_query_general_mixed_mechanical_data_french_pipeline pipeline T5Transformer from amiraMamdouh
+author: John Snow Labs
+name: finetuned_query_general_mixed_mechanical_data_french_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_query_general_mixed_mechanical_data_french_pipeline` is a English model originally trained by amiraMamdouh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_query_general_mixed_mechanical_data_french_pipeline_en_5.5.1_3.0_1737978623602.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_query_general_mixed_mechanical_data_french_pipeline_en_5.5.1_3.0_1737978623602.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuned_query_general_mixed_mechanical_data_french_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuned_query_general_mixed_mechanical_data_french_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_query_general_mixed_mechanical_data_french_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|285.5 MB|
+
+## References
+
+https://huggingface.co/amiraMamdouh/finetuned_query_general_mixed_mechanical_data_fr
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-finetuned_sentiment_model_en.md b/docs/_posts/ahmedlone127/2025-01-27-finetuned_sentiment_model_en.md
new file mode 100644
index 00000000000000..1cfbe121e47b2d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-finetuned_sentiment_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuned_sentiment_model DistilBertForSequenceClassification from KoontzP
+author: John Snow Labs
+name: finetuned_sentiment_model
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_sentiment_model` is a English model originally trained by KoontzP.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_sentiment_model_en_5.5.1_3.0_1737939562687.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_sentiment_model_en_5.5.1_3.0_1737939562687.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuned_sentiment_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuned_sentiment_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_sentiment_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/KoontzP/Finetuned-sentiment-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-finetuned_sentiment_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-finetuned_sentiment_model_pipeline_en.md
new file mode 100644
index 00000000000000..9401c13f27aca7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-finetuned_sentiment_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuned_sentiment_model_pipeline pipeline DistilBertForSequenceClassification from KoontzP
+author: John Snow Labs
+name: finetuned_sentiment_model_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_sentiment_model_pipeline` is a English model originally trained by KoontzP.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_sentiment_model_pipeline_en_5.5.1_3.0_1737939576410.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_sentiment_model_pipeline_en_5.5.1_3.0_1737939576410.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuned_sentiment_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuned_sentiment_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_sentiment_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/KoontzP/Finetuned-sentiment-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-finetuning_sentiment_model_3000_samples_2_mo27harakani_en.md b/docs/_posts/ahmedlone127/2025-01-27-finetuning_sentiment_model_3000_samples_2_mo27harakani_en.md
new file mode 100644
index 00000000000000..885f8e9858aab5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-finetuning_sentiment_model_3000_samples_2_mo27harakani_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_2_mo27harakani DistilBertForSequenceClassification from mo27harakani
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_2_mo27harakani
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_2_mo27harakani` is a English model originally trained by mo27harakani.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_2_mo27harakani_en_5.5.1_3.0_1737940066104.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_2_mo27harakani_en_5.5.1_3.0_1737940066104.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_2_mo27harakani","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_2_mo27harakani", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_2_mo27harakani|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/mo27harakani/finetuning-sentiment-model-3000-samples-2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-finetuning_sentiment_model_3000_samples_2_mo27harakani_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-finetuning_sentiment_model_3000_samples_2_mo27harakani_pipeline_en.md
new file mode 100644
index 00000000000000..6808ff2d66f3c5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-finetuning_sentiment_model_3000_samples_2_mo27harakani_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_2_mo27harakani_pipeline pipeline DistilBertForSequenceClassification from mo27harakani
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_2_mo27harakani_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_2_mo27harakani_pipeline` is a English model originally trained by mo27harakani.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_2_mo27harakani_pipeline_en_5.5.1_3.0_1737940079387.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_2_mo27harakani_pipeline_en_5.5.1_3.0_1737940079387.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuning_sentiment_model_3000_samples_2_mo27harakani_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuning_sentiment_model_3000_samples_2_mo27harakani_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_2_mo27harakani_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/mo27harakani/finetuning-sentiment-model-3000-samples-2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-finetuning_sentiment_model_3000_samples_aralbert_en.md b/docs/_posts/ahmedlone127/2025-01-27-finetuning_sentiment_model_3000_samples_aralbert_en.md
new file mode 100644
index 00000000000000..e7c3fb509701fe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-finetuning_sentiment_model_3000_samples_aralbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_aralbert DistilBertForSequenceClassification from aralbert
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_aralbert
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_aralbert` is a English model originally trained by aralbert.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_aralbert_en_5.5.1_3.0_1737939526053.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_aralbert_en_5.5.1_3.0_1737939526053.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_aralbert","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_aralbert", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_aralbert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/aralbert/finetuning-sentiment-model-3000-samples
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-finetuning_sentiment_model_3000_samples_aralbert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-finetuning_sentiment_model_3000_samples_aralbert_pipeline_en.md
new file mode 100644
index 00000000000000..88bb0e7a2e7f4d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-finetuning_sentiment_model_3000_samples_aralbert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_aralbert_pipeline pipeline DistilBertForSequenceClassification from aralbert
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_aralbert_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_aralbert_pipeline` is a English model originally trained by aralbert.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_aralbert_pipeline_en_5.5.1_3.0_1737939538955.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_aralbert_pipeline_en_5.5.1_3.0_1737939538955.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuning_sentiment_model_3000_samples_aralbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuning_sentiment_model_3000_samples_aralbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_aralbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/aralbert/finetuning-sentiment-model-3000-samples
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-finetuning_sentiment_model_3000_samples_mikelodiof1_en.md b/docs/_posts/ahmedlone127/2025-01-27-finetuning_sentiment_model_3000_samples_mikelodiof1_en.md
new file mode 100644
index 00000000000000..b413a82c868846
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-finetuning_sentiment_model_3000_samples_mikelodiof1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_mikelodiof1 DistilBertForSequenceClassification from mikelodiof1
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_mikelodiof1
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_mikelodiof1` is a English model originally trained by mikelodiof1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_mikelodiof1_en_5.5.1_3.0_1737940130084.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_mikelodiof1_en_5.5.1_3.0_1737940130084.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_mikelodiof1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_mikelodiof1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_mikelodiof1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/mikelodiof1/finetuning-sentiment-model-3000-samples
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-finetuning_sentiment_model_3000_samples_mikelodiof1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-finetuning_sentiment_model_3000_samples_mikelodiof1_pipeline_en.md
new file mode 100644
index 00000000000000..45c632090dfd8a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-finetuning_sentiment_model_3000_samples_mikelodiof1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_mikelodiof1_pipeline pipeline DistilBertForSequenceClassification from mikelodiof1
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_mikelodiof1_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_mikelodiof1_pipeline` is a English model originally trained by mikelodiof1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_mikelodiof1_pipeline_en_5.5.1_3.0_1737940143342.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_mikelodiof1_pipeline_en_5.5.1_3.0_1737940143342.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuning_sentiment_model_3000_samples_mikelodiof1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuning_sentiment_model_3000_samples_mikelodiof1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_mikelodiof1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/mikelodiof1/finetuning-sentiment-model-3000-samples
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-finetuning_sentiment_model_3000_samples_sibing_en.md b/docs/_posts/ahmedlone127/2025-01-27-finetuning_sentiment_model_3000_samples_sibing_en.md
new file mode 100644
index 00000000000000..f67521e8652920
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-finetuning_sentiment_model_3000_samples_sibing_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_sibing DistilBertForSequenceClassification from Sibing
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_sibing
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_sibing` is a English model originally trained by Sibing.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_sibing_en_5.5.1_3.0_1737939914067.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_sibing_en_5.5.1_3.0_1737939914067.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_sibing","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_sibing", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_sibing|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Sibing/finetuning-sentiment-model-3000-samples
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-finetuning_sentiment_model_3000_samples_sibing_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-finetuning_sentiment_model_3000_samples_sibing_pipeline_en.md
new file mode 100644
index 00000000000000..24c26ef174d274
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-finetuning_sentiment_model_3000_samples_sibing_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_sibing_pipeline pipeline DistilBertForSequenceClassification from Sibing
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_sibing_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_sibing_pipeline` is a English model originally trained by Sibing.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_sibing_pipeline_en_5.5.1_3.0_1737939927962.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_sibing_pipeline_en_5.5.1_3.0_1737939927962.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuning_sentiment_model_3000_samples_sibing_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuning_sentiment_model_3000_samples_sibing_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_sibing_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Sibing/finetuning-sentiment-model-3000-samples
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-finetuning_sentiment_model_5000_samples_juanhurtado16_en.md b/docs/_posts/ahmedlone127/2025-01-27-finetuning_sentiment_model_5000_samples_juanhurtado16_en.md
new file mode 100644
index 00000000000000..49b190cdf9bf82
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-finetuning_sentiment_model_5000_samples_juanhurtado16_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuning_sentiment_model_5000_samples_juanhurtado16 DistilBertForSequenceClassification from JuanHurtado16
+author: John Snow Labs
+name: finetuning_sentiment_model_5000_samples_juanhurtado16
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_5000_samples_juanhurtado16` is a English model originally trained by JuanHurtado16.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_5000_samples_juanhurtado16_en_5.5.1_3.0_1737939104091.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_5000_samples_juanhurtado16_en_5.5.1_3.0_1737939104091.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_5000_samples_juanhurtado16","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_5000_samples_juanhurtado16", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_5000_samples_juanhurtado16|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/JuanHurtado16/finetuning-sentiment-model-5000-samples
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-finetuning_sentiment_model_5000_samples_juanhurtado16_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-finetuning_sentiment_model_5000_samples_juanhurtado16_pipeline_en.md
new file mode 100644
index 00000000000000..8cbe33dab19e49
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-finetuning_sentiment_model_5000_samples_juanhurtado16_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuning_sentiment_model_5000_samples_juanhurtado16_pipeline pipeline DistilBertForSequenceClassification from JuanHurtado16
+author: John Snow Labs
+name: finetuning_sentiment_model_5000_samples_juanhurtado16_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_5000_samples_juanhurtado16_pipeline` is a English model originally trained by JuanHurtado16.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_5000_samples_juanhurtado16_pipeline_en_5.5.1_3.0_1737939130201.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_5000_samples_juanhurtado16_pipeline_en_5.5.1_3.0_1737939130201.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuning_sentiment_model_5000_samples_juanhurtado16_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuning_sentiment_model_5000_samples_juanhurtado16_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_5000_samples_juanhurtado16_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/JuanHurtado16/finetuning-sentiment-model-5000-samples
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-finetuning_sentiment_model_5000_samples_kurtbadelt_en.md b/docs/_posts/ahmedlone127/2025-01-27-finetuning_sentiment_model_5000_samples_kurtbadelt_en.md
new file mode 100644
index 00000000000000..8cdd46a385f903
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-finetuning_sentiment_model_5000_samples_kurtbadelt_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuning_sentiment_model_5000_samples_kurtbadelt DistilBertForSequenceClassification from KurtBadelt
+author: John Snow Labs
+name: finetuning_sentiment_model_5000_samples_kurtbadelt
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_5000_samples_kurtbadelt` is a English model originally trained by KurtBadelt.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_5000_samples_kurtbadelt_en_5.5.1_3.0_1737939104078.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_5000_samples_kurtbadelt_en_5.5.1_3.0_1737939104078.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_5000_samples_kurtbadelt","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_5000_samples_kurtbadelt", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_5000_samples_kurtbadelt|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/KurtBadelt/finetuning-sentiment-model-5000-samples
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-finetuning_sentiment_model_5000_samples_kurtbadelt_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-finetuning_sentiment_model_5000_samples_kurtbadelt_pipeline_en.md
new file mode 100644
index 00000000000000..f91151c157238d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-finetuning_sentiment_model_5000_samples_kurtbadelt_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuning_sentiment_model_5000_samples_kurtbadelt_pipeline pipeline DistilBertForSequenceClassification from KurtBadelt
+author: John Snow Labs
+name: finetuning_sentiment_model_5000_samples_kurtbadelt_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_5000_samples_kurtbadelt_pipeline` is a English model originally trained by KurtBadelt.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_5000_samples_kurtbadelt_pipeline_en_5.5.1_3.0_1737939127559.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_5000_samples_kurtbadelt_pipeline_en_5.5.1_3.0_1737939127559.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuning_sentiment_model_5000_samples_kurtbadelt_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuning_sentiment_model_5000_samples_kurtbadelt_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_5000_samples_kurtbadelt_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/KurtBadelt/finetuning-sentiment-model-5000-samples
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-flan_t5_base_max_en.md b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_base_max_en.md
new file mode 100644
index 00000000000000..73be2905319985
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_base_max_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English flan_t5_base_max T5Transformer from Jetmaxx
+author: John Snow Labs
+name: flan_t5_base_max
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_base_max` is a English model originally trained by Jetmaxx.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_base_max_en_5.5.1_3.0_1737979942300.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_base_max_en_5.5.1_3.0_1737979942300.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("flan_t5_base_max","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("flan_t5_base_max", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_base_max|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Jetmaxx/flan-t5-base-max
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-flan_t5_base_max_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_base_max_pipeline_en.md
new file mode 100644
index 00000000000000..765725f0f8ee79
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_base_max_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English flan_t5_base_max_pipeline pipeline T5Transformer from Jetmaxx
+author: John Snow Labs
+name: flan_t5_base_max_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_base_max_pipeline` is a English model originally trained by Jetmaxx.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_base_max_pipeline_en_5.5.1_3.0_1737979993019.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_base_max_pipeline_en_5.5.1_3.0_1737979993019.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("flan_t5_base_max_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("flan_t5_base_max_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_base_max_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Jetmaxx/flan-t5-base-max
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-flan_t5_base_spanish_yoremnokki_en.md b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_base_spanish_yoremnokki_en.md
new file mode 100644
index 00000000000000..f9114277c8768f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_base_spanish_yoremnokki_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English flan_t5_base_spanish_yoremnokki T5Transformer from alfsnd
+author: John Snow Labs
+name: flan_t5_base_spanish_yoremnokki
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_base_spanish_yoremnokki` is a English model originally trained by alfsnd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_base_spanish_yoremnokki_en_5.5.1_3.0_1737999825753.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_base_spanish_yoremnokki_en_5.5.1_3.0_1737999825753.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("flan_t5_base_spanish_yoremnokki","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("flan_t5_base_spanish_yoremnokki", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_base_spanish_yoremnokki|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/alfsnd/flan-t5-base-spanish-yoremnokki
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-flan_t5_base_spanish_yoremnokki_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_base_spanish_yoremnokki_pipeline_en.md
new file mode 100644
index 00000000000000..9b456193adc9bf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_base_spanish_yoremnokki_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English flan_t5_base_spanish_yoremnokki_pipeline pipeline T5Transformer from alfsnd
+author: John Snow Labs
+name: flan_t5_base_spanish_yoremnokki_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_base_spanish_yoremnokki_pipeline` is a English model originally trained by alfsnd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_base_spanish_yoremnokki_pipeline_en_5.5.1_3.0_1737999881429.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_base_spanish_yoremnokki_pipeline_en_5.5.1_3.0_1737999881429.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("flan_t5_base_spanish_yoremnokki_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("flan_t5_base_spanish_yoremnokki_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_base_spanish_yoremnokki_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/alfsnd/flan-t5-base-spanish-yoremnokki
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-flan_t5_dutch_fol_baseline_en.md b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_dutch_fol_baseline_en.md
new file mode 100644
index 00000000000000..87952da13eaa9f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_dutch_fol_baseline_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English flan_t5_dutch_fol_baseline T5Transformer from snewmanaa
+author: John Snow Labs
+name: flan_t5_dutch_fol_baseline
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_dutch_fol_baseline` is a English model originally trained by snewmanaa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_dutch_fol_baseline_en_5.5.1_3.0_1737978392398.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_dutch_fol_baseline_en_5.5.1_3.0_1737978392398.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("flan_t5_dutch_fol_baseline","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("flan_t5_dutch_fol_baseline", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_dutch_fol_baseline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/snewmanaa/flan-t5-NL-FOL-baseline
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-flan_t5_dutch_fol_baseline_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_dutch_fol_baseline_pipeline_en.md
new file mode 100644
index 00000000000000..7808188ff318e1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_dutch_fol_baseline_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English flan_t5_dutch_fol_baseline_pipeline pipeline T5Transformer from snewmanaa
+author: John Snow Labs
+name: flan_t5_dutch_fol_baseline_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_dutch_fol_baseline_pipeline` is a English model originally trained by snewmanaa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_dutch_fol_baseline_pipeline_en_5.5.1_3.0_1737978455631.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_dutch_fol_baseline_pipeline_en_5.5.1_3.0_1737978455631.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("flan_t5_dutch_fol_baseline_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("flan_t5_dutch_fol_baseline_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_dutch_fol_baseline_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/snewmanaa/flan-t5-NL-FOL-baseline
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-flan_t5_finetuned_en.md b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_finetuned_en.md
new file mode 100644
index 00000000000000..f3b68ca0c549ca
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_finetuned_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English flan_t5_finetuned T5Transformer from sigilius
+author: John Snow Labs
+name: flan_t5_finetuned
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_finetuned` is a English model originally trained by sigilius.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_finetuned_en_5.5.1_3.0_1738001810454.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_finetuned_en_5.5.1_3.0_1738001810454.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("flan_t5_finetuned","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("flan_t5_finetuned", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_finetuned|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/sigilius/flan-t5-finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-flan_t5_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_finetuned_pipeline_en.md
new file mode 100644
index 00000000000000..7f3c5616a798b0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_finetuned_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English flan_t5_finetuned_pipeline pipeline T5Transformer from sigilius
+author: John Snow Labs
+name: flan_t5_finetuned_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_finetuned_pipeline` is a English model originally trained by sigilius.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_finetuned_pipeline_en_5.5.1_3.0_1738001869188.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_finetuned_pipeline_en_5.5.1_3.0_1738001869188.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("flan_t5_finetuned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("flan_t5_finetuned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_finetuned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/sigilius/flan-t5-finetuned
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-flan_t5_rouge_squad_qg_120_en.md b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_rouge_squad_qg_120_en.md
new file mode 100644
index 00000000000000..66977a077088d6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_rouge_squad_qg_120_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English flan_t5_rouge_squad_qg_120 T5Transformer from devagonal
+author: John Snow Labs
+name: flan_t5_rouge_squad_qg_120
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_rouge_squad_qg_120` is a English model originally trained by devagonal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_rouge_squad_qg_120_en_5.5.1_3.0_1737992091956.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_rouge_squad_qg_120_en_5.5.1_3.0_1737992091956.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("flan_t5_rouge_squad_qg_120","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("flan_t5_rouge_squad_qg_120", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_rouge_squad_qg_120|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/devagonal/flan-t5-rouge-squad-qg-120
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-flan_t5_rouge_squad_qg_120_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_rouge_squad_qg_120_pipeline_en.md
new file mode 100644
index 00000000000000..ec9559aa236f4e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_rouge_squad_qg_120_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English flan_t5_rouge_squad_qg_120_pipeline pipeline T5Transformer from devagonal
+author: John Snow Labs
+name: flan_t5_rouge_squad_qg_120_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_rouge_squad_qg_120_pipeline` is a English model originally trained by devagonal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_rouge_squad_qg_120_pipeline_en_5.5.1_3.0_1737992142847.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_rouge_squad_qg_120_pipeline_en_5.5.1_3.0_1737992142847.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("flan_t5_rouge_squad_qg_120_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("flan_t5_rouge_squad_qg_120_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_rouge_squad_qg_120_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/devagonal/flan-t5-rouge-squad-qg-120
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-flan_t5_rouge_squad_qg_120b_en.md b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_rouge_squad_qg_120b_en.md
new file mode 100644
index 00000000000000..039f5c8cca6262
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_rouge_squad_qg_120b_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English flan_t5_rouge_squad_qg_120b T5Transformer from devagonal
+author: John Snow Labs
+name: flan_t5_rouge_squad_qg_120b
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_rouge_squad_qg_120b` is a English model originally trained by devagonal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_rouge_squad_qg_120b_en_5.5.1_3.0_1737989415575.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_rouge_squad_qg_120b_en_5.5.1_3.0_1737989415575.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("flan_t5_rouge_squad_qg_120b","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("flan_t5_rouge_squad_qg_120b", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_rouge_squad_qg_120b|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/devagonal/flan-t5-rouge-squad-qg-120b
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-flan_t5_rouge_squad_qg_120b_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_rouge_squad_qg_120b_pipeline_en.md
new file mode 100644
index 00000000000000..8cbf73d923ac28
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_rouge_squad_qg_120b_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English flan_t5_rouge_squad_qg_120b_pipeline pipeline T5Transformer from devagonal
+author: John Snow Labs
+name: flan_t5_rouge_squad_qg_120b_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_rouge_squad_qg_120b_pipeline` is a English model originally trained by devagonal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_rouge_squad_qg_120b_pipeline_en_5.5.1_3.0_1737989467151.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_rouge_squad_qg_120b_pipeline_en_5.5.1_3.0_1737989467151.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("flan_t5_rouge_squad_qg_120b_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("flan_t5_rouge_squad_qg_120b_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_rouge_squad_qg_120b_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/devagonal/flan-t5-rouge-squad-qg-120b
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-flan_t5_rouge_squad_qg_60_en.md b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_rouge_squad_qg_60_en.md
new file mode 100644
index 00000000000000..4eac2cd195f6d2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_rouge_squad_qg_60_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English flan_t5_rouge_squad_qg_60 T5Transformer from devagonal
+author: John Snow Labs
+name: flan_t5_rouge_squad_qg_60
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_rouge_squad_qg_60` is a English model originally trained by devagonal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_rouge_squad_qg_60_en_5.5.1_3.0_1737946471402.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_rouge_squad_qg_60_en_5.5.1_3.0_1737946471402.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("flan_t5_rouge_squad_qg_60","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("flan_t5_rouge_squad_qg_60", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_rouge_squad_qg_60|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/devagonal/flan-t5-rouge-squad-qg-60
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-flan_t5_rouge_squad_qg_60_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_rouge_squad_qg_60_pipeline_en.md
new file mode 100644
index 00000000000000..0d876143d3eeec
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_rouge_squad_qg_60_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English flan_t5_rouge_squad_qg_60_pipeline pipeline T5Transformer from devagonal
+author: John Snow Labs
+name: flan_t5_rouge_squad_qg_60_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_rouge_squad_qg_60_pipeline` is a English model originally trained by devagonal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_rouge_squad_qg_60_pipeline_en_5.5.1_3.0_1737946533453.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_rouge_squad_qg_60_pipeline_en_5.5.1_3.0_1737946533453.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("flan_t5_rouge_squad_qg_60_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("flan_t5_rouge_squad_qg_60_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_rouge_squad_qg_60_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/devagonal/flan-t5-rouge-squad-qg-60
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-flan_t5_rouge_squad_qg_en.md b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_rouge_squad_qg_en.md
new file mode 100644
index 00000000000000..79645c578a86b8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_rouge_squad_qg_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English flan_t5_rouge_squad_qg T5Transformer from devagonal
+author: John Snow Labs
+name: flan_t5_rouge_squad_qg
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_rouge_squad_qg` is a English model originally trained by devagonal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_rouge_squad_qg_en_5.5.1_3.0_1737980104995.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_rouge_squad_qg_en_5.5.1_3.0_1737980104995.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("flan_t5_rouge_squad_qg","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("flan_t5_rouge_squad_qg", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_rouge_squad_qg|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/devagonal/flan-t5-rouge-squad-qg
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-flan_t5_rouge_squad_qg_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_rouge_squad_qg_pipeline_en.md
new file mode 100644
index 00000000000000..daafd5e49bd501
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_rouge_squad_qg_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English flan_t5_rouge_squad_qg_pipeline pipeline T5Transformer from devagonal
+author: John Snow Labs
+name: flan_t5_rouge_squad_qg_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_rouge_squad_qg_pipeline` is a English model originally trained by devagonal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_rouge_squad_qg_pipeline_en_5.5.1_3.0_1737980156327.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_rouge_squad_qg_pipeline_en_5.5.1_3.0_1737980156327.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("flan_t5_rouge_squad_qg_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("flan_t5_rouge_squad_qg_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_rouge_squad_qg_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/devagonal/flan-t5-rouge-squad-qg
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-flan_t5_slim_short_en.md b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_slim_short_en.md
new file mode 100644
index 00000000000000..d3d00ef42a576a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_slim_short_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English flan_t5_slim_short T5Transformer from Jawaker
+author: John Snow Labs
+name: flan_t5_slim_short
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_slim_short` is a English model originally trained by Jawaker.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_slim_short_en_5.5.1_3.0_1737992466019.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_slim_short_en_5.5.1_3.0_1737992466019.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("flan_t5_slim_short","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("flan_t5_slim_short", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_slim_short|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|167.2 MB|
+
+## References
+
+https://huggingface.co/Jawaker/flan-t5-slim-short
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-flan_t5_slim_short_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_slim_short_pipeline_en.md
new file mode 100644
index 00000000000000..6bf05f61eb10cd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_slim_short_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English flan_t5_slim_short_pipeline pipeline T5Transformer from Jawaker
+author: John Snow Labs
+name: flan_t5_slim_short_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_slim_short_pipeline` is a English model originally trained by Jawaker.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_slim_short_pipeline_en_5.5.1_3.0_1737992474254.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_slim_short_pipeline_en_5.5.1_3.0_1737992474254.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("flan_t5_slim_short_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("flan_t5_slim_short_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_slim_short_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|167.2 MB|
+
+## References
+
+https://huggingface.co/Jawaker/flan-t5-slim-short
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-flan_t5_small_adarsh_12_en.md b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_small_adarsh_12_en.md
new file mode 100644
index 00000000000000..2c637a4fe65053
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_small_adarsh_12_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English flan_t5_small_adarsh_12 T5Transformer from Adarsh-12
+author: John Snow Labs
+name: flan_t5_small_adarsh_12
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_small_adarsh_12` is a English model originally trained by Adarsh-12.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_small_adarsh_12_en_5.5.1_3.0_1737962289183.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_small_adarsh_12_en_5.5.1_3.0_1737962289183.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("flan_t5_small_adarsh_12","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("flan_t5_small_adarsh_12", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_small_adarsh_12|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|349.8 MB|
+
+## References
+
+https://huggingface.co/Adarsh-12/flan_t5_small
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-flan_t5_small_adarsh_12_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_small_adarsh_12_pipeline_en.md
new file mode 100644
index 00000000000000..bb34ceb483098c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_small_adarsh_12_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English flan_t5_small_adarsh_12_pipeline pipeline T5Transformer from Adarsh-12
+author: John Snow Labs
+name: flan_t5_small_adarsh_12_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_small_adarsh_12_pipeline` is a English model originally trained by Adarsh-12.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_small_adarsh_12_pipeline_en_5.5.1_3.0_1737962306966.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_small_adarsh_12_pipeline_en_5.5.1_3.0_1737962306966.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("flan_t5_small_adarsh_12_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("flan_t5_small_adarsh_12_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_small_adarsh_12_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|349.8 MB|
+
+## References
+
+https://huggingface.co/Adarsh-12/flan_t5_small
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-flan_t5_small_bnfx_en.md b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_small_bnfx_en.md
new file mode 100644
index 00000000000000..4edad13de4375d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_small_bnfx_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English flan_t5_small_bnfx T5Transformer from infra620
+author: John Snow Labs
+name: flan_t5_small_bnfx
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_small_bnfx` is a English model originally trained by infra620.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_small_bnfx_en_5.5.1_3.0_1738001302861.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_small_bnfx_en_5.5.1_3.0_1738001302861.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("flan_t5_small_bnfx","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("flan_t5_small_bnfx", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_small_bnfx|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|349.8 MB|
+
+## References
+
+https://huggingface.co/infra620/flan-t5-small-bnfx
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-flan_t5_small_bnfx_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_small_bnfx_pipeline_en.md
new file mode 100644
index 00000000000000..3b3d7a6989922d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_small_bnfx_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English flan_t5_small_bnfx_pipeline pipeline T5Transformer from infra620
+author: John Snow Labs
+name: flan_t5_small_bnfx_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_small_bnfx_pipeline` is a English model originally trained by infra620.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_small_bnfx_pipeline_en_5.5.1_3.0_1738001321556.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_small_bnfx_pipeline_en_5.5.1_3.0_1738001321556.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("flan_t5_small_bnfx_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("flan_t5_small_bnfx_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_small_bnfx_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|349.8 MB|
+
+## References
+
+https://huggingface.co/infra620/flan-t5-small-bnfx
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-flan_t5_small_gigatrue_incs2s_0_5sparsity_en.md b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_small_gigatrue_incs2s_0_5sparsity_en.md
new file mode 100644
index 00000000000000..49f67a4afad17b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_small_gigatrue_incs2s_0_5sparsity_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English flan_t5_small_gigatrue_incs2s_0_5sparsity T5Transformer from Plasmoxy
+author: John Snow Labs
+name: flan_t5_small_gigatrue_incs2s_0_5sparsity
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_small_gigatrue_incs2s_0_5sparsity` is a English model originally trained by Plasmoxy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_small_gigatrue_incs2s_0_5sparsity_en_5.5.1_3.0_1737945665155.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_small_gigatrue_incs2s_0_5sparsity_en_5.5.1_3.0_1737945665155.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("flan_t5_small_gigatrue_incs2s_0_5sparsity","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("flan_t5_small_gigatrue_incs2s_0_5sparsity", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_small_gigatrue_incs2s_0_5sparsity|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|177.9 MB|
+
+## References
+
+https://huggingface.co/Plasmoxy/flan-t5-small-gigatrue-INCS2S-0.5sparsity
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-flan_t5_small_gigatrue_incs2s_0_5sparsity_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_small_gigatrue_incs2s_0_5sparsity_pipeline_en.md
new file mode 100644
index 00000000000000..66329b9a0428b7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_small_gigatrue_incs2s_0_5sparsity_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English flan_t5_small_gigatrue_incs2s_0_5sparsity_pipeline pipeline T5Transformer from Plasmoxy
+author: John Snow Labs
+name: flan_t5_small_gigatrue_incs2s_0_5sparsity_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_small_gigatrue_incs2s_0_5sparsity_pipeline` is a English model originally trained by Plasmoxy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_small_gigatrue_incs2s_0_5sparsity_pipeline_en_5.5.1_3.0_1737945728145.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_small_gigatrue_incs2s_0_5sparsity_pipeline_en_5.5.1_3.0_1737945728145.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("flan_t5_small_gigatrue_incs2s_0_5sparsity_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("flan_t5_small_gigatrue_incs2s_0_5sparsity_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_small_gigatrue_incs2s_0_5sparsity_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|177.9 MB|
+
+## References
+
+https://huggingface.co/Plasmoxy/flan-t5-small-gigatrue-INCS2S-0.5sparsity
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-flan_t5_small_ner_en.md b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_small_ner_en.md
new file mode 100644
index 00000000000000..0bfccc1cdfa4ca
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_small_ner_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English flan_t5_small_ner T5Transformer from agentlans
+author: John Snow Labs
+name: flan_t5_small_ner
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_small_ner` is a English model originally trained by agentlans.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_small_ner_en_5.5.1_3.0_1737979710793.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_small_ner_en_5.5.1_3.0_1737979710793.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("flan_t5_small_ner","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("flan_t5_small_ner", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_small_ner|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|349.7 MB|
+
+## References
+
+https://huggingface.co/agentlans/flan-t5-small-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-flan_t5_small_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_small_ner_pipeline_en.md
new file mode 100644
index 00000000000000..fc8d7ba9b5ab6d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_small_ner_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English flan_t5_small_ner_pipeline pipeline T5Transformer from agentlans
+author: John Snow Labs
+name: flan_t5_small_ner_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_small_ner_pipeline` is a English model originally trained by agentlans.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_small_ner_pipeline_en_5.5.1_3.0_1737979728849.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_small_ner_pipeline_en_5.5.1_3.0_1737979728849.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("flan_t5_small_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("flan_t5_small_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_small_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|349.7 MB|
+
+## References
+
+https://huggingface.co/agentlans/flan-t5-small-ner
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-flan_t5_small_sih_en.md b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_small_sih_en.md
new file mode 100644
index 00000000000000..96e82c56b8b1a4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_small_sih_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English flan_t5_small_sih T5Transformer from abhilekhborah
+author: John Snow Labs
+name: flan_t5_small_sih
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_small_sih` is a English model originally trained by abhilekhborah.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_small_sih_en_5.5.1_3.0_1738008391109.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_small_sih_en_5.5.1_3.0_1738008391109.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("flan_t5_small_sih","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("flan_t5_small_sih", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_small_sih|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|349.8 MB|
+
+## References
+
+https://huggingface.co/abhilekhborah/flan-t5-small-sih
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-flan_t5_small_sih_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_small_sih_pipeline_en.md
new file mode 100644
index 00000000000000..ec76ee62f03aa8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-flan_t5_small_sih_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English flan_t5_small_sih_pipeline pipeline T5Transformer from abhilekhborah
+author: John Snow Labs
+name: flan_t5_small_sih_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_small_sih_pipeline` is a English model originally trained by abhilekhborah.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_small_sih_pipeline_en_5.5.1_3.0_1738008410113.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_small_sih_pipeline_en_5.5.1_3.0_1738008410113.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("flan_t5_small_sih_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("flan_t5_small_sih_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_small_sih_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|349.8 MB|
+
+## References
+
+https://huggingface.co/abhilekhborah/flan-t5-small-sih
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-flant5_base_en.md b/docs/_posts/ahmedlone127/2025-01-27-flant5_base_en.md
new file mode 100644
index 00000000000000..fda898f146b917
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-flant5_base_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English flant5_base T5Transformer from meoo225
+author: John Snow Labs
+name: flant5_base
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flant5_base` is a English model originally trained by meoo225.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flant5_base_en_5.5.1_3.0_1737962067711.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flant5_base_en_5.5.1_3.0_1737962067711.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("flant5_base","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("flant5_base", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flant5_base|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/meoo225/FLANT5_base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-flant5_base_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-flant5_base_pipeline_en.md
new file mode 100644
index 00000000000000..74c6f49e60f3c0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-flant5_base_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English flant5_base_pipeline pipeline T5Transformer from meoo225
+author: John Snow Labs
+name: flant5_base_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flant5_base_pipeline` is a English model originally trained by meoo225.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flant5_base_pipeline_en_5.5.1_3.0_1737962119003.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flant5_base_pipeline_en_5.5.1_3.0_1737962119003.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("flant5_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("flant5_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flant5_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/meoo225/FLANT5_base
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-flant5_large_sufficiency_classifier_dutch_en.md b/docs/_posts/ahmedlone127/2025-01-27-flant5_large_sufficiency_classifier_dutch_en.md
new file mode 100644
index 00000000000000..46ca7d89438b4d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-flant5_large_sufficiency_classifier_dutch_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English flant5_large_sufficiency_classifier_dutch T5Transformer from yjmsvma
+author: John Snow Labs
+name: flant5_large_sufficiency_classifier_dutch
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flant5_large_sufficiency_classifier_dutch` is a English model originally trained by yjmsvma.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flant5_large_sufficiency_classifier_dutch_en_5.5.1_3.0_1738000416303.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flant5_large_sufficiency_classifier_dutch_en_5.5.1_3.0_1738000416303.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("flant5_large_sufficiency_classifier_dutch","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("flant5_large_sufficiency_classifier_dutch", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flant5_large_sufficiency_classifier_dutch|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|3.1 GB|
+
+## References
+
+https://huggingface.co/yjmsvma/flant5-large-sufficiency-classifier-nl
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-flant5_large_sufficiency_classifier_dutch_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-flant5_large_sufficiency_classifier_dutch_pipeline_en.md
new file mode 100644
index 00000000000000..6540d12b5637e9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-flant5_large_sufficiency_classifier_dutch_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English flant5_large_sufficiency_classifier_dutch_pipeline pipeline T5Transformer from yjmsvma
+author: John Snow Labs
+name: flant5_large_sufficiency_classifier_dutch_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flant5_large_sufficiency_classifier_dutch_pipeline` is a English model originally trained by yjmsvma.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flant5_large_sufficiency_classifier_dutch_pipeline_en_5.5.1_3.0_1738000569637.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flant5_large_sufficiency_classifier_dutch_pipeline_en_5.5.1_3.0_1738000569637.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("flant5_large_sufficiency_classifier_dutch_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("flant5_large_sufficiency_classifier_dutch_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flant5_large_sufficiency_classifier_dutch_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|3.1 GB|
+
+## References
+
+https://huggingface.co/yjmsvma/flant5-large-sufficiency-classifier-nl
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-flant5_large_sufficiency_classifier_en.md b/docs/_posts/ahmedlone127/2025-01-27-flant5_large_sufficiency_classifier_en.md
new file mode 100644
index 00000000000000..d2274c421ac309
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-flant5_large_sufficiency_classifier_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English flant5_large_sufficiency_classifier T5Transformer from yjmsvma
+author: John Snow Labs
+name: flant5_large_sufficiency_classifier
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flant5_large_sufficiency_classifier` is a English model originally trained by yjmsvma.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flant5_large_sufficiency_classifier_en_5.5.1_3.0_1737992034795.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flant5_large_sufficiency_classifier_en_5.5.1_3.0_1737992034795.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("flant5_large_sufficiency_classifier","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("flant5_large_sufficiency_classifier", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flant5_large_sufficiency_classifier|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|3.1 GB|
+
+## References
+
+https://huggingface.co/yjmsvma/flant5-large-sufficiency-classifier
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-flant5_large_sufficiency_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-flant5_large_sufficiency_classifier_pipeline_en.md
new file mode 100644
index 00000000000000..34e0923a57bb87
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-flant5_large_sufficiency_classifier_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English flant5_large_sufficiency_classifier_pipeline pipeline T5Transformer from yjmsvma
+author: John Snow Labs
+name: flant5_large_sufficiency_classifier_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flant5_large_sufficiency_classifier_pipeline` is a English model originally trained by yjmsvma.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flant5_large_sufficiency_classifier_pipeline_en_5.5.1_3.0_1737992178283.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flant5_large_sufficiency_classifier_pipeline_en_5.5.1_3.0_1737992178283.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("flant5_large_sufficiency_classifier_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("flant5_large_sufficiency_classifier_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flant5_large_sufficiency_classifier_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|3.1 GB|
+
+## References
+
+https://huggingface.co/yjmsvma/flant5-large-sufficiency-classifier
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-flux_prompt_enhancer_en.md b/docs/_posts/ahmedlone127/2025-01-27-flux_prompt_enhancer_en.md
new file mode 100644
index 00000000000000..f6d52849bc096d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-flux_prompt_enhancer_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English flux_prompt_enhancer T5Transformer from imranali291
+author: John Snow Labs
+name: flux_prompt_enhancer
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flux_prompt_enhancer` is a English model originally trained by imranali291.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flux_prompt_enhancer_en_5.5.1_3.0_1738002112998.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flux_prompt_enhancer_en_5.5.1_3.0_1738002112998.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("flux_prompt_enhancer","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("flux_prompt_enhancer", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flux_prompt_enhancer|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|283.0 MB|
+
+## References
+
+https://huggingface.co/imranali291/flux-prompt-enhancer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-flux_prompt_enhancer_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-flux_prompt_enhancer_pipeline_en.md
new file mode 100644
index 00000000000000..7138f48c9bcf6a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-flux_prompt_enhancer_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English flux_prompt_enhancer_pipeline pipeline T5Transformer from imranali291
+author: John Snow Labs
+name: flux_prompt_enhancer_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flux_prompt_enhancer_pipeline` is a English model originally trained by imranali291.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flux_prompt_enhancer_pipeline_en_5.5.1_3.0_1738002128777.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flux_prompt_enhancer_pipeline_en_5.5.1_3.0_1738002128777.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("flux_prompt_enhancer_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("flux_prompt_enhancer_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flux_prompt_enhancer_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|283.0 MB|
+
+## References
+
+https://huggingface.co/imranali291/flux-prompt-enhancer
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-fm_tc_hybridxml_multilingual_pipeline_xx.md b/docs/_posts/ahmedlone127/2025-01-27-fm_tc_hybridxml_multilingual_pipeline_xx.md
new file mode 100644
index 00000000000000..e1a51c7eafd3aa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-fm_tc_hybridxml_multilingual_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual fm_tc_hybridxml_multilingual_pipeline pipeline XlmRoBertaForSequenceClassification from adriansanz
+author: John Snow Labs
+name: fm_tc_hybridxml_multilingual_pipeline
+date: 2025-01-27
+tags: [xx, open_source, pipeline, onnx]
+task: Text Classification
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fm_tc_hybridxml_multilingual_pipeline` is a Multilingual model originally trained by adriansanz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fm_tc_hybridxml_multilingual_pipeline_xx_5.5.1_3.0_1737960647597.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fm_tc_hybridxml_multilingual_pipeline_xx_5.5.1_3.0_1737960647597.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fm_tc_hybridxml_multilingual_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fm_tc_hybridxml_multilingual_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fm_tc_hybridxml_multilingual_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|783.3 MB|
+
+## References
+
+https://huggingface.co/adriansanz/fm-tc-hybridXML-MULTILINGUAL
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-fm_tc_hybridxml_multilingual_xx.md b/docs/_posts/ahmedlone127/2025-01-27-fm_tc_hybridxml_multilingual_xx.md
new file mode 100644
index 00000000000000..a6ccde19adef15
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-fm_tc_hybridxml_multilingual_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual fm_tc_hybridxml_multilingual XlmRoBertaForSequenceClassification from adriansanz
+author: John Snow Labs
+name: fm_tc_hybridxml_multilingual
+date: 2025-01-27
+tags: [xx, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fm_tc_hybridxml_multilingual` is a Multilingual model originally trained by adriansanz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fm_tc_hybridxml_multilingual_xx_5.5.1_3.0_1737960508530.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fm_tc_hybridxml_multilingual_xx_5.5.1_3.0_1737960508530.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("fm_tc_hybridxml_multilingual","xx") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("fm_tc_hybridxml_multilingual", "xx")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fm_tc_hybridxml_multilingual|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|xx|
+|Size:|783.3 MB|
+
+## References
+
+https://huggingface.co/adriansanz/fm-tc-hybridXML-MULTILINGUAL
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-food_image_classification_shresthadev403_en.md b/docs/_posts/ahmedlone127/2025-01-27-food_image_classification_shresthadev403_en.md
new file mode 100644
index 00000000000000..c7f28e4f90f03c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-food_image_classification_shresthadev403_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English food_image_classification_shresthadev403 ViTForImageClassification from Shresthadev403
+author: John Snow Labs
+name: food_image_classification_shresthadev403
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`food_image_classification_shresthadev403` is a English model originally trained by Shresthadev403.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/food_image_classification_shresthadev403_en_5.5.1_3.0_1737974570866.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/food_image_classification_shresthadev403_en_5.5.1_3.0_1737974570866.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""food_image_classification_shresthadev403","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("food_image_classification_shresthadev403","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|food_image_classification_shresthadev403|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.6 MB|
+
+## References
+
+https://huggingface.co/Shresthadev403/food-image-classification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-food_image_classification_shresthadev403_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-food_image_classification_shresthadev403_pipeline_en.md
new file mode 100644
index 00000000000000..053a879801edc9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-food_image_classification_shresthadev403_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English food_image_classification_shresthadev403_pipeline pipeline ViTForImageClassification from Shresthadev403
+author: John Snow Labs
+name: food_image_classification_shresthadev403_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`food_image_classification_shresthadev403_pipeline` is a English model originally trained by Shresthadev403.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/food_image_classification_shresthadev403_pipeline_en_5.5.1_3.0_1737974587263.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/food_image_classification_shresthadev403_pipeline_en_5.5.1_3.0_1737974587263.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("food_image_classification_shresthadev403_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("food_image_classification_shresthadev403_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|food_image_classification_shresthadev403_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.6 MB|
+
+## References
+
+https://huggingface.co/Shresthadev403/food-image-classification
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-food_nateraw_en.md b/docs/_posts/ahmedlone127/2025-01-27-food_nateraw_en.md
new file mode 100644
index 00000000000000..8ffe242d7d85b7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-food_nateraw_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English food_nateraw ViTForImageClassification from nateraw
+author: John Snow Labs
+name: food_nateraw
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`food_nateraw` is a English model originally trained by nateraw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/food_nateraw_en_5.5.1_3.0_1738021796001.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/food_nateraw_en_5.5.1_3.0_1738021796001.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""food_nateraw","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("food_nateraw","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|food_nateraw|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.6 MB|
+
+## References
+
+https://huggingface.co/nateraw/food
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-food_nateraw_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-food_nateraw_pipeline_en.md
new file mode 100644
index 00000000000000..f9922610857de0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-food_nateraw_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English food_nateraw_pipeline pipeline ViTForImageClassification from nateraw
+author: John Snow Labs
+name: food_nateraw_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`food_nateraw_pipeline` is a English model originally trained by nateraw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/food_nateraw_pipeline_en_5.5.1_3.0_1738021812019.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/food_nateraw_pipeline_en_5.5.1_3.0_1738021812019.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("food_nateraw_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("food_nateraw_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|food_nateraw_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.6 MB|
+
+## References
+
+https://huggingface.co/nateraw/food
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-food_not_food_model_en.md b/docs/_posts/ahmedlone127/2025-01-27-food_not_food_model_en.md
new file mode 100644
index 00000000000000..df3a9c359df77b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-food_not_food_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English food_not_food_model DistilBertForSequenceClassification from ArhumCodes
+author: John Snow Labs
+name: food_not_food_model
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`food_not_food_model` is a English model originally trained by ArhumCodes.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/food_not_food_model_en_5.5.1_3.0_1737939104067.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/food_not_food_model_en_5.5.1_3.0_1737939104067.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("food_not_food_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("food_not_food_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|food_not_food_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/ArhumCodes/food_not_food_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-food_not_food_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-food_not_food_model_pipeline_en.md
new file mode 100644
index 00000000000000..0321207c3deffb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-food_not_food_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English food_not_food_model_pipeline pipeline DistilBertForSequenceClassification from ArhumCodes
+author: John Snow Labs
+name: food_not_food_model_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`food_not_food_model_pipeline` is a English model originally trained by ArhumCodes.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/food_not_food_model_pipeline_en_5.5.1_3.0_1737939130219.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/food_not_food_model_pipeline_en_5.5.1_3.0_1737939130219.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("food_not_food_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("food_not_food_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|food_not_food_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/ArhumCodes/food_not_food_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-ft5_bleu4_durga_q1_clean_en.md b/docs/_posts/ahmedlone127/2025-01-27-ft5_bleu4_durga_q1_clean_en.md
new file mode 100644
index 00000000000000..7e60f08204f1eb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-ft5_bleu4_durga_q1_clean_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English ft5_bleu4_durga_q1_clean T5Transformer from devagonal
+author: John Snow Labs
+name: ft5_bleu4_durga_q1_clean
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ft5_bleu4_durga_q1_clean` is a English model originally trained by devagonal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ft5_bleu4_durga_q1_clean_en_5.5.1_3.0_1737961478294.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ft5_bleu4_durga_q1_clean_en_5.5.1_3.0_1737961478294.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("ft5_bleu4_durga_q1_clean","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("ft5_bleu4_durga_q1_clean", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ft5_bleu4_durga_q1_clean|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/devagonal/ft5-bleu4-durga-q1-clean
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-ft5_bleu4_durga_q1_clean_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-ft5_bleu4_durga_q1_clean_pipeline_en.md
new file mode 100644
index 00000000000000..797ad48973993f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-ft5_bleu4_durga_q1_clean_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English ft5_bleu4_durga_q1_clean_pipeline pipeline T5Transformer from devagonal
+author: John Snow Labs
+name: ft5_bleu4_durga_q1_clean_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ft5_bleu4_durga_q1_clean_pipeline` is a English model originally trained by devagonal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ft5_bleu4_durga_q1_clean_pipeline_en_5.5.1_3.0_1737961542165.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ft5_bleu4_durga_q1_clean_pipeline_en_5.5.1_3.0_1737961542165.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ft5_bleu4_durga_q1_clean_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ft5_bleu4_durga_q1_clean_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ft5_bleu4_durga_q1_clean_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/devagonal/ft5-bleu4-durga-q1-clean
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-ft5_rouge_durga_q1_clean_en.md b/docs/_posts/ahmedlone127/2025-01-27-ft5_rouge_durga_q1_clean_en.md
new file mode 100644
index 00000000000000..100f68b7b505bb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-ft5_rouge_durga_q1_clean_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English ft5_rouge_durga_q1_clean T5Transformer from devagonal
+author: John Snow Labs
+name: ft5_rouge_durga_q1_clean
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ft5_rouge_durga_q1_clean` is a English model originally trained by devagonal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ft5_rouge_durga_q1_clean_en_5.5.1_3.0_1737961438672.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ft5_rouge_durga_q1_clean_en_5.5.1_3.0_1737961438672.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("ft5_rouge_durga_q1_clean","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("ft5_rouge_durga_q1_clean", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ft5_rouge_durga_q1_clean|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/devagonal/ft5-rouge-durga-q1-clean
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-ft5_rouge_durga_q1_clean_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-ft5_rouge_durga_q1_clean_pipeline_en.md
new file mode 100644
index 00000000000000..c449aaeb113821
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-ft5_rouge_durga_q1_clean_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English ft5_rouge_durga_q1_clean_pipeline pipeline T5Transformer from devagonal
+author: John Snow Labs
+name: ft5_rouge_durga_q1_clean_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ft5_rouge_durga_q1_clean_pipeline` is a English model originally trained by devagonal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ft5_rouge_durga_q1_clean_pipeline_en_5.5.1_3.0_1737961489110.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ft5_rouge_durga_q1_clean_pipeline_en_5.5.1_3.0_1737961489110.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ft5_rouge_durga_q1_clean_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ft5_rouge_durga_q1_clean_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ft5_rouge_durga_q1_clean_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/devagonal/ft5-rouge-durga-q1-clean
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-gate_vit_small_patch16_224_hf_en.md b/docs/_posts/ahmedlone127/2025-01-27-gate_vit_small_patch16_224_hf_en.md
new file mode 100644
index 00000000000000..10b67fd02a015e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-gate_vit_small_patch16_224_hf_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English gate_vit_small_patch16_224_hf ViTForImageClassification from magicslabnu
+author: John Snow Labs
+name: gate_vit_small_patch16_224_hf
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gate_vit_small_patch16_224_hf` is a English model originally trained by magicslabnu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gate_vit_small_patch16_224_hf_en_5.5.1_3.0_1737974342270.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gate_vit_small_patch16_224_hf_en_5.5.1_3.0_1737974342270.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""gate_vit_small_patch16_224_hf","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("gate_vit_small_patch16_224_hf","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gate_vit_small_patch16_224_hf|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|82.6 MB|
+
+## References
+
+https://huggingface.co/magicslabnu/gate_vit_small_patch16_224_hf
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-gate_vit_small_patch16_224_hf_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-gate_vit_small_patch16_224_hf_pipeline_en.md
new file mode 100644
index 00000000000000..76b5b38cd5d0d2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-gate_vit_small_patch16_224_hf_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English gate_vit_small_patch16_224_hf_pipeline pipeline ViTForImageClassification from magicslabnu
+author: John Snow Labs
+name: gate_vit_small_patch16_224_hf_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gate_vit_small_patch16_224_hf_pipeline` is a English model originally trained by magicslabnu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gate_vit_small_patch16_224_hf_pipeline_en_5.5.1_3.0_1737974346355.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gate_vit_small_patch16_224_hf_pipeline_en_5.5.1_3.0_1737974346355.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gate_vit_small_patch16_224_hf_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gate_vit_small_patch16_224_hf_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gate_vit_small_patch16_224_hf_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|82.6 MB|
+
+## References
+
+https://huggingface.co/magicslabnu/gate_vit_small_patch16_224_hf
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-gena_lm_bert_base_t2t_en.md b/docs/_posts/ahmedlone127/2025-01-27-gena_lm_bert_base_t2t_en.md
new file mode 100644
index 00000000000000..ebb6d1b0044d1a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-gena_lm_bert_base_t2t_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English gena_lm_bert_base_t2t BertEmbeddings from AIRI-Institute
+author: John Snow Labs
+name: gena_lm_bert_base_t2t
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gena_lm_bert_base_t2t` is a English model originally trained by AIRI-Institute.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gena_lm_bert_base_t2t_en_5.5.1_3.0_1737954341508.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gena_lm_bert_base_t2t_en_5.5.1_3.0_1737954341508.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("gena_lm_bert_base_t2t","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("gena_lm_bert_base_t2t","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gena_lm_bert_base_t2t|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|262.6 MB|
+
+## References
+
+https://huggingface.co/AIRI-Institute/gena-lm-bert-base-t2t
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-gena_lm_bert_base_t2t_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-gena_lm_bert_base_t2t_pipeline_en.md
new file mode 100644
index 00000000000000..4dd19c4d55ef3c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-gena_lm_bert_base_t2t_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English gena_lm_bert_base_t2t_pipeline pipeline BertEmbeddings from AIRI-Institute
+author: John Snow Labs
+name: gena_lm_bert_base_t2t_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gena_lm_bert_base_t2t_pipeline` is a English model originally trained by AIRI-Institute.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gena_lm_bert_base_t2t_pipeline_en_5.5.1_3.0_1737954416884.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gena_lm_bert_base_t2t_pipeline_en_5.5.1_3.0_1737954416884.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gena_lm_bert_base_t2t_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gena_lm_bert_base_t2t_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gena_lm_bert_base_t2t_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|262.6 MB|
+
+## References
+
+https://huggingface.co/AIRI-Institute/gena-lm-bert-base-t2t
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-gender_hungdang1610_en.md b/docs/_posts/ahmedlone127/2025-01-27-gender_hungdang1610_en.md
new file mode 100644
index 00000000000000..3cbaa0b90124e8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-gender_hungdang1610_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English gender_hungdang1610 ViTForImageClassification from hungdang1610
+author: John Snow Labs
+name: gender_hungdang1610
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gender_hungdang1610` is a English model originally trained by hungdang1610.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gender_hungdang1610_en_5.5.1_3.0_1738022278381.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gender_hungdang1610_en_5.5.1_3.0_1738022278381.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""gender_hungdang1610","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("gender_hungdang1610","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gender_hungdang1610|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/hungdang1610/gender
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-gender_hungdang1610_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-gender_hungdang1610_pipeline_en.md
new file mode 100644
index 00000000000000..3efe0bca3314dc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-gender_hungdang1610_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English gender_hungdang1610_pipeline pipeline ViTForImageClassification from hungdang1610
+author: John Snow Labs
+name: gender_hungdang1610_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gender_hungdang1610_pipeline` is a English model originally trained by hungdang1610.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gender_hungdang1610_pipeline_en_5.5.1_3.0_1738022297619.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gender_hungdang1610_pipeline_en_5.5.1_3.0_1738022297619.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gender_hungdang1610_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gender_hungdang1610_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gender_hungdang1610_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/hungdang1610/gender
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-gendernew_v002_en.md b/docs/_posts/ahmedlone127/2025-01-27-gendernew_v002_en.md
new file mode 100644
index 00000000000000..e6f343f6cb8263
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-gendernew_v002_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English gendernew_v002 ViTForImageClassification from cledoux42
+author: John Snow Labs
+name: gendernew_v002
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gendernew_v002` is a English model originally trained by cledoux42.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gendernew_v002_en_5.5.1_3.0_1737957404976.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gendernew_v002_en_5.5.1_3.0_1737957404976.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""gendernew_v002","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("gendernew_v002","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gendernew_v002|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/cledoux42/GenderNew_v002
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-gendernew_v002_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-gendernew_v002_pipeline_en.md
new file mode 100644
index 00000000000000..7b47a92791c14d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-gendernew_v002_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English gendernew_v002_pipeline pipeline ViTForImageClassification from cledoux42
+author: John Snow Labs
+name: gendernew_v002_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gendernew_v002_pipeline` is a English model originally trained by cledoux42.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gendernew_v002_pipeline_en_5.5.1_3.0_1737957421454.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gendernew_v002_pipeline_en_5.5.1_3.0_1737957421454.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gendernew_v002_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gendernew_v002_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gendernew_v002_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/cledoux42/GenderNew_v002
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-gk_qa_en.md b/docs/_posts/ahmedlone127/2025-01-27-gk_qa_en.md
new file mode 100644
index 00000000000000..98132b58e4a2ed
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-gk_qa_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English gk_qa T5Transformer from Sarathbabu-Karunanithi
+author: John Snow Labs
+name: gk_qa
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gk_qa` is a English model originally trained by Sarathbabu-Karunanithi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gk_qa_en_5.5.1_3.0_1737944309335.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gk_qa_en_5.5.1_3.0_1737944309335.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("gk_qa","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("gk_qa", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gk_qa|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Sarathbabu-Karunanithi/GK_QA
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-gk_qa_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-gk_qa_pipeline_en.md
new file mode 100644
index 00000000000000..d9489e78bcfab5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-gk_qa_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English gk_qa_pipeline pipeline T5Transformer from Sarathbabu-Karunanithi
+author: John Snow Labs
+name: gk_qa_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gk_qa_pipeline` is a English model originally trained by Sarathbabu-Karunanithi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gk_qa_pipeline_en_5.5.1_3.0_1737944363200.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gk_qa_pipeline_en_5.5.1_3.0_1737944363200.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gk_qa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gk_qa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gk_qa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Sarathbabu-Karunanithi/GK_QA
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-google_bert_base_uncased_finetuned_yelp_accelerate_en.md b/docs/_posts/ahmedlone127/2025-01-27-google_bert_base_uncased_finetuned_yelp_accelerate_en.md
new file mode 100644
index 00000000000000..8e2c729d2bcc5e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-google_bert_base_uncased_finetuned_yelp_accelerate_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English google_bert_base_uncased_finetuned_yelp_accelerate BertEmbeddings from adheebhussain
+author: John Snow Labs
+name: google_bert_base_uncased_finetuned_yelp_accelerate
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`google_bert_base_uncased_finetuned_yelp_accelerate` is a English model originally trained by adheebhussain.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/google_bert_base_uncased_finetuned_yelp_accelerate_en_5.5.1_3.0_1737953883942.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/google_bert_base_uncased_finetuned_yelp_accelerate_en_5.5.1_3.0_1737953883942.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("google_bert_base_uncased_finetuned_yelp_accelerate","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("google_bert_base_uncased_finetuned_yelp_accelerate","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|google_bert_base_uncased_finetuned_yelp_accelerate|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/adheebhussain/google-bert-base-uncased-finetuned-yelp-accelerate
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-google_bert_base_uncased_finetuned_yelp_accelerate_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-google_bert_base_uncased_finetuned_yelp_accelerate_pipeline_en.md
new file mode 100644
index 00000000000000..13d8c9e3a39812
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-google_bert_base_uncased_finetuned_yelp_accelerate_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English google_bert_base_uncased_finetuned_yelp_accelerate_pipeline pipeline BertEmbeddings from adheebhussain
+author: John Snow Labs
+name: google_bert_base_uncased_finetuned_yelp_accelerate_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`google_bert_base_uncased_finetuned_yelp_accelerate_pipeline` is a English model originally trained by adheebhussain.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/google_bert_base_uncased_finetuned_yelp_accelerate_pipeline_en_5.5.1_3.0_1737953906911.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/google_bert_base_uncased_finetuned_yelp_accelerate_pipeline_en_5.5.1_3.0_1737953906911.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("google_bert_base_uncased_finetuned_yelp_accelerate_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("google_bert_base_uncased_finetuned_yelp_accelerate_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|google_bert_base_uncased_finetuned_yelp_accelerate_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/adheebhussain/google-bert-base-uncased-finetuned-yelp-accelerate
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-google_flan_large_q_cpu_en.md b/docs/_posts/ahmedlone127/2025-01-27-google_flan_large_q_cpu_en.md
new file mode 100644
index 00000000000000..d8cb14027389cd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-google_flan_large_q_cpu_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English google_flan_large_q_cpu T5Transformer from kartheekkumar65
+author: John Snow Labs
+name: google_flan_large_q_cpu
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`google_flan_large_q_cpu` is a English model originally trained by kartheekkumar65.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/google_flan_large_q_cpu_en_5.5.1_3.0_1738007192463.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/google_flan_large_q_cpu_en_5.5.1_3.0_1738007192463.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("google_flan_large_q_cpu","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("google_flan_large_q_cpu", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|google_flan_large_q_cpu|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|3.1 GB|
+
+## References
+
+https://huggingface.co/kartheekkumar65/google-flan-large-Q-cpu
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-google_flan_large_q_cpu_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-google_flan_large_q_cpu_pipeline_en.md
new file mode 100644
index 00000000000000..a1a4758730e94c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-google_flan_large_q_cpu_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English google_flan_large_q_cpu_pipeline pipeline T5Transformer from kartheekkumar65
+author: John Snow Labs
+name: google_flan_large_q_cpu_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`google_flan_large_q_cpu_pipeline` is a English model originally trained by kartheekkumar65.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/google_flan_large_q_cpu_pipeline_en_5.5.1_3.0_1738007344178.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/google_flan_large_q_cpu_pipeline_en_5.5.1_3.0_1738007344178.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("google_flan_large_q_cpu_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("google_flan_large_q_cpu_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|google_flan_large_q_cpu_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|3.1 GB|
+
+## References
+
+https://huggingface.co/kartheekkumar65/google-flan-large-Q-cpu
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-google_flan_large_q_en.md b/docs/_posts/ahmedlone127/2025-01-27-google_flan_large_q_en.md
new file mode 100644
index 00000000000000..7f01d2fd8a59ce
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-google_flan_large_q_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English google_flan_large_q T5Transformer from kartheekkumar65
+author: John Snow Labs
+name: google_flan_large_q
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`google_flan_large_q` is a English model originally trained by kartheekkumar65.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/google_flan_large_q_en_5.5.1_3.0_1737963970433.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/google_flan_large_q_en_5.5.1_3.0_1737963970433.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("google_flan_large_q","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("google_flan_large_q", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|google_flan_large_q|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|3.1 GB|
+
+## References
+
+https://huggingface.co/kartheekkumar65/google-flan-large-Q
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-google_flan_large_q_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-google_flan_large_q_pipeline_en.md
new file mode 100644
index 00000000000000..51ae5582e1ddda
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-google_flan_large_q_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English google_flan_large_q_pipeline pipeline T5Transformer from kartheekkumar65
+author: John Snow Labs
+name: google_flan_large_q_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`google_flan_large_q_pipeline` is a English model originally trained by kartheekkumar65.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/google_flan_large_q_pipeline_en_5.5.1_3.0_1737964112507.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/google_flan_large_q_pipeline_en_5.5.1_3.0_1737964112507.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("google_flan_large_q_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("google_flan_large_q_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|google_flan_large_q_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|3.1 GB|
+
+## References
+
+https://huggingface.co/kartheekkumar65/google-flan-large-Q
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-google_flan_t5_base_ft_v_2025_01_15_en.md b/docs/_posts/ahmedlone127/2025-01-27-google_flan_t5_base_ft_v_2025_01_15_en.md
new file mode 100644
index 00000000000000..2442901452fab4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-google_flan_t5_base_ft_v_2025_01_15_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English google_flan_t5_base_ft_v_2025_01_15 T5Transformer from Fastgurugroup2
+author: John Snow Labs
+name: google_flan_t5_base_ft_v_2025_01_15
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`google_flan_t5_base_ft_v_2025_01_15` is a English model originally trained by Fastgurugroup2.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/google_flan_t5_base_ft_v_2025_01_15_en_5.5.1_3.0_1737962083200.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/google_flan_t5_base_ft_v_2025_01_15_en_5.5.1_3.0_1737962083200.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("google_flan_t5_base_ft_v_2025_01_15","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("google_flan_t5_base_ft_v_2025_01_15", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|google_flan_t5_base_ft_v_2025_01_15|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Fastgurugroup2/google-flan-t5-base_FT_v_2025-01-15
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-google_flan_t5_base_ft_v_2025_01_15_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-google_flan_t5_base_ft_v_2025_01_15_pipeline_en.md
new file mode 100644
index 00000000000000..4147b69e8356b1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-google_flan_t5_base_ft_v_2025_01_15_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English google_flan_t5_base_ft_v_2025_01_15_pipeline pipeline T5Transformer from Fastgurugroup2
+author: John Snow Labs
+name: google_flan_t5_base_ft_v_2025_01_15_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`google_flan_t5_base_ft_v_2025_01_15_pipeline` is a English model originally trained by Fastgurugroup2.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/google_flan_t5_base_ft_v_2025_01_15_pipeline_en_5.5.1_3.0_1737962134187.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/google_flan_t5_base_ft_v_2025_01_15_pipeline_en_5.5.1_3.0_1737962134187.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("google_flan_t5_base_ft_v_2025_01_15_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("google_flan_t5_base_ft_v_2025_01_15_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|google_flan_t5_base_ft_v_2025_01_15_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Fastgurugroup2/google-flan-t5-base_FT_v_2025-01-15
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-google_t5_base_grammatical_error_correction_finetuned_c4_200m_550k_en.md b/docs/_posts/ahmedlone127/2025-01-27-google_t5_base_grammatical_error_correction_finetuned_c4_200m_550k_en.md
new file mode 100644
index 00000000000000..cedf823b17aebd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-google_t5_base_grammatical_error_correction_finetuned_c4_200m_550k_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English google_t5_base_grammatical_error_correction_finetuned_c4_200m_550k T5Transformer from abhinavsarkar
+author: John Snow Labs
+name: google_t5_base_grammatical_error_correction_finetuned_c4_200m_550k
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`google_t5_base_grammatical_error_correction_finetuned_c4_200m_550k` is a English model originally trained by abhinavsarkar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/google_t5_base_grammatical_error_correction_finetuned_c4_200m_550k_en_5.5.1_3.0_1737980242460.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/google_t5_base_grammatical_error_correction_finetuned_c4_200m_550k_en_5.5.1_3.0_1737980242460.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("google_t5_base_grammatical_error_correction_finetuned_c4_200m_550k","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("google_t5_base_grammatical_error_correction_finetuned_c4_200m_550k", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|google_t5_base_grammatical_error_correction_finetuned_c4_200m_550k|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|914.6 MB|
+
+## References
+
+https://huggingface.co/abhinavsarkar/Google-T5-base-Grammatical_Error_Correction-Finetuned-C4-200M-550k
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-google_t5_base_grammatical_error_correction_finetuned_c4_200m_550k_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-google_t5_base_grammatical_error_correction_finetuned_c4_200m_550k_pipeline_en.md
new file mode 100644
index 00000000000000..88c8511bfa6960
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-google_t5_base_grammatical_error_correction_finetuned_c4_200m_550k_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English google_t5_base_grammatical_error_correction_finetuned_c4_200m_550k_pipeline pipeline T5Transformer from abhinavsarkar
+author: John Snow Labs
+name: google_t5_base_grammatical_error_correction_finetuned_c4_200m_550k_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`google_t5_base_grammatical_error_correction_finetuned_c4_200m_550k_pipeline` is a English model originally trained by abhinavsarkar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/google_t5_base_grammatical_error_correction_finetuned_c4_200m_550k_pipeline_en_5.5.1_3.0_1737980290175.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/google_t5_base_grammatical_error_correction_finetuned_c4_200m_550k_pipeline_en_5.5.1_3.0_1737980290175.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("google_t5_base_grammatical_error_correction_finetuned_c4_200m_550k_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("google_t5_base_grammatical_error_correction_finetuned_c4_200m_550k_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|google_t5_base_grammatical_error_correction_finetuned_c4_200m_550k_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|914.6 MB|
+
+## References
+
+https://huggingface.co/abhinavsarkar/Google-T5-base-Grammatical_Error_Correction-Finetuned-C4-200M-550k
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-google_vit_base_patch16_224_batch32_lr5e_05_standford_dogs_en.md b/docs/_posts/ahmedlone127/2025-01-27-google_vit_base_patch16_224_batch32_lr5e_05_standford_dogs_en.md
new file mode 100644
index 00000000000000..652beba7f7fe1b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-google_vit_base_patch16_224_batch32_lr5e_05_standford_dogs_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English google_vit_base_patch16_224_batch32_lr5e_05_standford_dogs ViTForImageClassification from amaye15
+author: John Snow Labs
+name: google_vit_base_patch16_224_batch32_lr5e_05_standford_dogs
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`google_vit_base_patch16_224_batch32_lr5e_05_standford_dogs` is a English model originally trained by amaye15.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/google_vit_base_patch16_224_batch32_lr5e_05_standford_dogs_en_5.5.1_3.0_1737975158300.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/google_vit_base_patch16_224_batch32_lr5e_05_standford_dogs_en_5.5.1_3.0_1737975158300.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""google_vit_base_patch16_224_batch32_lr5e_05_standford_dogs","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("google_vit_base_patch16_224_batch32_lr5e_05_standford_dogs","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|google_vit_base_patch16_224_batch32_lr5e_05_standford_dogs|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.7 MB|
+
+## References
+
+https://huggingface.co/amaye15/google-vit-base-patch16-224-batch32-lr5e-05-standford-dogs
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-google_vit_base_patch16_224_batch32_lr5e_05_standford_dogs_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-google_vit_base_patch16_224_batch32_lr5e_05_standford_dogs_pipeline_en.md
new file mode 100644
index 00000000000000..ddbfb0a428a15e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-google_vit_base_patch16_224_batch32_lr5e_05_standford_dogs_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English google_vit_base_patch16_224_batch32_lr5e_05_standford_dogs_pipeline pipeline ViTForImageClassification from amaye15
+author: John Snow Labs
+name: google_vit_base_patch16_224_batch32_lr5e_05_standford_dogs_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`google_vit_base_patch16_224_batch32_lr5e_05_standford_dogs_pipeline` is a English model originally trained by amaye15.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/google_vit_base_patch16_224_batch32_lr5e_05_standford_dogs_pipeline_en_5.5.1_3.0_1737975174503.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/google_vit_base_patch16_224_batch32_lr5e_05_standford_dogs_pipeline_en_5.5.1_3.0_1737975174503.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("google_vit_base_patch16_224_batch32_lr5e_05_standford_dogs_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("google_vit_base_patch16_224_batch32_lr5e_05_standford_dogs_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|google_vit_base_patch16_224_batch32_lr5e_05_standford_dogs_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.7 MB|
+
+## References
+
+https://huggingface.co/amaye15/google-vit-base-patch16-224-batch32-lr5e-05-standford-dogs
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-gpt2_chizuruv2_en.md b/docs/_posts/ahmedlone127/2025-01-27-gpt2_chizuruv2_en.md
new file mode 100644
index 00000000000000..2be334b15e2b30
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-gpt2_chizuruv2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English gpt2_chizuruv2 GPT2Transformer from AkumaLucif3r
+author: John Snow Labs
+name: gpt2_chizuruv2
+date: 2025-01-27
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_chizuruv2` is a English model originally trained by AkumaLucif3r.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_chizuruv2_en_5.5.1_3.0_1737995275584.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_chizuruv2_en_5.5.1_3.0_1737995275584.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("gpt2_chizuruv2","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("gpt2_chizuruv2","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_chizuruv2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/AkumaLucif3r/GPT2-ChizuruV2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-gpt2_chizuruv2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-gpt2_chizuruv2_pipeline_en.md
new file mode 100644
index 00000000000000..9b1d72e971b78a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-gpt2_chizuruv2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English gpt2_chizuruv2_pipeline pipeline GPT2Transformer from AkumaLucif3r
+author: John Snow Labs
+name: gpt2_chizuruv2_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_chizuruv2_pipeline` is a English model originally trained by AkumaLucif3r.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_chizuruv2_pipeline_en_5.5.1_3.0_1737995302734.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_chizuruv2_pipeline_en_5.5.1_3.0_1737995302734.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpt2_chizuruv2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpt2_chizuruv2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_chizuruv2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/AkumaLucif3r/GPT2-ChizuruV2
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-gpt2_finetuned_wikitext2_lengoctuong_en.md b/docs/_posts/ahmedlone127/2025-01-27-gpt2_finetuned_wikitext2_lengoctuong_en.md
new file mode 100644
index 00000000000000..27642c6f4a1798
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-gpt2_finetuned_wikitext2_lengoctuong_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English gpt2_finetuned_wikitext2_lengoctuong GPT2Transformer from lengoctuong
+author: John Snow Labs
+name: gpt2_finetuned_wikitext2_lengoctuong
+date: 2025-01-27
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_finetuned_wikitext2_lengoctuong` is a English model originally trained by lengoctuong.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_finetuned_wikitext2_lengoctuong_en_5.5.1_3.0_1737994649186.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_finetuned_wikitext2_lengoctuong_en_5.5.1_3.0_1737994649186.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("gpt2_finetuned_wikitext2_lengoctuong","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("gpt2_finetuned_wikitext2_lengoctuong","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_finetuned_wikitext2_lengoctuong|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/lengoctuong/gpt2-finetuned-wikitext2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-gpt2_finetuned_wikitext2_lengoctuong_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-gpt2_finetuned_wikitext2_lengoctuong_pipeline_en.md
new file mode 100644
index 00000000000000..447463bf4a3ad6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-gpt2_finetuned_wikitext2_lengoctuong_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English gpt2_finetuned_wikitext2_lengoctuong_pipeline pipeline GPT2Transformer from lengoctuong
+author: John Snow Labs
+name: gpt2_finetuned_wikitext2_lengoctuong_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_finetuned_wikitext2_lengoctuong_pipeline` is a English model originally trained by lengoctuong.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_finetuned_wikitext2_lengoctuong_pipeline_en_5.5.1_3.0_1737994672856.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_finetuned_wikitext2_lengoctuong_pipeline_en_5.5.1_3.0_1737994672856.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpt2_finetuned_wikitext2_lengoctuong_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpt2_finetuned_wikitext2_lengoctuong_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_finetuned_wikitext2_lengoctuong_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/lengoctuong/gpt2-finetuned-wikitext2
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-gpt2_medium_indonesian_indonesian_nlp_id.md b/docs/_posts/ahmedlone127/2025-01-27-gpt2_medium_indonesian_indonesian_nlp_id.md
new file mode 100644
index 00000000000000..2e15b4af51bdfc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-gpt2_medium_indonesian_indonesian_nlp_id.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Indonesian gpt2_medium_indonesian_indonesian_nlp GPT2Transformer from indonesian-nlp
+author: John Snow Labs
+name: gpt2_medium_indonesian_indonesian_nlp
+date: 2025-01-27
+tags: [id, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: id
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_medium_indonesian_indonesian_nlp` is a Indonesian model originally trained by indonesian-nlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_medium_indonesian_indonesian_nlp_id_5.5.1_3.0_1737997709395.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_medium_indonesian_indonesian_nlp_id_5.5.1_3.0_1737997709395.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("gpt2_medium_indonesian_indonesian_nlp","id") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("gpt2_medium_indonesian_indonesian_nlp","id") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_medium_indonesian_indonesian_nlp|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|id|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/indonesian-nlp/gpt2-medium-indonesian
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-gpt2_medium_indonesian_indonesian_nlp_pipeline_id.md b/docs/_posts/ahmedlone127/2025-01-27-gpt2_medium_indonesian_indonesian_nlp_pipeline_id.md
new file mode 100644
index 00000000000000..5fd81c84908c46
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-gpt2_medium_indonesian_indonesian_nlp_pipeline_id.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Indonesian gpt2_medium_indonesian_indonesian_nlp_pipeline pipeline GPT2Transformer from indonesian-nlp
+author: John Snow Labs
+name: gpt2_medium_indonesian_indonesian_nlp_pipeline
+date: 2025-01-27
+tags: [id, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: id
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_medium_indonesian_indonesian_nlp_pipeline` is a Indonesian model originally trained by indonesian-nlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_medium_indonesian_indonesian_nlp_pipeline_id_5.5.1_3.0_1737997776491.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_medium_indonesian_indonesian_nlp_pipeline_id_5.5.1_3.0_1737997776491.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpt2_medium_indonesian_indonesian_nlp_pipeline", lang = "id")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpt2_medium_indonesian_indonesian_nlp_pipeline", lang = "id")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_medium_indonesian_indonesian_nlp_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|id|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/indonesian-nlp/gpt2-medium-indonesian
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-gpt3_narsil_en.md b/docs/_posts/ahmedlone127/2025-01-27-gpt3_narsil_en.md
new file mode 100644
index 00000000000000..89470f10f7c6a4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-gpt3_narsil_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English gpt3_narsil GPT2Transformer from Narsil
+author: John Snow Labs
+name: gpt3_narsil
+date: 2025-01-27
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt3_narsil` is a English model originally trained by Narsil.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt3_narsil_en_5.5.1_3.0_1737996230240.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt3_narsil_en_5.5.1_3.0_1737996230240.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("gpt3_narsil","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("gpt3_narsil","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt3_narsil|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/Narsil/gpt3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-gpt3_narsil_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-gpt3_narsil_pipeline_en.md
new file mode 100644
index 00000000000000..aa03ca288c1982
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-gpt3_narsil_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English gpt3_narsil_pipeline pipeline GPT2Transformer from Narsil
+author: John Snow Labs
+name: gpt3_narsil_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt3_narsil_pipeline` is a English model originally trained by Narsil.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt3_narsil_pipeline_en_5.5.1_3.0_1737996254336.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt3_narsil_pipeline_en_5.5.1_3.0_1737996254336.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpt3_narsil_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpt3_narsil_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt3_narsil_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/Narsil/gpt3
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-grammar_correction_t5_small_en.md b/docs/_posts/ahmedlone127/2025-01-27-grammar_correction_t5_small_en.md
new file mode 100644
index 00000000000000..9efb421f621d16
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-grammar_correction_t5_small_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English grammar_correction_t5_small T5Transformer from nezahatkorkmaz
+author: John Snow Labs
+name: grammar_correction_t5_small
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`grammar_correction_t5_small` is a English model originally trained by nezahatkorkmaz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/grammar_correction_t5_small_en_5.5.1_3.0_1738006430726.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/grammar_correction_t5_small_en_5.5.1_3.0_1738006430726.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("grammar_correction_t5_small","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("grammar_correction_t5_small", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|grammar_correction_t5_small|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|275.3 MB|
+
+## References
+
+https://huggingface.co/nezahatkorkmaz/grammar-correction-t5-small
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-grammar_correction_t5_small_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-grammar_correction_t5_small_pipeline_en.md
new file mode 100644
index 00000000000000..60dcd46e750471
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-grammar_correction_t5_small_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English grammar_correction_t5_small_pipeline pipeline T5Transformer from nezahatkorkmaz
+author: John Snow Labs
+name: grammar_correction_t5_small_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`grammar_correction_t5_small_pipeline` is a English model originally trained by nezahatkorkmaz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/grammar_correction_t5_small_pipeline_en_5.5.1_3.0_1738006448113.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/grammar_correction_t5_small_pipeline_en_5.5.1_3.0_1738006448113.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("grammar_correction_t5_small_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("grammar_correction_t5_small_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|grammar_correction_t5_small_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|275.3 MB|
+
+## References
+
+https://huggingface.co/nezahatkorkmaz/grammar-correction-t5-small
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-hair_color_en.md b/docs/_posts/ahmedlone127/2025-01-27-hair_color_en.md
new file mode 100644
index 00000000000000..c3534fd8bec3f5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-hair_color_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English hair_color ViTForImageClassification from enzostvs
+author: John Snow Labs
+name: hair_color
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hair_color` is a English model originally trained by enzostvs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hair_color_en_5.5.1_3.0_1737956879328.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hair_color_en_5.5.1_3.0_1737956879328.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""hair_color","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("hair_color","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hair_color|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/enzostvs/hair-color
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-hair_color_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-hair_color_pipeline_en.md
new file mode 100644
index 00000000000000..53f9df01b1560b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-hair_color_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English hair_color_pipeline pipeline ViTForImageClassification from enzostvs
+author: John Snow Labs
+name: hair_color_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hair_color_pipeline` is a English model originally trained by enzostvs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hair_color_pipeline_en_5.5.1_3.0_1737956896688.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hair_color_pipeline_en_5.5.1_3.0_1737956896688.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("hair_color_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hair_color_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hair_color_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/enzostvs/hair-color
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-hf_nlp_dirty_en.md b/docs/_posts/ahmedlone127/2025-01-27-hf_nlp_dirty_en.md
new file mode 100644
index 00000000000000..7de96b5ad624ec
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-hf_nlp_dirty_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English hf_nlp_dirty CamemBertEmbeddings from sarincasm
+author: John Snow Labs
+name: hf_nlp_dirty
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hf_nlp_dirty` is a English model originally trained by sarincasm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hf_nlp_dirty_en_5.5.1_3.0_1737975885387.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hf_nlp_dirty_en_5.5.1_3.0_1737975885387.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("hf_nlp_dirty","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("hf_nlp_dirty","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hf_nlp_dirty|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/sarincasm/hf-nlp-dirty
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-hf_nlp_dirty_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-hf_nlp_dirty_pipeline_en.md
new file mode 100644
index 00000000000000..c6d980880b0551
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-hf_nlp_dirty_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English hf_nlp_dirty_pipeline pipeline CamemBertEmbeddings from sarincasm
+author: John Snow Labs
+name: hf_nlp_dirty_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hf_nlp_dirty_pipeline` is a English model originally trained by sarincasm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hf_nlp_dirty_pipeline_en_5.5.1_3.0_1737975959757.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hf_nlp_dirty_pipeline_en_5.5.1_3.0_1737975959757.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("hf_nlp_dirty_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hf_nlp_dirty_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hf_nlp_dirty_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/sarincasm/hf-nlp-dirty
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-hf_text_classification_en.md b/docs/_posts/ahmedlone127/2025-01-27-hf_text_classification_en.md
new file mode 100644
index 00000000000000..9fc1a021c02516
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-hf_text_classification_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English hf_text_classification DistilBertForSequenceClassification from ngchuchi
+author: John Snow Labs
+name: hf_text_classification
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hf_text_classification` is a English model originally trained by ngchuchi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hf_text_classification_en_5.5.1_3.0_1737940022997.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hf_text_classification_en_5.5.1_3.0_1737940022997.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("hf_text_classification","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("hf_text_classification", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hf_text_classification|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/ngchuchi/hf_text_classification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-hf_text_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-hf_text_classification_pipeline_en.md
new file mode 100644
index 00000000000000..9d933b2306d05e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-hf_text_classification_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English hf_text_classification_pipeline pipeline DistilBertForSequenceClassification from ngchuchi
+author: John Snow Labs
+name: hf_text_classification_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hf_text_classification_pipeline` is a English model originally trained by ngchuchi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hf_text_classification_pipeline_en_5.5.1_3.0_1737940036594.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hf_text_classification_pipeline_en_5.5.1_3.0_1737940036594.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("hf_text_classification_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hf_text_classification_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hf_text_classification_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/ngchuchi/hf_text_classification
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-homeo_vet_1a_en.md b/docs/_posts/ahmedlone127/2025-01-27-homeo_vet_1a_en.md
new file mode 100644
index 00000000000000..e3e8b82a7baed1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-homeo_vet_1a_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English homeo_vet_1a T5Transformer from Arambh
+author: John Snow Labs
+name: homeo_vet_1a
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`homeo_vet_1a` is a English model originally trained by Arambh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/homeo_vet_1a_en_5.5.1_3.0_1738000099186.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/homeo_vet_1a_en_5.5.1_3.0_1738000099186.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("homeo_vet_1a","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("homeo_vet_1a", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|homeo_vet_1a|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|238.5 MB|
+
+## References
+
+https://huggingface.co/Arambh/homeo-vet-1a
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-homeo_vet_1a_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-homeo_vet_1a_pipeline_en.md
new file mode 100644
index 00000000000000..1783ac62ee5be9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-homeo_vet_1a_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English homeo_vet_1a_pipeline pipeline T5Transformer from Arambh
+author: John Snow Labs
+name: homeo_vet_1a_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`homeo_vet_1a_pipeline` is a English model originally trained by Arambh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/homeo_vet_1a_pipeline_en_5.5.1_3.0_1738000122103.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/homeo_vet_1a_pipeline_en_5.5.1_3.0_1738000122103.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("homeo_vet_1a_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("homeo_vet_1a_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|homeo_vet_1a_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|238.5 MB|
+
+## References
+
+https://huggingface.co/Arambh/homeo-vet-1a
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-idt5_base_qaqg_tydiqa_v1_en.md b/docs/_posts/ahmedlone127/2025-01-27-idt5_base_qaqg_tydiqa_v1_en.md
new file mode 100644
index 00000000000000..5b49270ae6b892
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-idt5_base_qaqg_tydiqa_v1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English idt5_base_qaqg_tydiqa_v1 T5Transformer from hawalurahman
+author: John Snow Labs
+name: idt5_base_qaqg_tydiqa_v1
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`idt5_base_qaqg_tydiqa_v1` is a English model originally trained by hawalurahman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/idt5_base_qaqg_tydiqa_v1_en_5.5.1_3.0_1738006688924.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/idt5_base_qaqg_tydiqa_v1_en_5.5.1_3.0_1738006688924.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("idt5_base_qaqg_tydiqa_v1","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("idt5_base_qaqg_tydiqa_v1", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|idt5_base_qaqg_tydiqa_v1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|976.9 MB|
+
+## References
+
+https://huggingface.co/hawalurahman/idt5-base-qaqg-TydiQA-v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-idt5_base_qaqg_tydiqa_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-idt5_base_qaqg_tydiqa_v1_pipeline_en.md
new file mode 100644
index 00000000000000..5cb5365e893f97
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-idt5_base_qaqg_tydiqa_v1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English idt5_base_qaqg_tydiqa_v1_pipeline pipeline T5Transformer from hawalurahman
+author: John Snow Labs
+name: idt5_base_qaqg_tydiqa_v1_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`idt5_base_qaqg_tydiqa_v1_pipeline` is a English model originally trained by hawalurahman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/idt5_base_qaqg_tydiqa_v1_pipeline_en_5.5.1_3.0_1738006741661.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/idt5_base_qaqg_tydiqa_v1_pipeline_en_5.5.1_3.0_1738006741661.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("idt5_base_qaqg_tydiqa_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("idt5_base_qaqg_tydiqa_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|idt5_base_qaqg_tydiqa_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|976.9 MB|
+
+## References
+
+https://huggingface.co/hawalurahman/idt5-base-qaqg-TydiQA-v1
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-idt5_base_qg_baseline_tydiqa_indonesian_en.md b/docs/_posts/ahmedlone127/2025-01-27-idt5_base_qg_baseline_tydiqa_indonesian_en.md
new file mode 100644
index 00000000000000..3f5d0d33cf540c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-idt5_base_qg_baseline_tydiqa_indonesian_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English idt5_base_qg_baseline_tydiqa_indonesian T5Transformer from hawalurahman
+author: John Snow Labs
+name: idt5_base_qg_baseline_tydiqa_indonesian
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`idt5_base_qg_baseline_tydiqa_indonesian` is a English model originally trained by hawalurahman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/idt5_base_qg_baseline_tydiqa_indonesian_en_5.5.1_3.0_1737944831676.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/idt5_base_qg_baseline_tydiqa_indonesian_en_5.5.1_3.0_1737944831676.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("idt5_base_qg_baseline_tydiqa_indonesian","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("idt5_base_qg_baseline_tydiqa_indonesian", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|idt5_base_qg_baseline_tydiqa_indonesian|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|972.9 MB|
+
+## References
+
+https://huggingface.co/hawalurahman/idt5-base-qg-baseline-TydiQA-id
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-idt5_base_qg_baseline_tydiqa_indonesian_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-idt5_base_qg_baseline_tydiqa_indonesian_pipeline_en.md
new file mode 100644
index 00000000000000..6bda3d38caa354
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-idt5_base_qg_baseline_tydiqa_indonesian_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English idt5_base_qg_baseline_tydiqa_indonesian_pipeline pipeline T5Transformer from hawalurahman
+author: John Snow Labs
+name: idt5_base_qg_baseline_tydiqa_indonesian_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`idt5_base_qg_baseline_tydiqa_indonesian_pipeline` is a English model originally trained by hawalurahman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/idt5_base_qg_baseline_tydiqa_indonesian_pipeline_en_5.5.1_3.0_1737944892517.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/idt5_base_qg_baseline_tydiqa_indonesian_pipeline_en_5.5.1_3.0_1737944892517.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("idt5_base_qg_baseline_tydiqa_indonesian_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("idt5_base_qg_baseline_tydiqa_indonesian_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|idt5_base_qg_baseline_tydiqa_indonesian_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|972.9 MB|
+
+## References
+
+https://huggingface.co/hawalurahman/idt5-base-qg-baseline-TydiQA-id
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-image_classification_fullstuck_en.md b/docs/_posts/ahmedlone127/2025-01-27-image_classification_fullstuck_en.md
new file mode 100644
index 00000000000000..2f1529fb62f827
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-image_classification_fullstuck_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English image_classification_fullstuck ViTForImageClassification from fullstuck
+author: John Snow Labs
+name: image_classification_fullstuck
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`image_classification_fullstuck` is a English model originally trained by fullstuck.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/image_classification_fullstuck_en_5.5.1_3.0_1738021150630.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/image_classification_fullstuck_en_5.5.1_3.0_1738021150630.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""image_classification_fullstuck","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("image_classification_fullstuck","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|image_classification_fullstuck|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/fullstuck/image_classification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-image_classification_fullstuck_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-image_classification_fullstuck_pipeline_en.md
new file mode 100644
index 00000000000000..ce0c52bd4e919a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-image_classification_fullstuck_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English image_classification_fullstuck_pipeline pipeline ViTForImageClassification from fullstuck
+author: John Snow Labs
+name: image_classification_fullstuck_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`image_classification_fullstuck_pipeline` is a English model originally trained by fullstuck.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/image_classification_fullstuck_pipeline_en_5.5.1_3.0_1738021176339.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/image_classification_fullstuck_pipeline_en_5.5.1_3.0_1738021176339.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("image_classification_fullstuck_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("image_classification_fullstuck_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|image_classification_fullstuck_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/fullstuck/image_classification
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-image_classification_kausarme_en.md b/docs/_posts/ahmedlone127/2025-01-27-image_classification_kausarme_en.md
new file mode 100644
index 00000000000000..51d32ab3962653
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-image_classification_kausarme_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English image_classification_kausarme ViTForImageClassification from kausarme
+author: John Snow Labs
+name: image_classification_kausarme
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`image_classification_kausarme` is a English model originally trained by kausarme.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/image_classification_kausarme_en_5.5.1_3.0_1737975173429.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/image_classification_kausarme_en_5.5.1_3.0_1737975173429.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""image_classification_kausarme","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("image_classification_kausarme","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|image_classification_kausarme|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/kausarme/image_classification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-image_classification_kausarme_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-image_classification_kausarme_pipeline_en.md
new file mode 100644
index 00000000000000..aa8b891151218a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-image_classification_kausarme_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English image_classification_kausarme_pipeline pipeline ViTForImageClassification from kausarme
+author: John Snow Labs
+name: image_classification_kausarme_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`image_classification_kausarme_pipeline` is a English model originally trained by kausarme.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/image_classification_kausarme_pipeline_en_5.5.1_3.0_1737975191657.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/image_classification_kausarme_pipeline_en_5.5.1_3.0_1737975191657.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("image_classification_kausarme_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("image_classification_kausarme_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|image_classification_kausarme_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/kausarme/image_classification
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-imdbreviews_classification_distilbert_v02_clf_finetuning_felohdez_en.md b/docs/_posts/ahmedlone127/2025-01-27-imdbreviews_classification_distilbert_v02_clf_finetuning_felohdez_en.md
new file mode 100644
index 00000000000000..7d19472927bd9c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-imdbreviews_classification_distilbert_v02_clf_finetuning_felohdez_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English imdbreviews_classification_distilbert_v02_clf_finetuning_felohdez DistilBertForSequenceClassification from felohdez
+author: John Snow Labs
+name: imdbreviews_classification_distilbert_v02_clf_finetuning_felohdez
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`imdbreviews_classification_distilbert_v02_clf_finetuning_felohdez` is a English model originally trained by felohdez.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/imdbreviews_classification_distilbert_v02_clf_finetuning_felohdez_en_5.5.1_3.0_1737939334477.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/imdbreviews_classification_distilbert_v02_clf_finetuning_felohdez_en_5.5.1_3.0_1737939334477.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("imdbreviews_classification_distilbert_v02_clf_finetuning_felohdez","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("imdbreviews_classification_distilbert_v02_clf_finetuning_felohdez", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|imdbreviews_classification_distilbert_v02_clf_finetuning_felohdez|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/felohdez/imdbreviews_classification_distilbert_v02_clf_finetuning
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-imdbreviews_classification_distilbert_v02_clf_finetuning_felohdez_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-imdbreviews_classification_distilbert_v02_clf_finetuning_felohdez_pipeline_en.md
new file mode 100644
index 00000000000000..5cffa7ccf055fa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-imdbreviews_classification_distilbert_v02_clf_finetuning_felohdez_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English imdbreviews_classification_distilbert_v02_clf_finetuning_felohdez_pipeline pipeline DistilBertForSequenceClassification from felohdez
+author: John Snow Labs
+name: imdbreviews_classification_distilbert_v02_clf_finetuning_felohdez_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`imdbreviews_classification_distilbert_v02_clf_finetuning_felohdez_pipeline` is a English model originally trained by felohdez.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/imdbreviews_classification_distilbert_v02_clf_finetuning_felohdez_pipeline_en_5.5.1_3.0_1737939347574.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/imdbreviews_classification_distilbert_v02_clf_finetuning_felohdez_pipeline_en_5.5.1_3.0_1737939347574.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("imdbreviews_classification_distilbert_v02_clf_finetuning_felohdez_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("imdbreviews_classification_distilbert_v02_clf_finetuning_felohdez_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|imdbreviews_classification_distilbert_v02_clf_finetuning_felohdez_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/felohdez/imdbreviews_classification_distilbert_v02_clf_finetuning
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-imdbreviews_classification_distilbert_v02_cristian9481_en.md b/docs/_posts/ahmedlone127/2025-01-27-imdbreviews_classification_distilbert_v02_cristian9481_en.md
new file mode 100644
index 00000000000000..48e0f4c494f0ab
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-imdbreviews_classification_distilbert_v02_cristian9481_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English imdbreviews_classification_distilbert_v02_cristian9481 DistilBertForSequenceClassification from Cristian9481
+author: John Snow Labs
+name: imdbreviews_classification_distilbert_v02_cristian9481
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`imdbreviews_classification_distilbert_v02_cristian9481` is a English model originally trained by Cristian9481.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/imdbreviews_classification_distilbert_v02_cristian9481_en_5.5.1_3.0_1737939327768.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/imdbreviews_classification_distilbert_v02_cristian9481_en_5.5.1_3.0_1737939327768.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("imdbreviews_classification_distilbert_v02_cristian9481","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("imdbreviews_classification_distilbert_v02_cristian9481", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|imdbreviews_classification_distilbert_v02_cristian9481|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Cristian9481/imdbreviews_classification_distilbert_v02
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-imdbreviews_classification_distilbert_v02_cristian9481_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-imdbreviews_classification_distilbert_v02_cristian9481_pipeline_en.md
new file mode 100644
index 00000000000000..de33a79cdc45a0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-imdbreviews_classification_distilbert_v02_cristian9481_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English imdbreviews_classification_distilbert_v02_cristian9481_pipeline pipeline DistilBertForSequenceClassification from Cristian9481
+author: John Snow Labs
+name: imdbreviews_classification_distilbert_v02_cristian9481_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`imdbreviews_classification_distilbert_v02_cristian9481_pipeline` is a English model originally trained by Cristian9481.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/imdbreviews_classification_distilbert_v02_cristian9481_pipeline_en_5.5.1_3.0_1737939341182.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/imdbreviews_classification_distilbert_v02_cristian9481_pipeline_en_5.5.1_3.0_1737939341182.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("imdbreviews_classification_distilbert_v02_cristian9481_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("imdbreviews_classification_distilbert_v02_cristian9481_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|imdbreviews_classification_distilbert_v02_cristian9481_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Cristian9481/imdbreviews_classification_distilbert_v02
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-imgclfcd4_en.md b/docs/_posts/ahmedlone127/2025-01-27-imgclfcd4_en.md
new file mode 100644
index 00000000000000..b4725a8dade8ac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-imgclfcd4_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English imgclfcd4 ViTForImageClassification from abhishek
+author: John Snow Labs
+name: imgclfcd4
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`imgclfcd4` is a English model originally trained by abhishek.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/imgclfcd4_en_5.5.1_3.0_1737974737056.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/imgclfcd4_en_5.5.1_3.0_1737974737056.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""imgclfcd4","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("imgclfcd4","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|imgclfcd4|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/abhishek/imgclfcd4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-imgclfcd4_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-imgclfcd4_pipeline_en.md
new file mode 100644
index 00000000000000..517cf28a0e5ae3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-imgclfcd4_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English imgclfcd4_pipeline pipeline ViTForImageClassification from abhishek
+author: John Snow Labs
+name: imgclfcd4_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`imgclfcd4_pipeline` is a English model originally trained by abhishek.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/imgclfcd4_pipeline_en_5.5.1_3.0_1737974754903.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/imgclfcd4_pipeline_en_5.5.1_3.0_1737974754903.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("imgclfcd4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("imgclfcd4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|imgclfcd4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/abhishek/imgclfcd4
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-indian_food_image_detection_en.md b/docs/_posts/ahmedlone127/2025-01-27-indian_food_image_detection_en.md
new file mode 100644
index 00000000000000..d5664fa4e71cee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-indian_food_image_detection_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English indian_food_image_detection ViTForImageClassification from dima806
+author: John Snow Labs
+name: indian_food_image_detection
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indian_food_image_detection` is a English model originally trained by dima806.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indian_food_image_detection_en_5.5.1_3.0_1738021435322.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indian_food_image_detection_en_5.5.1_3.0_1738021435322.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""indian_food_image_detection","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("indian_food_image_detection","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|indian_food_image_detection|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.5 MB|
+
+## References
+
+https://huggingface.co/dima806/indian_food_image_detection
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-indian_food_image_detection_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-indian_food_image_detection_pipeline_en.md
new file mode 100644
index 00000000000000..f30fa5a5f94b63
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-indian_food_image_detection_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English indian_food_image_detection_pipeline pipeline ViTForImageClassification from dima806
+author: John Snow Labs
+name: indian_food_image_detection_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indian_food_image_detection_pipeline` is a English model originally trained by dima806.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indian_food_image_detection_pipeline_en_5.5.1_3.0_1738021451382.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indian_food_image_detection_pipeline_en_5.5.1_3.0_1738021451382.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("indian_food_image_detection_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("indian_food_image_detection_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|indian_food_image_detection_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.6 MB|
+
+## References
+
+https://huggingface.co/dima806/indian_food_image_detection
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-init_gpt2_120m_en.md b/docs/_posts/ahmedlone127/2025-01-27-init_gpt2_120m_en.md
new file mode 100644
index 00000000000000..dfe4dfeb049e72
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-init_gpt2_120m_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English init_gpt2_120m GPT2Transformer from MiniLLM
+author: John Snow Labs
+name: init_gpt2_120m
+date: 2025-01-27
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`init_gpt2_120m` is a English model originally trained by MiniLLM.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/init_gpt2_120m_en_5.5.1_3.0_1737997941156.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/init_gpt2_120m_en_5.5.1_3.0_1737997941156.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("init_gpt2_120m","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("init_gpt2_120m","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|init_gpt2_120m|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|298.6 MB|
+
+## References
+
+https://huggingface.co/MiniLLM/init-gpt2-120M
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-init_gpt2_120m_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-init_gpt2_120m_pipeline_en.md
new file mode 100644
index 00000000000000..a6437c06119003
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-init_gpt2_120m_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English init_gpt2_120m_pipeline pipeline GPT2Transformer from MiniLLM
+author: John Snow Labs
+name: init_gpt2_120m_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`init_gpt2_120m_pipeline` is a English model originally trained by MiniLLM.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/init_gpt2_120m_pipeline_en_5.5.1_3.0_1737998029379.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/init_gpt2_120m_pipeline_en_5.5.1_3.0_1737998029379.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("init_gpt2_120m_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("init_gpt2_120m_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|init_gpt2_120m_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|298.6 MB|
+
+## References
+
+https://huggingface.co/MiniLLM/init-gpt2-120M
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-ir_en.md b/docs/_posts/ahmedlone127/2025-01-27-ir_en.md
new file mode 100644
index 00000000000000..1c477c70f2bfe9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-ir_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ir RoBertaForSequenceClassification from PeryGrey
+author: John Snow Labs
+name: ir
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ir` is a English model originally trained by PeryGrey.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ir_en_5.5.1_3.0_1737938346135.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ir_en_5.5.1_3.0_1737938346135.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("ir","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("ir", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ir|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|468.3 MB|
+
+## References
+
+https://huggingface.co/PeryGrey/IR
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-ir_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-ir_pipeline_en.md
new file mode 100644
index 00000000000000..e811cba1af7a7c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-ir_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ir_pipeline pipeline RoBertaForSequenceClassification from PeryGrey
+author: John Snow Labs
+name: ir_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ir_pipeline` is a English model originally trained by PeryGrey.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ir_pipeline_en_5.5.1_3.0_1737938369801.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ir_pipeline_en_5.5.1_3.0_1737938369801.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ir_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ir_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ir_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|468.3 MB|
+
+## References
+
+https://huggingface.co/PeryGrey/IR
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-jellyfish_types_image_detection_en.md b/docs/_posts/ahmedlone127/2025-01-27-jellyfish_types_image_detection_en.md
new file mode 100644
index 00000000000000..976fba12a78031
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-jellyfish_types_image_detection_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English jellyfish_types_image_detection ViTForImageClassification from dima806
+author: John Snow Labs
+name: jellyfish_types_image_detection
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`jellyfish_types_image_detection` is a English model originally trained by dima806.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/jellyfish_types_image_detection_en_5.5.1_3.0_1738021113408.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/jellyfish_types_image_detection_en_5.5.1_3.0_1738021113408.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""jellyfish_types_image_detection","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("jellyfish_types_image_detection","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|jellyfish_types_image_detection|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/dima806/jellyfish_types_image_detection
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-jellyfish_types_image_detection_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-jellyfish_types_image_detection_pipeline_en.md
new file mode 100644
index 00000000000000..69a8c7cd9fe390
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-jellyfish_types_image_detection_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English jellyfish_types_image_detection_pipeline pipeline ViTForImageClassification from dima806
+author: John Snow Labs
+name: jellyfish_types_image_detection_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`jellyfish_types_image_detection_pipeline` is a English model originally trained by dima806.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/jellyfish_types_image_detection_pipeline_en_5.5.1_3.0_1738021130148.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/jellyfish_types_image_detection_pipeline_en_5.5.1_3.0_1738021130148.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("jellyfish_types_image_detection_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("jellyfish_types_image_detection_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|jellyfish_types_image_detection_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/dima806/jellyfish_types_image_detection
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-johao_vit_model_en.md b/docs/_posts/ahmedlone127/2025-01-27-johao_vit_model_en.md
new file mode 100644
index 00000000000000..677a464031ea6f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-johao_vit_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English johao_vit_model ViTForImageClassification from platzi
+author: John Snow Labs
+name: johao_vit_model
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`johao_vit_model` is a English model originally trained by platzi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/johao_vit_model_en_5.5.1_3.0_1737974487901.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/johao_vit_model_en_5.5.1_3.0_1737974487901.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""johao_vit_model","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("johao_vit_model","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|johao_vit_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/platzi/johao-vit_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-johao_vit_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-johao_vit_model_pipeline_en.md
new file mode 100644
index 00000000000000..38bec7e0420ed4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-johao_vit_model_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English johao_vit_model_pipeline pipeline ViTForImageClassification from platzi
+author: John Snow Labs
+name: johao_vit_model_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`johao_vit_model_pipeline` is a English model originally trained by platzi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/johao_vit_model_pipeline_en_5.5.1_3.0_1737974504902.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/johao_vit_model_pipeline_en_5.5.1_3.0_1737974504902.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("johao_vit_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("johao_vit_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|johao_vit_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/platzi/johao-vit_model
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-kazparc_russian_english_model_2_en.md b/docs/_posts/ahmedlone127/2025-01-27-kazparc_russian_english_model_2_en.md
new file mode 100644
index 00000000000000..0a8020cda10cc2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-kazparc_russian_english_model_2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English kazparc_russian_english_model_2 T5Transformer from Goshective
+author: John Snow Labs
+name: kazparc_russian_english_model_2
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kazparc_russian_english_model_2` is a English model originally trained by Goshective.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kazparc_russian_english_model_2_en_5.5.1_3.0_1737963155473.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kazparc_russian_english_model_2_en_5.5.1_3.0_1737963155473.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("kazparc_russian_english_model_2","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("kazparc_russian_english_model_2", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|kazparc_russian_english_model_2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|280.9 MB|
+
+## References
+
+https://huggingface.co/Goshective/kazparc_ru_en_model_2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-kazparc_russian_english_model_2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-kazparc_russian_english_model_2_pipeline_en.md
new file mode 100644
index 00000000000000..14d78d9c1e032a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-kazparc_russian_english_model_2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English kazparc_russian_english_model_2_pipeline pipeline T5Transformer from Goshective
+author: John Snow Labs
+name: kazparc_russian_english_model_2_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kazparc_russian_english_model_2_pipeline` is a English model originally trained by Goshective.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kazparc_russian_english_model_2_pipeline_en_5.5.1_3.0_1737963171373.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kazparc_russian_english_model_2_pipeline_en_5.5.1_3.0_1737963171373.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("kazparc_russian_english_model_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("kazparc_russian_english_model_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|kazparc_russian_english_model_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|280.9 MB|
+
+## References
+
+https://huggingface.co/Goshective/kazparc_ru_en_model_2
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-kcbert_parent_09252023_mlm_en.md b/docs/_posts/ahmedlone127/2025-01-27-kcbert_parent_09252023_mlm_en.md
new file mode 100644
index 00000000000000..02e5e2c6a68ada
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-kcbert_parent_09252023_mlm_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English kcbert_parent_09252023_mlm BertEmbeddings from JuneKo
+author: John Snow Labs
+name: kcbert_parent_09252023_mlm
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kcbert_parent_09252023_mlm` is a English model originally trained by JuneKo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kcbert_parent_09252023_mlm_en_5.5.1_3.0_1737984872331.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kcbert_parent_09252023_mlm_en_5.5.1_3.0_1737984872331.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("kcbert_parent_09252023_mlm","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("kcbert_parent_09252023_mlm","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|kcbert_parent_09252023_mlm|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|406.2 MB|
+
+## References
+
+https://huggingface.co/JuneKo/kcBERT_parent_09252023_MLM
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-kcbert_parent_09252023_mlm_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-kcbert_parent_09252023_mlm_pipeline_en.md
new file mode 100644
index 00000000000000..58173dcf062a77
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-kcbert_parent_09252023_mlm_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English kcbert_parent_09252023_mlm_pipeline pipeline BertEmbeddings from JuneKo
+author: John Snow Labs
+name: kcbert_parent_09252023_mlm_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kcbert_parent_09252023_mlm_pipeline` is a English model originally trained by JuneKo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kcbert_parent_09252023_mlm_pipeline_en_5.5.1_3.0_1737984893659.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kcbert_parent_09252023_mlm_pipeline_en_5.5.1_3.0_1737984893659.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("kcbert_parent_09252023_mlm_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("kcbert_parent_09252023_mlm_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|kcbert_parent_09252023_mlm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.2 MB|
+
+## References
+
+https://huggingface.co/JuneKo/kcBERT_parent_09252023_MLM
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-ke_t5_base_legislative_bill_summary_en.md b/docs/_posts/ahmedlone127/2025-01-27-ke_t5_base_legislative_bill_summary_en.md
new file mode 100644
index 00000000000000..f4337dba89fcf7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-ke_t5_base_legislative_bill_summary_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English ke_t5_base_legislative_bill_summary T5Transformer from habapchan
+author: John Snow Labs
+name: ke_t5_base_legislative_bill_summary
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ke_t5_base_legislative_bill_summary` is a English model originally trained by habapchan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ke_t5_base_legislative_bill_summary_en_5.5.1_3.0_1737992104606.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ke_t5_base_legislative_bill_summary_en_5.5.1_3.0_1737992104606.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("ke_t5_base_legislative_bill_summary","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("ke_t5_base_legislative_bill_summary", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ke_t5_base_legislative_bill_summary|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/habapchan/ke-t5-base-legislative_bill_summary
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-ke_t5_base_legislative_bill_summary_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-ke_t5_base_legislative_bill_summary_pipeline_en.md
new file mode 100644
index 00000000000000..2612eace47a0d3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-ke_t5_base_legislative_bill_summary_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English ke_t5_base_legislative_bill_summary_pipeline pipeline T5Transformer from habapchan
+author: John Snow Labs
+name: ke_t5_base_legislative_bill_summary_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ke_t5_base_legislative_bill_summary_pipeline` is a English model originally trained by habapchan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ke_t5_base_legislative_bill_summary_pipeline_en_5.5.1_3.0_1737992162702.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ke_t5_base_legislative_bill_summary_pipeline_en_5.5.1_3.0_1737992162702.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ke_t5_base_legislative_bill_summary_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ke_t5_base_legislative_bill_summary_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ke_t5_base_legislative_bill_summary_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/habapchan/ke-t5-base-legislative_bill_summary
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-keybart_bloomberg_en.md b/docs/_posts/ahmedlone127/2025-01-27-keybart_bloomberg_en.md
new file mode 100644
index 00000000000000..3a8e617b1c29d1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-keybart_bloomberg_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English keybart_bloomberg BartTransformer from bloomberg
+author: John Snow Labs
+name: keybart_bloomberg
+date: 2025-01-27
+tags: [en, open_source, onnx, text_generation, bart]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BartTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`keybart_bloomberg` is a English model originally trained by bloomberg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/keybart_bloomberg_en_5.5.1_3.0_1737955787078.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/keybart_bloomberg_en_5.5.1_3.0_1737955787078.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = BartTransformer.pretrained("keybart_bloomberg","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = BartTransformer.pretrained("keybart_bloomberg","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|keybart_bloomberg|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.9 GB|
+
+## References
+
+https://huggingface.co/bloomberg/KeyBART
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-keybart_bloomberg_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-keybart_bloomberg_pipeline_en.md
new file mode 100644
index 00000000000000..3f6137c67f151c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-keybart_bloomberg_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English keybart_bloomberg_pipeline pipeline BartTransformer from bloomberg
+author: John Snow Labs
+name: keybart_bloomberg_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`keybart_bloomberg_pipeline` is a English model originally trained by bloomberg.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/keybart_bloomberg_pipeline_en_5.5.1_3.0_1737955899062.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/keybart_bloomberg_pipeline_en_5.5.1_3.0_1737955899062.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("keybart_bloomberg_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("keybart_bloomberg_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|keybart_bloomberg_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.9 GB|
+
+## References
+
+https://huggingface.co/bloomberg/KeyBART
+
+## Included Models
+
+- DocumentAssembler
+- BartTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-keyword_summarizer_10000_v1_en.md b/docs/_posts/ahmedlone127/2025-01-27-keyword_summarizer_10000_v1_en.md
new file mode 100644
index 00000000000000..6afc7a571d006e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-keyword_summarizer_10000_v1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English keyword_summarizer_10000_v1 T5Transformer from ZephyrUtopia
+author: John Snow Labs
+name: keyword_summarizer_10000_v1
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`keyword_summarizer_10000_v1` is a English model originally trained by ZephyrUtopia.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/keyword_summarizer_10000_v1_en_5.5.1_3.0_1737963261117.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/keyword_summarizer_10000_v1_en_5.5.1_3.0_1737963261117.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("keyword_summarizer_10000_v1","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("keyword_summarizer_10000_v1", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|keyword_summarizer_10000_v1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/ZephyrUtopia/keyword-summarizer-10000-v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-keyword_summarizer_10000_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-keyword_summarizer_10000_v1_pipeline_en.md
new file mode 100644
index 00000000000000..c6dabf451d22ed
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-keyword_summarizer_10000_v1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English keyword_summarizer_10000_v1_pipeline pipeline T5Transformer from ZephyrUtopia
+author: John Snow Labs
+name: keyword_summarizer_10000_v1_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`keyword_summarizer_10000_v1_pipeline` is a English model originally trained by ZephyrUtopia.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/keyword_summarizer_10000_v1_pipeline_en_5.5.1_3.0_1737963311719.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/keyword_summarizer_10000_v1_pipeline_en_5.5.1_3.0_1737963311719.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("keyword_summarizer_10000_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("keyword_summarizer_10000_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|keyword_summarizer_10000_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/ZephyrUtopia/keyword-summarizer-10000-v1
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-kitchen_layouts_2_3_0_86m_en.md b/docs/_posts/ahmedlone127/2025-01-27-kitchen_layouts_2_3_0_86m_en.md
new file mode 100644
index 00000000000000..89694bd3e20b14
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-kitchen_layouts_2_3_0_86m_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English kitchen_layouts_2_3_0_86m ViTForImageClassification from JuanMa360
+author: John Snow Labs
+name: kitchen_layouts_2_3_0_86m
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kitchen_layouts_2_3_0_86m` is a English model originally trained by JuanMa360.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kitchen_layouts_2_3_0_86m_en_5.5.1_3.0_1738021160953.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kitchen_layouts_2_3_0_86m_en_5.5.1_3.0_1738021160953.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""kitchen_layouts_2_3_0_86m","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("kitchen_layouts_2_3_0_86m","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|kitchen_layouts_2_3_0_86m|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/JuanMa360/kitchen-layouts-2.3.0-86M
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-kitchen_layouts_2_3_0_86m_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-kitchen_layouts_2_3_0_86m_pipeline_en.md
new file mode 100644
index 00000000000000..0061e634a8977a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-kitchen_layouts_2_3_0_86m_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English kitchen_layouts_2_3_0_86m_pipeline pipeline ViTForImageClassification from JuanMa360
+author: John Snow Labs
+name: kitchen_layouts_2_3_0_86m_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kitchen_layouts_2_3_0_86m_pipeline` is a English model originally trained by JuanMa360.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kitchen_layouts_2_3_0_86m_pipeline_en_5.5.1_3.0_1738021181795.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kitchen_layouts_2_3_0_86m_pipeline_en_5.5.1_3.0_1738021181795.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("kitchen_layouts_2_3_0_86m_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("kitchen_layouts_2_3_0_86m_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|kitchen_layouts_2_3_0_86m_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/JuanMa360/kitchen-layouts-2.3.0-86M
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-kvasir_v2_classifier_a838264168_en.md b/docs/_posts/ahmedlone127/2025-01-27-kvasir_v2_classifier_a838264168_en.md
new file mode 100644
index 00000000000000..b00060cde39acd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-kvasir_v2_classifier_a838264168_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English kvasir_v2_classifier_a838264168 ViTForImageClassification from a838264168
+author: John Snow Labs
+name: kvasir_v2_classifier_a838264168
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kvasir_v2_classifier_a838264168` is a English model originally trained by a838264168.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kvasir_v2_classifier_a838264168_en_5.5.1_3.0_1737974718601.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kvasir_v2_classifier_a838264168_en_5.5.1_3.0_1737974718601.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""kvasir_v2_classifier_a838264168","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("kvasir_v2_classifier_a838264168","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|kvasir_v2_classifier_a838264168|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/a838264168/kvasir-v2-classifier
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-kvasir_v2_classifier_a838264168_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-kvasir_v2_classifier_a838264168_pipeline_en.md
new file mode 100644
index 00000000000000..a8ec86cfbafd78
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-kvasir_v2_classifier_a838264168_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English kvasir_v2_classifier_a838264168_pipeline pipeline ViTForImageClassification from a838264168
+author: John Snow Labs
+name: kvasir_v2_classifier_a838264168_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kvasir_v2_classifier_a838264168_pipeline` is a English model originally trained by a838264168.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kvasir_v2_classifier_a838264168_pipeline_en_5.5.1_3.0_1737974735342.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kvasir_v2_classifier_a838264168_pipeline_en_5.5.1_3.0_1737974735342.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("kvasir_v2_classifier_a838264168_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("kvasir_v2_classifier_a838264168_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|kvasir_v2_classifier_a838264168_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/a838264168/kvasir-v2-classifier
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-language_detection_sundaynight_en.md b/docs/_posts/ahmedlone127/2025-01-27-language_detection_sundaynight_en.md
new file mode 100644
index 00000000000000..d176c073714831
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-language_detection_sundaynight_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English language_detection_sundaynight XlmRoBertaForSequenceClassification from sirgecko
+author: John Snow Labs
+name: language_detection_sundaynight
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`language_detection_sundaynight` is a English model originally trained by sirgecko.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/language_detection_sundaynight_en_5.5.1_3.0_1737959099228.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/language_detection_sundaynight_en_5.5.1_3.0_1737959099228.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("language_detection_sundaynight","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("language_detection_sundaynight", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|language_detection_sundaynight|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|655.1 MB|
+
+## References
+
+https://huggingface.co/sirgecko/language-detection-sundaynight
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-language_detection_sundaynight_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-language_detection_sundaynight_pipeline_en.md
new file mode 100644
index 00000000000000..1c462e918a6f61
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-language_detection_sundaynight_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English language_detection_sundaynight_pipeline pipeline XlmRoBertaForSequenceClassification from sirgecko
+author: John Snow Labs
+name: language_detection_sundaynight_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`language_detection_sundaynight_pipeline` is a English model originally trained by sirgecko.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/language_detection_sundaynight_pipeline_en_5.5.1_3.0_1737959285625.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/language_detection_sundaynight_pipeline_en_5.5.1_3.0_1737959285625.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("language_detection_sundaynight_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("language_detection_sundaynight_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|language_detection_sundaynight_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|655.1 MB|
+
+## References
+
+https://huggingface.co/sirgecko/language-detection-sundaynight
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-legal_base_v1_5__checkpoint1_en.md b/docs/_posts/ahmedlone127/2025-01-27-legal_base_v1_5__checkpoint1_en.md
new file mode 100644
index 00000000000000..eb6f89c9791cd2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-legal_base_v1_5__checkpoint1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English legal_base_v1_5__checkpoint1 RoBertaEmbeddings from eduagarcia-temp
+author: John Snow Labs
+name: legal_base_v1_5__checkpoint1
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`legal_base_v1_5__checkpoint1` is a English model originally trained by eduagarcia-temp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/legal_base_v1_5__checkpoint1_en_5.5.1_3.0_1737965825364.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/legal_base_v1_5__checkpoint1_en_5.5.1_3.0_1737965825364.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("legal_base_v1_5__checkpoint1","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("legal_base_v1_5__checkpoint1","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|legal_base_v1_5__checkpoint1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|296.6 MB|
+
+## References
+
+https://huggingface.co/eduagarcia-temp/legal_base_v1_5__checkpoint1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-legal_base_v1_5__checkpoint1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-legal_base_v1_5__checkpoint1_pipeline_en.md
new file mode 100644
index 00000000000000..39ee4339166625
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-legal_base_v1_5__checkpoint1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English legal_base_v1_5__checkpoint1_pipeline pipeline RoBertaEmbeddings from eduagarcia-temp
+author: John Snow Labs
+name: legal_base_v1_5__checkpoint1_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`legal_base_v1_5__checkpoint1_pipeline` is a English model originally trained by eduagarcia-temp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/legal_base_v1_5__checkpoint1_pipeline_en_5.5.1_3.0_1737965912069.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/legal_base_v1_5__checkpoint1_pipeline_en_5.5.1_3.0_1737965912069.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("legal_base_v1_5__checkpoint1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("legal_base_v1_5__checkpoint1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|legal_base_v1_5__checkpoint1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|296.6 MB|
+
+## References
+
+https://huggingface.co/eduagarcia-temp/legal_base_v1_5__checkpoint1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-legal_base_v2_5__checkpoint_3_50000_en.md b/docs/_posts/ahmedlone127/2025-01-27-legal_base_v2_5__checkpoint_3_50000_en.md
new file mode 100644
index 00000000000000..7ff8814df2cdef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-legal_base_v2_5__checkpoint_3_50000_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English legal_base_v2_5__checkpoint_3_50000 RoBertaEmbeddings from eduagarcia-temp
+author: John Snow Labs
+name: legal_base_v2_5__checkpoint_3_50000
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`legal_base_v2_5__checkpoint_3_50000` is a English model originally trained by eduagarcia-temp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/legal_base_v2_5__checkpoint_3_50000_en_5.5.1_3.0_1737966602629.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/legal_base_v2_5__checkpoint_3_50000_en_5.5.1_3.0_1737966602629.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("legal_base_v2_5__checkpoint_3_50000","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("legal_base_v2_5__checkpoint_3_50000","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|legal_base_v2_5__checkpoint_3_50000|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|296.9 MB|
+
+## References
+
+https://huggingface.co/eduagarcia-temp/legal_base-v2_5__checkpoint_3_50000
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-legal_base_v2_5__checkpoint_3_50000_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-legal_base_v2_5__checkpoint_3_50000_pipeline_en.md
new file mode 100644
index 00000000000000..9b9c4485c06c69
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-legal_base_v2_5__checkpoint_3_50000_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English legal_base_v2_5__checkpoint_3_50000_pipeline pipeline RoBertaEmbeddings from eduagarcia-temp
+author: John Snow Labs
+name: legal_base_v2_5__checkpoint_3_50000_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`legal_base_v2_5__checkpoint_3_50000_pipeline` is a English model originally trained by eduagarcia-temp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/legal_base_v2_5__checkpoint_3_50000_pipeline_en_5.5.1_3.0_1737966688019.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/legal_base_v2_5__checkpoint_3_50000_pipeline_en_5.5.1_3.0_1737966688019.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("legal_base_v2_5__checkpoint_3_50000_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("legal_base_v2_5__checkpoint_3_50000_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|legal_base_v2_5__checkpoint_3_50000_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|296.9 MB|
+
+## References
+
+https://huggingface.co/eduagarcia-temp/legal_base-v2_5__checkpoint_3_50000
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-legal_pashto_defence_flan_t5_en.md b/docs/_posts/ahmedlone127/2025-01-27-legal_pashto_defence_flan_t5_en.md
new file mode 100644
index 00000000000000..95c9f53453590f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-legal_pashto_defence_flan_t5_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English legal_pashto_defence_flan_t5 T5Transformer from subha-roy
+author: John Snow Labs
+name: legal_pashto_defence_flan_t5
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`legal_pashto_defence_flan_t5` is a English model originally trained by subha-roy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/legal_pashto_defence_flan_t5_en_5.5.1_3.0_1737962391071.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/legal_pashto_defence_flan_t5_en_5.5.1_3.0_1737962391071.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("legal_pashto_defence_flan_t5","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("legal_pashto_defence_flan_t5", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|legal_pashto_defence_flan_t5|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/subha-roy/legal-ps-defence-FLAN-T5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-legal_pashto_defence_flan_t5_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-legal_pashto_defence_flan_t5_pipeline_en.md
new file mode 100644
index 00000000000000..d1f7f8a841ab2f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-legal_pashto_defence_flan_t5_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English legal_pashto_defence_flan_t5_pipeline pipeline T5Transformer from subha-roy
+author: John Snow Labs
+name: legal_pashto_defence_flan_t5_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`legal_pashto_defence_flan_t5_pipeline` is a English model originally trained by subha-roy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/legal_pashto_defence_flan_t5_pipeline_en_5.5.1_3.0_1737962442864.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/legal_pashto_defence_flan_t5_pipeline_en_5.5.1_3.0_1737962442864.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("legal_pashto_defence_flan_t5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("legal_pashto_defence_flan_t5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|legal_pashto_defence_flan_t5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/subha-roy/legal-ps-defence-FLAN-T5
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-lernnavibert_de.md b/docs/_posts/ahmedlone127/2025-01-27-lernnavibert_de.md
new file mode 100644
index 00000000000000..d21e4df3972a79
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-lernnavibert_de.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: German lernnavibert BertEmbeddings from epfl-ml4ed
+author: John Snow Labs
+name: lernnavibert
+date: 2025-01-27
+tags: [de, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: de
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lernnavibert` is a German model originally trained by epfl-ml4ed.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lernnavibert_de_5.5.1_3.0_1737953977814.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lernnavibert_de_5.5.1_3.0_1737953977814.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("lernnavibert","de") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("lernnavibert","de") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lernnavibert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|de|
+|Size:|409.9 MB|
+
+## References
+
+https://huggingface.co/epfl-ml4ed/LernnaviBERT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-lernnavibert_pipeline_de.md b/docs/_posts/ahmedlone127/2025-01-27-lernnavibert_pipeline_de.md
new file mode 100644
index 00000000000000..95292fd73cf822
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-lernnavibert_pipeline_de.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: German lernnavibert_pipeline pipeline BertEmbeddings from epfl-ml4ed
+author: John Snow Labs
+name: lernnavibert_pipeline
+date: 2025-01-27
+tags: [de, open_source, pipeline, onnx]
+task: Embeddings
+language: de
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lernnavibert_pipeline` is a German model originally trained by epfl-ml4ed.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lernnavibert_pipeline_de_5.5.1_3.0_1737953998435.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lernnavibert_pipeline_de_5.5.1_3.0_1737953998435.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("lernnavibert_pipeline", lang = "de")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("lernnavibert_pipeline", lang = "de")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lernnavibert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|de|
+|Size:|409.9 MB|
+
+## References
+
+https://huggingface.co/epfl-ml4ed/LernnaviBERT
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-levit_256_en.md b/docs/_posts/ahmedlone127/2025-01-27-levit_256_en.md
new file mode 100644
index 00000000000000..741dfd9fea9084
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-levit_256_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English levit_256 ViTForImageClassification from facebook
+author: John Snow Labs
+name: levit_256
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`levit_256` is a English model originally trained by facebook.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/levit_256_en_5.5.1_3.0_1737975016912.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/levit_256_en_5.5.1_3.0_1737975016912.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""levit_256","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("levit_256","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|levit_256|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|71.1 MB|
+
+## References
+
+https://huggingface.co/facebook/levit-256
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-levit_256_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-levit_256_pipeline_en.md
new file mode 100644
index 00000000000000..9ad8e509577d7b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-levit_256_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English levit_256_pipeline pipeline ViTForImageClassification from facebook
+author: John Snow Labs
+name: levit_256_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`levit_256_pipeline` is a English model originally trained by facebook.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/levit_256_pipeline_en_5.5.1_3.0_1737975020320.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/levit_256_pipeline_en_5.5.1_3.0_1737975020320.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("levit_256_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("levit_256_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|levit_256_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|71.2 MB|
+
+## References
+
+https://huggingface.co/facebook/levit-256
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-llm_project_en.md b/docs/_posts/ahmedlone127/2025-01-27-llm_project_en.md
new file mode 100644
index 00000000000000..5179879507a791
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-llm_project_en.md
@@ -0,0 +1,96 @@
+---
+layout: model
+title: English llm_project DistilBertForSequenceClassification from ThuyTran102
+author: John Snow Labs
+name: llm_project
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`llm_project` is a English model originally trained by ThuyTran102.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/llm_project_en_5.5.1_3.0_1737939747713.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/llm_project_en_5.5.1_3.0_1737939747713.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("llm_project","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("llm_project", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|llm_project|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+References
+
+https://huggingface.co/ThuyTran102/LLM_project
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-llm_project_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-llm_project_pipeline_en.md
new file mode 100644
index 00000000000000..c7062a9d551efa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-llm_project_pipeline_en.md
@@ -0,0 +1,72 @@
+---
+layout: model
+title: English llm_project_pipeline pipeline DistilBertForSequenceClassification from ThuyTran102
+author: John Snow Labs
+name: llm_project_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`llm_project_pipeline` is a English model originally trained by ThuyTran102.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/llm_project_pipeline_en_5.5.1_3.0_1737939762641.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/llm_project_pipeline_en_5.5.1_3.0_1737939762641.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("llm_project_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("llm_project_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|llm_project_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+References
+
+https://huggingface.co/ThuyTran102/LLM_project
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-llmbook_distilbert_base_uncased_finetuned_emotion_en.md b/docs/_posts/ahmedlone127/2025-01-27-llmbook_distilbert_base_uncased_finetuned_emotion_en.md
new file mode 100644
index 00000000000000..90624050034b52
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-llmbook_distilbert_base_uncased_finetuned_emotion_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English llmbook_distilbert_base_uncased_finetuned_emotion DistilBertForSequenceClassification from yurongzhong
+author: John Snow Labs
+name: llmbook_distilbert_base_uncased_finetuned_emotion
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`llmbook_distilbert_base_uncased_finetuned_emotion` is a English model originally trained by yurongzhong.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/llmbook_distilbert_base_uncased_finetuned_emotion_en_5.5.1_3.0_1737939622492.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/llmbook_distilbert_base_uncased_finetuned_emotion_en_5.5.1_3.0_1737939622492.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("llmbook_distilbert_base_uncased_finetuned_emotion","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("llmbook_distilbert_base_uncased_finetuned_emotion", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|llmbook_distilbert_base_uncased_finetuned_emotion|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/yurongzhong/LLMBook_distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-llmbook_distilbert_base_uncased_finetuned_emotion_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-llmbook_distilbert_base_uncased_finetuned_emotion_pipeline_en.md
new file mode 100644
index 00000000000000..6145b11c782e60
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-llmbook_distilbert_base_uncased_finetuned_emotion_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English llmbook_distilbert_base_uncased_finetuned_emotion_pipeline pipeline DistilBertForSequenceClassification from yurongzhong
+author: John Snow Labs
+name: llmbook_distilbert_base_uncased_finetuned_emotion_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`llmbook_distilbert_base_uncased_finetuned_emotion_pipeline` is a English model originally trained by yurongzhong.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/llmbook_distilbert_base_uncased_finetuned_emotion_pipeline_en_5.5.1_3.0_1737939636315.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/llmbook_distilbert_base_uncased_finetuned_emotion_pipeline_en_5.5.1_3.0_1737939636315.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("llmbook_distilbert_base_uncased_finetuned_emotion_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("llmbook_distilbert_base_uncased_finetuned_emotion_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|llmbook_distilbert_base_uncased_finetuned_emotion_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/yurongzhong/LLMBook_distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-long_t5_storysummarizer_en.md b/docs/_posts/ahmedlone127/2025-01-27-long_t5_storysummarizer_en.md
new file mode 100644
index 00000000000000..4429dd7efb8a76
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-long_t5_storysummarizer_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English long_t5_storysummarizer T5Transformer from walthercarrasco
+author: John Snow Labs
+name: long_t5_storysummarizer
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`long_t5_storysummarizer` is a English model originally trained by walthercarrasco.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/long_t5_storysummarizer_en_5.5.1_3.0_1738008186255.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/long_t5_storysummarizer_en_5.5.1_3.0_1738008186255.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("long_t5_storysummarizer","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("long_t5_storysummarizer", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|long_t5_storysummarizer|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/walthercarrasco/long-t5-storysummarizer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-long_t5_storysummarizer_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-long_t5_storysummarizer_pipeline_en.md
new file mode 100644
index 00000000000000..177d699e8b961d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-long_t5_storysummarizer_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English long_t5_storysummarizer_pipeline pipeline T5Transformer from walthercarrasco
+author: John Snow Labs
+name: long_t5_storysummarizer_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`long_t5_storysummarizer_pipeline` is a English model originally trained by walthercarrasco.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/long_t5_storysummarizer_pipeline_en_5.5.1_3.0_1738008238293.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/long_t5_storysummarizer_pipeline_en_5.5.1_3.0_1738008238293.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("long_t5_storysummarizer_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("long_t5_storysummarizer_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|long_t5_storysummarizer_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/walthercarrasco/long-t5-storysummarizer
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-lora_flan_t5_base_bot_en.md b/docs/_posts/ahmedlone127/2025-01-27-lora_flan_t5_base_bot_en.md
new file mode 100644
index 00000000000000..7a7006dd8e0fe3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-lora_flan_t5_base_bot_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English lora_flan_t5_base_bot T5Transformer from shanthi-323
+author: John Snow Labs
+name: lora_flan_t5_base_bot
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lora_flan_t5_base_bot` is a English model originally trained by shanthi-323.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lora_flan_t5_base_bot_en_5.5.1_3.0_1737961469897.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lora_flan_t5_base_bot_en_5.5.1_3.0_1737961469897.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("lora_flan_t5_base_bot","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("lora_flan_t5_base_bot", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lora_flan_t5_base_bot|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/shanthi-323/lora-flan-t5-base-bot_
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-lora_flan_t5_base_bot_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-lora_flan_t5_base_bot_pipeline_en.md
new file mode 100644
index 00000000000000..11ee0a7b9ba5f5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-lora_flan_t5_base_bot_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English lora_flan_t5_base_bot_pipeline pipeline T5Transformer from shanthi-323
+author: John Snow Labs
+name: lora_flan_t5_base_bot_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lora_flan_t5_base_bot_pipeline` is a English model originally trained by shanthi-323.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lora_flan_t5_base_bot_pipeline_en_5.5.1_3.0_1737961520797.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lora_flan_t5_base_bot_pipeline_en_5.5.1_3.0_1737961520797.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("lora_flan_t5_base_bot_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("lora_flan_t5_base_bot_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lora_flan_t5_base_bot_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/shanthi-323/lora-flan-t5-base-bot_
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-lora_flan_t5_large_chat_lap2004_en.md b/docs/_posts/ahmedlone127/2025-01-27-lora_flan_t5_large_chat_lap2004_en.md
new file mode 100644
index 00000000000000..d1a9e006087239
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-lora_flan_t5_large_chat_lap2004_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English lora_flan_t5_large_chat_lap2004 T5Transformer from lap2004
+author: John Snow Labs
+name: lora_flan_t5_large_chat_lap2004
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lora_flan_t5_large_chat_lap2004` is a English model originally trained by lap2004.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lora_flan_t5_large_chat_lap2004_en_5.5.1_3.0_1738007850970.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lora_flan_t5_large_chat_lap2004_en_5.5.1_3.0_1738007850970.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("lora_flan_t5_large_chat_lap2004","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("lora_flan_t5_large_chat_lap2004", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lora_flan_t5_large_chat_lap2004|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|3.1 GB|
+
+## References
+
+https://huggingface.co/lap2004/lora-flan-t5-large-chat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-lora_flan_t5_large_chat_lap2004_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-lora_flan_t5_large_chat_lap2004_pipeline_en.md
new file mode 100644
index 00000000000000..68ce3a57ba8fac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-lora_flan_t5_large_chat_lap2004_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English lora_flan_t5_large_chat_lap2004_pipeline pipeline T5Transformer from lap2004
+author: John Snow Labs
+name: lora_flan_t5_large_chat_lap2004_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lora_flan_t5_large_chat_lap2004_pipeline` is a English model originally trained by lap2004.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lora_flan_t5_large_chat_lap2004_pipeline_en_5.5.1_3.0_1738007997905.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lora_flan_t5_large_chat_lap2004_pipeline_en_5.5.1_3.0_1738007997905.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("lora_flan_t5_large_chat_lap2004_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("lora_flan_t5_large_chat_lap2004_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lora_flan_t5_large_chat_lap2004_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|3.1 GB|
+
+## References
+
+https://huggingface.co/lap2004/lora-flan-t5-large-chat
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-lora_flan_t5_med_cardio_en.md b/docs/_posts/ahmedlone127/2025-01-27-lora_flan_t5_med_cardio_en.md
new file mode 100644
index 00000000000000..d145cea15cace5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-lora_flan_t5_med_cardio_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English lora_flan_t5_med_cardio T5Transformer from Yudsky
+author: John Snow Labs
+name: lora_flan_t5_med_cardio
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lora_flan_t5_med_cardio` is a English model originally trained by Yudsky.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lora_flan_t5_med_cardio_en_5.5.1_3.0_1738001000591.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lora_flan_t5_med_cardio_en_5.5.1_3.0_1738001000591.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("lora_flan_t5_med_cardio","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("lora_flan_t5_med_cardio", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lora_flan_t5_med_cardio|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|3.1 GB|
+
+## References
+
+https://huggingface.co/Yudsky/lora-flan-t5-med-cardio
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-lora_flan_t5_med_cardio_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-lora_flan_t5_med_cardio_pipeline_en.md
new file mode 100644
index 00000000000000..e6280e10ac71ef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-lora_flan_t5_med_cardio_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English lora_flan_t5_med_cardio_pipeline pipeline T5Transformer from Yudsky
+author: John Snow Labs
+name: lora_flan_t5_med_cardio_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lora_flan_t5_med_cardio_pipeline` is a English model originally trained by Yudsky.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lora_flan_t5_med_cardio_pipeline_en_5.5.1_3.0_1738001171887.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lora_flan_t5_med_cardio_pipeline_en_5.5.1_3.0_1738001171887.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("lora_flan_t5_med_cardio_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("lora_flan_t5_med_cardio_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lora_flan_t5_med_cardio_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|3.1 GB|
+
+## References
+
+https://huggingface.co/Yudsky/lora-flan-t5-med-cardio
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-lora_flan_t5_small_chat_en.md b/docs/_posts/ahmedlone127/2025-01-27-lora_flan_t5_small_chat_en.md
new file mode 100644
index 00000000000000..d2190031b523ef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-lora_flan_t5_small_chat_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English lora_flan_t5_small_chat T5Transformer from error1203
+author: John Snow Labs
+name: lora_flan_t5_small_chat
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lora_flan_t5_small_chat` is a English model originally trained by error1203.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lora_flan_t5_small_chat_en_5.5.1_3.0_1738007871168.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lora_flan_t5_small_chat_en_5.5.1_3.0_1738007871168.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("lora_flan_t5_small_chat","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("lora_flan_t5_small_chat", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lora_flan_t5_small_chat|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|352.4 MB|
+
+## References
+
+https://huggingface.co/error1203/lora-flan-t5-small-chat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-lora_flan_t5_small_chat_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-lora_flan_t5_small_chat_pipeline_en.md
new file mode 100644
index 00000000000000..eb7ff0d7a38e94
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-lora_flan_t5_small_chat_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English lora_flan_t5_small_chat_pipeline pipeline T5Transformer from error1203
+author: John Snow Labs
+name: lora_flan_t5_small_chat_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lora_flan_t5_small_chat_pipeline` is a English model originally trained by error1203.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lora_flan_t5_small_chat_pipeline_en_5.5.1_3.0_1738007890847.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lora_flan_t5_small_chat_pipeline_en_5.5.1_3.0_1738007890847.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("lora_flan_t5_small_chat_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("lora_flan_t5_small_chat_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lora_flan_t5_small_chat_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|352.4 MB|
+
+## References
+
+https://huggingface.co/error1203/lora-flan-t5-small-chat
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-lr04_6_epochs_en.md b/docs/_posts/ahmedlone127/2025-01-27-lr04_6_epochs_en.md
new file mode 100644
index 00000000000000..09123095e6426d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-lr04_6_epochs_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English lr04_6_epochs T5Transformer from MartinElMolon
+author: John Snow Labs
+name: lr04_6_epochs
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lr04_6_epochs` is a English model originally trained by MartinElMolon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lr04_6_epochs_en_5.5.1_3.0_1738008351659.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lr04_6_epochs_en_5.5.1_3.0_1738008351659.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("lr04_6_epochs","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("lr04_6_epochs", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lr04_6_epochs|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|663.2 MB|
+
+## References
+
+https://huggingface.co/MartinElMolon/lr04_6_epochs
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-lr04_6_epochs_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-lr04_6_epochs_pipeline_en.md
new file mode 100644
index 00000000000000..19e6847ded87b7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-lr04_6_epochs_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English lr04_6_epochs_pipeline pipeline T5Transformer from MartinElMolon
+author: John Snow Labs
+name: lr04_6_epochs_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lr04_6_epochs_pipeline` is a English model originally trained by MartinElMolon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lr04_6_epochs_pipeline_en_5.5.1_3.0_1738008461195.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lr04_6_epochs_pipeline_en_5.5.1_3.0_1738008461195.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("lr04_6_epochs_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("lr04_6_epochs_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lr04_6_epochs_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|663.2 MB|
+
+## References
+
+https://huggingface.co/MartinElMolon/lr04_6_epochs
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-m_e5_toxic_classification_en.md b/docs/_posts/ahmedlone127/2025-01-27-m_e5_toxic_classification_en.md
new file mode 100644
index 00000000000000..5bf152683be288
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-m_e5_toxic_classification_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English m_e5_toxic_classification XlmRoBertaForSequenceClassification from megabot131
+author: John Snow Labs
+name: m_e5_toxic_classification
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`m_e5_toxic_classification` is a English model originally trained by megabot131.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/m_e5_toxic_classification_en_5.5.1_3.0_1737958974447.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/m_e5_toxic_classification_en_5.5.1_3.0_1737958974447.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("m_e5_toxic_classification","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("m_e5_toxic_classification", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|m_e5_toxic_classification|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|667.2 MB|
+
+## References
+
+https://huggingface.co/megabot131/m-e5-toxic-classification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-m_e5_toxic_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-m_e5_toxic_classification_pipeline_en.md
new file mode 100644
index 00000000000000..d9387ba896c142
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-m_e5_toxic_classification_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English m_e5_toxic_classification_pipeline pipeline XlmRoBertaForSequenceClassification from megabot131
+author: John Snow Labs
+name: m_e5_toxic_classification_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`m_e5_toxic_classification_pipeline` is a English model originally trained by megabot131.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/m_e5_toxic_classification_pipeline_en_5.5.1_3.0_1737959173758.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/m_e5_toxic_classification_pipeline_en_5.5.1_3.0_1737959173758.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("m_e5_toxic_classification_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("m_e5_toxic_classification_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|m_e5_toxic_classification_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|667.2 MB|
+
+## References
+
+https://huggingface.co/megabot131/m-e5-toxic-classification
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-magnesiumbert_en.md b/docs/_posts/ahmedlone127/2025-01-27-magnesiumbert_en.md
new file mode 100644
index 00000000000000..87025cbe22e8c2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-magnesiumbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English magnesiumbert BertEmbeddings from MADD123
+author: John Snow Labs
+name: magnesiumbert
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`magnesiumbert` is a English model originally trained by MADD123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/magnesiumbert_en_5.5.1_3.0_1737953878790.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/magnesiumbert_en_5.5.1_3.0_1737953878790.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("magnesiumbert","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("magnesiumbert","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|magnesiumbert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|409.9 MB|
+
+## References
+
+https://huggingface.co/MADD123/MagnesiumBERT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-magnesiumbert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-magnesiumbert_pipeline_en.md
new file mode 100644
index 00000000000000..a38045878dd532
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-magnesiumbert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English magnesiumbert_pipeline pipeline BertEmbeddings from MADD123
+author: John Snow Labs
+name: magnesiumbert_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`magnesiumbert_pipeline` is a English model originally trained by MADD123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/magnesiumbert_pipeline_en_5.5.1_3.0_1737953900392.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/magnesiumbert_pipeline_en_5.5.1_3.0_1737953900392.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("magnesiumbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("magnesiumbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|magnesiumbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.9 MB|
+
+## References
+
+https://huggingface.co/MADD123/MagnesiumBERT
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-malayalam_relevance_clf_en.md b/docs/_posts/ahmedlone127/2025-01-27-malayalam_relevance_clf_en.md
new file mode 100644
index 00000000000000..357e2b5c1208bd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-malayalam_relevance_clf_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English malayalam_relevance_clf XlmRoBertaForSequenceClassification from Jatin-WIAI
+author: John Snow Labs
+name: malayalam_relevance_clf
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`malayalam_relevance_clf` is a English model originally trained by Jatin-WIAI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/malayalam_relevance_clf_en_5.5.1_3.0_1737958839170.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/malayalam_relevance_clf_en_5.5.1_3.0_1737958839170.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("malayalam_relevance_clf","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("malayalam_relevance_clf", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|malayalam_relevance_clf|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|800.0 MB|
+
+## References
+
+https://huggingface.co/Jatin-WIAI/malayalam_relevance_clf
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-malayalam_relevance_clf_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-malayalam_relevance_clf_pipeline_en.md
new file mode 100644
index 00000000000000..205d1bb19536f0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-malayalam_relevance_clf_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English malayalam_relevance_clf_pipeline pipeline XlmRoBertaForSequenceClassification from Jatin-WIAI
+author: John Snow Labs
+name: malayalam_relevance_clf_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`malayalam_relevance_clf_pipeline` is a English model originally trained by Jatin-WIAI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/malayalam_relevance_clf_pipeline_en_5.5.1_3.0_1737958973366.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/malayalam_relevance_clf_pipeline_en_5.5.1_3.0_1737958973366.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("malayalam_relevance_clf_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("malayalam_relevance_clf_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|malayalam_relevance_clf_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|800.0 MB|
+
+## References
+
+https://huggingface.co/Jatin-WIAI/malayalam_relevance_clf
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-mammals_45_types_image_classification_en.md b/docs/_posts/ahmedlone127/2025-01-27-mammals_45_types_image_classification_en.md
new file mode 100644
index 00000000000000..4d491f750d6b21
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-mammals_45_types_image_classification_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mammals_45_types_image_classification ViTForImageClassification from dima806
+author: John Snow Labs
+name: mammals_45_types_image_classification
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mammals_45_types_image_classification` is a English model originally trained by dima806.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mammals_45_types_image_classification_en_5.5.1_3.0_1738022278631.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mammals_45_types_image_classification_en_5.5.1_3.0_1738022278631.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""mammals_45_types_image_classification","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("mammals_45_types_image_classification","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mammals_45_types_image_classification|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.4 MB|
+
+## References
+
+https://huggingface.co/dima806/mammals_45_types_image_classification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-mammals_45_types_image_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-mammals_45_types_image_classification_pipeline_en.md
new file mode 100644
index 00000000000000..145a177ff04e3f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-mammals_45_types_image_classification_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mammals_45_types_image_classification_pipeline pipeline ViTForImageClassification from dima806
+author: John Snow Labs
+name: mammals_45_types_image_classification_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mammals_45_types_image_classification_pipeline` is a English model originally trained by dima806.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mammals_45_types_image_classification_pipeline_en_5.5.1_3.0_1738022303187.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mammals_45_types_image_classification_pipeline_en_5.5.1_3.0_1738022303187.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mammals_45_types_image_classification_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mammals_45_types_image_classification_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mammals_45_types_image_classification_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.5 MB|
+
+## References
+
+https://huggingface.co/dima806/mammals_45_types_image_classification
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-marian_finetuned_kde4_english_tonga_tonga_islands_french_longma98_en.md b/docs/_posts/ahmedlone127/2025-01-27-marian_finetuned_kde4_english_tonga_tonga_islands_french_longma98_en.md
new file mode 100644
index 00000000000000..16c9dd741a1317
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-marian_finetuned_kde4_english_tonga_tonga_islands_french_longma98_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English marian_finetuned_kde4_english_tonga_tonga_islands_french_longma98 MarianTransformer from longma98
+author: John Snow Labs
+name: marian_finetuned_kde4_english_tonga_tonga_islands_french_longma98
+date: 2025-01-27
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_french_longma98` is a English model originally trained by longma98.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_longma98_en_5.5.1_3.0_1737937410583.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_longma98_en_5.5.1_3.0_1737937410583.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("marian_finetuned_kde4_english_tonga_tonga_islands_french_longma98","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("marian_finetuned_kde4_english_tonga_tonga_islands_french_longma98","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_french_longma98|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|397.1 MB|
+
+## References
+
+https://huggingface.co/longma98/marian-finetuned-kde4-en-to-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-marian_finetuned_kde4_english_tonga_tonga_islands_french_longma98_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-marian_finetuned_kde4_english_tonga_tonga_islands_french_longma98_pipeline_en.md
new file mode 100644
index 00000000000000..c8f469f04f75a1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-marian_finetuned_kde4_english_tonga_tonga_islands_french_longma98_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English marian_finetuned_kde4_english_tonga_tonga_islands_french_longma98_pipeline pipeline MarianTransformer from longma98
+author: John Snow Labs
+name: marian_finetuned_kde4_english_tonga_tonga_islands_french_longma98_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_french_longma98_pipeline` is a English model originally trained by longma98.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_longma98_pipeline_en_5.5.1_3.0_1737937430957.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_longma98_pipeline_en_5.5.1_3.0_1737937430957.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_french_longma98_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_french_longma98_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_french_longma98_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|397.6 MB|
+
+## References
+
+https://huggingface.co/longma98/marian-finetuned-kde4-en-to-fr
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-max_pruned_50_model_en.md b/docs/_posts/ahmedlone127/2025-01-27-max_pruned_50_model_en.md
new file mode 100644
index 00000000000000..116375f108cca3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-max_pruned_50_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English max_pruned_50_model DistilBertForSequenceClassification from andygoh5
+author: John Snow Labs
+name: max_pruned_50_model
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`max_pruned_50_model` is a English model originally trained by andygoh5.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/max_pruned_50_model_en_5.5.1_3.0_1737939463385.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/max_pruned_50_model_en_5.5.1_3.0_1737939463385.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("max_pruned_50_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("max_pruned_50_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|max_pruned_50_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/andygoh5/max-pruned-50-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-max_pruned_50_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-max_pruned_50_model_pipeline_en.md
new file mode 100644
index 00000000000000..6f74aff186cdc0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-max_pruned_50_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English max_pruned_50_model_pipeline pipeline DistilBertForSequenceClassification from andygoh5
+author: John Snow Labs
+name: max_pruned_50_model_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`max_pruned_50_model_pipeline` is a English model originally trained by andygoh5.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/max_pruned_50_model_pipeline_en_5.5.1_3.0_1737939482143.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/max_pruned_50_model_pipeline_en_5.5.1_3.0_1737939482143.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("max_pruned_50_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("max_pruned_50_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|max_pruned_50_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/andygoh5/max-pruned-50-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-medflan_t5_large_en.md b/docs/_posts/ahmedlone127/2025-01-27-medflan_t5_large_en.md
new file mode 100644
index 00000000000000..bf9c4fbed872d9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-medflan_t5_large_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English medflan_t5_large T5Transformer from Karthikeyan-M3011
+author: John Snow Labs
+name: medflan_t5_large
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`medflan_t5_large` is a English model originally trained by Karthikeyan-M3011.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/medflan_t5_large_en_5.5.1_3.0_1737944667983.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/medflan_t5_large_en_5.5.1_3.0_1737944667983.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("medflan_t5_large","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("medflan_t5_large", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|medflan_t5_large|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|3.1 GB|
+
+## References
+
+https://huggingface.co/Karthikeyan-M3011/medflan-t5-large
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-medflan_t5_large_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-medflan_t5_large_pipeline_en.md
new file mode 100644
index 00000000000000..2b5b07a6df2086
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-medflan_t5_large_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English medflan_t5_large_pipeline pipeline T5Transformer from Karthikeyan-M3011
+author: John Snow Labs
+name: medflan_t5_large_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`medflan_t5_large_pipeline` is a English model originally trained by Karthikeyan-M3011.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/medflan_t5_large_pipeline_en_5.5.1_3.0_1737944816760.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/medflan_t5_large_pipeline_en_5.5.1_3.0_1737944816760.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("medflan_t5_large_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("medflan_t5_large_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|medflan_t5_large_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|3.1 GB|
+
+## References
+
+https://huggingface.co/Karthikeyan-M3011/medflan-t5-large
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-medical_summarization_finetuned_medical_summary_en.md b/docs/_posts/ahmedlone127/2025-01-27-medical_summarization_finetuned_medical_summary_en.md
new file mode 100644
index 00000000000000..a63a9c2f5ab8ac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-medical_summarization_finetuned_medical_summary_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English medical_summarization_finetuned_medical_summary T5Transformer from smiling-pranjal
+author: John Snow Labs
+name: medical_summarization_finetuned_medical_summary
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`medical_summarization_finetuned_medical_summary` is a English model originally trained by smiling-pranjal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/medical_summarization_finetuned_medical_summary_en_5.5.1_3.0_1737977827308.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/medical_summarization_finetuned_medical_summary_en_5.5.1_3.0_1737977827308.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("medical_summarization_finetuned_medical_summary","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("medical_summarization_finetuned_medical_summary", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|medical_summarization_finetuned_medical_summary|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|284.9 MB|
+
+## References
+
+https://huggingface.co/smiling-pranjal/medical_summarization-finetuned-Medical-summary
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-medical_summarization_finetuned_medical_summary_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-medical_summarization_finetuned_medical_summary_pipeline_en.md
new file mode 100644
index 00000000000000..7fcabf692858f6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-medical_summarization_finetuned_medical_summary_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English medical_summarization_finetuned_medical_summary_pipeline pipeline T5Transformer from smiling-pranjal
+author: John Snow Labs
+name: medical_summarization_finetuned_medical_summary_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`medical_summarization_finetuned_medical_summary_pipeline` is a English model originally trained by smiling-pranjal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/medical_summarization_finetuned_medical_summary_pipeline_en_5.5.1_3.0_1737977842482.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/medical_summarization_finetuned_medical_summary_pipeline_en_5.5.1_3.0_1737977842482.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("medical_summarization_finetuned_medical_summary_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("medical_summarization_finetuned_medical_summary_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|medical_summarization_finetuned_medical_summary_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|284.9 MB|
+
+## References
+
+https://huggingface.co/smiling-pranjal/medical_summarization-finetuned-Medical-summary
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-meeting_summarizer_model_en.md b/docs/_posts/ahmedlone127/2025-01-27-meeting_summarizer_model_en.md
new file mode 100644
index 00000000000000..3bdf5673662144
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-meeting_summarizer_model_en.md
@@ -0,0 +1,88 @@
+---
+layout: model
+title: English meeting_summarizer_model T5Transformer from cameronslee
+author: John Snow Labs
+name: meeting_summarizer_model
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`meeting_summarizer_model` is a English model originally trained by cameronslee.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/meeting_summarizer_model_en_5.5.1_3.0_1737977974639.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/meeting_summarizer_model_en_5.5.1_3.0_1737977974639.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("meeting_summarizer_model","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("meeting_summarizer_model", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|meeting_summarizer_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|282.0 MB|
+
+## References
+
+References
+
+https://huggingface.co/cameronslee/meeting_summarizer_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-meeting_summarizer_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-meeting_summarizer_model_pipeline_en.md
new file mode 100644
index 00000000000000..5c41680a05607a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-meeting_summarizer_model_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English meeting_summarizer_model_pipeline pipeline T5Transformer from cameronslee
+author: John Snow Labs
+name: meeting_summarizer_model_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`meeting_summarizer_model_pipeline` is a English model originally trained by cameronslee.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/meeting_summarizer_model_pipeline_en_5.5.1_3.0_1737977990565.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/meeting_summarizer_model_pipeline_en_5.5.1_3.0_1737977990565.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("meeting_summarizer_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("meeting_summarizer_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|meeting_summarizer_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|282.0 MB|
+
+## References
+
+References
+
+https://huggingface.co/cameronslee/meeting_summarizer_model
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-mergedistill_maltese_italian_128_v2_en.md b/docs/_posts/ahmedlone127/2025-01-27-mergedistill_maltese_italian_128_v2_en.md
new file mode 100644
index 00000000000000..894821104e42bb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-mergedistill_maltese_italian_128_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mergedistill_maltese_italian_128_v2 BertEmbeddings from amitness
+author: John Snow Labs
+name: mergedistill_maltese_italian_128_v2
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mergedistill_maltese_italian_128_v2` is a English model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_italian_128_v2_en_5.5.1_3.0_1737985131705.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_italian_128_v2_en_5.5.1_3.0_1737985131705.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("mergedistill_maltese_italian_128_v2","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("mergedistill_maltese_italian_128_v2","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mergedistill_maltese_italian_128_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|538.7 MB|
+
+## References
+
+https://huggingface.co/amitness/mergedistill-mt-it-128-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-mergedistill_maltese_italian_128_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-mergedistill_maltese_italian_128_v2_pipeline_en.md
new file mode 100644
index 00000000000000..c9f9dcd3a1190b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-mergedistill_maltese_italian_128_v2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mergedistill_maltese_italian_128_v2_pipeline pipeline BertEmbeddings from amitness
+author: John Snow Labs
+name: mergedistill_maltese_italian_128_v2_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mergedistill_maltese_italian_128_v2_pipeline` is a English model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_italian_128_v2_pipeline_en_5.5.1_3.0_1737985159558.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_italian_128_v2_pipeline_en_5.5.1_3.0_1737985159558.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mergedistill_maltese_italian_128_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mergedistill_maltese_italian_128_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mergedistill_maltese_italian_128_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|538.7 MB|
+
+## References
+
+https://huggingface.co/amitness/mergedistill-mt-it-128-v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-mergedistill_maltese_italian_en.md b/docs/_posts/ahmedlone127/2025-01-27-mergedistill_maltese_italian_en.md
new file mode 100644
index 00000000000000..cf76372442a919
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-mergedistill_maltese_italian_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mergedistill_maltese_italian BertEmbeddings from amitness
+author: John Snow Labs
+name: mergedistill_maltese_italian
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mergedistill_maltese_italian` is a English model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_italian_en_5.5.1_3.0_1737985481569.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_italian_en_5.5.1_3.0_1737985481569.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("mergedistill_maltese_italian","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("mergedistill_maltese_italian","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mergedistill_maltese_italian|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|538.8 MB|
+
+## References
+
+https://huggingface.co/amitness/mergedistill-mt-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-mergedistill_maltese_italian_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-mergedistill_maltese_italian_pipeline_en.md
new file mode 100644
index 00000000000000..06b95090d25b0b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-mergedistill_maltese_italian_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mergedistill_maltese_italian_pipeline pipeline BertEmbeddings from amitness
+author: John Snow Labs
+name: mergedistill_maltese_italian_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mergedistill_maltese_italian_pipeline` is a English model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_italian_pipeline_en_5.5.1_3.0_1737985513223.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_italian_pipeline_en_5.5.1_3.0_1737985513223.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mergedistill_maltese_italian_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mergedistill_maltese_italian_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mergedistill_maltese_italian_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|538.8 MB|
+
+## References
+
+https://huggingface.co/amitness/mergedistill-mt-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-message_responder_en.md b/docs/_posts/ahmedlone127/2025-01-27-message_responder_en.md
new file mode 100644
index 00000000000000..4853177c1be95a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-message_responder_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English message_responder T5Transformer from 3mr7amdy
+author: John Snow Labs
+name: message_responder
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`message_responder` is a English model originally trained by 3mr7amdy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/message_responder_en_5.5.1_3.0_1737979637224.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/message_responder_en_5.5.1_3.0_1737979637224.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("message_responder","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("message_responder", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|message_responder|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|3.1 GB|
+
+## References
+
+https://huggingface.co/3mr7amdy/message-responder
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-message_responder_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-message_responder_pipeline_en.md
new file mode 100644
index 00000000000000..85a2f9b4f65f37
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-message_responder_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English message_responder_pipeline pipeline T5Transformer from 3mr7amdy
+author: John Snow Labs
+name: message_responder_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`message_responder_pipeline` is a English model originally trained by 3mr7amdy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/message_responder_pipeline_en_5.5.1_3.0_1737979803529.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/message_responder_pipeline_en_5.5.1_3.0_1737979803529.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("message_responder_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("message_responder_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|message_responder_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|3.1 GB|
+
+## References
+
+https://huggingface.co/3mr7amdy/message-responder
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-mgg_model_tclss_en.md b/docs/_posts/ahmedlone127/2025-01-27-mgg_model_tclss_en.md
new file mode 100644
index 00000000000000..12b008c5786de5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-mgg_model_tclss_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mgg_model_tclss DistilBertForSequenceClassification from ManuGG
+author: John Snow Labs
+name: mgg_model_tclss
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mgg_model_tclss` is a English model originally trained by ManuGG.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mgg_model_tclss_en_5.5.1_3.0_1737939574563.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mgg_model_tclss_en_5.5.1_3.0_1737939574563.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("mgg_model_tclss","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("mgg_model_tclss", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mgg_model_tclss|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/ManuGG/MGG_model_tclss
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-mgg_model_tclss_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-mgg_model_tclss_pipeline_en.md
new file mode 100644
index 00000000000000..fc93c1039f4433
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-mgg_model_tclss_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mgg_model_tclss_pipeline pipeline DistilBertForSequenceClassification from ManuGG
+author: John Snow Labs
+name: mgg_model_tclss_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mgg_model_tclss_pipeline` is a English model originally trained by ManuGG.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mgg_model_tclss_pipeline_en_5.5.1_3.0_1737939588774.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mgg_model_tclss_pipeline_en_5.5.1_3.0_1737939588774.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mgg_model_tclss_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mgg_model_tclss_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mgg_model_tclss_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/ManuGG/MGG_model_tclss
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-model_xlm_sentiment_en.md b/docs/_posts/ahmedlone127/2025-01-27-model_xlm_sentiment_en.md
new file mode 100644
index 00000000000000..3e1c1685d1022d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-model_xlm_sentiment_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English model_xlm_sentiment XlmRoBertaForSequenceClassification from alkin12
+author: John Snow Labs
+name: model_xlm_sentiment
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_xlm_sentiment` is a English model originally trained by alkin12.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_xlm_sentiment_en_5.5.1_3.0_1737959430833.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_xlm_sentiment_en_5.5.1_3.0_1737959430833.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("model_xlm_sentiment","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("model_xlm_sentiment", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|model_xlm_sentiment|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|864.5 MB|
+
+## References
+
+https://huggingface.co/alkin12/model_xlm_sentiment
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-model_xlm_sentiment_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-model_xlm_sentiment_pipeline_en.md
new file mode 100644
index 00000000000000..e088ac49cde4cf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-model_xlm_sentiment_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English model_xlm_sentiment_pipeline pipeline XlmRoBertaForSequenceClassification from alkin12
+author: John Snow Labs
+name: model_xlm_sentiment_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_xlm_sentiment_pipeline` is a English model originally trained by alkin12.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_xlm_sentiment_pipeline_en_5.5.1_3.0_1737959499382.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_xlm_sentiment_pipeline_en_5.5.1_3.0_1737959499382.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("model_xlm_sentiment_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("model_xlm_sentiment_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|model_xlm_sentiment_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|864.5 MB|
+
+## References
+
+https://huggingface.co/alkin12/model_xlm_sentiment
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-motarjem_v0_1_en.md b/docs/_posts/ahmedlone127/2025-01-27-motarjem_v0_1_en.md
new file mode 100644
index 00000000000000..4a71a6d217073c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-motarjem_v0_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English motarjem_v0_1 MarianTransformer from abdeljalilELmajjodi
+author: John Snow Labs
+name: motarjem_v0_1
+date: 2025-01-27
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`motarjem_v0_1` is a English model originally trained by abdeljalilELmajjodi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/motarjem_v0_1_en_5.5.1_3.0_1737937415374.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/motarjem_v0_1_en_5.5.1_3.0_1737937415374.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("motarjem_v0_1","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("motarjem_v0_1","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|motarjem_v0_1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|436.2 MB|
+
+## References
+
+https://huggingface.co/abdeljalilELmajjodi/Motarjem-v0.1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-motarjem_v0_1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-motarjem_v0_1_pipeline_en.md
new file mode 100644
index 00000000000000..2d4c6c69e88beb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-motarjem_v0_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English motarjem_v0_1_pipeline pipeline MarianTransformer from abdeljalilELmajjodi
+author: John Snow Labs
+name: motarjem_v0_1_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`motarjem_v0_1_pipeline` is a English model originally trained by abdeljalilELmajjodi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/motarjem_v0_1_pipeline_en_5.5.1_3.0_1737937443924.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/motarjem_v0_1_pipeline_en_5.5.1_3.0_1737937443924.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("motarjem_v0_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("motarjem_v0_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|motarjem_v0_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|436.7 MB|
+
+## References
+
+https://huggingface.co/abdeljalilELmajjodi/Motarjem-v0.1
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-movie_classifier_en.md b/docs/_posts/ahmedlone127/2025-01-27-movie_classifier_en.md
new file mode 100644
index 00000000000000..111c138f21d8ef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-movie_classifier_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English movie_classifier DistilBertForSequenceClassification from camtay07
+author: John Snow Labs
+name: movie_classifier
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`movie_classifier` is a English model originally trained by camtay07.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/movie_classifier_en_5.5.1_3.0_1737940179870.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/movie_classifier_en_5.5.1_3.0_1737940179870.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("movie_classifier","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("movie_classifier", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|movie_classifier|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/camtay07/movie_classifier
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-movie_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-movie_classifier_pipeline_en.md
new file mode 100644
index 00000000000000..02e8915348a677
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-movie_classifier_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English movie_classifier_pipeline pipeline DistilBertForSequenceClassification from camtay07
+author: John Snow Labs
+name: movie_classifier_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`movie_classifier_pipeline` is a English model originally trained by camtay07.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/movie_classifier_pipeline_en_5.5.1_3.0_1737940193076.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/movie_classifier_pipeline_en_5.5.1_3.0_1737940193076.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("movie_classifier_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("movie_classifier_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|movie_classifier_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/camtay07/movie_classifier
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-mt5_base_ainu_en.md b/docs/_posts/ahmedlone127/2025-01-27-mt5_base_ainu_en.md
new file mode 100644
index 00000000000000..b38ae361f467a0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-mt5_base_ainu_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mt5_base_ainu T5Transformer from aynumosir
+author: John Snow Labs
+name: mt5_base_ainu
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_base_ainu` is a English model originally trained by aynumosir.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_base_ainu_en_5.5.1_3.0_1738001339165.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_base_ainu_en_5.5.1_3.0_1738001339165.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("mt5_base_ainu","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("mt5_base_ainu", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_base_ainu|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|2.3 GB|
+
+## References
+
+https://huggingface.co/aynumosir/mt5-base-ainu
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-mt5_base_ainu_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-mt5_base_ainu_pipeline_en.md
new file mode 100644
index 00000000000000..ef2e0bd279d17f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-mt5_base_ainu_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mt5_base_ainu_pipeline pipeline T5Transformer from aynumosir
+author: John Snow Labs
+name: mt5_base_ainu_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_base_ainu_pipeline` is a English model originally trained by aynumosir.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_base_ainu_pipeline_en_5.5.1_3.0_1738001504652.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_base_ainu_pipeline_en_5.5.1_3.0_1738001504652.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mt5_base_ainu_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mt5_base_ainu_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_base_ainu_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|2.3 GB|
+
+## References
+
+https://huggingface.co/aynumosir/mt5-base-ainu
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-mt5_base_english_thai_wiki_en.md b/docs/_posts/ahmedlone127/2025-01-27-mt5_base_english_thai_wiki_en.md
new file mode 100644
index 00000000000000..c6fdd7691cda21
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-mt5_base_english_thai_wiki_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mt5_base_english_thai_wiki T5Transformer from e22vvb
+author: John Snow Labs
+name: mt5_base_english_thai_wiki
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_base_english_thai_wiki` is a English model originally trained by e22vvb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_base_english_thai_wiki_en_5.5.1_3.0_1738009391417.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_base_english_thai_wiki_en_5.5.1_3.0_1738009391417.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("mt5_base_english_thai_wiki","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("mt5_base_english_thai_wiki", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_base_english_thai_wiki|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/e22vvb/mt5_base_EN_TH_wiki
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-mt5_base_english_thai_wiki_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-mt5_base_english_thai_wiki_pipeline_en.md
new file mode 100644
index 00000000000000..e4766b10359ddc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-mt5_base_english_thai_wiki_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mt5_base_english_thai_wiki_pipeline pipeline T5Transformer from e22vvb
+author: John Snow Labs
+name: mt5_base_english_thai_wiki_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_base_english_thai_wiki_pipeline` is a English model originally trained by e22vvb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_base_english_thai_wiki_pipeline_en_5.5.1_3.0_1738009866955.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_base_english_thai_wiki_pipeline_en_5.5.1_3.0_1738009866955.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mt5_base_english_thai_wiki_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mt5_base_english_thai_wiki_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_base_english_thai_wiki_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/e22vvb/mt5_base_EN_TH_wiki
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-mt5_base_multi_label_all_czech_iv_en.md b/docs/_posts/ahmedlone127/2025-01-27-mt5_base_multi_label_all_czech_iv_en.md
new file mode 100644
index 00000000000000..e1bb464cb96571
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-mt5_base_multi_label_all_czech_iv_en.md
@@ -0,0 +1,88 @@
+---
+layout: model
+title: English mt5_base_multi_label_all_czech_iv T5Transformer from chi2024
+author: John Snow Labs
+name: mt5_base_multi_label_all_czech_iv
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_base_multi_label_all_czech_iv` is a English model originally trained by chi2024.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_base_multi_label_all_czech_iv_en_5.5.1_3.0_1737978392405.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_base_multi_label_all_czech_iv_en_5.5.1_3.0_1737978392405.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("mt5_base_multi_label_all_czech_iv","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("mt5_base_multi_label_all_czech_iv", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_base_multi_label_all_czech_iv|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|2.3 GB|
+
+## References
+
+References
+
+https://huggingface.co/chi2024/mt5-base-multi-label-all-cs-iv
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-mt5_base_multi_label_all_czech_iv_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-mt5_base_multi_label_all_czech_iv_pipeline_en.md
new file mode 100644
index 00000000000000..a5c4b9ceec273a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-mt5_base_multi_label_all_czech_iv_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English mt5_base_multi_label_all_czech_iv_pipeline pipeline T5Transformer from chi2024
+author: John Snow Labs
+name: mt5_base_multi_label_all_czech_iv_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_base_multi_label_all_czech_iv_pipeline` is a English model originally trained by chi2024.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_base_multi_label_all_czech_iv_pipeline_en_5.5.1_3.0_1737978692437.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_base_multi_label_all_czech_iv_pipeline_en_5.5.1_3.0_1737978692437.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("mt5_base_multi_label_all_czech_iv_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("mt5_base_multi_label_all_czech_iv_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_base_multi_label_all_czech_iv_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|2.3 GB|
+
+## References
+
+References
+
+https://huggingface.co/chi2024/mt5-base-multi-label-all-cs-iv
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-mt5_base_multi_label_english_iiib_02c_en.md b/docs/_posts/ahmedlone127/2025-01-27-mt5_base_multi_label_english_iiib_02c_en.md
new file mode 100644
index 00000000000000..d89b511afc341e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-mt5_base_multi_label_english_iiib_02c_en.md
@@ -0,0 +1,88 @@
+---
+layout: model
+title: English mt5_base_multi_label_english_iiib_02c T5Transformer from chi2024
+author: John Snow Labs
+name: mt5_base_multi_label_english_iiib_02c
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_base_multi_label_english_iiib_02c` is a English model originally trained by chi2024.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_base_multi_label_english_iiib_02c_en_5.5.1_3.0_1737944229079.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_base_multi_label_english_iiib_02c_en_5.5.1_3.0_1737944229079.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("mt5_base_multi_label_english_iiib_02c","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("mt5_base_multi_label_english_iiib_02c", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_base_multi_label_english_iiib_02c|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|2.3 GB|
+
+## References
+
+References
+
+https://huggingface.co/chi2024/mt5-base-multi-label-en-iiib-02c
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-mt5_base_multi_label_english_iiib_02c_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-mt5_base_multi_label_english_iiib_02c_pipeline_en.md
new file mode 100644
index 00000000000000..667fb72d4f446a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-mt5_base_multi_label_english_iiib_02c_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English mt5_base_multi_label_english_iiib_02c_pipeline pipeline T5Transformer from chi2024
+author: John Snow Labs
+name: mt5_base_multi_label_english_iiib_02c_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_base_multi_label_english_iiib_02c_pipeline` is a English model originally trained by chi2024.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_base_multi_label_english_iiib_02c_pipeline_en_5.5.1_3.0_1737944530609.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_base_multi_label_english_iiib_02c_pipeline_en_5.5.1_3.0_1737944530609.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("mt5_base_multi_label_english_iiib_02c_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("mt5_base_multi_label_english_iiib_02c_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_base_multi_label_english_iiib_02c_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|2.3 GB|
+
+## References
+
+References
+
+https://huggingface.co/chi2024/mt5-base-multi-label-en-iiib-02c
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-mt5_base_thai_spider_en.md b/docs/_posts/ahmedlone127/2025-01-27-mt5_base_thai_spider_en.md
new file mode 100644
index 00000000000000..be7ac00a443862
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-mt5_base_thai_spider_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mt5_base_thai_spider T5Transformer from e22vvb
+author: John Snow Labs
+name: mt5_base_thai_spider
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_base_thai_spider` is a English model originally trained by e22vvb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_base_thai_spider_en_5.5.1_3.0_1737993772516.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_base_thai_spider_en_5.5.1_3.0_1737993772516.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("mt5_base_thai_spider","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("mt5_base_thai_spider", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_base_thai_spider|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/e22vvb/mt5-base_TH_spider
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-mt5_base_thai_spider_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-mt5_base_thai_spider_pipeline_en.md
new file mode 100644
index 00000000000000..cf89d028046250
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-mt5_base_thai_spider_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mt5_base_thai_spider_pipeline pipeline T5Transformer from e22vvb
+author: John Snow Labs
+name: mt5_base_thai_spider_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_base_thai_spider_pipeline` is a English model originally trained by e22vvb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_base_thai_spider_pipeline_en_5.5.1_3.0_1737994252346.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_base_thai_spider_pipeline_en_5.5.1_3.0_1737994252346.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mt5_base_thai_spider_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mt5_base_thai_spider_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_base_thai_spider_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/e22vvb/mt5-base_TH_spider
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-mt5_bleu4_durga_q1_clean_en.md b/docs/_posts/ahmedlone127/2025-01-27-mt5_bleu4_durga_q1_clean_en.md
new file mode 100644
index 00000000000000..b8d72f07a878e7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-mt5_bleu4_durga_q1_clean_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mt5_bleu4_durga_q1_clean T5Transformer from devagonal
+author: John Snow Labs
+name: mt5_bleu4_durga_q1_clean
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_bleu4_durga_q1_clean` is a English model originally trained by devagonal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_bleu4_durga_q1_clean_en_5.5.1_3.0_1737991353120.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_bleu4_durga_q1_clean_en_5.5.1_3.0_1737991353120.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("mt5_bleu4_durga_q1_clean","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("mt5_bleu4_durga_q1_clean", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_bleu4_durga_q1_clean|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|2.2 GB|
+
+## References
+
+https://huggingface.co/devagonal/mt5-bleu4-durga-q1-clean
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-mt5_bleu4_durga_q1_clean_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-mt5_bleu4_durga_q1_clean_pipeline_en.md
new file mode 100644
index 00000000000000..bf1d507adfc1e2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-mt5_bleu4_durga_q1_clean_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mt5_bleu4_durga_q1_clean_pipeline pipeline T5Transformer from devagonal
+author: John Snow Labs
+name: mt5_bleu4_durga_q1_clean_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_bleu4_durga_q1_clean_pipeline` is a English model originally trained by devagonal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_bleu4_durga_q1_clean_pipeline_en_5.5.1_3.0_1737991547078.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_bleu4_durga_q1_clean_pipeline_en_5.5.1_3.0_1737991547078.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mt5_bleu4_durga_q1_clean_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mt5_bleu4_durga_q1_clean_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_bleu4_durga_q1_clean_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|2.2 GB|
+
+## References
+
+https://huggingface.co/devagonal/mt5-bleu4-durga-q1-clean
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-mt5_custom_translation_en.md b/docs/_posts/ahmedlone127/2025-01-27-mt5_custom_translation_en.md
new file mode 100644
index 00000000000000..3cf47a2dd28a59
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-mt5_custom_translation_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mt5_custom_translation T5Transformer from Kumshe
+author: John Snow Labs
+name: mt5_custom_translation
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_custom_translation` is a English model originally trained by Kumshe.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_custom_translation_en_5.5.1_3.0_1737963357188.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_custom_translation_en_5.5.1_3.0_1737963357188.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("mt5_custom_translation","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("mt5_custom_translation", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_custom_translation|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/Kumshe/mt5-custom-translation
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-mt5_custom_translation_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-mt5_custom_translation_pipeline_en.md
new file mode 100644
index 00000000000000..9b5be046f4d19e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-mt5_custom_translation_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mt5_custom_translation_pipeline pipeline T5Transformer from Kumshe
+author: John Snow Labs
+name: mt5_custom_translation_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_custom_translation_pipeline` is a English model originally trained by Kumshe.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_custom_translation_pipeline_en_5.5.1_3.0_1737963484750.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_custom_translation_pipeline_en_5.5.1_3.0_1737963484750.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mt5_custom_translation_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mt5_custom_translation_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_custom_translation_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/Kumshe/mt5-custom-translation
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-mt5_dp_en.md b/docs/_posts/ahmedlone127/2025-01-27-mt5_dp_en.md
new file mode 100644
index 00000000000000..54db4e05189f23
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-mt5_dp_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mt5_dp T5Transformer from engindemir
+author: John Snow Labs
+name: mt5_dp
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_dp` is a English model originally trained by engindemir.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_dp_en_5.5.1_3.0_1737990434086.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_dp_en_5.5.1_3.0_1737990434086.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("mt5_dp","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("mt5_dp", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_dp|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|2.3 GB|
+
+## References
+
+https://huggingface.co/engindemir/mt5_dp
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-mt5_dp_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-mt5_dp_pipeline_en.md
new file mode 100644
index 00000000000000..7f006cf3458c0a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-mt5_dp_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mt5_dp_pipeline pipeline T5Transformer from engindemir
+author: John Snow Labs
+name: mt5_dp_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_dp_pipeline` is a English model originally trained by engindemir.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_dp_pipeline_en_5.5.1_3.0_1737990644718.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_dp_pipeline_en_5.5.1_3.0_1737990644718.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mt5_dp_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mt5_dp_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_dp_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|2.3 GB|
+
+## References
+
+https://huggingface.co/engindemir/mt5_dp
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-mt5_er_v1_en.md b/docs/_posts/ahmedlone127/2025-01-27-mt5_er_v1_en.md
new file mode 100644
index 00000000000000..fd0ccacf6263c6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-mt5_er_v1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mt5_er_v1 T5Transformer from Tippawan
+author: John Snow Labs
+name: mt5_er_v1
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_er_v1` is a English model originally trained by Tippawan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_er_v1_en_5.5.1_3.0_1737990938947.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_er_v1_en_5.5.1_3.0_1737990938947.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("mt5_er_v1","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("mt5_er_v1", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_er_v1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|819.8 MB|
+
+## References
+
+https://huggingface.co/Tippawan/mt5-er-v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-mt5_er_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-mt5_er_v1_pipeline_en.md
new file mode 100644
index 00000000000000..2762f06472d12e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-mt5_er_v1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mt5_er_v1_pipeline pipeline T5Transformer from Tippawan
+author: John Snow Labs
+name: mt5_er_v1_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_er_v1_pipeline` is a English model originally trained by Tippawan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_er_v1_pipeline_en_5.5.1_3.0_1737991212972.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_er_v1_pipeline_en_5.5.1_3.0_1737991212972.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mt5_er_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mt5_er_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_er_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|819.8 MB|
+
+## References
+
+https://huggingface.co/Tippawan/mt5-er-v1
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-mt5_romainian_tonga_tonga_islands_emoji_en.md b/docs/_posts/ahmedlone127/2025-01-27-mt5_romainian_tonga_tonga_islands_emoji_en.md
new file mode 100644
index 00000000000000..ce9f0bb35e31b1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-mt5_romainian_tonga_tonga_islands_emoji_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mt5_romainian_tonga_tonga_islands_emoji T5Transformer from StefaniaCri
+author: John Snow Labs
+name: mt5_romainian_tonga_tonga_islands_emoji
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_romainian_tonga_tonga_islands_emoji` is a English model originally trained by StefaniaCri.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_romainian_tonga_tonga_islands_emoji_en_5.5.1_3.0_1737946550660.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_romainian_tonga_tonga_islands_emoji_en_5.5.1_3.0_1737946550660.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("mt5_romainian_tonga_tonga_islands_emoji","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("mt5_romainian_tonga_tonga_islands_emoji", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_romainian_tonga_tonga_islands_emoji|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|2.2 GB|
+
+## References
+
+https://huggingface.co/StefaniaCri/mt5_romainian_to_emoji
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-mt5_romainian_tonga_tonga_islands_emoji_generated_en.md b/docs/_posts/ahmedlone127/2025-01-27-mt5_romainian_tonga_tonga_islands_emoji_generated_en.md
new file mode 100644
index 00000000000000..856873f2019998
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-mt5_romainian_tonga_tonga_islands_emoji_generated_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mt5_romainian_tonga_tonga_islands_emoji_generated T5Transformer from StefaniaCri
+author: John Snow Labs
+name: mt5_romainian_tonga_tonga_islands_emoji_generated
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_romainian_tonga_tonga_islands_emoji_generated` is a English model originally trained by StefaniaCri.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_romainian_tonga_tonga_islands_emoji_generated_en_5.5.1_3.0_1737979317382.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_romainian_tonga_tonga_islands_emoji_generated_en_5.5.1_3.0_1737979317382.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("mt5_romainian_tonga_tonga_islands_emoji_generated","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("mt5_romainian_tonga_tonga_islands_emoji_generated", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_romainian_tonga_tonga_islands_emoji_generated|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|2.2 GB|
+
+## References
+
+https://huggingface.co/StefaniaCri/mt5_romainian_to_emoji_generated
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-mt5_romainian_tonga_tonga_islands_emoji_generated_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-mt5_romainian_tonga_tonga_islands_emoji_generated_pipeline_en.md
new file mode 100644
index 00000000000000..c4acf6e124c856
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-mt5_romainian_tonga_tonga_islands_emoji_generated_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mt5_romainian_tonga_tonga_islands_emoji_generated_pipeline pipeline T5Transformer from StefaniaCri
+author: John Snow Labs
+name: mt5_romainian_tonga_tonga_islands_emoji_generated_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_romainian_tonga_tonga_islands_emoji_generated_pipeline` is a English model originally trained by StefaniaCri.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_romainian_tonga_tonga_islands_emoji_generated_pipeline_en_5.5.1_3.0_1737979642792.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_romainian_tonga_tonga_islands_emoji_generated_pipeline_en_5.5.1_3.0_1737979642792.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mt5_romainian_tonga_tonga_islands_emoji_generated_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mt5_romainian_tonga_tonga_islands_emoji_generated_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_romainian_tonga_tonga_islands_emoji_generated_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|2.2 GB|
+
+## References
+
+https://huggingface.co/StefaniaCri/mt5_romainian_to_emoji_generated
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-mt5_romainian_tonga_tonga_islands_emoji_mixed_en.md b/docs/_posts/ahmedlone127/2025-01-27-mt5_romainian_tonga_tonga_islands_emoji_mixed_en.md
new file mode 100644
index 00000000000000..774bce300ac488
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-mt5_romainian_tonga_tonga_islands_emoji_mixed_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mt5_romainian_tonga_tonga_islands_emoji_mixed T5Transformer from StefaniaCri
+author: John Snow Labs
+name: mt5_romainian_tonga_tonga_islands_emoji_mixed
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_romainian_tonga_tonga_islands_emoji_mixed` is a English model originally trained by StefaniaCri.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_romainian_tonga_tonga_islands_emoji_mixed_en_5.5.1_3.0_1738002063213.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_romainian_tonga_tonga_islands_emoji_mixed_en_5.5.1_3.0_1738002063213.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("mt5_romainian_tonga_tonga_islands_emoji_mixed","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("mt5_romainian_tonga_tonga_islands_emoji_mixed", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_romainian_tonga_tonga_islands_emoji_mixed|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|2.2 GB|
+
+## References
+
+https://huggingface.co/StefaniaCri/mt5_romainian_to_emoji_mixed
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-mt5_romainian_tonga_tonga_islands_emoji_mixed_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-mt5_romainian_tonga_tonga_islands_emoji_mixed_pipeline_en.md
new file mode 100644
index 00000000000000..e8f023828bedfe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-mt5_romainian_tonga_tonga_islands_emoji_mixed_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mt5_romainian_tonga_tonga_islands_emoji_mixed_pipeline pipeline T5Transformer from StefaniaCri
+author: John Snow Labs
+name: mt5_romainian_tonga_tonga_islands_emoji_mixed_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_romainian_tonga_tonga_islands_emoji_mixed_pipeline` is a English model originally trained by StefaniaCri.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_romainian_tonga_tonga_islands_emoji_mixed_pipeline_en_5.5.1_3.0_1738002373232.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_romainian_tonga_tonga_islands_emoji_mixed_pipeline_en_5.5.1_3.0_1738002373232.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mt5_romainian_tonga_tonga_islands_emoji_mixed_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mt5_romainian_tonga_tonga_islands_emoji_mixed_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_romainian_tonga_tonga_islands_emoji_mixed_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|2.2 GB|
+
+## References
+
+https://huggingface.co/StefaniaCri/mt5_romainian_to_emoji_mixed
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-mt5_romainian_tonga_tonga_islands_emoji_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-mt5_romainian_tonga_tonga_islands_emoji_pipeline_en.md
new file mode 100644
index 00000000000000..ebb69c365166a1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-mt5_romainian_tonga_tonga_islands_emoji_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mt5_romainian_tonga_tonga_islands_emoji_pipeline pipeline T5Transformer from StefaniaCri
+author: John Snow Labs
+name: mt5_romainian_tonga_tonga_islands_emoji_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_romainian_tonga_tonga_islands_emoji_pipeline` is a English model originally trained by StefaniaCri.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_romainian_tonga_tonga_islands_emoji_pipeline_en_5.5.1_3.0_1737946866225.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_romainian_tonga_tonga_islands_emoji_pipeline_en_5.5.1_3.0_1737946866225.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mt5_romainian_tonga_tonga_islands_emoji_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mt5_romainian_tonga_tonga_islands_emoji_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_romainian_tonga_tonga_islands_emoji_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|2.2 GB|
+
+## References
+
+https://huggingface.co/StefaniaCri/mt5_romainian_to_emoji
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-mt5_rouge_durga_q1_clean_en.md b/docs/_posts/ahmedlone127/2025-01-27-mt5_rouge_durga_q1_clean_en.md
new file mode 100644
index 00000000000000..b7f2e422e0a090
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-mt5_rouge_durga_q1_clean_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mt5_rouge_durga_q1_clean T5Transformer from devagonal
+author: John Snow Labs
+name: mt5_rouge_durga_q1_clean
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_rouge_durga_q1_clean` is a English model originally trained by devagonal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_rouge_durga_q1_clean_en_5.5.1_3.0_1737993429393.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_rouge_durga_q1_clean_en_5.5.1_3.0_1737993429393.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("mt5_rouge_durga_q1_clean","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("mt5_rouge_durga_q1_clean", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_rouge_durga_q1_clean|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|2.2 GB|
+
+## References
+
+https://huggingface.co/devagonal/mt5-rouge-durga-q1-clean
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-mt5_rouge_durga_q1_clean_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-mt5_rouge_durga_q1_clean_pipeline_en.md
new file mode 100644
index 00000000000000..6b2b89551ee0b6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-mt5_rouge_durga_q1_clean_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mt5_rouge_durga_q1_clean_pipeline pipeline T5Transformer from devagonal
+author: John Snow Labs
+name: mt5_rouge_durga_q1_clean_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_rouge_durga_q1_clean_pipeline` is a English model originally trained by devagonal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_rouge_durga_q1_clean_pipeline_en_5.5.1_3.0_1737993622676.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_rouge_durga_q1_clean_pipeline_en_5.5.1_3.0_1737993622676.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mt5_rouge_durga_q1_clean_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mt5_rouge_durga_q1_clean_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_rouge_durga_q1_clean_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|2.2 GB|
+
+## References
+
+https://huggingface.co/devagonal/mt5-rouge-durga-q1-clean
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-mt5_small_anaphora_czech_3e_en.md b/docs/_posts/ahmedlone127/2025-01-27-mt5_small_anaphora_czech_3e_en.md
new file mode 100644
index 00000000000000..0bec11a5a6ff00
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-mt5_small_anaphora_czech_3e_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mt5_small_anaphora_czech_3e T5Transformer from patrixtano
+author: John Snow Labs
+name: mt5_small_anaphora_czech_3e
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_small_anaphora_czech_3e` is a English model originally trained by patrixtano.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_small_anaphora_czech_3e_en_5.5.1_3.0_1737979827059.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_small_anaphora_czech_3e_en_5.5.1_3.0_1737979827059.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("mt5_small_anaphora_czech_3e","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("mt5_small_anaphora_czech_3e", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_small_anaphora_czech_3e|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/patrixtano/mt5-small-anaphora_czech_3e
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-mt5_small_anaphora_czech_3e_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-mt5_small_anaphora_czech_3e_pipeline_en.md
new file mode 100644
index 00000000000000..514f5605e4d5d9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-mt5_small_anaphora_czech_3e_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mt5_small_anaphora_czech_3e_pipeline pipeline T5Transformer from patrixtano
+author: John Snow Labs
+name: mt5_small_anaphora_czech_3e_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_small_anaphora_czech_3e_pipeline` is a English model originally trained by patrixtano.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_small_anaphora_czech_3e_pipeline_en_5.5.1_3.0_1737979972680.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_small_anaphora_czech_3e_pipeline_en_5.5.1_3.0_1737979972680.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mt5_small_anaphora_czech_3e_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mt5_small_anaphora_czech_3e_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_small_anaphora_czech_3e_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/patrixtano/mt5-small-anaphora_czech_3e
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-mt5_small_gigatrue_slovak_en.md b/docs/_posts/ahmedlone127/2025-01-27-mt5_small_gigatrue_slovak_en.md
new file mode 100644
index 00000000000000..fe3b114594c567
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-mt5_small_gigatrue_slovak_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mt5_small_gigatrue_slovak T5Transformer from Plasmoxy
+author: John Snow Labs
+name: mt5_small_gigatrue_slovak
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_small_gigatrue_slovak` is a English model originally trained by Plasmoxy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_small_gigatrue_slovak_en_5.5.1_3.0_1738008253397.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_small_gigatrue_slovak_en_5.5.1_3.0_1738008253397.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("mt5_small_gigatrue_slovak","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("mt5_small_gigatrue_slovak", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_small_gigatrue_slovak|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|816.2 MB|
+
+## References
+
+https://huggingface.co/Plasmoxy/mt5-small-gigatrue-slovak
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-mt5_small_gigatrue_slovak_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-mt5_small_gigatrue_slovak_pipeline_en.md
new file mode 100644
index 00000000000000..bc04ab58b15be3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-mt5_small_gigatrue_slovak_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mt5_small_gigatrue_slovak_pipeline pipeline T5Transformer from Plasmoxy
+author: John Snow Labs
+name: mt5_small_gigatrue_slovak_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_small_gigatrue_slovak_pipeline` is a English model originally trained by Plasmoxy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_small_gigatrue_slovak_pipeline_en_5.5.1_3.0_1738008529131.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_small_gigatrue_slovak_pipeline_en_5.5.1_3.0_1738008529131.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mt5_small_gigatrue_slovak_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mt5_small_gigatrue_slovak_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_small_gigatrue_slovak_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|816.2 MB|
+
+## References
+
+https://huggingface.co/Plasmoxy/mt5-small-gigatrue-slovak
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-mt5_small_hak_en.md b/docs/_posts/ahmedlone127/2025-01-27-mt5_small_hak_en.md
new file mode 100644
index 00000000000000..b6d100e71e039b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-mt5_small_hak_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mt5_small_hak T5Transformer from qavit
+author: John Snow Labs
+name: mt5_small_hak
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_small_hak` is a English model originally trained by qavit.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_small_hak_en_5.5.1_3.0_1737993166349.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_small_hak_en_5.5.1_3.0_1737993166349.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("mt5_small_hak","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("mt5_small_hak", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_small_hak|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/qavit/mt5-small-hak
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-mt5_small_hak_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-mt5_small_hak_pipeline_en.md
new file mode 100644
index 00000000000000..3128c7662fb117
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-mt5_small_hak_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mt5_small_hak_pipeline pipeline T5Transformer from qavit
+author: John Snow Labs
+name: mt5_small_hak_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_small_hak_pipeline` is a English model originally trained by qavit.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_small_hak_pipeline_en_5.5.1_3.0_1737993289420.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_small_hak_pipeline_en_5.5.1_3.0_1737993289420.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mt5_small_hak_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mt5_small_hak_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_small_hak_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/qavit/mt5-small-hak
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-mt5_small_meoo225_en.md b/docs/_posts/ahmedlone127/2025-01-27-mt5_small_meoo225_en.md
new file mode 100644
index 00000000000000..dd305de93bd2d9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-mt5_small_meoo225_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mt5_small_meoo225 T5Transformer from meoo225
+author: John Snow Labs
+name: mt5_small_meoo225
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_small_meoo225` is a English model originally trained by meoo225.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_small_meoo225_en_5.5.1_3.0_1738002470070.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_small_meoo225_en_5.5.1_3.0_1738002470070.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("mt5_small_meoo225","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("mt5_small_meoo225", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_small_meoo225|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/meoo225/mT5_small
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-mt5_small_meoo225_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-mt5_small_meoo225_pipeline_en.md
new file mode 100644
index 00000000000000..924a85bea76c16
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-mt5_small_meoo225_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mt5_small_meoo225_pipeline pipeline T5Transformer from meoo225
+author: John Snow Labs
+name: mt5_small_meoo225_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_small_meoo225_pipeline` is a English model originally trained by meoo225.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_small_meoo225_pipeline_en_5.5.1_3.0_1738002660293.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_small_meoo225_pipeline_en_5.5.1_3.0_1738002660293.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mt5_small_meoo225_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mt5_small_meoo225_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_small_meoo225_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/meoo225/mT5_small
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-mt5_small_qa_v2_enhanced_en.md b/docs/_posts/ahmedlone127/2025-01-27-mt5_small_qa_v2_enhanced_en.md
new file mode 100644
index 00000000000000..a7c483093c4a4f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-mt5_small_qa_v2_enhanced_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mt5_small_qa_v2_enhanced T5Transformer from hawalurahman
+author: John Snow Labs
+name: mt5_small_qa_v2_enhanced
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_small_qa_v2_enhanced` is a English model originally trained by hawalurahman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_small_qa_v2_enhanced_en_5.5.1_3.0_1737999575517.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_small_qa_v2_enhanced_en_5.5.1_3.0_1737999575517.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("mt5_small_qa_v2_enhanced","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("mt5_small_qa_v2_enhanced", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_small_qa_v2_enhanced|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/hawalurahman/mt5-small-qa_v2_enhanced
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-mt5_small_qa_v2_enhanced_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-mt5_small_qa_v2_enhanced_pipeline_en.md
new file mode 100644
index 00000000000000..b1e3a16bff484a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-mt5_small_qa_v2_enhanced_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mt5_small_qa_v2_enhanced_pipeline pipeline T5Transformer from hawalurahman
+author: John Snow Labs
+name: mt5_small_qa_v2_enhanced_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_small_qa_v2_enhanced_pipeline` is a English model originally trained by hawalurahman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_small_qa_v2_enhanced_pipeline_en_5.5.1_3.0_1737999705948.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_small_qa_v2_enhanced_pipeline_en_5.5.1_3.0_1737999705948.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mt5_small_qa_v2_enhanced_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mt5_small_qa_v2_enhanced_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_small_qa_v2_enhanced_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/hawalurahman/mt5-small-qa_v2_enhanced
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-multi_ner_final_en.md b/docs/_posts/ahmedlone127/2025-01-27-multi_ner_final_en.md
new file mode 100644
index 00000000000000..861ff75cd89cfb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-multi_ner_final_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English multi_ner_final BertForTokenClassification from tahirmuhammadcs
+author: John Snow Labs
+name: multi_ner_final
+date: 2025-01-27
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multi_ner_final` is a English model originally trained by tahirmuhammadcs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multi_ner_final_en_5.5.1_3.0_1738017300019.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multi_ner_final_en_5.5.1_3.0_1738017300019.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("multi_ner_final","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("multi_ner_final", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|multi_ner_final|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/tahirmuhammadcs/multi-ner-final
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-multi_ner_final_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-multi_ner_final_pipeline_en.md
new file mode 100644
index 00000000000000..6b983d0761340e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-multi_ner_final_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English multi_ner_final_pipeline pipeline BertForTokenClassification from tahirmuhammadcs
+author: John Snow Labs
+name: multi_ner_final_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multi_ner_final_pipeline` is a English model originally trained by tahirmuhammadcs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multi_ner_final_pipeline_en_5.5.1_3.0_1738017333293.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multi_ner_final_pipeline_en_5.5.1_3.0_1738017333293.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("multi_ner_final_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("multi_ner_final_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|multi_ner_final_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/tahirmuhammadcs/multi-ner-final
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-mymodel_flan_t5_las_en.md b/docs/_posts/ahmedlone127/2025-01-27-mymodel_flan_t5_las_en.md
new file mode 100644
index 00000000000000..bd0d8cd8eec408
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-mymodel_flan_t5_las_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mymodel_flan_t5_las T5Transformer from lukmanarifs
+author: John Snow Labs
+name: mymodel_flan_t5_las
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mymodel_flan_t5_las` is a English model originally trained by lukmanarifs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mymodel_flan_t5_las_en_5.5.1_3.0_1737945341876.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mymodel_flan_t5_las_en_5.5.1_3.0_1737945341876.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("mymodel_flan_t5_las","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("mymodel_flan_t5_las", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mymodel_flan_t5_las|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/lukmanarifs/mymodel-flan-t5-las
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-mymodel_flan_t5_las_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-mymodel_flan_t5_las_pipeline_en.md
new file mode 100644
index 00000000000000..952f14a7e713c9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-mymodel_flan_t5_las_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mymodel_flan_t5_las_pipeline pipeline T5Transformer from lukmanarifs
+author: John Snow Labs
+name: mymodel_flan_t5_las_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mymodel_flan_t5_las_pipeline` is a English model originally trained by lukmanarifs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mymodel_flan_t5_las_pipeline_en_5.5.1_3.0_1737945394320.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mymodel_flan_t5_las_pipeline_en_5.5.1_3.0_1737945394320.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mymodel_flan_t5_las_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mymodel_flan_t5_las_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mymodel_flan_t5_las_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/lukmanarifs/mymodel-flan-t5-las
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-mythology_t5_en.md b/docs/_posts/ahmedlone127/2025-01-27-mythology_t5_en.md
new file mode 100644
index 00000000000000..932248ecd0d8dd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-mythology_t5_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mythology_t5 T5Transformer from Sasza
+author: John Snow Labs
+name: mythology_t5
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mythology_t5` is a English model originally trained by Sasza.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mythology_t5_en_5.5.1_3.0_1738009016469.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mythology_t5_en_5.5.1_3.0_1738009016469.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("mythology_t5","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("mythology_t5", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mythology_t5|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|3.1 GB|
+
+## References
+
+https://huggingface.co/Sasza/mythology-t5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-mythology_t5_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-mythology_t5_pipeline_en.md
new file mode 100644
index 00000000000000..9cb3ad35c18dcc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-mythology_t5_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mythology_t5_pipeline pipeline T5Transformer from Sasza
+author: John Snow Labs
+name: mythology_t5_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mythology_t5_pipeline` is a English model originally trained by Sasza.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mythology_t5_pipeline_en_5.5.1_3.0_1738009170936.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mythology_t5_pipeline_en_5.5.1_3.0_1738009170936.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mythology_t5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mythology_t5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mythology_t5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|3.1 GB|
+
+## References
+
+https://huggingface.co/Sasza/mythology-t5
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-ner_test_bert_base_uncased_finetuned_500k_adamw_1_epoch_en.md b/docs/_posts/ahmedlone127/2025-01-27-ner_test_bert_base_uncased_finetuned_500k_adamw_1_epoch_en.md
new file mode 100644
index 00000000000000..2f58049991a1c5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-ner_test_bert_base_uncased_finetuned_500k_adamw_1_epoch_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ner_test_bert_base_uncased_finetuned_500k_adamw_1_epoch BertForTokenClassification from adambuttrick
+author: John Snow Labs
+name: ner_test_bert_base_uncased_finetuned_500k_adamw_1_epoch
+date: 2025-01-27
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_test_bert_base_uncased_finetuned_500k_adamw_1_epoch` is a English model originally trained by adambuttrick.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_test_bert_base_uncased_finetuned_500k_adamw_1_epoch_en_5.5.1_3.0_1738018074483.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_test_bert_base_uncased_finetuned_500k_adamw_1_epoch_en_5.5.1_3.0_1738018074483.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("ner_test_bert_base_uncased_finetuned_500k_adamw_1_epoch","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("ner_test_bert_base_uncased_finetuned_500k_adamw_1_epoch", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_test_bert_base_uncased_finetuned_500k_adamw_1_epoch|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/adambuttrick/ner-test-bert-base-uncased-finetuned-500K-AdamW-1-epoch
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-ner_test_bert_base_uncased_finetuned_500k_adamw_1_epoch_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-ner_test_bert_base_uncased_finetuned_500k_adamw_1_epoch_pipeline_en.md
new file mode 100644
index 00000000000000..fd24b2a4d83d98
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-ner_test_bert_base_uncased_finetuned_500k_adamw_1_epoch_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ner_test_bert_base_uncased_finetuned_500k_adamw_1_epoch_pipeline pipeline BertForTokenClassification from adambuttrick
+author: John Snow Labs
+name: ner_test_bert_base_uncased_finetuned_500k_adamw_1_epoch_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_test_bert_base_uncased_finetuned_500k_adamw_1_epoch_pipeline` is a English model originally trained by adambuttrick.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_test_bert_base_uncased_finetuned_500k_adamw_1_epoch_pipeline_en_5.5.1_3.0_1738018094736.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_test_bert_base_uncased_finetuned_500k_adamw_1_epoch_pipeline_en_5.5.1_3.0_1738018094736.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ner_test_bert_base_uncased_finetuned_500k_adamw_1_epoch_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ner_test_bert_base_uncased_finetuned_500k_adamw_1_epoch_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_test_bert_base_uncased_finetuned_500k_adamw_1_epoch_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/adambuttrick/ner-test-bert-base-uncased-finetuned-500K-AdamW-1-epoch
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-neuracraft_en.md b/docs/_posts/ahmedlone127/2025-01-27-neuracraft_en.md
new file mode 100644
index 00000000000000..4928bdb60974b1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-neuracraft_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English neuracraft T5Transformer from Erfan11
+author: John Snow Labs
+name: neuracraft
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`neuracraft` is a English model originally trained by Erfan11.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/neuracraft_en_5.5.1_3.0_1737945881663.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/neuracraft_en_5.5.1_3.0_1737945881663.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("neuracraft","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("neuracraft", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|neuracraft|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|148.0 MB|
+
+## References
+
+https://huggingface.co/Erfan11/Neuracraft
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-neuracraft_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-neuracraft_pipeline_en.md
new file mode 100644
index 00000000000000..63e6767b0b8d2a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-neuracraft_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English neuracraft_pipeline pipeline T5Transformer from Erfan11
+author: John Snow Labs
+name: neuracraft_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`neuracraft_pipeline` is a English model originally trained by Erfan11.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/neuracraft_pipeline_en_5.5.1_3.0_1737945932063.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/neuracraft_pipeline_en_5.5.1_3.0_1737945932063.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("neuracraft_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("neuracraft_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|neuracraft_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|148.0 MB|
+
+## References
+
+https://huggingface.co/Erfan11/Neuracraft
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-neurips_distilbert_climate_change_1_en.md b/docs/_posts/ahmedlone127/2025-01-27-neurips_distilbert_climate_change_1_en.md
new file mode 100644
index 00000000000000..f92796f66f80b2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-neurips_distilbert_climate_change_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English neurips_distilbert_climate_change_1 DistilBertForSequenceClassification from neurips-user
+author: John Snow Labs
+name: neurips_distilbert_climate_change_1
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`neurips_distilbert_climate_change_1` is a English model originally trained by neurips-user.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/neurips_distilbert_climate_change_1_en_5.5.1_3.0_1737939572935.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/neurips_distilbert_climate_change_1_en_5.5.1_3.0_1737939572935.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("neurips_distilbert_climate_change_1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("neurips_distilbert_climate_change_1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|neurips_distilbert_climate_change_1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/neurips-user/neurips-distilbert-climate-change-1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-neurips_distilbert_climate_change_1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-neurips_distilbert_climate_change_1_pipeline_en.md
new file mode 100644
index 00000000000000..5ab66002f213ae
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-neurips_distilbert_climate_change_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English neurips_distilbert_climate_change_1_pipeline pipeline DistilBertForSequenceClassification from neurips-user
+author: John Snow Labs
+name: neurips_distilbert_climate_change_1_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`neurips_distilbert_climate_change_1_pipeline` is a English model originally trained by neurips-user.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/neurips_distilbert_climate_change_1_pipeline_en_5.5.1_3.0_1737939587324.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/neurips_distilbert_climate_change_1_pipeline_en_5.5.1_3.0_1737939587324.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("neurips_distilbert_climate_change_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("neurips_distilbert_climate_change_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|neurips_distilbert_climate_change_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/neurips-user/neurips-distilbert-climate-change-1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-nlp_hw5_postaggermodel_en.md b/docs/_posts/ahmedlone127/2025-01-27-nlp_hw5_postaggermodel_en.md
new file mode 100644
index 00000000000000..72f100b1518ff7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-nlp_hw5_postaggermodel_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English nlp_hw5_postaggermodel BertForTokenClassification from Pedrampd
+author: John Snow Labs
+name: nlp_hw5_postaggermodel
+date: 2025-01-27
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nlp_hw5_postaggermodel` is a English model originally trained by Pedrampd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nlp_hw5_postaggermodel_en_5.5.1_3.0_1738017122740.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nlp_hw5_postaggermodel_en_5.5.1_3.0_1738017122740.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("nlp_hw5_postaggermodel","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("nlp_hw5_postaggermodel", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nlp_hw5_postaggermodel|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|407.3 MB|
+
+## References
+
+https://huggingface.co/Pedrampd/NLP-HW5-PosTaggerModel
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-nlp_hw5_postaggermodel_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-nlp_hw5_postaggermodel_pipeline_en.md
new file mode 100644
index 00000000000000..295323a17cfde9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-nlp_hw5_postaggermodel_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English nlp_hw5_postaggermodel_pipeline pipeline BertForTokenClassification from Pedrampd
+author: John Snow Labs
+name: nlp_hw5_postaggermodel_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nlp_hw5_postaggermodel_pipeline` is a English model originally trained by Pedrampd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nlp_hw5_postaggermodel_pipeline_en_5.5.1_3.0_1738017143480.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nlp_hw5_postaggermodel_pipeline_en_5.5.1_3.0_1738017143480.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("nlp_hw5_postaggermodel_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("nlp_hw5_postaggermodel_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nlp_hw5_postaggermodel_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.3 MB|
+
+## References
+
+https://huggingface.co/Pedrampd/NLP-HW5-PosTaggerModel
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-nsfw_classifier_en.md b/docs/_posts/ahmedlone127/2025-01-27-nsfw_classifier_en.md
new file mode 100644
index 00000000000000..bb6d10e32c9c5e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-nsfw_classifier_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English nsfw_classifier ViTForImageClassification from giacomoarienti
+author: John Snow Labs
+name: nsfw_classifier
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nsfw_classifier` is a English model originally trained by giacomoarienti.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nsfw_classifier_en_5.5.1_3.0_1738021358735.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nsfw_classifier_en_5.5.1_3.0_1738021358735.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""nsfw_classifier","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("nsfw_classifier","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nsfw_classifier|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/giacomoarienti/nsfw-classifier
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-nsfw_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-nsfw_classifier_pipeline_en.md
new file mode 100644
index 00000000000000..3ca180fd809b51
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-nsfw_classifier_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English nsfw_classifier_pipeline pipeline ViTForImageClassification from giacomoarienti
+author: John Snow Labs
+name: nsfw_classifier_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nsfw_classifier_pipeline` is a English model originally trained by giacomoarienti.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nsfw_classifier_pipeline_en_5.5.1_3.0_1738021374348.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nsfw_classifier_pipeline_en_5.5.1_3.0_1738021374348.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("nsfw_classifier_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("nsfw_classifier_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nsfw_classifier_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/giacomoarienti/nsfw-classifier
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-nsfw_image_detector_en.md b/docs/_posts/ahmedlone127/2025-01-27-nsfw_image_detector_en.md
new file mode 100644
index 00000000000000..7ef53205bc5643
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-nsfw_image_detector_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English nsfw_image_detector ViTForImageClassification from LukeJacob2023
+author: John Snow Labs
+name: nsfw_image_detector
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nsfw_image_detector` is a English model originally trained by LukeJacob2023.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nsfw_image_detector_en_5.5.1_3.0_1737957088757.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nsfw_image_detector_en_5.5.1_3.0_1737957088757.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""nsfw_image_detector","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("nsfw_image_detector","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nsfw_image_detector|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/LukeJacob2023/nsfw-image-detector
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-nsfw_image_detector_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-nsfw_image_detector_pipeline_en.md
new file mode 100644
index 00000000000000..df49f64bce3ece
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-nsfw_image_detector_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English nsfw_image_detector_pipeline pipeline ViTForImageClassification from LukeJacob2023
+author: John Snow Labs
+name: nsfw_image_detector_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nsfw_image_detector_pipeline` is a English model originally trained by LukeJacob2023.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nsfw_image_detector_pipeline_en_5.5.1_3.0_1737957106585.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nsfw_image_detector_pipeline_en_5.5.1_3.0_1737957106585.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("nsfw_image_detector_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("nsfw_image_detector_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nsfw_image_detector_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/LukeJacob2023/nsfw-image-detector
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-ocronos_vintage_en.md b/docs/_posts/ahmedlone127/2025-01-27-ocronos_vintage_en.md
new file mode 100644
index 00000000000000..044b5bc83cbcca
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-ocronos_vintage_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English ocronos_vintage GPT2Transformer from PleIAs
+author: John Snow Labs
+name: ocronos_vintage
+date: 2025-01-27
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ocronos_vintage` is a English model originally trained by PleIAs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ocronos_vintage_en_5.5.1_3.0_1737996576478.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ocronos_vintage_en_5.5.1_3.0_1737996576478.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("ocronos_vintage","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("ocronos_vintage","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ocronos_vintage|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|238.7 MB|
+
+## References
+
+https://huggingface.co/PleIAs/OCRonos-Vintage
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-ocronos_vintage_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-ocronos_vintage_pipeline_en.md
new file mode 100644
index 00000000000000..8d18e49354d469
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-ocronos_vintage_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English ocronos_vintage_pipeline pipeline GPT2Transformer from PleIAs
+author: John Snow Labs
+name: ocronos_vintage_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ocronos_vintage_pipeline` is a English model originally trained by PleIAs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ocronos_vintage_pipeline_en_5.5.1_3.0_1737996658404.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ocronos_vintage_pipeline_en_5.5.1_3.0_1737996658404.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ocronos_vintage_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ocronos_vintage_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ocronos_vintage_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|238.7 MB|
+
+## References
+
+https://huggingface.co/PleIAs/OCRonos-Vintage
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-odiaberta_large_en.md b/docs/_posts/ahmedlone127/2025-01-27-odiaberta_large_en.md
new file mode 100644
index 00000000000000..6a112a1157a687
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-odiaberta_large_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English odiaberta_large RoBertaEmbeddings from Nikhil7280
+author: John Snow Labs
+name: odiaberta_large
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`odiaberta_large` is a English model originally trained by Nikhil7280.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/odiaberta_large_en_5.5.1_3.0_1737966066804.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/odiaberta_large_en_5.5.1_3.0_1737966066804.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("odiaberta_large","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("odiaberta_large","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|odiaberta_large|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|470.7 MB|
+
+## References
+
+https://huggingface.co/Nikhil7280/OdiaBERTa-large
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-odiaberta_large_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-odiaberta_large_pipeline_en.md
new file mode 100644
index 00000000000000..70e81ae50bf649
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-odiaberta_large_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English odiaberta_large_pipeline pipeline RoBertaEmbeddings from Nikhil7280
+author: John Snow Labs
+name: odiaberta_large_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`odiaberta_large_pipeline` is a English model originally trained by Nikhil7280.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/odiaberta_large_pipeline_en_5.5.1_3.0_1737966091330.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/odiaberta_large_pipeline_en_5.5.1_3.0_1737966091330.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("odiaberta_large_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("odiaberta_large_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|odiaberta_large_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|470.7 MB|
+
+## References
+
+https://huggingface.co/Nikhil7280/OdiaBERTa-large
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-opus_big_enfr_ft_en.md b/docs/_posts/ahmedlone127/2025-01-27-opus_big_enfr_ft_en.md
new file mode 100644
index 00000000000000..839fc9c30709fe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-opus_big_enfr_ft_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_big_enfr_ft MarianTransformer from ethansimrm
+author: John Snow Labs
+name: opus_big_enfr_ft
+date: 2025-01-27
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_big_enfr_ft` is a English model originally trained by ethansimrm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_big_enfr_ft_en_5.5.1_3.0_1737937462137.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_big_enfr_ft_en_5.5.1_3.0_1737937462137.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_big_enfr_ft","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_big_enfr_ft","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_big_enfr_ft|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/ethansimrm/opus_big_enfr_FT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-opus_big_enfr_ft_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-opus_big_enfr_ft_pipeline_en.md
new file mode 100644
index 00000000000000..d284aefc2631cf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-opus_big_enfr_ft_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_big_enfr_ft_pipeline pipeline MarianTransformer from ethansimrm
+author: John Snow Labs
+name: opus_big_enfr_ft_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_big_enfr_ft_pipeline` is a English model originally trained by ethansimrm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_big_enfr_ft_pipeline_en_5.5.1_3.0_1737937516937.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_big_enfr_ft_pipeline_en_5.5.1_3.0_1737937516937.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("opus_big_enfr_ft_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_big_enfr_ft_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_big_enfr_ft_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/ethansimrm/opus_big_enfr_FT
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-opus_model_en.md b/docs/_posts/ahmedlone127/2025-01-27-opus_model_en.md
new file mode 100644
index 00000000000000..18961c3ae7a9ea
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-opus_model_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English opus_model T5Transformer from FrancisYang77
+author: John Snow Labs
+name: opus_model
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_model` is a English model originally trained by FrancisYang77.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_model_en_5.5.1_3.0_1738000828028.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_model_en_5.5.1_3.0_1738000828028.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("opus_model","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("opus_model", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|286.7 MB|
+
+## References
+
+https://huggingface.co/FrancisYang77/opus_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-opus_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-opus_model_pipeline_en.md
new file mode 100644
index 00000000000000..e71d0287800c0f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-opus_model_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English opus_model_pipeline pipeline T5Transformer from FrancisYang77
+author: John Snow Labs
+name: opus_model_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_model_pipeline` is a English model originally trained by FrancisYang77.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opus_model_pipeline_en_5.5.1_3.0_1738000843427.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_model_pipeline_en_5.5.1_3.0_1738000843427.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("opus_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|286.7 MB|
+
+## References
+
+https://huggingface.co/FrancisYang77/opus_model
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-oxford_flowers_image_detection_en.md b/docs/_posts/ahmedlone127/2025-01-27-oxford_flowers_image_detection_en.md
new file mode 100644
index 00000000000000..b755e6f819b2da
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-oxford_flowers_image_detection_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English oxford_flowers_image_detection ViTForImageClassification from dima806
+author: John Snow Labs
+name: oxford_flowers_image_detection
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`oxford_flowers_image_detection` is a English model originally trained by dima806.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/oxford_flowers_image_detection_en_5.5.1_3.0_1738021547365.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/oxford_flowers_image_detection_en_5.5.1_3.0_1738021547365.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""oxford_flowers_image_detection","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("oxford_flowers_image_detection","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|oxford_flowers_image_detection|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.6 MB|
+
+## References
+
+https://huggingface.co/dima806/oxford_flowers_image_detection
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-oxford_flowers_image_detection_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-oxford_flowers_image_detection_pipeline_en.md
new file mode 100644
index 00000000000000..9eedd375c71e7c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-oxford_flowers_image_detection_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English oxford_flowers_image_detection_pipeline pipeline ViTForImageClassification from dima806
+author: John Snow Labs
+name: oxford_flowers_image_detection_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`oxford_flowers_image_detection_pipeline` is a English model originally trained by dima806.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/oxford_flowers_image_detection_pipeline_en_5.5.1_3.0_1738021564256.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/oxford_flowers_image_detection_pipeline_en_5.5.1_3.0_1738021564256.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("oxford_flowers_image_detection_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("oxford_flowers_image_detection_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|oxford_flowers_image_detection_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.6 MB|
+
+## References
+
+https://huggingface.co/dima806/oxford_flowers_image_detection
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-planes_trains_automobiles_en.md b/docs/_posts/ahmedlone127/2025-01-27-planes_trains_automobiles_en.md
new file mode 100644
index 00000000000000..465b98e37d3138
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-planes_trains_automobiles_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English planes_trains_automobiles ViTForImageClassification from nateraw
+author: John Snow Labs
+name: planes_trains_automobiles
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`planes_trains_automobiles` is a English model originally trained by nateraw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/planes_trains_automobiles_en_5.5.1_3.0_1738021019952.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/planes_trains_automobiles_en_5.5.1_3.0_1738021019952.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""planes_trains_automobiles","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("planes_trains_automobiles","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|planes_trains_automobiles|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/nateraw/planes-trains-automobiles
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-planes_trains_automobiles_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-planes_trains_automobiles_pipeline_en.md
new file mode 100644
index 00000000000000..1085f2eece1d80
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-planes_trains_automobiles_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English planes_trains_automobiles_pipeline pipeline ViTForImageClassification from nateraw
+author: John Snow Labs
+name: planes_trains_automobiles_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`planes_trains_automobiles_pipeline` is a English model originally trained by nateraw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/planes_trains_automobiles_pipeline_en_5.5.1_3.0_1738021036892.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/planes_trains_automobiles_pipeline_en_5.5.1_3.0_1738021036892.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("planes_trains_automobiles_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("planes_trains_automobiles_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|planes_trains_automobiles_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/nateraw/planes-trains-automobiles
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-practice_t5_model_en.md b/docs/_posts/ahmedlone127/2025-01-27-practice_t5_model_en.md
new file mode 100644
index 00000000000000..3b4c9452457f98
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-practice_t5_model_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English practice_t5_model T5Transformer from Shreshth16
+author: John Snow Labs
+name: practice_t5_model
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`practice_t5_model` is a English model originally trained by Shreshth16.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/practice_t5_model_en_5.5.1_3.0_1737999728501.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/practice_t5_model_en_5.5.1_3.0_1737999728501.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("practice_t5_model","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("practice_t5_model", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|practice_t5_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|863.4 MB|
+
+## References
+
+https://huggingface.co/Shreshth16/Practice_T5_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-practice_t5_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-practice_t5_model_pipeline_en.md
new file mode 100644
index 00000000000000..fb68735f44c70b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-practice_t5_model_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English practice_t5_model_pipeline pipeline T5Transformer from Shreshth16
+author: John Snow Labs
+name: practice_t5_model_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`practice_t5_model_pipeline` is a English model originally trained by Shreshth16.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/practice_t5_model_pipeline_en_5.5.1_3.0_1737999796815.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/practice_t5_model_pipeline_en_5.5.1_3.0_1737999796815.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("practice_t5_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("practice_t5_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|practice_t5_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|863.4 MB|
+
+## References
+
+https://huggingface.co/Shreshth16/Practice_T5_model
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-predict_fine_tuned_en.md b/docs/_posts/ahmedlone127/2025-01-27-predict_fine_tuned_en.md
new file mode 100644
index 00000000000000..634b0a49a3788c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-predict_fine_tuned_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English predict_fine_tuned T5Transformer from kelzo
+author: John Snow Labs
+name: predict_fine_tuned
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`predict_fine_tuned` is a English model originally trained by kelzo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/predict_fine_tuned_en_5.5.1_3.0_1737962559496.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/predict_fine_tuned_en_5.5.1_3.0_1737962559496.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("predict_fine_tuned","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("predict_fine_tuned", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|predict_fine_tuned|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|148.0 MB|
+
+## References
+
+https://huggingface.co/kelzo/Predict-fine-tuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-predict_fine_tuned_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-predict_fine_tuned_pipeline_en.md
new file mode 100644
index 00000000000000..aa1d9a59bce2ac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-predict_fine_tuned_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English predict_fine_tuned_pipeline pipeline T5Transformer from kelzo
+author: John Snow Labs
+name: predict_fine_tuned_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`predict_fine_tuned_pipeline` is a English model originally trained by kelzo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/predict_fine_tuned_pipeline_en_5.5.1_3.0_1737962606950.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/predict_fine_tuned_pipeline_en_5.5.1_3.0_1737962606950.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("predict_fine_tuned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("predict_fine_tuned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|predict_fine_tuned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|148.0 MB|
+
+## References
+
+https://huggingface.co/kelzo/Predict-fine-tuned
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-problema_topicos_en.md b/docs/_posts/ahmedlone127/2025-01-27-problema_topicos_en.md
new file mode 100644
index 00000000000000..20de773104c008
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-problema_topicos_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English problema_topicos BertEmbeddings from germanchura
+author: John Snow Labs
+name: problema_topicos
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`problema_topicos` is a English model originally trained by germanchura.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/problema_topicos_en_5.5.1_3.0_1737985483888.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/problema_topicos_en_5.5.1_3.0_1737985483888.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("problema_topicos","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("problema_topicos","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|problema_topicos|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/germanchura/problema_topicos
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-problema_topicos_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-problema_topicos_pipeline_en.md
new file mode 100644
index 00000000000000..d6f247cc597658
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-problema_topicos_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English problema_topicos_pipeline pipeline BertEmbeddings from germanchura
+author: John Snow Labs
+name: problema_topicos_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`problema_topicos_pipeline` is a English model originally trained by germanchura.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/problema_topicos_pipeline_en_5.5.1_3.0_1737985508054.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/problema_topicos_pipeline_en_5.5.1_3.0_1737985508054.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("problema_topicos_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("problema_topicos_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|problema_topicos_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/germanchura/problema_topicos
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-product_title_encoder_product_en.md b/docs/_posts/ahmedlone127/2025-01-27-product_title_encoder_product_en.md
new file mode 100644
index 00000000000000..fef8ff85041698
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-product_title_encoder_product_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English product_title_encoder_product BertEmbeddings from kwakwak
+author: John Snow Labs
+name: product_title_encoder_product
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`product_title_encoder_product` is a English model originally trained by kwakwak.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/product_title_encoder_product_en_5.5.1_3.0_1737953674672.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/product_title_encoder_product_en_5.5.1_3.0_1737953674672.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("product_title_encoder_product","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("product_title_encoder_product","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|product_title_encoder_product|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|84.6 MB|
+
+## References
+
+https://huggingface.co/kwakwak/product_title_encoder-product
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-product_title_encoder_product_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-product_title_encoder_product_pipeline_en.md
new file mode 100644
index 00000000000000..61dddb72b1faa9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-product_title_encoder_product_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English product_title_encoder_product_pipeline pipeline BertEmbeddings from kwakwak
+author: John Snow Labs
+name: product_title_encoder_product_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`product_title_encoder_product_pipeline` is a English model originally trained by kwakwak.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/product_title_encoder_product_pipeline_en_5.5.1_3.0_1737953678881.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/product_title_encoder_product_pipeline_en_5.5.1_3.0_1737953678881.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("product_title_encoder_product_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("product_title_encoder_product_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|product_title_encoder_product_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|84.7 MB|
+
+## References
+
+https://huggingface.co/kwakwak/product_title_encoder-product
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-qsaf_propositional_en.md b/docs/_posts/ahmedlone127/2025-01-27-qsaf_propositional_en.md
new file mode 100644
index 00000000000000..7318efac349663
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-qsaf_propositional_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English qsaf_propositional T5Transformer from ryusangwon
+author: John Snow Labs
+name: qsaf_propositional
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qsaf_propositional` is a English model originally trained by ryusangwon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qsaf_propositional_en_5.5.1_3.0_1737945759037.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qsaf_propositional_en_5.5.1_3.0_1737945759037.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("qsaf_propositional","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("qsaf_propositional", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qsaf_propositional|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|3.1 GB|
+
+## References
+
+https://huggingface.co/ryusangwon/qsaf_propositional
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-qsaf_propositional_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-qsaf_propositional_pipeline_en.md
new file mode 100644
index 00000000000000..21dc0b193c5546
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-qsaf_propositional_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English qsaf_propositional_pipeline pipeline T5Transformer from ryusangwon
+author: John Snow Labs
+name: qsaf_propositional_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qsaf_propositional_pipeline` is a English model originally trained by ryusangwon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qsaf_propositional_pipeline_en_5.5.1_3.0_1737945917561.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qsaf_propositional_pipeline_en_5.5.1_3.0_1737945917561.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("qsaf_propositional_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("qsaf_propositional_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qsaf_propositional_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|3.1 GB|
+
+## References
+
+https://huggingface.co/ryusangwon/qsaf_propositional
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-query_answer_distilbert_base_uncased_en.md b/docs/_posts/ahmedlone127/2025-01-27-query_answer_distilbert_base_uncased_en.md
new file mode 100644
index 00000000000000..20aa65c0ed97c8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-query_answer_distilbert_base_uncased_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English query_answer_distilbert_base_uncased DistilBertForQuestionAnswering from strainer-k
+author: John Snow Labs
+name: query_answer_distilbert_base_uncased
+date: 2025-01-27
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`query_answer_distilbert_base_uncased` is a English model originally trained by strainer-k.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/query_answer_distilbert_base_uncased_en_5.5.1_3.0_1737973813832.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/query_answer_distilbert_base_uncased_en_5.5.1_3.0_1737973813832.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("query_answer_distilbert_base_uncased","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("query_answer_distilbert_base_uncased", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|query_answer_distilbert_base_uncased|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/strainer-k/query_answer_distilbert-base-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-query_answer_distilbert_base_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-query_answer_distilbert_base_uncased_pipeline_en.md
new file mode 100644
index 00000000000000..4b9236ba9820b0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-query_answer_distilbert_base_uncased_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English query_answer_distilbert_base_uncased_pipeline pipeline DistilBertForQuestionAnswering from strainer-k
+author: John Snow Labs
+name: query_answer_distilbert_base_uncased_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`query_answer_distilbert_base_uncased_pipeline` is a English model originally trained by strainer-k.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/query_answer_distilbert_base_uncased_pipeline_en_5.5.1_3.0_1737973835016.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/query_answer_distilbert_base_uncased_pipeline_en_5.5.1_3.0_1737973835016.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("query_answer_distilbert_base_uncased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("query_answer_distilbert_base_uncased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|query_answer_distilbert_base_uncased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/strainer-k/query_answer_distilbert-base-uncased
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-question_model_en.md b/docs/_posts/ahmedlone127/2025-01-27-question_model_en.md
new file mode 100644
index 00000000000000..0bb75e0c080335
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-question_model_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English question_model T5Transformer from kikaigakushuu
+author: John Snow Labs
+name: question_model
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`question_model` is a English model originally trained by kikaigakushuu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/question_model_en_5.5.1_3.0_1738001958778.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/question_model_en_5.5.1_3.0_1738001958778.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("question_model","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("question_model", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|question_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/kikaigakushuu/Question_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-question_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-question_model_pipeline_en.md
new file mode 100644
index 00000000000000..e8167062153ac5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-question_model_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English question_model_pipeline pipeline T5Transformer from kikaigakushuu
+author: John Snow Labs
+name: question_model_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`question_model_pipeline` is a English model originally trained by kikaigakushuu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/question_model_pipeline_en_5.5.1_3.0_1738002012776.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/question_model_pipeline_en_5.5.1_3.0_1738002012776.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("question_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("question_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|question_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/kikaigakushuu/Question_model
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-regression_xlm_roberta_divemt_en.md b/docs/_posts/ahmedlone127/2025-01-27-regression_xlm_roberta_divemt_en.md
new file mode 100644
index 00000000000000..af6370dad4356e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-regression_xlm_roberta_divemt_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English regression_xlm_roberta_divemt XlmRoBertaForSequenceClassification from iknlpt3
+author: John Snow Labs
+name: regression_xlm_roberta_divemt
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`regression_xlm_roberta_divemt` is a English model originally trained by iknlpt3.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/regression_xlm_roberta_divemt_en_5.5.1_3.0_1737960527157.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/regression_xlm_roberta_divemt_en_5.5.1_3.0_1737960527157.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("regression_xlm_roberta_divemt","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("regression_xlm_roberta_divemt", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|regression_xlm_roberta_divemt|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|804.9 MB|
+
+## References
+
+https://huggingface.co/iknlpt3/regression_xlm_roberta_divemt
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-regression_xlm_roberta_divemt_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-regression_xlm_roberta_divemt_pipeline_en.md
new file mode 100644
index 00000000000000..4a50d15fb5f766
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-regression_xlm_roberta_divemt_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English regression_xlm_roberta_divemt_pipeline pipeline XlmRoBertaForSequenceClassification from iknlpt3
+author: John Snow Labs
+name: regression_xlm_roberta_divemt_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`regression_xlm_roberta_divemt_pipeline` is a English model originally trained by iknlpt3.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/regression_xlm_roberta_divemt_pipeline_en_5.5.1_3.0_1737960663954.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/regression_xlm_roberta_divemt_pipeline_en_5.5.1_3.0_1737960663954.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("regression_xlm_roberta_divemt_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("regression_xlm_roberta_divemt_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|regression_xlm_roberta_divemt_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|805.0 MB|
+
+## References
+
+https://huggingface.co/iknlpt3/regression_xlm_roberta_divemt
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-resultadoss2_en.md b/docs/_posts/ahmedlone127/2025-01-27-resultadoss2_en.md
new file mode 100644
index 00000000000000..f127cd3933bf2f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-resultadoss2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English resultadoss2 DistilBertForSequenceClassification from jmdrst
+author: John Snow Labs
+name: resultadoss2
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`resultadoss2` is a English model originally trained by jmdrst.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/resultadoss2_en_5.5.1_3.0_1737939345324.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/resultadoss2_en_5.5.1_3.0_1737939345324.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("resultadoss2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("resultadoss2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|resultadoss2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/jmdrst/resultadoss2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-resultadoss2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-resultadoss2_pipeline_en.md
new file mode 100644
index 00000000000000..ac2ac90ec5334d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-resultadoss2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English resultadoss2_pipeline pipeline DistilBertForSequenceClassification from jmdrst
+author: John Snow Labs
+name: resultadoss2_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`resultadoss2_pipeline` is a English model originally trained by jmdrst.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/resultadoss2_pipeline_en_5.5.1_3.0_1737939361395.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/resultadoss2_pipeline_en_5.5.1_3.0_1737939361395.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("resultadoss2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("resultadoss2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|resultadoss2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/jmdrst/resultadoss2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-results_elpeeee_en.md b/docs/_posts/ahmedlone127/2025-01-27-results_elpeeee_en.md
new file mode 100644
index 00000000000000..aea6d540f91b0e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-results_elpeeee_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English results_elpeeee T5Transformer from elpeeee
+author: John Snow Labs
+name: results_elpeeee
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_elpeeee` is a English model originally trained by elpeeee.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_elpeeee_en_5.5.1_3.0_1737961953370.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_elpeeee_en_5.5.1_3.0_1737961953370.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("results_elpeeee","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("results_elpeeee", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_elpeeee|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|285.7 MB|
+
+## References
+
+https://huggingface.co/elpeeee/results
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-results_elpeeee_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-results_elpeeee_pipeline_en.md
new file mode 100644
index 00000000000000..d4a4b30a5c3a44
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-results_elpeeee_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English results_elpeeee_pipeline pipeline T5Transformer from elpeeee
+author: John Snow Labs
+name: results_elpeeee_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_elpeeee_pipeline` is a English model originally trained by elpeeee.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_elpeeee_pipeline_en_5.5.1_3.0_1737961968850.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_elpeeee_pipeline_en_5.5.1_3.0_1737961968850.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("results_elpeeee_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("results_elpeeee_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_elpeeee_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|285.7 MB|
+
+## References
+
+https://huggingface.co/elpeeee/results
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-results_en.md b/docs/_posts/ahmedlone127/2025-01-27-results_en.md
new file mode 100644
index 00000000000000..58480157db2d68
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-results_en.md
@@ -0,0 +1,98 @@
+---
+layout: model
+title: English results DistilBertForQuestionAnswering from Souvik123
+author: John Snow Labs
+name: results
+date: 2025-01-27
+tags: [distilbert, en, open_source, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results` is a English model originally trained by Souvik123.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_en_5.5.1_3.0_1737984249659.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_en_5.5.1_3.0_1737984249659.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = MultiDocumentAssembler() \
+    .setInputCol(["question", "context"]) \
+    .setOutputCol(["document_question", "document_context"])
+    
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("results","en") \
+            .setInputCols(["document_question","document_context"]) \
+            .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([document_assembler, spanClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val document_assembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering  
+    .pretrained("results", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|412.2 MB|
+
+## References
+
+References
+
+References
+
+References
+
+References
+
+https://huggingface.co/Souvik123/results
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-results_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-results_pipeline_en.md
new file mode 100644
index 00000000000000..8009b29e2ce459
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-results_pipeline_en.md
@@ -0,0 +1,74 @@
+---
+layout: model
+title: English results_pipeline pipeline RoBertaForTokenClassification from danielyoo
+author: John Snow Labs
+name: results_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_pipeline` is a English model originally trained by danielyoo.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_pipeline_en_5.5.1_3.0_1737984277078.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_pipeline_en_5.5.1_3.0_1737984277078.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("results_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("results_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|412.8 MB|
+
+## References
+
+References
+
+References
+
+https://huggingface.co/danielyoo/results
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-results_t5small_gptmore_en.md b/docs/_posts/ahmedlone127/2025-01-27-results_t5small_gptmore_en.md
new file mode 100644
index 00000000000000..666cd85aeb9c07
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-results_t5small_gptmore_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English results_t5small_gptmore T5Transformer from gptMore
+author: John Snow Labs
+name: results_t5small_gptmore
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_t5small_gptmore` is a English model originally trained by gptMore.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_t5small_gptmore_en_5.5.1_3.0_1737945412020.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_t5small_gptmore_en_5.5.1_3.0_1737945412020.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("results_t5small_gptmore","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("results_t5small_gptmore", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_t5small_gptmore|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|286.1 MB|
+
+## References
+
+https://huggingface.co/gptMore/results_t5small
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-results_t5small_gptmore_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-results_t5small_gptmore_pipeline_en.md
new file mode 100644
index 00000000000000..c6e335cd0c96d6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-results_t5small_gptmore_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English results_t5small_gptmore_pipeline pipeline T5Transformer from gptMore
+author: John Snow Labs
+name: results_t5small_gptmore_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_t5small_gptmore_pipeline` is a English model originally trained by gptMore.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_t5small_gptmore_pipeline_en_5.5.1_3.0_1737945427842.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_t5small_gptmore_pipeline_en_5.5.1_3.0_1737945427842.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("results_t5small_gptmore_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("results_t5small_gptmore_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_t5small_gptmore_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|286.1 MB|
+
+## References
+
+https://huggingface.co/gptMore/results_t5small
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-results_timosh_nlp_en.md b/docs/_posts/ahmedlone127/2025-01-27-results_timosh_nlp_en.md
new file mode 100644
index 00000000000000..5dba3e18c37aab
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-results_timosh_nlp_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English results_timosh_nlp T5Transformer from Timosh-nlp
+author: John Snow Labs
+name: results_timosh_nlp
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_timosh_nlp` is a English model originally trained by Timosh-nlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_timosh_nlp_en_5.5.1_3.0_1737961800917.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_timosh_nlp_en_5.5.1_3.0_1737961800917.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("results_timosh_nlp","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("results_timosh_nlp", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_timosh_nlp|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|270.2 MB|
+
+## References
+
+https://huggingface.co/Timosh-nlp/results
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-results_timosh_nlp_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-results_timosh_nlp_pipeline_en.md
new file mode 100644
index 00000000000000..9a5c202f26e9b7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-results_timosh_nlp_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English results_timosh_nlp_pipeline pipeline T5Transformer from Timosh-nlp
+author: John Snow Labs
+name: results_timosh_nlp_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_timosh_nlp_pipeline` is a English model originally trained by Timosh-nlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_timosh_nlp_pipeline_en_5.5.1_3.0_1737961818528.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_timosh_nlp_pipeline_en_5.5.1_3.0_1737961818528.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("results_timosh_nlp_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("results_timosh_nlp_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_timosh_nlp_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|270.2 MB|
+
+## References
+
+https://huggingface.co/Timosh-nlp/results
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-results_trmphuc_en.md b/docs/_posts/ahmedlone127/2025-01-27-results_trmphuc_en.md
new file mode 100644
index 00000000000000..a882ddef3666e4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-results_trmphuc_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English results_trmphuc T5Transformer from TrmPhuc
+author: John Snow Labs
+name: results_trmphuc
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_trmphuc` is a English model originally trained by TrmPhuc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_trmphuc_en_5.5.1_3.0_1737964271787.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_trmphuc_en_5.5.1_3.0_1737964271787.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("results_trmphuc","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("results_trmphuc", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_trmphuc|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|202.0 MB|
+
+## References
+
+https://huggingface.co/TrmPhuc/results
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-results_trmphuc_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-results_trmphuc_pipeline_en.md
new file mode 100644
index 00000000000000..a37b2bd351fbbe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-results_trmphuc_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English results_trmphuc_pipeline pipeline T5Transformer from TrmPhuc
+author: John Snow Labs
+name: results_trmphuc_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_trmphuc_pipeline` is a English model originally trained by TrmPhuc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_trmphuc_pipeline_en_5.5.1_3.0_1737964297693.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_trmphuc_pipeline_en_5.5.1_3.0_1737964297693.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("results_trmphuc_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("results_trmphuc_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_trmphuc_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|202.0 MB|
+
+## References
+
+https://huggingface.co/TrmPhuc/results
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-roberta_base_ainu_en.md b/docs/_posts/ahmedlone127/2025-01-27-roberta_base_ainu_en.md
new file mode 100644
index 00000000000000..008905828eca7b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-roberta_base_ainu_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_base_ainu RoBertaEmbeddings from aynumosir
+author: John Snow Labs
+name: roberta_base_ainu
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_ainu` is a English model originally trained by aynumosir.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_ainu_en_5.5.1_3.0_1737965475648.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_ainu_en_5.5.1_3.0_1737965475648.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("roberta_base_ainu","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("roberta_base_ainu","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_ainu|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|465.0 MB|
+
+## References
+
+https://huggingface.co/aynumosir/roberta-base-ainu
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-roberta_base_ainu_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-roberta_base_ainu_pipeline_en.md
new file mode 100644
index 00000000000000..a42757136cc44d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-roberta_base_ainu_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_base_ainu_pipeline pipeline RoBertaEmbeddings from aynumosir
+author: John Snow Labs
+name: roberta_base_ainu_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_ainu_pipeline` is a English model originally trained by aynumosir.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_ainu_pipeline_en_5.5.1_3.0_1737965499983.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_ainu_pipeline_en_5.5.1_3.0_1737965499983.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_base_ainu_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_ainu_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_ainu_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|465.0 MB|
+
+## References
+
+https://huggingface.co/aynumosir/roberta-base-ainu
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-roberta_base_biomedical_clinical_spanish_serdarcaglar_es.md b/docs/_posts/ahmedlone127/2025-01-27-roberta_base_biomedical_clinical_spanish_serdarcaglar_es.md
new file mode 100644
index 00000000000000..a608a93be0c5d1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-roberta_base_biomedical_clinical_spanish_serdarcaglar_es.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Castilian, Spanish roberta_base_biomedical_clinical_spanish_serdarcaglar RoBertaEmbeddings from serdarcaglar
+author: John Snow Labs
+name: roberta_base_biomedical_clinical_spanish_serdarcaglar
+date: 2025-01-27
+tags: [es, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: es
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_biomedical_clinical_spanish_serdarcaglar` is a Castilian, Spanish model originally trained by serdarcaglar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_biomedical_clinical_spanish_serdarcaglar_es_5.5.1_3.0_1737966085760.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_biomedical_clinical_spanish_serdarcaglar_es_5.5.1_3.0_1737966085760.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("roberta_base_biomedical_clinical_spanish_serdarcaglar","es") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("roberta_base_biomedical_clinical_spanish_serdarcaglar","es") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_biomedical_clinical_spanish_serdarcaglar|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|es|
+|Size:|469.7 MB|
+
+## References
+
+https://huggingface.co/serdarcaglar/roberta-base-biomedical-clinical-es
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-roberta_base_biomedical_clinical_spanish_serdarcaglar_pipeline_es.md b/docs/_posts/ahmedlone127/2025-01-27-roberta_base_biomedical_clinical_spanish_serdarcaglar_pipeline_es.md
new file mode 100644
index 00000000000000..6d2e18f6e5207f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-roberta_base_biomedical_clinical_spanish_serdarcaglar_pipeline_es.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Castilian, Spanish roberta_base_biomedical_clinical_spanish_serdarcaglar_pipeline pipeline RoBertaEmbeddings from serdarcaglar
+author: John Snow Labs
+name: roberta_base_biomedical_clinical_spanish_serdarcaglar_pipeline
+date: 2025-01-27
+tags: [es, open_source, pipeline, onnx]
+task: Embeddings
+language: es
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_biomedical_clinical_spanish_serdarcaglar_pipeline` is a Castilian, Spanish model originally trained by serdarcaglar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_biomedical_clinical_spanish_serdarcaglar_pipeline_es_5.5.1_3.0_1737966109837.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_biomedical_clinical_spanish_serdarcaglar_pipeline_es_5.5.1_3.0_1737966109837.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_base_biomedical_clinical_spanish_serdarcaglar_pipeline", lang = "es")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_biomedical_clinical_spanish_serdarcaglar_pipeline", lang = "es")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_biomedical_clinical_spanish_serdarcaglar_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|es|
+|Size:|469.7 MB|
+
+## References
+
+https://huggingface.co/serdarcaglar/roberta-base-biomedical-clinical-es
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-roberta_base_biomedical_spanish_serdarcaglar_es.md b/docs/_posts/ahmedlone127/2025-01-27-roberta_base_biomedical_spanish_serdarcaglar_es.md
new file mode 100644
index 00000000000000..65acbc27cc5aaf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-roberta_base_biomedical_spanish_serdarcaglar_es.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Castilian, Spanish roberta_base_biomedical_spanish_serdarcaglar RoBertaEmbeddings from serdarcaglar
+author: John Snow Labs
+name: roberta_base_biomedical_spanish_serdarcaglar
+date: 2025-01-27
+tags: [es, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: es
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_biomedical_spanish_serdarcaglar` is a Castilian, Spanish model originally trained by serdarcaglar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_biomedical_spanish_serdarcaglar_es_5.5.1_3.0_1738019535699.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_biomedical_spanish_serdarcaglar_es_5.5.1_3.0_1738019535699.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("roberta_base_biomedical_spanish_serdarcaglar","es") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("roberta_base_biomedical_spanish_serdarcaglar","es") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_biomedical_spanish_serdarcaglar|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|es|
+|Size:|469.6 MB|
+
+## References
+
+https://huggingface.co/serdarcaglar/roberta-base-biomedical-es
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-roberta_base_biomedical_spanish_serdarcaglar_pipeline_es.md b/docs/_posts/ahmedlone127/2025-01-27-roberta_base_biomedical_spanish_serdarcaglar_pipeline_es.md
new file mode 100644
index 00000000000000..5db565c6fff51d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-roberta_base_biomedical_spanish_serdarcaglar_pipeline_es.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Castilian, Spanish roberta_base_biomedical_spanish_serdarcaglar_pipeline pipeline RoBertaEmbeddings from serdarcaglar
+author: John Snow Labs
+name: roberta_base_biomedical_spanish_serdarcaglar_pipeline
+date: 2025-01-27
+tags: [es, open_source, pipeline, onnx]
+task: Embeddings
+language: es
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_biomedical_spanish_serdarcaglar_pipeline` is a Castilian, Spanish model originally trained by serdarcaglar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_biomedical_spanish_serdarcaglar_pipeline_es_5.5.1_3.0_1738019564415.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_biomedical_spanish_serdarcaglar_pipeline_es_5.5.1_3.0_1738019564415.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_base_biomedical_spanish_serdarcaglar_pipeline", lang = "es")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_biomedical_spanish_serdarcaglar_pipeline", lang = "es")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_biomedical_spanish_serdarcaglar_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|es|
+|Size:|469.7 MB|
+
+## References
+
+https://huggingface.co/serdarcaglar/roberta-base-biomedical-es
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-roberta_base_turkish_scientific_cased_pipeline_tr.md b/docs/_posts/ahmedlone127/2025-01-27-roberta_base_turkish_scientific_cased_pipeline_tr.md
new file mode 100644
index 00000000000000..4581b680ef5939
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-roberta_base_turkish_scientific_cased_pipeline_tr.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Turkish roberta_base_turkish_scientific_cased_pipeline pipeline RoBertaEmbeddings from serdarcaglar
+author: John Snow Labs
+name: roberta_base_turkish_scientific_cased_pipeline
+date: 2025-01-27
+tags: [tr, open_source, pipeline, onnx]
+task: Embeddings
+language: tr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_turkish_scientific_cased_pipeline` is a Turkish model originally trained by serdarcaglar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_turkish_scientific_cased_pipeline_tr_5.5.1_3.0_1738020027537.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_turkish_scientific_cased_pipeline_tr_5.5.1_3.0_1738020027537.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_base_turkish_scientific_cased_pipeline", lang = "tr")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_turkish_scientific_cased_pipeline", lang = "tr")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_turkish_scientific_cased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|tr|
+|Size:|311.3 MB|
+
+## References
+
+https://huggingface.co/serdarcaglar/roberta-base-turkish-scientific-cased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-roberta_base_turkish_scientific_cased_tr.md b/docs/_posts/ahmedlone127/2025-01-27-roberta_base_turkish_scientific_cased_tr.md
new file mode 100644
index 00000000000000..d3695bacd5c68b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-roberta_base_turkish_scientific_cased_tr.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Turkish roberta_base_turkish_scientific_cased RoBertaEmbeddings from serdarcaglar
+author: John Snow Labs
+name: roberta_base_turkish_scientific_cased
+date: 2025-01-27
+tags: [tr, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: tr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_turkish_scientific_cased` is a Turkish model originally trained by serdarcaglar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_turkish_scientific_cased_tr_5.5.1_3.0_1738020010828.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_turkish_scientific_cased_tr_5.5.1_3.0_1738020010828.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("roberta_base_turkish_scientific_cased","tr") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("roberta_base_turkish_scientific_cased","tr") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_turkish_scientific_cased|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|tr|
+|Size:|311.3 MB|
+
+## References
+
+https://huggingface.co/serdarcaglar/roberta-base-turkish-scientific-cased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-roberta_empai_final_en.md b/docs/_posts/ahmedlone127/2025-01-27-roberta_empai_final_en.md
new file mode 100644
index 00000000000000..9848919dfbde88
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-roberta_empai_final_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_empai_final RoBertaEmbeddings from LuangMV97
+author: John Snow Labs
+name: roberta_empai_final
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_empai_final` is a English model originally trained by LuangMV97.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_empai_final_en_5.5.1_3.0_1737966368573.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_empai_final_en_5.5.1_3.0_1737966368573.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("roberta_empai_final","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("roberta_empai_final","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_empai_final|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|466.4 MB|
+
+## References
+
+https://huggingface.co/LuangMV97/RoBERTa_EmpAI_final
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-roberta_empai_final_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-roberta_empai_final_pipeline_en.md
new file mode 100644
index 00000000000000..05f34599206b4b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-roberta_empai_final_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_empai_final_pipeline pipeline RoBertaEmbeddings from LuangMV97
+author: John Snow Labs
+name: roberta_empai_final_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_empai_final_pipeline` is a English model originally trained by LuangMV97.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_empai_final_pipeline_en_5.5.1_3.0_1737966398742.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_empai_final_pipeline_en_5.5.1_3.0_1737966398742.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_empai_final_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_empai_final_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_empai_final_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.4 MB|
+
+## References
+
+https://huggingface.co/LuangMV97/RoBERTa_EmpAI_final
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-roberta_large_unlabeled_labeled_gab_reddit_task_semeval2023_t10_90000sample_en.md b/docs/_posts/ahmedlone127/2025-01-27-roberta_large_unlabeled_labeled_gab_reddit_task_semeval2023_t10_90000sample_en.md
new file mode 100644
index 00000000000000..171c9584e1ea3e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-roberta_large_unlabeled_labeled_gab_reddit_task_semeval2023_t10_90000sample_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_large_unlabeled_labeled_gab_reddit_task_semeval2023_t10_90000sample RoBertaEmbeddings from HPL
+author: John Snow Labs
+name: roberta_large_unlabeled_labeled_gab_reddit_task_semeval2023_t10_90000sample
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_unlabeled_labeled_gab_reddit_task_semeval2023_t10_90000sample` is a English model originally trained by HPL.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_unlabeled_labeled_gab_reddit_task_semeval2023_t10_90000sample_en_5.5.1_3.0_1738020344122.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_unlabeled_labeled_gab_reddit_task_semeval2023_t10_90000sample_en_5.5.1_3.0_1738020344122.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("roberta_large_unlabeled_labeled_gab_reddit_task_semeval2023_t10_90000sample","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("roberta_large_unlabeled_labeled_gab_reddit_task_semeval2023_t10_90000sample","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_large_unlabeled_labeled_gab_reddit_task_semeval2023_t10_90000sample|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/HPL/roberta-large-unlabeled-labeled-gab-reddit-task-semeval2023-t10-90000sample
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-roberta_large_unlabeled_labeled_gab_reddit_task_semeval2023_t10_90000sample_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-roberta_large_unlabeled_labeled_gab_reddit_task_semeval2023_t10_90000sample_pipeline_en.md
new file mode 100644
index 00000000000000..98ad01829ad106
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-roberta_large_unlabeled_labeled_gab_reddit_task_semeval2023_t10_90000sample_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_large_unlabeled_labeled_gab_reddit_task_semeval2023_t10_90000sample_pipeline pipeline RoBertaEmbeddings from HPL
+author: John Snow Labs
+name: roberta_large_unlabeled_labeled_gab_reddit_task_semeval2023_t10_90000sample_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_unlabeled_labeled_gab_reddit_task_semeval2023_t10_90000sample_pipeline` is a English model originally trained by HPL.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_unlabeled_labeled_gab_reddit_task_semeval2023_t10_90000sample_pipeline_en_5.5.1_3.0_1738020409328.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_unlabeled_labeled_gab_reddit_task_semeval2023_t10_90000sample_pipeline_en_5.5.1_3.0_1738020409328.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_large_unlabeled_labeled_gab_reddit_task_semeval2023_t10_90000sample_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_large_unlabeled_labeled_gab_reddit_task_semeval2023_t10_90000sample_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_large_unlabeled_labeled_gab_reddit_task_semeval2023_t10_90000sample_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/HPL/roberta-large-unlabeled-labeled-gab-reddit-task-semeval2023-t10-90000sample
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-roberta_point_of_sales_classification_en.md b/docs/_posts/ahmedlone127/2025-01-27-roberta_point_of_sales_classification_en.md
new file mode 100644
index 00000000000000..40a2731d98140c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-roberta_point_of_sales_classification_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_point_of_sales_classification XlmRoBertaForSequenceClassification from IssamL
+author: John Snow Labs
+name: roberta_point_of_sales_classification
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_point_of_sales_classification` is a English model originally trained by IssamL.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_point_of_sales_classification_en_5.5.1_3.0_1737960087933.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_point_of_sales_classification_en_5.5.1_3.0_1737960087933.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("roberta_point_of_sales_classification","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("roberta_point_of_sales_classification", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_point_of_sales_classification|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|851.8 MB|
+
+## References
+
+https://huggingface.co/IssamL/roberta_point_of_sales_classification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-roberta_point_of_sales_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-roberta_point_of_sales_classification_pipeline_en.md
new file mode 100644
index 00000000000000..70c2ef4c7a5713
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-roberta_point_of_sales_classification_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_point_of_sales_classification_pipeline pipeline XlmRoBertaForSequenceClassification from IssamL
+author: John Snow Labs
+name: roberta_point_of_sales_classification_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_point_of_sales_classification_pipeline` is a English model originally trained by IssamL.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_point_of_sales_classification_pipeline_en_5.5.1_3.0_1737960151440.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_point_of_sales_classification_pipeline_en_5.5.1_3.0_1737960151440.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_point_of_sales_classification_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_point_of_sales_classification_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_point_of_sales_classification_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|851.8 MB|
+
+## References
+
+https://huggingface.co/IssamL/roberta_point_of_sales_classification
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-roberta_pretrained_litcov10k_manipulated_en.md b/docs/_posts/ahmedlone127/2025-01-27-roberta_pretrained_litcov10k_manipulated_en.md
new file mode 100644
index 00000000000000..d27f5a99da9d9a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-roberta_pretrained_litcov10k_manipulated_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_pretrained_litcov10k_manipulated RoBertaEmbeddings from IneG
+author: John Snow Labs
+name: roberta_pretrained_litcov10k_manipulated
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_pretrained_litcov10k_manipulated` is a English model originally trained by IneG.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_pretrained_litcov10k_manipulated_en_5.5.1_3.0_1738019765128.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_pretrained_litcov10k_manipulated_en_5.5.1_3.0_1738019765128.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("roberta_pretrained_litcov10k_manipulated","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("roberta_pretrained_litcov10k_manipulated","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_pretrained_litcov10k_manipulated|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/IneG/RoBERTa_pretrained_litcov10K_manipulated
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-roberta_pretrained_litcov10k_manipulated_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-roberta_pretrained_litcov10k_manipulated_pipeline_en.md
new file mode 100644
index 00000000000000..5871393f450e2c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-roberta_pretrained_litcov10k_manipulated_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_pretrained_litcov10k_manipulated_pipeline pipeline RoBertaEmbeddings from IneG
+author: John Snow Labs
+name: roberta_pretrained_litcov10k_manipulated_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_pretrained_litcov10k_manipulated_pipeline` is a English model originally trained by IneG.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_pretrained_litcov10k_manipulated_pipeline_en_5.5.1_3.0_1738019828962.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_pretrained_litcov10k_manipulated_pipeline_en_5.5.1_3.0_1738019828962.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_pretrained_litcov10k_manipulated_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_pretrained_litcov10k_manipulated_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_pretrained_litcov10k_manipulated_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/IneG/RoBERTa_pretrained_litcov10K_manipulated
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-roberta_realnews_epoch1_1m_en.md b/docs/_posts/ahmedlone127/2025-01-27-roberta_realnews_epoch1_1m_en.md
new file mode 100644
index 00000000000000..c6109e47098055
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-roberta_realnews_epoch1_1m_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_realnews_epoch1_1m RoBertaEmbeddings from ArnavL
+author: John Snow Labs
+name: roberta_realnews_epoch1_1m
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_realnews_epoch1_1m` is a English model originally trained by ArnavL.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_realnews_epoch1_1m_en_5.5.1_3.0_1737965430133.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_realnews_epoch1_1m_en_5.5.1_3.0_1737965430133.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("roberta_realnews_epoch1_1m","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("roberta_realnews_epoch1_1m","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_realnews_epoch1_1m|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|466.3 MB|
+
+## References
+
+https://huggingface.co/ArnavL/roberta-realnews-epoch1-1M
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-roberta_realnews_epoch1_1m_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-roberta_realnews_epoch1_1m_pipeline_en.md
new file mode 100644
index 00000000000000..072d66f16fb392
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-roberta_realnews_epoch1_1m_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_realnews_epoch1_1m_pipeline pipeline RoBertaEmbeddings from ArnavL
+author: John Snow Labs
+name: roberta_realnews_epoch1_1m_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_realnews_epoch1_1m_pipeline` is a English model originally trained by ArnavL.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_realnews_epoch1_1m_pipeline_en_5.5.1_3.0_1737965454659.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_realnews_epoch1_1m_pipeline_en_5.5.1_3.0_1737965454659.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_realnews_epoch1_1m_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_realnews_epoch1_1m_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_realnews_epoch1_1m_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.3 MB|
+
+## References
+
+https://huggingface.co/ArnavL/roberta-realnews-epoch1-1M
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-roberta_spam_en.md b/docs/_posts/ahmedlone127/2025-01-27-roberta_spam_en.md
new file mode 100644
index 00000000000000..a0810c9a4639a4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-roberta_spam_en.md
@@ -0,0 +1,98 @@
+---
+layout: model
+title: English roberta_spam RoBertaForSequenceClassification from mshenoda
+author: John Snow Labs
+name: roberta_spam
+date: 2025-01-27
+tags: [roberta, en, open_source, sequence_classification, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_spam` is a English model originally trained by mshenoda.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_spam_en_5.5.1_3.0_1737938423086.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_spam_en_5.5.1_3.0_1737938423086.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = DocumentAssembler()\
+    .setInputCol("text")\
+    .setOutputCol("document")
+
+tokenizer = Tokenizer()\
+    .setInputCols("document")\
+    .setOutputCol("token")  
+    
+sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_spam","en")\
+            .setInputCols(["document","token"])\
+            .setOutputCol("class")
+
+pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val document_assembler = new DocumentAssembler()
+    .setInputCol("text")
+    .setOutputCol("document")
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document") 
+    .setOutputCol("token")  
+    
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_spam","en")
+            .setInputCols(Array("document","token"))
+            .setOutputCol("class")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_spam|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|462.5 MB|
+
+## References
+
+References
+
+https://huggingface.co/mshenoda/roberta-spam
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-roberta_spam_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-roberta_spam_pipeline_en.md
new file mode 100644
index 00000000000000..c6232de0e15543
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-roberta_spam_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_spam_pipeline pipeline RoBertaForSequenceClassification from roze-sha
+author: John Snow Labs
+name: roberta_spam_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_spam_pipeline` is a English model originally trained by roze-sha.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_spam_pipeline_en_5.5.1_3.0_1737938447821.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_spam_pipeline_en_5.5.1_3.0_1737938447821.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_spam_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_spam_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_spam_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|462.5 MB|
+
+## References
+
+https://huggingface.co/roze-sha/roberta-spam
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-romansh_model_en.md b/docs/_posts/ahmedlone127/2025-01-27-romansh_model_en.md
new file mode 100644
index 00000000000000..ef3e6e6beb6c9d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-romansh_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English romansh_model XlmRoBertaForSequenceClassification from GalacticLinguists
+author: John Snow Labs
+name: romansh_model
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`romansh_model` is a English model originally trained by GalacticLinguists.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/romansh_model_en_5.5.1_3.0_1737960404671.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/romansh_model_en_5.5.1_3.0_1737960404671.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("romansh_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("romansh_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|romansh_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|831.5 MB|
+
+## References
+
+https://huggingface.co/GalacticLinguists/rm-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-romansh_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-romansh_model_pipeline_en.md
new file mode 100644
index 00000000000000..9a10672942d249
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-romansh_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English romansh_model_pipeline pipeline XlmRoBertaForSequenceClassification from GalacticLinguists
+author: John Snow Labs
+name: romansh_model_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`romansh_model_pipeline` is a English model originally trained by GalacticLinguists.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/romansh_model_pipeline_en_5.5.1_3.0_1737960519438.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/romansh_model_pipeline_en_5.5.1_3.0_1737960519438.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("romansh_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("romansh_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|romansh_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|831.5 MB|
+
+## References
+
+https://huggingface.co/GalacticLinguists/rm-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-rubert_base_finetuned_macedonian_en.md b/docs/_posts/ahmedlone127/2025-01-27-rubert_base_finetuned_macedonian_en.md
new file mode 100644
index 00000000000000..ff6a66d0ce4785
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-rubert_base_finetuned_macedonian_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English rubert_base_finetuned_macedonian BertEmbeddings from AnyaPanova
+author: John Snow Labs
+name: rubert_base_finetuned_macedonian
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_base_finetuned_macedonian` is a English model originally trained by AnyaPanova.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_base_finetuned_macedonian_en_5.5.1_3.0_1737985269653.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_base_finetuned_macedonian_en_5.5.1_3.0_1737985269653.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("rubert_base_finetuned_macedonian","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("rubert_base_finetuned_macedonian","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rubert_base_finetuned_macedonian|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|667.1 MB|
+
+## References
+
+https://huggingface.co/AnyaPanova/ruBert-base-finetuned-mk
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-rubert_base_finetuned_macedonian_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-rubert_base_finetuned_macedonian_pipeline_en.md
new file mode 100644
index 00000000000000..3544f96e978b1b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-rubert_base_finetuned_macedonian_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English rubert_base_finetuned_macedonian_pipeline pipeline BertEmbeddings from AnyaPanova
+author: John Snow Labs
+name: rubert_base_finetuned_macedonian_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_base_finetuned_macedonian_pipeline` is a English model originally trained by AnyaPanova.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_base_finetuned_macedonian_pipeline_en_5.5.1_3.0_1737985303125.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_base_finetuned_macedonian_pipeline_en_5.5.1_3.0_1737985303125.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("rubert_base_finetuned_macedonian_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("rubert_base_finetuned_macedonian_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rubert_base_finetuned_macedonian_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|667.1 MB|
+
+## References
+
+https://huggingface.co/AnyaPanova/ruBert-base-finetuned-mk
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-rubert_ner_sddcs_pipeline_ru.md b/docs/_posts/ahmedlone127/2025-01-27-rubert_ner_sddcs_pipeline_ru.md
new file mode 100644
index 00000000000000..d30c80d9c10e9e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-rubert_ner_sddcs_pipeline_ru.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Russian rubert_ner_sddcs_pipeline pipeline BertForTokenClassification from Mykes
+author: John Snow Labs
+name: rubert_ner_sddcs_pipeline
+date: 2025-01-27
+tags: [ru, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: ru
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_ner_sddcs_pipeline` is a Russian model originally trained by Mykes.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_ner_sddcs_pipeline_ru_5.5.1_3.0_1738017846325.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_ner_sddcs_pipeline_ru_5.5.1_3.0_1738017846325.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("rubert_ner_sddcs_pipeline", lang = "ru")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("rubert_ner_sddcs_pipeline", lang = "ru")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rubert_ner_sddcs_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ru|
+|Size:|109.2 MB|
+
+## References
+
+https://huggingface.co/Mykes/rubert_ner_SDDCS
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-rubert_ner_sddcs_ru.md b/docs/_posts/ahmedlone127/2025-01-27-rubert_ner_sddcs_ru.md
new file mode 100644
index 00000000000000..08c58ae938b8f5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-rubert_ner_sddcs_ru.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Russian rubert_ner_sddcs BertForTokenClassification from Mykes
+author: John Snow Labs
+name: rubert_ner_sddcs
+date: 2025-01-27
+tags: [ru, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: ru
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_ner_sddcs` is a Russian model originally trained by Mykes.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_ner_sddcs_ru_5.5.1_3.0_1738017841166.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_ner_sddcs_ru_5.5.1_3.0_1738017841166.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("rubert_ner_sddcs","ru") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("rubert_ner_sddcs", "ru")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rubert_ner_sddcs|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|ru|
+|Size:|109.1 MB|
+
+## References
+
+https://huggingface.co/Mykes/rubert_ner_SDDCS
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sage_model_en.md b/docs/_posts/ahmedlone127/2025-01-27-sage_model_en.md
new file mode 100644
index 00000000000000..bd23af56d0ae74
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sage_model_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English sage_model T5Transformer from Adarsh-12
+author: John Snow Labs
+name: sage_model
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sage_model` is a English model originally trained by Adarsh-12.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sage_model_en_5.5.1_3.0_1737991610224.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sage_model_en_5.5.1_3.0_1737991610224.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("sage_model","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("sage_model", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sage_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|349.8 MB|
+
+## References
+
+https://huggingface.co/Adarsh-12/SAGE_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sage_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-sage_model_pipeline_en.md
new file mode 100644
index 00000000000000..b50dc03860d7b8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sage_model_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English sage_model_pipeline pipeline T5Transformer from Adarsh-12
+author: John Snow Labs
+name: sage_model_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sage_model_pipeline` is a English model originally trained by Adarsh-12.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sage_model_pipeline_en_5.5.1_3.0_1737991628262.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sage_model_pipeline_en_5.5.1_3.0_1737991628262.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sage_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sage_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sage_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|349.8 MB|
+
+## References
+
+https://huggingface.co/Adarsh-12/SAGE_model
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-samsum_en.md b/docs/_posts/ahmedlone127/2025-01-27-samsum_en.md
new file mode 100644
index 00000000000000..cfd39dad3aa305
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-samsum_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English samsum T5Transformer from LLM2407
+author: John Snow Labs
+name: samsum
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`samsum` is a English model originally trained by LLM2407.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/samsum_en_5.5.1_3.0_1737944695798.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/samsum_en_5.5.1_3.0_1737944695798.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("samsum","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("samsum", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|samsum|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|277.4 MB|
+
+## References
+
+https://huggingface.co/LLM2407/samsum
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-samsum_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-samsum_pipeline_en.md
new file mode 100644
index 00000000000000..cf828fb96c9a85
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-samsum_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English samsum_pipeline pipeline T5Transformer from LLM2407
+author: John Snow Labs
+name: samsum_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`samsum_pipeline` is a English model originally trained by LLM2407.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/samsum_pipeline_en_5.5.1_3.0_1737944720347.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/samsum_pipeline_en_5.5.1_3.0_1737944720347.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("samsum_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("samsum_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|samsum_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|277.4 MB|
+
+## References
+
+https://huggingface.co/LLM2407/samsum
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-scrolls3_en.md b/docs/_posts/ahmedlone127/2025-01-27-scrolls3_en.md
new file mode 100644
index 00000000000000..4acb712b76f40c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-scrolls3_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English scrolls3 T5Transformer from yal27
+author: John Snow Labs
+name: scrolls3
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scrolls3` is a English model originally trained by yal27.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/scrolls3_en_5.5.1_3.0_1737963446937.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scrolls3_en_5.5.1_3.0_1737963446937.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("scrolls3","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("scrolls3", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|scrolls3|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|867.2 MB|
+
+## References
+
+https://huggingface.co/yal27/scrolls3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-scrolls3_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-scrolls3_pipeline_en.md
new file mode 100644
index 00000000000000..9e3716f791e06f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-scrolls3_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English scrolls3_pipeline pipeline T5Transformer from yal27
+author: John Snow Labs
+name: scrolls3_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scrolls3_pipeline` is a English model originally trained by yal27.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/scrolls3_pipeline_en_5.5.1_3.0_1737963505275.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scrolls3_pipeline_en_5.5.1_3.0_1737963505275.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("scrolls3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("scrolls3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|scrolls3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|867.2 MB|
+
+## References
+
+https://huggingface.co/yal27/scrolls3
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-scrolls4_en.md b/docs/_posts/ahmedlone127/2025-01-27-scrolls4_en.md
new file mode 100644
index 00000000000000..67132d928b7e53
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-scrolls4_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English scrolls4 T5Transformer from yal27
+author: John Snow Labs
+name: scrolls4
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scrolls4` is a English model originally trained by yal27.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/scrolls4_en_5.5.1_3.0_1737961621023.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scrolls4_en_5.5.1_3.0_1737961621023.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("scrolls4","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("scrolls4", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|scrolls4|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|892.8 MB|
+
+## References
+
+https://huggingface.co/yal27/scrolls4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-scrolls4_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-scrolls4_pipeline_en.md
new file mode 100644
index 00000000000000..ce59c82223d4c0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-scrolls4_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English scrolls4_pipeline pipeline T5Transformer from yal27
+author: John Snow Labs
+name: scrolls4_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scrolls4_pipeline` is a English model originally trained by yal27.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/scrolls4_pipeline_en_5.5.1_3.0_1737961675307.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scrolls4_pipeline_en_5.5.1_3.0_1737961675307.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("scrolls4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("scrolls4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|scrolls4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|892.8 MB|
+
+## References
+
+https://huggingface.co/yal27/scrolls4
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-secondresults_en.md b/docs/_posts/ahmedlone127/2025-01-27-secondresults_en.md
new file mode 100644
index 00000000000000..82f8a57b74ae26
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-secondresults_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English secondresults T5Transformer from supkon
+author: John Snow Labs
+name: secondresults
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`secondresults` is a English model originally trained by supkon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/secondresults_en_5.5.1_3.0_1737978026625.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/secondresults_en_5.5.1_3.0_1737978026625.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("secondresults","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("secondresults", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|secondresults|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|519.4 MB|
+
+## References
+
+https://huggingface.co/supkon/secondresults
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-secondresults_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-secondresults_pipeline_en.md
new file mode 100644
index 00000000000000..c008438e23870c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-secondresults_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English secondresults_pipeline pipeline T5Transformer from supkon
+author: John Snow Labs
+name: secondresults_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`secondresults_pipeline` is a English model originally trained by supkon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/secondresults_pipeline_en_5.5.1_3.0_1737978198453.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/secondresults_pipeline_en_5.5.1_3.0_1737978198453.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("secondresults_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("secondresults_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|secondresults_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|519.4 MB|
+
+## References
+
+https://huggingface.co/supkon/secondresults
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-segmenter_distill_v0_1_en.md b/docs/_posts/ahmedlone127/2025-01-27-segmenter_distill_v0_1_en.md
new file mode 100644
index 00000000000000..e898e32d39e119
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-segmenter_distill_v0_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English segmenter_distill_v0_1 XlmRoBertaForTokenClassification from datalawyer
+author: John Snow Labs
+name: segmenter_distill_v0_1
+date: 2025-01-27
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`segmenter_distill_v0_1` is a English model originally trained by datalawyer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/segmenter_distill_v0_1_en_5.5.1_3.0_1737969567838.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/segmenter_distill_v0_1_en_5.5.1_3.0_1737969567838.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("segmenter_distill_v0_1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("segmenter_distill_v0_1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|segmenter_distill_v0_1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/datalawyer/segmenter-distill-v0.1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-segmenter_distill_v0_1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-segmenter_distill_v0_1_pipeline_en.md
new file mode 100644
index 00000000000000..277f53d9d6acaa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-segmenter_distill_v0_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English segmenter_distill_v0_1_pipeline pipeline XlmRoBertaForTokenClassification from datalawyer
+author: John Snow Labs
+name: segmenter_distill_v0_1_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`segmenter_distill_v0_1_pipeline` is a English model originally trained by datalawyer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/segmenter_distill_v0_1_pipeline_en_5.5.1_3.0_1737969741856.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/segmenter_distill_v0_1_pipeline_en_5.5.1_3.0_1737969741856.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("segmenter_distill_v0_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("segmenter_distill_v0_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|segmenter_distill_v0_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/datalawyer/segmenter-distill-v0.1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sempl_italian_mt5_small_it.md b/docs/_posts/ahmedlone127/2025-01-27-sempl_italian_mt5_small_it.md
new file mode 100644
index 00000000000000..e83a8bd78e4ba7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sempl_italian_mt5_small_it.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Italian sempl_italian_mt5_small T5Transformer from VerbACxSS
+author: John Snow Labs
+name: sempl_italian_mt5_small
+date: 2025-01-27
+tags: [it, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: it
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sempl_italian_mt5_small` is a Italian model originally trained by VerbACxSS.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sempl_italian_mt5_small_it_5.5.1_3.0_1738002247729.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sempl_italian_mt5_small_it_5.5.1_3.0_1738002247729.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("sempl_italian_mt5_small","it") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("sempl_italian_mt5_small", "it")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sempl_italian_mt5_small|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|it|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/VerbACxSS/sempl-it-mt5-small
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sempl_italian_mt5_small_pipeline_it.md b/docs/_posts/ahmedlone127/2025-01-27-sempl_italian_mt5_small_pipeline_it.md
new file mode 100644
index 00000000000000..65109e4f5c670a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sempl_italian_mt5_small_pipeline_it.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Italian sempl_italian_mt5_small_pipeline pipeline T5Transformer from VerbACxSS
+author: John Snow Labs
+name: sempl_italian_mt5_small_pipeline
+date: 2025-01-27
+tags: [it, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: it
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sempl_italian_mt5_small_pipeline` is a Italian model originally trained by VerbACxSS.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sempl_italian_mt5_small_pipeline_it_5.5.1_3.0_1738002347047.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sempl_italian_mt5_small_pipeline_it_5.5.1_3.0_1738002347047.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sempl_italian_mt5_small_pipeline", lang = "it")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sempl_italian_mt5_small_pipeline", lang = "it")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sempl_italian_mt5_small_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|it|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/VerbACxSS/sempl-it-mt5-small
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sent_afrikalm_multilang_en.md b/docs/_posts/ahmedlone127/2025-01-27-sent_afrikalm_multilang_en.md
new file mode 100644
index 00000000000000..7efa9f92e61314
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sent_afrikalm_multilang_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_afrikalm_multilang BertSentenceEmbeddings from frankl1
+author: John Snow Labs
+name: sent_afrikalm_multilang
+date: 2025-01-27
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_afrikalm_multilang` is a English model originally trained by frankl1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_afrikalm_multilang_en_5.5.1_3.0_1737942005371.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_afrikalm_multilang_en_5.5.1_3.0_1737942005371.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_afrikalm_multilang","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_afrikalm_multilang","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_afrikalm_multilang|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|138.3 MB|
+
+## References
+
+https://huggingface.co/frankl1/afrikalm-multilang
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sent_afrikalm_multilang_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-sent_afrikalm_multilang_pipeline_en.md
new file mode 100644
index 00000000000000..961b9897c9342a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sent_afrikalm_multilang_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_afrikalm_multilang_pipeline pipeline BertSentenceEmbeddings from frankl1
+author: John Snow Labs
+name: sent_afrikalm_multilang_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_afrikalm_multilang_pipeline` is a English model originally trained by frankl1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_afrikalm_multilang_pipeline_en_5.5.1_3.0_1737942012457.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_afrikalm_multilang_pipeline_en_5.5.1_3.0_1737942012457.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_afrikalm_multilang_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_afrikalm_multilang_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_afrikalm_multilang_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|138.8 MB|
+
+## References
+
+https://huggingface.co/frankl1/afrikalm-multilang
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sent_all_minilm_l6_v2_personal_project_default_2024_06_03_en.md b/docs/_posts/ahmedlone127/2025-01-27-sent_all_minilm_l6_v2_personal_project_default_2024_06_03_en.md
new file mode 100644
index 00000000000000..a94b906d3369f9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sent_all_minilm_l6_v2_personal_project_default_2024_06_03_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_all_minilm_l6_v2_personal_project_default_2024_06_03 BertSentenceEmbeddings from brugmark
+author: John Snow Labs
+name: sent_all_minilm_l6_v2_personal_project_default_2024_06_03
+date: 2025-01-27
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_all_minilm_l6_v2_personal_project_default_2024_06_03` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_default_2024_06_03_en_5.5.1_3.0_1737941714190.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_default_2024_06_03_en_5.5.1_3.0_1737941714190.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_all_minilm_l6_v2_personal_project_default_2024_06_03","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_all_minilm_l6_v2_personal_project_default_2024_06_03","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_all_minilm_l6_v2_personal_project_default_2024_06_03|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|83.9 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-default-2024-06-03
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sent_all_minilm_l6_v2_personal_project_default_2024_06_03_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-sent_all_minilm_l6_v2_personal_project_default_2024_06_03_pipeline_en.md
new file mode 100644
index 00000000000000..0a913fe87e9d36
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sent_all_minilm_l6_v2_personal_project_default_2024_06_03_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_all_minilm_l6_v2_personal_project_default_2024_06_03_pipeline pipeline BertSentenceEmbeddings from brugmark
+author: John Snow Labs
+name: sent_all_minilm_l6_v2_personal_project_default_2024_06_03_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_all_minilm_l6_v2_personal_project_default_2024_06_03_pipeline` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_default_2024_06_03_pipeline_en_5.5.1_3.0_1737941718970.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_default_2024_06_03_pipeline_en_5.5.1_3.0_1737941718970.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_all_minilm_l6_v2_personal_project_default_2024_06_03_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_all_minilm_l6_v2_personal_project_default_2024_06_03_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_all_minilm_l6_v2_personal_project_default_2024_06_03_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|84.5 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-default-2024-06-03
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sent_bert_adaptation_referencias_german_vinos_steffstaurini_en.md b/docs/_posts/ahmedlone127/2025-01-27-sent_bert_adaptation_referencias_german_vinos_steffstaurini_en.md
new file mode 100644
index 00000000000000..8f360e02525c7d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sent_bert_adaptation_referencias_german_vinos_steffstaurini_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_adaptation_referencias_german_vinos_steffstaurini BertSentenceEmbeddings from steffstaurini
+author: John Snow Labs
+name: sent_bert_adaptation_referencias_german_vinos_steffstaurini
+date: 2025-01-27
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_adaptation_referencias_german_vinos_steffstaurini` is a English model originally trained by steffstaurini.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_referencias_german_vinos_steffstaurini_en_5.5.1_3.0_1737941861507.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_referencias_german_vinos_steffstaurini_en_5.5.1_3.0_1737941861507.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_adaptation_referencias_german_vinos_steffstaurini","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_adaptation_referencias_german_vinos_steffstaurini","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_adaptation_referencias_german_vinos_steffstaurini|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/steffstaurini/bert_adaptation_referencias_de_vinos
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sent_bert_adaptation_referencias_german_vinos_steffstaurini_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-sent_bert_adaptation_referencias_german_vinos_steffstaurini_pipeline_en.md
new file mode 100644
index 00000000000000..ffa11c3f0f7fa4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sent_bert_adaptation_referencias_german_vinos_steffstaurini_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_adaptation_referencias_german_vinos_steffstaurini_pipeline pipeline BertSentenceEmbeddings from steffstaurini
+author: John Snow Labs
+name: sent_bert_adaptation_referencias_german_vinos_steffstaurini_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_adaptation_referencias_german_vinos_steffstaurini_pipeline` is a English model originally trained by steffstaurini.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_referencias_german_vinos_steffstaurini_pipeline_en_5.5.1_3.0_1737941884751.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_referencias_german_vinos_steffstaurini_pipeline_en_5.5.1_3.0_1737941884751.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_adaptation_referencias_german_vinos_steffstaurini_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_adaptation_referencias_german_vinos_steffstaurini_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_adaptation_referencias_german_vinos_steffstaurini_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.2 MB|
+
+## References
+
+https://huggingface.co/steffstaurini/bert_adaptation_referencias_de_vinos
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sent_bert_base_120_en.md b/docs/_posts/ahmedlone127/2025-01-27-sent_bert_base_120_en.md
new file mode 100644
index 00000000000000..ad317ee373b5b7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sent_bert_base_120_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_base_120 BertSentenceEmbeddings from gokuls
+author: John Snow Labs
+name: sent_bert_base_120
+date: 2025-01-27
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_120` is a English model originally trained by gokuls.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_120_en_5.5.1_3.0_1738016097594.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_120_en_5.5.1_3.0_1738016097594.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_120","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_120","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_120|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|408.1 MB|
+
+## References
+
+https://huggingface.co/gokuls/bert_base_120
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sent_bert_base_120_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-sent_bert_base_120_pipeline_en.md
new file mode 100644
index 00000000000000..05e85c79d1f6a7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sent_bert_base_120_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_base_120_pipeline pipeline BertSentenceEmbeddings from gokuls
+author: John Snow Labs
+name: sent_bert_base_120_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_120_pipeline` is a English model originally trained by gokuls.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_120_pipeline_en_5.5.1_3.0_1738016118082.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_120_pipeline_en_5.5.1_3.0_1738016118082.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_base_120_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_120_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_120_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|408.6 MB|
+
+## References
+
+https://huggingface.co/gokuls/bert_base_120
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sent_bert_base_arapoembert_ar.md b/docs/_posts/ahmedlone127/2025-01-27-sent_bert_base_arapoembert_ar.md
new file mode 100644
index 00000000000000..dbc25942566096
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sent_bert_base_arapoembert_ar.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Arabic sent_bert_base_arapoembert BertSentenceEmbeddings from faisalq
+author: John Snow Labs
+name: sent_bert_base_arapoembert
+date: 2025-01-27
+tags: [ar, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: ar
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_arapoembert` is a Arabic model originally trained by faisalq.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_arapoembert_ar_5.5.1_3.0_1738015858138.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_arapoembert_ar_5.5.1_3.0_1738015858138.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_arapoembert","ar") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_arapoembert","ar") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_arapoembert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|ar|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/faisalq/bert-base-arapoembert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sent_bert_base_arapoembert_pipeline_ar.md b/docs/_posts/ahmedlone127/2025-01-27-sent_bert_base_arapoembert_pipeline_ar.md
new file mode 100644
index 00000000000000..b2bb3493e0eb7b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sent_bert_base_arapoembert_pipeline_ar.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Arabic sent_bert_base_arapoembert_pipeline pipeline BertSentenceEmbeddings from faisalq
+author: John Snow Labs
+name: sent_bert_base_arapoembert_pipeline
+date: 2025-01-27
+tags: [ar, open_source, pipeline, onnx]
+task: Embeddings
+language: ar
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_arapoembert_pipeline` is a Arabic model originally trained by faisalq.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_arapoembert_pipeline_ar_5.5.1_3.0_1738015878885.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_arapoembert_pipeline_ar_5.5.1_3.0_1738015878885.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_base_arapoembert_pipeline", lang = "ar")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_arapoembert_pipeline", lang = "ar")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_arapoembert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ar|
+|Size:|407.4 MB|
+
+## References
+
+https://huggingface.co/faisalq/bert-base-arapoembert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sent_bert_base_cased_wikitext2_hannahzhanng_en.md b/docs/_posts/ahmedlone127/2025-01-27-sent_bert_base_cased_wikitext2_hannahzhanng_en.md
new file mode 100644
index 00000000000000..e4f4b7fa0d8a0d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sent_bert_base_cased_wikitext2_hannahzhanng_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_base_cased_wikitext2_hannahzhanng BertSentenceEmbeddings from hannahzhanng
+author: John Snow Labs
+name: sent_bert_base_cased_wikitext2_hannahzhanng
+date: 2025-01-27
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_cased_wikitext2_hannahzhanng` is a English model originally trained by hannahzhanng.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_cased_wikitext2_hannahzhanng_en_5.5.1_3.0_1737941536571.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_cased_wikitext2_hannahzhanng_en_5.5.1_3.0_1737941536571.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_cased_wikitext2_hannahzhanng","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_cased_wikitext2_hannahzhanng","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_cased_wikitext2_hannahzhanng|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|403.4 MB|
+
+## References
+
+https://huggingface.co/hannahzhanng/bert-base-cased-wikitext2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sent_bert_base_cased_wikitext2_hannahzhanng_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-sent_bert_base_cased_wikitext2_hannahzhanng_pipeline_en.md
new file mode 100644
index 00000000000000..4df9adc57f10a8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sent_bert_base_cased_wikitext2_hannahzhanng_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_base_cased_wikitext2_hannahzhanng_pipeline pipeline BertSentenceEmbeddings from hannahzhanng
+author: John Snow Labs
+name: sent_bert_base_cased_wikitext2_hannahzhanng_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_cased_wikitext2_hannahzhanng_pipeline` is a English model originally trained by hannahzhanng.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_cased_wikitext2_hannahzhanng_pipeline_en_5.5.1_3.0_1737941562884.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_cased_wikitext2_hannahzhanng_pipeline_en_5.5.1_3.0_1737941562884.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_base_cased_wikitext2_hannahzhanng_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_cased_wikitext2_hannahzhanng_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_cased_wikitext2_hannahzhanng_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|404.0 MB|
+
+## References
+
+https://huggingface.co/hannahzhanng/bert-base-cased-wikitext2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sent_bert_base_german_uncased_de.md b/docs/_posts/ahmedlone127/2025-01-27-sent_bert_base_german_uncased_de.md
new file mode 100644
index 00000000000000..be7740fd035199
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sent_bert_base_german_uncased_de.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: German sent_bert_base_german_uncased BertSentenceEmbeddings from voize
+author: John Snow Labs
+name: sent_bert_base_german_uncased
+date: 2025-01-27
+tags: [de, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: de
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_german_uncased` is a German model originally trained by voize.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_german_uncased_de_5.5.1_3.0_1737941925512.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_german_uncased_de_5.5.1_3.0_1737941925512.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_german_uncased","de") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_german_uncased","de") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_german_uncased|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|de|
+|Size:|409.9 MB|
+
+## References
+
+https://huggingface.co/voize/bert-base-german-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sent_bert_base_german_uncased_pipeline_de.md b/docs/_posts/ahmedlone127/2025-01-27-sent_bert_base_german_uncased_pipeline_de.md
new file mode 100644
index 00000000000000..34619521ed873c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sent_bert_base_german_uncased_pipeline_de.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: German sent_bert_base_german_uncased_pipeline pipeline BertSentenceEmbeddings from voize
+author: John Snow Labs
+name: sent_bert_base_german_uncased_pipeline
+date: 2025-01-27
+tags: [de, open_source, pipeline, onnx]
+task: Embeddings
+language: de
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_german_uncased_pipeline` is a German model originally trained by voize.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_german_uncased_pipeline_de_5.5.1_3.0_1737941947716.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_german_uncased_pipeline_de_5.5.1_3.0_1737941947716.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_base_german_uncased_pipeline", lang = "de")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_german_uncased_pipeline", lang = "de")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_german_uncased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|de|
+|Size:|410.4 MB|
+
+## References
+
+https://huggingface.co/voize/bert-base-german-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sent_bert_base_uncased_finetuned_fin_en.md b/docs/_posts/ahmedlone127/2025-01-27-sent_bert_base_uncased_finetuned_fin_en.md
new file mode 100644
index 00000000000000..742c921f89e6cf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sent_bert_base_uncased_finetuned_fin_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_base_uncased_finetuned_fin BertSentenceEmbeddings from fhzh123
+author: John Snow Labs
+name: sent_bert_base_uncased_finetuned_fin
+date: 2025-01-27
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_uncased_finetuned_fin` is a English model originally trained by fhzh123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_finetuned_fin_en_5.5.1_3.0_1737941395453.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_finetuned_fin_en_5.5.1_3.0_1737941395453.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_uncased_finetuned_fin","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_uncased_finetuned_fin","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_uncased_finetuned_fin|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/fhzh123/bert-base-uncased-finetuned-fin
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sent_bert_base_uncased_finetuned_fin_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-sent_bert_base_uncased_finetuned_fin_pipeline_en.md
new file mode 100644
index 00000000000000..bf4b1620117929
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sent_bert_base_uncased_finetuned_fin_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_base_uncased_finetuned_fin_pipeline pipeline BertSentenceEmbeddings from fhzh123
+author: John Snow Labs
+name: sent_bert_base_uncased_finetuned_fin_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_uncased_finetuned_fin_pipeline` is a English model originally trained by fhzh123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_finetuned_fin_pipeline_en_5.5.1_3.0_1737941417126.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_finetuned_fin_pipeline_en_5.5.1_3.0_1737941417126.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_base_uncased_finetuned_fin_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_uncased_finetuned_fin_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_uncased_finetuned_fin_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.7 MB|
+
+## References
+
+https://huggingface.co/fhzh123/bert-base-uncased-finetuned-fin
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sent_bert_fair_uncased_en.md b/docs/_posts/ahmedlone127/2025-01-27-sent_bert_fair_uncased_en.md
new file mode 100644
index 00000000000000..1aa8a0bd8e0f7b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sent_bert_fair_uncased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_fair_uncased BertSentenceEmbeddings from MScDS2023
+author: John Snow Labs
+name: sent_bert_fair_uncased
+date: 2025-01-27
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_fair_uncased` is a English model originally trained by MScDS2023.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_fair_uncased_en_5.5.1_3.0_1737942104430.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_fair_uncased_en_5.5.1_3.0_1737942104430.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_fair_uncased","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_fair_uncased","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_fair_uncased|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/MScDS2023/bert-fair-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sent_bert_fair_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-sent_bert_fair_uncased_pipeline_en.md
new file mode 100644
index 00000000000000..b6d85bc7b16b0b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sent_bert_fair_uncased_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_fair_uncased_pipeline pipeline BertSentenceEmbeddings from MScDS2023
+author: John Snow Labs
+name: sent_bert_fair_uncased_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_fair_uncased_pipeline` is a English model originally trained by MScDS2023.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_fair_uncased_pipeline_en_5.5.1_3.0_1737942125851.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_fair_uncased_pipeline_en_5.5.1_3.0_1737942125851.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_fair_uncased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_fair_uncased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_fair_uncased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.7 MB|
+
+## References
+
+https://huggingface.co/MScDS2023/bert-fair-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sent_bert_large_nordic_pile_1m_steps_pipeline_sv.md b/docs/_posts/ahmedlone127/2025-01-27-sent_bert_large_nordic_pile_1m_steps_pipeline_sv.md
new file mode 100644
index 00000000000000..bc2466ac550f56
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sent_bert_large_nordic_pile_1m_steps_pipeline_sv.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Swedish sent_bert_large_nordic_pile_1m_steps_pipeline pipeline BertSentenceEmbeddings from AI-Sweden-Models
+author: John Snow Labs
+name: sent_bert_large_nordic_pile_1m_steps_pipeline
+date: 2025-01-27
+tags: [sv, open_source, pipeline, onnx]
+task: Embeddings
+language: sv
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_large_nordic_pile_1m_steps_pipeline` is a Swedish model originally trained by AI-Sweden-Models.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_large_nordic_pile_1m_steps_pipeline_sv_5.5.1_3.0_1737941659757.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_large_nordic_pile_1m_steps_pipeline_sv_5.5.1_3.0_1737941659757.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_large_nordic_pile_1m_steps_pipeline", lang = "sv")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_large_nordic_pile_1m_steps_pipeline", lang = "sv")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_large_nordic_pile_1m_steps_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|sv|
+|Size:|1.4 GB|
+
+## References
+
+https://huggingface.co/AI-Sweden-Models/bert-large-nordic-pile-1M-steps
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sent_bert_large_nordic_pile_1m_steps_sv.md b/docs/_posts/ahmedlone127/2025-01-27-sent_bert_large_nordic_pile_1m_steps_sv.md
new file mode 100644
index 00000000000000..75eacb672465bc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sent_bert_large_nordic_pile_1m_steps_sv.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Swedish sent_bert_large_nordic_pile_1m_steps BertSentenceEmbeddings from AI-Sweden-Models
+author: John Snow Labs
+name: sent_bert_large_nordic_pile_1m_steps
+date: 2025-01-27
+tags: [sv, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: sv
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_large_nordic_pile_1m_steps` is a Swedish model originally trained by AI-Sweden-Models.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_large_nordic_pile_1m_steps_sv_5.5.1_3.0_1737941589705.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_large_nordic_pile_1m_steps_sv_5.5.1_3.0_1737941589705.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_large_nordic_pile_1m_steps","sv") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_large_nordic_pile_1m_steps","sv") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_large_nordic_pile_1m_steps|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|sv|
+|Size:|1.4 GB|
+
+## References
+
+https://huggingface.co/AI-Sweden-Models/bert-large-nordic-pile-1M-steps
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sent_berth5_en.md b/docs/_posts/ahmedlone127/2025-01-27-sent_berth5_en.md
new file mode 100644
index 00000000000000..ba7232feec7f96
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sent_berth5_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_berth5 BertSentenceEmbeddings from JeloH
+author: John Snow Labs
+name: sent_berth5
+date: 2025-01-27
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_berth5` is a English model originally trained by JeloH.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_berth5_en_5.5.1_3.0_1737941678167.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_berth5_en_5.5.1_3.0_1737941678167.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_berth5","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_berth5","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_berth5|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/JeloH/BertH5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sent_berth5_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-sent_berth5_pipeline_en.md
new file mode 100644
index 00000000000000..cd58cd5f950805
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sent_berth5_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_berth5_pipeline pipeline BertSentenceEmbeddings from JeloH
+author: John Snow Labs
+name: sent_berth5_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_berth5_pipeline` is a English model originally trained by JeloH.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_berth5_pipeline_en_5.5.1_3.0_1737941701951.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_berth5_pipeline_en_5.5.1_3.0_1737941701951.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_berth5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_berth5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_berth5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.6 MB|
+
+## References
+
+https://huggingface.co/JeloH/BertH5
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sent_burmese_model_paoloant_en.md b/docs/_posts/ahmedlone127/2025-01-27-sent_burmese_model_paoloant_en.md
new file mode 100644
index 00000000000000..dbc416b790b6e4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sent_burmese_model_paoloant_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_burmese_model_paoloant BertSentenceEmbeddings from Paoloant
+author: John Snow Labs
+name: sent_burmese_model_paoloant
+date: 2025-01-27
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_burmese_model_paoloant` is a English model originally trained by Paoloant.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_burmese_model_paoloant_en_5.5.1_3.0_1737941183783.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_burmese_model_paoloant_en_5.5.1_3.0_1737941183783.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_burmese_model_paoloant","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_burmese_model_paoloant","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_burmese_model_paoloant|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/Paoloant/my-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sent_burmese_model_paoloant_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-sent_burmese_model_paoloant_pipeline_en.md
new file mode 100644
index 00000000000000..e8f77b7b4770d8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sent_burmese_model_paoloant_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_burmese_model_paoloant_pipeline pipeline BertSentenceEmbeddings from Paoloant
+author: John Snow Labs
+name: sent_burmese_model_paoloant_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_burmese_model_paoloant_pipeline` is a English model originally trained by Paoloant.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_burmese_model_paoloant_pipeline_en_5.5.1_3.0_1737941204906.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_burmese_model_paoloant_pipeline_en_5.5.1_3.0_1737941204906.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_burmese_model_paoloant_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_burmese_model_paoloant_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_burmese_model_paoloant_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|404.2 MB|
+
+## References
+
+https://huggingface.co/Paoloant/my-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sent_finbert_basevocab_cased_en.md b/docs/_posts/ahmedlone127/2025-01-27-sent_finbert_basevocab_cased_en.md
new file mode 100644
index 00000000000000..0279e793b0c656
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sent_finbert_basevocab_cased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_finbert_basevocab_cased BertSentenceEmbeddings from radmada
+author: John Snow Labs
+name: sent_finbert_basevocab_cased
+date: 2025-01-27
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_finbert_basevocab_cased` is a English model originally trained by radmada.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_finbert_basevocab_cased_en_5.5.1_3.0_1738015685232.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_finbert_basevocab_cased_en_5.5.1_3.0_1738015685232.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_finbert_basevocab_cased","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_finbert_basevocab_cased","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_finbert_basevocab_cased|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/radmada/FinBERT-BaseVocab-Cased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sent_finbert_basevocab_cased_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-sent_finbert_basevocab_cased_pipeline_en.md
new file mode 100644
index 00000000000000..ba2f033ba6fea9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sent_finbert_basevocab_cased_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_finbert_basevocab_cased_pipeline pipeline BertSentenceEmbeddings from radmada
+author: John Snow Labs
+name: sent_finbert_basevocab_cased_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_finbert_basevocab_cased_pipeline` is a English model originally trained by radmada.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_finbert_basevocab_cased_pipeline_en_5.5.1_3.0_1738015705340.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_finbert_basevocab_cased_pipeline_en_5.5.1_3.0_1738015705340.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_finbert_basevocab_cased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_finbert_basevocab_cased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_finbert_basevocab_cased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|404.2 MB|
+
+## References
+
+https://huggingface.co/radmada/FinBERT-BaseVocab-Cased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sent_hing_mbert_mixed_v2_hi.md b/docs/_posts/ahmedlone127/2025-01-27-sent_hing_mbert_mixed_v2_hi.md
new file mode 100644
index 00000000000000..f3a979242b29cf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sent_hing_mbert_mixed_v2_hi.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Hindi sent_hing_mbert_mixed_v2 BertSentenceEmbeddings from l3cube-pune
+author: John Snow Labs
+name: sent_hing_mbert_mixed_v2
+date: 2025-01-27
+tags: [hi, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: hi
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_hing_mbert_mixed_v2` is a Hindi model originally trained by l3cube-pune.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_hing_mbert_mixed_v2_hi_5.5.1_3.0_1737941840753.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_hing_mbert_mixed_v2_hi_5.5.1_3.0_1737941840753.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_hing_mbert_mixed_v2","hi") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_hing_mbert_mixed_v2","hi") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_hing_mbert_mixed_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|hi|
+|Size:|890.6 MB|
+
+## References
+
+https://huggingface.co/l3cube-pune/hing-mbert-mixed-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sent_hing_mbert_mixed_v2_pipeline_hi.md b/docs/_posts/ahmedlone127/2025-01-27-sent_hing_mbert_mixed_v2_pipeline_hi.md
new file mode 100644
index 00000000000000..c83d8e82f17bc1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sent_hing_mbert_mixed_v2_pipeline_hi.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Hindi sent_hing_mbert_mixed_v2_pipeline pipeline BertSentenceEmbeddings from l3cube-pune
+author: John Snow Labs
+name: sent_hing_mbert_mixed_v2_pipeline
+date: 2025-01-27
+tags: [hi, open_source, pipeline, onnx]
+task: Embeddings
+language: hi
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_hing_mbert_mixed_v2_pipeline` is a Hindi model originally trained by l3cube-pune.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_hing_mbert_mixed_v2_pipeline_hi_5.5.1_3.0_1737941888196.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_hing_mbert_mixed_v2_pipeline_hi_5.5.1_3.0_1737941888196.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_hing_mbert_mixed_v2_pipeline", lang = "hi")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_hing_mbert_mixed_v2_pipeline", lang = "hi")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_hing_mbert_mixed_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|hi|
+|Size:|891.1 MB|
+
+## References
+
+https://huggingface.co/l3cube-pune/hing-mbert-mixed-v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sent_issuebert_base_en.md b/docs/_posts/ahmedlone127/2025-01-27-sent_issuebert_base_en.md
new file mode 100644
index 00000000000000..6619243f2edec4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sent_issuebert_base_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_issuebert_base BertSentenceEmbeddings from gbkwon
+author: John Snow Labs
+name: sent_issuebert_base
+date: 2025-01-27
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_issuebert_base` is a English model originally trained by gbkwon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_issuebert_base_en_5.5.1_3.0_1738015993453.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_issuebert_base_en_5.5.1_3.0_1738015993453.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_issuebert_base","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_issuebert_base","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_issuebert_base|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|408.3 MB|
+
+## References
+
+https://huggingface.co/gbkwon/issueBERT-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sent_issuebert_base_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-sent_issuebert_base_pipeline_en.md
new file mode 100644
index 00000000000000..c8f04a4037cac8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sent_issuebert_base_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_issuebert_base_pipeline pipeline BertSentenceEmbeddings from gbkwon
+author: John Snow Labs
+name: sent_issuebert_base_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_issuebert_base_pipeline` is a English model originally trained by gbkwon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_issuebert_base_pipeline_en_5.5.1_3.0_1738016013893.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_issuebert_base_pipeline_en_5.5.1_3.0_1738016013893.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_issuebert_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_issuebert_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_issuebert_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|408.9 MB|
+
+## References
+
+https://huggingface.co/gbkwon/issueBERT-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sent_mbert_ottoman_raw_en.md b/docs/_posts/ahmedlone127/2025-01-27-sent_mbert_ottoman_raw_en.md
new file mode 100644
index 00000000000000..5bbc529ff59d1e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sent_mbert_ottoman_raw_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_mbert_ottoman_raw BertSentenceEmbeddings from onurkeles
+author: John Snow Labs
+name: sent_mbert_ottoman_raw
+date: 2025-01-27
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_mbert_ottoman_raw` is a English model originally trained by onurkeles.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_mbert_ottoman_raw_en_5.5.1_3.0_1737941811411.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_mbert_ottoman_raw_en_5.5.1_3.0_1737941811411.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_mbert_ottoman_raw","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_mbert_ottoman_raw","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_mbert_ottoman_raw|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|663.7 MB|
+
+## References
+
+https://huggingface.co/onurkeles/mbert-ottoman-raw
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sent_mbert_ottoman_raw_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-sent_mbert_ottoman_raw_pipeline_en.md
new file mode 100644
index 00000000000000..e4e50ef8a5a4ec
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sent_mbert_ottoman_raw_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_mbert_ottoman_raw_pipeline pipeline BertSentenceEmbeddings from onurkeles
+author: John Snow Labs
+name: sent_mbert_ottoman_raw_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_mbert_ottoman_raw_pipeline` is a English model originally trained by onurkeles.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_mbert_ottoman_raw_pipeline_en_5.5.1_3.0_1737941847511.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_mbert_ottoman_raw_pipeline_en_5.5.1_3.0_1737941847511.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_mbert_ottoman_raw_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_mbert_ottoman_raw_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_mbert_ottoman_raw_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|664.2 MB|
+
+## References
+
+https://huggingface.co/onurkeles/mbert-ottoman-raw
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sent_medbert_base_en.md b/docs/_posts/ahmedlone127/2025-01-27-sent_medbert_base_en.md
new file mode 100644
index 00000000000000..87249a418257fd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sent_medbert_base_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_medbert_base BertSentenceEmbeddings from suayptalha
+author: John Snow Labs
+name: sent_medbert_base
+date: 2025-01-27
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_medbert_base` is a English model originally trained by suayptalha.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_medbert_base_en_5.5.1_3.0_1737941516488.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_medbert_base_en_5.5.1_3.0_1737941516488.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_medbert_base","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_medbert_base","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_medbert_base|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/suayptalha/medBERT-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sent_medbert_base_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-sent_medbert_base_pipeline_en.md
new file mode 100644
index 00000000000000..3ce6f0d89799bb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sent_medbert_base_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_medbert_base_pipeline pipeline BertSentenceEmbeddings from suayptalha
+author: John Snow Labs
+name: sent_medbert_base_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_medbert_base_pipeline` is a English model originally trained by suayptalha.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_medbert_base_pipeline_en_5.5.1_3.0_1737941538264.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_medbert_base_pipeline_en_5.5.1_3.0_1737941538264.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_medbert_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_medbert_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_medbert_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.7 MB|
+
+## References
+
+https://huggingface.co/suayptalha/medBERT-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sent_pcscibert_cased_en.md b/docs/_posts/ahmedlone127/2025-01-27-sent_pcscibert_cased_en.md
new file mode 100644
index 00000000000000..841c0b44b9d2ef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sent_pcscibert_cased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_pcscibert_cased BertSentenceEmbeddings from jmzk96
+author: John Snow Labs
+name: sent_pcscibert_cased
+date: 2025-01-27
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_pcscibert_cased` is a English model originally trained by jmzk96.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_pcscibert_cased_en_5.5.1_3.0_1738015795956.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_pcscibert_cased_en_5.5.1_3.0_1738015795956.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_pcscibert_cased","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_pcscibert_cased","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_pcscibert_cased|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|409.8 MB|
+
+## References
+
+https://huggingface.co/jmzk96/PCSciBERT_cased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sent_pcscibert_cased_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-sent_pcscibert_cased_pipeline_en.md
new file mode 100644
index 00000000000000..493922f9629e71
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sent_pcscibert_cased_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_pcscibert_cased_pipeline pipeline BertSentenceEmbeddings from jmzk96
+author: John Snow Labs
+name: sent_pcscibert_cased_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_pcscibert_cased_pipeline` is a English model originally trained by jmzk96.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_pcscibert_cased_pipeline_en_5.5.1_3.0_1738015816172.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_pcscibert_cased_pipeline_en_5.5.1_3.0_1738015816172.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_pcscibert_cased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_pcscibert_cased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_pcscibert_cased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.4 MB|
+
+## References
+
+https://huggingface.co/jmzk96/PCSciBERT_cased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sent_pcscibert_uncased_en.md b/docs/_posts/ahmedlone127/2025-01-27-sent_pcscibert_uncased_en.md
new file mode 100644
index 00000000000000..1c4ed6e293a75a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sent_pcscibert_uncased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_pcscibert_uncased BertSentenceEmbeddings from jmzk96
+author: John Snow Labs
+name: sent_pcscibert_uncased
+date: 2025-01-27
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_pcscibert_uncased` is a English model originally trained by jmzk96.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_pcscibert_uncased_en_5.5.1_3.0_1738015566511.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_pcscibert_uncased_en_5.5.1_3.0_1738015566511.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_pcscibert_uncased","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_pcscibert_uncased","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_pcscibert_uncased|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|409.9 MB|
+
+## References
+
+https://huggingface.co/jmzk96/PCSciBERT_uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sent_pcscibert_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-sent_pcscibert_uncased_pipeline_en.md
new file mode 100644
index 00000000000000..eb407965b6c40e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sent_pcscibert_uncased_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_pcscibert_uncased_pipeline pipeline BertSentenceEmbeddings from jmzk96
+author: John Snow Labs
+name: sent_pcscibert_uncased_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_pcscibert_uncased_pipeline` is a English model originally trained by jmzk96.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_pcscibert_uncased_pipeline_en_5.5.1_3.0_1738015587135.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_pcscibert_uncased_pipeline_en_5.5.1_3.0_1738015587135.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_pcscibert_uncased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_pcscibert_uncased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_pcscibert_uncased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.5 MB|
+
+## References
+
+https://huggingface.co/jmzk96/PCSciBERT_uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sent_portuguese_caselawbert_en.md b/docs/_posts/ahmedlone127/2025-01-27-sent_portuguese_caselawbert_en.md
new file mode 100644
index 00000000000000..d5aa8353e7284e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sent_portuguese_caselawbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_portuguese_caselawbert BertSentenceEmbeddings from SharedBailii
+author: John Snow Labs
+name: sent_portuguese_caselawbert
+date: 2025-01-27
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_portuguese_caselawbert` is a English model originally trained by SharedBailii.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_portuguese_caselawbert_en_5.5.1_3.0_1737941169619.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_portuguese_caselawbert_en_5.5.1_3.0_1737941169619.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_portuguese_caselawbert","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_portuguese_caselawbert","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_portuguese_caselawbert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|406.7 MB|
+
+## References
+
+https://huggingface.co/SharedBailii/PT-CaseLawBert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sent_portuguese_caselawbert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-sent_portuguese_caselawbert_pipeline_en.md
new file mode 100644
index 00000000000000..b3c67f78b3de50
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sent_portuguese_caselawbert_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_portuguese_caselawbert_pipeline pipeline BertSentenceEmbeddings from SharedBailii
+author: John Snow Labs
+name: sent_portuguese_caselawbert_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_portuguese_caselawbert_pipeline` is a English model originally trained by SharedBailii.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_portuguese_caselawbert_pipeline_en_5.5.1_3.0_1737941191205.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_portuguese_caselawbert_pipeline_en_5.5.1_3.0_1737941191205.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_portuguese_caselawbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_portuguese_caselawbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_portuguese_caselawbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.3 MB|
+
+## References
+
+https://huggingface.co/SharedBailii/PT-CaseLawBert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sent_problema_topicos_en.md b/docs/_posts/ahmedlone127/2025-01-27-sent_problema_topicos_en.md
new file mode 100644
index 00000000000000..275ef222a08bdf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sent_problema_topicos_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_problema_topicos BertSentenceEmbeddings from germanchura
+author: John Snow Labs
+name: sent_problema_topicos
+date: 2025-01-27
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_problema_topicos` is a English model originally trained by germanchura.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_problema_topicos_en_5.5.1_3.0_1737942095666.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_problema_topicos_en_5.5.1_3.0_1737942095666.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_problema_topicos","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_problema_topicos","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_problema_topicos|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/germanchura/problema_topicos
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sent_problema_topicos_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-sent_problema_topicos_pipeline_en.md
new file mode 100644
index 00000000000000..d37b821a6a43ba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sent_problema_topicos_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_problema_topicos_pipeline pipeline BertSentenceEmbeddings from germanchura
+author: John Snow Labs
+name: sent_problema_topicos_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_problema_topicos_pipeline` is a English model originally trained by germanchura.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_problema_topicos_pipeline_en_5.5.1_3.0_1737942117281.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_problema_topicos_pipeline_en_5.5.1_3.0_1737942117281.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_problema_topicos_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_problema_topicos_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_problema_topicos_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.8 MB|
+
+## References
+
+https://huggingface.co/germanchura/problema_topicos
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sent_product_title_encoder_product_en.md b/docs/_posts/ahmedlone127/2025-01-27-sent_product_title_encoder_product_en.md
new file mode 100644
index 00000000000000..c87da2116d0261
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sent_product_title_encoder_product_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_product_title_encoder_product BertSentenceEmbeddings from kwakwak
+author: John Snow Labs
+name: sent_product_title_encoder_product
+date: 2025-01-27
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_product_title_encoder_product` is a English model originally trained by kwakwak.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_product_title_encoder_product_en_5.5.1_3.0_1737941238350.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_product_title_encoder_product_en_5.5.1_3.0_1737941238350.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_product_title_encoder_product","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_product_title_encoder_product","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_product_title_encoder_product|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|84.6 MB|
+
+## References
+
+https://huggingface.co/kwakwak/product_title_encoder-product
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sent_product_title_encoder_product_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-sent_product_title_encoder_product_pipeline_en.md
new file mode 100644
index 00000000000000..2b0fed0cb3dedb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sent_product_title_encoder_product_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_product_title_encoder_product_pipeline pipeline BertSentenceEmbeddings from kwakwak
+author: John Snow Labs
+name: sent_product_title_encoder_product_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_product_title_encoder_product_pipeline` is a English model originally trained by kwakwak.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_product_title_encoder_product_pipeline_en_5.5.1_3.0_1737941242670.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_product_title_encoder_product_pipeline_en_5.5.1_3.0_1737941242670.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_product_title_encoder_product_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_product_title_encoder_product_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_product_title_encoder_product_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|85.2 MB|
+
+## References
+
+https://huggingface.co/kwakwak/product_title_encoder-product
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sent_simlm_base_wiki100w_en.md b/docs/_posts/ahmedlone127/2025-01-27-sent_simlm_base_wiki100w_en.md
new file mode 100644
index 00000000000000..4ec07e2c3ace6f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sent_simlm_base_wiki100w_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_simlm_base_wiki100w BertSentenceEmbeddings from intfloat
+author: John Snow Labs
+name: sent_simlm_base_wiki100w
+date: 2025-01-27
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_simlm_base_wiki100w` is a English model originally trained by intfloat.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_simlm_base_wiki100w_en_5.5.1_3.0_1737941295509.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_simlm_base_wiki100w_en_5.5.1_3.0_1737941295509.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_simlm_base_wiki100w","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_simlm_base_wiki100w","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_simlm_base_wiki100w|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.8 MB|
+
+## References
+
+https://huggingface.co/intfloat/simlm-base-wiki100w
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sent_simlm_base_wiki100w_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-sent_simlm_base_wiki100w_pipeline_en.md
new file mode 100644
index 00000000000000..2a495c83c89e6e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sent_simlm_base_wiki100w_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_simlm_base_wiki100w_pipeline pipeline BertSentenceEmbeddings from intfloat
+author: John Snow Labs
+name: sent_simlm_base_wiki100w_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_simlm_base_wiki100w_pipeline` is a English model originally trained by intfloat.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_simlm_base_wiki100w_pipeline_en_5.5.1_3.0_1737941317485.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_simlm_base_wiki100w_pipeline_en_5.5.1_3.0_1737941317485.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_simlm_base_wiki100w_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_simlm_base_wiki100w_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_simlm_base_wiki100w_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|408.3 MB|
+
+## References
+
+https://huggingface.co/intfloat/simlm-base-wiki100w
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sentiment_analysis_model_1_en.md b/docs/_posts/ahmedlone127/2025-01-27-sentiment_analysis_model_1_en.md
new file mode 100644
index 00000000000000..8a3be195728820
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sentiment_analysis_model_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sentiment_analysis_model_1 DistilBertForSequenceClassification from Vic21MC
+author: John Snow Labs
+name: sentiment_analysis_model_1
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentiment_analysis_model_1` is a English model originally trained by Vic21MC.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentiment_analysis_model_1_en_5.5.1_3.0_1737939643307.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentiment_analysis_model_1_en_5.5.1_3.0_1737939643307.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("sentiment_analysis_model_1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("sentiment_analysis_model_1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sentiment_analysis_model_1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Vic21MC/sentiment-analysis-model-1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sentiment_analysis_model_1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-sentiment_analysis_model_1_pipeline_en.md
new file mode 100644
index 00000000000000..3b07a63a76ef61
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sentiment_analysis_model_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English sentiment_analysis_model_1_pipeline pipeline DistilBertForSequenceClassification from Vic21MC
+author: John Snow Labs
+name: sentiment_analysis_model_1_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentiment_analysis_model_1_pipeline` is a English model originally trained by Vic21MC.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentiment_analysis_model_1_pipeline_en_5.5.1_3.0_1737939657054.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentiment_analysis_model_1_pipeline_en_5.5.1_3.0_1737939657054.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sentiment_analysis_model_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sentiment_analysis_model_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sentiment_analysis_model_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Vic21MC/sentiment-analysis-model-1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sft_mt5_pile_ner_test_seq2seq_format_en.md b/docs/_posts/ahmedlone127/2025-01-27-sft_mt5_pile_ner_test_seq2seq_format_en.md
new file mode 100644
index 00000000000000..319e7b0a7070e4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sft_mt5_pile_ner_test_seq2seq_format_en.md
@@ -0,0 +1,88 @@
+---
+layout: model
+title: English sft_mt5_pile_ner_test_seq2seq_format T5Transformer from nqv2291
+author: John Snow Labs
+name: sft_mt5_pile_ner_test_seq2seq_format
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sft_mt5_pile_ner_test_seq2seq_format` is a English model originally trained by nqv2291.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sft_mt5_pile_ner_test_seq2seq_format_en_5.5.1_3.0_1737990846749.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sft_mt5_pile_ner_test_seq2seq_format_en_5.5.1_3.0_1737990846749.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("sft_mt5_pile_ner_test_seq2seq_format","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("sft_mt5_pile_ner_test_seq2seq_format", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sft_mt5_pile_ner_test_seq2seq_format|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|2.3 GB|
+
+## References
+
+References
+
+https://huggingface.co/nqv2291/sft_mt5-Pile-NER-test-seq2seq-format
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sft_mt5_pile_ner_test_seq2seq_format_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-sft_mt5_pile_ner_test_seq2seq_format_pipeline_en.md
new file mode 100644
index 00000000000000..d255a45e81cc6d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sft_mt5_pile_ner_test_seq2seq_format_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English sft_mt5_pile_ner_test_seq2seq_format_pipeline pipeline T5Transformer from vietnqw
+author: John Snow Labs
+name: sft_mt5_pile_ner_test_seq2seq_format_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sft_mt5_pile_ner_test_seq2seq_format_pipeline` is a English model originally trained by vietnqw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sft_mt5_pile_ner_test_seq2seq_format_pipeline_en_5.5.1_3.0_1737991142126.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sft_mt5_pile_ner_test_seq2seq_format_pipeline_en_5.5.1_3.0_1737991142126.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sft_mt5_pile_ner_test_seq2seq_format_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sft_mt5_pile_ner_test_seq2seq_format_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sft_mt5_pile_ner_test_seq2seq_format_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|2.3 GB|
+
+## References
+
+https://huggingface.co/vietnqw/sft_mt5-Pile-NER-test-seq2seq-format
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sign_language_classification_heem2_en.md b/docs/_posts/ahmedlone127/2025-01-27-sign_language_classification_heem2_en.md
new file mode 100644
index 00000000000000..3eec13c4e84a6d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sign_language_classification_heem2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sign_language_classification_heem2 ViTForImageClassification from Heem2
+author: John Snow Labs
+name: sign_language_classification_heem2
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sign_language_classification_heem2` is a English model originally trained by Heem2.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sign_language_classification_heem2_en_5.5.1_3.0_1737974374083.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sign_language_classification_heem2_en_5.5.1_3.0_1737974374083.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""sign_language_classification_heem2","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("sign_language_classification_heem2","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sign_language_classification_heem2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.4 MB|
+
+## References
+
+https://huggingface.co/Heem2/sign-language-classification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sign_language_classification_heem2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-sign_language_classification_heem2_pipeline_en.md
new file mode 100644
index 00000000000000..bebdec40225762
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sign_language_classification_heem2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English sign_language_classification_heem2_pipeline pipeline ViTForImageClassification from Heem2
+author: John Snow Labs
+name: sign_language_classification_heem2_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sign_language_classification_heem2_pipeline` is a English model originally trained by Heem2.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sign_language_classification_heem2_pipeline_en_5.5.1_3.0_1737974392117.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sign_language_classification_heem2_pipeline_en_5.5.1_3.0_1737974392117.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sign_language_classification_heem2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sign_language_classification_heem2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sign_language_classification_heem2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.4 MB|
+
+## References
+
+https://huggingface.co/Heem2/sign-language-classification
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-simple_conversation_t5_en.md b/docs/_posts/ahmedlone127/2025-01-27-simple_conversation_t5_en.md
new file mode 100644
index 00000000000000..36273959bfef5c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-simple_conversation_t5_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English simple_conversation_t5 T5Transformer from belyakoff
+author: John Snow Labs
+name: simple_conversation_t5
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`simple_conversation_t5` is a English model originally trained by belyakoff.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/simple_conversation_t5_en_5.5.1_3.0_1737988973885.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/simple_conversation_t5_en_5.5.1_3.0_1737988973885.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("simple_conversation_t5","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("simple_conversation_t5", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|simple_conversation_t5|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|927.1 MB|
+
+## References
+
+https://huggingface.co/belyakoff/simple-conversation-t5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-simple_conversation_t5_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-simple_conversation_t5_pipeline_en.md
new file mode 100644
index 00000000000000..0bd794e72b92c9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-simple_conversation_t5_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English simple_conversation_t5_pipeline pipeline T5Transformer from belyakoff
+author: John Snow Labs
+name: simple_conversation_t5_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`simple_conversation_t5_pipeline` is a English model originally trained by belyakoff.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/simple_conversation_t5_pipeline_en_5.5.1_3.0_1737989021501.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/simple_conversation_t5_pipeline_en_5.5.1_3.0_1737989021501.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("simple_conversation_t5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("simple_conversation_t5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|simple_conversation_t5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|927.1 MB|
+
+## References
+
+https://huggingface.co/belyakoff/simple-conversation-t5
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-simple_korean_translator_en.md b/docs/_posts/ahmedlone127/2025-01-27-simple_korean_translator_en.md
new file mode 100644
index 00000000000000..f37d05798a600b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-simple_korean_translator_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English simple_korean_translator T5Transformer from ehottl
+author: John Snow Labs
+name: simple_korean_translator
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`simple_korean_translator` is a English model originally trained by ehottl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/simple_korean_translator_en_5.5.1_3.0_1737946475079.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/simple_korean_translator_en_5.5.1_3.0_1737946475079.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("simple_korean_translator","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("simple_korean_translator", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|simple_korean_translator|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/ehottl/simple-korean-translator
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-simple_korean_translator_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-simple_korean_translator_pipeline_en.md
new file mode 100644
index 00000000000000..87a5ce4274ea25
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-simple_korean_translator_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English simple_korean_translator_pipeline pipeline T5Transformer from ehottl
+author: John Snow Labs
+name: simple_korean_translator_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`simple_korean_translator_pipeline` is a English model originally trained by ehottl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/simple_korean_translator_pipeline_en_5.5.1_3.0_1737946540023.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/simple_korean_translator_pipeline_en_5.5.1_3.0_1737946540023.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("simple_korean_translator_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("simple_korean_translator_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|simple_korean_translator_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/ehottl/simple-korean-translator
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-skintelligent_wrinkles_en.md b/docs/_posts/ahmedlone127/2025-01-27-skintelligent_wrinkles_en.md
new file mode 100644
index 00000000000000..9eb8edd34e8c44
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-skintelligent_wrinkles_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English skintelligent_wrinkles ViTForImageClassification from imfarzanansari
+author: John Snow Labs
+name: skintelligent_wrinkles
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`skintelligent_wrinkles` is a English model originally trained by imfarzanansari.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/skintelligent_wrinkles_en_5.5.1_3.0_1738021244405.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/skintelligent_wrinkles_en_5.5.1_3.0_1738021244405.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""skintelligent_wrinkles","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("skintelligent_wrinkles","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|skintelligent_wrinkles|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/imfarzanansari/skintelligent-wrinkles
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-skintelligent_wrinkles_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-skintelligent_wrinkles_pipeline_en.md
new file mode 100644
index 00000000000000..375074e61f37c2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-skintelligent_wrinkles_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English skintelligent_wrinkles_pipeline pipeline ViTForImageClassification from imfarzanansari
+author: John Snow Labs
+name: skintelligent_wrinkles_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`skintelligent_wrinkles_pipeline` is a English model originally trained by imfarzanansari.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/skintelligent_wrinkles_pipeline_en_5.5.1_3.0_1738021260848.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/skintelligent_wrinkles_pipeline_en_5.5.1_3.0_1738021260848.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("skintelligent_wrinkles_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("skintelligent_wrinkles_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|skintelligent_wrinkles_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/imfarzanansari/skintelligent-wrinkles
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-slm_custom_model_5_2k_en.md b/docs/_posts/ahmedlone127/2025-01-27-slm_custom_model_5_2k_en.md
new file mode 100644
index 00000000000000..4a12bd4a80a124
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-slm_custom_model_5_2k_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English slm_custom_model_5_2k T5Transformer from karthikeyan-r
+author: John Snow Labs
+name: slm_custom_model_5_2k
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`slm_custom_model_5_2k` is a English model originally trained by karthikeyan-r.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/slm_custom_model_5_2k_en_5.5.1_3.0_1737989013286.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/slm_custom_model_5_2k_en_5.5.1_3.0_1737989013286.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("slm_custom_model_5_2k","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("slm_custom_model_5_2k", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|slm_custom_model_5_2k|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|277.5 MB|
+
+## References
+
+https://huggingface.co/karthikeyan-r/slm-custom-model_5_2K
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-slm_custom_model_5_2k_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-slm_custom_model_5_2k_pipeline_en.md
new file mode 100644
index 00000000000000..581eec29ec7415
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-slm_custom_model_5_2k_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English slm_custom_model_5_2k_pipeline pipeline T5Transformer from karthikeyan-r
+author: John Snow Labs
+name: slm_custom_model_5_2k_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`slm_custom_model_5_2k_pipeline` is a English model originally trained by karthikeyan-r.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/slm_custom_model_5_2k_pipeline_en_5.5.1_3.0_1737989029679.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/slm_custom_model_5_2k_pipeline_en_5.5.1_3.0_1737989029679.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("slm_custom_model_5_2k_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("slm_custom_model_5_2k_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|slm_custom_model_5_2k_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|277.5 MB|
+
+## References
+
+https://huggingface.co/karthikeyan-r/slm-custom-model_5_2K
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-slm_custom_model_5_en.md b/docs/_posts/ahmedlone127/2025-01-27-slm_custom_model_5_en.md
new file mode 100644
index 00000000000000..bd0d2832bc6dff
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-slm_custom_model_5_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English slm_custom_model_5 T5Transformer from karthikeyan-r
+author: John Snow Labs
+name: slm_custom_model_5
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`slm_custom_model_5` is a English model originally trained by karthikeyan-r.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/slm_custom_model_5_en_5.5.1_3.0_1737989143192.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/slm_custom_model_5_en_5.5.1_3.0_1737989143192.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("slm_custom_model_5","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("slm_custom_model_5", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|slm_custom_model_5|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|273.8 MB|
+
+## References
+
+https://huggingface.co/karthikeyan-r/slm-custom-model_5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-slm_custom_model_5_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-slm_custom_model_5_pipeline_en.md
new file mode 100644
index 00000000000000..ca190b1f2e57ac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-slm_custom_model_5_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English slm_custom_model_5_pipeline pipeline T5Transformer from karthikeyan-r
+author: John Snow Labs
+name: slm_custom_model_5_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`slm_custom_model_5_pipeline` is a English model originally trained by karthikeyan-r.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/slm_custom_model_5_pipeline_en_5.5.1_3.0_1737989159940.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/slm_custom_model_5_pipeline_en_5.5.1_3.0_1737989159940.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("slm_custom_model_5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("slm_custom_model_5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|slm_custom_model_5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|273.8 MB|
+
+## References
+
+https://huggingface.co/karthikeyan-r/slm-custom-model_5
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-slovak_t5_base_pipeline_sk.md b/docs/_posts/ahmedlone127/2025-01-27-slovak_t5_base_pipeline_sk.md
new file mode 100644
index 00000000000000..c56ebfb2fae45a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-slovak_t5_base_pipeline_sk.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Slovak slovak_t5_base_pipeline pipeline T5Transformer from TUKE-KEMT
+author: John Snow Labs
+name: slovak_t5_base_pipeline
+date: 2025-01-27
+tags: [sk, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: sk
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`slovak_t5_base_pipeline` is a Slovak model originally trained by TUKE-KEMT.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/slovak_t5_base_pipeline_sk_5.5.1_3.0_1738001875938.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/slovak_t5_base_pipeline_sk_5.5.1_3.0_1738001875938.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("slovak_t5_base_pipeline", lang = "sk")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("slovak_t5_base_pipeline", lang = "sk")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|slovak_t5_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|sk|
+|Size:|1.8 GB|
+
+## References
+
+https://huggingface.co/TUKE-KEMT/slovak-t5-base
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-slovak_t5_base_sk.md b/docs/_posts/ahmedlone127/2025-01-27-slovak_t5_base_sk.md
new file mode 100644
index 00000000000000..4b6190978012ed
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-slovak_t5_base_sk.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Slovak slovak_t5_base T5Transformer from TUKE-KEMT
+author: John Snow Labs
+name: slovak_t5_base
+date: 2025-01-27
+tags: [sk, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: sk
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`slovak_t5_base` is a Slovak model originally trained by TUKE-KEMT.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/slovak_t5_base_sk_5.5.1_3.0_1738001781793.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/slovak_t5_base_sk_5.5.1_3.0_1738001781793.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("slovak_t5_base","sk") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("slovak_t5_base", "sk")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|slovak_t5_base|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|sk|
+|Size:|1.8 GB|
+
+## References
+
+https://huggingface.co/TUKE-KEMT/slovak-t5-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-smartbert_v3_en.md b/docs/_posts/ahmedlone127/2025-01-27-smartbert_v3_en.md
new file mode 100644
index 00000000000000..c56afcfcf8be8b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-smartbert_v3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English smartbert_v3 RoBertaEmbeddings from web3se
+author: John Snow Labs
+name: smartbert_v3
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`smartbert_v3` is a English model originally trained by web3se.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/smartbert_v3_en_5.5.1_3.0_1738019982170.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/smartbert_v3_en_5.5.1_3.0_1738019982170.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("smartbert_v3","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("smartbert_v3","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|smartbert_v3|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|466.0 MB|
+
+## References
+
+https://huggingface.co/web3se/SmartBERT-v3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-smartbert_v3_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-smartbert_v3_pipeline_en.md
new file mode 100644
index 00000000000000..8bd1b6eeea544e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-smartbert_v3_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English smartbert_v3_pipeline pipeline RoBertaEmbeddings from web3se
+author: John Snow Labs
+name: smartbert_v3_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`smartbert_v3_pipeline` is a English model originally trained by web3se.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/smartbert_v3_pipeline_en_5.5.1_3.0_1738020006333.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/smartbert_v3_pipeline_en_5.5.1_3.0_1738020006333.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("smartbert_v3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("smartbert_v3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|smartbert_v3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.0 MB|
+
+## References
+
+https://huggingface.co/web3se/SmartBERT-v3
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-soa_model_en.md b/docs/_posts/ahmedlone127/2025-01-27-soa_model_en.md
new file mode 100644
index 00000000000000..b4449e7cc685a4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-soa_model_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English soa_model T5Transformer from robertauny
+author: John Snow Labs
+name: soa_model
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`soa_model` is a English model originally trained by robertauny.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/soa_model_en_5.5.1_3.0_1737979865060.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/soa_model_en_5.5.1_3.0_1737979865060.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("soa_model","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("soa_model", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|soa_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|148.0 MB|
+
+## References
+
+https://huggingface.co/robertauny/SOA-Model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-soa_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-soa_model_pipeline_en.md
new file mode 100644
index 00000000000000..3da441361f645d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-soa_model_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English soa_model_pipeline pipeline T5Transformer from robertauny
+author: John Snow Labs
+name: soa_model_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`soa_model_pipeline` is a English model originally trained by robertauny.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/soa_model_pipeline_en_5.5.1_3.0_1737979913513.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/soa_model_pipeline_en_5.5.1_3.0_1737979913513.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("soa_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("soa_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|soa_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|148.0 MB|
+
+## References
+
+https://huggingface.co/robertauny/SOA-Model
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sorani_spell_correction_model_en.md b/docs/_posts/ahmedlone127/2025-01-27-sorani_spell_correction_model_en.md
new file mode 100644
index 00000000000000..3e382f970223ed
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sorani_spell_correction_model_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English sorani_spell_correction_model T5Transformer from 3ed0k4
+author: John Snow Labs
+name: sorani_spell_correction_model
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sorani_spell_correction_model` is a English model originally trained by 3ed0k4.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sorani_spell_correction_model_en_5.5.1_3.0_1737992333981.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sorani_spell_correction_model_en_5.5.1_3.0_1737992333981.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("sorani_spell_correction_model","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("sorani_spell_correction_model", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sorani_spell_correction_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|148.0 MB|
+
+## References
+
+https://huggingface.co/3ed0k4/sorani-spell-correction-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sorani_spell_correction_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-sorani_spell_correction_model_pipeline_en.md
new file mode 100644
index 00000000000000..fea2d2b1e20789
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sorani_spell_correction_model_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English sorani_spell_correction_model_pipeline pipeline T5Transformer from 3ed0k4
+author: John Snow Labs
+name: sorani_spell_correction_model_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sorani_spell_correction_model_pipeline` is a English model originally trained by 3ed0k4.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sorani_spell_correction_model_pipeline_en_5.5.1_3.0_1737992381720.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sorani_spell_correction_model_pipeline_en_5.5.1_3.0_1737992381720.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sorani_spell_correction_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sorani_spell_correction_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sorani_spell_correction_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|148.0 MB|
+
+## References
+
+https://huggingface.co/3ed0k4/sorani-spell-correction-model
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-speech_latex_en.md b/docs/_posts/ahmedlone127/2025-01-27-speech_latex_en.md
new file mode 100644
index 00000000000000..f140fa4f5cc21c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-speech_latex_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English speech_latex T5Transformer from vinalal
+author: John Snow Labs
+name: speech_latex
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`speech_latex` is a English model originally trained by vinalal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/speech_latex_en_5.5.1_3.0_1737992159139.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/speech_latex_en_5.5.1_3.0_1737992159139.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("speech_latex","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("speech_latex", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|speech_latex|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|265.8 MB|
+
+## References
+
+https://huggingface.co/vinalal/speech-latex
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-speech_latex_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-speech_latex_pipeline_en.md
new file mode 100644
index 00000000000000..c7da5403c787e0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-speech_latex_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English speech_latex_pipeline pipeline T5Transformer from vinalal
+author: John Snow Labs
+name: speech_latex_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`speech_latex_pipeline` is a English model originally trained by vinalal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/speech_latex_pipeline_en_5.5.1_3.0_1737992179028.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/speech_latex_pipeline_en_5.5.1_3.0_1737992179028.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("speech_latex_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("speech_latex_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|speech_latex_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|265.8 MB|
+
+## References
+
+https://huggingface.co/vinalal/speech-latex
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sqlt5_en.md b/docs/_posts/ahmedlone127/2025-01-27-sqlt5_en.md
new file mode 100644
index 00000000000000..cd02bc4b045893
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sqlt5_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English sqlt5 T5Transformer from Sarathbabu-Karunanithi
+author: John Snow Labs
+name: sqlt5
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sqlt5` is a English model originally trained by Sarathbabu-Karunanithi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sqlt5_en_5.5.1_3.0_1737945301368.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sqlt5_en_5.5.1_3.0_1737945301368.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("sqlt5","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("sqlt5", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sqlt5|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Sarathbabu-Karunanithi/SQLT5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-sqlt5_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-sqlt5_pipeline_en.md
new file mode 100644
index 00000000000000..4625f8ffdc2d6c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-sqlt5_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English sqlt5_pipeline pipeline T5Transformer from Sarathbabu-Karunanithi
+author: John Snow Labs
+name: sqlt5_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sqlt5_pipeline` is a English model originally trained by Sarathbabu-Karunanithi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sqlt5_pipeline_en_5.5.1_3.0_1737945354221.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sqlt5_pipeline_en_5.5.1_3.0_1737945354221.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sqlt5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sqlt5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sqlt5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Sarathbabu-Karunanithi/SQLT5
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-substitution_cipher_alphabet_eng_en.md b/docs/_posts/ahmedlone127/2025-01-27-substitution_cipher_alphabet_eng_en.md
new file mode 100644
index 00000000000000..7d79b4f640ccc6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-substitution_cipher_alphabet_eng_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English substitution_cipher_alphabet_eng T5Transformer from Cipher-AI
+author: John Snow Labs
+name: substitution_cipher_alphabet_eng
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`substitution_cipher_alphabet_eng` is a English model originally trained by Cipher-AI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/substitution_cipher_alphabet_eng_en_5.5.1_3.0_1737979157263.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/substitution_cipher_alphabet_eng_en_5.5.1_3.0_1737979157263.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("substitution_cipher_alphabet_eng","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("substitution_cipher_alphabet_eng", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|substitution_cipher_alphabet_eng|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|921.8 MB|
+
+## References
+
+https://huggingface.co/Cipher-AI/Substitution-Cipher-Alphabet-Eng
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-substitution_cipher_alphabet_eng_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-substitution_cipher_alphabet_eng_pipeline_en.md
new file mode 100644
index 00000000000000..3e1c8f74b0232c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-substitution_cipher_alphabet_eng_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English substitution_cipher_alphabet_eng_pipeline pipeline T5Transformer from Cipher-AI
+author: John Snow Labs
+name: substitution_cipher_alphabet_eng_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`substitution_cipher_alphabet_eng_pipeline` is a English model originally trained by Cipher-AI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/substitution_cipher_alphabet_eng_pipeline_en_5.5.1_3.0_1737979204238.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/substitution_cipher_alphabet_eng_pipeline_en_5.5.1_3.0_1737979204238.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("substitution_cipher_alphabet_eng_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("substitution_cipher_alphabet_eng_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|substitution_cipher_alphabet_eng_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|921.8 MB|
+
+## References
+
+https://huggingface.co/Cipher-AI/Substitution-Cipher-Alphabet-Eng
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-substitution_cipher_text_eng_en.md b/docs/_posts/ahmedlone127/2025-01-27-substitution_cipher_text_eng_en.md
new file mode 100644
index 00000000000000..9fa46a73e226c9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-substitution_cipher_text_eng_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English substitution_cipher_text_eng T5Transformer from Cipher-AI
+author: John Snow Labs
+name: substitution_cipher_text_eng
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`substitution_cipher_text_eng` is a English model originally trained by Cipher-AI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/substitution_cipher_text_eng_en_5.5.1_3.0_1737980970465.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/substitution_cipher_text_eng_en_5.5.1_3.0_1737980970465.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("substitution_cipher_text_eng","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("substitution_cipher_text_eng", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|substitution_cipher_text_eng|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|926.9 MB|
+
+## References
+
+https://huggingface.co/Cipher-AI/Substitution-Cipher-Text-Eng
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-substitution_cipher_text_eng_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-substitution_cipher_text_eng_pipeline_en.md
new file mode 100644
index 00000000000000..743776448ad062
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-substitution_cipher_text_eng_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English substitution_cipher_text_eng_pipeline pipeline T5Transformer from Cipher-AI
+author: John Snow Labs
+name: substitution_cipher_text_eng_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`substitution_cipher_text_eng_pipeline` is a English model originally trained by Cipher-AI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/substitution_cipher_text_eng_pipeline_en_5.5.1_3.0_1737981018088.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/substitution_cipher_text_eng_pipeline_en_5.5.1_3.0_1737981018088.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("substitution_cipher_text_eng_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("substitution_cipher_text_eng_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|substitution_cipher_text_eng_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|926.9 MB|
+
+## References
+
+https://huggingface.co/Cipher-AI/Substitution-Cipher-Text-Eng
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-supcon_en.md b/docs/_posts/ahmedlone127/2025-01-27-supcon_en.md
new file mode 100644
index 00000000000000..ca57a59fd431c1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-supcon_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English supcon RoBertaEmbeddings from igandarillas
+author: John Snow Labs
+name: supcon
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`supcon` is a English model originally trained by igandarillas.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/supcon_en_5.5.1_3.0_1737965831276.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/supcon_en_5.5.1_3.0_1737965831276.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("supcon","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("supcon","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|supcon|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|464.1 MB|
+
+## References
+
+https://huggingface.co/igandarillas/supcon
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-supcon_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-supcon_pipeline_en.md
new file mode 100644
index 00000000000000..53311d04120580
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-supcon_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English supcon_pipeline pipeline RoBertaEmbeddings from igandarillas
+author: John Snow Labs
+name: supcon_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`supcon_pipeline` is a English model originally trained by igandarillas.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/supcon_pipeline_en_5.5.1_3.0_1737965855216.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/supcon_pipeline_en_5.5.1_3.0_1737965855216.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("supcon_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("supcon_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|supcon_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|464.2 MB|
+
+## References
+
+https://huggingface.co/igandarillas/supcon
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-switch_med_en.md b/docs/_posts/ahmedlone127/2025-01-27-switch_med_en.md
new file mode 100644
index 00000000000000..1bed2961cda43b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-switch_med_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English switch_med GPT2Transformer from iliyan14
+author: John Snow Labs
+name: switch_med
+date: 2025-01-27
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`switch_med` is a English model originally trained by iliyan14.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/switch_med_en_5.5.1_3.0_1737995805978.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/switch_med_en_5.5.1_3.0_1737995805978.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("switch_med","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("switch_med","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|switch_med|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/iliyan14/switch-Med
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-switch_med_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-switch_med_pipeline_en.md
new file mode 100644
index 00000000000000..f498604f641661
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-switch_med_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English switch_med_pipeline pipeline GPT2Transformer from iliyan14
+author: John Snow Labs
+name: switch_med_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`switch_med_pipeline` is a English model originally trained by iliyan14.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/switch_med_pipeline_en_5.5.1_3.0_1737995829970.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/switch_med_pipeline_en_5.5.1_3.0_1737995829970.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("switch_med_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("switch_med_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|switch_med_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/iliyan14/switch-Med
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-synthesis_response_en.md b/docs/_posts/ahmedlone127/2025-01-27-synthesis_response_en.md
new file mode 100644
index 00000000000000..e1682938504b64
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-synthesis_response_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English synthesis_response T5Transformer from suriya7
+author: John Snow Labs
+name: synthesis_response
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`synthesis_response` is a English model originally trained by suriya7.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/synthesis_response_en_5.5.1_3.0_1737963959385.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/synthesis_response_en_5.5.1_3.0_1737963959385.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("synthesis_response","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("synthesis_response", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|synthesis_response|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/suriya7/synthesis-response
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-synthesis_response_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-synthesis_response_pipeline_en.md
new file mode 100644
index 00000000000000..1b360475a1404e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-synthesis_response_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English synthesis_response_pipeline pipeline T5Transformer from suriya7
+author: John Snow Labs
+name: synthesis_response_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`synthesis_response_pipeline` is a English model originally trained by suriya7.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/synthesis_response_pipeline_en_5.5.1_3.0_1737964010085.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/synthesis_response_pipeline_en_5.5.1_3.0_1737964010085.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("synthesis_response_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("synthesis_response_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|synthesis_response_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/suriya7/synthesis-response
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_base_bbc_news_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_base_bbc_news_en.md
new file mode 100644
index 00000000000000..ea56506a276470
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_base_bbc_news_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_base_bbc_news T5Transformer from Shriyans
+author: John Snow Labs
+name: t5_base_bbc_news
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_base_bbc_news` is a English model originally trained by Shriyans.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_base_bbc_news_en_5.5.1_3.0_1737962479094.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_base_bbc_news_en_5.5.1_3.0_1737962479094.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_base_bbc_news","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_base_bbc_news", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_base_bbc_news|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|919.7 MB|
+
+## References
+
+https://huggingface.co/Shriyans/t5-base-bbc-news
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_base_bbc_news_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_base_bbc_news_pipeline_en.md
new file mode 100644
index 00000000000000..881a2627724c47
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_base_bbc_news_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_base_bbc_news_pipeline pipeline T5Transformer from Shriyans
+author: John Snow Labs
+name: t5_base_bbc_news_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_base_bbc_news_pipeline` is a English model originally trained by Shriyans.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_base_bbc_news_pipeline_en_5.5.1_3.0_1737962526619.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_base_bbc_news_pipeline_en_5.5.1_3.0_1737962526619.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_base_bbc_news_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_base_bbc_news_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_base_bbc_news_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|919.8 MB|
+
+## References
+
+https://huggingface.co/Shriyans/t5-base-bbc-news
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_base_p_l_akk_english_20241108_111409_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_base_p_l_akk_english_20241108_111409_en.md
new file mode 100644
index 00000000000000..354211f7b64b8b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_base_p_l_akk_english_20241108_111409_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_base_p_l_akk_english_20241108_111409 T5Transformer from Thalesian
+author: John Snow Labs
+name: t5_base_p_l_akk_english_20241108_111409
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_base_p_l_akk_english_20241108_111409` is a English model originally trained by Thalesian.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_base_p_l_akk_english_20241108_111409_en_5.5.1_3.0_1737945035588.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_base_p_l_akk_english_20241108_111409_en_5.5.1_3.0_1737945035588.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_base_p_l_akk_english_20241108_111409","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_base_p_l_akk_english_20241108_111409", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_base_p_l_akk_english_20241108_111409|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|2.0 GB|
+
+## References
+
+https://huggingface.co/Thalesian/t5-base-p-l-akk-en-20241108-111409
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_base_p_l_akk_english_20241108_111409_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_base_p_l_akk_english_20241108_111409_pipeline_en.md
new file mode 100644
index 00000000000000..c0d2bf3ba540ba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_base_p_l_akk_english_20241108_111409_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_base_p_l_akk_english_20241108_111409_pipeline pipeline T5Transformer from Thalesian
+author: John Snow Labs
+name: t5_base_p_l_akk_english_20241108_111409_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_base_p_l_akk_english_20241108_111409_pipeline` is a English model originally trained by Thalesian.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_base_p_l_akk_english_20241108_111409_pipeline_en_5.5.1_3.0_1737945138417.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_base_p_l_akk_english_20241108_111409_pipeline_en_5.5.1_3.0_1737945138417.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_base_p_l_akk_english_20241108_111409_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_base_p_l_akk_english_20241108_111409_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_base_p_l_akk_english_20241108_111409_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|2.0 GB|
+
+## References
+
+https://huggingface.co/Thalesian/t5-base-p-l-akk-en-20241108-111409
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_base_p_l_akk_english_20241125_151008_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_base_p_l_akk_english_20241125_151008_en.md
new file mode 100644
index 00000000000000..37029355b8d672
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_base_p_l_akk_english_20241125_151008_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_base_p_l_akk_english_20241125_151008 T5Transformer from Thalesian
+author: John Snow Labs
+name: t5_base_p_l_akk_english_20241125_151008
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_base_p_l_akk_english_20241125_151008` is a English model originally trained by Thalesian.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_base_p_l_akk_english_20241125_151008_en_5.5.1_3.0_1737989826001.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_base_p_l_akk_english_20241125_151008_en_5.5.1_3.0_1737989826001.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_base_p_l_akk_english_20241125_151008","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_base_p_l_akk_english_20241125_151008", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_base_p_l_akk_english_20241125_151008|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|2.0 GB|
+
+## References
+
+https://huggingface.co/Thalesian/t5-base-p-l-akk-en-20241125-151008
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_base_p_l_akk_english_20241125_151008_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_base_p_l_akk_english_20241125_151008_pipeline_en.md
new file mode 100644
index 00000000000000..281b73e8e1bf1b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_base_p_l_akk_english_20241125_151008_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_base_p_l_akk_english_20241125_151008_pipeline pipeline T5Transformer from Thalesian
+author: John Snow Labs
+name: t5_base_p_l_akk_english_20241125_151008_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_base_p_l_akk_english_20241125_151008_pipeline` is a English model originally trained by Thalesian.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_base_p_l_akk_english_20241125_151008_pipeline_en_5.5.1_3.0_1737989923873.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_base_p_l_akk_english_20241125_151008_pipeline_en_5.5.1_3.0_1737989923873.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_base_p_l_akk_english_20241125_151008_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_base_p_l_akk_english_20241125_151008_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_base_p_l_akk_english_20241125_151008_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|2.0 GB|
+
+## References
+
+https://huggingface.co/Thalesian/t5-base-p-l-akk-en-20241125-151008
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_base_pos2neg_ggallipoli_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_base_pos2neg_ggallipoli_en.md
new file mode 100644
index 00000000000000..837d31fce3aa36
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_base_pos2neg_ggallipoli_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_base_pos2neg_ggallipoli T5Transformer from ggallipoli
+author: John Snow Labs
+name: t5_base_pos2neg_ggallipoli
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_base_pos2neg_ggallipoli` is a English model originally trained by ggallipoli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_base_pos2neg_ggallipoli_en_5.5.1_3.0_1738006573817.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_base_pos2neg_ggallipoli_en_5.5.1_3.0_1738006573817.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_base_pos2neg_ggallipoli","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_base_pos2neg_ggallipoli", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_base_pos2neg_ggallipoli|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|927.1 MB|
+
+## References
+
+https://huggingface.co/ggallipoli/t5-base_pos2neg
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_base_pos2neg_ggallipoli_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_base_pos2neg_ggallipoli_pipeline_en.md
new file mode 100644
index 00000000000000..8b0db657be6228
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_base_pos2neg_ggallipoli_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_base_pos2neg_ggallipoli_pipeline pipeline T5Transformer from ggallipoli
+author: John Snow Labs
+name: t5_base_pos2neg_ggallipoli_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_base_pos2neg_ggallipoli_pipeline` is a English model originally trained by ggallipoli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_base_pos2neg_ggallipoli_pipeline_en_5.5.1_3.0_1738006621860.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_base_pos2neg_ggallipoli_pipeline_en_5.5.1_3.0_1738006621860.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_base_pos2neg_ggallipoli_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_base_pos2neg_ggallipoli_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_base_pos2neg_ggallipoli_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|927.1 MB|
+
+## References
+
+https://huggingface.co/ggallipoli/t5-base_pos2neg
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_base_rouge_squad_qg_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_base_rouge_squad_qg_en.md
new file mode 100644
index 00000000000000..a7fd7a971c11b6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_base_rouge_squad_qg_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_base_rouge_squad_qg T5Transformer from devagonal
+author: John Snow Labs
+name: t5_base_rouge_squad_qg
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_base_rouge_squad_qg` is a English model originally trained by devagonal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_base_rouge_squad_qg_en_5.5.1_3.0_1737962695987.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_base_rouge_squad_qg_en_5.5.1_3.0_1737962695987.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_base_rouge_squad_qg","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_base_rouge_squad_qg", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_base_rouge_squad_qg|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|912.2 MB|
+
+## References
+
+https://huggingface.co/devagonal/t5-base-rouge-squad-qg
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_base_rouge_squad_qg_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_base_rouge_squad_qg_pipeline_en.md
new file mode 100644
index 00000000000000..fbc26d8036b3b2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_base_rouge_squad_qg_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_base_rouge_squad_qg_pipeline pipeline T5Transformer from devagonal
+author: John Snow Labs
+name: t5_base_rouge_squad_qg_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_base_rouge_squad_qg_pipeline` is a English model originally trained by devagonal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_base_rouge_squad_qg_pipeline_en_5.5.1_3.0_1737962745118.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_base_rouge_squad_qg_pipeline_en_5.5.1_3.0_1737962745118.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_base_rouge_squad_qg_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_base_rouge_squad_qg_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_base_rouge_squad_qg_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|912.2 MB|
+
+## References
+
+https://huggingface.co/devagonal/t5-base-rouge-squad-qg
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_base_spanish_yoremnokki_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_base_spanish_yoremnokki_en.md
new file mode 100644
index 00000000000000..e213b036fb7c05
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_base_spanish_yoremnokki_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_base_spanish_yoremnokki T5Transformer from alfsnd
+author: John Snow Labs
+name: t5_base_spanish_yoremnokki
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_base_spanish_yoremnokki` is a English model originally trained by alfsnd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_base_spanish_yoremnokki_en_5.5.1_3.0_1738007256635.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_base_spanish_yoremnokki_en_5.5.1_3.0_1738007256635.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_base_spanish_yoremnokki","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_base_spanish_yoremnokki", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_base_spanish_yoremnokki|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|892.3 MB|
+
+## References
+
+https://huggingface.co/alfsnd/t5-base-spanish-yoremnokki
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_base_spanish_yoremnokki_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_base_spanish_yoremnokki_pipeline_en.md
new file mode 100644
index 00000000000000..3ebedc79fd4356
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_base_spanish_yoremnokki_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_base_spanish_yoremnokki_pipeline pipeline T5Transformer from alfsnd
+author: John Snow Labs
+name: t5_base_spanish_yoremnokki_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_base_spanish_yoremnokki_pipeline` is a English model originally trained by alfsnd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_base_spanish_yoremnokki_pipeline_en_5.5.1_3.0_1738007311401.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_base_spanish_yoremnokki_pipeline_en_5.5.1_3.0_1738007311401.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_base_spanish_yoremnokki_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_base_spanish_yoremnokki_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_base_spanish_yoremnokki_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|892.3 MB|
+
+## References
+
+https://huggingface.co/alfsnd/t5-base-spanish-yoremnokki
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_educhat_finetuned_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_educhat_finetuned_en.md
new file mode 100644
index 00000000000000..15e87f8a208b5a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_educhat_finetuned_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_educhat_finetuned T5Transformer from and-de
+author: John Snow Labs
+name: t5_educhat_finetuned
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_educhat_finetuned` is a English model originally trained by and-de.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_educhat_finetuned_en_5.5.1_3.0_1738000862356.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_educhat_finetuned_en_5.5.1_3.0_1738000862356.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_educhat_finetuned","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_educhat_finetuned", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_educhat_finetuned|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|286.4 MB|
+
+## References
+
+https://huggingface.co/and-de/t5-educhat-finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_educhat_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_educhat_finetuned_pipeline_en.md
new file mode 100644
index 00000000000000..d65659cd7ee929
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_educhat_finetuned_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_educhat_finetuned_pipeline pipeline T5Transformer from and-de
+author: John Snow Labs
+name: t5_educhat_finetuned_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_educhat_finetuned_pipeline` is a English model originally trained by and-de.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_educhat_finetuned_pipeline_en_5.5.1_3.0_1738000880924.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_educhat_finetuned_pipeline_en_5.5.1_3.0_1738000880924.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_educhat_finetuned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_educhat_finetuned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_educhat_finetuned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|286.4 MB|
+
+## References
+
+https://huggingface.co/and-de/t5-educhat-finetuned
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_final_model_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_final_model_en.md
new file mode 100644
index 00000000000000..7b1ae1242a0fcc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_final_model_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_final_model T5Transformer from shaminishara2000
+author: John Snow Labs
+name: t5_final_model
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_final_model` is a English model originally trained by shaminishara2000.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_final_model_en_5.5.1_3.0_1737978562994.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_final_model_en_5.5.1_3.0_1737978562994.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_final_model","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_final_model", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_final_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|288.4 MB|
+
+## References
+
+https://huggingface.co/shaminishara2000/t5-final_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_final_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_final_model_pipeline_en.md
new file mode 100644
index 00000000000000..987a568e2b036e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_final_model_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_final_model_pipeline pipeline T5Transformer from shaminishara2000
+author: John Snow Labs
+name: t5_final_model_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_final_model_pipeline` is a English model originally trained by shaminishara2000.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_final_model_pipeline_en_5.5.1_3.0_1737978577475.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_final_model_pipeline_en_5.5.1_3.0_1737978577475.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_final_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_final_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_final_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|288.4 MB|
+
+## References
+
+https://huggingface.co/shaminishara2000/t5-final_model
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_fine_tune_save_example_ancestor9_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_fine_tune_save_example_ancestor9_en.md
new file mode 100644
index 00000000000000..e890d503246908
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_fine_tune_save_example_ancestor9_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_fine_tune_save_example_ancestor9 T5Transformer from ancestor9
+author: John Snow Labs
+name: t5_fine_tune_save_example_ancestor9
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_fine_tune_save_example_ancestor9` is a English model originally trained by ancestor9.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_fine_tune_save_example_ancestor9_en_5.5.1_3.0_1737991051325.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_fine_tune_save_example_ancestor9_en_5.5.1_3.0_1737991051325.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_fine_tune_save_example_ancestor9","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_fine_tune_save_example_ancestor9", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_fine_tune_save_example_ancestor9|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|284.3 MB|
+
+## References
+
+https://huggingface.co/ancestor9/t5-fine-tune-save-example
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_fine_tune_save_example_ancestor9_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_fine_tune_save_example_ancestor9_pipeline_en.md
new file mode 100644
index 00000000000000..9112ecb3e23e85
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_fine_tune_save_example_ancestor9_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_fine_tune_save_example_ancestor9_pipeline pipeline T5Transformer from ancestor9
+author: John Snow Labs
+name: t5_fine_tune_save_example_ancestor9_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_fine_tune_save_example_ancestor9_pipeline` is a English model originally trained by ancestor9.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_fine_tune_save_example_ancestor9_pipeline_en_5.5.1_3.0_1737991066616.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_fine_tune_save_example_ancestor9_pipeline_en_5.5.1_3.0_1737991066616.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_fine_tune_save_example_ancestor9_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_fine_tune_save_example_ancestor9_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_fine_tune_save_example_ancestor9_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|284.3 MB|
+
+## References
+
+https://huggingface.co/ancestor9/t5-fine-tune-save-example
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_finetune_address_burmese_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_finetune_address_burmese_en.md
new file mode 100644
index 00000000000000..1bd48465f34f94
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_finetune_address_burmese_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_finetune_address_burmese T5Transformer from zulkifliarshad
+author: John Snow Labs
+name: t5_finetune_address_burmese
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_finetune_address_burmese` is a English model originally trained by zulkifliarshad.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_finetune_address_burmese_en_5.5.1_3.0_1737979970904.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_finetune_address_burmese_en_5.5.1_3.0_1737979970904.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_finetune_address_burmese","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_finetune_address_burmese", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_finetune_address_burmese|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|882.5 MB|
+
+## References
+
+https://huggingface.co/zulkifliarshad/t5-finetune-address-my
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_finetune_address_burmese_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_finetune_address_burmese_pipeline_en.md
new file mode 100644
index 00000000000000..70bcfb409b7c26
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_finetune_address_burmese_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_finetune_address_burmese_pipeline pipeline T5Transformer from zulkifliarshad
+author: John Snow Labs
+name: t5_finetune_address_burmese_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_finetune_address_burmese_pipeline` is a English model originally trained by zulkifliarshad.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_finetune_address_burmese_pipeline_en_5.5.1_3.0_1737980026993.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_finetune_address_burmese_pipeline_en_5.5.1_3.0_1737980026993.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_finetune_address_burmese_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_finetune_address_burmese_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_finetune_address_burmese_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|882.5 MB|
+
+## References
+
+https://huggingface.co/zulkifliarshad/t5-finetune-address-my
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_finetuned_ant3wan95_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_finetuned_ant3wan95_en.md
new file mode 100644
index 00000000000000..25f560d505a413
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_finetuned_ant3wan95_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_finetuned_ant3wan95 T5Transformer from Ant3wan95
+author: John Snow Labs
+name: t5_finetuned_ant3wan95
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_finetuned_ant3wan95` is a English model originally trained by Ant3wan95.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_finetuned_ant3wan95_en_5.5.1_3.0_1737989517476.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_finetuned_ant3wan95_en_5.5.1_3.0_1737989517476.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_finetuned_ant3wan95","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_finetuned_ant3wan95", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_finetuned_ant3wan95|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.4 MB|
+
+## References
+
+https://huggingface.co/Ant3wan95/t5-finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_finetuned_ant3wan95_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_finetuned_ant3wan95_pipeline_en.md
new file mode 100644
index 00000000000000..87349c298a3ab4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_finetuned_ant3wan95_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_finetuned_ant3wan95_pipeline pipeline T5Transformer from Ant3wan95
+author: John Snow Labs
+name: t5_finetuned_ant3wan95_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_finetuned_ant3wan95_pipeline` is a English model originally trained by Ant3wan95.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_finetuned_ant3wan95_pipeline_en_5.5.1_3.0_1737989520063.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_finetuned_ant3wan95_pipeline_en_5.5.1_3.0_1737989520063.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_finetuned_ant3wan95_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_finetuned_ant3wan95_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_finetuned_ant3wan95_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.4 MB|
+
+## References
+
+https://huggingface.co/Ant3wan95/t5-finetuned
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_finetuned_movie_chatbot_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_finetuned_movie_chatbot_en.md
new file mode 100644
index 00000000000000..480d31af6f449d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_finetuned_movie_chatbot_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_finetuned_movie_chatbot T5Transformer from takanami12
+author: John Snow Labs
+name: t5_finetuned_movie_chatbot
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_finetuned_movie_chatbot` is a English model originally trained by takanami12.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_finetuned_movie_chatbot_en_5.5.1_3.0_1738008585411.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_finetuned_movie_chatbot_en_5.5.1_3.0_1738008585411.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_finetuned_movie_chatbot","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_finetuned_movie_chatbot", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_finetuned_movie_chatbot|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|279.4 MB|
+
+## References
+
+https://huggingface.co/takanami12/t5_finetuned_movie_chatbot
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_finetuned_movie_chatbot_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_finetuned_movie_chatbot_pipeline_en.md
new file mode 100644
index 00000000000000..66bc839904d634
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_finetuned_movie_chatbot_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_finetuned_movie_chatbot_pipeline pipeline T5Transformer from takanami12
+author: John Snow Labs
+name: t5_finetuned_movie_chatbot_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_finetuned_movie_chatbot_pipeline` is a English model originally trained by takanami12.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_finetuned_movie_chatbot_pipeline_en_5.5.1_3.0_1738008602381.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_finetuned_movie_chatbot_pipeline_en_5.5.1_3.0_1738008602381.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_finetuned_movie_chatbot_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_finetuned_movie_chatbot_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_finetuned_movie_chatbot_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|279.4 MB|
+
+## References
+
+https://huggingface.co/takanami12/t5_finetuned_movie_chatbot
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_grammar_correction_amar5499_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_grammar_correction_amar5499_en.md
new file mode 100644
index 00000000000000..972cc5f404d1e3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_grammar_correction_amar5499_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_grammar_correction_amar5499 T5Transformer from Amar5499
+author: John Snow Labs
+name: t5_grammar_correction_amar5499
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_grammar_correction_amar5499` is a English model originally trained by Amar5499.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_grammar_correction_amar5499_en_5.5.1_3.0_1737963681983.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_grammar_correction_amar5499_en_5.5.1_3.0_1737963681983.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_grammar_correction_amar5499","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_grammar_correction_amar5499", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_grammar_correction_amar5499|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/Amar5499/t5-grammar-correction
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_grammar_correction_amar5499_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_grammar_correction_amar5499_pipeline_en.md
new file mode 100644
index 00000000000000..98924cbe1a8dca
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_grammar_correction_amar5499_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_grammar_correction_amar5499_pipeline pipeline T5Transformer from Amar5499
+author: John Snow Labs
+name: t5_grammar_correction_amar5499_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_grammar_correction_amar5499_pipeline` is a English model originally trained by Amar5499.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_grammar_correction_amar5499_pipeline_en_5.5.1_3.0_1737964164324.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_grammar_correction_amar5499_pipeline_en_5.5.1_3.0_1737964164324.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_grammar_correction_amar5499_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_grammar_correction_amar5499_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_grammar_correction_amar5499_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/Amar5499/t5-grammar-correction
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_large_for2inf_family_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_large_for2inf_family_en.md
new file mode 100644
index 00000000000000..37a76e59223c72
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_large_for2inf_family_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_large_for2inf_family T5Transformer from ggallipoli
+author: John Snow Labs
+name: t5_large_for2inf_family
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_large_for2inf_family` is a English model originally trained by ggallipoli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_large_for2inf_family_en_5.5.1_3.0_1737991157735.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_large_for2inf_family_en_5.5.1_3.0_1737991157735.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_large_for2inf_family","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_large_for2inf_family", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_large_for2inf_family|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|2.9 GB|
+
+## References
+
+https://huggingface.co/ggallipoli/t5-large_for2inf_family
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_large_for2inf_family_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_large_for2inf_family_pipeline_en.md
new file mode 100644
index 00000000000000..a9886905833f10
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_large_for2inf_family_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_large_for2inf_family_pipeline pipeline T5Transformer from ggallipoli
+author: John Snow Labs
+name: t5_large_for2inf_family_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_large_for2inf_family_pipeline` is a English model originally trained by ggallipoli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_large_for2inf_family_pipeline_en_5.5.1_3.0_1737991298954.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_large_for2inf_family_pipeline_en_5.5.1_3.0_1737991298954.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_large_for2inf_family_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_large_for2inf_family_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_large_for2inf_family_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|2.9 GB|
+
+## References
+
+https://huggingface.co/ggallipoli/t5-large_for2inf_family
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_large_for2inf_music_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_large_for2inf_music_en.md
new file mode 100644
index 00000000000000..407c82299c12a6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_large_for2inf_music_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_large_for2inf_music T5Transformer from ggallipoli
+author: John Snow Labs
+name: t5_large_for2inf_music
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_large_for2inf_music` is a English model originally trained by ggallipoli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_large_for2inf_music_en_5.5.1_3.0_1737980715745.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_large_for2inf_music_en_5.5.1_3.0_1737980715745.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_large_for2inf_music","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_large_for2inf_music", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_large_for2inf_music|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|2.9 GB|
+
+## References
+
+https://huggingface.co/ggallipoli/t5-large_for2inf_music
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_large_for2inf_music_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_large_for2inf_music_pipeline_en.md
new file mode 100644
index 00000000000000..4b8f3ef7687318
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_large_for2inf_music_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_large_for2inf_music_pipeline pipeline T5Transformer from ggallipoli
+author: John Snow Labs
+name: t5_large_for2inf_music_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_large_for2inf_music_pipeline` is a English model originally trained by ggallipoli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_large_for2inf_music_pipeline_en_5.5.1_3.0_1737980855477.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_large_for2inf_music_pipeline_en_5.5.1_3.0_1737980855477.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_large_for2inf_music_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_large_for2inf_music_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_large_for2inf_music_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|2.9 GB|
+
+## References
+
+https://huggingface.co/ggallipoli/t5-large_for2inf_music
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_large_neg2pos_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_large_neg2pos_en.md
new file mode 100644
index 00000000000000..6726e4e89bf788
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_large_neg2pos_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_large_neg2pos T5Transformer from ggallipoli
+author: John Snow Labs
+name: t5_large_neg2pos
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_large_neg2pos` is a English model originally trained by ggallipoli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_large_neg2pos_en_5.5.1_3.0_1738009589827.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_large_neg2pos_en_5.5.1_3.0_1738009589827.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_large_neg2pos","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_large_neg2pos", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_large_neg2pos|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|2.9 GB|
+
+## References
+
+https://huggingface.co/ggallipoli/t5-large_neg2pos
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_large_neg2pos_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_large_neg2pos_pipeline_en.md
new file mode 100644
index 00000000000000..d1aaa1593e9675
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_large_neg2pos_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_large_neg2pos_pipeline pipeline T5Transformer from ggallipoli
+author: John Snow Labs
+name: t5_large_neg2pos_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_large_neg2pos_pipeline` is a English model originally trained by ggallipoli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_large_neg2pos_pipeline_en_5.5.1_3.0_1738009731227.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_large_neg2pos_pipeline_en_5.5.1_3.0_1738009731227.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_large_neg2pos_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_large_neg2pos_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_large_neg2pos_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|2.9 GB|
+
+## References
+
+https://huggingface.co/ggallipoli/t5-large_neg2pos
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_model_enrichi_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_model_enrichi_en.md
new file mode 100644
index 00000000000000..c72ccf2fd08d1b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_model_enrichi_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_model_enrichi T5Transformer from rdetch22
+author: John Snow Labs
+name: t5_model_enrichi
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_model_enrichi` is a English model originally trained by rdetch22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_model_enrichi_en_5.5.1_3.0_1737961505061.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_model_enrichi_en_5.5.1_3.0_1737961505061.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_model_enrichi","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_model_enrichi", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_model_enrichi|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|148.0 MB|
+
+## References
+
+https://huggingface.co/rdetch22/t5_model_enrichi
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_model_enrichi_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_model_enrichi_pipeline_en.md
new file mode 100644
index 00000000000000..d25763b457ea5d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_model_enrichi_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_model_enrichi_pipeline pipeline T5Transformer from rdetch22
+author: John Snow Labs
+name: t5_model_enrichi_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_model_enrichi_pipeline` is a English model originally trained by rdetch22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_model_enrichi_pipeline_en_5.5.1_3.0_1737961555484.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_model_enrichi_pipeline_en_5.5.1_3.0_1737961555484.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_model_enrichi_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_model_enrichi_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_model_enrichi_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|148.0 MB|
+
+## References
+
+https://huggingface.co/rdetch22/t5_model_enrichi
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_questionanswering_nq_5_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_questionanswering_nq_5_en.md
new file mode 100644
index 00000000000000..b0e048c20da7a4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_questionanswering_nq_5_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_questionanswering_nq_5 T5Transformer from aayeshanakarmi
+author: John Snow Labs
+name: t5_questionanswering_nq_5
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_questionanswering_nq_5` is a English model originally trained by aayeshanakarmi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_questionanswering_nq_5_en_5.5.1_3.0_1737980752145.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_questionanswering_nq_5_en_5.5.1_3.0_1737980752145.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_questionanswering_nq_5","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_questionanswering_nq_5", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_questionanswering_nq_5|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|282.9 MB|
+
+## References
+
+https://huggingface.co/aayeshanakarmi/T5-QuestionAnswering-NQ-5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_questionanswering_nq_5_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_questionanswering_nq_5_pipeline_en.md
new file mode 100644
index 00000000000000..a59008aff40c70
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_questionanswering_nq_5_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_questionanswering_nq_5_pipeline pipeline T5Transformer from aayeshanakarmi
+author: John Snow Labs
+name: t5_questionanswering_nq_5_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_questionanswering_nq_5_pipeline` is a English model originally trained by aayeshanakarmi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_questionanswering_nq_5_pipeline_en_5.5.1_3.0_1737980769251.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_questionanswering_nq_5_pipeline_en_5.5.1_3.0_1737980769251.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_questionanswering_nq_5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_questionanswering_nq_5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_questionanswering_nq_5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|282.9 MB|
+
+## References
+
+https://huggingface.co/aayeshanakarmi/T5-QuestionAnswering-NQ-5
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_rls2000_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_rls2000_en.md
new file mode 100644
index 00000000000000..15f907c12ce0cb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_rls2000_en.md
@@ -0,0 +1,88 @@
+---
+layout: model
+title: English t5_rls2000 T5Transformer from marcus2000
+author: John Snow Labs
+name: t5_rls2000
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_rls2000` is a English model originally trained by marcus2000.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_rls2000_en_5.5.1_3.0_1737981212892.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_rls2000_en_5.5.1_3.0_1737981212892.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_rls2000","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_rls2000", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_rls2000|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|2.9 GB|
+
+## References
+
+References
+
+https://huggingface.co/marcus2000/T5-RLS2000
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_rls2000_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_rls2000_pipeline_en.md
new file mode 100644
index 00000000000000..7a22ff87f044b2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_rls2000_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_rls2000_pipeline pipeline T5Transformer from athugodage
+author: John Snow Labs
+name: t5_rls2000_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_rls2000_pipeline` is a English model originally trained by athugodage.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_rls2000_pipeline_en_5.5.1_3.0_1737981347575.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_rls2000_pipeline_en_5.5.1_3.0_1737981347575.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_rls2000_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_rls2000_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_rls2000_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|2.9 GB|
+
+## References
+
+https://huggingface.co/athugodage/T5-RLS2000
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_10k_model_with_openai_summarize_comparisons_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_10k_model_with_openai_summarize_comparisons_en.md
new file mode 100644
index 00000000000000..f36c92a2929115
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_10k_model_with_openai_summarize_comparisons_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_small_10k_model_with_openai_summarize_comparisons T5Transformer from Muadil
+author: John Snow Labs
+name: t5_small_10k_model_with_openai_summarize_comparisons
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_10k_model_with_openai_summarize_comparisons` is a English model originally trained by Muadil.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_10k_model_with_openai_summarize_comparisons_en_5.5.1_3.0_1737961808947.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_10k_model_with_openai_summarize_comparisons_en_5.5.1_3.0_1737961808947.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_small_10k_model_with_openai_summarize_comparisons","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_small_10k_model_with_openai_summarize_comparisons", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_10k_model_with_openai_summarize_comparisons|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|155.5 MB|
+
+## References
+
+https://huggingface.co/Muadil/t5_small_10k_model_with_openai_summarize_comparisons
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_10k_model_with_openai_summarize_comparisons_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_10k_model_with_openai_summarize_comparisons_pipeline_en.md
new file mode 100644
index 00000000000000..1d84ca70bb0764
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_10k_model_with_openai_summarize_comparisons_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_small_10k_model_with_openai_summarize_comparisons_pipeline pipeline T5Transformer from Muadil
+author: John Snow Labs
+name: t5_small_10k_model_with_openai_summarize_comparisons_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_10k_model_with_openai_summarize_comparisons_pipeline` is a English model originally trained by Muadil.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_10k_model_with_openai_summarize_comparisons_pipeline_en_5.5.1_3.0_1737961858414.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_10k_model_with_openai_summarize_comparisons_pipeline_en_5.5.1_3.0_1737961858414.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_small_10k_model_with_openai_summarize_comparisons_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_small_10k_model_with_openai_summarize_comparisons_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_10k_model_with_openai_summarize_comparisons_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|155.5 MB|
+
+## References
+
+https://huggingface.co/Muadil/t5_small_10k_model_with_openai_summarize_comparisons
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_bhavaishkumar112_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_bhavaishkumar112_en.md
new file mode 100644
index 00000000000000..a863ec39b21543
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_bhavaishkumar112_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_small_bhavaishkumar112 T5Transformer from BhavaishKumar112
+author: John Snow Labs
+name: t5_small_bhavaishkumar112
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_bhavaishkumar112` is a English model originally trained by BhavaishKumar112.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_bhavaishkumar112_en_5.5.1_3.0_1738007757871.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_bhavaishkumar112_en_5.5.1_3.0_1738007757871.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_small_bhavaishkumar112","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_small_bhavaishkumar112", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_bhavaishkumar112|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|265.0 MB|
+
+## References
+
+https://huggingface.co/BhavaishKumar112/t5-small
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_bhavaishkumar112_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_bhavaishkumar112_pipeline_en.md
new file mode 100644
index 00000000000000..2205cf089f28ad
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_bhavaishkumar112_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_small_bhavaishkumar112_pipeline pipeline T5Transformer from BhavaishKumar112
+author: John Snow Labs
+name: t5_small_bhavaishkumar112_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_bhavaishkumar112_pipeline` is a English model originally trained by BhavaishKumar112.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_bhavaishkumar112_pipeline_en_5.5.1_3.0_1738007776066.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_bhavaishkumar112_pipeline_en_5.5.1_3.0_1738007776066.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_small_bhavaishkumar112_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_small_bhavaishkumar112_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_bhavaishkumar112_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|265.0 MB|
+
+## References
+
+https://huggingface.co/BhavaishKumar112/t5-small
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_english_vietnamese_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_english_vietnamese_en.md
new file mode 100644
index 00000000000000..9084696c21c81f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_english_vietnamese_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_small_english_vietnamese T5Transformer from thainq107
+author: John Snow Labs
+name: t5_small_english_vietnamese
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_english_vietnamese` is a English model originally trained by thainq107.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_english_vietnamese_en_5.5.1_3.0_1737946835418.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_english_vietnamese_en_5.5.1_3.0_1737946835418.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_small_english_vietnamese","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_small_english_vietnamese", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_english_vietnamese|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|819.2 MB|
+
+## References
+
+https://huggingface.co/thainq107/t5-small-en-vi
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_english_vietnamese_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_english_vietnamese_pipeline_en.md
new file mode 100644
index 00000000000000..a7163eb5663b9a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_english_vietnamese_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_small_english_vietnamese_pipeline pipeline T5Transformer from thainq107
+author: John Snow Labs
+name: t5_small_english_vietnamese_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_english_vietnamese_pipeline` is a English model originally trained by thainq107.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_english_vietnamese_pipeline_en_5.5.1_3.0_1737947104434.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_english_vietnamese_pipeline_en_5.5.1_3.0_1737947104434.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_small_english_vietnamese_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_small_english_vietnamese_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_english_vietnamese_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|819.2 MB|
+
+## References
+
+https://huggingface.co/thainq107/t5-small-en-vi
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_fine_tuned_nips_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_fine_tuned_nips_en.md
new file mode 100644
index 00000000000000..607a702edbc203
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_fine_tuned_nips_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_small_fine_tuned_nips T5Transformer from BRUNOKRISTI
+author: John Snow Labs
+name: t5_small_fine_tuned_nips
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_fine_tuned_nips` is a English model originally trained by BRUNOKRISTI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_fine_tuned_nips_en_5.5.1_3.0_1737945726782.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_fine_tuned_nips_en_5.5.1_3.0_1737945726782.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_small_fine_tuned_nips","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_small_fine_tuned_nips", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_fine_tuned_nips|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|287.6 MB|
+
+## References
+
+https://huggingface.co/BRUNOKRISTI/t5-small-fine-tuned-nips
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_fine_tuned_nips_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_fine_tuned_nips_pipeline_en.md
new file mode 100644
index 00000000000000..a85aa18fdd1fce
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_fine_tuned_nips_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_small_fine_tuned_nips_pipeline pipeline T5Transformer from BRUNOKRISTI
+author: John Snow Labs
+name: t5_small_fine_tuned_nips_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_fine_tuned_nips_pipeline` is a English model originally trained by BRUNOKRISTI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_fine_tuned_nips_pipeline_en_5.5.1_3.0_1737945744955.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_fine_tuned_nips_pipeline_en_5.5.1_3.0_1737945744955.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_small_fine_tuned_nips_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_small_fine_tuned_nips_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_fine_tuned_nips_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|287.6 MB|
+
+## References
+
+https://huggingface.co/BRUNOKRISTI/t5-small-fine-tuned-nips
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_finetuned_aspect_based_news_summary_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_finetuned_aspect_based_news_summary_en.md
new file mode 100644
index 00000000000000..214a511d701c4f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_finetuned_aspect_based_news_summary_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_small_finetuned_aspect_based_news_summary T5Transformer from Ftmhd
+author: John Snow Labs
+name: t5_small_finetuned_aspect_based_news_summary
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_finetuned_aspect_based_news_summary` is a English model originally trained by Ftmhd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_finetuned_aspect_based_news_summary_en_5.5.1_3.0_1737989306802.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_finetuned_aspect_based_news_summary_en_5.5.1_3.0_1737989306802.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_small_finetuned_aspect_based_news_summary","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_small_finetuned_aspect_based_news_summary", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_finetuned_aspect_based_news_summary|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|265.7 MB|
+
+## References
+
+https://huggingface.co/Ftmhd/t5-small-finetuned-aspect_based_news_summary
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_finetuned_aspect_based_news_summary_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_finetuned_aspect_based_news_summary_pipeline_en.md
new file mode 100644
index 00000000000000..3b962b54ea5f7b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_finetuned_aspect_based_news_summary_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_small_finetuned_aspect_based_news_summary_pipeline pipeline T5Transformer from Ftmhd
+author: John Snow Labs
+name: t5_small_finetuned_aspect_based_news_summary_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_finetuned_aspect_based_news_summary_pipeline` is a English model originally trained by Ftmhd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_finetuned_aspect_based_news_summary_pipeline_en_5.5.1_3.0_1737989325191.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_finetuned_aspect_based_news_summary_pipeline_en_5.5.1_3.0_1737989325191.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_small_finetuned_aspect_based_news_summary_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_small_finetuned_aspect_based_news_summary_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_finetuned_aspect_based_news_summary_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|265.7 MB|
+
+## References
+
+https://huggingface.co/Ftmhd/t5-small-finetuned-aspect_based_news_summary
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_finetuned_jiaaaaaaax_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_finetuned_jiaaaaaaax_en.md
new file mode 100644
index 00000000000000..e9e44efb89dd76
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_finetuned_jiaaaaaaax_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_small_finetuned_jiaaaaaaax T5Transformer from Jiaaaaaaax
+author: John Snow Labs
+name: t5_small_finetuned_jiaaaaaaax
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_finetuned_jiaaaaaaax` is a English model originally trained by Jiaaaaaaax.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_finetuned_jiaaaaaaax_en_5.5.1_3.0_1737944522727.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_finetuned_jiaaaaaaax_en_5.5.1_3.0_1737944522727.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_small_finetuned_jiaaaaaaax","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_small_finetuned_jiaaaaaaax", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_finetuned_jiaaaaaaax|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|279.0 MB|
+
+## References
+
+https://huggingface.co/Jiaaaaaaax/t5-small-finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_finetuned_jiaaaaaaax_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_finetuned_jiaaaaaaax_pipeline_en.md
new file mode 100644
index 00000000000000..821928b9dfaaf3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_finetuned_jiaaaaaaax_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_small_finetuned_jiaaaaaaax_pipeline pipeline T5Transformer from Jiaaaaaaax
+author: John Snow Labs
+name: t5_small_finetuned_jiaaaaaaax_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_finetuned_jiaaaaaaax_pipeline` is a English model originally trained by Jiaaaaaaax.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_finetuned_jiaaaaaaax_pipeline_en_5.5.1_3.0_1737944539324.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_finetuned_jiaaaaaaax_pipeline_en_5.5.1_3.0_1737944539324.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_small_finetuned_jiaaaaaaax_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_small_finetuned_jiaaaaaaax_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_finetuned_jiaaaaaaax_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|279.0 MB|
+
+## References
+
+https://huggingface.co/Jiaaaaaaax/t5-small-finetuned
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_finetuned_nnguyen96_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_finetuned_nnguyen96_en.md
new file mode 100644
index 00000000000000..a5dd7a5ac2d839
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_finetuned_nnguyen96_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_small_finetuned_nnguyen96 T5Transformer from nnguyen96
+author: John Snow Labs
+name: t5_small_finetuned_nnguyen96
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_finetuned_nnguyen96` is a English model originally trained by nnguyen96.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_finetuned_nnguyen96_en_5.5.1_3.0_1737980483809.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_finetuned_nnguyen96_en_5.5.1_3.0_1737980483809.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_small_finetuned_nnguyen96","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_small_finetuned_nnguyen96", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_finetuned_nnguyen96|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|274.6 MB|
+
+## References
+
+https://huggingface.co/nnguyen96/t5-small_finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_finetuned_nnguyen96_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_finetuned_nnguyen96_pipeline_en.md
new file mode 100644
index 00000000000000..eec9613ed9da79
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_finetuned_nnguyen96_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_small_finetuned_nnguyen96_pipeline pipeline T5Transformer from nnguyen96
+author: John Snow Labs
+name: t5_small_finetuned_nnguyen96_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_finetuned_nnguyen96_pipeline` is a English model originally trained by nnguyen96.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_finetuned_nnguyen96_pipeline_en_5.5.1_3.0_1737980500721.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_finetuned_nnguyen96_pipeline_en_5.5.1_3.0_1737980500721.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_small_finetuned_nnguyen96_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_small_finetuned_nnguyen96_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_finetuned_nnguyen96_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|274.6 MB|
+
+## References
+
+https://huggingface.co/nnguyen96/t5-small_finetuned
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_finetuned_xsum_easwar03_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_finetuned_xsum_easwar03_en.md
new file mode 100644
index 00000000000000..b7e4ec3264e4d3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_finetuned_xsum_easwar03_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_small_finetuned_xsum_easwar03 T5Transformer from easwar03
+author: John Snow Labs
+name: t5_small_finetuned_xsum_easwar03
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_finetuned_xsum_easwar03` is a English model originally trained by easwar03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_finetuned_xsum_easwar03_en_5.5.1_3.0_1737989799181.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_finetuned_xsum_easwar03_en_5.5.1_3.0_1737989799181.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_small_finetuned_xsum_easwar03","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_small_finetuned_xsum_easwar03", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_finetuned_xsum_easwar03|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|257.8 MB|
+
+## References
+
+https://huggingface.co/easwar03/t5-small-finetuned-xsum
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_finetuned_xsum_easwar03_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_finetuned_xsum_easwar03_pipeline_en.md
new file mode 100644
index 00000000000000..2f5f45933a93b6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_finetuned_xsum_easwar03_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_small_finetuned_xsum_easwar03_pipeline pipeline T5Transformer from easwar03
+author: John Snow Labs
+name: t5_small_finetuned_xsum_easwar03_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_finetuned_xsum_easwar03_pipeline` is a English model originally trained by easwar03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_finetuned_xsum_easwar03_pipeline_en_5.5.1_3.0_1737989818275.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_finetuned_xsum_easwar03_pipeline_en_5.5.1_3.0_1737989818275.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_small_finetuned_xsum_easwar03_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_small_finetuned_xsum_easwar03_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_finetuned_xsum_easwar03_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|257.8 MB|
+
+## References
+
+https://huggingface.co/easwar03/t5-small-finetuned-xsum
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_finetuned_xsum_youssef14582_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_finetuned_xsum_youssef14582_en.md
new file mode 100644
index 00000000000000..4942319c62c5a2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_finetuned_xsum_youssef14582_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_small_finetuned_xsum_youssef14582 T5Transformer from youssef14582
+author: John Snow Labs
+name: t5_small_finetuned_xsum_youssef14582
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_finetuned_xsum_youssef14582` is a English model originally trained by youssef14582.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_finetuned_xsum_youssef14582_en_5.5.1_3.0_1738008809343.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_finetuned_xsum_youssef14582_en_5.5.1_3.0_1738008809343.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_small_finetuned_xsum_youssef14582","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_small_finetuned_xsum_youssef14582", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_finetuned_xsum_youssef14582|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|280.0 MB|
+
+## References
+
+https://huggingface.co/youssef14582/t5-small-finetuned-xsum
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_finetuned_xsum_youssef14582_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_finetuned_xsum_youssef14582_pipeline_en.md
new file mode 100644
index 00000000000000..383c822155909e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_finetuned_xsum_youssef14582_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_small_finetuned_xsum_youssef14582_pipeline pipeline T5Transformer from youssef14582
+author: John Snow Labs
+name: t5_small_finetuned_xsum_youssef14582_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_finetuned_xsum_youssef14582_pipeline` is a English model originally trained by youssef14582.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_finetuned_xsum_youssef14582_pipeline_en_5.5.1_3.0_1738008827063.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_finetuned_xsum_youssef14582_pipeline_en_5.5.1_3.0_1738008827063.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_small_finetuned_xsum_youssef14582_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_small_finetuned_xsum_youssef14582_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_finetuned_xsum_youssef14582_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|280.0 MB|
+
+## References
+
+https://huggingface.co/youssef14582/t5-small-finetuned-xsum
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_for2inf_family_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_for2inf_family_en.md
new file mode 100644
index 00000000000000..e93f0c1677a29a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_for2inf_family_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_small_for2inf_family T5Transformer from ggallipoli
+author: John Snow Labs
+name: t5_small_for2inf_family
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_for2inf_family` is a English model originally trained by ggallipoli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_for2inf_family_en_5.5.1_3.0_1738006749235.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_for2inf_family_en_5.5.1_3.0_1738006749235.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_small_for2inf_family","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_small_for2inf_family", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_for2inf_family|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|287.9 MB|
+
+## References
+
+https://huggingface.co/ggallipoli/t5-small_for2inf_family
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_for2inf_family_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_for2inf_family_pipeline_en.md
new file mode 100644
index 00000000000000..733efceae261f2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_for2inf_family_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_small_for2inf_family_pipeline pipeline T5Transformer from ggallipoli
+author: John Snow Labs
+name: t5_small_for2inf_family_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_for2inf_family_pipeline` is a English model originally trained by ggallipoli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_for2inf_family_pipeline_en_5.5.1_3.0_1738006766888.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_for2inf_family_pipeline_en_5.5.1_3.0_1738006766888.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_small_for2inf_family_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_small_for2inf_family_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_for2inf_family_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|287.9 MB|
+
+## References
+
+https://huggingface.co/ggallipoli/t5-small_for2inf_family
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_for2inf_music_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_for2inf_music_en.md
new file mode 100644
index 00000000000000..ed04684bbbe767
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_for2inf_music_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_small_for2inf_music T5Transformer from ggallipoli
+author: John Snow Labs
+name: t5_small_for2inf_music
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_for2inf_music` is a English model originally trained by ggallipoli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_for2inf_music_en_5.5.1_3.0_1738009023094.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_for2inf_music_en_5.5.1_3.0_1738009023094.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_small_for2inf_music","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_small_for2inf_music", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_for2inf_music|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|285.7 MB|
+
+## References
+
+https://huggingface.co/ggallipoli/t5-small_for2inf_music
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_for2inf_music_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_for2inf_music_pipeline_en.md
new file mode 100644
index 00000000000000..24e5e6c4bde192
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_for2inf_music_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_small_for2inf_music_pipeline pipeline T5Transformer from ggallipoli
+author: John Snow Labs
+name: t5_small_for2inf_music_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_for2inf_music_pipeline` is a English model originally trained by ggallipoli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_for2inf_music_pipeline_en_5.5.1_3.0_1738009041514.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_for2inf_music_pipeline_en_5.5.1_3.0_1738009041514.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_small_for2inf_music_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_small_for2inf_music_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_for2inf_music_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|285.7 MB|
+
+## References
+
+https://huggingface.co/ggallipoli/t5-small_for2inf_music
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_inf2for_music_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_inf2for_music_en.md
new file mode 100644
index 00000000000000..96ff48c58bd715
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_inf2for_music_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_small_inf2for_music T5Transformer from ggallipoli
+author: John Snow Labs
+name: t5_small_inf2for_music
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_inf2for_music` is a English model originally trained by ggallipoli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_inf2for_music_en_5.5.1_3.0_1737945370991.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_inf2for_music_en_5.5.1_3.0_1737945370991.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_small_inf2for_music","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_small_inf2for_music", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_inf2for_music|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|285.4 MB|
+
+## References
+
+https://huggingface.co/ggallipoli/t5-small_inf2for_music
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_inf2for_music_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_inf2for_music_pipeline_en.md
new file mode 100644
index 00000000000000..f6a089f55aa881
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_inf2for_music_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_small_inf2for_music_pipeline pipeline T5Transformer from ggallipoli
+author: John Snow Labs
+name: t5_small_inf2for_music_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_inf2for_music_pipeline` is a English model originally trained by ggallipoli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_inf2for_music_pipeline_en_5.5.1_3.0_1737945386801.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_inf2for_music_pipeline_en_5.5.1_3.0_1737945386801.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_small_inf2for_music_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_small_inf2for_music_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_inf2for_music_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|285.4 MB|
+
+## References
+
+https://huggingface.co/ggallipoli/t5-small_inf2for_music
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_legal_summarizer_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_legal_summarizer_en.md
new file mode 100644
index 00000000000000..54baf1b4e09cf2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_legal_summarizer_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_small_legal_summarizer T5Transformer from easwar03
+author: John Snow Labs
+name: t5_small_legal_summarizer
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_legal_summarizer` is a English model originally trained by easwar03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_legal_summarizer_en_5.5.1_3.0_1738008260129.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_legal_summarizer_en_5.5.1_3.0_1738008260129.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_small_legal_summarizer","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_small_legal_summarizer", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_legal_summarizer|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|256.7 MB|
+
+## References
+
+https://huggingface.co/easwar03/t5-small-legal-summarizer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_legal_summarizer_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_legal_summarizer_pipeline_en.md
new file mode 100644
index 00000000000000..e41d72e55dadec
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_legal_summarizer_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_small_legal_summarizer_pipeline pipeline T5Transformer from easwar03
+author: John Snow Labs
+name: t5_small_legal_summarizer_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_legal_summarizer_pipeline` is a English model originally trained by easwar03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_legal_summarizer_pipeline_en_5.5.1_3.0_1738008282158.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_legal_summarizer_pipeline_en_5.5.1_3.0_1738008282158.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_small_legal_summarizer_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_small_legal_summarizer_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_legal_summarizer_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|256.7 MB|
+
+## References
+
+https://huggingface.co/easwar03/t5-small-legal-summarizer
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_normal_arxiv_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_normal_arxiv_en.md
new file mode 100644
index 00000000000000..b30d2b37f2b103
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_normal_arxiv_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_small_normal_arxiv T5Transformer from manikantavarma
+author: John Snow Labs
+name: t5_small_normal_arxiv
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_normal_arxiv` is a English model originally trained by manikantavarma.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_normal_arxiv_en_5.5.1_3.0_1737961654555.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_normal_arxiv_en_5.5.1_3.0_1737961654555.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_small_normal_arxiv","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_small_normal_arxiv", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_normal_arxiv|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|276.1 MB|
+
+## References
+
+https://huggingface.co/manikantavarma/t5-small-normal-arxiv
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_normal_arxiv_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_normal_arxiv_pipeline_en.md
new file mode 100644
index 00000000000000..d18571f0278bf7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_normal_arxiv_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_small_normal_arxiv_pipeline pipeline T5Transformer from manikantavarma
+author: John Snow Labs
+name: t5_small_normal_arxiv_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_normal_arxiv_pipeline` is a English model originally trained by manikantavarma.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_normal_arxiv_pipeline_en_5.5.1_3.0_1737961671643.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_normal_arxiv_pipeline_en_5.5.1_3.0_1737961671643.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_small_normal_arxiv_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_small_normal_arxiv_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_normal_arxiv_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|276.1 MB|
+
+## References
+
+https://huggingface.co/manikantavarma/t5-small-normal-arxiv
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_pos2neg_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_pos2neg_en.md
new file mode 100644
index 00000000000000..cbe80d8c799dfc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_pos2neg_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_small_pos2neg T5Transformer from ggallipoli
+author: John Snow Labs
+name: t5_small_pos2neg
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_pos2neg` is a English model originally trained by ggallipoli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_pos2neg_en_5.5.1_3.0_1737989006075.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_pos2neg_en_5.5.1_3.0_1737989006075.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_small_pos2neg","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_small_pos2neg", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_pos2neg|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|288.6 MB|
+
+## References
+
+https://huggingface.co/ggallipoli/t5-small_pos2neg
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_pos2neg_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_pos2neg_pipeline_en.md
new file mode 100644
index 00000000000000..23a1be40321683
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_pos2neg_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_small_pos2neg_pipeline pipeline T5Transformer from ggallipoli
+author: John Snow Labs
+name: t5_small_pos2neg_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_pos2neg_pipeline` is a English model originally trained by ggallipoli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_pos2neg_pipeline_en_5.5.1_3.0_1737989020692.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_pos2neg_pipeline_en_5.5.1_3.0_1737989020692.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_small_pos2neg_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_small_pos2neg_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_pos2neg_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|288.6 MB|
+
+## References
+
+https://huggingface.co/ggallipoli/t5-small_pos2neg
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_priyankrathore_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_priyankrathore_en.md
new file mode 100644
index 00000000000000..a052b90c4e6df0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_priyankrathore_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_small_priyankrathore T5Transformer from priyankrathore
+author: John Snow Labs
+name: t5_small_priyankrathore
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_priyankrathore` is a English model originally trained by priyankrathore.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_priyankrathore_en_5.5.1_3.0_1737962679263.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_priyankrathore_en_5.5.1_3.0_1737962679263.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_small_priyankrathore","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_small_priyankrathore", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_priyankrathore|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|282.6 MB|
+
+## References
+
+https://huggingface.co/priyankrathore/T5_Small
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_priyankrathore_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_priyankrathore_pipeline_en.md
new file mode 100644
index 00000000000000..e575a5077bfd26
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_priyankrathore_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_small_priyankrathore_pipeline pipeline T5Transformer from priyankrathore
+author: John Snow Labs
+name: t5_small_priyankrathore_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_priyankrathore_pipeline` is a English model originally trained by priyankrathore.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_priyankrathore_pipeline_en_5.5.1_3.0_1737962696274.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_priyankrathore_pipeline_en_5.5.1_3.0_1737962696274.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_small_priyankrathore_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_small_priyankrathore_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_priyankrathore_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|282.6 MB|
+
+## References
+
+https://huggingface.co/priyankrathore/T5_Small
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_samsum_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_samsum_en.md
new file mode 100644
index 00000000000000..c96d42cf8424fd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_samsum_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_small_samsum T5Transformer from athuldinesh
+author: John Snow Labs
+name: t5_small_samsum
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_samsum` is a English model originally trained by athuldinesh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_samsum_en_5.5.1_3.0_1737988870994.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_samsum_en_5.5.1_3.0_1737988870994.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_small_samsum","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_small_samsum", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_samsum|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|279.2 MB|
+
+## References
+
+https://huggingface.co/athuldinesh/t5_small_samsum
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_samsum_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_samsum_pipeline_en.md
new file mode 100644
index 00000000000000..0be76e244905d2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_samsum_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_small_samsum_pipeline pipeline T5Transformer from athuldinesh
+author: John Snow Labs
+name: t5_small_samsum_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_samsum_pipeline` is a English model originally trained by athuldinesh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_samsum_pipeline_en_5.5.1_3.0_1737988886942.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_samsum_pipeline_en_5.5.1_3.0_1737988886942.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_small_samsum_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_small_samsum_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_samsum_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|279.2 MB|
+
+## References
+
+https://huggingface.co/athuldinesh/t5_small_samsum
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_search_query_generation_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_search_query_generation_en.md
new file mode 100644
index 00000000000000..cbccb306d6995e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_search_query_generation_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_small_search_query_generation T5Transformer from 1rsh
+author: John Snow Labs
+name: t5_small_search_query_generation
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_search_query_generation` is a English model originally trained by 1rsh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_search_query_generation_en_5.5.1_3.0_1737981016624.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_search_query_generation_en_5.5.1_3.0_1737981016624.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_small_search_query_generation","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_small_search_query_generation", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_search_query_generation|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|286.7 MB|
+
+## References
+
+https://huggingface.co/1rsh/t5-small-search-query-generation
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_search_query_generation_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_search_query_generation_pipeline_en.md
new file mode 100644
index 00000000000000..ba973ff7efabba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_search_query_generation_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_small_search_query_generation_pipeline pipeline T5Transformer from 1rsh
+author: John Snow Labs
+name: t5_small_search_query_generation_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_search_query_generation_pipeline` is a English model originally trained by 1rsh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_search_query_generation_pipeline_en_5.5.1_3.0_1737981031988.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_search_query_generation_pipeline_en_5.5.1_3.0_1737981031988.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_small_search_query_generation_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_small_search_query_generation_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_search_query_generation_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|286.7 MB|
+
+## References
+
+https://huggingface.co/1rsh/t5-small-search-query-generation
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_10k_2_1ep_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_10k_2_1ep_en.md
new file mode 100644
index 00000000000000..e6b45e6423239d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_10k_2_1ep_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_small_sum_dpo_10k_2_1ep T5Transformer from Muadil
+author: John Snow Labs
+name: t5_small_sum_dpo_10k_2_1ep
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_sum_dpo_10k_2_1ep` is a English model originally trained by Muadil.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_10k_2_1ep_en_5.5.1_3.0_1737977703701.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_10k_2_1ep_en_5.5.1_3.0_1737977703701.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_small_sum_dpo_10k_2_1ep","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_small_sum_dpo_10k_2_1ep", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_sum_dpo_10k_2_1ep|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|155.5 MB|
+
+## References
+
+https://huggingface.co/Muadil/t5-small_sum_DPO_10k_2_1ep
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_10k_2_1ep_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_10k_2_1ep_pipeline_en.md
new file mode 100644
index 00000000000000..5aad29a5b1d571
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_10k_2_1ep_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_small_sum_dpo_10k_2_1ep_pipeline pipeline T5Transformer from Muadil
+author: John Snow Labs
+name: t5_small_sum_dpo_10k_2_1ep_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_sum_dpo_10k_2_1ep_pipeline` is a English model originally trained by Muadil.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_10k_2_1ep_pipeline_en_5.5.1_3.0_1737977753626.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_10k_2_1ep_pipeline_en_5.5.1_3.0_1737977753626.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_small_sum_dpo_10k_2_1ep_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_small_sum_dpo_10k_2_1ep_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_sum_dpo_10k_2_1ep_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|155.5 MB|
+
+## References
+
+https://huggingface.co/Muadil/t5-small_sum_DPO_10k_2_1ep
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_10k_32_1ep_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_10k_32_1ep_en.md
new file mode 100644
index 00000000000000..fcc110405d9f6d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_10k_32_1ep_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_small_sum_dpo_10k_32_1ep T5Transformer from Muadil
+author: John Snow Labs
+name: t5_small_sum_dpo_10k_32_1ep
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_sum_dpo_10k_32_1ep` is a English model originally trained by Muadil.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_10k_32_1ep_en_5.5.1_3.0_1737943811413.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_10k_32_1ep_en_5.5.1_3.0_1737943811413.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_small_sum_dpo_10k_32_1ep","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_small_sum_dpo_10k_32_1ep", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_sum_dpo_10k_32_1ep|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|150.2 MB|
+
+## References
+
+https://huggingface.co/Muadil/t5-small_sum_DPO_10k_32_1ep
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_10k_32_1ep_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_10k_32_1ep_pipeline_en.md
new file mode 100644
index 00000000000000..3ca9734ed2ab2e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_10k_32_1ep_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_small_sum_dpo_10k_32_1ep_pipeline pipeline T5Transformer from Muadil
+author: John Snow Labs
+name: t5_small_sum_dpo_10k_32_1ep_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_sum_dpo_10k_32_1ep_pipeline` is a English model originally trained by Muadil.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_10k_32_1ep_pipeline_en_5.5.1_3.0_1737943861221.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_10k_32_1ep_pipeline_en_5.5.1_3.0_1737943861221.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_small_sum_dpo_10k_32_1ep_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_small_sum_dpo_10k_32_1ep_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_sum_dpo_10k_32_1ep_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|150.2 MB|
+
+## References
+
+https://huggingface.co/Muadil/t5-small_sum_DPO_10k_32_1ep
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_10k_4_1ep_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_10k_4_1ep_en.md
new file mode 100644
index 00000000000000..28608c621bdad8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_10k_4_1ep_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_small_sum_dpo_10k_4_1ep T5Transformer from Muadil
+author: John Snow Labs
+name: t5_small_sum_dpo_10k_4_1ep
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_sum_dpo_10k_4_1ep` is a English model originally trained by Muadil.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_10k_4_1ep_en_5.5.1_3.0_1737962853685.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_10k_4_1ep_en_5.5.1_3.0_1737962853685.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_small_sum_dpo_10k_4_1ep","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_small_sum_dpo_10k_4_1ep", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_sum_dpo_10k_4_1ep|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|155.0 MB|
+
+## References
+
+https://huggingface.co/Muadil/t5-small_sum_DPO_10k_4_1ep
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_10k_4_1ep_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_10k_4_1ep_pipeline_en.md
new file mode 100644
index 00000000000000..1ba7e631fdd83d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_10k_4_1ep_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_small_sum_dpo_10k_4_1ep_pipeline pipeline T5Transformer from Muadil
+author: John Snow Labs
+name: t5_small_sum_dpo_10k_4_1ep_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_sum_dpo_10k_4_1ep_pipeline` is a English model originally trained by Muadil.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_10k_4_1ep_pipeline_en_5.5.1_3.0_1737962902726.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_10k_4_1ep_pipeline_en_5.5.1_3.0_1737962902726.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_small_sum_dpo_10k_4_1ep_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_small_sum_dpo_10k_4_1ep_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_sum_dpo_10k_4_1ep_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|155.0 MB|
+
+## References
+
+https://huggingface.co/Muadil/t5-small_sum_DPO_10k_4_1ep
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_10k_64_10ep_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_10k_64_10ep_en.md
new file mode 100644
index 00000000000000..dbb9b4b203b79c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_10k_64_10ep_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_small_sum_dpo_10k_64_10ep T5Transformer from Muadil
+author: John Snow Labs
+name: t5_small_sum_dpo_10k_64_10ep
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_sum_dpo_10k_64_10ep` is a English model originally trained by Muadil.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_10k_64_10ep_en_5.5.1_3.0_1737962337243.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_10k_64_10ep_en_5.5.1_3.0_1737962337243.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_small_sum_dpo_10k_64_10ep","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_small_sum_dpo_10k_64_10ep", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_sum_dpo_10k_64_10ep|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|156.3 MB|
+
+## References
+
+https://huggingface.co/Muadil/t5-small_sum_DPO_10k_64_10ep
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_10k_64_10ep_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_10k_64_10ep_pipeline_en.md
new file mode 100644
index 00000000000000..782276d4bb5394
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_10k_64_10ep_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_small_sum_dpo_10k_64_10ep_pipeline pipeline T5Transformer from Muadil
+author: John Snow Labs
+name: t5_small_sum_dpo_10k_64_10ep_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_sum_dpo_10k_64_10ep_pipeline` is a English model originally trained by Muadil.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_10k_64_10ep_pipeline_en_5.5.1_3.0_1737962386471.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_10k_64_10ep_pipeline_en_5.5.1_3.0_1737962386471.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_small_sum_dpo_10k_64_10ep_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_small_sum_dpo_10k_64_10ep_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_sum_dpo_10k_64_10ep_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|156.3 MB|
+
+## References
+
+https://huggingface.co/Muadil/t5-small_sum_DPO_10k_64_10ep
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_10k_64_1ep_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_10k_64_1ep_en.md
new file mode 100644
index 00000000000000..14f15ef8d8c506
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_10k_64_1ep_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_small_sum_dpo_10k_64_1ep T5Transformer from Muadil
+author: John Snow Labs
+name: t5_small_sum_dpo_10k_64_1ep
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_sum_dpo_10k_64_1ep` is a English model originally trained by Muadil.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_10k_64_1ep_en_5.5.1_3.0_1738006456526.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_10k_64_1ep_en_5.5.1_3.0_1738006456526.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_small_sum_dpo_10k_64_1ep","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_small_sum_dpo_10k_64_1ep", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_sum_dpo_10k_64_1ep|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|150.2 MB|
+
+## References
+
+https://huggingface.co/Muadil/t5-small_sum_DPO_10k_64_1ep
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_10k_64_1ep_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_10k_64_1ep_pipeline_en.md
new file mode 100644
index 00000000000000..60be51f491b419
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_10k_64_1ep_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_small_sum_dpo_10k_64_1ep_pipeline pipeline T5Transformer from Muadil
+author: John Snow Labs
+name: t5_small_sum_dpo_10k_64_1ep_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_sum_dpo_10k_64_1ep_pipeline` is a English model originally trained by Muadil.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_10k_64_1ep_pipeline_en_5.5.1_3.0_1738006503989.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_10k_64_1ep_pipeline_en_5.5.1_3.0_1738006503989.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_small_sum_dpo_10k_64_1ep_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_small_sum_dpo_10k_64_1ep_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_sum_dpo_10k_64_1ep_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|150.2 MB|
+
+## References
+
+https://huggingface.co/Muadil/t5-small_sum_DPO_10k_64_1ep
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_10k_8_1ep_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_10k_8_1ep_en.md
new file mode 100644
index 00000000000000..960605b2a3e664
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_10k_8_1ep_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_small_sum_dpo_10k_8_1ep T5Transformer from Muadil
+author: John Snow Labs
+name: t5_small_sum_dpo_10k_8_1ep
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_sum_dpo_10k_8_1ep` is a English model originally trained by Muadil.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_10k_8_1ep_en_5.5.1_3.0_1737946122851.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_10k_8_1ep_en_5.5.1_3.0_1737946122851.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_small_sum_dpo_10k_8_1ep","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_small_sum_dpo_10k_8_1ep", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_sum_dpo_10k_8_1ep|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|154.2 MB|
+
+## References
+
+https://huggingface.co/Muadil/t5-small_sum_DPO_10k_8_1ep
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_10k_8_1ep_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_10k_8_1ep_pipeline_en.md
new file mode 100644
index 00000000000000..ea70741159d09d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_10k_8_1ep_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_small_sum_dpo_10k_8_1ep_pipeline pipeline T5Transformer from Muadil
+author: John Snow Labs
+name: t5_small_sum_dpo_10k_8_1ep_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_sum_dpo_10k_8_1ep_pipeline` is a English model originally trained by Muadil.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_10k_8_1ep_pipeline_en_5.5.1_3.0_1737946172737.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_10k_8_1ep_pipeline_en_5.5.1_3.0_1737946172737.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_small_sum_dpo_10k_8_1ep_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_small_sum_dpo_10k_8_1ep_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_sum_dpo_10k_8_1ep_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|154.2 MB|
+
+## References
+
+https://huggingface.co/Muadil/t5-small_sum_DPO_10k_8_1ep
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_177k_32_2ep_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_177k_32_2ep_en.md
new file mode 100644
index 00000000000000..832c3cbf681ea5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_177k_32_2ep_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_small_sum_dpo_177k_32_2ep T5Transformer from Muadil
+author: John Snow Labs
+name: t5_small_sum_dpo_177k_32_2ep
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_sum_dpo_177k_32_2ep` is a English model originally trained by Muadil.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_177k_32_2ep_en_5.5.1_3.0_1737989633596.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_177k_32_2ep_en_5.5.1_3.0_1737989633596.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_small_sum_dpo_177k_32_2ep","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_small_sum_dpo_177k_32_2ep", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_sum_dpo_177k_32_2ep|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|156.6 MB|
+
+## References
+
+https://huggingface.co/Muadil/t5-small_sum_DPO_177k_32_2ep
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_177k_32_2ep_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_177k_32_2ep_pipeline_en.md
new file mode 100644
index 00000000000000..b9b3ae1d102941
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_177k_32_2ep_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_small_sum_dpo_177k_32_2ep_pipeline pipeline T5Transformer from Muadil
+author: John Snow Labs
+name: t5_small_sum_dpo_177k_32_2ep_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_sum_dpo_177k_32_2ep_pipeline` is a English model originally trained by Muadil.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_177k_32_2ep_pipeline_en_5.5.1_3.0_1737989683889.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_177k_32_2ep_pipeline_en_5.5.1_3.0_1737989683889.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_small_sum_dpo_177k_32_2ep_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_small_sum_dpo_177k_32_2ep_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_sum_dpo_177k_32_2ep_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|156.6 MB|
+
+## References
+
+https://huggingface.co/Muadil/t5-small_sum_DPO_177k_32_2ep
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_50k_16_1ep_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_50k_16_1ep_en.md
new file mode 100644
index 00000000000000..9dac181178a77f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_50k_16_1ep_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_small_sum_dpo_50k_16_1ep T5Transformer from Muadil
+author: John Snow Labs
+name: t5_small_sum_dpo_50k_16_1ep
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_sum_dpo_50k_16_1ep` is a English model originally trained by Muadil.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_50k_16_1ep_en_5.5.1_3.0_1737944928012.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_50k_16_1ep_en_5.5.1_3.0_1737944928012.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_small_sum_dpo_50k_16_1ep","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_small_sum_dpo_50k_16_1ep", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_sum_dpo_50k_16_1ep|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|155.7 MB|
+
+## References
+
+https://huggingface.co/Muadil/t5-small_sum_DPO_50k_16_1ep
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_50k_16_1ep_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_50k_16_1ep_pipeline_en.md
new file mode 100644
index 00000000000000..e8c40f9e125b6f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_50k_16_1ep_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_small_sum_dpo_50k_16_1ep_pipeline pipeline T5Transformer from Muadil
+author: John Snow Labs
+name: t5_small_sum_dpo_50k_16_1ep_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_sum_dpo_50k_16_1ep_pipeline` is a English model originally trained by Muadil.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_50k_16_1ep_pipeline_en_5.5.1_3.0_1737944979158.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_50k_16_1ep_pipeline_en_5.5.1_3.0_1737944979158.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_small_sum_dpo_50k_16_1ep_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_small_sum_dpo_50k_16_1ep_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_sum_dpo_50k_16_1ep_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|155.7 MB|
+
+## References
+
+https://huggingface.co/Muadil/t5-small_sum_DPO_50k_16_1ep
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_50k_1_1ep_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_50k_1_1ep_en.md
new file mode 100644
index 00000000000000..03a42a3dbac57e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_50k_1_1ep_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_small_sum_dpo_50k_1_1ep T5Transformer from Muadil
+author: John Snow Labs
+name: t5_small_sum_dpo_50k_1_1ep
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_sum_dpo_50k_1_1ep` is a English model originally trained by Muadil.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_50k_1_1ep_en_5.5.1_3.0_1737943714775.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_50k_1_1ep_en_5.5.1_3.0_1737943714775.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_small_sum_dpo_50k_1_1ep","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_small_sum_dpo_50k_1_1ep", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_sum_dpo_50k_1_1ep|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|156.7 MB|
+
+## References
+
+https://huggingface.co/Muadil/t5-small_sum_DPO_50k_1_1ep
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_50k_1_1ep_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_50k_1_1ep_pipeline_en.md
new file mode 100644
index 00000000000000..844281a6a389e3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_50k_1_1ep_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_small_sum_dpo_50k_1_1ep_pipeline pipeline T5Transformer from Muadil
+author: John Snow Labs
+name: t5_small_sum_dpo_50k_1_1ep_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_sum_dpo_50k_1_1ep_pipeline` is a English model originally trained by Muadil.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_50k_1_1ep_pipeline_en_5.5.1_3.0_1737943765127.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_50k_1_1ep_pipeline_en_5.5.1_3.0_1737943765127.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_small_sum_dpo_50k_1_1ep_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_small_sum_dpo_50k_1_1ep_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_sum_dpo_50k_1_1ep_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|156.7 MB|
+
+## References
+
+https://huggingface.co/Muadil/t5-small_sum_DPO_50k_1_1ep
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_50k_4_1ep_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_50k_4_1ep_en.md
new file mode 100644
index 00000000000000..98b563bebcc02e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_50k_4_1ep_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_small_sum_dpo_50k_4_1ep T5Transformer from Muadil
+author: John Snow Labs
+name: t5_small_sum_dpo_50k_4_1ep
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_sum_dpo_50k_4_1ep` is a English model originally trained by Muadil.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_50k_4_1ep_en_5.5.1_3.0_1737945667201.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_50k_4_1ep_en_5.5.1_3.0_1737945667201.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_small_sum_dpo_50k_4_1ep","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_small_sum_dpo_50k_4_1ep", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_sum_dpo_50k_4_1ep|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|156.3 MB|
+
+## References
+
+https://huggingface.co/Muadil/t5-small_sum_DPO_50k_4_1ep
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_50k_4_1ep_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_50k_4_1ep_pipeline_en.md
new file mode 100644
index 00000000000000..d440078b40f0f2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_small_sum_dpo_50k_4_1ep_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_small_sum_dpo_50k_4_1ep_pipeline pipeline T5Transformer from Muadil
+author: John Snow Labs
+name: t5_small_sum_dpo_50k_4_1ep_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_sum_dpo_50k_4_1ep_pipeline` is a English model originally trained by Muadil.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_50k_4_1ep_pipeline_en_5.5.1_3.0_1737945719051.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_50k_4_1ep_pipeline_en_5.5.1_3.0_1737945719051.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_small_sum_dpo_50k_4_1ep_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_small_sum_dpo_50k_4_1ep_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_sum_dpo_50k_4_1ep_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|156.3 MB|
+
+## References
+
+https://huggingface.co/Muadil/t5-small_sum_DPO_50k_4_1ep
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_travel_model_finetuned_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_travel_model_finetuned_en.md
new file mode 100644
index 00000000000000..af22d606bfa3d9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_travel_model_finetuned_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_travel_model_finetuned T5Transformer from rdetch22
+author: John Snow Labs
+name: t5_travel_model_finetuned
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_travel_model_finetuned` is a English model originally trained by rdetch22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_travel_model_finetuned_en_5.5.1_3.0_1737961831172.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_travel_model_finetuned_en_5.5.1_3.0_1737961831172.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_travel_model_finetuned","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_travel_model_finetuned", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_travel_model_finetuned|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|261.8 MB|
+
+## References
+
+https://huggingface.co/rdetch22/t5_travel_model_finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_travel_model_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_travel_model_finetuned_pipeline_en.md
new file mode 100644
index 00000000000000..341e2a0de5118c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_travel_model_finetuned_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_travel_model_finetuned_pipeline pipeline T5Transformer from rdetch22
+author: John Snow Labs
+name: t5_travel_model_finetuned_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_travel_model_finetuned_pipeline` is a English model originally trained by rdetch22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_travel_model_finetuned_pipeline_en_5.5.1_3.0_1737961849638.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_travel_model_finetuned_pipeline_en_5.5.1_3.0_1737961849638.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_travel_model_finetuned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_travel_model_finetuned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_travel_model_finetuned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|261.8 MB|
+
+## References
+
+https://huggingface.co/rdetch22/t5_travel_model_finetuned
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_u_sub_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_u_sub_en.md
new file mode 100644
index 00000000000000..9e8633c9239ec5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_u_sub_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_u_sub T5Transformer from AryaR-06
+author: John Snow Labs
+name: t5_u_sub
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_u_sub` is a English model originally trained by AryaR-06.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_u_sub_en_5.5.1_3.0_1737979277146.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_u_sub_en_5.5.1_3.0_1737979277146.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_u_sub","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_u_sub", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_u_sub|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|862.4 MB|
+
+## References
+
+https://huggingface.co/AryaR-06/t5-u-sub
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t5_u_sub_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-t5_u_sub_pipeline_en.md
new file mode 100644
index 00000000000000..bfe70159348d9b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t5_u_sub_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_u_sub_pipeline pipeline T5Transformer from AryaR-06
+author: John Snow Labs
+name: t5_u_sub_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_u_sub_pipeline` is a English model originally trained by AryaR-06.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_u_sub_pipeline_en_5.5.1_3.0_1737979334229.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_u_sub_pipeline_en_5.5.1_3.0_1737979334229.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_u_sub_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_u_sub_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_u_sub_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|862.4 MB|
+
+## References
+
+https://huggingface.co/AryaR-06/t5-u-sub
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t_eta_en.md b/docs/_posts/ahmedlone127/2025-01-27-t_eta_en.md
new file mode 100644
index 00000000000000..dd080e077477f0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t_eta_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t_eta T5Transformer from motasem
+author: John Snow Labs
+name: t_eta
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t_eta` is a English model originally trained by motasem.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t_eta_en_5.5.1_3.0_1737980951751.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t_eta_en_5.5.1_3.0_1737980951751.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t_eta","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t_eta", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t_eta|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|742.4 MB|
+
+## References
+
+https://huggingface.co/motasem/T_ETA
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-t_eta_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-t_eta_pipeline_en.md
new file mode 100644
index 00000000000000..6d26b6d4df2a45
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-t_eta_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t_eta_pipeline pipeline T5Transformer from motasem
+author: John Snow Labs
+name: t_eta_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t_eta_pipeline` is a English model originally trained by motasem.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t_eta_pipeline_en_5.5.1_3.0_1737981042442.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t_eta_pipeline_en_5.5.1_3.0_1737981042442.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t_eta_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t_eta_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t_eta_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|742.4 MB|
+
+## References
+
+https://huggingface.co/motasem/T_ETA
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-tapt_helpfulness_base_pretraining_model_ltuzova_en.md b/docs/_posts/ahmedlone127/2025-01-27-tapt_helpfulness_base_pretraining_model_ltuzova_en.md
new file mode 100644
index 00000000000000..0d17863e41178c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-tapt_helpfulness_base_pretraining_model_ltuzova_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English tapt_helpfulness_base_pretraining_model_ltuzova RoBertaEmbeddings from ltuzova
+author: John Snow Labs
+name: tapt_helpfulness_base_pretraining_model_ltuzova
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tapt_helpfulness_base_pretraining_model_ltuzova` is a English model originally trained by ltuzova.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tapt_helpfulness_base_pretraining_model_ltuzova_en_5.5.1_3.0_1737966187028.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tapt_helpfulness_base_pretraining_model_ltuzova_en_5.5.1_3.0_1737966187028.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("tapt_helpfulness_base_pretraining_model_ltuzova","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("tapt_helpfulness_base_pretraining_model_ltuzova","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tapt_helpfulness_base_pretraining_model_ltuzova|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|466.4 MB|
+
+## References
+
+https://huggingface.co/ltuzova/tapt_helpfulness_base_pretraining_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-tapt_helpfulness_base_pretraining_model_ltuzova_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-tapt_helpfulness_base_pretraining_model_ltuzova_pipeline_en.md
new file mode 100644
index 00000000000000..3d590cbe88fc51
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-tapt_helpfulness_base_pretraining_model_ltuzova_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English tapt_helpfulness_base_pretraining_model_ltuzova_pipeline pipeline RoBertaEmbeddings from ltuzova
+author: John Snow Labs
+name: tapt_helpfulness_base_pretraining_model_ltuzova_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tapt_helpfulness_base_pretraining_model_ltuzova_pipeline` is a English model originally trained by ltuzova.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tapt_helpfulness_base_pretraining_model_ltuzova_pipeline_en_5.5.1_3.0_1737966210387.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tapt_helpfulness_base_pretraining_model_ltuzova_pipeline_en_5.5.1_3.0_1737966210387.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("tapt_helpfulness_base_pretraining_model_ltuzova_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("tapt_helpfulness_base_pretraining_model_ltuzova_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tapt_helpfulness_base_pretraining_model_ltuzova_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.4 MB|
+
+## References
+
+https://huggingface.co/ltuzova/tapt_helpfulness_base_pretraining_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-teapotllm_en.md b/docs/_posts/ahmedlone127/2025-01-27-teapotllm_en.md
new file mode 100644
index 00000000000000..3bacd924b67b27
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-teapotllm_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English teapotllm T5Transformer from teapotai
+author: John Snow Labs
+name: teapotllm
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`teapotllm` is a English model originally trained by teapotai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/teapotllm_en_5.5.1_3.0_1737999596366.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/teapotllm_en_5.5.1_3.0_1737999596366.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("teapotllm","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("teapotllm", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|teapotllm|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/teapotai/teapotllm
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-teapotllm_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-teapotllm_pipeline_en.md
new file mode 100644
index 00000000000000..9271167da25f49
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-teapotllm_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English teapotllm_pipeline pipeline T5Transformer from teapotai
+author: John Snow Labs
+name: teapotllm_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`teapotllm_pipeline` is a English model originally trained by teapotai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/teapotllm_pipeline_en_5.5.1_3.0_1737999655257.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/teapotllm_pipeline_en_5.5.1_3.0_1737999655257.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("teapotllm_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("teapotllm_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|teapotllm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/teapotai/teapotllm
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-test2_ai02_en.md b/docs/_posts/ahmedlone127/2025-01-27-test2_ai02_en.md
new file mode 100644
index 00000000000000..db9912a10d7e7e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-test2_ai02_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English test2_ai02 BertForSequenceClassification from ai02
+author: John Snow Labs
+name: test2_ai02
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test2_ai02` is a English model originally trained by ai02.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test2_ai02_en_5.5.1_3.0_1737936158807.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test2_ai02_en_5.5.1_3.0_1737936158807.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("test2_ai02","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("test2_ai02", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test2_ai02|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|405.9 MB|
+
+## References
+
+https://huggingface.co/ai02/test2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-test2_ai02_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-test2_ai02_pipeline_en.md
new file mode 100644
index 00000000000000..d44c218a656ab4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-test2_ai02_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English test2_ai02_pipeline pipeline BertForSequenceClassification from ai02
+author: John Snow Labs
+name: test2_ai02_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test2_ai02_pipeline` is a English model originally trained by ai02.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test2_ai02_pipeline_en_5.5.1_3.0_1737936181109.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test2_ai02_pipeline_en_5.5.1_3.0_1737936181109.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("test2_ai02_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("test2_ai02_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test2_ai02_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|405.9 MB|
+
+## References
+
+https://huggingface.co/ai02/test2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-test_10_image_en.md b/docs/_posts/ahmedlone127/2025-01-27-test_10_image_en.md
new file mode 100644
index 00000000000000..2efa9bf3f2da0d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-test_10_image_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English test_10_image ViTForImageClassification from vuongnhathien
+author: John Snow Labs
+name: test_10_image
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_10_image` is a English model originally trained by vuongnhathien.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_10_image_en_5.5.1_3.0_1737973990539.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_10_image_en_5.5.1_3.0_1737973990539.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""test_10_image","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("test_10_image","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_10_image|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.6 MB|
+
+## References
+
+https://huggingface.co/vuongnhathien/test-10-image
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-test_10_image_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-test_10_image_pipeline_en.md
new file mode 100644
index 00000000000000..4ba1bc59996b19
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-test_10_image_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English test_10_image_pipeline pipeline ViTForImageClassification from vuongnhathien
+author: John Snow Labs
+name: test_10_image_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_10_image_pipeline` is a English model originally trained by vuongnhathien.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_10_image_pipeline_en_5.5.1_3.0_1737974014270.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_10_image_pipeline_en_5.5.1_3.0_1737974014270.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("test_10_image_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("test_10_image_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_10_image_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.6 MB|
+
+## References
+
+https://huggingface.co/vuongnhathien/test-10-image
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-test_model_drerol74_en.md b/docs/_posts/ahmedlone127/2025-01-27-test_model_drerol74_en.md
new file mode 100644
index 00000000000000..19b79d439d9d39
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-test_model_drerol74_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English test_model_drerol74 DistilBertForSequenceClassification from drerol74
+author: John Snow Labs
+name: test_model_drerol74
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_model_drerol74` is a English model originally trained by drerol74.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_model_drerol74_en_5.5.1_3.0_1737939886185.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_model_drerol74_en_5.5.1_3.0_1737939886185.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("test_model_drerol74","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("test_model_drerol74", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_model_drerol74|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/drerol74/test-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-test_model_drerol74_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-test_model_drerol74_pipeline_en.md
new file mode 100644
index 00000000000000..260ad7e88c2175
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-test_model_drerol74_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English test_model_drerol74_pipeline pipeline DistilBertForSequenceClassification from drerol74
+author: John Snow Labs
+name: test_model_drerol74_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_model_drerol74_pipeline` is a English model originally trained by drerol74.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_model_drerol74_pipeline_en_5.5.1_3.0_1737939899990.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_model_drerol74_pipeline_en_5.5.1_3.0_1737939899990.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("test_model_drerol74_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("test_model_drerol74_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_model_drerol74_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/drerol74/test-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-test_w5_long_en.md b/docs/_posts/ahmedlone127/2025-01-27-test_w5_long_en.md
new file mode 100644
index 00000000000000..abf10fda3a84e7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-test_w5_long_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English test_w5_long RoBertaEmbeddings from NbAiLabArchive
+author: John Snow Labs
+name: test_w5_long
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_w5_long` is a English model originally trained by NbAiLabArchive.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_w5_long_en_5.5.1_3.0_1738019537509.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_w5_long_en_5.5.1_3.0_1738019537509.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("test_w5_long","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("test_w5_long","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_w5_long|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|464.2 MB|
+
+## References
+
+https://huggingface.co/NbAiLabArchive/test_w5_long
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-test_w5_long_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-test_w5_long_pipeline_en.md
new file mode 100644
index 00000000000000..2f4e24b9cfbb9f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-test_w5_long_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English test_w5_long_pipeline pipeline RoBertaEmbeddings from NbAiLabArchive
+author: John Snow Labs
+name: test_w5_long_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_w5_long_pipeline` is a English model originally trained by NbAiLabArchive.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_w5_long_pipeline_en_5.5.1_3.0_1738019564867.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_w5_long_pipeline_en_5.5.1_3.0_1738019564867.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("test_w5_long_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("test_w5_long_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_w5_long_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|464.2 MB|
+
+## References
+
+https://huggingface.co/NbAiLabArchive/test_w5_long
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-test_w5_long_roberta_tokenizer_en.md b/docs/_posts/ahmedlone127/2025-01-27-test_w5_long_roberta_tokenizer_en.md
new file mode 100644
index 00000000000000..648db525872530
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-test_w5_long_roberta_tokenizer_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English test_w5_long_roberta_tokenizer RoBertaEmbeddings from NbAiLabArchive
+author: John Snow Labs
+name: test_w5_long_roberta_tokenizer
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_w5_long_roberta_tokenizer` is a English model originally trained by NbAiLabArchive.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_w5_long_roberta_tokenizer_en_5.5.1_3.0_1738019608060.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_w5_long_roberta_tokenizer_en_5.5.1_3.0_1738019608060.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("test_w5_long_roberta_tokenizer","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("test_w5_long_roberta_tokenizer","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_w5_long_roberta_tokenizer|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|465.1 MB|
+
+## References
+
+https://huggingface.co/NbAiLabArchive/test_w5_long_roberta_tokenizer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-test_w5_long_roberta_tokenizer_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-test_w5_long_roberta_tokenizer_pipeline_en.md
new file mode 100644
index 00000000000000..868bcf812737ed
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-test_w5_long_roberta_tokenizer_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English test_w5_long_roberta_tokenizer_pipeline pipeline RoBertaEmbeddings from NbAiLabArchive
+author: John Snow Labs
+name: test_w5_long_roberta_tokenizer_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_w5_long_roberta_tokenizer_pipeline` is a English model originally trained by NbAiLabArchive.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_w5_long_roberta_tokenizer_pipeline_en_5.5.1_3.0_1738019631559.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_w5_long_roberta_tokenizer_pipeline_en_5.5.1_3.0_1738019631559.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("test_w5_long_roberta_tokenizer_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("test_w5_long_roberta_tokenizer_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_w5_long_roberta_tokenizer_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|465.2 MB|
+
+## References
+
+https://huggingface.co/NbAiLabArchive/test_w5_long_roberta_tokenizer
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-text_classification_02_en.md b/docs/_posts/ahmedlone127/2025-01-27-text_classification_02_en.md
new file mode 100644
index 00000000000000..f5e31d94ca3142
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-text_classification_02_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English text_classification_02 DistilBertForSequenceClassification from allenzhangloveml
+author: John Snow Labs
+name: text_classification_02
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`text_classification_02` is a English model originally trained by allenzhangloveml.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/text_classification_02_en_5.5.1_3.0_1737939362240.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/text_classification_02_en_5.5.1_3.0_1737939362240.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("text_classification_02","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("text_classification_02", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|text_classification_02|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/allenzhangloveml/text_classification_02
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-text_classification_02_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-text_classification_02_pipeline_en.md
new file mode 100644
index 00000000000000..a196767a8df02d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-text_classification_02_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English text_classification_02_pipeline pipeline DistilBertForSequenceClassification from allenzhangloveml
+author: John Snow Labs
+name: text_classification_02_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`text_classification_02_pipeline` is a English model originally trained by allenzhangloveml.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/text_classification_02_pipeline_en_5.5.1_3.0_1737939376957.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/text_classification_02_pipeline_en_5.5.1_3.0_1737939376957.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("text_classification_02_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("text_classification_02_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|text_classification_02_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/allenzhangloveml/text_classification_02
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-text_classification_en.md b/docs/_posts/ahmedlone127/2025-01-27-text_classification_en.md
new file mode 100644
index 00000000000000..aabaa0f840720b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-text_classification_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English text_classification XlmRoBertaForSequenceClassification from AbrorBalxiyev
+author: John Snow Labs
+name: text_classification
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`text_classification` is a English model originally trained by AbrorBalxiyev.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/text_classification_en_5.5.1_3.0_1737958635833.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/text_classification_en_5.5.1_3.0_1737958635833.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("text_classification","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("text_classification", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|text_classification|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|825.2 MB|
+
+## References
+
+https://huggingface.co/AbrorBalxiyev/text-classification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-text_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-text_classification_pipeline_en.md
new file mode 100644
index 00000000000000..04b0e4c93ba7da
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-text_classification_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English text_classification_pipeline pipeline XlmRoBertaForSequenceClassification from AbrorBalxiyev
+author: John Snow Labs
+name: text_classification_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`text_classification_pipeline` is a English model originally trained by AbrorBalxiyev.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/text_classification_pipeline_en_5.5.1_3.0_1737958758910.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/text_classification_pipeline_en_5.5.1_3.0_1737958758910.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("text_classification_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("text_classification_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|text_classification_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|825.2 MB|
+
+## References
+
+https://huggingface.co/AbrorBalxiyev/text-classification
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-text_tonga_tonga_islands_music_en.md b/docs/_posts/ahmedlone127/2025-01-27-text_tonga_tonga_islands_music_en.md
new file mode 100644
index 00000000000000..f54283a3e5959f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-text_tonga_tonga_islands_music_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English text_tonga_tonga_islands_music BartTransformer from sander-wood
+author: John Snow Labs
+name: text_tonga_tonga_islands_music
+date: 2025-01-27
+tags: [en, open_source, onnx, text_generation, bart]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BartTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`text_tonga_tonga_islands_music` is a English model originally trained by sander-wood.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/text_tonga_tonga_islands_music_en_5.5.1_3.0_1737986561577.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/text_tonga_tonga_islands_music_en_5.5.1_3.0_1737986561577.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = BartTransformer.pretrained("text_tonga_tonga_islands_music","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = BartTransformer.pretrained("text_tonga_tonga_islands_music","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|text_tonga_tonga_islands_music|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|807.1 MB|
+
+## References
+
+https://huggingface.co/sander-wood/text-to-music
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-text_tonga_tonga_islands_music_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-text_tonga_tonga_islands_music_pipeline_en.md
new file mode 100644
index 00000000000000..80512a28bf765f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-text_tonga_tonga_islands_music_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English text_tonga_tonga_islands_music_pipeline pipeline BartTransformer from sander-wood
+author: John Snow Labs
+name: text_tonga_tonga_islands_music_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`text_tonga_tonga_islands_music_pipeline` is a English model originally trained by sander-wood.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/text_tonga_tonga_islands_music_pipeline_en_5.5.1_3.0_1737986602600.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/text_tonga_tonga_islands_music_pipeline_en_5.5.1_3.0_1737986602600.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("text_tonga_tonga_islands_music_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("text_tonga_tonga_islands_music_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|text_tonga_tonga_islands_music_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|807.1 MB|
+
+## References
+
+https://huggingface.co/sander-wood/text-to-music
+
+## Included Models
+
+- DocumentAssembler
+- BartTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-textsummarizer_en.md b/docs/_posts/ahmedlone127/2025-01-27-textsummarizer_en.md
new file mode 100644
index 00000000000000..eba7e8867b9e0c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-textsummarizer_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English textsummarizer T5Transformer from dheerajnarne
+author: John Snow Labs
+name: textsummarizer
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`textsummarizer` is a English model originally trained by dheerajnarne.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/textsummarizer_en_5.5.1_3.0_1737944547447.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/textsummarizer_en_5.5.1_3.0_1737944547447.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("textsummarizer","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("textsummarizer", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|textsummarizer|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|284.7 MB|
+
+## References
+
+https://huggingface.co/dheerajnarne/textsummarizer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-textsummarizer_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-textsummarizer_pipeline_en.md
new file mode 100644
index 00000000000000..abd00fa8aae353
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-textsummarizer_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English textsummarizer_pipeline pipeline T5Transformer from dheerajnarne
+author: John Snow Labs
+name: textsummarizer_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`textsummarizer_pipeline` is a English model originally trained by dheerajnarne.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/textsummarizer_pipeline_en_5.5.1_3.0_1737944571753.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/textsummarizer_pipeline_en_5.5.1_3.0_1737944571753.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("textsummarizer_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("textsummarizer_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|textsummarizer_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|284.7 MB|
+
+## References
+
+https://huggingface.co/dheerajnarne/textsummarizer
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-tiny_t5forconditionalgeneration_peft_internal_testing_en.md b/docs/_posts/ahmedlone127/2025-01-27-tiny_t5forconditionalgeneration_peft_internal_testing_en.md
new file mode 100644
index 00000000000000..7dd83ed15bd578
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-tiny_t5forconditionalgeneration_peft_internal_testing_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English tiny_t5forconditionalgeneration_peft_internal_testing T5Transformer from peft-internal-testing
+author: John Snow Labs
+name: tiny_t5forconditionalgeneration_peft_internal_testing
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_t5forconditionalgeneration_peft_internal_testing` is a English model originally trained by peft-internal-testing.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_t5forconditionalgeneration_peft_internal_testing_en_5.5.1_3.0_1737946040568.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_t5forconditionalgeneration_peft_internal_testing_en_5.5.1_3.0_1737946040568.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("tiny_t5forconditionalgeneration_peft_internal_testing","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("tiny_t5forconditionalgeneration_peft_internal_testing", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tiny_t5forconditionalgeneration_peft_internal_testing|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|4.5 MB|
+
+## References
+
+https://huggingface.co/peft-internal-testing/tiny-T5ForConditionalGeneration
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-tiny_t5forconditionalgeneration_peft_internal_testing_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-tiny_t5forconditionalgeneration_peft_internal_testing_pipeline_en.md
new file mode 100644
index 00000000000000..139968844641ea
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-tiny_t5forconditionalgeneration_peft_internal_testing_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English tiny_t5forconditionalgeneration_peft_internal_testing_pipeline pipeline T5Transformer from peft-internal-testing
+author: John Snow Labs
+name: tiny_t5forconditionalgeneration_peft_internal_testing_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_t5forconditionalgeneration_peft_internal_testing_pipeline` is a English model originally trained by peft-internal-testing.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_t5forconditionalgeneration_peft_internal_testing_pipeline_en_5.5.1_3.0_1737946041115.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_t5forconditionalgeneration_peft_internal_testing_pipeline_en_5.5.1_3.0_1737946041115.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("tiny_t5forconditionalgeneration_peft_internal_testing_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("tiny_t5forconditionalgeneration_peft_internal_testing_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tiny_t5forconditionalgeneration_peft_internal_testing_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|4.5 MB|
+
+## References
+
+https://huggingface.co/peft-internal-testing/tiny-T5ForConditionalGeneration
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-tiny_t5forconditionalgeneration_trl_internal_testing_en.md b/docs/_posts/ahmedlone127/2025-01-27-tiny_t5forconditionalgeneration_trl_internal_testing_en.md
new file mode 100644
index 00000000000000..51c9223fe35c1c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-tiny_t5forconditionalgeneration_trl_internal_testing_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English tiny_t5forconditionalgeneration_trl_internal_testing T5Transformer from trl-internal-testing
+author: John Snow Labs
+name: tiny_t5forconditionalgeneration_trl_internal_testing
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_t5forconditionalgeneration_trl_internal_testing` is a English model originally trained by trl-internal-testing.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_t5forconditionalgeneration_trl_internal_testing_en_5.5.1_3.0_1737944886882.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_t5forconditionalgeneration_trl_internal_testing_en_5.5.1_3.0_1737944886882.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("tiny_t5forconditionalgeneration_trl_internal_testing","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("tiny_t5forconditionalgeneration_trl_internal_testing", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tiny_t5forconditionalgeneration_trl_internal_testing|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|4.5 MB|
+
+## References
+
+https://huggingface.co/trl-internal-testing/tiny-T5ForConditionalGeneration
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-tiny_t5forconditionalgeneration_trl_internal_testing_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-tiny_t5forconditionalgeneration_trl_internal_testing_pipeline_en.md
new file mode 100644
index 00000000000000..f43daa72bd57fc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-tiny_t5forconditionalgeneration_trl_internal_testing_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English tiny_t5forconditionalgeneration_trl_internal_testing_pipeline pipeline T5Transformer from trl-internal-testing
+author: John Snow Labs
+name: tiny_t5forconditionalgeneration_trl_internal_testing_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_t5forconditionalgeneration_trl_internal_testing_pipeline` is a English model originally trained by trl-internal-testing.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_t5forconditionalgeneration_trl_internal_testing_pipeline_en_5.5.1_3.0_1737944887537.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_t5forconditionalgeneration_trl_internal_testing_pipeline_en_5.5.1_3.0_1737944887537.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("tiny_t5forconditionalgeneration_trl_internal_testing_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("tiny_t5forconditionalgeneration_trl_internal_testing_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tiny_t5forconditionalgeneration_trl_internal_testing_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|4.5 MB|
+
+## References
+
+https://huggingface.co/trl-internal-testing/tiny-T5ForConditionalGeneration
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-tinybert_finetuned_ner_en.md b/docs/_posts/ahmedlone127/2025-01-27-tinybert_finetuned_ner_en.md
new file mode 100644
index 00000000000000..104498149994e2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-tinybert_finetuned_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English tinybert_finetuned_ner BertForTokenClassification from adel-cybral
+author: John Snow Labs
+name: tinybert_finetuned_ner
+date: 2025-01-27
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tinybert_finetuned_ner` is a English model originally trained by adel-cybral.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tinybert_finetuned_ner_en_5.5.1_3.0_1738017776674.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tinybert_finetuned_ner_en_5.5.1_3.0_1738017776674.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("tinybert_finetuned_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("tinybert_finetuned_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tinybert_finetuned_ner|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|53.9 MB|
+
+## References
+
+https://huggingface.co/adel-cybral/TinyBERT-finetuned-NER
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-tinybert_finetuned_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-tinybert_finetuned_ner_pipeline_en.md
new file mode 100644
index 00000000000000..a1a15255ef2089
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-tinybert_finetuned_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English tinybert_finetuned_ner_pipeline pipeline BertForTokenClassification from adel-cybral
+author: John Snow Labs
+name: tinybert_finetuned_ner_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tinybert_finetuned_ner_pipeline` is a English model originally trained by adel-cybral.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tinybert_finetuned_ner_pipeline_en_5.5.1_3.0_1738017779302.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tinybert_finetuned_ner_pipeline_en_5.5.1_3.0_1738017779302.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("tinybert_finetuned_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("tinybert_finetuned_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tinybert_finetuned_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|53.9 MB|
+
+## References
+
+https://huggingface.co/adel-cybral/TinyBERT-finetuned-NER
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-tinystoriesproject_en.md b/docs/_posts/ahmedlone127/2025-01-27-tinystoriesproject_en.md
new file mode 100644
index 00000000000000..52718051d6fff4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-tinystoriesproject_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English tinystoriesproject GPT2Transformer from jackoyoungblood
+author: John Snow Labs
+name: tinystoriesproject
+date: 2025-01-27
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tinystoriesproject` is a English model originally trained by jackoyoungblood.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tinystoriesproject_en_5.5.1_3.0_1737995728214.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tinystoriesproject_en_5.5.1_3.0_1737995728214.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("tinystoriesproject","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("tinystoriesproject","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tinystoriesproject|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.4 MB|
+
+## References
+
+https://huggingface.co/jackoyoungblood/TinyStoriesProject
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-tinystoriesproject_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-tinystoriesproject_pipeline_en.md
new file mode 100644
index 00000000000000..3ec44c99237435
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-tinystoriesproject_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English tinystoriesproject_pipeline pipeline GPT2Transformer from jackoyoungblood
+author: John Snow Labs
+name: tinystoriesproject_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tinystoriesproject_pipeline` is a English model originally trained by jackoyoungblood.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tinystoriesproject_pipeline_en_5.5.1_3.0_1737995752314.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tinystoriesproject_pipeline_en_5.5.1_3.0_1737995752314.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("tinystoriesproject_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("tinystoriesproject_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tinystoriesproject_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.4 MB|
+
+## References
+
+https://huggingface.co/jackoyoungblood/TinyStoriesProject
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-tmp_thamed_chowdhury_en.md b/docs/_posts/ahmedlone127/2025-01-27-tmp_thamed_chowdhury_en.md
new file mode 100644
index 00000000000000..af6e49522d1d72
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-tmp_thamed_chowdhury_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English tmp_thamed_chowdhury T5Transformer from Thamed-Chowdhury
+author: John Snow Labs
+name: tmp_thamed_chowdhury
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tmp_thamed_chowdhury` is a English model originally trained by Thamed-Chowdhury.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tmp_thamed_chowdhury_en_5.5.1_3.0_1737991423634.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tmp_thamed_chowdhury_en_5.5.1_3.0_1737991423634.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("tmp_thamed_chowdhury","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("tmp_thamed_chowdhury", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tmp_thamed_chowdhury|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Thamed-Chowdhury/tmp
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-tmp_thamed_chowdhury_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-tmp_thamed_chowdhury_pipeline_en.md
new file mode 100644
index 00000000000000..fca9b320a69821
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-tmp_thamed_chowdhury_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English tmp_thamed_chowdhury_pipeline pipeline T5Transformer from Thamed-Chowdhury
+author: John Snow Labs
+name: tmp_thamed_chowdhury_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tmp_thamed_chowdhury_pipeline` is a English model originally trained by Thamed-Chowdhury.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tmp_thamed_chowdhury_pipeline_en_5.5.1_3.0_1737991474668.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tmp_thamed_chowdhury_pipeline_en_5.5.1_3.0_1737991474668.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("tmp_thamed_chowdhury_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("tmp_thamed_chowdhury_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tmp_thamed_chowdhury_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Thamed-Chowdhury/tmp
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-toxic_comments_classifier_distilbert_en.md b/docs/_posts/ahmedlone127/2025-01-27-toxic_comments_classifier_distilbert_en.md
new file mode 100644
index 00000000000000..7d01ac54edf5ce
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-toxic_comments_classifier_distilbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English toxic_comments_classifier_distilbert BertForSequenceClassification from dima806
+author: John Snow Labs
+name: toxic_comments_classifier_distilbert
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`toxic_comments_classifier_distilbert` is a English model originally trained by dima806.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/toxic_comments_classifier_distilbert_en_5.5.1_3.0_1738005232331.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/toxic_comments_classifier_distilbert_en_5.5.1_3.0_1738005232331.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("toxic_comments_classifier_distilbert","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("toxic_comments_classifier_distilbert", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|toxic_comments_classifier_distilbert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/dima806/toxic-comments-classifier-distilbert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-toxic_comments_classifier_distilbert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-toxic_comments_classifier_distilbert_pipeline_en.md
new file mode 100644
index 00000000000000..8f0d27ba6ed148
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-toxic_comments_classifier_distilbert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English toxic_comments_classifier_distilbert_pipeline pipeline BertForSequenceClassification from dima806
+author: John Snow Labs
+name: toxic_comments_classifier_distilbert_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`toxic_comments_classifier_distilbert_pipeline` is a English model originally trained by dima806.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/toxic_comments_classifier_distilbert_pipeline_en_5.5.1_3.0_1738005253827.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/toxic_comments_classifier_distilbert_pipeline_en_5.5.1_3.0_1738005253827.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("toxic_comments_classifier_distilbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("toxic_comments_classifier_distilbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|toxic_comments_classifier_distilbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/dima806/toxic-comments-classifier-distilbert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-traffic_sign_detection_dima806_en.md b/docs/_posts/ahmedlone127/2025-01-27-traffic_sign_detection_dima806_en.md
new file mode 100644
index 00000000000000..4edc5e2c5b2c7e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-traffic_sign_detection_dima806_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English traffic_sign_detection_dima806 ViTForImageClassification from dima806
+author: John Snow Labs
+name: traffic_sign_detection_dima806
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`traffic_sign_detection_dima806` is a English model originally trained by dima806.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/traffic_sign_detection_dima806_en_5.5.1_3.0_1737975040655.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/traffic_sign_detection_dima806_en_5.5.1_3.0_1737975040655.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""traffic_sign_detection_dima806","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("traffic_sign_detection_dima806","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|traffic_sign_detection_dima806|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.4 MB|
+
+## References
+
+https://huggingface.co/dima806/traffic_sign_detection
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-traffic_sign_detection_dima806_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-traffic_sign_detection_dima806_pipeline_en.md
new file mode 100644
index 00000000000000..b7f36a6e7736f7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-traffic_sign_detection_dima806_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English traffic_sign_detection_dima806_pipeline pipeline ViTForImageClassification from dima806
+author: John Snow Labs
+name: traffic_sign_detection_dima806_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`traffic_sign_detection_dima806_pipeline` is a English model originally trained by dima806.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/traffic_sign_detection_dima806_pipeline_en_5.5.1_3.0_1737975057151.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/traffic_sign_detection_dima806_pipeline_en_5.5.1_3.0_1737975057151.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("traffic_sign_detection_dima806_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("traffic_sign_detection_dima806_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|traffic_sign_detection_dima806_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.4 MB|
+
+## References
+
+https://huggingface.co/dima806/traffic_sign_detection
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-transcripts_clm_model_01_en.md b/docs/_posts/ahmedlone127/2025-01-27-transcripts_clm_model_01_en.md
new file mode 100644
index 00000000000000..65ca86b66b582c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-transcripts_clm_model_01_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English transcripts_clm_model_01 GPT2Transformer from cirec
+author: John Snow Labs
+name: transcripts_clm_model_01
+date: 2025-01-27
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`transcripts_clm_model_01` is a English model originally trained by cirec.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/transcripts_clm_model_01_en_5.5.1_3.0_1737995416029.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/transcripts_clm_model_01_en_5.5.1_3.0_1737995416029.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("transcripts_clm_model_01","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("transcripts_clm_model_01","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|transcripts_clm_model_01|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|308.4 MB|
+
+## References
+
+https://huggingface.co/cirec/transcripts-clm-model-01
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-transcripts_clm_model_01_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-transcripts_clm_model_01_pipeline_en.md
new file mode 100644
index 00000000000000..6e53a822ec751d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-transcripts_clm_model_01_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English transcripts_clm_model_01_pipeline pipeline GPT2Transformer from cirec
+author: John Snow Labs
+name: transcripts_clm_model_01_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`transcripts_clm_model_01_pipeline` is a English model originally trained by cirec.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/transcripts_clm_model_01_pipeline_en_5.5.1_3.0_1737995431376.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/transcripts_clm_model_01_pipeline_en_5.5.1_3.0_1737995431376.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("transcripts_clm_model_01_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("transcripts_clm_model_01_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|transcripts_clm_model_01_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|308.4 MB|
+
+## References
+
+https://huggingface.co/cirec/transcripts-clm-model-01
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-translater_en.md b/docs/_posts/ahmedlone127/2025-01-27-translater_en.md
new file mode 100644
index 00000000000000..a94dc9f0d0a009
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-translater_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English translater T5Transformer from Choudharyritu
+author: John Snow Labs
+name: translater
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`translater` is a English model originally trained by Choudharyritu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/translater_en_5.5.1_3.0_1737989673648.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/translater_en_5.5.1_3.0_1737989673648.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("translater","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("translater", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|translater|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|211.8 MB|
+
+## References
+
+https://huggingface.co/Choudharyritu/translater
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-translater_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-translater_pipeline_en.md
new file mode 100644
index 00000000000000..f231d42913a6e6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-translater_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English translater_pipeline pipeline T5Transformer from Choudharyritu
+author: John Snow Labs
+name: translater_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`translater_pipeline` is a English model originally trained by Choudharyritu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/translater_pipeline_en_5.5.1_3.0_1737989701706.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/translater_pipeline_en_5.5.1_3.0_1737989701706.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("translater_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("translater_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|translater_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|211.8 MB|
+
+## References
+
+https://huggingface.co/Choudharyritu/translater
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-travel_t5_small_zohaz_en.md b/docs/_posts/ahmedlone127/2025-01-27-travel_t5_small_zohaz_en.md
new file mode 100644
index 00000000000000..0124cc04866e9c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-travel_t5_small_zohaz_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English travel_t5_small_zohaz T5Transformer from Zohaz
+author: John Snow Labs
+name: travel_t5_small_zohaz
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`travel_t5_small_zohaz` is a English model originally trained by Zohaz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/travel_t5_small_zohaz_en_5.5.1_3.0_1738002213908.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/travel_t5_small_zohaz_en_5.5.1_3.0_1738002213908.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("travel_t5_small_zohaz","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("travel_t5_small_zohaz", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|travel_t5_small_zohaz|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|274.7 MB|
+
+## References
+
+https://huggingface.co/Zohaz/travel_t5-small
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-travel_t5_small_zohaz_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-travel_t5_small_zohaz_pipeline_en.md
new file mode 100644
index 00000000000000..53ce04b15c9e1d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-travel_t5_small_zohaz_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English travel_t5_small_zohaz_pipeline pipeline T5Transformer from Zohaz
+author: John Snow Labs
+name: travel_t5_small_zohaz_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`travel_t5_small_zohaz_pipeline` is a English model originally trained by Zohaz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/travel_t5_small_zohaz_pipeline_en_5.5.1_3.0_1738002231093.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/travel_t5_small_zohaz_pipeline_en_5.5.1_3.0_1738002231093.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("travel_t5_small_zohaz_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("travel_t5_small_zohaz_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|travel_t5_small_zohaz_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|274.7 MB|
+
+## References
+
+https://huggingface.co/Zohaz/travel_t5-small
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-ukrainian_mt5_small_keytotext_fiction_en.md b/docs/_posts/ahmedlone127/2025-01-27-ukrainian_mt5_small_keytotext_fiction_en.md
new file mode 100644
index 00000000000000..e6ec030c25509f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-ukrainian_mt5_small_keytotext_fiction_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English ukrainian_mt5_small_keytotext_fiction T5Transformer from iliushchenko
+author: John Snow Labs
+name: ukrainian_mt5_small_keytotext_fiction
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ukrainian_mt5_small_keytotext_fiction` is a English model originally trained by iliushchenko.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ukrainian_mt5_small_keytotext_fiction_en_5.5.1_3.0_1738007718260.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ukrainian_mt5_small_keytotext_fiction_en_5.5.1_3.0_1738007718260.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("ukrainian_mt5_small_keytotext_fiction","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("ukrainian_mt5_small_keytotext_fiction", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ukrainian_mt5_small_keytotext_fiction|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|316.4 MB|
+
+## References
+
+https://huggingface.co/iliushchenko/uk-mt5-small-keytotext-fiction
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-ukrainian_mt5_small_keytotext_fiction_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-ukrainian_mt5_small_keytotext_fiction_pipeline_en.md
new file mode 100644
index 00000000000000..43344de437cfd0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-ukrainian_mt5_small_keytotext_fiction_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English ukrainian_mt5_small_keytotext_fiction_pipeline pipeline T5Transformer from iliushchenko
+author: John Snow Labs
+name: ukrainian_mt5_small_keytotext_fiction_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ukrainian_mt5_small_keytotext_fiction_pipeline` is a English model originally trained by iliushchenko.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ukrainian_mt5_small_keytotext_fiction_pipeline_en_5.5.1_3.0_1738007737386.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ukrainian_mt5_small_keytotext_fiction_pipeline_en_5.5.1_3.0_1738007737386.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ukrainian_mt5_small_keytotext_fiction_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ukrainian_mt5_small_keytotext_fiction_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ukrainian_mt5_small_keytotext_fiction_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|316.4 MB|
+
+## References
+
+https://huggingface.co/iliushchenko/uk-mt5-small-keytotext-fiction
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-ul_interior_classification_en.md b/docs/_posts/ahmedlone127/2025-01-27-ul_interior_classification_en.md
new file mode 100644
index 00000000000000..75bffdba97f252
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-ul_interior_classification_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ul_interior_classification ViTForImageClassification from sharmajai901
+author: John Snow Labs
+name: ul_interior_classification
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ul_interior_classification` is a English model originally trained by sharmajai901.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ul_interior_classification_en_5.5.1_3.0_1737957271309.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ul_interior_classification_en_5.5.1_3.0_1737957271309.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""ul_interior_classification","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("ul_interior_classification","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ul_interior_classification|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.4 MB|
+
+## References
+
+https://huggingface.co/sharmajai901/UL_interior_classification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-ul_interior_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-ul_interior_classification_pipeline_en.md
new file mode 100644
index 00000000000000..a921c89645a9ba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-ul_interior_classification_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English ul_interior_classification_pipeline pipeline ViTForImageClassification from sharmajai901
+author: John Snow Labs
+name: ul_interior_classification_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ul_interior_classification_pipeline` is a English model originally trained by sharmajai901.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ul_interior_classification_pipeline_en_5.5.1_3.0_1737957287963.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ul_interior_classification_pipeline_en_5.5.1_3.0_1737957287963.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ul_interior_classification_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ul_interior_classification_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ul_interior_classification_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.4 MB|
+
+## References
+
+https://huggingface.co/sharmajai901/UL_interior_classification
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-urlbert_tiny_v3_phishing_classifier_en.md b/docs/_posts/ahmedlone127/2025-01-27-urlbert_tiny_v3_phishing_classifier_en.md
new file mode 100644
index 00000000000000..145a8520615639
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-urlbert_tiny_v3_phishing_classifier_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English urlbert_tiny_v3_phishing_classifier BertForSequenceClassification from CrabInHoney
+author: John Snow Labs
+name: urlbert_tiny_v3_phishing_classifier
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`urlbert_tiny_v3_phishing_classifier` is a English model originally trained by CrabInHoney.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/urlbert_tiny_v3_phishing_classifier_en_5.5.1_3.0_1738006073522.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/urlbert_tiny_v3_phishing_classifier_en_5.5.1_3.0_1738006073522.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("urlbert_tiny_v3_phishing_classifier","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("urlbert_tiny_v3_phishing_classifier", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|urlbert_tiny_v3_phishing_classifier|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|13.9 MB|
+
+## References
+
+https://huggingface.co/CrabInHoney/urlbert-tiny-v3-phishing-classifier
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-urlbert_tiny_v3_phishing_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-urlbert_tiny_v3_phishing_classifier_pipeline_en.md
new file mode 100644
index 00000000000000..ea592bbc83093a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-urlbert_tiny_v3_phishing_classifier_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English urlbert_tiny_v3_phishing_classifier_pipeline pipeline BertForSequenceClassification from CrabInHoney
+author: John Snow Labs
+name: urlbert_tiny_v3_phishing_classifier_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`urlbert_tiny_v3_phishing_classifier_pipeline` is a English model originally trained by CrabInHoney.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/urlbert_tiny_v3_phishing_classifier_pipeline_en_5.5.1_3.0_1738006074467.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/urlbert_tiny_v3_phishing_classifier_pipeline_en_5.5.1_3.0_1738006074467.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("urlbert_tiny_v3_phishing_classifier_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("urlbert_tiny_v3_phishing_classifier_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|urlbert_tiny_v3_phishing_classifier_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|13.9 MB|
+
+## References
+
+https://huggingface.co/CrabInHoney/urlbert-tiny-v3-phishing-classifier
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vehicle_10_types_image_detection_en.md b/docs/_posts/ahmedlone127/2025-01-27-vehicle_10_types_image_detection_en.md
new file mode 100644
index 00000000000000..4afb7e8c25e8a1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vehicle_10_types_image_detection_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vehicle_10_types_image_detection ViTForImageClassification from dima806
+author: John Snow Labs
+name: vehicle_10_types_image_detection
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vehicle_10_types_image_detection` is a English model originally trained by dima806.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vehicle_10_types_image_detection_en_5.5.1_3.0_1737974417547.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vehicle_10_types_image_detection_en_5.5.1_3.0_1737974417547.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vehicle_10_types_image_detection","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vehicle_10_types_image_detection","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vehicle_10_types_image_detection|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/dima806/vehicle_10_types_image_detection
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vehicle_10_types_image_detection_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-vehicle_10_types_image_detection_pipeline_en.md
new file mode 100644
index 00000000000000..16200beb0e41bc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vehicle_10_types_image_detection_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vehicle_10_types_image_detection_pipeline pipeline ViTForImageClassification from dima806
+author: John Snow Labs
+name: vehicle_10_types_image_detection_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vehicle_10_types_image_detection_pipeline` is a English model originally trained by dima806.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vehicle_10_types_image_detection_pipeline_en_5.5.1_3.0_1737974434260.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vehicle_10_types_image_detection_pipeline_en_5.5.1_3.0_1737974434260.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vehicle_10_types_image_detection_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vehicle_10_types_image_detection_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vehicle_10_types_image_detection_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/dima806/vehicle_10_types_image_detection
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vietnamese_t5_summary_model_falcon_en.md b/docs/_posts/ahmedlone127/2025-01-27-vietnamese_t5_summary_model_falcon_en.md
new file mode 100644
index 00000000000000..187472b58847d7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vietnamese_t5_summary_model_falcon_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English vietnamese_t5_summary_model_falcon T5Transformer from mrzaizai2k
+author: John Snow Labs
+name: vietnamese_t5_summary_model_falcon
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vietnamese_t5_summary_model_falcon` is a English model originally trained by mrzaizai2k.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vietnamese_t5_summary_model_falcon_en_5.5.1_3.0_1737962660714.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vietnamese_t5_summary_model_falcon_en_5.5.1_3.0_1737962660714.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("vietnamese_t5_summary_model_falcon","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("vietnamese_t5_summary_model_falcon", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vietnamese_t5_summary_model_falcon|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|271.1 MB|
+
+## References
+
+https://huggingface.co/mrzaizai2k/vietnamese_t5_summary_model_falcon
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vietnamese_t5_summary_model_falcon_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-vietnamese_t5_summary_model_falcon_pipeline_en.md
new file mode 100644
index 00000000000000..30c265c6a4f384
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vietnamese_t5_summary_model_falcon_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vietnamese_t5_summary_model_falcon_pipeline pipeline T5Transformer from mrzaizai2k
+author: John Snow Labs
+name: vietnamese_t5_summary_model_falcon_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vietnamese_t5_summary_model_falcon_pipeline` is a English model originally trained by mrzaizai2k.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vietnamese_t5_summary_model_falcon_pipeline_en_5.5.1_3.0_1737962677860.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vietnamese_t5_summary_model_falcon_pipeline_en_5.5.1_3.0_1737962677860.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vietnamese_t5_summary_model_falcon_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vietnamese_t5_summary_model_falcon_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vietnamese_t5_summary_model_falcon_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|271.1 MB|
+
+## References
+
+https://huggingface.co/mrzaizai2k/vietnamese_t5_summary_model_falcon
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vit5_large_vimex_en.md b/docs/_posts/ahmedlone127/2025-01-27-vit5_large_vimex_en.md
new file mode 100644
index 00000000000000..4ae17b12524a7d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vit5_large_vimex_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English vit5_large_vimex T5Transformer from ngwgsang
+author: John Snow Labs
+name: vit5_large_vimex
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit5_large_vimex` is a English model originally trained by ngwgsang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit5_large_vimex_en_5.5.1_3.0_1737992915469.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit5_large_vimex_en_5.5.1_3.0_1737992915469.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("vit5_large_vimex","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("vit5_large_vimex", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit5_large_vimex|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|3.0 GB|
+
+## References
+
+https://huggingface.co/ngwgsang/vit5-large-vimex
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vit5_large_vimex_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-vit5_large_vimex_pipeline_en.md
new file mode 100644
index 00000000000000..c43db4ba2b768a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vit5_large_vimex_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit5_large_vimex_pipeline pipeline T5Transformer from ngwgsang
+author: John Snow Labs
+name: vit5_large_vimex_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit5_large_vimex_pipeline` is a English model originally trained by ngwgsang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit5_large_vimex_pipeline_en_5.5.1_3.0_1737993076394.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit5_large_vimex_pipeline_en_5.5.1_3.0_1737993076394.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit5_large_vimex_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit5_large_vimex_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit5_large_vimex_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|3.0 GB|
+
+## References
+
+https://huggingface.co/ngwgsang/vit5-large-vimex
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vit5_student_en.md b/docs/_posts/ahmedlone127/2025-01-27-vit5_student_en.md
new file mode 100644
index 00000000000000..b06c7214b1d86e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vit5_student_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English vit5_student T5Transformer from ngwgsang
+author: John Snow Labs
+name: vit5_student
+date: 2025-01-27
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit5_student` is a English model originally trained by ngwgsang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit5_student_en_5.5.1_3.0_1737980292740.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit5_student_en_5.5.1_3.0_1737980292740.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("vit5_student","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("vit5_student", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit5_student|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|484.7 MB|
+
+## References
+
+https://huggingface.co/ngwgsang/vit5-student
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vit5_student_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-vit5_student_pipeline_en.md
new file mode 100644
index 00000000000000..fe627154cdd4c6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vit5_student_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit5_student_pipeline pipeline T5Transformer from ngwgsang
+author: John Snow Labs
+name: vit5_student_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit5_student_pipeline` is a English model originally trained by ngwgsang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit5_student_pipeline_en_5.5.1_3.0_1737980458800.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit5_student_pipeline_en_5.5.1_3.0_1737980458800.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit5_student_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit5_student_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit5_student_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|484.7 MB|
+
+## References
+
+https://huggingface.co/ngwgsang/vit5-student
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vit_base_beans_demo_v5_brightmzb_en.md b/docs/_posts/ahmedlone127/2025-01-27-vit_base_beans_demo_v5_brightmzb_en.md
new file mode 100644
index 00000000000000..fabbf61334482a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vit_base_beans_demo_v5_brightmzb_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_base_beans_demo_v5_brightmzb ViTForImageClassification from Brightmzb
+author: John Snow Labs
+name: vit_base_beans_demo_v5_brightmzb
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_beans_demo_v5_brightmzb` is a English model originally trained by Brightmzb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_beans_demo_v5_brightmzb_en_5.5.1_3.0_1737974237214.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_beans_demo_v5_brightmzb_en_5.5.1_3.0_1737974237214.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vit_base_beans_demo_v5_brightmzb","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vit_base_beans_demo_v5_brightmzb","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_beans_demo_v5_brightmzb|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/Brightmzb/vit-base-beans-demo-v5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vit_base_beans_demo_v5_brightmzb_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-vit_base_beans_demo_v5_brightmzb_pipeline_en.md
new file mode 100644
index 00000000000000..4b1337d00c3f72
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vit_base_beans_demo_v5_brightmzb_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_base_beans_demo_v5_brightmzb_pipeline pipeline ViTForImageClassification from Brightmzb
+author: John Snow Labs
+name: vit_base_beans_demo_v5_brightmzb_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_beans_demo_v5_brightmzb_pipeline` is a English model originally trained by Brightmzb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_beans_demo_v5_brightmzb_pipeline_en_5.5.1_3.0_1737974253855.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_beans_demo_v5_brightmzb_pipeline_en_5.5.1_3.0_1737974253855.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_base_beans_demo_v5_brightmzb_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_base_beans_demo_v5_brightmzb_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_beans_demo_v5_brightmzb_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/Brightmzb/vit-base-beans-demo-v5
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vit_base_beans_demo_v5_digo_prayudha_en.md b/docs/_posts/ahmedlone127/2025-01-27-vit_base_beans_demo_v5_digo_prayudha_en.md
new file mode 100644
index 00000000000000..a95e99565bfccb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vit_base_beans_demo_v5_digo_prayudha_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_base_beans_demo_v5_digo_prayudha ViTForImageClassification from digo-prayudha
+author: John Snow Labs
+name: vit_base_beans_demo_v5_digo_prayudha
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_beans_demo_v5_digo_prayudha` is a English model originally trained by digo-prayudha.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_beans_demo_v5_digo_prayudha_en_5.5.1_3.0_1737957069814.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_beans_demo_v5_digo_prayudha_en_5.5.1_3.0_1737957069814.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vit_base_beans_demo_v5_digo_prayudha","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vit_base_beans_demo_v5_digo_prayudha","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_beans_demo_v5_digo_prayudha|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/digo-prayudha/vit-base-beans-demo-v5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vit_base_beans_demo_v5_digo_prayudha_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-vit_base_beans_demo_v5_digo_prayudha_pipeline_en.md
new file mode 100644
index 00000000000000..f7590beb6e52f7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vit_base_beans_demo_v5_digo_prayudha_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_base_beans_demo_v5_digo_prayudha_pipeline pipeline ViTForImageClassification from digo-prayudha
+author: John Snow Labs
+name: vit_base_beans_demo_v5_digo_prayudha_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_beans_demo_v5_digo_prayudha_pipeline` is a English model originally trained by digo-prayudha.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_beans_demo_v5_digo_prayudha_pipeline_en_5.5.1_3.0_1737957086490.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_beans_demo_v5_digo_prayudha_pipeline_en_5.5.1_3.0_1737957086490.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_base_beans_demo_v5_digo_prayudha_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_base_beans_demo_v5_digo_prayudha_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_beans_demo_v5_digo_prayudha_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/digo-prayudha/vit-base-beans-demo-v5
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vit_base_beans_fmagot01_en.md b/docs/_posts/ahmedlone127/2025-01-27-vit_base_beans_fmagot01_en.md
new file mode 100644
index 00000000000000..c73ecde19a3063
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vit_base_beans_fmagot01_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_base_beans_fmagot01 ViTForImageClassification from fmagot01
+author: John Snow Labs
+name: vit_base_beans_fmagot01
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_beans_fmagot01` is a English model originally trained by fmagot01.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_beans_fmagot01_en_5.5.1_3.0_1737974839637.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_beans_fmagot01_en_5.5.1_3.0_1737974839637.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vit_base_beans_fmagot01","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vit_base_beans_fmagot01","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_beans_fmagot01|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/fmagot01/vit-base-beans
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vit_base_beans_fmagot01_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-vit_base_beans_fmagot01_pipeline_en.md
new file mode 100644
index 00000000000000..4a86c286dd795c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vit_base_beans_fmagot01_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_base_beans_fmagot01_pipeline pipeline ViTForImageClassification from fmagot01
+author: John Snow Labs
+name: vit_base_beans_fmagot01_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_beans_fmagot01_pipeline` is a English model originally trained by fmagot01.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_beans_fmagot01_pipeline_en_5.5.1_3.0_1737974860349.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_beans_fmagot01_pipeline_en_5.5.1_3.0_1737974860349.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_base_beans_fmagot01_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_base_beans_fmagot01_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_beans_fmagot01_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/fmagot01/vit-base-beans
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vit_base_classification_nepal_bhasa_en.md b/docs/_posts/ahmedlone127/2025-01-27-vit_base_classification_nepal_bhasa_en.md
new file mode 100644
index 00000000000000..a98de44ec5c038
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vit_base_classification_nepal_bhasa_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_base_classification_nepal_bhasa ViTForImageClassification from akashmaggon
+author: John Snow Labs
+name: vit_base_classification_nepal_bhasa
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_classification_nepal_bhasa` is a English model originally trained by akashmaggon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_classification_nepal_bhasa_en_5.5.1_3.0_1737974140240.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_classification_nepal_bhasa_en_5.5.1_3.0_1737974140240.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vit_base_classification_nepal_bhasa","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vit_base_classification_nepal_bhasa","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_classification_nepal_bhasa|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/akashmaggon/vit-base-classification-new
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vit_base_classification_nepal_bhasa_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-vit_base_classification_nepal_bhasa_pipeline_en.md
new file mode 100644
index 00000000000000..af245bb6d3d8df
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vit_base_classification_nepal_bhasa_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_base_classification_nepal_bhasa_pipeline pipeline ViTForImageClassification from akashmaggon
+author: John Snow Labs
+name: vit_base_classification_nepal_bhasa_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_classification_nepal_bhasa_pipeline` is a English model originally trained by akashmaggon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_classification_nepal_bhasa_pipeline_en_5.5.1_3.0_1737974161048.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_classification_nepal_bhasa_pipeline_en_5.5.1_3.0_1737974161048.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_base_classification_nepal_bhasa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_base_classification_nepal_bhasa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_classification_nepal_bhasa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/akashmaggon/vit-base-classification-new
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vit_base_oxford_iiit_pets_ketutsatria_en.md b/docs/_posts/ahmedlone127/2025-01-27-vit_base_oxford_iiit_pets_ketutsatria_en.md
new file mode 100644
index 00000000000000..26deddab25bdaf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vit_base_oxford_iiit_pets_ketutsatria_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_base_oxford_iiit_pets_ketutsatria ViTForImageClassification from ketutsatria
+author: John Snow Labs
+name: vit_base_oxford_iiit_pets_ketutsatria
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_oxford_iiit_pets_ketutsatria` is a English model originally trained by ketutsatria.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_oxford_iiit_pets_ketutsatria_en_5.5.1_3.0_1737957343792.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_oxford_iiit_pets_ketutsatria_en_5.5.1_3.0_1737957343792.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vit_base_oxford_iiit_pets_ketutsatria","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vit_base_oxford_iiit_pets_ketutsatria","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_oxford_iiit_pets_ketutsatria|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.4 MB|
+
+## References
+
+https://huggingface.co/ketutsatria/vit-base-oxford-iiit-pets
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vit_base_oxford_iiit_pets_ketutsatria_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-vit_base_oxford_iiit_pets_ketutsatria_pipeline_en.md
new file mode 100644
index 00000000000000..c45262ef522c56
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vit_base_oxford_iiit_pets_ketutsatria_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_base_oxford_iiit_pets_ketutsatria_pipeline pipeline ViTForImageClassification from ketutsatria
+author: John Snow Labs
+name: vit_base_oxford_iiit_pets_ketutsatria_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_oxford_iiit_pets_ketutsatria_pipeline` is a English model originally trained by ketutsatria.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_oxford_iiit_pets_ketutsatria_pipeline_en_5.5.1_3.0_1737957361763.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_oxford_iiit_pets_ketutsatria_pipeline_en_5.5.1_3.0_1737957361763.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_base_oxford_iiit_pets_ketutsatria_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_base_oxford_iiit_pets_ketutsatria_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_oxford_iiit_pets_ketutsatria_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.4 MB|
+
+## References
+
+https://huggingface.co/ketutsatria/vit-base-oxford-iiit-pets
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vit_base_patch16_224_cifar10_nateraw_en.md b/docs/_posts/ahmedlone127/2025-01-27-vit_base_patch16_224_cifar10_nateraw_en.md
new file mode 100644
index 00000000000000..efe9c3fe05e205
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vit_base_patch16_224_cifar10_nateraw_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_base_patch16_224_cifar10_nateraw ViTForImageClassification from nateraw
+author: John Snow Labs
+name: vit_base_patch16_224_cifar10_nateraw
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_patch16_224_cifar10_nateraw` is a English model originally trained by nateraw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_cifar10_nateraw_en_5.5.1_3.0_1738021584413.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_cifar10_nateraw_en_5.5.1_3.0_1738021584413.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vit_base_patch16_224_cifar10_nateraw","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vit_base_patch16_224_cifar10_nateraw","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_patch16_224_cifar10_nateraw|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/nateraw/vit-base-patch16-224-cifar10
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vit_base_patch16_224_cifar10_nateraw_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-vit_base_patch16_224_cifar10_nateraw_pipeline_en.md
new file mode 100644
index 00000000000000..253aa6cb918958
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vit_base_patch16_224_cifar10_nateraw_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_base_patch16_224_cifar10_nateraw_pipeline pipeline ViTForImageClassification from nateraw
+author: John Snow Labs
+name: vit_base_patch16_224_cifar10_nateraw_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_patch16_224_cifar10_nateraw_pipeline` is a English model originally trained by nateraw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_cifar10_nateraw_pipeline_en_5.5.1_3.0_1738021600391.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_cifar10_nateraw_pipeline_en_5.5.1_3.0_1738021600391.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_base_patch16_224_cifar10_nateraw_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_base_patch16_224_cifar10_nateraw_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_patch16_224_cifar10_nateraw_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/nateraw/vit-base-patch16-224-cifar10
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vit_base_patch16_224_in21k_finetuned_cifar10_nielsr_en.md b/docs/_posts/ahmedlone127/2025-01-27-vit_base_patch16_224_in21k_finetuned_cifar10_nielsr_en.md
new file mode 100644
index 00000000000000..092edf1319edeb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vit_base_patch16_224_in21k_finetuned_cifar10_nielsr_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_base_patch16_224_in21k_finetuned_cifar10_nielsr ViTForImageClassification from nielsr
+author: John Snow Labs
+name: vit_base_patch16_224_in21k_finetuned_cifar10_nielsr
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_patch16_224_in21k_finetuned_cifar10_nielsr` is a English model originally trained by nielsr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_in21k_finetuned_cifar10_nielsr_en_5.5.1_3.0_1737974517110.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_in21k_finetuned_cifar10_nielsr_en_5.5.1_3.0_1737974517110.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vit_base_patch16_224_in21k_finetuned_cifar10_nielsr","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vit_base_patch16_224_in21k_finetuned_cifar10_nielsr","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_patch16_224_in21k_finetuned_cifar10_nielsr|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/nielsr/vit-base-patch16-224-in21k-finetuned-cifar10
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vit_base_patch16_224_in21k_finetuned_cifar10_nielsr_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-vit_base_patch16_224_in21k_finetuned_cifar10_nielsr_pipeline_en.md
new file mode 100644
index 00000000000000..f70235be3b2f71
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vit_base_patch16_224_in21k_finetuned_cifar10_nielsr_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_base_patch16_224_in21k_finetuned_cifar10_nielsr_pipeline pipeline ViTForImageClassification from nielsr
+author: John Snow Labs
+name: vit_base_patch16_224_in21k_finetuned_cifar10_nielsr_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_patch16_224_in21k_finetuned_cifar10_nielsr_pipeline` is a English model originally trained by nielsr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_in21k_finetuned_cifar10_nielsr_pipeline_en_5.5.1_3.0_1737974533957.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_in21k_finetuned_cifar10_nielsr_pipeline_en_5.5.1_3.0_1737974533957.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_base_patch16_224_in21k_finetuned_cifar10_nielsr_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_base_patch16_224_in21k_finetuned_cifar10_nielsr_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_patch16_224_in21k_finetuned_cifar10_nielsr_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/nielsr/vit-base-patch16-224-in21k-finetuned-cifar10
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vit_base_patch16_224_in21k_finetuned_cottonpestclassification_v3a_ossetian_en.md b/docs/_posts/ahmedlone127/2025-01-27-vit_base_patch16_224_in21k_finetuned_cottonpestclassification_v3a_ossetian_en.md
new file mode 100644
index 00000000000000..84c3b229ab2ef0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vit_base_patch16_224_in21k_finetuned_cottonpestclassification_v3a_ossetian_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_base_patch16_224_in21k_finetuned_cottonpestclassification_v3a_ossetian ViTForImageClassification from ashishp-wiai
+author: John Snow Labs
+name: vit_base_patch16_224_in21k_finetuned_cottonpestclassification_v3a_ossetian
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_patch16_224_in21k_finetuned_cottonpestclassification_v3a_ossetian` is a English model originally trained by ashishp-wiai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_in21k_finetuned_cottonpestclassification_v3a_ossetian_en_5.5.1_3.0_1737974690814.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_in21k_finetuned_cottonpestclassification_v3a_ossetian_en_5.5.1_3.0_1737974690814.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vit_base_patch16_224_in21k_finetuned_cottonpestclassification_v3a_ossetian","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vit_base_patch16_224_in21k_finetuned_cottonpestclassification_v3a_ossetian","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_patch16_224_in21k_finetuned_cottonpestclassification_v3a_ossetian|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.2 MB|
+
+## References
+
+https://huggingface.co/ashishp-wiai/vit-base-patch16-224-in21k-finetuned-CottonPestClassification_v3a_os
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vit_base_patch16_224_in21k_finetuned_cottonpestclassification_v3a_ossetian_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-vit_base_patch16_224_in21k_finetuned_cottonpestclassification_v3a_ossetian_pipeline_en.md
new file mode 100644
index 00000000000000..706a8f7a97efbe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vit_base_patch16_224_in21k_finetuned_cottonpestclassification_v3a_ossetian_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_base_patch16_224_in21k_finetuned_cottonpestclassification_v3a_ossetian_pipeline pipeline ViTForImageClassification from ashishp-wiai
+author: John Snow Labs
+name: vit_base_patch16_224_in21k_finetuned_cottonpestclassification_v3a_ossetian_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_patch16_224_in21k_finetuned_cottonpestclassification_v3a_ossetian_pipeline` is a English model originally trained by ashishp-wiai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_in21k_finetuned_cottonpestclassification_v3a_ossetian_pipeline_en_5.5.1_3.0_1737974709233.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_in21k_finetuned_cottonpestclassification_v3a_ossetian_pipeline_en_5.5.1_3.0_1737974709233.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_base_patch16_224_in21k_finetuned_cottonpestclassification_v3a_ossetian_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_base_patch16_224_in21k_finetuned_cottonpestclassification_v3a_ossetian_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_patch16_224_in21k_finetuned_cottonpestclassification_v3a_ossetian_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.2 MB|
+
+## References
+
+https://huggingface.co/ashishp-wiai/vit-base-patch16-224-in21k-finetuned-CottonPestClassification_v3a_os
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vit_base_patch16_224_in21k_lung_and_colon_cancer_en.md b/docs/_posts/ahmedlone127/2025-01-27-vit_base_patch16_224_in21k_lung_and_colon_cancer_en.md
new file mode 100644
index 00000000000000..71a9614b8e92b4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vit_base_patch16_224_in21k_lung_and_colon_cancer_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_base_patch16_224_in21k_lung_and_colon_cancer ViTForImageClassification from DunnBC22
+author: John Snow Labs
+name: vit_base_patch16_224_in21k_lung_and_colon_cancer
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_patch16_224_in21k_lung_and_colon_cancer` is a English model originally trained by DunnBC22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_in21k_lung_and_colon_cancer_en_5.5.1_3.0_1738021684590.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_in21k_lung_and_colon_cancer_en_5.5.1_3.0_1738021684590.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vit_base_patch16_224_in21k_lung_and_colon_cancer","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vit_base_patch16_224_in21k_lung_and_colon_cancer","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_patch16_224_in21k_lung_and_colon_cancer|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/DunnBC22/vit-base-patch16-224-in21k_lung_and_colon_cancer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vit_base_patch16_224_in21k_lung_and_colon_cancer_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-vit_base_patch16_224_in21k_lung_and_colon_cancer_pipeline_en.md
new file mode 100644
index 00000000000000..dd8c80b9b8a8ae
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vit_base_patch16_224_in21k_lung_and_colon_cancer_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_base_patch16_224_in21k_lung_and_colon_cancer_pipeline pipeline ViTForImageClassification from DunnBC22
+author: John Snow Labs
+name: vit_base_patch16_224_in21k_lung_and_colon_cancer_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_patch16_224_in21k_lung_and_colon_cancer_pipeline` is a English model originally trained by DunnBC22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_in21k_lung_and_colon_cancer_pipeline_en_5.5.1_3.0_1738021702816.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_in21k_lung_and_colon_cancer_pipeline_en_5.5.1_3.0_1738021702816.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_base_patch16_224_in21k_lung_and_colon_cancer_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_base_patch16_224_in21k_lung_and_colon_cancer_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_patch16_224_in21k_lung_and_colon_cancer_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/DunnBC22/vit-base-patch16-224-in21k_lung_and_colon_cancer
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vit_base_patch16_224_u8_40b_en.md b/docs/_posts/ahmedlone127/2025-01-27-vit_base_patch16_224_u8_40b_en.md
new file mode 100644
index 00000000000000..da08c7fa620a93
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vit_base_patch16_224_u8_40b_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_base_patch16_224_u8_40b ViTForImageClassification from Augusto777
+author: John Snow Labs
+name: vit_base_patch16_224_u8_40b
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_patch16_224_u8_40b` is a English model originally trained by Augusto777.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_u8_40b_en_5.5.1_3.0_1737974689259.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_u8_40b_en_5.5.1_3.0_1737974689259.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vit_base_patch16_224_u8_40b","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vit_base_patch16_224_u8_40b","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_patch16_224_u8_40b|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/Augusto777/vit-base-patch16-224-U8-40b
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vit_base_patch16_224_u8_40b_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-vit_base_patch16_224_u8_40b_pipeline_en.md
new file mode 100644
index 00000000000000..3b8105f83f9655
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vit_base_patch16_224_u8_40b_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_base_patch16_224_u8_40b_pipeline pipeline ViTForImageClassification from Augusto777
+author: John Snow Labs
+name: vit_base_patch16_224_u8_40b_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_patch16_224_u8_40b_pipeline` is a English model originally trained by Augusto777.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_u8_40b_pipeline_en_5.5.1_3.0_1737974709232.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_u8_40b_pipeline_en_5.5.1_3.0_1737974709232.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_base_patch16_224_u8_40b_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_base_patch16_224_u8_40b_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_patch16_224_u8_40b_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/Augusto777/vit-base-patch16-224-U8-40b
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vit_base_patch16_224_venda_u10_12_en.md b/docs/_posts/ahmedlone127/2025-01-27-vit_base_patch16_224_venda_u10_12_en.md
new file mode 100644
index 00000000000000..15417c4a1f14c0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vit_base_patch16_224_venda_u10_12_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_base_patch16_224_venda_u10_12 ViTForImageClassification from Augusto777
+author: John Snow Labs
+name: vit_base_patch16_224_venda_u10_12
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_patch16_224_venda_u10_12` is a English model originally trained by Augusto777.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_venda_u10_12_en_5.5.1_3.0_1737974122513.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_venda_u10_12_en_5.5.1_3.0_1737974122513.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vit_base_patch16_224_venda_u10_12","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vit_base_patch16_224_venda_u10_12","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_patch16_224_venda_u10_12|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/Augusto777/vit-base-patch16-224-ve-U10-12
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vit_base_patch16_224_venda_u10_12_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-vit_base_patch16_224_venda_u10_12_pipeline_en.md
new file mode 100644
index 00000000000000..e9682f5249ffb5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vit_base_patch16_224_venda_u10_12_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_base_patch16_224_venda_u10_12_pipeline pipeline ViTForImageClassification from Augusto777
+author: John Snow Labs
+name: vit_base_patch16_224_venda_u10_12_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_patch16_224_venda_u10_12_pipeline` is a English model originally trained by Augusto777.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_venda_u10_12_pipeline_en_5.5.1_3.0_1737974140113.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_venda_u10_12_pipeline_en_5.5.1_3.0_1737974140113.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_base_patch16_224_venda_u10_12_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_base_patch16_224_venda_u10_12_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_patch16_224_venda_u10_12_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/Augusto777/vit-base-patch16-224-ve-U10-12
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vit_base_violence_detection_en.md b/docs/_posts/ahmedlone127/2025-01-27-vit_base_violence_detection_en.md
new file mode 100644
index 00000000000000..6ece1fd0fce546
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vit_base_violence_detection_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_base_violence_detection ViTForImageClassification from jaranohaal
+author: John Snow Labs
+name: vit_base_violence_detection
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_violence_detection` is a English model originally trained by jaranohaal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_violence_detection_en_5.5.1_3.0_1738021576232.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_violence_detection_en_5.5.1_3.0_1738021576232.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vit_base_violence_detection","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vit_base_violence_detection","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_violence_detection|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|320.7 MB|
+
+## References
+
+https://huggingface.co/jaranohaal/vit-base-violence-detection
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vit_base_violence_detection_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-vit_base_violence_detection_pipeline_en.md
new file mode 100644
index 00000000000000..cb40c895f398f0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vit_base_violence_detection_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_base_violence_detection_pipeline pipeline ViTForImageClassification from jaranohaal
+author: John Snow Labs
+name: vit_base_violence_detection_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_violence_detection_pipeline` is a English model originally trained by jaranohaal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_violence_detection_pipeline_en_5.5.1_3.0_1738021592514.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_violence_detection_pipeline_en_5.5.1_3.0_1738021592514.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_base_violence_detection_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_base_violence_detection_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_violence_detection_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|320.7 MB|
+
+## References
+
+https://huggingface.co/jaranohaal/vit-base-violence-detection
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vit_devshubham_en.md b/docs/_posts/ahmedlone127/2025-01-27-vit_devshubham_en.md
new file mode 100644
index 00000000000000..5ecb274826ac5a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vit_devshubham_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_devshubham ViTForImageClassification from DevShubham
+author: John Snow Labs
+name: vit_devshubham
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_devshubham` is a English model originally trained by DevShubham.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_devshubham_en_5.5.1_3.0_1737974677865.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_devshubham_en_5.5.1_3.0_1737974677865.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vit_devshubham","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vit_devshubham","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_devshubham|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|324.2 MB|
+
+## References
+
+https://huggingface.co/DevShubham/vit
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vit_devshubham_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-vit_devshubham_pipeline_en.md
new file mode 100644
index 00000000000000..91c0d43ad4e841
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vit_devshubham_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_devshubham_pipeline pipeline ViTForImageClassification from DevShubham
+author: John Snow Labs
+name: vit_devshubham_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_devshubham_pipeline` is a English model originally trained by DevShubham.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_devshubham_pipeline_en_5.5.1_3.0_1737974694574.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_devshubham_pipeline_en_5.5.1_3.0_1737974694574.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_devshubham_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_devshubham_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_devshubham_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|324.2 MB|
+
+## References
+
+https://huggingface.co/DevShubham/vit
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vit_doclaynet_base_en.md b/docs/_posts/ahmedlone127/2025-01-27-vit_doclaynet_base_en.md
new file mode 100644
index 00000000000000..f6451bfd2e25df
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vit_doclaynet_base_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_doclaynet_base ViTForImageClassification from kaixkhazaki
+author: John Snow Labs
+name: vit_doclaynet_base
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_doclaynet_base` is a English model originally trained by kaixkhazaki.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_doclaynet_base_en_5.5.1_3.0_1737956905220.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_doclaynet_base_en_5.5.1_3.0_1737956905220.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vit_doclaynet_base","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vit_doclaynet_base","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_doclaynet_base|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/kaixkhazaki/vit_doclaynet_base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vit_doclaynet_base_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-vit_doclaynet_base_pipeline_en.md
new file mode 100644
index 00000000000000..05ed0a0d9ec715
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vit_doclaynet_base_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_doclaynet_base_pipeline pipeline ViTForImageClassification from kaixkhazaki
+author: John Snow Labs
+name: vit_doclaynet_base_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_doclaynet_base_pipeline` is a English model originally trained by kaixkhazaki.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_doclaynet_base_pipeline_en_5.5.1_3.0_1737956921903.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_doclaynet_base_pipeline_en_5.5.1_3.0_1737956921903.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_doclaynet_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_doclaynet_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_doclaynet_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/kaixkhazaki/vit_doclaynet_base
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vit_driver_drowsiness_detection_en.md b/docs/_posts/ahmedlone127/2025-01-27-vit_driver_drowsiness_detection_en.md
new file mode 100644
index 00000000000000..e97ce23861b7f0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vit_driver_drowsiness_detection_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_driver_drowsiness_detection ViTForImageClassification from chbh7051
+author: John Snow Labs
+name: vit_driver_drowsiness_detection
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_driver_drowsiness_detection` is a English model originally trained by chbh7051.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_driver_drowsiness_detection_en_5.5.1_3.0_1737974102037.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_driver_drowsiness_detection_en_5.5.1_3.0_1737974102037.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vit_driver_drowsiness_detection","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vit_driver_drowsiness_detection","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_driver_drowsiness_detection|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/chbh7051/vit-driver-drowsiness-detection
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vit_driver_drowsiness_detection_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-vit_driver_drowsiness_detection_pipeline_en.md
new file mode 100644
index 00000000000000..ecf27278dfb915
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vit_driver_drowsiness_detection_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_driver_drowsiness_detection_pipeline pipeline ViTForImageClassification from chbh7051
+author: John Snow Labs
+name: vit_driver_drowsiness_detection_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_driver_drowsiness_detection_pipeline` is a English model originally trained by chbh7051.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_driver_drowsiness_detection_pipeline_en_5.5.1_3.0_1737974118977.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_driver_drowsiness_detection_pipeline_en_5.5.1_3.0_1737974118977.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_driver_drowsiness_detection_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_driver_drowsiness_detection_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_driver_drowsiness_detection_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/chbh7051/vit-driver-drowsiness-detection
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vit_epochs5_batch32_lr5e_05_size224_tiles9_seed42_q2_complexity_en.md b/docs/_posts/ahmedlone127/2025-01-27-vit_epochs5_batch32_lr5e_05_size224_tiles9_seed42_q2_complexity_en.md
new file mode 100644
index 00000000000000..5b41397b1b96ce
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vit_epochs5_batch32_lr5e_05_size224_tiles9_seed42_q2_complexity_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_epochs5_batch32_lr5e_05_size224_tiles9_seed42_q2_complexity ViTForImageClassification from Omriy123
+author: John Snow Labs
+name: vit_epochs5_batch32_lr5e_05_size224_tiles9_seed42_q2_complexity
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_epochs5_batch32_lr5e_05_size224_tiles9_seed42_q2_complexity` is a English model originally trained by Omriy123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_epochs5_batch32_lr5e_05_size224_tiles9_seed42_q2_complexity_en_5.5.1_3.0_1738022277308.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_epochs5_batch32_lr5e_05_size224_tiles9_seed42_q2_complexity_en_5.5.1_3.0_1738022277308.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vit_epochs5_batch32_lr5e_05_size224_tiles9_seed42_q2_complexity","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vit_epochs5_batch32_lr5e_05_size224_tiles9_seed42_q2_complexity","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_epochs5_batch32_lr5e_05_size224_tiles9_seed42_q2_complexity|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/Omriy123/vit_epochs5_batch32_lr5e-05_size224_tiles9_seed42_q2_complexity
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vit_epochs5_batch32_lr5e_05_size224_tiles9_seed42_q2_complexity_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-vit_epochs5_batch32_lr5e_05_size224_tiles9_seed42_q2_complexity_pipeline_en.md
new file mode 100644
index 00000000000000..4e61bb4604e60f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vit_epochs5_batch32_lr5e_05_size224_tiles9_seed42_q2_complexity_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_epochs5_batch32_lr5e_05_size224_tiles9_seed42_q2_complexity_pipeline pipeline ViTForImageClassification from Omriy123
+author: John Snow Labs
+name: vit_epochs5_batch32_lr5e_05_size224_tiles9_seed42_q2_complexity_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_epochs5_batch32_lr5e_05_size224_tiles9_seed42_q2_complexity_pipeline` is a English model originally trained by Omriy123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_epochs5_batch32_lr5e_05_size224_tiles9_seed42_q2_complexity_pipeline_en_5.5.1_3.0_1738022303124.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_epochs5_batch32_lr5e_05_size224_tiles9_seed42_q2_complexity_pipeline_en_5.5.1_3.0_1738022303124.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_epochs5_batch32_lr5e_05_size224_tiles9_seed42_q2_complexity_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_epochs5_batch32_lr5e_05_size224_tiles9_seed42_q2_complexity_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_epochs5_batch32_lr5e_05_size224_tiles9_seed42_q2_complexity_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/Omriy123/vit_epochs5_batch32_lr5e-05_size224_tiles9_seed42_q2_complexity
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vit_facial_expression_recognition_thao2202_en.md b/docs/_posts/ahmedlone127/2025-01-27-vit_facial_expression_recognition_thao2202_en.md
new file mode 100644
index 00000000000000..bbb3fc883f803d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vit_facial_expression_recognition_thao2202_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_facial_expression_recognition_thao2202 ViTForImageClassification from Thao2202
+author: John Snow Labs
+name: vit_facial_expression_recognition_thao2202
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_facial_expression_recognition_thao2202` is a English model originally trained by Thao2202.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_facial_expression_recognition_thao2202_en_5.5.1_3.0_1738021640655.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_facial_expression_recognition_thao2202_en_5.5.1_3.0_1738021640655.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vit_facial_expression_recognition_thao2202","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vit_facial_expression_recognition_thao2202","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_facial_expression_recognition_thao2202|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/Thao2202/vit-Facial-Expression-Recognition
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vit_facial_expression_recognition_thao2202_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-vit_facial_expression_recognition_thao2202_pipeline_en.md
new file mode 100644
index 00000000000000..cbc642cf012fd6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vit_facial_expression_recognition_thao2202_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_facial_expression_recognition_thao2202_pipeline pipeline ViTForImageClassification from Thao2202
+author: John Snow Labs
+name: vit_facial_expression_recognition_thao2202_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_facial_expression_recognition_thao2202_pipeline` is a English model originally trained by Thao2202.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_facial_expression_recognition_thao2202_pipeline_en_5.5.1_3.0_1738021656942.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_facial_expression_recognition_thao2202_pipeline_en_5.5.1_3.0_1738021656942.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_facial_expression_recognition_thao2202_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_facial_expression_recognition_thao2202_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_facial_expression_recognition_thao2202_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/Thao2202/vit-Facial-Expression-Recognition
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vit_final_driver_drowsiness_detection_en.md b/docs/_posts/ahmedlone127/2025-01-27-vit_final_driver_drowsiness_detection_en.md
new file mode 100644
index 00000000000000..bb533d30fd70e2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vit_final_driver_drowsiness_detection_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_final_driver_drowsiness_detection ViTForImageClassification from chbh7051
+author: John Snow Labs
+name: vit_final_driver_drowsiness_detection
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_final_driver_drowsiness_detection` is a English model originally trained by chbh7051.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_final_driver_drowsiness_detection_en_5.5.1_3.0_1737974977789.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_final_driver_drowsiness_detection_en_5.5.1_3.0_1737974977789.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vit_final_driver_drowsiness_detection","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vit_final_driver_drowsiness_detection","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_final_driver_drowsiness_detection|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/chbh7051/vit-final-driver-drowsiness-detection
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vit_final_driver_drowsiness_detection_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-vit_final_driver_drowsiness_detection_pipeline_en.md
new file mode 100644
index 00000000000000..5877baf18b473c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vit_final_driver_drowsiness_detection_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_final_driver_drowsiness_detection_pipeline pipeline ViTForImageClassification from chbh7051
+author: John Snow Labs
+name: vit_final_driver_drowsiness_detection_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_final_driver_drowsiness_detection_pipeline` is a English model originally trained by chbh7051.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_final_driver_drowsiness_detection_pipeline_en_5.5.1_3.0_1737974997218.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_final_driver_drowsiness_detection_pipeline_en_5.5.1_3.0_1737974997218.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_final_driver_drowsiness_detection_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_final_driver_drowsiness_detection_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_final_driver_drowsiness_detection_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/chbh7051/vit-final-driver-drowsiness-detection
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vit_mae_base_classifier_en.md b/docs/_posts/ahmedlone127/2025-01-27-vit_mae_base_classifier_en.md
new file mode 100644
index 00000000000000..f5923b83456117
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vit_mae_base_classifier_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_mae_base_classifier ViTForImageClassification from jaypratap
+author: John Snow Labs
+name: vit_mae_base_classifier
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_mae_base_classifier` is a English model originally trained by jaypratap.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_mae_base_classifier_en_5.5.1_3.0_1737975092086.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_mae_base_classifier_en_5.5.1_3.0_1737975092086.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vit_mae_base_classifier","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vit_mae_base_classifier","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_mae_base_classifier|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|322.2 MB|
+
+## References
+
+https://huggingface.co/jaypratap/vit-mae-base-classifier
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vit_mae_base_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-vit_mae_base_classifier_pipeline_en.md
new file mode 100644
index 00000000000000..d4e6696fcbdde9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vit_mae_base_classifier_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_mae_base_classifier_pipeline pipeline ViTForImageClassification from jaypratap
+author: John Snow Labs
+name: vit_mae_base_classifier_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_mae_base_classifier_pipeline` is a English model originally trained by jaypratap.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_mae_base_classifier_pipeline_en_5.5.1_3.0_1737975108073.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_mae_base_classifier_pipeline_en_5.5.1_3.0_1737975108073.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_mae_base_classifier_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_mae_base_classifier_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_mae_base_classifier_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|322.2 MB|
+
+## References
+
+https://huggingface.co/jaypratap/vit-mae-base-classifier
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vit_plantnet300k_en.md b/docs/_posts/ahmedlone127/2025-01-27-vit_plantnet300k_en.md
new file mode 100644
index 00000000000000..a0741b708fa75f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vit_plantnet300k_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_plantnet300k ViTForImageClassification from janjibDEV
+author: John Snow Labs
+name: vit_plantnet300k
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_plantnet300k` is a English model originally trained by janjibDEV.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_plantnet300k_en_5.5.1_3.0_1737973990867.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_plantnet300k_en_5.5.1_3.0_1737973990867.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vit_plantnet300k","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vit_plantnet300k","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_plantnet300k|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.9 MB|
+
+## References
+
+https://huggingface.co/janjibDEV/vit-plantnet300k
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vit_plantnet300k_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-vit_plantnet300k_pipeline_en.md
new file mode 100644
index 00000000000000..6a3764673d9203
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vit_plantnet300k_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_plantnet300k_pipeline pipeline ViTForImageClassification from janjibDEV
+author: John Snow Labs
+name: vit_plantnet300k_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_plantnet300k_pipeline` is a English model originally trained by janjibDEV.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_plantnet300k_pipeline_en_5.5.1_3.0_1737974011798.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_plantnet300k_pipeline_en_5.5.1_3.0_1737974011798.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_plantnet300k_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_plantnet300k_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_plantnet300k_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.9 MB|
+
+## References
+
+https://huggingface.co/janjibDEV/vit-plantnet300k
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vit_real_fake_classification_v3_en.md b/docs/_posts/ahmedlone127/2025-01-27-vit_real_fake_classification_v3_en.md
new file mode 100644
index 00000000000000..4c3eb93ba4b5bb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vit_real_fake_classification_v3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_real_fake_classification_v3 ViTForImageClassification from date3k2
+author: John Snow Labs
+name: vit_real_fake_classification_v3
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_real_fake_classification_v3` is a English model originally trained by date3k2.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_real_fake_classification_v3_en_5.5.1_3.0_1737974034922.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_real_fake_classification_v3_en_5.5.1_3.0_1737974034922.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vit_real_fake_classification_v3","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vit_real_fake_classification_v3","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_real_fake_classification_v3|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/date3k2/vit-real-fake-classification-v3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vit_real_fake_classification_v3_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-vit_real_fake_classification_v3_pipeline_en.md
new file mode 100644
index 00000000000000..4ce13be09800dd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vit_real_fake_classification_v3_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_real_fake_classification_v3_pipeline pipeline ViTForImageClassification from date3k2
+author: John Snow Labs
+name: vit_real_fake_classification_v3_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_real_fake_classification_v3_pipeline` is a English model originally trained by date3k2.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_real_fake_classification_v3_pipeline_en_5.5.1_3.0_1737974051191.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_real_fake_classification_v3_pipeline_en_5.5.1_3.0_1737974051191.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_real_fake_classification_v3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_real_fake_classification_v3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_real_fake_classification_v3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/date3k2/vit-real-fake-classification-v3
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vit_with_hidden_states_en.md b/docs/_posts/ahmedlone127/2025-01-27-vit_with_hidden_states_en.md
new file mode 100644
index 00000000000000..8d107e501f56dd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vit_with_hidden_states_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_with_hidden_states ViTForImageClassification from IlyasMoutawwakil
+author: John Snow Labs
+name: vit_with_hidden_states
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_with_hidden_states` is a English model originally trained by IlyasMoutawwakil.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_with_hidden_states_en_5.5.1_3.0_1738021959793.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_with_hidden_states_en_5.5.1_3.0_1738021959793.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vit_with_hidden_states","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vit_with_hidden_states","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_with_hidden_states|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|324.2 MB|
+
+## References
+
+https://huggingface.co/IlyasMoutawwakil/vit-with-hidden_states
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vit_with_hidden_states_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-vit_with_hidden_states_pipeline_en.md
new file mode 100644
index 00000000000000..74eee91e21aef7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vit_with_hidden_states_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_with_hidden_states_pipeline pipeline ViTForImageClassification from IlyasMoutawwakil
+author: John Snow Labs
+name: vit_with_hidden_states_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_with_hidden_states_pipeline` is a English model originally trained by IlyasMoutawwakil.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_with_hidden_states_pipeline_en_5.5.1_3.0_1738021976192.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_with_hidden_states_pipeline_en_5.5.1_3.0_1738021976192.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_with_hidden_states_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_with_hidden_states_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_with_hidden_states_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|324.2 MB|
+
+## References
+
+https://huggingface.co/IlyasMoutawwakil/vit-with-hidden_states
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vits_age_gender_detect_en.md b/docs/_posts/ahmedlone127/2025-01-27-vits_age_gender_detect_en.md
new file mode 100644
index 00000000000000..27245ad667f858
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vits_age_gender_detect_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vits_age_gender_detect ViTForImageClassification from circulus
+author: John Snow Labs
+name: vits_age_gender_detect
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vits_age_gender_detect` is a English model originally trained by circulus.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vits_age_gender_detect_en_5.5.1_3.0_1738021820001.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vits_age_gender_detect_en_5.5.1_3.0_1738021820001.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vits_age_gender_detect","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vits_age_gender_detect","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vits_age_gender_detect|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/circulus/vits-age-gender-detect
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-vits_age_gender_detect_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-vits_age_gender_detect_pipeline_en.md
new file mode 100644
index 00000000000000..721f75637118af
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-vits_age_gender_detect_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vits_age_gender_detect_pipeline pipeline ViTForImageClassification from circulus
+author: John Snow Labs
+name: vits_age_gender_detect_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vits_age_gender_detect_pipeline` is a English model originally trained by circulus.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vits_age_gender_detect_pipeline_en_5.5.1_3.0_1738021875598.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vits_age_gender_detect_pipeline_en_5.5.1_3.0_1738021875598.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vits_age_gender_detect_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vits_age_gender_detect_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vits_age_gender_detect_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/circulus/vits-age-gender-detect
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-withinapps_ndd_claroline_test_content_en.md b/docs/_posts/ahmedlone127/2025-01-27-withinapps_ndd_claroline_test_content_en.md
new file mode 100644
index 00000000000000..cc2e38f0a037a5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-withinapps_ndd_claroline_test_content_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English withinapps_ndd_claroline_test_content DistilBertForSequenceClassification from lgk03
+author: John Snow Labs
+name: withinapps_ndd_claroline_test_content
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`withinapps_ndd_claroline_test_content` is a English model originally trained by lgk03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/withinapps_ndd_claroline_test_content_en_5.5.1_3.0_1737939816659.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/withinapps_ndd_claroline_test_content_en_5.5.1_3.0_1737939816659.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("withinapps_ndd_claroline_test_content","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("withinapps_ndd_claroline_test_content", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|withinapps_ndd_claroline_test_content|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/lgk03/WITHINAPPS_NDD-claroline_test-content
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-withinapps_ndd_claroline_test_content_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-withinapps_ndd_claroline_test_content_pipeline_en.md
new file mode 100644
index 00000000000000..5af2e7be96e5b9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-withinapps_ndd_claroline_test_content_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English withinapps_ndd_claroline_test_content_pipeline pipeline DistilBertForSequenceClassification from lgk03
+author: John Snow Labs
+name: withinapps_ndd_claroline_test_content_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`withinapps_ndd_claroline_test_content_pipeline` is a English model originally trained by lgk03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/withinapps_ndd_claroline_test_content_pipeline_en_5.5.1_3.0_1737939829771.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/withinapps_ndd_claroline_test_content_pipeline_en_5.5.1_3.0_1737939829771.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("withinapps_ndd_claroline_test_content_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("withinapps_ndd_claroline_test_content_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|withinapps_ndd_claroline_test_content_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/lgk03/WITHINAPPS_NDD-claroline_test-content
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-withinapps_ndd_pagekit_test_tags_en.md b/docs/_posts/ahmedlone127/2025-01-27-withinapps_ndd_pagekit_test_tags_en.md
new file mode 100644
index 00000000000000..e902e4d31bc613
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-withinapps_ndd_pagekit_test_tags_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English withinapps_ndd_pagekit_test_tags DistilBertForSequenceClassification from lgk03
+author: John Snow Labs
+name: withinapps_ndd_pagekit_test_tags
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`withinapps_ndd_pagekit_test_tags` is a English model originally trained by lgk03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/withinapps_ndd_pagekit_test_tags_en_5.5.1_3.0_1737939993584.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/withinapps_ndd_pagekit_test_tags_en_5.5.1_3.0_1737939993584.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("withinapps_ndd_pagekit_test_tags","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("withinapps_ndd_pagekit_test_tags", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|withinapps_ndd_pagekit_test_tags|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/lgk03/WITHINAPPS_NDD-pagekit_test-tags
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-withinapps_ndd_pagekit_test_tags_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-withinapps_ndd_pagekit_test_tags_pipeline_en.md
new file mode 100644
index 00000000000000..858cc7ef848291
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-withinapps_ndd_pagekit_test_tags_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English withinapps_ndd_pagekit_test_tags_pipeline pipeline DistilBertForSequenceClassification from lgk03
+author: John Snow Labs
+name: withinapps_ndd_pagekit_test_tags_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`withinapps_ndd_pagekit_test_tags_pipeline` is a English model originally trained by lgk03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/withinapps_ndd_pagekit_test_tags_pipeline_en_5.5.1_3.0_1737940007797.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/withinapps_ndd_pagekit_test_tags_pipeline_en_5.5.1_3.0_1737940007797.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("withinapps_ndd_pagekit_test_tags_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("withinapps_ndd_pagekit_test_tags_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|withinapps_ndd_pagekit_test_tags_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/lgk03/WITHINAPPS_NDD-pagekit_test-tags
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-wolfssl_roberta_en.md b/docs/_posts/ahmedlone127/2025-01-27-wolfssl_roberta_en.md
new file mode 100644
index 00000000000000..32247b22bfaefe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-wolfssl_roberta_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English wolfssl_roberta RoBertaEmbeddings from EdGoh95
+author: John Snow Labs
+name: wolfssl_roberta
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`wolfssl_roberta` is a English model originally trained by EdGoh95.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/wolfssl_roberta_en_5.5.1_3.0_1738019616673.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/wolfssl_roberta_en_5.5.1_3.0_1738019616673.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("wolfssl_roberta","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("wolfssl_roberta","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|wolfssl_roberta|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|310.7 MB|
+
+## References
+
+https://huggingface.co/EdGoh95/WolfSSL-ROBERTa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-wolfssl_roberta_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-wolfssl_roberta_pipeline_en.md
new file mode 100644
index 00000000000000..25ae48e584b30d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-wolfssl_roberta_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English wolfssl_roberta_pipeline pipeline RoBertaEmbeddings from EdGoh95
+author: John Snow Labs
+name: wolfssl_roberta_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`wolfssl_roberta_pipeline` is a English model originally trained by EdGoh95.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/wolfssl_roberta_pipeline_en_5.5.1_3.0_1738019632239.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/wolfssl_roberta_pipeline_en_5.5.1_3.0_1738019632239.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("wolfssl_roberta_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("wolfssl_roberta_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|wolfssl_roberta_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|310.8 MB|
+
+## References
+
+https://huggingface.co/EdGoh95/WolfSSL-ROBERTa
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_arman_persian_farsi_en.md b/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_arman_persian_farsi_en.md
new file mode 100644
index 00000000000000..357f67d01d1180
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_arman_persian_farsi_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_arman_persian_farsi XlmRoBertaForTokenClassification from rezzzzzaaaaaa
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_arman_persian_farsi
+date: 2025-01-27
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_arman_persian_farsi` is a English model originally trained by rezzzzzaaaaaa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_arman_persian_farsi_en_5.5.1_3.0_1737969154331.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_arman_persian_farsi_en_5.5.1_3.0_1737969154331.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_arman_persian_farsi","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_arman_persian_farsi", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_arman_persian_farsi|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|827.6 MB|
+
+## References
+
+https://huggingface.co/rezzzzzaaaaaa/xlm-roberta-base-finetuned-arman-fa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_arman_persian_farsi_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_arman_persian_farsi_pipeline_en.md
new file mode 100644
index 00000000000000..7bf5328e0cce82
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_arman_persian_farsi_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_arman_persian_farsi_pipeline pipeline XlmRoBertaForTokenClassification from rezzzzzaaaaaa
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_arman_persian_farsi_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_arman_persian_farsi_pipeline` is a English model originally trained by rezzzzzaaaaaa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_arman_persian_farsi_pipeline_en_5.5.1_3.0_1737969238033.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_arman_persian_farsi_pipeline_en_5.5.1_3.0_1737969238033.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_arman_persian_farsi_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_arman_persian_farsi_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_arman_persian_farsi_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|827.6 MB|
+
+## References
+
+https://huggingface.co/rezzzzzaaaaaa/xlm-roberta-base-finetuned-arman-fa
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_panx_all_esperesa_en.md b/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_panx_all_esperesa_en.md
new file mode 100644
index 00000000000000..10251d88154c79
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_panx_all_esperesa_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_esperesa XlmRoBertaForTokenClassification from esperesa
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_esperesa
+date: 2025-01-27
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_esperesa` is a English model originally trained by esperesa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_esperesa_en_5.5.1_3.0_1737968644014.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_esperesa_en_5.5.1_3.0_1737968644014.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_esperesa","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_esperesa", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_esperesa|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|859.8 MB|
+
+## References
+
+https://huggingface.co/esperesa/xlm-roberta-base-finetuned-panx-all
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_panx_all_esperesa_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_panx_all_esperesa_pipeline_en.md
new file mode 100644
index 00000000000000..50788387029b8d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_panx_all_esperesa_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_esperesa_pipeline pipeline XlmRoBertaForTokenClassification from esperesa
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_esperesa_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_esperesa_pipeline` is a English model originally trained by esperesa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_esperesa_pipeline_en_5.5.1_3.0_1737968720299.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_esperesa_pipeline_en_5.5.1_3.0_1737968720299.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_esperesa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_esperesa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_esperesa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|859.8 MB|
+
+## References
+
+https://huggingface.co/esperesa/xlm-roberta-base-finetuned-panx-all
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_panx_german_abdelwahab201_en.md b/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_panx_german_abdelwahab201_en.md
new file mode 100644
index 00000000000000..155dcc0663e6b7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_panx_german_abdelwahab201_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_abdelwahab201 XlmRoBertaForTokenClassification from Abdelwahab201
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_abdelwahab201
+date: 2025-01-27
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_abdelwahab201` is a English model originally trained by Abdelwahab201.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_abdelwahab201_en_5.5.1_3.0_1737968847267.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_abdelwahab201_en_5.5.1_3.0_1737968847267.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_abdelwahab201","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_abdelwahab201", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_abdelwahab201|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/Abdelwahab201/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_panx_german_abdelwahab201_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_panx_german_abdelwahab201_pipeline_en.md
new file mode 100644
index 00000000000000..ddfd6b43e30860
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_panx_german_abdelwahab201_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_abdelwahab201_pipeline pipeline XlmRoBertaForTokenClassification from Abdelwahab201
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_abdelwahab201_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_abdelwahab201_pipeline` is a English model originally trained by Abdelwahab201.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_abdelwahab201_pipeline_en_5.5.1_3.0_1737968939385.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_abdelwahab201_pipeline_en_5.5.1_3.0_1737968939385.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_abdelwahab201_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_abdelwahab201_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_abdelwahab201_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/Abdelwahab201/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_panx_german_c4big_en.md b/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_panx_german_c4big_en.md
new file mode 100644
index 00000000000000..2461fc4d546aa3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_panx_german_c4big_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_c4big XlmRoBertaForTokenClassification from c4big
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_c4big
+date: 2025-01-27
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_c4big` is a English model originally trained by c4big.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_c4big_en_5.5.1_3.0_1737968722751.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_c4big_en_5.5.1_3.0_1737968722751.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_c4big","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_c4big", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_c4big|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/c4big/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_panx_german_c4big_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_panx_german_c4big_pipeline_en.md
new file mode 100644
index 00000000000000..05c01b505d7534
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_panx_german_c4big_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_c4big_pipeline pipeline XlmRoBertaForTokenClassification from c4big
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_c4big_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_c4big_pipeline` is a English model originally trained by c4big.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_c4big_pipeline_en_5.5.1_3.0_1737968801133.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_c4big_pipeline_en_5.5.1_3.0_1737968801133.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_c4big_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_c4big_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_c4big_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/c4big/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_panx_german_fibleep_en.md b/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_panx_german_fibleep_en.md
new file mode 100644
index 00000000000000..a9757d675d0f42
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_panx_german_fibleep_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_fibleep XlmRoBertaForTokenClassification from fibleep
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_fibleep
+date: 2025-01-27
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_fibleep` is a English model originally trained by fibleep.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_fibleep_en_5.5.1_3.0_1737969027912.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_fibleep_en_5.5.1_3.0_1737969027912.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_fibleep","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_fibleep", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_fibleep|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|854.7 MB|
+
+## References
+
+https://huggingface.co/fibleep/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_panx_german_fibleep_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_panx_german_fibleep_pipeline_en.md
new file mode 100644
index 00000000000000..0ebab97d3c6b12
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_panx_german_fibleep_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_fibleep_pipeline pipeline XlmRoBertaForTokenClassification from fibleep
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_fibleep_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_fibleep_pipeline` is a English model originally trained by fibleep.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_fibleep_pipeline_en_5.5.1_3.0_1737969095414.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_fibleep_pipeline_en_5.5.1_3.0_1737969095414.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_fibleep_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_fibleep_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_fibleep_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|854.8 MB|
+
+## References
+
+https://huggingface.co/fibleep/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_panx_german_gogd_en.md b/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_panx_german_gogd_en.md
new file mode 100644
index 00000000000000..e1349a025199e2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_panx_german_gogd_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_gogd XlmRoBertaForTokenClassification from GoGD
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_gogd
+date: 2025-01-27
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_gogd` is a English model originally trained by GoGD.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_gogd_en_5.5.1_3.0_1737968645710.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_gogd_en_5.5.1_3.0_1737968645710.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_gogd","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_gogd", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_gogd|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/GoGD/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_panx_german_gogd_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_panx_german_gogd_pipeline_en.md
new file mode 100644
index 00000000000000..ae2b177e029af2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_panx_german_gogd_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_gogd_pipeline pipeline XlmRoBertaForTokenClassification from GoGD
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_gogd_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_gogd_pipeline` is a English model originally trained by GoGD.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_gogd_pipeline_en_5.5.1_3.0_1737968724358.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_gogd_pipeline_en_5.5.1_3.0_1737968724358.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_gogd_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_gogd_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_gogd_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/GoGD/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_panx_german_oscarnav_en.md b/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_panx_german_oscarnav_en.md
new file mode 100644
index 00000000000000..d414fd62bc79ae
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_panx_german_oscarnav_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_oscarnav XlmRoBertaForTokenClassification from OscarNav
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_oscarnav
+date: 2025-01-27
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_oscarnav` is a English model originally trained by OscarNav.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_oscarnav_en_5.5.1_3.0_1737968847571.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_oscarnav_en_5.5.1_3.0_1737968847571.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_oscarnav","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_oscarnav", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_oscarnav|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/OscarNav/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_panx_german_oscarnav_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_panx_german_oscarnav_pipeline_en.md
new file mode 100644
index 00000000000000..e813d6c755bfaf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_panx_german_oscarnav_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_oscarnav_pipeline pipeline XlmRoBertaForTokenClassification from OscarNav
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_oscarnav_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_oscarnav_pipeline` is a English model originally trained by OscarNav.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_oscarnav_pipeline_en_5.5.1_3.0_1737968939674.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_oscarnav_pipeline_en_5.5.1_3.0_1737968939674.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_oscarnav_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_oscarnav_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_oscarnav_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/OscarNav/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_panx_german_peterliuwt00376_en.md b/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_panx_german_peterliuwt00376_en.md
new file mode 100644
index 00000000000000..3888938c7e8c84
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_panx_german_peterliuwt00376_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_peterliuwt00376 XlmRoBertaForTokenClassification from PeterLiuWT00376
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_peterliuwt00376
+date: 2025-01-27
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_peterliuwt00376` is a English model originally trained by PeterLiuWT00376.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_peterliuwt00376_en_5.5.1_3.0_1737969041758.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_peterliuwt00376_en_5.5.1_3.0_1737969041758.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_peterliuwt00376","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_peterliuwt00376", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_peterliuwt00376|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/PeterLiuWT00376/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_panx_german_peterliuwt00376_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_panx_german_peterliuwt00376_pipeline_en.md
new file mode 100644
index 00000000000000..d3f6db050fa3f9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_panx_german_peterliuwt00376_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_peterliuwt00376_pipeline pipeline XlmRoBertaForTokenClassification from PeterLiuWT00376
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_peterliuwt00376_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_peterliuwt00376_pipeline` is a English model originally trained by PeterLiuWT00376.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_peterliuwt00376_pipeline_en_5.5.1_3.0_1737969127098.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_peterliuwt00376_pipeline_en_5.5.1_3.0_1737969127098.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_peterliuwt00376_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_peterliuwt00376_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_peterliuwt00376_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/PeterLiuWT00376/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_peyma_persian_farsi_en.md b/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_peyma_persian_farsi_en.md
new file mode 100644
index 00000000000000..5d57efef46ff6b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_peyma_persian_farsi_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_peyma_persian_farsi XlmRoBertaForTokenClassification from rezzzzzaaaaaa
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_peyma_persian_farsi
+date: 2025-01-27
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_peyma_persian_farsi` is a English model originally trained by rezzzzzaaaaaa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_peyma_persian_farsi_en_5.5.1_3.0_1737969245364.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_peyma_persian_farsi_en_5.5.1_3.0_1737969245364.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_peyma_persian_farsi","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_peyma_persian_farsi", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_peyma_persian_farsi|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|827.1 MB|
+
+## References
+
+https://huggingface.co/rezzzzzaaaaaa/xlm-roberta-base-finetuned-peyma-fa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_peyma_persian_farsi_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_peyma_persian_farsi_pipeline_en.md
new file mode 100644
index 00000000000000..9141bc04eeb60f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_finetuned_peyma_persian_farsi_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_peyma_persian_farsi_pipeline pipeline XlmRoBertaForTokenClassification from rezzzzzaaaaaa
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_peyma_persian_farsi_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_peyma_persian_farsi_pipeline` is a English model originally trained by rezzzzzaaaaaa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_peyma_persian_farsi_pipeline_en_5.5.1_3.0_1737969331549.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_peyma_persian_farsi_pipeline_en_5.5.1_3.0_1737969331549.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_peyma_persian_farsi_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_peyma_persian_farsi_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_peyma_persian_farsi_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|827.1 MB|
+
+## References
+
+https://huggingface.co/rezzzzzaaaaaa/xlm-roberta-base-finetuned-peyma-fa
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_vsmec_10_en.md b/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_vsmec_10_en.md
new file mode 100644
index 00000000000000..56665c70ca6f8c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_vsmec_10_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_vsmec_10 XlmRoBertaForSequenceClassification from tmnam20
+author: John Snow Labs
+name: xlm_roberta_base_vsmec_10
+date: 2025-01-27
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_vsmec_10` is a English model originally trained by tmnam20.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_vsmec_10_en_5.5.1_3.0_1737959425776.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_vsmec_10_en_5.5.1_3.0_1737959425776.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_vsmec_10","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_vsmec_10", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_vsmec_10|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|774.5 MB|
+
+## References
+
+https://huggingface.co/tmnam20/xlm-roberta-base-vsmec-10
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_vsmec_10_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_vsmec_10_pipeline_en.md
new file mode 100644
index 00000000000000..65b355f7425091
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-xlm_roberta_base_vsmec_10_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_vsmec_10_pipeline pipeline XlmRoBertaForSequenceClassification from tmnam20
+author: John Snow Labs
+name: xlm_roberta_base_vsmec_10_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_vsmec_10_pipeline` is a English model originally trained by tmnam20.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_vsmec_10_pipeline_en_5.5.1_3.0_1737959566898.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_vsmec_10_pipeline_en_5.5.1_3.0_1737959566898.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_vsmec_10_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_vsmec_10_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_vsmec_10_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|774.5 MB|
+
+## References
+
+https://huggingface.co/tmnam20/xlm-roberta-base-vsmec-10
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-xlm_v_base_trimmed_french_en.md b/docs/_posts/ahmedlone127/2025-01-27-xlm_v_base_trimmed_french_en.md
new file mode 100644
index 00000000000000..b15a3035afbb58
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-xlm_v_base_trimmed_french_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_v_base_trimmed_french XlmRoBertaEmbeddings from vocabtrimmer
+author: John Snow Labs
+name: xlm_v_base_trimmed_french
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_v_base_trimmed_french` is a English model originally trained by vocabtrimmer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_v_base_trimmed_french_en_5.5.1_3.0_1737977145842.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_v_base_trimmed_french_en_5.5.1_3.0_1737977145842.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("xlm_v_base_trimmed_french","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("xlm_v_base_trimmed_french","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_v_base_trimmed_french|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|584.0 MB|
+
+## References
+
+https://huggingface.co/vocabtrimmer/xlm-v-base-trimmed-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-xlm_v_base_trimmed_french_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-xlm_v_base_trimmed_french_pipeline_en.md
new file mode 100644
index 00000000000000..283b6a380313c2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-xlm_v_base_trimmed_french_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_v_base_trimmed_french_pipeline pipeline XlmRoBertaEmbeddings from vocabtrimmer
+author: John Snow Labs
+name: xlm_v_base_trimmed_french_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_v_base_trimmed_french_pipeline` is a English model originally trained by vocabtrimmer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_v_base_trimmed_french_pipeline_en_5.5.1_3.0_1737977311818.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_v_base_trimmed_french_pipeline_en_5.5.1_3.0_1737977311818.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_v_base_trimmed_french_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_v_base_trimmed_french_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_v_base_trimmed_french_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|584.0 MB|
+
+## References
+
+https://huggingface.co/vocabtrimmer/xlm-v-base-trimmed-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-xlm_v_base_trimmed_spanish_en.md b/docs/_posts/ahmedlone127/2025-01-27-xlm_v_base_trimmed_spanish_en.md
new file mode 100644
index 00000000000000..5b391256e73ddf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-xlm_v_base_trimmed_spanish_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_v_base_trimmed_spanish XlmRoBertaEmbeddings from vocabtrimmer
+author: John Snow Labs
+name: xlm_v_base_trimmed_spanish
+date: 2025-01-27
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_v_base_trimmed_spanish` is a English model originally trained by vocabtrimmer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_v_base_trimmed_spanish_en_5.5.1_3.0_1737977167764.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_v_base_trimmed_spanish_en_5.5.1_3.0_1737977167764.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("xlm_v_base_trimmed_spanish","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("xlm_v_base_trimmed_spanish","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_v_base_trimmed_spanish|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|624.5 MB|
+
+## References
+
+https://huggingface.co/vocabtrimmer/xlm-v-base-trimmed-es
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-xlm_v_base_trimmed_spanish_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-xlm_v_base_trimmed_spanish_pipeline_en.md
new file mode 100644
index 00000000000000..aaa7c86b5bf8aa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-xlm_v_base_trimmed_spanish_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_v_base_trimmed_spanish_pipeline pipeline XlmRoBertaEmbeddings from vocabtrimmer
+author: John Snow Labs
+name: xlm_v_base_trimmed_spanish_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_v_base_trimmed_spanish_pipeline` is a English model originally trained by vocabtrimmer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_v_base_trimmed_spanish_pipeline_en_5.5.1_3.0_1737977344990.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_v_base_trimmed_spanish_pipeline_en_5.5.1_3.0_1737977344990.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_v_base_trimmed_spanish_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_v_base_trimmed_spanish_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_v_base_trimmed_spanish_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|624.5 MB|
+
+## References
+
+https://huggingface.co/vocabtrimmer/xlm-v-base-trimmed-es
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-yoga_pose_image_classification_en.md b/docs/_posts/ahmedlone127/2025-01-27-yoga_pose_image_classification_en.md
new file mode 100644
index 00000000000000..5342c91e961d68
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-yoga_pose_image_classification_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English yoga_pose_image_classification ViTForImageClassification from dima806
+author: John Snow Labs
+name: yoga_pose_image_classification
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`yoga_pose_image_classification` is a English model originally trained by dima806.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/yoga_pose_image_classification_en_5.5.1_3.0_1737974834827.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/yoga_pose_image_classification_en_5.5.1_3.0_1737974834827.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""yoga_pose_image_classification","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("yoga_pose_image_classification","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|yoga_pose_image_classification|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/dima806/yoga_pose_image_classification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-yoga_pose_image_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-yoga_pose_image_classification_pipeline_en.md
new file mode 100644
index 00000000000000..89d4a18c3c1235
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-yoga_pose_image_classification_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English yoga_pose_image_classification_pipeline pipeline ViTForImageClassification from dima806
+author: John Snow Labs
+name: yoga_pose_image_classification_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`yoga_pose_image_classification_pipeline` is a English model originally trained by dima806.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/yoga_pose_image_classification_pipeline_en_5.5.1_3.0_1737974853780.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/yoga_pose_image_classification_pipeline_en_5.5.1_3.0_1737974853780.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("yoga_pose_image_classification_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("yoga_pose_image_classification_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|yoga_pose_image_classification_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/dima806/yoga_pose_image_classification
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-yt_grader_model_en.md b/docs/_posts/ahmedlone127/2025-01-27-yt_grader_model_en.md
new file mode 100644
index 00000000000000..a2472fea6eb3ed
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-yt_grader_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English yt_grader_model ViTForImageClassification from vargr
+author: John Snow Labs
+name: yt_grader_model
+date: 2025-01-27
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`yt_grader_model` is a English model originally trained by vargr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/yt_grader_model_en_5.5.1_3.0_1737974538055.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/yt_grader_model_en_5.5.1_3.0_1737974538055.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""yt_grader_model","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("yt_grader_model","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|yt_grader_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/vargr/yt-grader-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-27-yt_grader_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-27-yt_grader_model_pipeline_en.md
new file mode 100644
index 00000000000000..07e27355d964a6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-27-yt_grader_model_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English yt_grader_model_pipeline pipeline ViTForImageClassification from vargr
+author: John Snow Labs
+name: yt_grader_model_pipeline
+date: 2025-01-27
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`yt_grader_model_pipeline` is a English model originally trained by vargr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/yt_grader_model_pipeline_en_5.5.1_3.0_1737974556860.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/yt_grader_model_pipeline_en_5.5.1_3.0_1737974556860.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("yt_grader_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("yt_grader_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|yt_grader_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/vargr/yt-grader-model
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-10dimensions_respect_en.md b/docs/_posts/ahmedlone127/2025-01-28-10dimensions_respect_en.md
new file mode 100644
index 00000000000000..ced9e2b41f257f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-10dimensions_respect_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English 10dimensions_respect BertForSequenceClassification from Blablablab
+author: John Snow Labs
+name: 10dimensions_respect
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`10dimensions_respect` is a English model originally trained by Blablablab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/10dimensions_respect_en_5.5.1_3.0_1738066708002.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/10dimensions_respect_en_5.5.1_3.0_1738066708002.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("10dimensions_respect","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("10dimensions_respect", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|10dimensions_respect|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|405.9 MB|
+
+## References
+
+https://huggingface.co/Blablablab/10dimensions-respect
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-10dimensions_respect_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-10dimensions_respect_pipeline_en.md
new file mode 100644
index 00000000000000..73924d4cfad1a4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-10dimensions_respect_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English 10dimensions_respect_pipeline pipeline BertForSequenceClassification from Blablablab
+author: John Snow Labs
+name: 10dimensions_respect_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`10dimensions_respect_pipeline` is a English model originally trained by Blablablab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/10dimensions_respect_pipeline_en_5.5.1_3.0_1738066728275.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/10dimensions_respect_pipeline_en_5.5.1_3.0_1738066728275.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("10dimensions_respect_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("10dimensions_respect_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|10dimensions_respect_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|405.9 MB|
+
+## References
+
+https://huggingface.co/Blablablab/10dimensions-respect
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-10dimensions_romance_en.md b/docs/_posts/ahmedlone127/2025-01-28-10dimensions_romance_en.md
new file mode 100644
index 00000000000000..1babb078984dfe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-10dimensions_romance_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English 10dimensions_romance BertForSequenceClassification from Blablablab
+author: John Snow Labs
+name: 10dimensions_romance
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`10dimensions_romance` is a English model originally trained by Blablablab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/10dimensions_romance_en_5.5.1_3.0_1738059691671.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/10dimensions_romance_en_5.5.1_3.0_1738059691671.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("10dimensions_romance","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("10dimensions_romance", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|10dimensions_romance|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|405.9 MB|
+
+## References
+
+https://huggingface.co/Blablablab/10dimensions-romance
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-10dimensions_romance_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-10dimensions_romance_pipeline_en.md
new file mode 100644
index 00000000000000..29a944288f847f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-10dimensions_romance_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English 10dimensions_romance_pipeline pipeline BertForSequenceClassification from Blablablab
+author: John Snow Labs
+name: 10dimensions_romance_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`10dimensions_romance_pipeline` is a English model originally trained by Blablablab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/10dimensions_romance_pipeline_en_5.5.1_3.0_1738059711827.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/10dimensions_romance_pipeline_en_5.5.1_3.0_1738059711827.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("10dimensions_romance_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("10dimensions_romance_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|10dimensions_romance_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|405.9 MB|
+
+## References
+
+https://huggingface.co/Blablablab/10dimensions-romance
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-10dimensions_social_support_en.md b/docs/_posts/ahmedlone127/2025-01-28-10dimensions_social_support_en.md
new file mode 100644
index 00000000000000..5752a3dcfa0dac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-10dimensions_social_support_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English 10dimensions_social_support BertForSequenceClassification from Blablablab
+author: John Snow Labs
+name: 10dimensions_social_support
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`10dimensions_social_support` is a English model originally trained by Blablablab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/10dimensions_social_support_en_5.5.1_3.0_1738066642899.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/10dimensions_social_support_en_5.5.1_3.0_1738066642899.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("10dimensions_social_support","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("10dimensions_social_support", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|10dimensions_social_support|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|405.9 MB|
+
+## References
+
+https://huggingface.co/Blablablab/10dimensions-social_support
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-10dimensions_social_support_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-10dimensions_social_support_pipeline_en.md
new file mode 100644
index 00000000000000..3dacdc65bc0d47
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-10dimensions_social_support_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English 10dimensions_social_support_pipeline pipeline BertForSequenceClassification from Blablablab
+author: John Snow Labs
+name: 10dimensions_social_support_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`10dimensions_social_support_pipeline` is a English model originally trained by Blablablab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/10dimensions_social_support_pipeline_en_5.5.1_3.0_1738066662962.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/10dimensions_social_support_pipeline_en_5.5.1_3.0_1738066662962.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("10dimensions_social_support_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("10dimensions_social_support_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|10dimensions_social_support_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|405.9 MB|
+
+## References
+
+https://huggingface.co/Blablablab/10dimensions-social_support
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-20230813140223_en.md b/docs/_posts/ahmedlone127/2025-01-28-20230813140223_en.md
new file mode 100644
index 00000000000000..86c1f1e613e959
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-20230813140223_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English 20230813140223 BertForQuestionAnswering from dkqjrm
+author: John Snow Labs
+name: 20230813140223
+date: 2025-01-28
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`20230813140223` is a English model originally trained by dkqjrm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/20230813140223_en_5.5.1_3.0_1738062848280.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/20230813140223_en_5.5.1_3.0_1738062848280.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("20230813140223","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("20230813140223", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|20230813140223|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/dkqjrm/20230813140223
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-20230813140223_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-20230813140223_pipeline_en.md
new file mode 100644
index 00000000000000..e207451608da1f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-20230813140223_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English 20230813140223_pipeline pipeline BertForQuestionAnswering from dkqjrm
+author: John Snow Labs
+name: 20230813140223_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`20230813140223_pipeline` is a English model originally trained by dkqjrm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/20230813140223_pipeline_en_5.5.1_3.0_1738062907619.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/20230813140223_pipeline_en_5.5.1_3.0_1738062907619.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("20230813140223_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("20230813140223_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|20230813140223_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/dkqjrm/20230813140223
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-20230821153710_en.md b/docs/_posts/ahmedlone127/2025-01-28-20230821153710_en.md
new file mode 100644
index 00000000000000..3c0537e820afd6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-20230821153710_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English 20230821153710 BertForQuestionAnswering from dkqjrm
+author: John Snow Labs
+name: 20230821153710
+date: 2025-01-28
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`20230821153710` is a English model originally trained by dkqjrm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/20230821153710_en_5.5.1_3.0_1738061631824.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/20230821153710_en_5.5.1_3.0_1738061631824.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("20230821153710","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("20230821153710", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|20230821153710|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/dkqjrm/20230821153710
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-20230821153710_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-20230821153710_pipeline_en.md
new file mode 100644
index 00000000000000..52ebb1a60c8bd4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-20230821153710_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English 20230821153710_pipeline pipeline BertForQuestionAnswering from dkqjrm
+author: John Snow Labs
+name: 20230821153710_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`20230821153710_pipeline` is a English model originally trained by dkqjrm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/20230821153710_pipeline_en_5.5.1_3.0_1738061693680.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/20230821153710_pipeline_en_5.5.1_3.0_1738061693680.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("20230821153710_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("20230821153710_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|20230821153710_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/dkqjrm/20230821153710
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-actionable_policy_bert_base_multilingual_uncased_f1_weighted_pipeline_xx.md b/docs/_posts/ahmedlone127/2025-01-28-actionable_policy_bert_base_multilingual_uncased_f1_weighted_pipeline_xx.md
new file mode 100644
index 00000000000000..9c01013f93a363
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-actionable_policy_bert_base_multilingual_uncased_f1_weighted_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual actionable_policy_bert_base_multilingual_uncased_f1_weighted_pipeline pipeline BertForSequenceClassification from faodl
+author: John Snow Labs
+name: actionable_policy_bert_base_multilingual_uncased_f1_weighted_pipeline
+date: 2025-01-28
+tags: [xx, open_source, pipeline, onnx]
+task: Text Classification
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`actionable_policy_bert_base_multilingual_uncased_f1_weighted_pipeline` is a Multilingual model originally trained by faodl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/actionable_policy_bert_base_multilingual_uncased_f1_weighted_pipeline_xx_5.5.1_3.0_1738027717509.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/actionable_policy_bert_base_multilingual_uncased_f1_weighted_pipeline_xx_5.5.1_3.0_1738027717509.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("actionable_policy_bert_base_multilingual_uncased_f1_weighted_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("actionable_policy_bert_base_multilingual_uncased_f1_weighted_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|actionable_policy_bert_base_multilingual_uncased_f1_weighted_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|627.8 MB|
+
+## References
+
+https://huggingface.co/faodl/actionable-policy-bert-base-multilingual-uncased-f1_weighted
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-actionable_policy_bert_base_multilingual_uncased_f1_weighted_xx.md b/docs/_posts/ahmedlone127/2025-01-28-actionable_policy_bert_base_multilingual_uncased_f1_weighted_xx.md
new file mode 100644
index 00000000000000..299d58f13d85dc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-actionable_policy_bert_base_multilingual_uncased_f1_weighted_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual actionable_policy_bert_base_multilingual_uncased_f1_weighted BertForSequenceClassification from faodl
+author: John Snow Labs
+name: actionable_policy_bert_base_multilingual_uncased_f1_weighted
+date: 2025-01-28
+tags: [xx, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`actionable_policy_bert_base_multilingual_uncased_f1_weighted` is a Multilingual model originally trained by faodl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/actionable_policy_bert_base_multilingual_uncased_f1_weighted_xx_5.5.1_3.0_1738027686240.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/actionable_policy_bert_base_multilingual_uncased_f1_weighted_xx_5.5.1_3.0_1738027686240.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("actionable_policy_bert_base_multilingual_uncased_f1_weighted","xx") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("actionable_policy_bert_base_multilingual_uncased_f1_weighted", "xx")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|actionable_policy_bert_base_multilingual_uncased_f1_weighted|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|xx|
+|Size:|627.7 MB|
+
+## References
+
+https://huggingface.co/faodl/actionable-policy-bert-base-multilingual-uncased-f1_weighted
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-activity_name_en.md b/docs/_posts/ahmedlone127/2025-01-28-activity_name_en.md
new file mode 100644
index 00000000000000..34096ae904d763
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-activity_name_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English activity_name T5Transformer from JaveriaShakoor
+author: John Snow Labs
+name: activity_name
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`activity_name` is a English model originally trained by JaveriaShakoor.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/activity_name_en_5.5.1_3.0_1738092439885.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/activity_name_en_5.5.1_3.0_1738092439885.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("activity_name","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("activity_name", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|activity_name|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|287.4 MB|
+
+## References
+
+https://huggingface.co/JaveriaShakoor/Activity_Name
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-activity_name_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-activity_name_pipeline_en.md
new file mode 100644
index 00000000000000..90be8b9539cf6a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-activity_name_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English activity_name_pipeline pipeline T5Transformer from JaveriaShakoor
+author: John Snow Labs
+name: activity_name_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`activity_name_pipeline` is a English model originally trained by JaveriaShakoor.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/activity_name_pipeline_en_5.5.1_3.0_1738092455597.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/activity_name_pipeline_en_5.5.1_3.0_1738092455597.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("activity_name_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("activity_name_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|activity_name_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|287.4 MB|
+
+## References
+
+https://huggingface.co/JaveriaShakoor/Activity_Name
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-adapter_13classes_single_label_en.md b/docs/_posts/ahmedlone127/2025-01-28-adapter_13classes_single_label_en.md
new file mode 100644
index 00000000000000..da21c177e96bee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-adapter_13classes_single_label_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English adapter_13classes_single_label T5Transformer from CrisisNarratives
+author: John Snow Labs
+name: adapter_13classes_single_label
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`adapter_13classes_single_label` is a English model originally trained by CrisisNarratives.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/adapter_13classes_single_label_en_5.5.1_3.0_1738033417729.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/adapter_13classes_single_label_en_5.5.1_3.0_1738033417729.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("adapter_13classes_single_label","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("adapter_13classes_single_label", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|adapter_13classes_single_label|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|474.1 MB|
+
+## References
+
+https://huggingface.co/CrisisNarratives/adapter-13classes-single_label
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-adapter_13classes_single_label_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-adapter_13classes_single_label_pipeline_en.md
new file mode 100644
index 00000000000000..e2510436774cdf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-adapter_13classes_single_label_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English adapter_13classes_single_label_pipeline pipeline T5Transformer from CrisisNarratives
+author: John Snow Labs
+name: adapter_13classes_single_label_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`adapter_13classes_single_label_pipeline` is a English model originally trained by CrisisNarratives.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/adapter_13classes_single_label_pipeline_en_5.5.1_3.0_1738033568607.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/adapter_13classes_single_label_pipeline_en_5.5.1_3.0_1738033568607.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("adapter_13classes_single_label_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("adapter_13classes_single_label_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|adapter_13classes_single_label_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|474.1 MB|
+
+## References
+
+https://huggingface.co/CrisisNarratives/adapter-13classes-single_label
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-adapter_8classes_multi_label_en.md b/docs/_posts/ahmedlone127/2025-01-28-adapter_8classes_multi_label_en.md
new file mode 100644
index 00000000000000..72d5318f4d5f4d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-adapter_8classes_multi_label_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English adapter_8classes_multi_label T5Transformer from CrisisNarratives
+author: John Snow Labs
+name: adapter_8classes_multi_label
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`adapter_8classes_multi_label` is a English model originally trained by CrisisNarratives.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/adapter_8classes_multi_label_en_5.5.1_3.0_1738072599652.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/adapter_8classes_multi_label_en_5.5.1_3.0_1738072599652.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("adapter_8classes_multi_label","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("adapter_8classes_multi_label", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|adapter_8classes_multi_label|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|474.1 MB|
+
+## References
+
+https://huggingface.co/CrisisNarratives/adapter-8classes-multi_label
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-adapter_8classes_multi_label_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-adapter_8classes_multi_label_pipeline_en.md
new file mode 100644
index 00000000000000..c32bf5d820e0f4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-adapter_8classes_multi_label_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English adapter_8classes_multi_label_pipeline pipeline T5Transformer from CrisisNarratives
+author: John Snow Labs
+name: adapter_8classes_multi_label_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`adapter_8classes_multi_label_pipeline` is a English model originally trained by CrisisNarratives.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/adapter_8classes_multi_label_pipeline_en_5.5.1_3.0_1738072753163.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/adapter_8classes_multi_label_pipeline_en_5.5.1_3.0_1738072753163.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("adapter_8classes_multi_label_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("adapter_8classes_multi_label_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|adapter_8classes_multi_label_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|474.1 MB|
+
+## References
+
+https://huggingface.co/CrisisNarratives/adapter-8classes-multi_label
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-adapter_8classes_single_label_en.md b/docs/_posts/ahmedlone127/2025-01-28-adapter_8classes_single_label_en.md
new file mode 100644
index 00000000000000..8277536fe6634b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-adapter_8classes_single_label_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English adapter_8classes_single_label T5Transformer from CrisisNarratives
+author: John Snow Labs
+name: adapter_8classes_single_label
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`adapter_8classes_single_label` is a English model originally trained by CrisisNarratives.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/adapter_8classes_single_label_en_5.5.1_3.0_1738071498161.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/adapter_8classes_single_label_en_5.5.1_3.0_1738071498161.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("adapter_8classes_single_label","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("adapter_8classes_single_label", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|adapter_8classes_single_label|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|474.1 MB|
+
+## References
+
+https://huggingface.co/CrisisNarratives/adapter-8classes-single_label
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-adapter_8classes_single_label_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-adapter_8classes_single_label_pipeline_en.md
new file mode 100644
index 00000000000000..8350770f7c0ea3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-adapter_8classes_single_label_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English adapter_8classes_single_label_pipeline pipeline T5Transformer from CrisisNarratives
+author: John Snow Labs
+name: adapter_8classes_single_label_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`adapter_8classes_single_label_pipeline` is a English model originally trained by CrisisNarratives.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/adapter_8classes_single_label_pipeline_en_5.5.1_3.0_1738071649273.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/adapter_8classes_single_label_pipeline_en_5.5.1_3.0_1738071649273.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("adapter_8classes_single_label_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("adapter_8classes_single_label_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|adapter_8classes_single_label_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|474.1 MB|
+
+## References
+
+https://huggingface.co/CrisisNarratives/adapter-8classes-single_label
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-aeona_en.md b/docs/_posts/ahmedlone127/2025-01-28-aeona_en.md
new file mode 100644
index 00000000000000..58622df874d8e5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-aeona_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English aeona GPT2Transformer from deepparag
+author: John Snow Labs
+name: aeona
+date: 2025-01-28
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`aeona` is a English model originally trained by deepparag.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/aeona_en_5.5.1_3.0_1738043542285.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/aeona_en_5.5.1_3.0_1738043542285.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("aeona","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("aeona","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|aeona|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/deepparag/Aeona
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-aeona_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-aeona_pipeline_en.md
new file mode 100644
index 00000000000000..50d55b137ac66f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-aeona_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English aeona_pipeline pipeline GPT2Transformer from deepparag
+author: John Snow Labs
+name: aeona_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`aeona_pipeline` is a English model originally trained by deepparag.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/aeona_pipeline_en_5.5.1_3.0_1738043608570.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/aeona_pipeline_en_5.5.1_3.0_1738043608570.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("aeona_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("aeona_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|aeona_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/deepparag/Aeona
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-ai_vs_real_finetuned_eurosat_en.md b/docs/_posts/ahmedlone127/2025-01-28-ai_vs_real_finetuned_eurosat_en.md
new file mode 100644
index 00000000000000..bf71da805cedba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-ai_vs_real_finetuned_eurosat_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ai_vs_real_finetuned_eurosat SwinForImageClassification from t1msan
+author: John Snow Labs
+name: ai_vs_real_finetuned_eurosat
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ai_vs_real_finetuned_eurosat` is a English model originally trained by t1msan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ai_vs_real_finetuned_eurosat_en_5.5.1_3.0_1738095489829.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ai_vs_real_finetuned_eurosat_en_5.5.1_3.0_1738095489829.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""ai_vs_real_finetuned_eurosat","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("ai_vs_real_finetuned_eurosat","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ai_vs_real_finetuned_eurosat|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/t1msan/ai_vs_real-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-ai_vs_real_finetuned_eurosat_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-ai_vs_real_finetuned_eurosat_pipeline_en.md
new file mode 100644
index 00000000000000..5b293e65d8402e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-ai_vs_real_finetuned_eurosat_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English ai_vs_real_finetuned_eurosat_pipeline pipeline SwinForImageClassification from t1msan
+author: John Snow Labs
+name: ai_vs_real_finetuned_eurosat_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ai_vs_real_finetuned_eurosat_pipeline` is a English model originally trained by t1msan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ai_vs_real_finetuned_eurosat_pipeline_en_5.5.1_3.0_1738095500569.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ai_vs_real_finetuned_eurosat_pipeline_en_5.5.1_3.0_1738095500569.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ai_vs_real_finetuned_eurosat_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ai_vs_real_finetuned_eurosat_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ai_vs_real_finetuned_eurosat_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/t1msan/ai_vs_real-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-albert_base_technical_debt_code_tesoro_en.md b/docs/_posts/ahmedlone127/2025-01-28-albert_base_technical_debt_code_tesoro_en.md
new file mode 100644
index 00000000000000..4195d5d128ec9e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-albert_base_technical_debt_code_tesoro_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English albert_base_technical_debt_code_tesoro AlbertForSequenceClassification from NamCyan
+author: John Snow Labs
+name: albert_base_technical_debt_code_tesoro
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, albert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_technical_debt_code_tesoro` is a English model originally trained by NamCyan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_technical_debt_code_tesoro_en_5.5.1_3.0_1738066417893.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_technical_debt_code_tesoro_en_5.5.1_3.0_1738066417893.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = AlbertForSequenceClassification.pretrained("albert_base_technical_debt_code_tesoro","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = AlbertForSequenceClassification.pretrained("albert_base_technical_debt_code_tesoro", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_base_technical_debt_code_tesoro|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/NamCyan/albert-base-technical-debt-code-tesoro
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-albert_base_technical_debt_code_tesoro_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-albert_base_technical_debt_code_tesoro_pipeline_en.md
new file mode 100644
index 00000000000000..24d79c18da5d16
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-albert_base_technical_debt_code_tesoro_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English albert_base_technical_debt_code_tesoro_pipeline pipeline AlbertForSequenceClassification from NamCyan
+author: John Snow Labs
+name: albert_base_technical_debt_code_tesoro_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_technical_debt_code_tesoro_pipeline` is a English model originally trained by NamCyan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_technical_debt_code_tesoro_pipeline_en_5.5.1_3.0_1738066420225.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_technical_debt_code_tesoro_pipeline_en_5.5.1_3.0_1738066420225.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("albert_base_technical_debt_code_tesoro_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("albert_base_technical_debt_code_tesoro_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_base_technical_debt_code_tesoro_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/NamCyan/albert-base-technical-debt-code-tesoro
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-all_minilm_l6_v2_personal_project_finetuned_2024_06_03_en.md b/docs/_posts/ahmedlone127/2025-01-28-all_minilm_l6_v2_personal_project_finetuned_2024_06_03_en.md
new file mode 100644
index 00000000000000..4e6af6e231b2b5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-all_minilm_l6_v2_personal_project_finetuned_2024_06_03_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English all_minilm_l6_v2_personal_project_finetuned_2024_06_03 BertEmbeddings from brugmark
+author: John Snow Labs
+name: all_minilm_l6_v2_personal_project_finetuned_2024_06_03
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_minilm_l6_v2_personal_project_finetuned_2024_06_03` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_finetuned_2024_06_03_en_5.5.1_3.0_1738057240695.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_finetuned_2024_06_03_en_5.5.1_3.0_1738057240695.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("all_minilm_l6_v2_personal_project_finetuned_2024_06_03","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("all_minilm_l6_v2_personal_project_finetuned_2024_06_03","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_minilm_l6_v2_personal_project_finetuned_2024_06_03|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|79.6 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-finetuned-2024-06-03
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-all_minilm_l6_v2_personal_project_finetuned_2024_06_03_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-all_minilm_l6_v2_personal_project_finetuned_2024_06_03_pipeline_en.md
new file mode 100644
index 00000000000000..aa0d1e125a44bf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-all_minilm_l6_v2_personal_project_finetuned_2024_06_03_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English all_minilm_l6_v2_personal_project_finetuned_2024_06_03_pipeline pipeline BertEmbeddings from brugmark
+author: John Snow Labs
+name: all_minilm_l6_v2_personal_project_finetuned_2024_06_03_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_minilm_l6_v2_personal_project_finetuned_2024_06_03_pipeline` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_finetuned_2024_06_03_pipeline_en_5.5.1_3.0_1738057246124.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_minilm_l6_v2_personal_project_finetuned_2024_06_03_pipeline_en_5.5.1_3.0_1738057246124.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("all_minilm_l6_v2_personal_project_finetuned_2024_06_03_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("all_minilm_l6_v2_personal_project_finetuned_2024_06_03_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_minilm_l6_v2_personal_project_finetuned_2024_06_03_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|79.6 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-finetuned-2024-06-03
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-anomaly_model2_en.md b/docs/_posts/ahmedlone127/2025-01-28-anomaly_model2_en.md
new file mode 100644
index 00000000000000..8031335490ee1b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-anomaly_model2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English anomaly_model2 DistilBertForSequenceClassification from AmirrezaV1
+author: John Snow Labs
+name: anomaly_model2
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`anomaly_model2` is a English model originally trained by AmirrezaV1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/anomaly_model2_en_5.5.1_3.0_1738025859978.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/anomaly_model2_en_5.5.1_3.0_1738025859978.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("anomaly_model2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("anomaly_model2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|anomaly_model2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|507.6 MB|
+
+## References
+
+https://huggingface.co/AmirrezaV1/anomaly-model2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-anomaly_model2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-anomaly_model2_pipeline_en.md
new file mode 100644
index 00000000000000..4bfb95499b5116
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-anomaly_model2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English anomaly_model2_pipeline pipeline DistilBertForSequenceClassification from AmirrezaV1
+author: John Snow Labs
+name: anomaly_model2_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`anomaly_model2_pipeline` is a English model originally trained by AmirrezaV1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/anomaly_model2_pipeline_en_5.5.1_3.0_1738025885421.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/anomaly_model2_pipeline_en_5.5.1_3.0_1738025885421.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("anomaly_model2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("anomaly_model2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|anomaly_model2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|507.6 MB|
+
+## References
+
+https://huggingface.co/AmirrezaV1/anomaly-model2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-apa_recognizer_en.md b/docs/_posts/ahmedlone127/2025-01-28-apa_recognizer_en.md
new file mode 100644
index 00000000000000..f3194be2f22729
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-apa_recognizer_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English apa_recognizer DistilBertForSequenceClassification from LaLaf93
+author: John Snow Labs
+name: apa_recognizer
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`apa_recognizer` is a English model originally trained by LaLaf93.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/apa_recognizer_en_5.5.1_3.0_1738026110250.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/apa_recognizer_en_5.5.1_3.0_1738026110250.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("apa_recognizer","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("apa_recognizer", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|apa_recognizer|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/LaLaf93/APA_recognizer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-apa_recognizer_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-apa_recognizer_pipeline_en.md
new file mode 100644
index 00000000000000..eb511bb01ac41b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-apa_recognizer_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English apa_recognizer_pipeline pipeline DistilBertForSequenceClassification from LaLaf93
+author: John Snow Labs
+name: apa_recognizer_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`apa_recognizer_pipeline` is a English model originally trained by LaLaf93.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/apa_recognizer_pipeline_en_5.5.1_3.0_1738026122958.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/apa_recognizer_pipeline_en_5.5.1_3.0_1738026122958.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("apa_recognizer_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("apa_recognizer_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|apa_recognizer_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/LaLaf93/APA_recognizer
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-arabertv02_numerical_en.md b/docs/_posts/ahmedlone127/2025-01-28-arabertv02_numerical_en.md
new file mode 100644
index 00000000000000..8475a924ccc05f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-arabertv02_numerical_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English arabertv02_numerical BertForSequenceClassification from MaiiiAdel
+author: John Snow Labs
+name: arabertv02_numerical
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`arabertv02_numerical` is a English model originally trained by MaiiiAdel.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/arabertv02_numerical_en_5.5.1_3.0_1738027746819.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/arabertv02_numerical_en_5.5.1_3.0_1738027746819.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("arabertv02_numerical","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("arabertv02_numerical", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|arabertv02_numerical|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|507.3 MB|
+
+## References
+
+https://huggingface.co/MaiiiAdel/arabertv02_numerical
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-arabertv02_numerical_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-arabertv02_numerical_pipeline_en.md
new file mode 100644
index 00000000000000..2f76c0b9ed999c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-arabertv02_numerical_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English arabertv02_numerical_pipeline pipeline BertForSequenceClassification from MaiiiAdel
+author: John Snow Labs
+name: arabertv02_numerical_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`arabertv02_numerical_pipeline` is a English model originally trained by MaiiiAdel.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/arabertv02_numerical_pipeline_en_5.5.1_3.0_1738027772103.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/arabertv02_numerical_pipeline_en_5.5.1_3.0_1738027772103.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("arabertv02_numerical_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("arabertv02_numerical_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|arabertv02_numerical_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|507.3 MB|
+
+## References
+
+https://huggingface.co/MaiiiAdel/arabertv02_numerical
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-arbertv2_entitylinking_pre_training_en.md b/docs/_posts/ahmedlone127/2025-01-28-arbertv2_entitylinking_pre_training_en.md
new file mode 100644
index 00000000000000..3c5550ba292aca
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-arbertv2_entitylinking_pre_training_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English arbertv2_entitylinking_pre_training BertForTokenClassification from AfnanTS
+author: John Snow Labs
+name: arbertv2_entitylinking_pre_training
+date: 2025-01-28
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`arbertv2_entitylinking_pre_training` is a English model originally trained by AfnanTS.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/arbertv2_entitylinking_pre_training_en_5.5.1_3.0_1738045035814.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/arbertv2_entitylinking_pre_training_en_5.5.1_3.0_1738045035814.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("arbertv2_entitylinking_pre_training","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("arbertv2_entitylinking_pre_training", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|arbertv2_entitylinking_pre_training|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|607.1 MB|
+
+## References
+
+https://huggingface.co/AfnanTS/ARBERTv2_EntityLinking_pre-training
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-arbertv2_entitylinking_pre_training_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-arbertv2_entitylinking_pre_training_pipeline_en.md
new file mode 100644
index 00000000000000..c7353a3097fb23
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-arbertv2_entitylinking_pre_training_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English arbertv2_entitylinking_pre_training_pipeline pipeline BertForTokenClassification from AfnanTS
+author: John Snow Labs
+name: arbertv2_entitylinking_pre_training_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`arbertv2_entitylinking_pre_training_pipeline` is a English model originally trained by AfnanTS.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/arbertv2_entitylinking_pre_training_pipeline_en_5.5.1_3.0_1738045065898.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/arbertv2_entitylinking_pre_training_pipeline_en_5.5.1_3.0_1738045065898.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("arbertv2_entitylinking_pre_training_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("arbertv2_entitylinking_pre_training_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|arbertv2_entitylinking_pre_training_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|607.2 MB|
+
+## References
+
+https://huggingface.co/AfnanTS/ARBERTv2_EntityLinking_pre-training
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-ardiabertv2_scaleup_en.md b/docs/_posts/ahmedlone127/2025-01-28-ardiabertv2_scaleup_en.md
new file mode 100644
index 00000000000000..f2b9d3a768661f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-ardiabertv2_scaleup_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ardiabertv2_scaleup BertEmbeddings from HossamElsafty
+author: John Snow Labs
+name: ardiabertv2_scaleup
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ardiabertv2_scaleup` is a English model originally trained by HossamElsafty.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ardiabertv2_scaleup_en_5.5.1_3.0_1738084951257.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ardiabertv2_scaleup_en_5.5.1_3.0_1738084951257.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("ardiabertv2_scaleup","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("ardiabertv2_scaleup","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ardiabertv2_scaleup|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|605.2 MB|
+
+## References
+
+https://huggingface.co/HossamElsafty/ArDiaBERTv2_scaleup
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-ardiabertv2_scaleup_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-ardiabertv2_scaleup_pipeline_en.md
new file mode 100644
index 00000000000000..0ecda4114f3d44
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-ardiabertv2_scaleup_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ardiabertv2_scaleup_pipeline pipeline BertEmbeddings from HossamElsafty
+author: John Snow Labs
+name: ardiabertv2_scaleup_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ardiabertv2_scaleup_pipeline` is a English model originally trained by HossamElsafty.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ardiabertv2_scaleup_pipeline_en_5.5.1_3.0_1738084984833.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ardiabertv2_scaleup_pipeline_en_5.5.1_3.0_1738084984833.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ardiabertv2_scaleup_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ardiabertv2_scaleup_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ardiabertv2_scaleup_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|605.3 MB|
+
+## References
+
+https://huggingface.co/HossamElsafty/ArDiaBERTv2_scaleup
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-autotrain_2n9b3_mj6my_en.md b/docs/_posts/ahmedlone127/2025-01-28-autotrain_2n9b3_mj6my_en.md
new file mode 100644
index 00000000000000..8a75ec87051703
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-autotrain_2n9b3_mj6my_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English autotrain_2n9b3_mj6my GPT2Transformer from Yhhxhfh
+author: John Snow Labs
+name: autotrain_2n9b3_mj6my
+date: 2025-01-28
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_2n9b3_mj6my` is a English model originally trained by Yhhxhfh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_2n9b3_mj6my_en_5.5.1_3.0_1738042485364.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_2n9b3_mj6my_en_5.5.1_3.0_1738042485364.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("autotrain_2n9b3_mj6my","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("autotrain_2n9b3_mj6my","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_2n9b3_mj6my|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/Yhhxhfh/autotrain-2n9b3-mj6my
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-autotrain_2n9b3_mj6my_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-autotrain_2n9b3_mj6my_pipeline_en.md
new file mode 100644
index 00000000000000..13792715bfb42b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-autotrain_2n9b3_mj6my_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English autotrain_2n9b3_mj6my_pipeline pipeline GPT2Transformer from Yhhxhfh
+author: John Snow Labs
+name: autotrain_2n9b3_mj6my_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_2n9b3_mj6my_pipeline` is a English model originally trained by Yhhxhfh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_2n9b3_mj6my_pipeline_en_5.5.1_3.0_1738042508150.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_2n9b3_mj6my_pipeline_en_5.5.1_3.0_1738042508150.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("autotrain_2n9b3_mj6my_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("autotrain_2n9b3_mj6my_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_2n9b3_mj6my_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/Yhhxhfh/autotrain-2n9b3-mj6my
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-autotrain_8v13_xs57_x55z_61491134800_en.md b/docs/_posts/ahmedlone127/2025-01-28-autotrain_8v13_xs57_x55z_61491134800_en.md
new file mode 100644
index 00000000000000..293eda6dc0c93e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-autotrain_8v13_xs57_x55z_61491134800_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English autotrain_8v13_xs57_x55z_61491134800 SwinForImageClassification from SriPrasanna
+author: John Snow Labs
+name: autotrain_8v13_xs57_x55z_61491134800
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_8v13_xs57_x55z_61491134800` is a English model originally trained by SriPrasanna.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_8v13_xs57_x55z_61491134800_en_5.5.1_3.0_1738095464216.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_8v13_xs57_x55z_61491134800_en_5.5.1_3.0_1738095464216.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""autotrain_8v13_xs57_x55z_61491134800","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("autotrain_8v13_xs57_x55z_61491134800","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_8v13_xs57_x55z_61491134800|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/SriPrasanna/autotrain-8v13-xs57-x55z-61491134800
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-autotrain_8v13_xs57_x55z_61491134800_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-autotrain_8v13_xs57_x55z_61491134800_pipeline_en.md
new file mode 100644
index 00000000000000..df487bb7e4c5e4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-autotrain_8v13_xs57_x55z_61491134800_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English autotrain_8v13_xs57_x55z_61491134800_pipeline pipeline SwinForImageClassification from SriPrasanna
+author: John Snow Labs
+name: autotrain_8v13_xs57_x55z_61491134800_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_8v13_xs57_x55z_61491134800_pipeline` is a English model originally trained by SriPrasanna.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_8v13_xs57_x55z_61491134800_pipeline_en_5.5.1_3.0_1738095474797.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_8v13_xs57_x55z_61491134800_pipeline_en_5.5.1_3.0_1738095474797.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("autotrain_8v13_xs57_x55z_61491134800_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("autotrain_8v13_xs57_x55z_61491134800_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_8v13_xs57_x55z_61491134800_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/SriPrasanna/autotrain-8v13-xs57-x55z-61491134800
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-autotrain_cat_dog_demo_ex_81819141862_en.md b/docs/_posts/ahmedlone127/2025-01-28-autotrain_cat_dog_demo_ex_81819141862_en.md
new file mode 100644
index 00000000000000..e21ef9b1c3e1be
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-autotrain_cat_dog_demo_ex_81819141862_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English autotrain_cat_dog_demo_ex_81819141862 SwinForImageClassification from hdduytran
+author: John Snow Labs
+name: autotrain_cat_dog_demo_ex_81819141862
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_cat_dog_demo_ex_81819141862` is a English model originally trained by hdduytran.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_cat_dog_demo_ex_81819141862_en_5.5.1_3.0_1738095668320.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_cat_dog_demo_ex_81819141862_en_5.5.1_3.0_1738095668320.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""autotrain_cat_dog_demo_ex_81819141862","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("autotrain_cat_dog_demo_ex_81819141862","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_cat_dog_demo_ex_81819141862|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/hdduytran/autotrain-cat-dog-demo-ex-81819141862
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-autotrain_cat_dog_demo_ex_81819141862_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-autotrain_cat_dog_demo_ex_81819141862_pipeline_en.md
new file mode 100644
index 00000000000000..76a9d4c9d821ee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-autotrain_cat_dog_demo_ex_81819141862_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English autotrain_cat_dog_demo_ex_81819141862_pipeline pipeline SwinForImageClassification from hdduytran
+author: John Snow Labs
+name: autotrain_cat_dog_demo_ex_81819141862_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_cat_dog_demo_ex_81819141862_pipeline` is a English model originally trained by hdduytran.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_cat_dog_demo_ex_81819141862_pipeline_en_5.5.1_3.0_1738095678937.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_cat_dog_demo_ex_81819141862_pipeline_en_5.5.1_3.0_1738095678937.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("autotrain_cat_dog_demo_ex_81819141862_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("autotrain_cat_dog_demo_ex_81819141862_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_cat_dog_demo_ex_81819141862_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/hdduytran/autotrain-cat-dog-demo-ex-81819141862
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-babylm_roberta_base_epoch_1_en.md b/docs/_posts/ahmedlone127/2025-01-28-babylm_roberta_base_epoch_1_en.md
new file mode 100644
index 00000000000000..49eff14d1e7961
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-babylm_roberta_base_epoch_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English babylm_roberta_base_epoch_1 RoBertaEmbeddings from Raj-Sanjay-Shah
+author: John Snow Labs
+name: babylm_roberta_base_epoch_1
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`babylm_roberta_base_epoch_1` is a English model originally trained by Raj-Sanjay-Shah.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/babylm_roberta_base_epoch_1_en_5.5.1_3.0_1738102800940.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/babylm_roberta_base_epoch_1_en_5.5.1_3.0_1738102800940.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("babylm_roberta_base_epoch_1","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("babylm_roberta_base_epoch_1","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|babylm_roberta_base_epoch_1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|465.4 MB|
+
+## References
+
+https://huggingface.co/Raj-Sanjay-Shah/babyLM_roberta_base_epoch_1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-babylm_roberta_base_epoch_1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-babylm_roberta_base_epoch_1_pipeline_en.md
new file mode 100644
index 00000000000000..0f5be35795b2fd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-babylm_roberta_base_epoch_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English babylm_roberta_base_epoch_1_pipeline pipeline RoBertaEmbeddings from Raj-Sanjay-Shah
+author: John Snow Labs
+name: babylm_roberta_base_epoch_1_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`babylm_roberta_base_epoch_1_pipeline` is a English model originally trained by Raj-Sanjay-Shah.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/babylm_roberta_base_epoch_1_pipeline_en_5.5.1_3.0_1738102824764.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/babylm_roberta_base_epoch_1_pipeline_en_5.5.1_3.0_1738102824764.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("babylm_roberta_base_epoch_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("babylm_roberta_base_epoch_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|babylm_roberta_base_epoch_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|465.4 MB|
+
+## References
+
+https://huggingface.co/Raj-Sanjay-Shah/babyLM_roberta_base_epoch_1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-banglat5_small_4_en.md b/docs/_posts/ahmedlone127/2025-01-28-banglat5_small_4_en.md
new file mode 100644
index 00000000000000..ecb10f7afaed90
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-banglat5_small_4_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English banglat5_small_4 T5Transformer from Ayon128
+author: John Snow Labs
+name: banglat5_small_4
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`banglat5_small_4` is a English model originally trained by Ayon128.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/banglat5_small_4_en_5.5.1_3.0_1738093079941.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/banglat5_small_4_en_5.5.1_3.0_1738093079941.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("banglat5_small_4","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("banglat5_small_4", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|banglat5_small_4|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|288.3 MB|
+
+## References
+
+https://huggingface.co/Ayon128/banglat5-small-4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-banglat5_small_4_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-banglat5_small_4_pipeline_en.md
new file mode 100644
index 00000000000000..e44f808cfcebc0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-banglat5_small_4_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English banglat5_small_4_pipeline pipeline T5Transformer from Ayon128
+author: John Snow Labs
+name: banglat5_small_4_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`banglat5_small_4_pipeline` is a English model originally trained by Ayon128.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/banglat5_small_4_pipeline_en_5.5.1_3.0_1738093094814.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/banglat5_small_4_pipeline_en_5.5.1_3.0_1738093094814.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("banglat5_small_4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("banglat5_small_4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|banglat5_small_4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|288.3 MB|
+
+## References
+
+https://huggingface.co/Ayon128/banglat5-small-4
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bart_base_detox_en.md b/docs/_posts/ahmedlone127/2025-01-28-bart_base_detox_en.md
new file mode 100644
index 00000000000000..632eeb4f950500
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bart_base_detox_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bart_base_detox BartTransformer from s-nlp
+author: John Snow Labs
+name: bart_base_detox
+date: 2025-01-28
+tags: [en, open_source, onnx, text_generation, bart]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BartTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bart_base_detox` is a English model originally trained by s-nlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bart_base_detox_en_5.5.1_3.0_1738086554995.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bart_base_detox_en_5.5.1_3.0_1738086554995.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = BartTransformer.pretrained("bart_base_detox","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = BartTransformer.pretrained("bart_base_detox","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bart_base_detox|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|809.4 MB|
+
+## References
+
+https://huggingface.co/s-nlp/bart-base-detox
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bart_base_detox_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bart_base_detox_pipeline_en.md
new file mode 100644
index 00000000000000..16c67e05fb62dc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bart_base_detox_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bart_base_detox_pipeline pipeline BartTransformer from s-nlp
+author: John Snow Labs
+name: bart_base_detox_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bart_base_detox_pipeline` is a English model originally trained by s-nlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bart_base_detox_pipeline_en_5.5.1_3.0_1738086595927.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bart_base_detox_pipeline_en_5.5.1_3.0_1738086595927.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bart_base_detox_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bart_base_detox_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bart_base_detox_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|809.4 MB|
+
+## References
+
+https://huggingface.co/s-nlp/bart-base-detox
+
+## Included Models
+
+- DocumentAssembler
+- BartTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bart_base_toxic_antiexpert_en.md b/docs/_posts/ahmedlone127/2025-01-28-bart_base_toxic_antiexpert_en.md
new file mode 100644
index 00000000000000..6bb0e93f3b21da
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bart_base_toxic_antiexpert_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bart_base_toxic_antiexpert BartTransformer from hallisky
+author: John Snow Labs
+name: bart_base_toxic_antiexpert
+date: 2025-01-28
+tags: [en, open_source, onnx, text_generation, bart]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BartTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bart_base_toxic_antiexpert` is a English model originally trained by hallisky.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bart_base_toxic_antiexpert_en_5.5.1_3.0_1738087674340.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bart_base_toxic_antiexpert_en_5.5.1_3.0_1738087674340.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = BartTransformer.pretrained("bart_base_toxic_antiexpert","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = BartTransformer.pretrained("bart_base_toxic_antiexpert","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bart_base_toxic_antiexpert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|809.6 MB|
+
+## References
+
+https://huggingface.co/hallisky/bart-base-toxic-antiexpert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bart_base_toxic_antiexpert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bart_base_toxic_antiexpert_pipeline_en.md
new file mode 100644
index 00000000000000..a87c15080b281d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bart_base_toxic_antiexpert_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bart_base_toxic_antiexpert_pipeline pipeline BartTransformer from hallisky
+author: John Snow Labs
+name: bart_base_toxic_antiexpert_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bart_base_toxic_antiexpert_pipeline` is a English model originally trained by hallisky.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bart_base_toxic_antiexpert_pipeline_en_5.5.1_3.0_1738087715375.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bart_base_toxic_antiexpert_pipeline_en_5.5.1_3.0_1738087715375.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bart_base_toxic_antiexpert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bart_base_toxic_antiexpert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bart_base_toxic_antiexpert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|809.6 MB|
+
+## References
+
+https://huggingface.co/hallisky/bart-base-toxic-antiexpert
+
+## Included Models
+
+- DocumentAssembler
+- BartTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bart_samsum_derekepp_en.md b/docs/_posts/ahmedlone127/2025-01-28-bart_samsum_derekepp_en.md
new file mode 100644
index 00000000000000..9340a3108bed5b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bart_samsum_derekepp_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bart_samsum_derekepp BartTransformer from derekepp
+author: John Snow Labs
+name: bart_samsum_derekepp
+date: 2025-01-28
+tags: [en, open_source, onnx, text_generation, bart]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BartTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bart_samsum_derekepp` is a English model originally trained by derekepp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bart_samsum_derekepp_en_5.5.1_3.0_1738087330046.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bart_samsum_derekepp_en_5.5.1_3.0_1738087330046.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = BartTransformer.pretrained("bart_samsum_derekepp","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = BartTransformer.pretrained("bart_samsum_derekepp","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bart_samsum_derekepp|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.9 GB|
+
+## References
+
+https://huggingface.co/derekepp/bart-samsum
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bart_samsum_derekepp_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bart_samsum_derekepp_pipeline_en.md
new file mode 100644
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@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bart_samsum_derekepp_pipeline pipeline BartTransformer from derekepp
+author: John Snow Labs
+name: bart_samsum_derekepp_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bart_samsum_derekepp_pipeline` is a English model originally trained by derekepp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bart_samsum_derekepp_pipeline_en_5.5.1_3.0_1738087418139.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bart_samsum_derekepp_pipeline_en_5.5.1_3.0_1738087418139.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bart_samsum_derekepp_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bart_samsum_derekepp_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bart_samsum_derekepp_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.9 GB|
+
+## References
+
+https://huggingface.co/derekepp/bart-samsum
+
+## Included Models
+
+- DocumentAssembler
+- BartTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-batch_size16_ffpp_c23_opencv_1fps_unaugmentation_en.md b/docs/_posts/ahmedlone127/2025-01-28-batch_size16_ffpp_c23_opencv_1fps_unaugmentation_en.md
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+++ b/docs/_posts/ahmedlone127/2025-01-28-batch_size16_ffpp_c23_opencv_1fps_unaugmentation_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English batch_size16_ffpp_c23_opencv_1fps_unaugmentation SwinForImageClassification from hchcsuim
+author: John Snow Labs
+name: batch_size16_ffpp_c23_opencv_1fps_unaugmentation
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`batch_size16_ffpp_c23_opencv_1fps_unaugmentation` is a English model originally trained by hchcsuim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/batch_size16_ffpp_c23_opencv_1fps_unaugmentation_en_5.5.1_3.0_1738095037750.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/batch_size16_ffpp_c23_opencv_1fps_unaugmentation_en_5.5.1_3.0_1738095037750.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""batch_size16_ffpp_c23_opencv_1fps_unaugmentation","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("batch_size16_ffpp_c23_opencv_1fps_unaugmentation","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|batch_size16_ffpp_c23_opencv_1fps_unaugmentation|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/hchcsuim/batch-size16_FFPP-c23_opencv-1FPS_unaugmentation
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-batch_size16_ffpp_c23_opencv_1fps_unaugmentation_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-batch_size16_ffpp_c23_opencv_1fps_unaugmentation_pipeline_en.md
new file mode 100644
index 00000000000000..b78f685f414c0f
--- /dev/null
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@@ -0,0 +1,69 @@
+---
+layout: model
+title: English batch_size16_ffpp_c23_opencv_1fps_unaugmentation_pipeline pipeline SwinForImageClassification from hchcsuim
+author: John Snow Labs
+name: batch_size16_ffpp_c23_opencv_1fps_unaugmentation_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`batch_size16_ffpp_c23_opencv_1fps_unaugmentation_pipeline` is a English model originally trained by hchcsuim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/batch_size16_ffpp_c23_opencv_1fps_unaugmentation_pipeline_en_5.5.1_3.0_1738095054963.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/batch_size16_ffpp_c23_opencv_1fps_unaugmentation_pipeline_en_5.5.1_3.0_1738095054963.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("batch_size16_ffpp_c23_opencv_1fps_unaugmentation_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("batch_size16_ffpp_c23_opencv_1fps_unaugmentation_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|batch_size16_ffpp_c23_opencv_1fps_unaugmentation_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/hchcsuim/batch-size16_FFPP-c23_opencv-1FPS_unaugmentation
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-batch_size_16_ffpp_raw_1fps_faces_expand_0_aligned_0real_1fake_en.md b/docs/_posts/ahmedlone127/2025-01-28-batch_size_16_ffpp_raw_1fps_faces_expand_0_aligned_0real_1fake_en.md
new file mode 100644
index 00000000000000..722130f51a4f6b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-batch_size_16_ffpp_raw_1fps_faces_expand_0_aligned_0real_1fake_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English batch_size_16_ffpp_raw_1fps_faces_expand_0_aligned_0real_1fake SwinForImageClassification from hchcsuim
+author: John Snow Labs
+name: batch_size_16_ffpp_raw_1fps_faces_expand_0_aligned_0real_1fake
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`batch_size_16_ffpp_raw_1fps_faces_expand_0_aligned_0real_1fake` is a English model originally trained by hchcsuim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/batch_size_16_ffpp_raw_1fps_faces_expand_0_aligned_0real_1fake_en_5.5.1_3.0_1738095805237.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/batch_size_16_ffpp_raw_1fps_faces_expand_0_aligned_0real_1fake_en_5.5.1_3.0_1738095805237.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""batch_size_16_ffpp_raw_1fps_faces_expand_0_aligned_0real_1fake","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("batch_size_16_ffpp_raw_1fps_faces_expand_0_aligned_0real_1fake","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|batch_size_16_ffpp_raw_1fps_faces_expand_0_aligned_0real_1fake|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/hchcsuim/batch-size-16_FFPP-Raw_1FPS_faces-expand-0-aligned_0Real-1Fake
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-batch_size_16_ffpp_raw_1fps_faces_expand_0_aligned_0real_1fake_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-batch_size_16_ffpp_raw_1fps_faces_expand_0_aligned_0real_1fake_pipeline_en.md
new file mode 100644
index 00000000000000..489af0b6797465
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-batch_size_16_ffpp_raw_1fps_faces_expand_0_aligned_0real_1fake_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English batch_size_16_ffpp_raw_1fps_faces_expand_0_aligned_0real_1fake_pipeline pipeline SwinForImageClassification from hchcsuim
+author: John Snow Labs
+name: batch_size_16_ffpp_raw_1fps_faces_expand_0_aligned_0real_1fake_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`batch_size_16_ffpp_raw_1fps_faces_expand_0_aligned_0real_1fake_pipeline` is a English model originally trained by hchcsuim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/batch_size_16_ffpp_raw_1fps_faces_expand_0_aligned_0real_1fake_pipeline_en_5.5.1_3.0_1738095815843.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/batch_size_16_ffpp_raw_1fps_faces_expand_0_aligned_0real_1fake_pipeline_en_5.5.1_3.0_1738095815843.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("batch_size_16_ffpp_raw_1fps_faces_expand_0_aligned_0real_1fake_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("batch_size_16_ffpp_raw_1fps_faces_expand_0_aligned_0real_1fake_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|batch_size_16_ffpp_raw_1fps_faces_expand_0_aligned_0real_1fake_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/hchcsuim/batch-size-16_FFPP-Raw_1FPS_faces-expand-0-aligned_0Real-1Fake
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-beer_classifier_en.md b/docs/_posts/ahmedlone127/2025-01-28-beer_classifier_en.md
new file mode 100644
index 00000000000000..dc006627d0dcb6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-beer_classifier_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English beer_classifier ViTForImageClassification from LiamOldhamMsc
+author: John Snow Labs
+name: beer_classifier
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`beer_classifier` is a English model originally trained by LiamOldhamMsc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/beer_classifier_en_5.5.1_3.0_1738022432940.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/beer_classifier_en_5.5.1_3.0_1738022432940.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""beer_classifier","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("beer_classifier","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|beer_classifier|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/LiamOldhamMsc/beer-classifier
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-beer_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-beer_classifier_pipeline_en.md
new file mode 100644
index 00000000000000..5476c9d88b0a35
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-beer_classifier_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English beer_classifier_pipeline pipeline ViTForImageClassification from LiamOldhamMsc
+author: John Snow Labs
+name: beer_classifier_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`beer_classifier_pipeline` is a English model originally trained by LiamOldhamMsc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/beer_classifier_pipeline_en_5.5.1_3.0_1738022449996.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/beer_classifier_pipeline_en_5.5.1_3.0_1738022449996.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("beer_classifier_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("beer_classifier_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|beer_classifier_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/LiamOldhamMsc/beer-classifier
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_adaptation_martin_fierro_martinnnuez_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_adaptation_martin_fierro_martinnnuez_en.md
new file mode 100644
index 00000000000000..e4a45b752e128a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_adaptation_martin_fierro_martinnnuez_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_adaptation_martin_fierro_martinnnuez BertEmbeddings from martinnnuez
+author: John Snow Labs
+name: bert_adaptation_martin_fierro_martinnnuez
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_martin_fierro_martinnnuez` is a English model originally trained by martinnnuez.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_martin_fierro_martinnnuez_en_5.5.1_3.0_1738084950322.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_martin_fierro_martinnnuez_en_5.5.1_3.0_1738084950322.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_adaptation_martin_fierro_martinnnuez","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_adaptation_martin_fierro_martinnnuez","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_martin_fierro_martinnnuez|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/martinnnuez/bert_adaptation_martin_fierro
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_adaptation_martin_fierro_martinnnuez_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_adaptation_martin_fierro_martinnnuez_pipeline_en.md
new file mode 100644
index 00000000000000..1d6838b61ae1e9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_adaptation_martin_fierro_martinnnuez_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_adaptation_martin_fierro_martinnnuez_pipeline pipeline BertEmbeddings from martinnnuez
+author: John Snow Labs
+name: bert_adaptation_martin_fierro_martinnnuez_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_martin_fierro_martinnnuez_pipeline` is a English model originally trained by martinnnuez.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_martin_fierro_martinnnuez_pipeline_en_5.5.1_3.0_1738084977637.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_martin_fierro_martinnnuez_pipeline_en_5.5.1_3.0_1738084977637.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_adaptation_martin_fierro_martinnnuez_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_adaptation_martin_fierro_martinnnuez_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_martin_fierro_martinnnuez_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/martinnnuez/bert_adaptation_martin_fierro
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_adaptation_peppa_pig_chelo11_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_adaptation_peppa_pig_chelo11_en.md
new file mode 100644
index 00000000000000..246b8c2c93af7f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_adaptation_peppa_pig_chelo11_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_adaptation_peppa_pig_chelo11 BertEmbeddings from Chelo11
+author: John Snow Labs
+name: bert_adaptation_peppa_pig_chelo11
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_peppa_pig_chelo11` is a English model originally trained by Chelo11.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_peppa_pig_chelo11_en_5.5.1_3.0_1738098343321.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_peppa_pig_chelo11_en_5.5.1_3.0_1738098343321.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_adaptation_peppa_pig_chelo11","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_adaptation_peppa_pig_chelo11","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_peppa_pig_chelo11|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/Chelo11/bert_adaptation_peppa_pig
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_adaptation_peppa_pig_chelo11_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_adaptation_peppa_pig_chelo11_pipeline_en.md
new file mode 100644
index 00000000000000..1e718def133e27
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_adaptation_peppa_pig_chelo11_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_adaptation_peppa_pig_chelo11_pipeline pipeline BertEmbeddings from Chelo11
+author: John Snow Labs
+name: bert_adaptation_peppa_pig_chelo11_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_peppa_pig_chelo11_pipeline` is a English model originally trained by Chelo11.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_peppa_pig_chelo11_pipeline_en_5.5.1_3.0_1738098363773.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_peppa_pig_chelo11_pipeline_en_5.5.1_3.0_1738098363773.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_adaptation_peppa_pig_chelo11_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_adaptation_peppa_pig_chelo11_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_peppa_pig_chelo11_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/Chelo11/bert_adaptation_peppa_pig
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_adaptation_peppa_pig_nolasco99_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_adaptation_peppa_pig_nolasco99_en.md
new file mode 100644
index 00000000000000..a759cce17287d7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_adaptation_peppa_pig_nolasco99_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_adaptation_peppa_pig_nolasco99 BertEmbeddings from nolasco99
+author: John Snow Labs
+name: bert_adaptation_peppa_pig_nolasco99
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_peppa_pig_nolasco99` is a English model originally trained by nolasco99.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_peppa_pig_nolasco99_en_5.5.1_3.0_1738084738818.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_peppa_pig_nolasco99_en_5.5.1_3.0_1738084738818.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_adaptation_peppa_pig_nolasco99","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_adaptation_peppa_pig_nolasco99","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_peppa_pig_nolasco99|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/nolasco99/bert_adaptation_peppa_pig
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_adaptation_peppa_pig_nolasco99_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_adaptation_peppa_pig_nolasco99_pipeline_en.md
new file mode 100644
index 00000000000000..71c99c1b644286
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_adaptation_peppa_pig_nolasco99_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_adaptation_peppa_pig_nolasco99_pipeline pipeline BertEmbeddings from nolasco99
+author: John Snow Labs
+name: bert_adaptation_peppa_pig_nolasco99_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_peppa_pig_nolasco99_pipeline` is a English model originally trained by nolasco99.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_peppa_pig_nolasco99_pipeline_en_5.5.1_3.0_1738084759410.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_peppa_pig_nolasco99_pipeline_en_5.5.1_3.0_1738084759410.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_adaptation_peppa_pig_nolasco99_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_adaptation_peppa_pig_nolasco99_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_peppa_pig_nolasco99_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/nolasco99/bert_adaptation_peppa_pig
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_adaptation_referencias_german_vinos_dyvanoff_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_adaptation_referencias_german_vinos_dyvanoff_en.md
new file mode 100644
index 00000000000000..e195c0f32f250a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_adaptation_referencias_german_vinos_dyvanoff_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_adaptation_referencias_german_vinos_dyvanoff BertEmbeddings from dyvanoff
+author: John Snow Labs
+name: bert_adaptation_referencias_german_vinos_dyvanoff
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_referencias_german_vinos_dyvanoff` is a English model originally trained by dyvanoff.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_referencias_german_vinos_dyvanoff_en_5.5.1_3.0_1738098527036.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_referencias_german_vinos_dyvanoff_en_5.5.1_3.0_1738098527036.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_adaptation_referencias_german_vinos_dyvanoff","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_adaptation_referencias_german_vinos_dyvanoff","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_referencias_german_vinos_dyvanoff|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/dyvanoff/bert_adaptation_referencias_de_vinos
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_adaptation_referencias_german_vinos_dyvanoff_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_adaptation_referencias_german_vinos_dyvanoff_pipeline_en.md
new file mode 100644
index 00000000000000..efa7ab8bed1723
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_adaptation_referencias_german_vinos_dyvanoff_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_adaptation_referencias_german_vinos_dyvanoff_pipeline pipeline BertEmbeddings from dyvanoff
+author: John Snow Labs
+name: bert_adaptation_referencias_german_vinos_dyvanoff_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_referencias_german_vinos_dyvanoff_pipeline` is a English model originally trained by dyvanoff.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_referencias_german_vinos_dyvanoff_pipeline_en_5.5.1_3.0_1738098547201.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_referencias_german_vinos_dyvanoff_pipeline_en_5.5.1_3.0_1738098547201.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_adaptation_referencias_german_vinos_dyvanoff_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_adaptation_referencias_german_vinos_dyvanoff_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_referencias_german_vinos_dyvanoff_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/dyvanoff/bert_adaptation_referencias_de_vinos
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_alex_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_alex_en.md
new file mode 100644
index 00000000000000..970a16328daf08
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_alex_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_alex BertForQuestionAnswering from Alexhv
+author: John Snow Labs
+name: bert_alex
+date: 2025-01-28
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_alex` is a English model originally trained by Alexhv.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_alex_en_5.5.1_3.0_1738062731072.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_alex_en_5.5.1_3.0_1738062731072.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_alex","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_alex", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_alex|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/Alexhv/bert-alex
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_alex_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_alex_pipeline_en.md
new file mode 100644
index 00000000000000..be2c57ee3278eb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_alex_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_alex_pipeline pipeline BertForQuestionAnswering from Alexhv
+author: John Snow Labs
+name: bert_alex_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_alex_pipeline` is a English model originally trained by Alexhv.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_alex_pipeline_en_5.5.1_3.0_1738062795327.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_alex_pipeline_en_5.5.1_3.0_1738062795327.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_alex_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_alex_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_alex_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/Alexhv/bert-alex
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_assurance_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_assurance_en.md
new file mode 100644
index 00000000000000..78ddb8dfe998db
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_assurance_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_assurance BertForSequenceClassification from ortaymed
+author: John Snow Labs
+name: bert_assurance
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_assurance` is a English model originally trained by ortaymed.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_assurance_en_5.5.1_3.0_1738052131487.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_assurance_en_5.5.1_3.0_1738052131487.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("bert_assurance","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("bert_assurance", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_assurance|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/ortaymed/bert_assurance
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_assurance_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_assurance_pipeline_en.md
new file mode 100644
index 00000000000000..15df5f4f0baa79
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_assurance_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_assurance_pipeline pipeline BertForSequenceClassification from ortaymed
+author: John Snow Labs
+name: bert_assurance_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_assurance_pipeline` is a English model originally trained by ortaymed.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_assurance_pipeline_en_5.5.1_3.0_1738052151732.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_assurance_pipeline_en_5.5.1_3.0_1738052151732.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_assurance_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_assurance_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_assurance_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/ortaymed/bert_assurance
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_arabertv02_finetuned_arabert_tswana_v2_0_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_arabertv02_finetuned_arabert_tswana_v2_0_en.md
new file mode 100644
index 00000000000000..9d429e17bacb5e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_arabertv02_finetuned_arabert_tswana_v2_0_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_arabertv02_finetuned_arabert_tswana_v2_0 BertEmbeddings from betteib
+author: John Snow Labs
+name: bert_base_arabertv02_finetuned_arabert_tswana_v2_0
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_arabertv02_finetuned_arabert_tswana_v2_0` is a English model originally trained by betteib.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_arabertv02_finetuned_arabert_tswana_v2_0_en_5.5.1_3.0_1738057407590.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_arabertv02_finetuned_arabert_tswana_v2_0_en_5.5.1_3.0_1738057407590.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_base_arabertv02_finetuned_arabert_tswana_v2_0","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_base_arabertv02_finetuned_arabert_tswana_v2_0","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_arabertv02_finetuned_arabert_tswana_v2_0|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|504.5 MB|
+
+## References
+
+https://huggingface.co/betteib/bert-base-arabertv02-finetuned-arabert-tn-v2.0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_arabertv02_finetuned_arabert_tswana_v2_0_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_arabertv02_finetuned_arabert_tswana_v2_0_pipeline_en.md
new file mode 100644
index 00000000000000..24b07442aa6d1d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_arabertv02_finetuned_arabert_tswana_v2_0_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_arabertv02_finetuned_arabert_tswana_v2_0_pipeline pipeline BertEmbeddings from betteib
+author: John Snow Labs
+name: bert_base_arabertv02_finetuned_arabert_tswana_v2_0_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_arabertv02_finetuned_arabert_tswana_v2_0_pipeline` is a English model originally trained by betteib.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_arabertv02_finetuned_arabert_tswana_v2_0_pipeline_en_5.5.1_3.0_1738057433649.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_arabertv02_finetuned_arabert_tswana_v2_0_pipeline_en_5.5.1_3.0_1738057433649.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_arabertv02_finetuned_arabert_tswana_v2_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_arabertv02_finetuned_arabert_tswana_v2_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_arabertv02_finetuned_arabert_tswana_v2_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|504.5 MB|
+
+## References
+
+https://huggingface.co/betteib/bert-base-arabertv02-finetuned-arabert-tn-v2.0
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_cased_portuguese_tycholina_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_cased_portuguese_tycholina_en.md
new file mode 100644
index 00000000000000..7eb0e2c3410282
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_cased_portuguese_tycholina_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_cased_portuguese_tycholina BertEmbeddings from lailamt
+author: John Snow Labs
+name: bert_base_cased_portuguese_tycholina
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_portuguese_tycholina` is a English model originally trained by lailamt.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_portuguese_tycholina_en_5.5.1_3.0_1738057796275.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_portuguese_tycholina_en_5.5.1_3.0_1738057796275.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_base_cased_portuguese_tycholina","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_base_cased_portuguese_tycholina","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_cased_portuguese_tycholina|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|405.9 MB|
+
+## References
+
+https://huggingface.co/lailamt/bert-base-cased-pt-tycholina
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_cased_portuguese_tycholina_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_cased_portuguese_tycholina_pipeline_en.md
new file mode 100644
index 00000000000000..e92387f7322e79
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_cased_portuguese_tycholina_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_cased_portuguese_tycholina_pipeline pipeline BertEmbeddings from lailamt
+author: John Snow Labs
+name: bert_base_cased_portuguese_tycholina_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_portuguese_tycholina_pipeline` is a English model originally trained by lailamt.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_portuguese_tycholina_pipeline_en_5.5.1_3.0_1738057816328.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_portuguese_tycholina_pipeline_en_5.5.1_3.0_1738057816328.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_cased_portuguese_tycholina_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_cased_portuguese_tycholina_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_cased_portuguese_tycholina_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.0 MB|
+
+## References
+
+https://huggingface.co/lailamt/bert-base-cased-pt-tycholina
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_cased_wikitext2_klee_9_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_cased_wikitext2_klee_9_en.md
new file mode 100644
index 00000000000000..da41a3da265038
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_cased_wikitext2_klee_9_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_cased_wikitext2_klee_9 BertEmbeddings from klee-9
+author: John Snow Labs
+name: bert_base_cased_wikitext2_klee_9
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_wikitext2_klee_9` is a English model originally trained by klee-9.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_wikitext2_klee_9_en_5.5.1_3.0_1738057986943.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_wikitext2_klee_9_en_5.5.1_3.0_1738057986943.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_base_cased_wikitext2_klee_9","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_base_cased_wikitext2_klee_9","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_cased_wikitext2_klee_9|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|403.4 MB|
+
+## References
+
+https://huggingface.co/klee-9/bert-base-cased-wikitext2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_cased_wikitext2_klee_9_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_cased_wikitext2_klee_9_pipeline_en.md
new file mode 100644
index 00000000000000..2c2fcc4114b45f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_cased_wikitext2_klee_9_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_cased_wikitext2_klee_9_pipeline pipeline BertEmbeddings from klee-9
+author: John Snow Labs
+name: bert_base_cased_wikitext2_klee_9_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_wikitext2_klee_9_pipeline` is a English model originally trained by klee-9.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_wikitext2_klee_9_pipeline_en_5.5.1_3.0_1738058006972.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_wikitext2_klee_9_pipeline_en_5.5.1_3.0_1738058006972.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_cased_wikitext2_klee_9_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_cased_wikitext2_klee_9_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_cased_wikitext2_klee_9_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.5 MB|
+
+## References
+
+https://huggingface.co/klee-9/bert-base-cased-wikitext2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_cased_wikitext2_treysharp_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_cased_wikitext2_treysharp_en.md
new file mode 100644
index 00000000000000..38b42dd65c7da2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_cased_wikitext2_treysharp_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_cased_wikitext2_treysharp BertEmbeddings from TreySharp
+author: John Snow Labs
+name: bert_base_cased_wikitext2_treysharp
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_wikitext2_treysharp` is a English model originally trained by TreySharp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_wikitext2_treysharp_en_5.5.1_3.0_1738057377190.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_wikitext2_treysharp_en_5.5.1_3.0_1738057377190.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_base_cased_wikitext2_treysharp","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_base_cased_wikitext2_treysharp","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_cased_wikitext2_treysharp|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|403.4 MB|
+
+## References
+
+https://huggingface.co/TreySharp/bert-base-cased-wikitext2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_cased_wikitext2_treysharp_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_cased_wikitext2_treysharp_pipeline_en.md
new file mode 100644
index 00000000000000..63bd77fa2c07b9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_cased_wikitext2_treysharp_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_cased_wikitext2_treysharp_pipeline pipeline BertEmbeddings from TreySharp
+author: John Snow Labs
+name: bert_base_cased_wikitext2_treysharp_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_wikitext2_treysharp_pipeline` is a English model originally trained by TreySharp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_wikitext2_treysharp_pipeline_en_5.5.1_3.0_1738057397809.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_wikitext2_treysharp_pipeline_en_5.5.1_3.0_1738057397809.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_cased_wikitext2_treysharp_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_cased_wikitext2_treysharp_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_cased_wikitext2_treysharp_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.5 MB|
+
+## References
+
+https://huggingface.co/TreySharp/bert-base-cased-wikitext2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_chinese_finetuned_squadv2_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_chinese_finetuned_squadv2_en.md
new file mode 100644
index 00000000000000..086cefadfbd9af
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_chinese_finetuned_squadv2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_chinese_finetuned_squadv2 BertForQuestionAnswering from real-jiakai
+author: John Snow Labs
+name: bert_base_chinese_finetuned_squadv2
+date: 2025-01-28
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_chinese_finetuned_squadv2` is a English model originally trained by real-jiakai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_finetuned_squadv2_en_5.5.1_3.0_1738061661879.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_finetuned_squadv2_en_5.5.1_3.0_1738061661879.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_chinese_finetuned_squadv2","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_chinese_finetuned_squadv2", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_chinese_finetuned_squadv2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|381.0 MB|
+
+## References
+
+https://huggingface.co/real-jiakai/bert-base-chinese-finetuned-squadv2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_chinese_finetuned_squadv2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_chinese_finetuned_squadv2_pipeline_en.md
new file mode 100644
index 00000000000000..e9935611d52023
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_chinese_finetuned_squadv2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_chinese_finetuned_squadv2_pipeline pipeline BertForQuestionAnswering from real-jiakai
+author: John Snow Labs
+name: bert_base_chinese_finetuned_squadv2_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_chinese_finetuned_squadv2_pipeline` is a English model originally trained by real-jiakai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_finetuned_squadv2_pipeline_en_5.5.1_3.0_1738061682509.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_finetuned_squadv2_pipeline_en_5.5.1_3.0_1738061682509.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_chinese_finetuned_squadv2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_chinese_finetuned_squadv2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_chinese_finetuned_squadv2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|381.0 MB|
+
+## References
+
+https://huggingface.co/real-jiakai/bert-base-chinese-finetuned-squadv2
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_finetuned_mgbam_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_finetuned_mgbam_en.md
new file mode 100644
index 00000000000000..80bed8afc97d90
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_finetuned_mgbam_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_finetuned_mgbam BertForSequenceClassification from mgbam
+author: John Snow Labs
+name: bert_base_finetuned_mgbam
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_finetuned_mgbam` is a English model originally trained by mgbam.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_finetuned_mgbam_en_5.5.1_3.0_1738056215492.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_finetuned_mgbam_en_5.5.1_3.0_1738056215492.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("bert_base_finetuned_mgbam","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_finetuned_mgbam", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_finetuned_mgbam|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/mgbam/bert-base-finetuned-mgbam
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_finetuned_mgbam_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_finetuned_mgbam_pipeline_en.md
new file mode 100644
index 00000000000000..26966317faef48
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_finetuned_mgbam_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_finetuned_mgbam_pipeline pipeline BertForSequenceClassification from mgbam
+author: John Snow Labs
+name: bert_base_finetuned_mgbam_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_finetuned_mgbam_pipeline` is a English model originally trained by mgbam.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_finetuned_mgbam_pipeline_en_5.5.1_3.0_1738056235630.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_finetuned_mgbam_pipeline_en_5.5.1_3.0_1738056235630.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_finetuned_mgbam_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_finetuned_mgbam_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_finetuned_mgbam_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/mgbam/bert-base-finetuned-mgbam
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_german_cased_mlm_chemistry_technical_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_german_cased_mlm_chemistry_technical_en.md
new file mode 100644
index 00000000000000..76e012976b93ce
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_german_cased_mlm_chemistry_technical_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_german_cased_mlm_chemistry_technical BertEmbeddings from jonas-luehrs
+author: John Snow Labs
+name: bert_base_german_cased_mlm_chemistry_technical
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_german_cased_mlm_chemistry_technical` is a English model originally trained by jonas-luehrs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_german_cased_mlm_chemistry_technical_en_5.5.1_3.0_1738098044088.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_german_cased_mlm_chemistry_technical_en_5.5.1_3.0_1738098044088.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_base_german_cased_mlm_chemistry_technical","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_base_german_cased_mlm_chemistry_technical","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_german_cased_mlm_chemistry_technical|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/jonas-luehrs/bert-base-german-cased-MLM-chemistry_technical
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_german_cased_mlm_chemistry_technical_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_german_cased_mlm_chemistry_technical_pipeline_en.md
new file mode 100644
index 00000000000000..07260da98597c8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_german_cased_mlm_chemistry_technical_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_german_cased_mlm_chemistry_technical_pipeline pipeline BertEmbeddings from jonas-luehrs
+author: John Snow Labs
+name: bert_base_german_cased_mlm_chemistry_technical_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_german_cased_mlm_chemistry_technical_pipeline` is a English model originally trained by jonas-luehrs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_german_cased_mlm_chemistry_technical_pipeline_en_5.5.1_3.0_1738098064877.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_german_cased_mlm_chemistry_technical_pipeline_en_5.5.1_3.0_1738098064877.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_german_cased_mlm_chemistry_technical_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_german_cased_mlm_chemistry_technical_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_german_cased_mlm_chemistry_technical_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/jonas-luehrs/bert-base-german-cased-MLM-chemistry_technical
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_qarib60_1790k_ar.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_qarib60_1790k_ar.md
new file mode 100644
index 00000000000000..84ec7f4a4d1451
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_qarib60_1790k_ar.md
@@ -0,0 +1,92 @@
+---
+layout: model
+title: Arabic bert_base_qarib60_1790k BertEmbeddings from qarib
+author: John Snow Labs
+name: bert_base_qarib60_1790k
+date: 2025-01-28
+tags: [bert, ar, open_source, fill_mask, onnx]
+task: Embeddings
+language: ar
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings  model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_qarib60_1790k` is a Arabic model originally trained by qarib.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_qarib60_1790k_ar_5.5.1_3.0_1738096285933.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_qarib60_1790k_ar_5.5.1_3.0_1738096285933.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("documents")
+    
+    
+embeddings =BertEmbeddings.pretrained("bert_base_qarib60_1790k","ar") \
+            .setInputCols(["documents","token"]) \
+            .setOutputCol("embeddings")
+
+pipeline = Pipeline().setStages([document_assembler, embeddings])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val document_assembler = new DocumentAssembler()
+    .setInputCol("text") 
+    .setOutputCol("embeddings")
+    
+val embeddings = BertEmbeddings 
+    .pretrained("bert_base_qarib60_1790k", "ar")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("embeddings") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_qarib60_1790k|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|ar|
+|Size:|504.9 MB|
+
+## References
+
+References
+
+https://huggingface.co/qarib/bert-base-qarib60_1790k
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_qarib60_1790k_pipeline_ar.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_qarib60_1790k_pipeline_ar.md
new file mode 100644
index 00000000000000..dfd6bfa93c18f9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_qarib60_1790k_pipeline_ar.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Arabic bert_base_qarib60_1790k_pipeline pipeline BertEmbeddings from ahmedabdelali
+author: John Snow Labs
+name: bert_base_qarib60_1790k_pipeline
+date: 2025-01-28
+tags: [ar, open_source, pipeline, onnx]
+task: Embeddings
+language: ar
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_qarib60_1790k_pipeline` is a Arabic model originally trained by ahmedabdelali.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_qarib60_1790k_pipeline_ar_5.5.1_3.0_1738096311314.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_qarib60_1790k_pipeline_ar_5.5.1_3.0_1738096311314.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_qarib60_1790k_pipeline", lang = "ar")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_qarib60_1790k_pipeline", lang = "ar")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_qarib60_1790k_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ar|
+|Size:|505.0 MB|
+
+## References
+
+https://huggingface.co/ahmedabdelali/bert-base-qarib60_1790k
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_tsonga_phonetic_wikitext_0_01_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_tsonga_phonetic_wikitext_0_01_en.md
new file mode 100644
index 00000000000000..4fc5b680199f25
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_tsonga_phonetic_wikitext_0_01_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_tsonga_phonetic_wikitext_0_01 BertEmbeddings from psktoure
+author: John Snow Labs
+name: bert_base_tsonga_phonetic_wikitext_0_01
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_tsonga_phonetic_wikitext_0_01` is a English model originally trained by psktoure.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_tsonga_phonetic_wikitext_0_01_en_5.5.1_3.0_1738039601228.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_tsonga_phonetic_wikitext_0_01_en_5.5.1_3.0_1738039601228.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_base_tsonga_phonetic_wikitext_0_01","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_base_tsonga_phonetic_wikitext_0_01","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_tsonga_phonetic_wikitext_0_01|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/psktoure/BERT_BASE_TS_phonetic_wikitext_0.01
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_tsonga_phonetic_wikitext_0_01_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_tsonga_phonetic_wikitext_0_01_pipeline_en.md
new file mode 100644
index 00000000000000..95118008060361
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_tsonga_phonetic_wikitext_0_01_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_tsonga_phonetic_wikitext_0_01_pipeline pipeline BertEmbeddings from psktoure
+author: John Snow Labs
+name: bert_base_tsonga_phonetic_wikitext_0_01_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_tsonga_phonetic_wikitext_0_01_pipeline` is a English model originally trained by psktoure.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_tsonga_phonetic_wikitext_0_01_pipeline_en_5.5.1_3.0_1738039622895.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_tsonga_phonetic_wikitext_0_01_pipeline_en_5.5.1_3.0_1738039622895.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_tsonga_phonetic_wikitext_0_01_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_tsonga_phonetic_wikitext_0_01_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_tsonga_phonetic_wikitext_0_01_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.3 MB|
+
+## References
+
+https://huggingface.co/psktoure/BERT_BASE_TS_phonetic_wikitext_0.01
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_ep_4_87_b_32_lr_1_2e_06_dp_0_3_swati_0_southern_sotho_true_fh_false_hs_0_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_ep_4_87_b_32_lr_1_2e_06_dp_0_3_swati_0_southern_sotho_true_fh_false_hs_0_en.md
new file mode 100644
index 00000000000000..97b8f457b9af18
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_ep_4_87_b_32_lr_1_2e_06_dp_0_3_swati_0_southern_sotho_true_fh_false_hs_0_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_ep_4_87_b_32_lr_1_2e_06_dp_0_3_swati_0_southern_sotho_true_fh_false_hs_0 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_4_87_b_32_lr_1_2e_06_dp_0_3_swati_0_southern_sotho_true_fh_false_hs_0
+date: 2025-01-28
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_4_87_b_32_lr_1_2e_06_dp_0_3_swati_0_southern_sotho_true_fh_false_hs_0` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_4_87_b_32_lr_1_2e_06_dp_0_3_swati_0_southern_sotho_true_fh_false_hs_0_en_5.5.1_3.0_1738062225279.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_4_87_b_32_lr_1_2e_06_dp_0_3_swati_0_southern_sotho_true_fh_false_hs_0_en_5.5.1_3.0_1738062225279.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_4_87_b_32_lr_1_2e_06_dp_0_3_swati_0_southern_sotho_true_fh_false_hs_0","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_4_87_b_32_lr_1_2e_06_dp_0_3_swati_0_southern_sotho_true_fh_false_hs_0", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_4_87_b_32_lr_1_2e_06_dp_0_3_swati_0_southern_sotho_true_fh_false_hs_0|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-4.87-b-32-lr-1.2e-06-dp-0.3-ss-0-st-True-fh-False-hs-0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_ep_4_87_b_32_lr_1_2e_06_dp_0_3_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_ep_4_87_b_32_lr_1_2e_06_dp_0_3_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en.md
new file mode 100644
index 00000000000000..4bd04306d3ea6f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_ep_4_87_b_32_lr_1_2e_06_dp_0_3_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_ep_4_87_b_32_lr_1_2e_06_dp_0_3_swati_0_southern_sotho_true_fh_false_hs_0_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_ep_4_87_b_32_lr_1_2e_06_dp_0_3_swati_0_southern_sotho_true_fh_false_hs_0_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ep_4_87_b_32_lr_1_2e_06_dp_0_3_swati_0_southern_sotho_true_fh_false_hs_0_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_4_87_b_32_lr_1_2e_06_dp_0_3_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en_5.5.1_3.0_1738062251484.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_4_87_b_32_lr_1_2e_06_dp_0_3_swati_0_southern_sotho_true_fh_false_hs_0_pipeline_en_5.5.1_3.0_1738062251484.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_ep_4_87_b_32_lr_1_2e_06_dp_0_3_swati_0_southern_sotho_true_fh_false_hs_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_ep_4_87_b_32_lr_1_2e_06_dp_0_3_swati_0_southern_sotho_true_fh_false_hs_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_ep_4_87_b_32_lr_1_2e_06_dp_0_3_swati_0_southern_sotho_true_fh_false_hs_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-ep-4.87-b-32-lr-1.2e-06-dp-0.3-ss-0-st-True-fh-False-hs-0
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_0_4_lr_1e_06_wd_0_001_dp_0_99999_swati_100000_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_0_4_lr_1e_06_wd_0_001_dp_0_99999_swati_100000_en.md
new file mode 100644
index 00000000000000..56eb582f920c75
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_0_4_lr_1e_06_wd_0_001_dp_0_99999_swati_100000_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_0_4_lr_1e_06_wd_0_001_dp_0_99999_swati_100000 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_0_4_lr_1e_06_wd_0_001_dp_0_99999_swati_100000
+date: 2025-01-28
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_0_4_lr_1e_06_wd_0_001_dp_0_99999_swati_100000` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_0_4_lr_1e_06_wd_0_001_dp_0_99999_swati_100000_en_5.5.1_3.0_1738062764540.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_0_4_lr_1e_06_wd_0_001_dp_0_99999_swati_100000_en_5.5.1_3.0_1738062764540.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_0_4_lr_1e_06_wd_0_001_dp_0_99999_swati_100000","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_0_4_lr_1e_06_wd_0_001_dp_0_99999_swati_100000", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_0_4_lr_1e_06_wd_0_001_dp_0_99999_swati_100000|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-0.4-lr-1e-06-wd-0.001-dp-0.99999-ss-100000
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_0_4_lr_1e_06_wd_0_001_dp_0_99999_swati_100000_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_0_4_lr_1e_06_wd_0_001_dp_0_99999_swati_100000_pipeline_en.md
new file mode 100644
index 00000000000000..9f6ef64cff5184
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_0_4_lr_1e_06_wd_0_001_dp_0_99999_swati_100000_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_0_4_lr_1e_06_wd_0_001_dp_0_99999_swati_100000_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_0_4_lr_1e_06_wd_0_001_dp_0_99999_swati_100000_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_0_4_lr_1e_06_wd_0_001_dp_0_99999_swati_100000_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_0_4_lr_1e_06_wd_0_001_dp_0_99999_swati_100000_pipeline_en_5.5.1_3.0_1738062787338.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_0_4_lr_1e_06_wd_0_001_dp_0_99999_swati_100000_pipeline_en_5.5.1_3.0_1738062787338.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_0_4_lr_1e_06_wd_0_001_dp_0_99999_swati_100000_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_0_4_lr_1e_06_wd_0_001_dp_0_99999_swati_100000_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_0_4_lr_1e_06_wd_0_001_dp_0_99999_swati_100000_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-0.4-lr-1e-06-wd-0.001-dp-0.99999-ss-100000
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_0_5_lr_1e_05_wd_0_001_dp_0_99999_swati_120000_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_0_5_lr_1e_05_wd_0_001_dp_0_99999_swati_120000_en.md
new file mode 100644
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--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_0_5_lr_1e_05_wd_0_001_dp_0_99999_swati_120000_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_0_5_lr_1e_05_wd_0_001_dp_0_99999_swati_120000 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_0_5_lr_1e_05_wd_0_001_dp_0_99999_swati_120000
+date: 2025-01-28
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_0_5_lr_1e_05_wd_0_001_dp_0_99999_swati_120000` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_0_5_lr_1e_05_wd_0_001_dp_0_99999_swati_120000_en_5.5.1_3.0_1738062069420.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_0_5_lr_1e_05_wd_0_001_dp_0_99999_swati_120000_en_5.5.1_3.0_1738062069420.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_0_5_lr_1e_05_wd_0_001_dp_0_99999_swati_120000","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_0_5_lr_1e_05_wd_0_001_dp_0_99999_swati_120000", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_0_5_lr_1e_05_wd_0_001_dp_0_99999_swati_120000|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-0.5-lr-1e-05-wd-0.001-dp-0.99999-ss-120000
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_0_5_lr_1e_05_wd_0_001_dp_0_99999_swati_120000_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_0_5_lr_1e_05_wd_0_001_dp_0_99999_swati_120000_pipeline_en.md
new file mode 100644
index 00000000000000..420db61d340113
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_0_5_lr_1e_05_wd_0_001_dp_0_99999_swati_120000_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_0_5_lr_1e_05_wd_0_001_dp_0_99999_swati_120000_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_0_5_lr_1e_05_wd_0_001_dp_0_99999_swati_120000_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_0_5_lr_1e_05_wd_0_001_dp_0_99999_swati_120000_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_0_5_lr_1e_05_wd_0_001_dp_0_99999_swati_120000_pipeline_en_5.5.1_3.0_1738062092708.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_0_5_lr_1e_05_wd_0_001_dp_0_99999_swati_120000_pipeline_en_5.5.1_3.0_1738062092708.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_0_5_lr_1e_05_wd_0_001_dp_0_99999_swati_120000_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_0_5_lr_1e_05_wd_0_001_dp_0_99999_swati_120000_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_0_5_lr_1e_05_wd_0_001_dp_0_99999_swati_120000_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-0.5-lr-1e-05-wd-0.001-dp-0.99999-ss-120000
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_100_southern_sotho_true_fh_true_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_100_southern_sotho_true_fh_true_en.md
new file mode 100644
index 00000000000000..0c0a699c9f4bf8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_100_southern_sotho_true_fh_true_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_100_southern_sotho_true_fh_true BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_100_southern_sotho_true_fh_true
+date: 2025-01-28
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_100_southern_sotho_true_fh_true` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_100_southern_sotho_true_fh_true_en_5.5.1_3.0_1738062180132.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_100_southern_sotho_true_fh_true_en_5.5.1_3.0_1738062180132.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_100_southern_sotho_true_fh_true","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_100_southern_sotho_true_fh_true", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_100_southern_sotho_true_fh_true|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.0-lr-1e-06-wd-0.001-dp-0.2-ss-100-st-True-fh-True
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_100_southern_sotho_true_fh_true_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_100_southern_sotho_true_fh_true_pipeline_en.md
new file mode 100644
index 00000000000000..552a023f1511f2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_100_southern_sotho_true_fh_true_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_100_southern_sotho_true_fh_true_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_100_southern_sotho_true_fh_true_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_100_southern_sotho_true_fh_true_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_100_southern_sotho_true_fh_true_pipeline_en_5.5.1_3.0_1738062200452.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_100_southern_sotho_true_fh_true_pipeline_en_5.5.1_3.0_1738062200452.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_100_southern_sotho_true_fh_true_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_100_southern_sotho_true_fh_true_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_0_001_dp_0_2_swati_100_southern_sotho_true_fh_true_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.0-lr-1e-06-wd-0.001-dp-0.2-ss-100-st-True-fh-True
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_0_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_0_en.md
new file mode 100644
index 00000000000000..136a38a87c9863
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_0_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_0 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_0
+date: 2025-01-28
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_0` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_0_en_5.5.1_3.0_1738061635194.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_0_en_5.5.1_3.0_1738061635194.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_0","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_0", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_0|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.0-lr-1e-06-wd-1e-05-dp-1.0-ss-0-st-False-fh-False-hs-0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_0_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_0_pipeline_en.md
new file mode 100644
index 00000000000000..926ed89e55a7db
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_0_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_0_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_0_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_0_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_0_pipeline_en_5.5.1_3.0_1738061665080.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_0_pipeline_en_5.5.1_3.0_1738061665080.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_0_lr_1e_06_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.0-lr-1e-06-wd-1e-05-dp-1.0-ss-0-st-False-fh-False-hs-0
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_1_0_lr_3e_06_wd_0_005_dp_0_2_swati_5600_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_1_0_lr_3e_06_wd_0_005_dp_0_2_swati_5600_en.md
new file mode 100644
index 00000000000000..6975205ed1f72a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_1_0_lr_3e_06_wd_0_005_dp_0_2_swati_5600_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_0_lr_3e_06_wd_0_005_dp_0_2_swati_5600 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_0_lr_3e_06_wd_0_005_dp_0_2_swati_5600
+date: 2025-01-28
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_0_lr_3e_06_wd_0_005_dp_0_2_swati_5600` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_3e_06_wd_0_005_dp_0_2_swati_5600_en_5.5.1_3.0_1738061489280.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_3e_06_wd_0_005_dp_0_2_swati_5600_en_5.5.1_3.0_1738061489280.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_0_lr_3e_06_wd_0_005_dp_0_2_swati_5600","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_0_lr_3e_06_wd_0_005_dp_0_2_swati_5600", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_0_lr_3e_06_wd_0_005_dp_0_2_swati_5600|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.0-lr-3e-06-wd-0.005-dp-0.2-ss-5600
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_1_0_lr_3e_06_wd_0_005_dp_0_2_swati_5600_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_1_0_lr_3e_06_wd_0_005_dp_0_2_swati_5600_pipeline_en.md
new file mode 100644
index 00000000000000..db29570007cc58
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_1_0_lr_3e_06_wd_0_005_dp_0_2_swati_5600_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_0_lr_3e_06_wd_0_005_dp_0_2_swati_5600_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_0_lr_3e_06_wd_0_005_dp_0_2_swati_5600_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_0_lr_3e_06_wd_0_005_dp_0_2_swati_5600_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_3e_06_wd_0_005_dp_0_2_swati_5600_pipeline_en_5.5.1_3.0_1738061509980.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_3e_06_wd_0_005_dp_0_2_swati_5600_pipeline_en_5.5.1_3.0_1738061509980.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_0_lr_3e_06_wd_0_005_dp_0_2_swati_5600_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_0_lr_3e_06_wd_0_005_dp_0_2_swati_5600_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_0_lr_3e_06_wd_0_005_dp_0_2_swati_5600_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.0-lr-3e-06-wd-0.005-dp-0.2-ss-5600
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_1_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_700_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_1_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_700_en.md
new file mode 100644
index 00000000000000..c1e06881c04bbd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_1_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_700_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_700 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_700
+date: 2025-01-28
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_700` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_700_en_5.5.1_3.0_1738061814195.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_700_en_5.5.1_3.0_1738061814195.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_700","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_700", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_700|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.0-lr-5e-06-wd-0.001-dp-0.2-ss-0-st-False-fh-False-hs-700
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_1_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_700_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_1_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_700_pipeline_en.md
new file mode 100644
index 00000000000000..0fe1d63dd0b8d4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_1_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_700_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_700_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_700_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_700_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_700_pipeline_en_5.5.1_3.0_1738061834675.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_700_pipeline_en_5.5.1_3.0_1738061834675.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_700_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_700_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_0_lr_5e_06_wd_0_001_dp_0_2_swati_0_southern_sotho_false_fh_false_hs_700_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.0-lr-5e-06-wd-0.001-dp-0.2-ss-0-st-False-fh-False-hs-700
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_1_2_lr_1e_05_wd_0_001_dp_0_2_swati_0_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_1_2_lr_1e_05_wd_0_001_dp_0_2_swati_0_en.md
new file mode 100644
index 00000000000000..57dfa973744303
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_1_2_lr_1e_05_wd_0_001_dp_0_2_swati_0_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_2_lr_1e_05_wd_0_001_dp_0_2_swati_0 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_2_lr_1e_05_wd_0_001_dp_0_2_swati_0
+date: 2025-01-28
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_2_lr_1e_05_wd_0_001_dp_0_2_swati_0` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_2_lr_1e_05_wd_0_001_dp_0_2_swati_0_en_5.5.1_3.0_1738062191068.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_2_lr_1e_05_wd_0_001_dp_0_2_swati_0_en_5.5.1_3.0_1738062191068.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_2_lr_1e_05_wd_0_001_dp_0_2_swati_0","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_2_lr_1e_05_wd_0_001_dp_0_2_swati_0", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_2_lr_1e_05_wd_0_001_dp_0_2_swati_0|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.2-lr-1e-05-wd-0.001-dp-0.2-ss-0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_1_2_lr_1e_05_wd_0_001_dp_0_2_swati_0_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_1_2_lr_1e_05_wd_0_001_dp_0_2_swati_0_pipeline_en.md
new file mode 100644
index 00000000000000..d15504df77abcc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_1_2_lr_1e_05_wd_0_001_dp_0_2_swati_0_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_2_lr_1e_05_wd_0_001_dp_0_2_swati_0_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_2_lr_1e_05_wd_0_001_dp_0_2_swati_0_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_2_lr_1e_05_wd_0_001_dp_0_2_swati_0_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_2_lr_1e_05_wd_0_001_dp_0_2_swati_0_pipeline_en_5.5.1_3.0_1738062212432.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_2_lr_1e_05_wd_0_001_dp_0_2_swati_0_pipeline_en_5.5.1_3.0_1738062212432.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_2_lr_1e_05_wd_0_001_dp_0_2_swati_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_2_lr_1e_05_wd_0_001_dp_0_2_swati_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_2_lr_1e_05_wd_0_001_dp_0_2_swati_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.2-lr-1e-05-wd-0.001-dp-0.2-ss-0
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_1_5_lr_1e_06_wd_0_001_dp_0_99999_swati_10000_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_1_5_lr_1e_06_wd_0_001_dp_0_99999_swati_10000_en.md
new file mode 100644
index 00000000000000..a62b71a439b28e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_1_5_lr_1e_06_wd_0_001_dp_0_99999_swati_10000_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_5_lr_1e_06_wd_0_001_dp_0_99999_swati_10000 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_5_lr_1e_06_wd_0_001_dp_0_99999_swati_10000
+date: 2025-01-28
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_5_lr_1e_06_wd_0_001_dp_0_99999_swati_10000` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_5_lr_1e_06_wd_0_001_dp_0_99999_swati_10000_en_5.5.1_3.0_1738062314866.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_5_lr_1e_06_wd_0_001_dp_0_99999_swati_10000_en_5.5.1_3.0_1738062314866.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_5_lr_1e_06_wd_0_001_dp_0_99999_swati_10000","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_5_lr_1e_06_wd_0_001_dp_0_99999_swati_10000", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_5_lr_1e_06_wd_0_001_dp_0_99999_swati_10000|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.5-lr-1e-06-wd-0.001-dp-0.99999-ss-10000
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_1_5_lr_1e_06_wd_0_001_dp_0_99999_swati_10000_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_1_5_lr_1e_06_wd_0_001_dp_0_99999_swati_10000_pipeline_en.md
new file mode 100644
index 00000000000000..1f148ac940ba43
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_1_5_lr_1e_06_wd_0_001_dp_0_99999_swati_10000_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_5_lr_1e_06_wd_0_001_dp_0_99999_swati_10000_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_5_lr_1e_06_wd_0_001_dp_0_99999_swati_10000_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_5_lr_1e_06_wd_0_001_dp_0_99999_swati_10000_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_5_lr_1e_06_wd_0_001_dp_0_99999_swati_10000_pipeline_en_5.5.1_3.0_1738062335194.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_5_lr_1e_06_wd_0_001_dp_0_99999_swati_10000_pipeline_en_5.5.1_3.0_1738062335194.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_5_lr_1e_06_wd_0_001_dp_0_99999_swati_10000_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_5_lr_1e_06_wd_0_001_dp_0_99999_swati_10000_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_5_lr_1e_06_wd_0_001_dp_0_99999_swati_10000_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.5-lr-1e-06-wd-0.001-dp-0.99999-ss-10000
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_1_7_lr_1e_06_wd_0_001_dp_0_99999_swati_180000_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_1_7_lr_1e_06_wd_0_001_dp_0_99999_swati_180000_en.md
new file mode 100644
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--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_1_7_lr_1e_06_wd_0_001_dp_0_99999_swati_180000_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_7_lr_1e_06_wd_0_001_dp_0_99999_swati_180000 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_7_lr_1e_06_wd_0_001_dp_0_99999_swati_180000
+date: 2025-01-28
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_7_lr_1e_06_wd_0_001_dp_0_99999_swati_180000` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_7_lr_1e_06_wd_0_001_dp_0_99999_swati_180000_en_5.5.1_3.0_1738062641203.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_7_lr_1e_06_wd_0_001_dp_0_99999_swati_180000_en_5.5.1_3.0_1738062641203.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_7_lr_1e_06_wd_0_001_dp_0_99999_swati_180000","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_7_lr_1e_06_wd_0_001_dp_0_99999_swati_180000", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_7_lr_1e_06_wd_0_001_dp_0_99999_swati_180000|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.7-lr-1e-06-wd-0.001-dp-0.99999-ss-180000
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_1_7_lr_1e_06_wd_0_001_dp_0_99999_swati_180000_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_1_7_lr_1e_06_wd_0_001_dp_0_99999_swati_180000_pipeline_en.md
new file mode 100644
index 00000000000000..f6e7ba2ef3edc6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_1_7_lr_1e_06_wd_0_001_dp_0_99999_swati_180000_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_1_7_lr_1e_06_wd_0_001_dp_0_99999_swati_180000_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_1_7_lr_1e_06_wd_0_001_dp_0_99999_swati_180000_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_1_7_lr_1e_06_wd_0_001_dp_0_99999_swati_180000_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_7_lr_1e_06_wd_0_001_dp_0_99999_swati_180000_pipeline_en_5.5.1_3.0_1738062662031.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_7_lr_1e_06_wd_0_001_dp_0_99999_swati_180000_pipeline_en_5.5.1_3.0_1738062662031.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_7_lr_1e_06_wd_0_001_dp_0_99999_swati_180000_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_1_7_lr_1e_06_wd_0_001_dp_0_99999_swati_180000_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_1_7_lr_1e_06_wd_0_001_dp_0_99999_swati_180000_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.7-lr-1e-06-wd-0.001-dp-0.99999-ss-180000
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_01_swati_0_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_01_swati_0_en.md
new file mode 100644
index 00000000000000..caf180691065b3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_01_swati_0_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_01_swati_0 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_01_swati_0
+date: 2025-01-28
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_01_swati_0` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_01_swati_0_en_5.5.1_3.0_1738062354080.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_01_swati_0_en_5.5.1_3.0_1738062354080.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_01_swati_0","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_01_swati_0", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_01_swati_0|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-3.0-lr-1e-05-wd-0.001-dp-0.01-ss-0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_01_swati_0_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_01_swati_0_pipeline_en.md
new file mode 100644
index 00000000000000..750bfb0e36e38b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_01_swati_0_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_01_swati_0_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_01_swati_0_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_01_swati_0_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_01_swati_0_pipeline_en_5.5.1_3.0_1738062375033.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_01_swati_0_pipeline_en_5.5.1_3.0_1738062375033.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_01_swati_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_01_swati_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_3_0_lr_1e_05_wd_0_001_dp_0_01_swati_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-3.0-lr-1e-05-wd-0.001-dp-0.01-ss-0
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_002_swati_0_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_002_swati_0_en.md
new file mode 100644
index 00000000000000..249256cdbd12c7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_002_swati_0_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_002_swati_0 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_002_swati_0
+date: 2025-01-28
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_002_swati_0` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_002_swati_0_en_5.5.1_3.0_1738061947973.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_002_swati_0_en_5.5.1_3.0_1738061947973.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_002_swati_0","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_002_swati_0", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_002_swati_0|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-4.0-lr-1e-05-wd-0.001-dp-0.002-ss-0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_002_swati_0_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_002_swati_0_pipeline_en.md
new file mode 100644
index 00000000000000..916db851636a2d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_002_swati_0_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_002_swati_0_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_002_swati_0_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_002_swati_0_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_002_swati_0_pipeline_en_5.5.1_3.0_1738061968293.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_002_swati_0_pipeline_en_5.5.1_3.0_1738061968293.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_002_swati_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_002_swati_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_4_0_lr_1e_05_wd_0_001_dp_0_002_swati_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-4.0-lr-1e-05-wd-0.001-dp-0.002-ss-0
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_4_87_lr_4e_07_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_900_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_4_87_lr_4e_07_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_900_en.md
new file mode 100644
index 00000000000000..41c2e5189f6d86
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_4_87_lr_4e_07_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_900_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_4_87_lr_4e_07_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_900 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_4_87_lr_4e_07_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_900
+date: 2025-01-28
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_4_87_lr_4e_07_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_900` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_4_87_lr_4e_07_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_900_en_5.5.1_3.0_1738061500419.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_4_87_lr_4e_07_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_900_en_5.5.1_3.0_1738061500419.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_4_87_lr_4e_07_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_900","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_4_87_lr_4e_07_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_900", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_4_87_lr_4e_07_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_900|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-4.87-lr-4e-07-wd-1e-05-dp-1.0-ss-0-st-False-fh-False-hs-900
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_4_87_lr_4e_07_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_900_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_4_87_lr_4e_07_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_900_pipeline_en.md
new file mode 100644
index 00000000000000..27fc1409c26a51
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_4_87_lr_4e_07_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_900_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_4_87_lr_4e_07_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_900_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_4_87_lr_4e_07_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_900_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_4_87_lr_4e_07_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_900_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_4_87_lr_4e_07_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_900_pipeline_en_5.5.1_3.0_1738061526014.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_4_87_lr_4e_07_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_900_pipeline_en_5.5.1_3.0_1738061526014.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_4_87_lr_4e_07_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_900_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_4_87_lr_4e_07_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_900_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_4_87_lr_4e_07_wd_1e_05_dp_1_0_swati_0_southern_sotho_false_fh_false_hs_900_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-4.87-lr-4e-07-wd-1e-05-dp-1.0-ss-0-st-False-fh-False-hs-900
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_6_0_lr_1e_05_wd_0_001_dp_0_01_swati_0_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_6_0_lr_1e_05_wd_0_001_dp_0_01_swati_0_en.md
new file mode 100644
index 00000000000000..8c417a0a6b8070
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_6_0_lr_1e_05_wd_0_001_dp_0_01_swati_0_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_6_0_lr_1e_05_wd_0_001_dp_0_01_swati_0 BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_6_0_lr_1e_05_wd_0_001_dp_0_01_swati_0
+date: 2025-01-28
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_6_0_lr_1e_05_wd_0_001_dp_0_01_swati_0` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_6_0_lr_1e_05_wd_0_001_dp_0_01_swati_0_en_5.5.1_3.0_1738061497953.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_6_0_lr_1e_05_wd_0_001_dp_0_01_swati_0_en_5.5.1_3.0_1738061497953.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_6_0_lr_1e_05_wd_0_001_dp_0_01_swati_0","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_6_0_lr_1e_05_wd_0_001_dp_0_01_swati_0", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_6_0_lr_1e_05_wd_0_001_dp_0_01_swati_0|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-6.0-lr-1e-05-wd-0.001-dp-0.01-ss-0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_6_0_lr_1e_05_wd_0_001_dp_0_01_swati_0_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_6_0_lr_1e_05_wd_0_001_dp_0_01_swati_0_pipeline_en.md
new file mode 100644
index 00000000000000..7f26eda5f9bd32
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetune_squad_ep_6_0_lr_1e_05_wd_0_001_dp_0_01_swati_0_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetune_squad_ep_6_0_lr_1e_05_wd_0_001_dp_0_01_swati_0_pipeline pipeline BertForQuestionAnswering from danielkty22
+author: John Snow Labs
+name: bert_base_uncased_finetune_squad_ep_6_0_lr_1e_05_wd_0_001_dp_0_01_swati_0_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_6_0_lr_1e_05_wd_0_001_dp_0_01_swati_0_pipeline` is a English model originally trained by danielkty22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_6_0_lr_1e_05_wd_0_001_dp_0_01_swati_0_pipeline_en_5.5.1_3.0_1738061518923.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_6_0_lr_1e_05_wd_0_001_dp_0_01_swati_0_pipeline_en_5.5.1_3.0_1738061518923.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_6_0_lr_1e_05_wd_0_001_dp_0_01_swati_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_6_0_lr_1e_05_wd_0_001_dp_0_01_swati_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetune_squad_ep_6_0_lr_1e_05_wd_0_001_dp_0_01_swati_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-6.0-lr-1e-05-wd-0.001-dp-0.01-ss-0
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_mlm_nef_20240325_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_mlm_nef_20240325_en.md
new file mode 100644
index 00000000000000..c7f399b9851650
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_mlm_nef_20240325_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_uncased_finetuned_mlm_nef_20240325 BertEmbeddings from JTh34
+author: John Snow Labs
+name: bert_base_uncased_finetuned_mlm_nef_20240325
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_mlm_nef_20240325` is a English model originally trained by JTh34.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_mlm_nef_20240325_en_5.5.1_3.0_1738034698128.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_mlm_nef_20240325_en_5.5.1_3.0_1738034698128.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_base_uncased_finetuned_mlm_nef_20240325","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_base_uncased_finetuned_mlm_nef_20240325","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetuned_mlm_nef_20240325|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|417.5 MB|
+
+## References
+
+https://huggingface.co/JTh34/bert-base-uncased-finetuned-mlm-nef-20240325
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_mlm_nef_20240325_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_mlm_nef_20240325_pipeline_en.md
new file mode 100644
index 00000000000000..7c7b157044aeb3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_mlm_nef_20240325_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_uncased_finetuned_mlm_nef_20240325_pipeline pipeline BertEmbeddings from JTh34
+author: John Snow Labs
+name: bert_base_uncased_finetuned_mlm_nef_20240325_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_mlm_nef_20240325_pipeline` is a English model originally trained by JTh34.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_mlm_nef_20240325_pipeline_en_5.5.1_3.0_1738034719005.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_mlm_nef_20240325_pipeline_en_5.5.1_3.0_1738034719005.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetuned_mlm_nef_20240325_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_mlm_nef_20240325_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetuned_mlm_nef_20240325_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|417.5 MB|
+
+## References
+
+https://huggingface.co/JTh34/bert-base-uncased-finetuned-mlm-nef-20240325
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_news_1908_1909_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_news_1908_1909_en.md
new file mode 100644
index 00000000000000..39f09df6cca8a7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_news_1908_1909_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_uncased_finetuned_news_1908_1909 BertEmbeddings from sally9805
+author: John Snow Labs
+name: bert_base_uncased_finetuned_news_1908_1909
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_news_1908_1909` is a English model originally trained by sally9805.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_news_1908_1909_en_5.5.1_3.0_1738057384424.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_news_1908_1909_en_5.5.1_3.0_1738057384424.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_base_uncased_finetuned_news_1908_1909","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_base_uncased_finetuned_news_1908_1909","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetuned_news_1908_1909|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/sally9805/bert-base-uncased-finetuned-news-1908-1909
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_news_1908_1909_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_news_1908_1909_pipeline_en.md
new file mode 100644
index 00000000000000..30c79a1a97cc11
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_news_1908_1909_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_uncased_finetuned_news_1908_1909_pipeline pipeline BertEmbeddings from sally9805
+author: John Snow Labs
+name: bert_base_uncased_finetuned_news_1908_1909_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_news_1908_1909_pipeline` is a English model originally trained by sally9805.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_news_1908_1909_pipeline_en_5.5.1_3.0_1738057405380.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_news_1908_1909_pipeline_en_5.5.1_3.0_1738057405380.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetuned_news_1908_1909_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_news_1908_1909_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetuned_news_1908_1909_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/sally9805/bert-base-uncased-finetuned-news-1908-1909
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_news_1933_1936_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_news_1933_1936_en.md
new file mode 100644
index 00000000000000..a9a0d4d791e698
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_news_1933_1936_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_uncased_finetuned_news_1933_1936 BertEmbeddings from sally9805
+author: John Snow Labs
+name: bert_base_uncased_finetuned_news_1933_1936
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_news_1933_1936` is a English model originally trained by sally9805.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_news_1933_1936_en_5.5.1_3.0_1738039824936.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_news_1933_1936_en_5.5.1_3.0_1738039824936.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_base_uncased_finetuned_news_1933_1936","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_base_uncased_finetuned_news_1933_1936","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetuned_news_1933_1936|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/sally9805/bert-base-uncased-finetuned-news-1933-1936
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_news_1933_1936_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_news_1933_1936_pipeline_en.md
new file mode 100644
index 00000000000000..c188158c6e78de
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_news_1933_1936_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_uncased_finetuned_news_1933_1936_pipeline pipeline BertEmbeddings from sally9805
+author: John Snow Labs
+name: bert_base_uncased_finetuned_news_1933_1936_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_news_1933_1936_pipeline` is a English model originally trained by sally9805.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_news_1933_1936_pipeline_en_5.5.1_3.0_1738039845088.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_news_1933_1936_pipeline_en_5.5.1_3.0_1738039845088.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetuned_news_1933_1936_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_news_1933_1936_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetuned_news_1933_1936_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/sally9805/bert-base-uncased-finetuned-news-1933-1936
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_news_1942_1956_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_news_1942_1956_en.md
new file mode 100644
index 00000000000000..1d3baf3554f0fe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_news_1942_1956_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_uncased_finetuned_news_1942_1956 BertEmbeddings from sally9805
+author: John Snow Labs
+name: bert_base_uncased_finetuned_news_1942_1956
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_news_1942_1956` is a English model originally trained by sally9805.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_news_1942_1956_en_5.5.1_3.0_1738039916081.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_news_1942_1956_en_5.5.1_3.0_1738039916081.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_base_uncased_finetuned_news_1942_1956","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_base_uncased_finetuned_news_1942_1956","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetuned_news_1942_1956|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/sally9805/bert-base-uncased-finetuned-news-1942-1956
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_news_1942_1956_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_news_1942_1956_pipeline_en.md
new file mode 100644
index 00000000000000..81c464ed5f486a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_news_1942_1956_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_uncased_finetuned_news_1942_1956_pipeline pipeline BertEmbeddings from sally9805
+author: John Snow Labs
+name: bert_base_uncased_finetuned_news_1942_1956_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_news_1942_1956_pipeline` is a English model originally trained by sally9805.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_news_1942_1956_pipeline_en_5.5.1_3.0_1738039936786.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_news_1942_1956_pipeline_en_5.5.1_3.0_1738039936786.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetuned_news_1942_1956_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_news_1942_1956_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetuned_news_1942_1956_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/sally9805/bert-base-uncased-finetuned-news-1942-1956
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_news_1962_1972_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_news_1962_1972_en.md
new file mode 100644
index 00000000000000..b7367a90dfee74
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_news_1962_1972_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_uncased_finetuned_news_1962_1972 BertEmbeddings from sally9805
+author: John Snow Labs
+name: bert_base_uncased_finetuned_news_1962_1972
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_news_1962_1972` is a English model originally trained by sally9805.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_news_1962_1972_en_5.5.1_3.0_1738039973150.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_news_1962_1972_en_5.5.1_3.0_1738039973150.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_base_uncased_finetuned_news_1962_1972","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_base_uncased_finetuned_news_1962_1972","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetuned_news_1962_1972|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/sally9805/bert-base-uncased-finetuned-news-1962-1972
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_news_1962_1972_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_news_1962_1972_pipeline_en.md
new file mode 100644
index 00000000000000..72ff4a67f30702
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_news_1962_1972_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_uncased_finetuned_news_1962_1972_pipeline pipeline BertEmbeddings from sally9805
+author: John Snow Labs
+name: bert_base_uncased_finetuned_news_1962_1972_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_news_1962_1972_pipeline` is a English model originally trained by sally9805.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_news_1962_1972_pipeline_en_5.5.1_3.0_1738039993618.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_news_1962_1972_pipeline_en_5.5.1_3.0_1738039993618.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetuned_news_1962_1972_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_news_1962_1972_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetuned_news_1962_1972_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/sally9805/bert-base-uncased-finetuned-news-1962-1972
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_news_1963_1965_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_news_1963_1965_en.md
new file mode 100644
index 00000000000000..0eefe4cd71d51a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_news_1963_1965_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_uncased_finetuned_news_1963_1965 BertEmbeddings from sally9805
+author: John Snow Labs
+name: bert_base_uncased_finetuned_news_1963_1965
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_news_1963_1965` is a English model originally trained by sally9805.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_news_1963_1965_en_5.5.1_3.0_1738039910513.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_news_1963_1965_en_5.5.1_3.0_1738039910513.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_base_uncased_finetuned_news_1963_1965","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_base_uncased_finetuned_news_1963_1965","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetuned_news_1963_1965|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/sally9805/bert-base-uncased-finetuned-news-1963-1965
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_news_1963_1965_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_news_1963_1965_pipeline_en.md
new file mode 100644
index 00000000000000..712dba8fbbacaa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_news_1963_1965_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_uncased_finetuned_news_1963_1965_pipeline pipeline BertEmbeddings from sally9805
+author: John Snow Labs
+name: bert_base_uncased_finetuned_news_1963_1965_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_news_1963_1965_pipeline` is a English model originally trained by sally9805.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_news_1963_1965_pipeline_en_5.5.1_3.0_1738039931197.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_news_1963_1965_pipeline_en_5.5.1_3.0_1738039931197.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetuned_news_1963_1965_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_news_1963_1965_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetuned_news_1963_1965_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/sally9805/bert-base-uncased-finetuned-news-1963-1965
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_news_1996_1999_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_news_1996_1999_en.md
new file mode 100644
index 00000000000000..df80fcd48480a6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_news_1996_1999_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_uncased_finetuned_news_1996_1999 BertEmbeddings from sally9805
+author: John Snow Labs
+name: bert_base_uncased_finetuned_news_1996_1999
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_news_1996_1999` is a English model originally trained by sally9805.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_news_1996_1999_en_5.5.1_3.0_1738058245929.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_news_1996_1999_en_5.5.1_3.0_1738058245929.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_base_uncased_finetuned_news_1996_1999","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_base_uncased_finetuned_news_1996_1999","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetuned_news_1996_1999|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/sally9805/bert-base-uncased-finetuned-news-1996-1999
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_news_1996_1999_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_news_1996_1999_pipeline_en.md
new file mode 100644
index 00000000000000..d8a767916c7986
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_news_1996_1999_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_uncased_finetuned_news_1996_1999_pipeline pipeline BertEmbeddings from sally9805
+author: John Snow Labs
+name: bert_base_uncased_finetuned_news_1996_1999_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_news_1996_1999_pipeline` is a English model originally trained by sally9805.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_news_1996_1999_pipeline_en_5.5.1_3.0_1738058266427.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_news_1996_1999_pipeline_en_5.5.1_3.0_1738058266427.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetuned_news_1996_1999_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_news_1996_1999_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetuned_news_1996_1999_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/sally9805/bert-base-uncased-finetuned-news-1996-1999
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_news_2000_2004_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_news_2000_2004_en.md
new file mode 100644
index 00000000000000..d1e9e421ff518c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_news_2000_2004_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_uncased_finetuned_news_2000_2004 BertEmbeddings from sally9805
+author: John Snow Labs
+name: bert_base_uncased_finetuned_news_2000_2004
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_news_2000_2004` is a English model originally trained by sally9805.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_news_2000_2004_en_5.5.1_3.0_1738057645815.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_news_2000_2004_en_5.5.1_3.0_1738057645815.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_base_uncased_finetuned_news_2000_2004","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_base_uncased_finetuned_news_2000_2004","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetuned_news_2000_2004|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/sally9805/bert-base-uncased-finetuned-news-2000-2004
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_news_2000_2004_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_news_2000_2004_pipeline_en.md
new file mode 100644
index 00000000000000..5d433c97f5ed8d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_news_2000_2004_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_uncased_finetuned_news_2000_2004_pipeline pipeline BertEmbeddings from sally9805
+author: John Snow Labs
+name: bert_base_uncased_finetuned_news_2000_2004_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_news_2000_2004_pipeline` is a English model originally trained by sally9805.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_news_2000_2004_pipeline_en_5.5.1_3.0_1738057666144.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_news_2000_2004_pipeline_en_5.5.1_3.0_1738057666144.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetuned_news_2000_2004_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_news_2000_2004_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetuned_news_2000_2004_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/sally9805/bert-base-uncased-finetuned-news-2000-2004
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_squad_meghanaanil_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_squad_meghanaanil_en.md
new file mode 100644
index 00000000000000..8689af4eea82ea
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_squad_meghanaanil_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_base_uncased_finetuned_squad_meghanaanil BertForQuestionAnswering from meghanaanil
+author: John Snow Labs
+name: bert_base_uncased_finetuned_squad_meghanaanil
+date: 2025-01-28
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_squad_meghanaanil` is a English model originally trained by meghanaanil.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_squad_meghanaanil_en_5.5.1_3.0_1738061622794.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_squad_meghanaanil_en_5.5.1_3.0_1738061622794.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetuned_squad_meghanaanil","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetuned_squad_meghanaanil", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetuned_squad_meghanaanil|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/meghanaanil/bert-base-uncased-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_squad_meghanaanil_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_squad_meghanaanil_pipeline_en.md
new file mode 100644
index 00000000000000..9659a04139e090
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_finetuned_squad_meghanaanil_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_base_uncased_finetuned_squad_meghanaanil_pipeline pipeline BertForQuestionAnswering from meghanaanil
+author: John Snow Labs
+name: bert_base_uncased_finetuned_squad_meghanaanil_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_squad_meghanaanil_pipeline` is a English model originally trained by meghanaanil.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_squad_meghanaanil_pipeline_en_5.5.1_3.0_1738061643538.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_squad_meghanaanil_pipeline_en_5.5.1_3.0_1738061643538.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetuned_squad_meghanaanil_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_squad_meghanaanil_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetuned_squad_meghanaanil_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/meghanaanil/bert-base-uncased-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_issues_128_vantaa32_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_issues_128_vantaa32_en.md
new file mode 100644
index 00000000000000..7d606f7834b8f4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_issues_128_vantaa32_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_uncased_issues_128_vantaa32 BertEmbeddings from vantaa32
+author: John Snow Labs
+name: bert_base_uncased_issues_128_vantaa32
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_issues_128_vantaa32` is a English model originally trained by vantaa32.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_issues_128_vantaa32_en_5.5.1_3.0_1738084614641.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_issues_128_vantaa32_en_5.5.1_3.0_1738084614641.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_base_uncased_issues_128_vantaa32","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_base_uncased_issues_128_vantaa32","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_issues_128_vantaa32|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/vantaa32/bert-base-uncased-issues-128
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_issues_128_vantaa32_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_issues_128_vantaa32_pipeline_en.md
new file mode 100644
index 00000000000000..8900d9d37a81b7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_issues_128_vantaa32_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_uncased_issues_128_vantaa32_pipeline pipeline BertEmbeddings from vantaa32
+author: John Snow Labs
+name: bert_base_uncased_issues_128_vantaa32_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_issues_128_vantaa32_pipeline` is a English model originally trained by vantaa32.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_issues_128_vantaa32_pipeline_en_5.5.1_3.0_1738084635473.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_issues_128_vantaa32_pipeline_en_5.5.1_3.0_1738084635473.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_issues_128_vantaa32_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_issues_128_vantaa32_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_issues_128_vantaa32_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/vantaa32/bert-base-uncased-issues-128
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_issues_128_zzeal_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_issues_128_zzeal_en.md
new file mode 100644
index 00000000000000..b2e00eb5a70162
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_issues_128_zzeal_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_uncased_issues_128_zzeal BertEmbeddings from ZZeal
+author: John Snow Labs
+name: bert_base_uncased_issues_128_zzeal
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_issues_128_zzeal` is a English model originally trained by ZZeal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_issues_128_zzeal_en_5.5.1_3.0_1738098601224.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_issues_128_zzeal_en_5.5.1_3.0_1738098601224.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_base_uncased_issues_128_zzeal","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_base_uncased_issues_128_zzeal","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_issues_128_zzeal|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/ZZeal/bert-base-uncased-issues-128
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_issues_128_zzeal_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_issues_128_zzeal_pipeline_en.md
new file mode 100644
index 00000000000000..f3d424fa051711
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_issues_128_zzeal_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_uncased_issues_128_zzeal_pipeline pipeline BertEmbeddings from ZZeal
+author: John Snow Labs
+name: bert_base_uncased_issues_128_zzeal_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_issues_128_zzeal_pipeline` is a English model originally trained by ZZeal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_issues_128_zzeal_pipeline_en_5.5.1_3.0_1738098621917.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_issues_128_zzeal_pipeline_en_5.5.1_3.0_1738098621917.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_issues_128_zzeal_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_issues_128_zzeal_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_issues_128_zzeal_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/ZZeal/bert-base-uncased-issues-128
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_mlm_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_mlm_en.md
new file mode 100644
index 00000000000000..dba4a9e6e829c0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_mlm_en.md
@@ -0,0 +1,92 @@
+---
+layout: model
+title: English bert_base_uncased_mlm BertEmbeddings from wypoon
+author: John Snow Labs
+name: bert_base_uncased_mlm
+date: 2025-01-28
+tags: [bert, en, open_source, fill_mask, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings  model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_mlm` is a English model originally trained by wypoon.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_mlm_en_5.5.1_3.0_1738098276064.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_mlm_en_5.5.1_3.0_1738098276064.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("documents")
+    
+    
+embeddings =BertEmbeddings.pretrained("bert_base_uncased_mlm","en") \
+            .setInputCols(["documents","token"]) \
+            .setOutputCol("embeddings")
+
+pipeline = Pipeline().setStages([document_assembler, embeddings])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val document_assembler = new DocumentAssembler()
+    .setInputCol("text") 
+    .setOutputCol("embeddings")
+    
+val embeddings = BertEmbeddings 
+    .pretrained("bert_base_uncased_mlm", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("embeddings") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_mlm|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+References
+
+https://huggingface.co/wypoon/bert-base-uncased-mlm
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_mlm_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_mlm_pipeline_en.md
new file mode 100644
index 00000000000000..3bf025f3a91e86
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_mlm_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_uncased_mlm_pipeline pipeline BertEmbeddings from vtexas
+author: John Snow Labs
+name: bert_base_uncased_mlm_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_mlm_pipeline` is a English model originally trained by vtexas.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_mlm_pipeline_en_5.5.1_3.0_1738098295589.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_mlm_pipeline_en_5.5.1_3.0_1738098295589.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_mlm_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_mlm_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_mlm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/vtexas/bert-base-uncased-mlm
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_pal4_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_pal4_en.md
new file mode 100644
index 00000000000000..055926d11b68fa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_pal4_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_uncased_pal4 BertEmbeddings from anthony-lemurian
+author: John Snow Labs
+name: bert_base_uncased_pal4
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_pal4` is a English model originally trained by anthony-lemurian.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_pal4_en_5.5.1_3.0_1738035332507.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_pal4_en_5.5.1_3.0_1738035332507.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_base_uncased_pal4","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_base_uncased_pal4","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_pal4|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|332.7 MB|
+
+## References
+
+https://huggingface.co/anthony-lemurian/bert-base-uncased-pal4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_pal4_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_pal4_pipeline_en.md
new file mode 100644
index 00000000000000..83be1a32179f58
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_base_uncased_pal4_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_uncased_pal4_pipeline pipeline BertEmbeddings from anthony-lemurian
+author: John Snow Labs
+name: bert_base_uncased_pal4_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_pal4_pipeline` is a English model originally trained by anthony-lemurian.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_pal4_pipeline_en_5.5.1_3.0_1738035355394.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_pal4_pipeline_en_5.5.1_3.0_1738035355394.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_pal4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_pal4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_pal4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|332.7 MB|
+
+## References
+
+https://huggingface.co/anthony-lemurian/bert-base-uncased-pal4
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_cased_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_cased_en.md
new file mode 100644
index 00000000000000..89098ad3498b19
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_cased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_cased BertEmbeddings from wilsonmarciliojr
+author: John Snow Labs
+name: bert_cased
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_cased` is a English model originally trained by wilsonmarciliojr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_cased_en_5.5.1_3.0_1738034944476.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_cased_en_5.5.1_3.0_1738034944476.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_cased","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_cased","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_cased|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/wilsonmarciliojr/bert-cased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_cased_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_cased_pipeline_en.md
new file mode 100644
index 00000000000000..f32e33a256ee4f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_cased_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_cased_pipeline pipeline BertEmbeddings from wilsonmarciliojr
+author: John Snow Labs
+name: bert_cased_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_cased_pipeline` is a English model originally trained by wilsonmarciliojr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_cased_pipeline_en_5.5.1_3.0_1738034964399.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_cased_pipeline_en_5.5.1_3.0_1738034964399.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_cased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_cased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_cased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/wilsonmarciliojr/bert-cased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_cefr_model2_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_cefr_model2_en.md
new file mode 100644
index 00000000000000..958fef38d01647
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_cefr_model2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_cefr_model2 BertForSequenceClassification from kalobiralo
+author: John Snow Labs
+name: bert_cefr_model2
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_cefr_model2` is a English model originally trained by kalobiralo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_cefr_model2_en_5.5.1_3.0_1738100964906.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_cefr_model2_en_5.5.1_3.0_1738100964906.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("bert_cefr_model2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("bert_cefr_model2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_cefr_model2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/kalobiralo/bert_cefr_model2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_cefr_model2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_cefr_model2_pipeline_en.md
new file mode 100644
index 00000000000000..9d5f48f6d7fff2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_cefr_model2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_cefr_model2_pipeline pipeline BertForSequenceClassification from kalobiralo
+author: John Snow Labs
+name: bert_cefr_model2_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_cefr_model2_pipeline` is a English model originally trained by kalobiralo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_cefr_model2_pipeline_en_5.5.1_3.0_1738100985434.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_cefr_model2_pipeline_en_5.5.1_3.0_1738100985434.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_cefr_model2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_cefr_model2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_cefr_model2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/kalobiralo/bert_cefr_model2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_culturax_data_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_culturax_data_en.md
new file mode 100644
index 00000000000000..eda62371514240
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_culturax_data_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_culturax_data BertEmbeddings from Something2109
+author: John Snow Labs
+name: bert_culturax_data
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_culturax_data` is a English model originally trained by Something2109.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_culturax_data_en_5.5.1_3.0_1738096776316.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_culturax_data_en_5.5.1_3.0_1738096776316.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_culturax_data","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_culturax_data","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_culturax_data|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|412.5 MB|
+
+## References
+
+https://huggingface.co/Something2109/bert-culturaX-data
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_culturax_data_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_culturax_data_pipeline_en.md
new file mode 100644
index 00000000000000..e4c66096fbdeae
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_culturax_data_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_culturax_data_pipeline pipeline BertEmbeddings from Something2109
+author: John Snow Labs
+name: bert_culturax_data_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_culturax_data_pipeline` is a English model originally trained by Something2109.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_culturax_data_pipeline_en_5.5.1_3.0_1738096800422.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_culturax_data_pipeline_en_5.5.1_3.0_1738096800422.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_culturax_data_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_culturax_data_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_culturax_data_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|412.6 MB|
+
+## References
+
+https://huggingface.co/Something2109/bert-culturaX-data
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned3_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned3_en.md
new file mode 100644
index 00000000000000..6026cb469d5250
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_finetuned3 BertEmbeddings from Vashesh
+author: John Snow Labs
+name: bert_finetuned3
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned3` is a English model originally trained by Vashesh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned3_en_5.5.1_3.0_1738057263280.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned3_en_5.5.1_3.0_1738057263280.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_finetuned3","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_finetuned3","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned3|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/Vashesh/Bert_Finetuned3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned3_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned3_pipeline_en.md
new file mode 100644
index 00000000000000..90d99bc744f82f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned3_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_finetuned3_pipeline pipeline BertEmbeddings from Vashesh
+author: John Snow Labs
+name: bert_finetuned3_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned3_pipeline` is a English model originally trained by Vashesh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned3_pipeline_en_5.5.1_3.0_1738057284474.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned3_pipeline_en_5.5.1_3.0_1738057284474.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/Vashesh/Bert_Finetuned3
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_conditional_sentence_parser_negative_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_conditional_sentence_parser_negative_en.md
new file mode 100644
index 00000000000000..9f5be02773a7e0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_conditional_sentence_parser_negative_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_finetuned_conditional_sentence_parser_negative BertForTokenClassification from ddbejarano
+author: John Snow Labs
+name: bert_finetuned_conditional_sentence_parser_negative
+date: 2025-01-28
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_conditional_sentence_parser_negative` is a English model originally trained by ddbejarano.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_conditional_sentence_parser_negative_en_5.5.1_3.0_1738045098743.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_conditional_sentence_parser_negative_en_5.5.1_3.0_1738045098743.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_finetuned_conditional_sentence_parser_negative","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_conditional_sentence_parser_negative", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_conditional_sentence_parser_negative|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/ddbejarano/bert-finetuned-conditional-sentence-parser-NEGATIVE
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_conditional_sentence_parser_negative_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_conditional_sentence_parser_negative_pipeline_en.md
new file mode 100644
index 00000000000000..7086d666e5bd13
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_conditional_sentence_parser_negative_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_finetuned_conditional_sentence_parser_negative_pipeline pipeline BertForTokenClassification from ddbejarano
+author: John Snow Labs
+name: bert_finetuned_conditional_sentence_parser_negative_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_conditional_sentence_parser_negative_pipeline` is a English model originally trained by ddbejarano.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_conditional_sentence_parser_negative_pipeline_en_5.5.1_3.0_1738045119423.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_conditional_sentence_parser_negative_pipeline_en_5.5.1_3.0_1738045119423.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_conditional_sentence_parser_negative_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_conditional_sentence_parser_negative_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_conditional_sentence_parser_negative_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/ddbejarano/bert-finetuned-conditional-sentence-parser-NEGATIVE
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_imdb_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_imdb_en.md
new file mode 100644
index 00000000000000..94a8be7207f351
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_imdb_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_finetuned_imdb RoBertaEmbeddings from hanyuany14
+author: John Snow Labs
+name: bert_finetuned_imdb
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_imdb` is a English model originally trained by hanyuany14.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_imdb_en_5.5.1_3.0_1738102651539.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_imdb_en_5.5.1_3.0_1738102651539.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("bert_finetuned_imdb","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("bert_finetuned_imdb","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_imdb|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/hanyuany14/bert-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_imdb_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_imdb_pipeline_en.md
new file mode 100644
index 00000000000000..2625b3c2aa2370
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_imdb_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_finetuned_imdb_pipeline pipeline RoBertaEmbeddings from hanyuany14
+author: John Snow Labs
+name: bert_finetuned_imdb_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_imdb_pipeline` is a English model originally trained by hanyuany14.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_imdb_pipeline_en_5.5.1_3.0_1738102667097.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_imdb_pipeline_en_5.5.1_3.0_1738102667097.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_imdb_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_imdb_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_imdb_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/hanyuany14/bert-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_ner_2_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_ner_2_en.md
new file mode 100644
index 00000000000000..0ffc7b1b704ace
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_ner_2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_finetuned_ner_2 BertForTokenClassification from danstinga
+author: John Snow Labs
+name: bert_finetuned_ner_2
+date: 2025-01-28
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_2` is a English model originally trained by danstinga.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_2_en_5.5.1_3.0_1738044861144.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_2_en_5.5.1_3.0_1738044861144.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_finetuned_ner_2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner_2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/danstinga/bert-finetuned-ner-2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_ner_2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_ner_2_pipeline_en.md
new file mode 100644
index 00000000000000..423edd505b4cf4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_ner_2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_finetuned_ner_2_pipeline pipeline BertForTokenClassification from danstinga
+author: John Snow Labs
+name: bert_finetuned_ner_2_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_2_pipeline` is a English model originally trained by danstinga.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_2_pipeline_en_5.5.1_3.0_1738044881518.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_2_pipeline_en_5.5.1_3.0_1738044881518.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_ner_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_ner_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/danstinga/bert-finetuned-ner-2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_ner_augment_7_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_ner_augment_7_en.md
new file mode 100644
index 00000000000000..867ba2b5a6260b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_ner_augment_7_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_finetuned_ner_augment_7 BertForTokenClassification from lamthanhtin2811
+author: John Snow Labs
+name: bert_finetuned_ner_augment_7
+date: 2025-01-28
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_augment_7` is a English model originally trained by lamthanhtin2811.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_augment_7_en_5.5.1_3.0_1738044811416.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_augment_7_en_5.5.1_3.0_1738044811416.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_finetuned_ner_augment_7","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner_augment_7", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_augment_7|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/lamthanhtin2811/bert_finetuned-ner-augment-7
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_ner_augment_7_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_ner_augment_7_pipeline_en.md
new file mode 100644
index 00000000000000..827bbf55aa23e5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_ner_augment_7_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_finetuned_ner_augment_7_pipeline pipeline BertForTokenClassification from lamthanhtin2811
+author: John Snow Labs
+name: bert_finetuned_ner_augment_7_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_augment_7_pipeline` is a English model originally trained by lamthanhtin2811.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_augment_7_pipeline_en_5.5.1_3.0_1738044831991.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_augment_7_pipeline_en_5.5.1_3.0_1738044831991.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_ner_augment_7_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_ner_augment_7_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_augment_7_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/lamthanhtin2811/bert_finetuned-ner-augment-7
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_squad_bampam_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_squad_bampam_en.md
new file mode 100644
index 00000000000000..3a0ae1eeff73e1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_squad_bampam_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_finetuned_squad_bampam BertForQuestionAnswering from bampam
+author: John Snow Labs
+name: bert_finetuned_squad_bampam
+date: 2025-01-28
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_bampam` is a English model originally trained by bampam.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_bampam_en_5.5.1_3.0_1738061940210.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_bampam_en_5.5.1_3.0_1738061940210.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_bampam","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_bampam", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_bampam|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/bampam/bert-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_squad_bampam_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_squad_bampam_pipeline_en.md
new file mode 100644
index 00000000000000..d1cd8cc5267bc1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_squad_bampam_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_finetuned_squad_bampam_pipeline pipeline BertForQuestionAnswering from bampam
+author: John Snow Labs
+name: bert_finetuned_squad_bampam_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_bampam_pipeline` is a English model originally trained by bampam.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_bampam_pipeline_en_5.5.1_3.0_1738061960499.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_bampam_pipeline_en_5.5.1_3.0_1738061960499.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_squad_bampam_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_squad_bampam_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_bampam_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/bampam/bert-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_squad_ereverter_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_squad_ereverter_en.md
new file mode 100644
index 00000000000000..18b2c97050f552
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_squad_ereverter_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_finetuned_squad_ereverter BertForQuestionAnswering from eReverter
+author: John Snow Labs
+name: bert_finetuned_squad_ereverter
+date: 2025-01-28
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_ereverter` is a English model originally trained by eReverter.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_ereverter_en_5.5.1_3.0_1738061500718.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_ereverter_en_5.5.1_3.0_1738061500718.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_ereverter","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_ereverter", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_ereverter|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/eReverter/bert-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_squad_ereverter_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_squad_ereverter_pipeline_en.md
new file mode 100644
index 00000000000000..e3dee6d4e622b6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_squad_ereverter_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_finetuned_squad_ereverter_pipeline pipeline BertForQuestionAnswering from eReverter
+author: John Snow Labs
+name: bert_finetuned_squad_ereverter_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_ereverter_pipeline` is a English model originally trained by eReverter.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_ereverter_pipeline_en_5.5.1_3.0_1738061523113.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_ereverter_pipeline_en_5.5.1_3.0_1738061523113.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_squad_ereverter_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_squad_ereverter_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_ereverter_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/eReverter/bert-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_squad_fadliaulawi_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_squad_fadliaulawi_en.md
new file mode 100644
index 00000000000000..e1dcc9fd7f97ca
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_squad_fadliaulawi_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_finetuned_squad_fadliaulawi BertForQuestionAnswering from fadliaulawi
+author: John Snow Labs
+name: bert_finetuned_squad_fadliaulawi
+date: 2025-01-28
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_fadliaulawi` is a English model originally trained by fadliaulawi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_fadliaulawi_en_5.5.1_3.0_1738062110455.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_fadliaulawi_en_5.5.1_3.0_1738062110455.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_fadliaulawi","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_fadliaulawi", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_fadliaulawi|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/fadliaulawi/bert-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_squad_fadliaulawi_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_squad_fadliaulawi_pipeline_en.md
new file mode 100644
index 00000000000000..a43f1bf30c1b93
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_squad_fadliaulawi_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_finetuned_squad_fadliaulawi_pipeline pipeline BertForQuestionAnswering from fadliaulawi
+author: John Snow Labs
+name: bert_finetuned_squad_fadliaulawi_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_fadliaulawi_pipeline` is a English model originally trained by fadliaulawi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_fadliaulawi_pipeline_en_5.5.1_3.0_1738062130936.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_fadliaulawi_pipeline_en_5.5.1_3.0_1738062130936.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_squad_fadliaulawi_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_squad_fadliaulawi_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_fadliaulawi_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/fadliaulawi/bert-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_squad_hitrozhopiy_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_squad_hitrozhopiy_en.md
new file mode 100644
index 00000000000000..db18088739aefd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_squad_hitrozhopiy_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_finetuned_squad_hitrozhopiy BertForQuestionAnswering from hitrozhopiy
+author: John Snow Labs
+name: bert_finetuned_squad_hitrozhopiy
+date: 2025-01-28
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_hitrozhopiy` is a English model originally trained by hitrozhopiy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_hitrozhopiy_en_5.5.1_3.0_1738061821495.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_hitrozhopiy_en_5.5.1_3.0_1738061821495.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_hitrozhopiy","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_hitrozhopiy", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_hitrozhopiy|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/hitrozhopiy/bert-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_squad_hitrozhopiy_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_squad_hitrozhopiy_pipeline_en.md
new file mode 100644
index 00000000000000..2327cafe77cbbc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_squad_hitrozhopiy_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_finetuned_squad_hitrozhopiy_pipeline pipeline BertForQuestionAnswering from hitrozhopiy
+author: John Snow Labs
+name: bert_finetuned_squad_hitrozhopiy_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_hitrozhopiy_pipeline` is a English model originally trained by hitrozhopiy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_hitrozhopiy_pipeline_en_5.5.1_3.0_1738061841906.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_hitrozhopiy_pipeline_en_5.5.1_3.0_1738061841906.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_squad_hitrozhopiy_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_squad_hitrozhopiy_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_hitrozhopiy_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/hitrozhopiy/bert-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_squad_jakobkruse_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_squad_jakobkruse_en.md
new file mode 100644
index 00000000000000..10403538a3226a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_squad_jakobkruse_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_finetuned_squad_jakobkruse BertForQuestionAnswering from jakobkruse
+author: John Snow Labs
+name: bert_finetuned_squad_jakobkruse
+date: 2025-01-28
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_jakobkruse` is a English model originally trained by jakobkruse.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_jakobkruse_en_5.5.1_3.0_1738062303435.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_jakobkruse_en_5.5.1_3.0_1738062303435.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_jakobkruse","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_jakobkruse", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_jakobkruse|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/jakobkruse/bert-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_squad_jakobkruse_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_squad_jakobkruse_pipeline_en.md
new file mode 100644
index 00000000000000..8bb00e414345af
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_squad_jakobkruse_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_finetuned_squad_jakobkruse_pipeline pipeline BertForQuestionAnswering from jakobkruse
+author: John Snow Labs
+name: bert_finetuned_squad_jakobkruse_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_jakobkruse_pipeline` is a English model originally trained by jakobkruse.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_jakobkruse_pipeline_en_5.5.1_3.0_1738062323808.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_jakobkruse_pipeline_en_5.5.1_3.0_1738062323808.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_squad_jakobkruse_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_squad_jakobkruse_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_jakobkruse_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/jakobkruse/bert-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_squad_rahul13_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_squad_rahul13_en.md
new file mode 100644
index 00000000000000..8436ec38ffb1d1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_squad_rahul13_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_finetuned_squad_rahul13 BertForQuestionAnswering from Rahul13
+author: John Snow Labs
+name: bert_finetuned_squad_rahul13
+date: 2025-01-28
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_rahul13` is a English model originally trained by Rahul13.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_rahul13_en_5.5.1_3.0_1738062225480.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_rahul13_en_5.5.1_3.0_1738062225480.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_rahul13","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_rahul13", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_rahul13|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/Rahul13/bert-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_squad_rahul13_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_squad_rahul13_pipeline_en.md
new file mode 100644
index 00000000000000..bd9272183d1e38
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_squad_rahul13_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_finetuned_squad_rahul13_pipeline pipeline BertForQuestionAnswering from Rahul13
+author: John Snow Labs
+name: bert_finetuned_squad_rahul13_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_rahul13_pipeline` is a English model originally trained by Rahul13.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_rahul13_pipeline_en_5.5.1_3.0_1738062251500.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_rahul13_pipeline_en_5.5.1_3.0_1738062251500.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_squad_rahul13_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_squad_rahul13_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_rahul13_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/Rahul13/bert-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_squad_tilnoene_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_squad_tilnoene_en.md
new file mode 100644
index 00000000000000..5dc817322a1162
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_squad_tilnoene_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_finetuned_squad_tilnoene BertForQuestionAnswering from tilnoene
+author: John Snow Labs
+name: bert_finetuned_squad_tilnoene
+date: 2025-01-28
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_tilnoene` is a English model originally trained by tilnoene.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_tilnoene_en_5.5.1_3.0_1738061853042.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_tilnoene_en_5.5.1_3.0_1738061853042.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_tilnoene","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_tilnoene", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_tilnoene|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/tilnoene/bert-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_squad_tilnoene_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_squad_tilnoene_pipeline_en.md
new file mode 100644
index 00000000000000..d5610a322d393d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_finetuned_squad_tilnoene_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_finetuned_squad_tilnoene_pipeline pipeline BertForQuestionAnswering from tilnoene
+author: John Snow Labs
+name: bert_finetuned_squad_tilnoene_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_tilnoene_pipeline` is a English model originally trained by tilnoene.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_tilnoene_pipeline_en_5.5.1_3.0_1738061873795.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_tilnoene_pipeline_en_5.5.1_3.0_1738061873795.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_squad_tilnoene_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_squad_tilnoene_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_tilnoene_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/tilnoene/bert-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_l12_h512_uncased_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_l12_h512_uncased_en.md
new file mode 100644
index 00000000000000..99f54ef25e66f9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_l12_h512_uncased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_l12_h512_uncased BertEmbeddings from gaunernst
+author: John Snow Labs
+name: bert_l12_h512_uncased
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_l12_h512_uncased` is a English model originally trained by gaunernst.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_l12_h512_uncased_en_5.5.1_3.0_1738039780862.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_l12_h512_uncased_en_5.5.1_3.0_1738039780862.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_l12_h512_uncased","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_l12_h512_uncased","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_l12_h512_uncased|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|201.4 MB|
+
+## References
+
+https://huggingface.co/gaunernst/bert-L12-H512-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_l12_h512_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_l12_h512_uncased_pipeline_en.md
new file mode 100644
index 00000000000000..888dbaa8398916
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_l12_h512_uncased_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_l12_h512_uncased_pipeline pipeline BertEmbeddings from gaunernst
+author: John Snow Labs
+name: bert_l12_h512_uncased_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_l12_h512_uncased_pipeline` is a English model originally trained by gaunernst.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_l12_h512_uncased_pipeline_en_5.5.1_3.0_1738039790964.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_l12_h512_uncased_pipeline_en_5.5.1_3.0_1738039790964.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_l12_h512_uncased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_l12_h512_uncased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_l12_h512_uncased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|201.5 MB|
+
+## References
+
+https://huggingface.co/gaunernst/bert-L12-H512-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_l4_h768_uncased_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_l4_h768_uncased_en.md
new file mode 100644
index 00000000000000..53b6b283a3072d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_l4_h768_uncased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_l4_h768_uncased BertEmbeddings from gaunernst
+author: John Snow Labs
+name: bert_l4_h768_uncased
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_l4_h768_uncased` is a English model originally trained by gaunernst.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_l4_h768_uncased_en_5.5.1_3.0_1738084815118.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_l4_h768_uncased_en_5.5.1_3.0_1738084815118.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_l4_h768_uncased","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_l4_h768_uncased","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_l4_h768_uncased|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|195.1 MB|
+
+## References
+
+https://huggingface.co/gaunernst/bert-L4-H768-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_l4_h768_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_l4_h768_uncased_pipeline_en.md
new file mode 100644
index 00000000000000..db72d09af5051c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_l4_h768_uncased_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_l4_h768_uncased_pipeline pipeline BertEmbeddings from gaunernst
+author: John Snow Labs
+name: bert_l4_h768_uncased_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_l4_h768_uncased_pipeline` is a English model originally trained by gaunernst.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_l4_h768_uncased_pipeline_en_5.5.1_3.0_1738084825235.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_l4_h768_uncased_pipeline_en_5.5.1_3.0_1738084825235.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_l4_h768_uncased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_l4_h768_uncased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_l4_h768_uncased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|195.1 MB|
+
+## References
+
+https://huggingface.co/gaunernst/bert-L4-H768-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_l6_h512_uncased_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_l6_h512_uncased_en.md
new file mode 100644
index 00000000000000..ae636b67b8b56d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_l6_h512_uncased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_l6_h512_uncased BertEmbeddings from gaunernst
+author: John Snow Labs
+name: bert_l6_h512_uncased
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_l6_h512_uncased` is a English model originally trained by gaunernst.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_l6_h512_uncased_en_5.5.1_3.0_1738096630341.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_l6_h512_uncased_en_5.5.1_3.0_1738096630341.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_l6_h512_uncased","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_l6_h512_uncased","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_l6_h512_uncased|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|130.6 MB|
+
+## References
+
+https://huggingface.co/gaunernst/bert-L6-H512-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_l6_h512_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_l6_h512_uncased_pipeline_en.md
new file mode 100644
index 00000000000000..3fb6df255fdabb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_l6_h512_uncased_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_l6_h512_uncased_pipeline pipeline BertEmbeddings from gaunernst
+author: John Snow Labs
+name: bert_l6_h512_uncased_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_l6_h512_uncased_pipeline` is a English model originally trained by gaunernst.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_l6_h512_uncased_pipeline_en_5.5.1_3.0_1738096636507.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_l6_h512_uncased_pipeline_en_5.5.1_3.0_1738096636507.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_l6_h512_uncased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_l6_h512_uncased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_l6_h512_uncased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|130.6 MB|
+
+## References
+
+https://huggingface.co/gaunernst/bert-L6-H512-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_l8_h256_uncased_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_l8_h256_uncased_en.md
new file mode 100644
index 00000000000000..cc3d48b86ac64e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_l8_h256_uncased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_l8_h256_uncased BertEmbeddings from gaunernst
+author: John Snow Labs
+name: bert_l8_h256_uncased
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_l8_h256_uncased` is a English model originally trained by gaunernst.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_l8_h256_uncased_en_5.5.1_3.0_1738096713481.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_l8_h256_uncased_en_5.5.1_3.0_1738096713481.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_l8_h256_uncased","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_l8_h256_uncased","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_l8_h256_uncased|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|53.7 MB|
+
+## References
+
+https://huggingface.co/gaunernst/bert-L8-H256-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_l8_h256_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_l8_h256_uncased_pipeline_en.md
new file mode 100644
index 00000000000000..6dc2797c35bdec
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_l8_h256_uncased_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_l8_h256_uncased_pipeline pipeline BertEmbeddings from gaunernst
+author: John Snow Labs
+name: bert_l8_h256_uncased_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_l8_h256_uncased_pipeline` is a English model originally trained by gaunernst.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_l8_h256_uncased_pipeline_en_5.5.1_3.0_1738096716130.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_l8_h256_uncased_pipeline_en_5.5.1_3.0_1738096716130.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_l8_h256_uncased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_l8_h256_uncased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_l8_h256_uncased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|53.7 MB|
+
+## References
+
+https://huggingface.co/gaunernst/bert-L8-H256-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_l8_h768_uncased_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_l8_h768_uncased_en.md
new file mode 100644
index 00000000000000..9787dc951ced47
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_l8_h768_uncased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_l8_h768_uncased BertEmbeddings from gaunernst
+author: John Snow Labs
+name: bert_l8_h768_uncased
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_l8_h768_uncased` is a English model originally trained by gaunernst.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_l8_h768_uncased_en_5.5.1_3.0_1738039937808.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_l8_h768_uncased_en_5.5.1_3.0_1738039937808.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_l8_h768_uncased","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_l8_h768_uncased","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_l8_h768_uncased|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|301.2 MB|
+
+## References
+
+https://huggingface.co/gaunernst/bert-L8-H768-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_l8_h768_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_l8_h768_uncased_pipeline_en.md
new file mode 100644
index 00000000000000..66078bd4ca6853
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_l8_h768_uncased_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_l8_h768_uncased_pipeline pipeline BertEmbeddings from gaunernst
+author: John Snow Labs
+name: bert_l8_h768_uncased_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_l8_h768_uncased_pipeline` is a English model originally trained by gaunernst.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_l8_h768_uncased_pipeline_en_5.5.1_3.0_1738039957684.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_l8_h768_uncased_pipeline_en_5.5.1_3.0_1738039957684.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_l8_h768_uncased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_l8_h768_uncased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_l8_h768_uncased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|301.3 MB|
+
+## References
+
+https://huggingface.co/gaunernst/bert-L8-H768-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_large_cased_sclarge_squad_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_large_cased_sclarge_squad_en.md
new file mode 100644
index 00000000000000..b41771e740a8fc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_large_cased_sclarge_squad_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_large_cased_sclarge_squad BertForQuestionAnswering from CambridgeMolecularEngineering
+author: John Snow Labs
+name: bert_large_cased_sclarge_squad
+date: 2025-01-28
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_cased_sclarge_squad` is a English model originally trained by CambridgeMolecularEngineering.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_cased_sclarge_squad_en_5.5.1_3.0_1738061996809.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_cased_sclarge_squad_en_5.5.1_3.0_1738061996809.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("bert_large_cased_sclarge_squad","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("bert_large_cased_sclarge_squad", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_large_cased_sclarge_squad|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/CambridgeMolecularEngineering/bert-large-cased-sclarge-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_large_cased_sclarge_squad_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_large_cased_sclarge_squad_pipeline_en.md
new file mode 100644
index 00000000000000..4b99639fb2d144
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_large_cased_sclarge_squad_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_large_cased_sclarge_squad_pipeline pipeline BertForQuestionAnswering from CambridgeMolecularEngineering
+author: John Snow Labs
+name: bert_large_cased_sclarge_squad_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_cased_sclarge_squad_pipeline` is a English model originally trained by CambridgeMolecularEngineering.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_cased_sclarge_squad_pipeline_en_5.5.1_3.0_1738062058322.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_cased_sclarge_squad_pipeline_en_5.5.1_3.0_1738062058322.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_large_cased_sclarge_squad_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_large_cased_sclarge_squad_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_large_cased_sclarge_squad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/CambridgeMolecularEngineering/bert-large-cased-sclarge-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_mlm_imdb_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_mlm_imdb_en.md
new file mode 100644
index 00000000000000..404aac53fe00df
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_mlm_imdb_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_mlm_imdb BertEmbeddings from AirrStorm
+author: John Snow Labs
+name: bert_mlm_imdb
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_mlm_imdb` is a English model originally trained by AirrStorm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_mlm_imdb_en_5.5.1_3.0_1738096929274.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_mlm_imdb_en_5.5.1_3.0_1738096929274.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_mlm_imdb","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_mlm_imdb","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_mlm_imdb|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/AirrStorm/BERT-MLM-IMDb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_mlm_imdb_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_mlm_imdb_pipeline_en.md
new file mode 100644
index 00000000000000..85a4e6c872d4b1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_mlm_imdb_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_mlm_imdb_pipeline pipeline BertEmbeddings from AirrStorm
+author: John Snow Labs
+name: bert_mlm_imdb_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_mlm_imdb_pipeline` is a English model originally trained by AirrStorm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_mlm_imdb_pipeline_en_5.5.1_3.0_1738096949191.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_mlm_imdb_pipeline_en_5.5.1_3.0_1738096949191.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_mlm_imdb_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_mlm_imdb_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_mlm_imdb_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/AirrStorm/BERT-MLM-IMDb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_ner_cosuleabianca_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_ner_cosuleabianca_en.md
new file mode 100644
index 00000000000000..b0b6ceed3e47e3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_ner_cosuleabianca_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_ner_cosuleabianca BertForTokenClassification from cosuleabianca
+author: John Snow Labs
+name: bert_ner_cosuleabianca
+date: 2025-01-28
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ner_cosuleabianca` is a English model originally trained by cosuleabianca.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ner_cosuleabianca_en_5.5.1_3.0_1738045603863.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ner_cosuleabianca_en_5.5.1_3.0_1738045603863.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_ner_cosuleabianca","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_ner_cosuleabianca", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_ner_cosuleabianca|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|464.2 MB|
+
+## References
+
+https://huggingface.co/cosuleabianca/bert_ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_ner_cosuleabianca_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_ner_cosuleabianca_pipeline_en.md
new file mode 100644
index 00000000000000..86af94f6014d9e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_ner_cosuleabianca_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_ner_cosuleabianca_pipeline pipeline BertForTokenClassification from cosuleabianca
+author: John Snow Labs
+name: bert_ner_cosuleabianca_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ner_cosuleabianca_pipeline` is a English model originally trained by cosuleabianca.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ner_cosuleabianca_pipeline_en_5.5.1_3.0_1738045626894.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ner_cosuleabianca_pipeline_en_5.5.1_3.0_1738045626894.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_ner_cosuleabianca_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_ner_cosuleabianca_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_ner_cosuleabianca_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|464.2 MB|
+
+## References
+
+https://huggingface.co/cosuleabianca/bert_ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_ner_vishal24_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_ner_vishal24_en.md
new file mode 100644
index 00000000000000..7deb65bc976b58
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_ner_vishal24_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_ner_vishal24 BertForTokenClassification from Vishal24
+author: John Snow Labs
+name: bert_ner_vishal24
+date: 2025-01-28
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ner_vishal24` is a English model originally trained by Vishal24.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ner_vishal24_en_5.5.1_3.0_1738044675820.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ner_vishal24_en_5.5.1_3.0_1738044675820.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_ner_vishal24","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_ner_vishal24", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_ner_vishal24|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.8 MB|
+
+## References
+
+https://huggingface.co/Vishal24/bert-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_ner_vishal24_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_ner_vishal24_pipeline_en.md
new file mode 100644
index 00000000000000..42224370a457a1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_ner_vishal24_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_ner_vishal24_pipeline pipeline BertForTokenClassification from Vishal24
+author: John Snow Labs
+name: bert_ner_vishal24_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ner_vishal24_pipeline` is a English model originally trained by Vishal24.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ner_vishal24_pipeline_en_5.5.1_3.0_1738044695864.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ner_vishal24_pipeline_en_5.5.1_3.0_1738044695864.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_ner_vishal24_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_ner_vishal24_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_ner_vishal24_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.8 MB|
+
+## References
+
+https://huggingface.co/Vishal24/bert-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_phishing_detector_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_phishing_detector_en.md
new file mode 100644
index 00000000000000..5f7d2b3ec4446b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_phishing_detector_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_phishing_detector BertForSequenceClassification from imanoop7
+author: John Snow Labs
+name: bert_phishing_detector
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_phishing_detector` is a English model originally trained by imanoop7.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_phishing_detector_en_5.5.1_3.0_1738028389038.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_phishing_detector_en_5.5.1_3.0_1738028389038.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("bert_phishing_detector","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("bert_phishing_detector", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_phishing_detector|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/imanoop7/bert-phishing-detector
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_phishing_detector_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bert_phishing_detector_pipeline_en.md
new file mode 100644
index 00000000000000..5d5c6c13a86e4c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_phishing_detector_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_phishing_detector_pipeline pipeline BertForSequenceClassification from imanoop7
+author: John Snow Labs
+name: bert_phishing_detector_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_phishing_detector_pipeline` is a English model originally trained by imanoop7.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_phishing_detector_pipeline_en_5.5.1_3.0_1738028410380.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_phishing_detector_pipeline_en_5.5.1_3.0_1738028410380.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_phishing_detector_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_phishing_detector_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_phishing_detector_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/imanoop7/bert-phishing-detector
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_sequence_classifier_multilingual_sentiment_pipeline_xx.md b/docs/_posts/ahmedlone127/2025-01-28-bert_sequence_classifier_multilingual_sentiment_pipeline_xx.md
new file mode 100644
index 00000000000000..ac095afa996e3c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_sequence_classifier_multilingual_sentiment_pipeline_xx.md
@@ -0,0 +1,72 @@
+---
+layout: model
+title: Multilingual bert_sequence_classifier_multilingual_sentiment_pipeline pipeline BertForSequenceClassification from nlptown
+author: John Snow Labs
+name: bert_sequence_classifier_multilingual_sentiment_pipeline
+date: 2025-01-28
+tags: [xx, open_source, pipeline, onnx]
+task: Text Classification
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_sequence_classifier_multilingual_sentiment_pipeline` is a Multilingual model originally trained by nlptown.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_multilingual_sentiment_pipeline_xx_5.5.1_3.0_1738027622657.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_multilingual_sentiment_pipeline_xx_5.5.1_3.0_1738027622657.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("bert_sequence_classifier_multilingual_sentiment_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("bert_sequence_classifier_multilingual_sentiment_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_sequence_classifier_multilingual_sentiment_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|627.8 MB|
+
+## References
+
+References
+
+https://huggingface.co/nlptown/bert-base-multilingual-uncased-sentiment
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bert_sequence_classifier_multilingual_sentiment_xx.md b/docs/_posts/ahmedlone127/2025-01-28-bert_sequence_classifier_multilingual_sentiment_xx.md
new file mode 100644
index 00000000000000..676d3a9e040409
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bert_sequence_classifier_multilingual_sentiment_xx.md
@@ -0,0 +1,128 @@
+---
+layout: model
+title: BERT Sequence Classification Multilingual Sentiment
+author: John Snow Labs
+name: bert_sequence_classifier_multilingual_sentiment
+date: 2025-01-28
+tags: [en, nl, de, fr, it, es, sequence_classification, bert, multilingual, sentiment, xx, open_source, onnx]
+task: Text Classification
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+This a bert-base-multilingual-uncased model finetuned for sentiment analysis on product reviews in six languages: English, Dutch, German, French, Spanish and Italian. It predicts the sentiment of the review as a number of stars (between 1 and 5).
+
+This model is intended for direct use as a sentiment analysis model for product reviews in any of the six languages above, or for further finetuning on related sentiment analysis tasks.
+
+## Predicted Entities
+
+`1 star`, `2 stars`, `3 stars`, `4 stars`, `5 stars`
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_multilingual_sentiment_xx_5.5.1_3.0_1738027591267.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_multilingual_sentiment_xx_5.5.1_3.0_1738027591267.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier = BertForSequenceClassification \
+      .pretrained('bert_sequence_classifier_multilingual_sentiment', 'xx') \
+      .setInputCols(['token', 'document']) \
+      .setOutputCol('class') \
+      .setCaseSensitive(False) \
+      .setMaxSentenceLength(512)
+
+pipeline = Pipeline(stages=[
+    document_assembler,
+    tokenizer,
+    sequenceClassifier
+])
+
+example = spark.createDataFrame([['I really liked that movie!']]).toDF("text")
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document_assembler = DocumentAssembler()
+    .setInputCol("text")
+    .setOutputCol("document")
+
+val tokenizer = Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_multilingual_sentiment", "xx")
+      .setInputCols("document", "token")
+      .setOutputCol("class")
+      .setCaseSensitive(false)
+      .setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, tokenizer, sequenceClassifier))
+
+val example = Seq("I really liked that movie!").toDS.toDF("text")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("xx.classify.bert.sentiment.multilingual").predict("""I really liked that movie!""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_sequence_classifier_multilingual_sentiment|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|xx|
+|Size:|627.8 MB|
+
+## Benchmarking
+
+```bash
+
+The finetuned model obtained the following accuracy on 5,000 held-out product reviews in each of the languages:
+
+- Accuracy (exact) is the exact match on the number of stars.
+- Accuracy (off-by-1) is the percentage of reviews where the number of stars the model predicts differs by a maximum of 1 from the number given by the human reviewer.
+
+
+| Language | Accuracy (exact) | Accuracy (off-by-1) |
+| -------- | ---------------------- | ------------------- |
+| English  | 67%                 | 95%
+| Dutch    | 57%                 | 93%
+| German   | 61%                 | 94%
+| French   | 59%                 | 94%
+| Italian  | 59%                 | 95%
+| Spanish  | 58%                 | 95%
+```
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bertaidetector_en.md b/docs/_posts/ahmedlone127/2025-01-28-bertaidetector_en.md
new file mode 100644
index 00000000000000..a22c08877d3e67
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bertaidetector_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bertaidetector BertForSequenceClassification from pritamdeb68
+author: John Snow Labs
+name: bertaidetector
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bertaidetector` is a English model originally trained by pritamdeb68.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bertaidetector_en_5.5.1_3.0_1738051569113.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bertaidetector_en_5.5.1_3.0_1738051569113.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("bertaidetector","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("bertaidetector", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bertaidetector|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/pritamdeb68/BERTAIDetector
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bertaidetector_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bertaidetector_pipeline_en.md
new file mode 100644
index 00000000000000..d0fba8f294bbba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bertaidetector_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bertaidetector_pipeline pipeline BertForSequenceClassification from pritamdeb68
+author: John Snow Labs
+name: bertaidetector_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bertaidetector_pipeline` is a English model originally trained by pritamdeb68.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bertaidetector_pipeline_en_5.5.1_3.0_1738051589951.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bertaidetector_pipeline_en_5.5.1_3.0_1738051589951.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bertaidetector_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bertaidetector_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bertaidetector_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/pritamdeb68/BERTAIDetector
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-berth6_en.md b/docs/_posts/ahmedlone127/2025-01-28-berth6_en.md
new file mode 100644
index 00000000000000..bac22d4339217a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-berth6_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English berth6 BertEmbeddings from JeloH
+author: John Snow Labs
+name: berth6
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`berth6` is a English model originally trained by JeloH.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/berth6_en_5.5.1_3.0_1738084756823.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/berth6_en_5.5.1_3.0_1738084756823.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("berth6","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("berth6","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|berth6|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.3 MB|
+
+## References
+
+https://huggingface.co/JeloH/BertH6
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-berth6_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-berth6_pipeline_en.md
new file mode 100644
index 00000000000000..2ad10782e6286a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-berth6_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English berth6_pipeline pipeline BertEmbeddings from JeloH
+author: John Snow Labs
+name: berth6_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`berth6_pipeline` is a English model originally trained by JeloH.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/berth6_pipeline_en_5.5.1_3.0_1738084779281.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/berth6_pipeline_en_5.5.1_3.0_1738084779281.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("berth6_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("berth6_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|berth6_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.3 MB|
+
+## References
+
+https://huggingface.co/JeloH/BertH6
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bertimbau_finetuned_glassdoor_reviews_pipeline_pt.md b/docs/_posts/ahmedlone127/2025-01-28-bertimbau_finetuned_glassdoor_reviews_pipeline_pt.md
new file mode 100644
index 00000000000000..49cd4487dd1c8f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bertimbau_finetuned_glassdoor_reviews_pipeline_pt.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Portuguese bertimbau_finetuned_glassdoor_reviews_pipeline pipeline BertForSequenceClassification from stevillis
+author: John Snow Labs
+name: bertimbau_finetuned_glassdoor_reviews_pipeline
+date: 2025-01-28
+tags: [pt, open_source, pipeline, onnx]
+task: Text Classification
+language: pt
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bertimbau_finetuned_glassdoor_reviews_pipeline` is a Portuguese model originally trained by stevillis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bertimbau_finetuned_glassdoor_reviews_pipeline_pt_5.5.1_3.0_1738101079575.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bertimbau_finetuned_glassdoor_reviews_pipeline_pt_5.5.1_3.0_1738101079575.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bertimbau_finetuned_glassdoor_reviews_pipeline", lang = "pt")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bertimbau_finetuned_glassdoor_reviews_pipeline", lang = "pt")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bertimbau_finetuned_glassdoor_reviews_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|pt|
+|Size:|408.2 MB|
+
+## References
+
+https://huggingface.co/stevillis/bertimbau-finetuned-glassdoor-reviews
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bertimbau_finetuned_glassdoor_reviews_pt.md b/docs/_posts/ahmedlone127/2025-01-28-bertimbau_finetuned_glassdoor_reviews_pt.md
new file mode 100644
index 00000000000000..0b385f4572dfd6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bertimbau_finetuned_glassdoor_reviews_pt.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Portuguese bertimbau_finetuned_glassdoor_reviews BertForSequenceClassification from stevillis
+author: John Snow Labs
+name: bertimbau_finetuned_glassdoor_reviews
+date: 2025-01-28
+tags: [pt, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: pt
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bertimbau_finetuned_glassdoor_reviews` is a Portuguese model originally trained by stevillis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bertimbau_finetuned_glassdoor_reviews_pt_5.5.1_3.0_1738101059543.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bertimbau_finetuned_glassdoor_reviews_pt_5.5.1_3.0_1738101059543.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("bertimbau_finetuned_glassdoor_reviews","pt") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("bertimbau_finetuned_glassdoor_reviews", "pt")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bertimbau_finetuned_glassdoor_reviews|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|pt|
+|Size:|408.2 MB|
+
+## References
+
+https://huggingface.co/stevillis/bertimbau-finetuned-glassdoor-reviews
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bertskill_relative_key_query_modif_en.md b/docs/_posts/ahmedlone127/2025-01-28-bertskill_relative_key_query_modif_en.md
new file mode 100644
index 00000000000000..4b2c9559ccf614
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bertskill_relative_key_query_modif_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bertskill_relative_key_query_modif BertEmbeddings from meilanynonsitentua
+author: John Snow Labs
+name: bertskill_relative_key_query_modif
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bertskill_relative_key_query_modif` is a English model originally trained by meilanynonsitentua.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bertskill_relative_key_query_modif_en_5.5.1_3.0_1738058103904.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bertskill_relative_key_query_modif_en_5.5.1_3.0_1738058103904.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bertskill_relative_key_query_modif","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bertskill_relative_key_query_modif","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bertskill_relative_key_query_modif|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|414.1 MB|
+
+## References
+
+https://huggingface.co/meilanynonsitentua/bertskill-relative-key-query-modif
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-bertskill_relative_key_query_modif_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-bertskill_relative_key_query_modif_pipeline_en.md
new file mode 100644
index 00000000000000..20871151a69999
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-bertskill_relative_key_query_modif_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bertskill_relative_key_query_modif_pipeline pipeline BertEmbeddings from meilanynonsitentua
+author: John Snow Labs
+name: bertskill_relative_key_query_modif_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bertskill_relative_key_query_modif_pipeline` is a English model originally trained by meilanynonsitentua.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bertskill_relative_key_query_modif_pipeline_en_5.5.1_3.0_1738058124251.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bertskill_relative_key_query_modif_pipeline_en_5.5.1_3.0_1738058124251.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bertskill_relative_key_query_modif_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bertskill_relative_key_query_modif_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bertskill_relative_key_query_modif_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|414.1 MB|
+
+## References
+
+https://huggingface.co/meilanynonsitentua/bertskill-relative-key-query-modif
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-betterdistilbert_en.md b/docs/_posts/ahmedlone127/2025-01-28-betterdistilbert_en.md
new file mode 100644
index 00000000000000..a8e021773fc6d7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-betterdistilbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English betterdistilbert DistilBertForSequenceClassification from aliciiavs
+author: John Snow Labs
+name: betterdistilbert
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`betterdistilbert` is a English model originally trained by aliciiavs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/betterdistilbert_en_5.5.1_3.0_1738078003686.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/betterdistilbert_en_5.5.1_3.0_1738078003686.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("betterdistilbert","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("betterdistilbert", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|betterdistilbert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/aliciiavs/betterdistilbert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-betterdistilbert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-betterdistilbert_pipeline_en.md
new file mode 100644
index 00000000000000..a8177dd24fa160
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-betterdistilbert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English betterdistilbert_pipeline pipeline DistilBertForSequenceClassification from aliciiavs
+author: John Snow Labs
+name: betterdistilbert_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`betterdistilbert_pipeline` is a English model originally trained by aliciiavs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/betterdistilbert_pipeline_en_5.5.1_3.0_1738078016383.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/betterdistilbert_pipeline_en_5.5.1_3.0_1738078016383.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("betterdistilbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("betterdistilbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|betterdistilbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/aliciiavs/betterdistilbert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-billsum_summarizer_en.md b/docs/_posts/ahmedlone127/2025-01-28-billsum_summarizer_en.md
new file mode 100644
index 00000000000000..dbf56a79ccdcc1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-billsum_summarizer_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English billsum_summarizer T5Transformer from mouazc
+author: John Snow Labs
+name: billsum_summarizer
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`billsum_summarizer` is a English model originally trained by mouazc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/billsum_summarizer_en_5.5.1_3.0_1738030556696.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/billsum_summarizer_en_5.5.1_3.0_1738030556696.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("billsum_summarizer","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("billsum_summarizer", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|billsum_summarizer|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|272.2 MB|
+
+## References
+
+https://huggingface.co/mouazc/billsum_summarizer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-billsum_summarizer_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-billsum_summarizer_pipeline_en.md
new file mode 100644
index 00000000000000..f72547e23294d2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-billsum_summarizer_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English billsum_summarizer_pipeline pipeline T5Transformer from mouazc
+author: John Snow Labs
+name: billsum_summarizer_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`billsum_summarizer_pipeline` is a English model originally trained by mouazc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/billsum_summarizer_pipeline_en_5.5.1_3.0_1738030572636.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/billsum_summarizer_pipeline_en_5.5.1_3.0_1738030572636.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("billsum_summarizer_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("billsum_summarizer_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|billsum_summarizer_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|272.2 MB|
+
+## References
+
+https://huggingface.co/mouazc/billsum_summarizer
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-billsum_t5_small_en.md b/docs/_posts/ahmedlone127/2025-01-28-billsum_t5_small_en.md
new file mode 100644
index 00000000000000..b3bf1621b52619
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-billsum_t5_small_en.md
@@ -0,0 +1,88 @@
+---
+layout: model
+title: English billsum_t5_small T5Transformer from macadeliccc
+author: John Snow Labs
+name: billsum_t5_small
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`billsum_t5_small` is a English model originally trained by macadeliccc.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/billsum_t5_small_en_5.5.1_3.0_1738073178688.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/billsum_t5_small_en_5.5.1_3.0_1738073178688.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("billsum_t5_small","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("billsum_t5_small", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|billsum_t5_small|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|268.7 MB|
+
+## References
+
+References
+
+https://huggingface.co/macadeliccc/billsum_T5_small
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-billsum_t5_small_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-billsum_t5_small_pipeline_en.md
new file mode 100644
index 00000000000000..85f1a240a26e83
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-billsum_t5_small_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English billsum_t5_small_pipeline pipeline T5Transformer from macadeliccc
+author: John Snow Labs
+name: billsum_t5_small_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`billsum_t5_small_pipeline` is a English model originally trained by macadeliccc.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/billsum_t5_small_pipeline_en_5.5.1_3.0_1738073196394.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/billsum_t5_small_pipeline_en_5.5.1_3.0_1738073196394.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("billsum_t5_small_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("billsum_t5_small_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|billsum_t5_small_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|268.7 MB|
+
+## References
+
+References
+
+https://huggingface.co/macadeliccc/billsum_T5_small
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-biobert_all_en.md b/docs/_posts/ahmedlone127/2025-01-28-biobert_all_en.md
new file mode 100644
index 00000000000000..e2c4f24dd4d85d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-biobert_all_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English biobert_all BertForTokenClassification from jialinselenasong
+author: John Snow Labs
+name: biobert_all
+date: 2025-01-28
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biobert_all` is a English model originally trained by jialinselenasong.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biobert_all_en_5.5.1_3.0_1738045116755.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biobert_all_en_5.5.1_3.0_1738045116755.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("biobert_all","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("biobert_all", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|biobert_all|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.1 MB|
+
+## References
+
+https://huggingface.co/jialinselenasong/biobert-all
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-biobert_all_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-biobert_all_pipeline_en.md
new file mode 100644
index 00000000000000..bd65b0c852b063
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-biobert_all_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English biobert_all_pipeline pipeline BertForTokenClassification from jialinselenasong
+author: John Snow Labs
+name: biobert_all_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biobert_all_pipeline` is a English model originally trained by jialinselenasong.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biobert_all_pipeline_en_5.5.1_3.0_1738045137319.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biobert_all_pipeline_en_5.5.1_3.0_1738045137319.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("biobert_all_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("biobert_all_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|biobert_all_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.1 MB|
+
+## References
+
+https://huggingface.co/jialinselenasong/biobert-all
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_books_model_2_en.md b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_books_model_2_en.md
new file mode 100644
index 00000000000000..760e4bdf1c1f97
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_books_model_2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_books_model_2 T5Transformer from Taisiia7
+author: John Snow Labs
+name: burmese_awesome_books_model_2
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_books_model_2` is a English model originally trained by Taisiia7.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_books_model_2_en_5.5.1_3.0_1738072900538.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_books_model_2_en_5.5.1_3.0_1738072900538.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("burmese_awesome_books_model_2","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("burmese_awesome_books_model_2", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_books_model_2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|466.4 MB|
+
+## References
+
+https://huggingface.co/Taisiia7/my_awesome_books_model_2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_books_model_2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_books_model_2_pipeline_en.md
new file mode 100644
index 00000000000000..55689cf00464d6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_books_model_2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_books_model_2_pipeline pipeline T5Transformer from Taisiia7
+author: John Snow Labs
+name: burmese_awesome_books_model_2_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_books_model_2_pipeline` is a English model originally trained by Taisiia7.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_books_model_2_pipeline_en_5.5.1_3.0_1738072939007.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_books_model_2_pipeline_en_5.5.1_3.0_1738072939007.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_books_model_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_books_model_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_books_model_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.4 MB|
+
+## References
+
+https://huggingface.co/Taisiia7/my_awesome_books_model_2
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_eli5_mlm_model_kumarme072_en.md b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_eli5_mlm_model_kumarme072_en.md
new file mode 100644
index 00000000000000..23d1b4149d8546
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_eli5_mlm_model_kumarme072_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_eli5_mlm_model_kumarme072 BertEmbeddings from kumarme072
+author: John Snow Labs
+name: burmese_awesome_eli5_mlm_model_kumarme072
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_eli5_mlm_model_kumarme072` is a English model originally trained by kumarme072.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_kumarme072_en_5.5.1_3.0_1738057415508.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_kumarme072_en_5.5.1_3.0_1738057415508.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("burmese_awesome_eli5_mlm_model_kumarme072","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("burmese_awesome_eli5_mlm_model_kumarme072","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_eli5_mlm_model_kumarme072|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|408.2 MB|
+
+## References
+
+https://huggingface.co/kumarme072/my_awesome_eli5_mlm_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_eli5_mlm_model_kumarme072_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_eli5_mlm_model_kumarme072_pipeline_en.md
new file mode 100644
index 00000000000000..fb0e2d4bd72824
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_eli5_mlm_model_kumarme072_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_eli5_mlm_model_kumarme072_pipeline pipeline BertEmbeddings from kumarme072
+author: John Snow Labs
+name: burmese_awesome_eli5_mlm_model_kumarme072_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_eli5_mlm_model_kumarme072_pipeline` is a English model originally trained by kumarme072.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_kumarme072_pipeline_en_5.5.1_3.0_1738057435769.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_kumarme072_pipeline_en_5.5.1_3.0_1738057435769.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_eli5_mlm_model_kumarme072_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_eli5_mlm_model_kumarme072_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_eli5_mlm_model_kumarme072_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|408.2 MB|
+
+## References
+
+https://huggingface.co/kumarme072/my_awesome_eli5_mlm_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_food_model_william7642_en.md b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_food_model_william7642_en.md
new file mode 100644
index 00000000000000..f8e1cc50cb6a25
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_food_model_william7642_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_food_model_william7642 ViTForImageClassification from william7642
+author: John Snow Labs
+name: burmese_awesome_food_model_william7642
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_food_model_william7642` is a English model originally trained by william7642.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_food_model_william7642_en_5.5.1_3.0_1738022889439.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_food_model_william7642_en_5.5.1_3.0_1738022889439.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""burmese_awesome_food_model_william7642","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("burmese_awesome_food_model_william7642","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_food_model_william7642|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.6 MB|
+
+## References
+
+https://huggingface.co/william7642/my_awesome_food_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_food_model_william7642_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_food_model_william7642_pipeline_en.md
new file mode 100644
index 00000000000000..a08052443a869f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_food_model_william7642_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_food_model_william7642_pipeline pipeline ViTForImageClassification from william7642
+author: John Snow Labs
+name: burmese_awesome_food_model_william7642_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_food_model_william7642_pipeline` is a English model originally trained by william7642.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_food_model_william7642_pipeline_en_5.5.1_3.0_1738022907481.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_food_model_william7642_pipeline_en_5.5.1_3.0_1738022907481.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_food_model_william7642_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_food_model_william7642_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_food_model_william7642_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.6 MB|
+
+## References
+
+https://huggingface.co/william7642/my_awesome_food_model
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_model_amnaad24_en.md b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_model_amnaad24_en.md
new file mode 100644
index 00000000000000..8e7812b0f54d01
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_model_amnaad24_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_amnaad24 DistilBertForSequenceClassification from amnaad24
+author: John Snow Labs
+name: burmese_awesome_model_amnaad24
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_amnaad24` is a English model originally trained by amnaad24.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_amnaad24_en_5.5.1_3.0_1738025193460.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_amnaad24_en_5.5.1_3.0_1738025193460.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_amnaad24","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_amnaad24", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_amnaad24|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/amnaad24/my_awesome_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_model_amnaad24_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_model_amnaad24_pipeline_en.md
new file mode 100644
index 00000000000000..8678b54d666ca5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_model_amnaad24_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_amnaad24_pipeline pipeline DistilBertForSequenceClassification from amnaad24
+author: John Snow Labs
+name: burmese_awesome_model_amnaad24_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_amnaad24_pipeline` is a English model originally trained by amnaad24.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_amnaad24_pipeline_en_5.5.1_3.0_1738025211310.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_amnaad24_pipeline_en_5.5.1_3.0_1738025211310.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_amnaad24_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_amnaad24_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_amnaad24_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/amnaad24/my_awesome_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_model_eonpark_en.md b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_model_eonpark_en.md
new file mode 100644
index 00000000000000..d9e0d027876814
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_model_eonpark_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_eonpark DistilBertForSequenceClassification from eonpark
+author: John Snow Labs
+name: burmese_awesome_model_eonpark
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_eonpark` is a English model originally trained by eonpark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_eonpark_en_5.5.1_3.0_1738077241130.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_eonpark_en_5.5.1_3.0_1738077241130.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_eonpark","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_eonpark", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_eonpark|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/eonpark/my_awesome_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_model_eonpark_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_model_eonpark_pipeline_en.md
new file mode 100644
index 00000000000000..1040e649f66b80
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_model_eonpark_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_eonpark_pipeline pipeline DistilBertForSequenceClassification from eonpark
+author: John Snow Labs
+name: burmese_awesome_model_eonpark_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_eonpark_pipeline` is a English model originally trained by eonpark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_eonpark_pipeline_en_5.5.1_3.0_1738077253524.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_eonpark_pipeline_en_5.5.1_3.0_1738077253524.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_eonpark_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_eonpark_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_eonpark_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/eonpark/my_awesome_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_model_lauraalexandra_en.md b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_model_lauraalexandra_en.md
new file mode 100644
index 00000000000000..2cbebe821e2cf8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_model_lauraalexandra_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_lauraalexandra DistilBertForSequenceClassification from LauraAlexandra
+author: John Snow Labs
+name: burmese_awesome_model_lauraalexandra
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_lauraalexandra` is a English model originally trained by LauraAlexandra.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_lauraalexandra_en_5.5.1_3.0_1738025327271.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_lauraalexandra_en_5.5.1_3.0_1738025327271.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_lauraalexandra","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_lauraalexandra", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_lauraalexandra|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/LauraAlexandra/my_awesome_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_model_lauraalexandra_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_model_lauraalexandra_pipeline_en.md
new file mode 100644
index 00000000000000..1b504fdfb28d85
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_model_lauraalexandra_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_lauraalexandra_pipeline pipeline DistilBertForSequenceClassification from LauraAlexandra
+author: John Snow Labs
+name: burmese_awesome_model_lauraalexandra_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_lauraalexandra_pipeline` is a English model originally trained by LauraAlexandra.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_lauraalexandra_pipeline_en_5.5.1_3.0_1738025344415.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_lauraalexandra_pipeline_en_5.5.1_3.0_1738025344415.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_lauraalexandra_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_lauraalexandra_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_lauraalexandra_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/LauraAlexandra/my_awesome_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_model_luisdahuis_en.md b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_model_luisdahuis_en.md
new file mode 100644
index 00000000000000..4d08d101b4a43f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_model_luisdahuis_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_luisdahuis DistilBertForSequenceClassification from Luisdahuis
+author: John Snow Labs
+name: burmese_awesome_model_luisdahuis
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_luisdahuis` is a English model originally trained by Luisdahuis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_luisdahuis_en_5.5.1_3.0_1738026153700.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_luisdahuis_en_5.5.1_3.0_1738026153700.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_luisdahuis","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_luisdahuis", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_luisdahuis|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Luisdahuis/my_awesome_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_model_luisdahuis_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_model_luisdahuis_pipeline_en.md
new file mode 100644
index 00000000000000..b96b2a5fccebd9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_model_luisdahuis_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_luisdahuis_pipeline pipeline DistilBertForSequenceClassification from Luisdahuis
+author: John Snow Labs
+name: burmese_awesome_model_luisdahuis_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_luisdahuis_pipeline` is a English model originally trained by Luisdahuis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_luisdahuis_pipeline_en_5.5.1_3.0_1738026166480.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_luisdahuis_pipeline_en_5.5.1_3.0_1738026166480.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_luisdahuis_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_luisdahuis_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_luisdahuis_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Luisdahuis/my_awesome_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_model_mizworski_en.md b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_model_mizworski_en.md
new file mode 100644
index 00000000000000..f84af10d4cdc8f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_model_mizworski_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_mizworski DistilBertForSequenceClassification from mizworski
+author: John Snow Labs
+name: burmese_awesome_model_mizworski
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_mizworski` is a English model originally trained by mizworski.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_mizworski_en_5.5.1_3.0_1738025819798.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_mizworski_en_5.5.1_3.0_1738025819798.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_mizworski","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_mizworski", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_mizworski|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/mizworski/my_awesome_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_model_mizworski_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_model_mizworski_pipeline_en.md
new file mode 100644
index 00000000000000..fe316adb98e3ac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_model_mizworski_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_mizworski_pipeline pipeline DistilBertForSequenceClassification from mizworski
+author: John Snow Labs
+name: burmese_awesome_model_mizworski_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_mizworski_pipeline` is a English model originally trained by mizworski.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_mizworski_pipeline_en_5.5.1_3.0_1738025838568.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_mizworski_pipeline_en_5.5.1_3.0_1738025838568.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_mizworski_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_mizworski_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_mizworski_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/mizworski/my_awesome_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_model_monkeyzfl_en.md b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_model_monkeyzfl_en.md
new file mode 100644
index 00000000000000..829fafb6b297d7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_model_monkeyzfl_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_monkeyzfl DistilBertForSequenceClassification from MonkeYzFL
+author: John Snow Labs
+name: burmese_awesome_model_monkeyzfl
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_monkeyzfl` is a English model originally trained by MonkeYzFL.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_monkeyzfl_en_5.5.1_3.0_1738025828669.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_monkeyzfl_en_5.5.1_3.0_1738025828669.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_monkeyzfl","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_monkeyzfl", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_monkeyzfl|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/MonkeYzFL/my_awesome_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_model_monkeyzfl_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_model_monkeyzfl_pipeline_en.md
new file mode 100644
index 00000000000000..7a159751034b65
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_model_monkeyzfl_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_monkeyzfl_pipeline pipeline DistilBertForSequenceClassification from MonkeYzFL
+author: John Snow Labs
+name: burmese_awesome_model_monkeyzfl_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_monkeyzfl_pipeline` is a English model originally trained by MonkeYzFL.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_monkeyzfl_pipeline_en_5.5.1_3.0_1738025842080.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_monkeyzfl_pipeline_en_5.5.1_3.0_1738025842080.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_monkeyzfl_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_monkeyzfl_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_monkeyzfl_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/MonkeYzFL/my_awesome_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_model_ntkhoi_en.md b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_model_ntkhoi_en.md
new file mode 100644
index 00000000000000..08e315beef7f52
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_model_ntkhoi_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_ntkhoi DistilBertForSequenceClassification from ntkhoi
+author: John Snow Labs
+name: burmese_awesome_model_ntkhoi
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_ntkhoi` is a English model originally trained by ntkhoi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_ntkhoi_en_5.5.1_3.0_1738025558651.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_ntkhoi_en_5.5.1_3.0_1738025558651.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_ntkhoi","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_ntkhoi", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_ntkhoi|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/ntkhoi/my_awesome_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_model_ntkhoi_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_model_ntkhoi_pipeline_en.md
new file mode 100644
index 00000000000000..aafcd0c427540e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_model_ntkhoi_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_ntkhoi_pipeline pipeline DistilBertForSequenceClassification from ntkhoi
+author: John Snow Labs
+name: burmese_awesome_model_ntkhoi_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_ntkhoi_pipeline` is a English model originally trained by ntkhoi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_ntkhoi_pipeline_en_5.5.1_3.0_1738025571229.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_ntkhoi_pipeline_en_5.5.1_3.0_1738025571229.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_ntkhoi_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_ntkhoi_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_ntkhoi_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/ntkhoi/my_awesome_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_akibc123_en.md b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_akibc123_en.md
new file mode 100644
index 00000000000000..0818609bb15c14
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_akibc123_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_opus_books_model_akibc123 T5Transformer from akibc123
+author: John Snow Labs
+name: burmese_awesome_opus_books_model_akibc123
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_opus_books_model_akibc123` is a English model originally trained by akibc123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_akibc123_en_5.5.1_3.0_1738071423005.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_akibc123_en_5.5.1_3.0_1738071423005.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("burmese_awesome_opus_books_model_akibc123","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("burmese_awesome_opus_books_model_akibc123", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_opus_books_model_akibc123|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/akibc123/my_awesome_opus_books_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_akibc123_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_akibc123_pipeline_en.md
new file mode 100644
index 00000000000000..058054fcd4de1f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_akibc123_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_opus_books_model_akibc123_pipeline pipeline T5Transformer from akibc123
+author: John Snow Labs
+name: burmese_awesome_opus_books_model_akibc123_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_opus_books_model_akibc123_pipeline` is a English model originally trained by akibc123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_akibc123_pipeline_en_5.5.1_3.0_1738071472538.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_akibc123_pipeline_en_5.5.1_3.0_1738071472538.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_opus_books_model_akibc123_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_opus_books_model_akibc123_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_opus_books_model_akibc123_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/akibc123/my_awesome_opus_books_model
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_eviterlesroses_en.md b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_eviterlesroses_en.md
new file mode 100644
index 00000000000000..11bb11f604004a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_eviterlesroses_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_opus_books_model_eviterlesroses T5Transformer from EviterLesRoses
+author: John Snow Labs
+name: burmese_awesome_opus_books_model_eviterlesroses
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_opus_books_model_eviterlesroses` is a English model originally trained by EviterLesRoses.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_eviterlesroses_en_5.5.1_3.0_1738072695367.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_eviterlesroses_en_5.5.1_3.0_1738072695367.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("burmese_awesome_opus_books_model_eviterlesroses","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("burmese_awesome_opus_books_model_eviterlesroses", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_opus_books_model_eviterlesroses|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|282.3 MB|
+
+## References
+
+https://huggingface.co/EviterLesRoses/my_awesome_opus_books_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_eviterlesroses_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_eviterlesroses_pipeline_en.md
new file mode 100644
index 00000000000000..d1ecad210a88ca
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_eviterlesroses_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_opus_books_model_eviterlesroses_pipeline pipeline T5Transformer from EviterLesRoses
+author: John Snow Labs
+name: burmese_awesome_opus_books_model_eviterlesroses_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_opus_books_model_eviterlesroses_pipeline` is a English model originally trained by EviterLesRoses.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_eviterlesroses_pipeline_en_5.5.1_3.0_1738072719189.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_eviterlesroses_pipeline_en_5.5.1_3.0_1738072719189.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_opus_books_model_eviterlesroses_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_opus_books_model_eviterlesroses_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_opus_books_model_eviterlesroses_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|282.3 MB|
+
+## References
+
+https://huggingface.co/EviterLesRoses/my_awesome_opus_books_model
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_ghinaalamsyahh_en.md b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_ghinaalamsyahh_en.md
new file mode 100644
index 00000000000000..13b8cfe9a309a0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_ghinaalamsyahh_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_opus_books_model_ghinaalamsyahh T5Transformer from ghinaalamsyahh
+author: John Snow Labs
+name: burmese_awesome_opus_books_model_ghinaalamsyahh
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_opus_books_model_ghinaalamsyahh` is a English model originally trained by ghinaalamsyahh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_ghinaalamsyahh_en_5.5.1_3.0_1738071148150.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_ghinaalamsyahh_en_5.5.1_3.0_1738071148150.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("burmese_awesome_opus_books_model_ghinaalamsyahh","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("burmese_awesome_opus_books_model_ghinaalamsyahh", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_opus_books_model_ghinaalamsyahh|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|266.8 MB|
+
+## References
+
+https://huggingface.co/ghinaalamsyahh/my_awesome_opus_books_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_ghinaalamsyahh_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_ghinaalamsyahh_pipeline_en.md
new file mode 100644
index 00000000000000..16a723ec97ee98
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_ghinaalamsyahh_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_opus_books_model_ghinaalamsyahh_pipeline pipeline T5Transformer from ghinaalamsyahh
+author: John Snow Labs
+name: burmese_awesome_opus_books_model_ghinaalamsyahh_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_opus_books_model_ghinaalamsyahh_pipeline` is a English model originally trained by ghinaalamsyahh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_ghinaalamsyahh_pipeline_en_5.5.1_3.0_1738071165429.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_ghinaalamsyahh_pipeline_en_5.5.1_3.0_1738071165429.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_opus_books_model_ghinaalamsyahh_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_opus_books_model_ghinaalamsyahh_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_opus_books_model_ghinaalamsyahh_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|266.8 MB|
+
+## References
+
+https://huggingface.co/ghinaalamsyahh/my_awesome_opus_books_model
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_malvikavishy_en.md b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_malvikavishy_en.md
new file mode 100644
index 00000000000000..ba089797e0ebf7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_malvikavishy_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_opus_books_model_malvikavishy T5Transformer from malvikavishy
+author: John Snow Labs
+name: burmese_awesome_opus_books_model_malvikavishy
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_opus_books_model_malvikavishy` is a English model originally trained by malvikavishy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_malvikavishy_en_5.5.1_3.0_1738070965059.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_malvikavishy_en_5.5.1_3.0_1738070965059.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("burmese_awesome_opus_books_model_malvikavishy","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("burmese_awesome_opus_books_model_malvikavishy", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_opus_books_model_malvikavishy|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|282.2 MB|
+
+## References
+
+https://huggingface.co/malvikavishy/my_awesome_opus_books_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_malvikavishy_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_malvikavishy_pipeline_en.md
new file mode 100644
index 00000000000000..533bc53ec2cfc0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_malvikavishy_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_opus_books_model_malvikavishy_pipeline pipeline T5Transformer from malvikavishy
+author: John Snow Labs
+name: burmese_awesome_opus_books_model_malvikavishy_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_opus_books_model_malvikavishy_pipeline` is a English model originally trained by malvikavishy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_malvikavishy_pipeline_en_5.5.1_3.0_1738070980675.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_malvikavishy_pipeline_en_5.5.1_3.0_1738070980675.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_opus_books_model_malvikavishy_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_opus_books_model_malvikavishy_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_opus_books_model_malvikavishy_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|282.2 MB|
+
+## References
+
+https://huggingface.co/malvikavishy/my_awesome_opus_books_model
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_murada_en.md b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_murada_en.md
new file mode 100644
index 00000000000000..c035661a3b6e91
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_murada_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_opus_books_model_murada T5Transformer from MuradA
+author: John Snow Labs
+name: burmese_awesome_opus_books_model_murada
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_opus_books_model_murada` is a English model originally trained by MuradA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_murada_en_5.5.1_3.0_1738033050372.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_murada_en_5.5.1_3.0_1738033050372.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("burmese_awesome_opus_books_model_murada","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("burmese_awesome_opus_books_model_murada", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_opus_books_model_murada|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|279.5 MB|
+
+## References
+
+https://huggingface.co/MuradA/my_awesome_opus_books_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_murada_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_murada_pipeline_en.md
new file mode 100644
index 00000000000000..51dcce5724415e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_murada_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_opus_books_model_murada_pipeline pipeline T5Transformer from MuradA
+author: John Snow Labs
+name: burmese_awesome_opus_books_model_murada_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_opus_books_model_murada_pipeline` is a English model originally trained by MuradA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_murada_pipeline_en_5.5.1_3.0_1738033066225.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_murada_pipeline_en_5.5.1_3.0_1738033066225.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_opus_books_model_murada_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_opus_books_model_murada_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_opus_books_model_murada_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|279.5 MB|
+
+## References
+
+https://huggingface.co/MuradA/my_awesome_opus_books_model
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_ngdonna2020_en.md b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_ngdonna2020_en.md
new file mode 100644
index 00000000000000..b6498e5ca4ded8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_ngdonna2020_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_opus_books_model_ngdonna2020 T5Transformer from ngdonna2020
+author: John Snow Labs
+name: burmese_awesome_opus_books_model_ngdonna2020
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_opus_books_model_ngdonna2020` is a English model originally trained by ngdonna2020.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_ngdonna2020_en_5.5.1_3.0_1738032488267.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_ngdonna2020_en_5.5.1_3.0_1738032488267.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("burmese_awesome_opus_books_model_ngdonna2020","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("burmese_awesome_opus_books_model_ngdonna2020", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_opus_books_model_ngdonna2020|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|282.2 MB|
+
+## References
+
+https://huggingface.co/ngdonna2020/my_awesome_opus_books_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_ngdonna2020_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_ngdonna2020_pipeline_en.md
new file mode 100644
index 00000000000000..d98b6a3ff5a832
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_ngdonna2020_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_opus_books_model_ngdonna2020_pipeline pipeline T5Transformer from ngdonna2020
+author: John Snow Labs
+name: burmese_awesome_opus_books_model_ngdonna2020_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_opus_books_model_ngdonna2020_pipeline` is a English model originally trained by ngdonna2020.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_ngdonna2020_pipeline_en_5.5.1_3.0_1738032503577.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_ngdonna2020_pipeline_en_5.5.1_3.0_1738032503577.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_opus_books_model_ngdonna2020_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_opus_books_model_ngdonna2020_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_opus_books_model_ngdonna2020_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|282.2 MB|
+
+## References
+
+https://huggingface.co/ngdonna2020/my_awesome_opus_books_model
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_okita12345_en.md b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_okita12345_en.md
new file mode 100644
index 00000000000000..230aa4b0593c75
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_okita12345_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_opus_books_model_okita12345 T5Transformer from Okita12345
+author: John Snow Labs
+name: burmese_awesome_opus_books_model_okita12345
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_opus_books_model_okita12345` is a English model originally trained by Okita12345.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_okita12345_en_5.5.1_3.0_1738093325951.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_okita12345_en_5.5.1_3.0_1738093325951.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("burmese_awesome_opus_books_model_okita12345","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("burmese_awesome_opus_books_model_okita12345", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_opus_books_model_okita12345|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|279.6 MB|
+
+## References
+
+https://huggingface.co/Okita12345/my_awesome_opus_books_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_okita12345_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_okita12345_pipeline_en.md
new file mode 100644
index 00000000000000..27e5b6b65b363f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_okita12345_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_opus_books_model_okita12345_pipeline pipeline T5Transformer from Okita12345
+author: John Snow Labs
+name: burmese_awesome_opus_books_model_okita12345_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_opus_books_model_okita12345_pipeline` is a English model originally trained by Okita12345.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_okita12345_pipeline_en_5.5.1_3.0_1738093341737.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_okita12345_pipeline_en_5.5.1_3.0_1738093341737.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_opus_books_model_okita12345_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_opus_books_model_okita12345_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_opus_books_model_okita12345_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|279.6 MB|
+
+## References
+
+https://huggingface.co/Okita12345/my_awesome_opus_books_model
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_ruthvikm_en.md b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_ruthvikm_en.md
new file mode 100644
index 00000000000000..bee35c12143d8b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_ruthvikm_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_opus_books_model_ruthvikm T5Transformer from RuthvikM
+author: John Snow Labs
+name: burmese_awesome_opus_books_model_ruthvikm
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_opus_books_model_ruthvikm` is a English model originally trained by RuthvikM.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_ruthvikm_en_5.5.1_3.0_1738033269517.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_ruthvikm_en_5.5.1_3.0_1738033269517.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("burmese_awesome_opus_books_model_ruthvikm","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("burmese_awesome_opus_books_model_ruthvikm", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_opus_books_model_ruthvikm|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|148.0 MB|
+
+## References
+
+https://huggingface.co/RuthvikM/my_awesome_opus_books_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_ruthvikm_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_ruthvikm_pipeline_en.md
new file mode 100644
index 00000000000000..d443c02ad62e52
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_ruthvikm_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_opus_books_model_ruthvikm_pipeline pipeline T5Transformer from RuthvikM
+author: John Snow Labs
+name: burmese_awesome_opus_books_model_ruthvikm_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_opus_books_model_ruthvikm_pipeline` is a English model originally trained by RuthvikM.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_ruthvikm_pipeline_en_5.5.1_3.0_1738033316295.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_ruthvikm_pipeline_en_5.5.1_3.0_1738033316295.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_opus_books_model_ruthvikm_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_opus_books_model_ruthvikm_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_opus_books_model_ruthvikm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|148.0 MB|
+
+## References
+
+https://huggingface.co/RuthvikM/my_awesome_opus_books_model
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_xfuu11ecaf_en.md b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_xfuu11ecaf_en.md
new file mode 100644
index 00000000000000..c4290af07da272
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_xfuu11ecaf_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_opus_books_model_xfuu11ecaf T5Transformer from xfuu11ecaf
+author: John Snow Labs
+name: burmese_awesome_opus_books_model_xfuu11ecaf
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_opus_books_model_xfuu11ecaf` is a English model originally trained by xfuu11ecaf.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_xfuu11ecaf_en_5.5.1_3.0_1738092774867.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_xfuu11ecaf_en_5.5.1_3.0_1738092774867.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("burmese_awesome_opus_books_model_xfuu11ecaf","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("burmese_awesome_opus_books_model_xfuu11ecaf", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_opus_books_model_xfuu11ecaf|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|282.2 MB|
+
+## References
+
+https://huggingface.co/xfuu11ecaf/my_awesome_opus_books_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_xfuu11ecaf_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_xfuu11ecaf_pipeline_en.md
new file mode 100644
index 00000000000000..f7158a28a99577
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_xfuu11ecaf_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_opus_books_model_xfuu11ecaf_pipeline pipeline T5Transformer from xfuu11ecaf
+author: John Snow Labs
+name: burmese_awesome_opus_books_model_xfuu11ecaf_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_opus_books_model_xfuu11ecaf_pipeline` is a English model originally trained by xfuu11ecaf.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_xfuu11ecaf_pipeline_en_5.5.1_3.0_1738092790401.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_xfuu11ecaf_pipeline_en_5.5.1_3.0_1738092790401.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_opus_books_model_xfuu11ecaf_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_opus_books_model_xfuu11ecaf_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_opus_books_model_xfuu11ecaf_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|282.2 MB|
+
+## References
+
+https://huggingface.co/xfuu11ecaf/my_awesome_opus_books_model
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_yunzliang_en.md b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_yunzliang_en.md
new file mode 100644
index 00000000000000..cb3e2d825dad5c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_yunzliang_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_opus_books_model_yunzliang T5Transformer from yunzliang
+author: John Snow Labs
+name: burmese_awesome_opus_books_model_yunzliang
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_opus_books_model_yunzliang` is a English model originally trained by yunzliang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_yunzliang_en_5.5.1_3.0_1738091722936.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_yunzliang_en_5.5.1_3.0_1738091722936.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("burmese_awesome_opus_books_model_yunzliang","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("burmese_awesome_opus_books_model_yunzliang", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_opus_books_model_yunzliang|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|281.2 MB|
+
+## References
+
+https://huggingface.co/yunzliang/my_awesome_opus_books_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_yunzliang_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_yunzliang_pipeline_en.md
new file mode 100644
index 00000000000000..10251c4721725a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_opus_books_model_yunzliang_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_opus_books_model_yunzliang_pipeline pipeline T5Transformer from yunzliang
+author: John Snow Labs
+name: burmese_awesome_opus_books_model_yunzliang_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_opus_books_model_yunzliang_pipeline` is a English model originally trained by yunzliang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_yunzliang_pipeline_en_5.5.1_3.0_1738091738493.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_yunzliang_pipeline_en_5.5.1_3.0_1738091738493.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_opus_books_model_yunzliang_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_opus_books_model_yunzliang_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_opus_books_model_yunzliang_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|281.2 MB|
+
+## References
+
+https://huggingface.co/yunzliang/my_awesome_opus_books_model
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_pec_model_en.md b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_pec_model_en.md
new file mode 100644
index 00000000000000..39a64d895a95d5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_pec_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_pec_model DistilBertForTokenClassification from PaulBin
+author: John Snow Labs
+name: burmese_awesome_pec_model
+date: 2025-01-28
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_pec_model` is a English model originally trained by PaulBin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_pec_model_en_5.5.1_3.0_1738101628477.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_pec_model_en_5.5.1_3.0_1738101628477.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_pec_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_pec_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_pec_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/PaulBin/my_awesome_PEC_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_pec_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_pec_model_pipeline_en.md
new file mode 100644
index 00000000000000..1a661d4811fe15
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_pec_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_pec_model_pipeline pipeline DistilBertForTokenClassification from PaulBin
+author: John Snow Labs
+name: burmese_awesome_pec_model_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_pec_model_pipeline` is a English model originally trained by PaulBin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_pec_model_pipeline_en_5.5.1_3.0_1738101643505.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_pec_model_pipeline_en_5.5.1_3.0_1738101643505.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_pec_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_pec_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_pec_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/PaulBin/my_awesome_PEC_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_qa_model_vnktrmnb_en.md b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_qa_model_vnktrmnb_en.md
new file mode 100644
index 00000000000000..002284d23025aa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_qa_model_vnktrmnb_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_vnktrmnb BertForQuestionAnswering from vnktrmnb
+author: John Snow Labs
+name: burmese_awesome_qa_model_vnktrmnb
+date: 2025-01-28
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_vnktrmnb` is a English model originally trained by vnktrmnb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_vnktrmnb_en_5.5.1_3.0_1738062429906.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_vnktrmnb_en_5.5.1_3.0_1738062429906.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("burmese_awesome_qa_model_vnktrmnb","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("burmese_awesome_qa_model_vnktrmnb", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_vnktrmnb|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|664.0 MB|
+
+## References
+
+https://huggingface.co/vnktrmnb/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_qa_model_vnktrmnb_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_qa_model_vnktrmnb_pipeline_en.md
new file mode 100644
index 00000000000000..e662a1cda3d07d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_qa_model_vnktrmnb_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_vnktrmnb_pipeline pipeline BertForQuestionAnswering from vnktrmnb
+author: John Snow Labs
+name: burmese_awesome_qa_model_vnktrmnb_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_vnktrmnb_pipeline` is a English model originally trained by vnktrmnb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_vnktrmnb_pipeline_en_5.5.1_3.0_1738062463263.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_vnktrmnb_pipeline_en_5.5.1_3.0_1738062463263.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_vnktrmnb_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_vnktrmnb_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_vnktrmnb_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|664.0 MB|
+
+## References
+
+https://huggingface.co/vnktrmnb/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_wnut_model_clboetticher_hf_en.md b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_wnut_model_clboetticher_hf_en.md
new file mode 100644
index 00000000000000..83459b15a3be03
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_wnut_model_clboetticher_hf_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_clboetticher_hf DistilBertForTokenClassification from clboetticher-hf
+author: John Snow Labs
+name: burmese_awesome_wnut_model_clboetticher_hf
+date: 2025-01-28
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_clboetticher_hf` is a English model originally trained by clboetticher-hf.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_clboetticher_hf_en_5.5.1_3.0_1738101629837.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_clboetticher_hf_en_5.5.1_3.0_1738101629837.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_clboetticher_hf","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_clboetticher_hf", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_clboetticher_hf|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/clboetticher-hf/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_wnut_model_clboetticher_hf_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_wnut_model_clboetticher_hf_pipeline_en.md
new file mode 100644
index 00000000000000..94c946f4e70cba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-burmese_awesome_wnut_model_clboetticher_hf_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_clboetticher_hf_pipeline pipeline DistilBertForTokenClassification from clboetticher-hf
+author: John Snow Labs
+name: burmese_awesome_wnut_model_clboetticher_hf_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_clboetticher_hf_pipeline` is a English model originally trained by clboetticher-hf.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_clboetticher_hf_pipeline_en_5.5.1_3.0_1738101646110.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_clboetticher_hf_pipeline_en_5.5.1_3.0_1738101646110.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_wnut_model_clboetticher_hf_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_wnut_model_clboetticher_hf_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_clboetticher_hf_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/clboetticher-hf/my_awesome_wnut_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-burmese_pretrained_model_en.md b/docs/_posts/ahmedlone127/2025-01-28-burmese_pretrained_model_en.md
new file mode 100644
index 00000000000000..e4e28ea3b2c09e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-burmese_pretrained_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_pretrained_model DistilBertForSequenceClassification from Sarathkumar1304ai
+author: John Snow Labs
+name: burmese_pretrained_model
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_pretrained_model` is a English model originally trained by Sarathkumar1304ai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_pretrained_model_en_5.5.1_3.0_1738078016869.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_pretrained_model_en_5.5.1_3.0_1738078016869.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_pretrained_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_pretrained_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_pretrained_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|246.0 MB|
+
+## References
+
+https://huggingface.co/Sarathkumar1304ai/my-pretrained-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-burmese_pretrained_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-burmese_pretrained_model_pipeline_en.md
new file mode 100644
index 00000000000000..eb338873e2d2db
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-burmese_pretrained_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_pretrained_model_pipeline pipeline DistilBertForSequenceClassification from Sarathkumar1304ai
+author: John Snow Labs
+name: burmese_pretrained_model_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_pretrained_model_pipeline` is a English model originally trained by Sarathkumar1304ai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_pretrained_model_pipeline_en_5.5.1_3.0_1738078032250.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_pretrained_model_pipeline_en_5.5.1_3.0_1738078032250.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_pretrained_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_pretrained_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_pretrained_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|246.0 MB|
+
+## References
+
+https://huggingface.co/Sarathkumar1304ai/my-pretrained-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-burmese_t5_qa_model_en.md b/docs/_posts/ahmedlone127/2025-01-28-burmese_t5_qa_model_en.md
new file mode 100644
index 00000000000000..538329aadd962e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-burmese_t5_qa_model_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_t5_qa_model T5Transformer from Poomsaeroy
+author: John Snow Labs
+name: burmese_t5_qa_model
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_t5_qa_model` is a English model originally trained by Poomsaeroy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_t5_qa_model_en_5.5.1_3.0_1738093148514.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_t5_qa_model_en_5.5.1_3.0_1738093148514.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("burmese_t5_qa_model","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("burmese_t5_qa_model", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_t5_qa_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|147.6 MB|
+
+## References
+
+https://huggingface.co/Poomsaeroy/my-T5-qa-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-burmese_t5_qa_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-burmese_t5_qa_model_pipeline_en.md
new file mode 100644
index 00000000000000..f5579898cdbf02
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-burmese_t5_qa_model_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_t5_qa_model_pipeline pipeline T5Transformer from Poomsaeroy
+author: John Snow Labs
+name: burmese_t5_qa_model_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_t5_qa_model_pipeline` is a English model originally trained by Poomsaeroy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_t5_qa_model_pipeline_en_5.5.1_3.0_1738093195452.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_t5_qa_model_pipeline_en_5.5.1_3.0_1738093195452.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_t5_qa_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_t5_qa_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_t5_qa_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|147.6 MB|
+
+## References
+
+https://huggingface.co/Poomsaeroy/my-T5-qa-model
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-cardiobertpt_pipeline_pt.md b/docs/_posts/ahmedlone127/2025-01-28-cardiobertpt_pipeline_pt.md
new file mode 100644
index 00000000000000..2a70d623d721e8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-cardiobertpt_pipeline_pt.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Portuguese cardiobertpt_pipeline pipeline BertEmbeddings from pucpr-br
+author: John Snow Labs
+name: cardiobertpt_pipeline
+date: 2025-01-28
+tags: [pt, open_source, pipeline, onnx]
+task: Embeddings
+language: pt
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cardiobertpt_pipeline` is a Portuguese model originally trained by pucpr-br.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cardiobertpt_pipeline_pt_5.5.1_3.0_1738035112386.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cardiobertpt_pipeline_pt_5.5.1_3.0_1738035112386.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("cardiobertpt_pipeline", lang = "pt")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cardiobertpt_pipeline", lang = "pt")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cardiobertpt_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|pt|
+|Size:|662.7 MB|
+
+## References
+
+https://huggingface.co/pucpr-br/cardiobertpt
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-cardiobertpt_pt.md b/docs/_posts/ahmedlone127/2025-01-28-cardiobertpt_pt.md
new file mode 100644
index 00000000000000..8a7bfe23835866
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-cardiobertpt_pt.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Portuguese cardiobertpt BertEmbeddings from pucpr-br
+author: John Snow Labs
+name: cardiobertpt
+date: 2025-01-28
+tags: [pt, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: pt
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cardiobertpt` is a Portuguese model originally trained by pucpr-br.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cardiobertpt_pt_5.5.1_3.0_1738035078281.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cardiobertpt_pt_5.5.1_3.0_1738035078281.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("cardiobertpt","pt") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("cardiobertpt","pt") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cardiobertpt|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|pt|
+|Size:|662.7 MB|
+
+## References
+
+https://huggingface.co/pucpr-br/cardiobertpt
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-cfe_telmex_classification_finetuned_v3_en.md b/docs/_posts/ahmedlone127/2025-01-28-cfe_telmex_classification_finetuned_v3_en.md
new file mode 100644
index 00000000000000..d3cafa719239d8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-cfe_telmex_classification_finetuned_v3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English cfe_telmex_classification_finetuned_v3 SwinForImageClassification from JoseVilla
+author: John Snow Labs
+name: cfe_telmex_classification_finetuned_v3
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cfe_telmex_classification_finetuned_v3` is a English model originally trained by JoseVilla.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cfe_telmex_classification_finetuned_v3_en_5.5.1_3.0_1738095854222.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cfe_telmex_classification_finetuned_v3_en_5.5.1_3.0_1738095854222.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""cfe_telmex_classification_finetuned_v3","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("cfe_telmex_classification_finetuned_v3","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cfe_telmex_classification_finetuned_v3|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/JoseVilla/cfe-telmex-classification-finetuned-v3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-cfe_telmex_classification_finetuned_v3_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-cfe_telmex_classification_finetuned_v3_pipeline_en.md
new file mode 100644
index 00000000000000..d1fcd833bfb2d6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-cfe_telmex_classification_finetuned_v3_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English cfe_telmex_classification_finetuned_v3_pipeline pipeline SwinForImageClassification from JoseVilla
+author: John Snow Labs
+name: cfe_telmex_classification_finetuned_v3_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cfe_telmex_classification_finetuned_v3_pipeline` is a English model originally trained by JoseVilla.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cfe_telmex_classification_finetuned_v3_pipeline_en_5.5.1_3.0_1738095865469.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cfe_telmex_classification_finetuned_v3_pipeline_en_5.5.1_3.0_1738095865469.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("cfe_telmex_classification_finetuned_v3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cfe_telmex_classification_finetuned_v3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cfe_telmex_classification_finetuned_v3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/JoseVilla/cfe-telmex-classification-finetuned-v3
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-chilean_spanish_incivility_es.md b/docs/_posts/ahmedlone127/2025-01-28-chilean_spanish_incivility_es.md
new file mode 100644
index 00000000000000..a301c59f4f05d7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-chilean_spanish_incivility_es.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Castilian, Spanish chilean_spanish_incivility BertForSequenceClassification from jorgeortizfuentes
+author: John Snow Labs
+name: chilean_spanish_incivility
+date: 2025-01-28
+tags: [es, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: es
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`chilean_spanish_incivility` is a Castilian, Spanish model originally trained by jorgeortizfuentes.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/chilean_spanish_incivility_es_5.5.1_3.0_1738051996392.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/chilean_spanish_incivility_es_5.5.1_3.0_1738051996392.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("chilean_spanish_incivility","es") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("chilean_spanish_incivility", "es")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|chilean_spanish_incivility|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|es|
+|Size:|411.6 MB|
+
+## References
+
+https://huggingface.co/jorgeortizfuentes/chilean-spanish-incivility
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-chilean_spanish_incivility_pipeline_es.md b/docs/_posts/ahmedlone127/2025-01-28-chilean_spanish_incivility_pipeline_es.md
new file mode 100644
index 00000000000000..0502cfc33c7879
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-chilean_spanish_incivility_pipeline_es.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Castilian, Spanish chilean_spanish_incivility_pipeline pipeline BertForSequenceClassification from jorgeortizfuentes
+author: John Snow Labs
+name: chilean_spanish_incivility_pipeline
+date: 2025-01-28
+tags: [es, open_source, pipeline, onnx]
+task: Text Classification
+language: es
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`chilean_spanish_incivility_pipeline` is a Castilian, Spanish model originally trained by jorgeortizfuentes.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/chilean_spanish_incivility_pipeline_es_5.5.1_3.0_1738052017276.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/chilean_spanish_incivility_pipeline_es_5.5.1_3.0_1738052017276.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("chilean_spanish_incivility_pipeline", lang = "es")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("chilean_spanish_incivility_pipeline", lang = "es")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|chilean_spanish_incivility_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|es|
+|Size:|411.6 MB|
+
+## References
+
+https://huggingface.co/jorgeortizfuentes/chilean-spanish-incivility
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-chungli_ao_indicbert_news_en.md b/docs/_posts/ahmedlone127/2025-01-28-chungli_ao_indicbert_news_en.md
new file mode 100644
index 00000000000000..7ef12762850ddf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-chungli_ao_indicbert_news_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English chungli_ao_indicbert_news BertEmbeddings from N1ch0
+author: John Snow Labs
+name: chungli_ao_indicbert_news
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`chungli_ao_indicbert_news` is a English model originally trained by N1ch0.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/chungli_ao_indicbert_news_en_5.5.1_3.0_1738035494685.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/chungli_ao_indicbert_news_en_5.5.1_3.0_1738035494685.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("chungli_ao_indicbert_news","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("chungli_ao_indicbert_news","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|chungli_ao_indicbert_news|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/N1ch0/chungli-ao-IndicBERT-news
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-chungli_ao_indicbert_news_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-chungli_ao_indicbert_news_pipeline_en.md
new file mode 100644
index 00000000000000..5eb1d86db5251c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-chungli_ao_indicbert_news_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English chungli_ao_indicbert_news_pipeline pipeline BertEmbeddings from N1ch0
+author: John Snow Labs
+name: chungli_ao_indicbert_news_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`chungli_ao_indicbert_news_pipeline` is a English model originally trained by N1ch0.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/chungli_ao_indicbert_news_pipeline_en_5.5.1_3.0_1738035550507.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/chungli_ao_indicbert_news_pipeline_en_5.5.1_3.0_1738035550507.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("chungli_ao_indicbert_news_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("chungli_ao_indicbert_news_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|chungli_ao_indicbert_news_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/N1ch0/chungli-ao-IndicBERT-news
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-chungli_ao_mbert_news_en.md b/docs/_posts/ahmedlone127/2025-01-28-chungli_ao_mbert_news_en.md
new file mode 100644
index 00000000000000..aded3f4a8e5ec0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-chungli_ao_mbert_news_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English chungli_ao_mbert_news BertEmbeddings from N1ch0
+author: John Snow Labs
+name: chungli_ao_mbert_news
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`chungli_ao_mbert_news` is a English model originally trained by N1ch0.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/chungli_ao_mbert_news_en_5.5.1_3.0_1738057721274.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/chungli_ao_mbert_news_en_5.5.1_3.0_1738057721274.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("chungli_ao_mbert_news","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("chungli_ao_mbert_news","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|chungli_ao_mbert_news|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|665.0 MB|
+
+## References
+
+https://huggingface.co/N1ch0/chungli-ao-mBERT-news
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-chungli_ao_mbert_news_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-chungli_ao_mbert_news_pipeline_en.md
new file mode 100644
index 00000000000000..70829e7ed7c372
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-chungli_ao_mbert_news_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English chungli_ao_mbert_news_pipeline pipeline BertEmbeddings from N1ch0
+author: John Snow Labs
+name: chungli_ao_mbert_news_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`chungli_ao_mbert_news_pipeline` is a English model originally trained by N1ch0.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/chungli_ao_mbert_news_pipeline_en_5.5.1_3.0_1738057753671.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/chungli_ao_mbert_news_pipeline_en_5.5.1_3.0_1738057753671.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("chungli_ao_mbert_news_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("chungli_ao_mbert_news_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|chungli_ao_mbert_news_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|665.0 MB|
+
+## References
+
+https://huggingface.co/N1ch0/chungli-ao-mBERT-news
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-citation_parser_type_pipeline_xx.md b/docs/_posts/ahmedlone127/2025-01-28-citation_parser_type_pipeline_xx.md
new file mode 100644
index 00000000000000..189b1c1ff7eaad
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-citation_parser_type_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual citation_parser_type_pipeline pipeline DistilBertForSequenceClassification from SIRIS-Lab
+author: John Snow Labs
+name: citation_parser_type_pipeline
+date: 2025-01-28
+tags: [xx, open_source, pipeline, onnx]
+task: Text Classification
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`citation_parser_type_pipeline` is a Multilingual model originally trained by SIRIS-Lab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/citation_parser_type_pipeline_xx_5.5.1_3.0_1738025818513.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/citation_parser_type_pipeline_xx_5.5.1_3.0_1738025818513.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("citation_parser_type_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("citation_parser_type_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|citation_parser_type_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|507.6 MB|
+
+## References
+
+https://huggingface.co/SIRIS-Lab/citation-parser-TYPE
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-citation_parser_type_xx.md b/docs/_posts/ahmedlone127/2025-01-28-citation_parser_type_xx.md
new file mode 100644
index 00000000000000..a85042cb67adcf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-citation_parser_type_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual citation_parser_type DistilBertForSequenceClassification from SIRIS-Lab
+author: John Snow Labs
+name: citation_parser_type
+date: 2025-01-28
+tags: [xx, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`citation_parser_type` is a Multilingual model originally trained by SIRIS-Lab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/citation_parser_type_xx_5.5.1_3.0_1738025792469.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/citation_parser_type_xx_5.5.1_3.0_1738025792469.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("citation_parser_type","xx") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("citation_parser_type", "xx")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|citation_parser_type|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|xx|
+|Size:|507.6 MB|
+
+## References
+
+https://huggingface.co/SIRIS-Lab/citation-parser-TYPE
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-clasificacion1_idsv0_en.md b/docs/_posts/ahmedlone127/2025-01-28-clasificacion1_idsv0_en.md
new file mode 100644
index 00000000000000..fad38fd7ade68f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-clasificacion1_idsv0_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English clasificacion1_idsv0 SwinForImageClassification from BuroIdentidadDigital
+author: John Snow Labs
+name: clasificacion1_idsv0
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clasificacion1_idsv0` is a English model originally trained by BuroIdentidadDigital.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clasificacion1_idsv0_en_5.5.1_3.0_1738095812834.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clasificacion1_idsv0_en_5.5.1_3.0_1738095812834.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""clasificacion1_idsv0","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("clasificacion1_idsv0","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clasificacion1_idsv0|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/BuroIdentidadDigital/Clasificacion1_IdsV0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-clasificacion1_idsv0_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-clasificacion1_idsv0_pipeline_en.md
new file mode 100644
index 00000000000000..70846bef5bfc5d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-clasificacion1_idsv0_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English clasificacion1_idsv0_pipeline pipeline SwinForImageClassification from BuroIdentidadDigital
+author: John Snow Labs
+name: clasificacion1_idsv0_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clasificacion1_idsv0_pipeline` is a English model originally trained by BuroIdentidadDigital.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clasificacion1_idsv0_pipeline_en_5.5.1_3.0_1738095823519.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clasificacion1_idsv0_pipeline_en_5.5.1_3.0_1738095823519.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("clasificacion1_idsv0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("clasificacion1_idsv0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clasificacion1_idsv0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/BuroIdentidadDigital/Clasificacion1_IdsV0
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-classification_bert_danish_superior_en.md b/docs/_posts/ahmedlone127/2025-01-28-classification_bert_danish_superior_en.md
new file mode 100644
index 00000000000000..5e9d111e3a7ba1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-classification_bert_danish_superior_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English classification_bert_danish_superior DistilBertForSequenceClassification from cm309
+author: John Snow Labs
+name: classification_bert_danish_superior
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`classification_bert_danish_superior` is a English model originally trained by cm309.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/classification_bert_danish_superior_en_5.5.1_3.0_1738025450069.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/classification_bert_danish_superior_en_5.5.1_3.0_1738025450069.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("classification_bert_danish_superior","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("classification_bert_danish_superior", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|classification_bert_danish_superior|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/cm309/classification_bert_da_superior
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-classification_bert_danish_superior_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-classification_bert_danish_superior_pipeline_en.md
new file mode 100644
index 00000000000000..fbc14f0f29875b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-classification_bert_danish_superior_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English classification_bert_danish_superior_pipeline pipeline DistilBertForSequenceClassification from cm309
+author: John Snow Labs
+name: classification_bert_danish_superior_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`classification_bert_danish_superior_pipeline` is a English model originally trained by cm309.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/classification_bert_danish_superior_pipeline_en_5.5.1_3.0_1738025463087.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/classification_bert_danish_superior_pipeline_en_5.5.1_3.0_1738025463087.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("classification_bert_danish_superior_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("classification_bert_danish_superior_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|classification_bert_danish_superior_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/cm309/classification_bert_da_superior
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-clinicalbert_en.md b/docs/_posts/ahmedlone127/2025-01-28-clinicalbert_en.md
new file mode 100644
index 00000000000000..3f77646977c6a6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-clinicalbert_en.md
@@ -0,0 +1,96 @@
+---
+layout: model
+title: English clinicalbert DistilBertEmbeddings from DHEIVER
+author: John Snow Labs
+name: clinicalbert
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clinicalbert` is a English model originally trained by DHEIVER.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clinicalbert_en_5.5.1_3.0_1738096777344.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clinicalbert_en_5.5.1_3.0_1738096777344.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("clinicalbert","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("clinicalbert","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clinicalbert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|412.5 MB|
+
+## References
+
+References
+
+https://huggingface.co/DHEIVER/ClinicalBERT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-clinicalbert_finetuned_ner_en.md b/docs/_posts/ahmedlone127/2025-01-28-clinicalbert_finetuned_ner_en.md
new file mode 100644
index 00000000000000..2cebaa4f350305
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-clinicalbert_finetuned_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English clinicalbert_finetuned_ner BertForTokenClassification from MutazYoune
+author: John Snow Labs
+name: clinicalbert_finetuned_ner
+date: 2025-01-28
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clinicalbert_finetuned_ner` is a English model originally trained by MutazYoune.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clinicalbert_finetuned_ner_en_5.5.1_3.0_1738044960822.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clinicalbert_finetuned_ner_en_5.5.1_3.0_1738044960822.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("clinicalbert_finetuned_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("clinicalbert_finetuned_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clinicalbert_finetuned_ner|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.3 MB|
+
+## References
+
+https://huggingface.co/MutazYoune/ClinicalBERT-Finetuned-NER
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-clinicalbert_finetuned_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-clinicalbert_finetuned_ner_pipeline_en.md
new file mode 100644
index 00000000000000..cf914eb4358a08
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-clinicalbert_finetuned_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English clinicalbert_finetuned_ner_pipeline pipeline BertForTokenClassification from MutazYoune
+author: John Snow Labs
+name: clinicalbert_finetuned_ner_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clinicalbert_finetuned_ner_pipeline` is a English model originally trained by MutazYoune.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clinicalbert_finetuned_ner_pipeline_en_5.5.1_3.0_1738044980818.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clinicalbert_finetuned_ner_pipeline_en_5.5.1_3.0_1738044980818.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("clinicalbert_finetuned_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("clinicalbert_finetuned_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clinicalbert_finetuned_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.4 MB|
+
+## References
+
+https://huggingface.co/MutazYoune/ClinicalBERT-Finetuned-NER
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-clinicalbert_finetuned_philippine_languages_en.md b/docs/_posts/ahmedlone127/2025-01-28-clinicalbert_finetuned_philippine_languages_en.md
new file mode 100644
index 00000000000000..83c889f8c9007b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-clinicalbert_finetuned_philippine_languages_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English clinicalbert_finetuned_philippine_languages BertEmbeddings from MutazYoune
+author: John Snow Labs
+name: clinicalbert_finetuned_philippine_languages
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clinicalbert_finetuned_philippine_languages` is a English model originally trained by MutazYoune.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clinicalbert_finetuned_philippine_languages_en_5.5.1_3.0_1738098553768.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clinicalbert_finetuned_philippine_languages_en_5.5.1_3.0_1738098553768.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("clinicalbert_finetuned_philippine_languages","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("clinicalbert_finetuned_philippine_languages","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clinicalbert_finetuned_philippine_languages|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|403.3 MB|
+
+## References
+
+https://huggingface.co/MutazYoune/ClinicalBERT-Finetuned-PHI
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-clinicalbert_finetuned_philippine_languages_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-clinicalbert_finetuned_philippine_languages_pipeline_en.md
new file mode 100644
index 00000000000000..10f79b3717593b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-clinicalbert_finetuned_philippine_languages_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English clinicalbert_finetuned_philippine_languages_pipeline pipeline BertEmbeddings from MutazYoune
+author: John Snow Labs
+name: clinicalbert_finetuned_philippine_languages_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clinicalbert_finetuned_philippine_languages_pipeline` is a English model originally trained by MutazYoune.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clinicalbert_finetuned_philippine_languages_pipeline_en_5.5.1_3.0_1738098573728.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clinicalbert_finetuned_philippine_languages_pipeline_en_5.5.1_3.0_1738098573728.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("clinicalbert_finetuned_philippine_languages_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("clinicalbert_finetuned_philippine_languages_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clinicalbert_finetuned_philippine_languages_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.3 MB|
+
+## References
+
+https://huggingface.co/MutazYoune/ClinicalBERT-Finetuned-PHI
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-clinicalbert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-clinicalbert_pipeline_en.md
new file mode 100644
index 00000000000000..ff3eeb327db768
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-clinicalbert_pipeline_en.md
@@ -0,0 +1,72 @@
+---
+layout: model
+title: English clinicalbert_pipeline pipeline DistilBertEmbeddings from DHEIVER
+author: John Snow Labs
+name: clinicalbert_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clinicalbert_pipeline` is a English model originally trained by DHEIVER.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clinicalbert_pipeline_en_5.5.1_3.0_1738096801929.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clinicalbert_pipeline_en_5.5.1_3.0_1738096801929.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("clinicalbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("clinicalbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clinicalbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|412.5 MB|
+
+## References
+
+References
+
+https://huggingface.co/DHEIVER/ClinicalBERT
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-clip_softmax_bert_base_en.md b/docs/_posts/ahmedlone127/2025-01-28-clip_softmax_bert_base_en.md
new file mode 100644
index 00000000000000..89347e051f9c24
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-clip_softmax_bert_base_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English clip_softmax_bert_base BertEmbeddings from magicslabnu
+author: John Snow Labs
+name: clip_softmax_bert_base
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_softmax_bert_base` is a English model originally trained by magicslabnu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_softmax_bert_base_en_5.5.1_3.0_1738096260145.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_softmax_bert_base_en_5.5.1_3.0_1738096260145.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("clip_softmax_bert_base","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("clip_softmax_bert_base","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_softmax_bert_base|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|408.4 MB|
+
+## References
+
+https://huggingface.co/magicslabnu/clip_softmax_bert_base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-clip_softmax_bert_base_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-clip_softmax_bert_base_pipeline_en.md
new file mode 100644
index 00000000000000..63931f648b8861
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-clip_softmax_bert_base_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English clip_softmax_bert_base_pipeline pipeline BertEmbeddings from magicslabnu
+author: John Snow Labs
+name: clip_softmax_bert_base_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_softmax_bert_base_pipeline` is a English model originally trained by magicslabnu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clip_softmax_bert_base_pipeline_en_5.5.1_3.0_1738096280457.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_softmax_bert_base_pipeline_en_5.5.1_3.0_1738096280457.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("clip_softmax_bert_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("clip_softmax_bert_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_softmax_bert_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|408.4 MB|
+
+## References
+
+https://huggingface.co/magicslabnu/clip_softmax_bert_base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-cnn_news_summary_model_trained_on_reduced_data_nkadoor_en.md b/docs/_posts/ahmedlone127/2025-01-28-cnn_news_summary_model_trained_on_reduced_data_nkadoor_en.md
new file mode 100644
index 00000000000000..59a621ae2f5d5b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-cnn_news_summary_model_trained_on_reduced_data_nkadoor_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English cnn_news_summary_model_trained_on_reduced_data_nkadoor T5Transformer from nkadoor
+author: John Snow Labs
+name: cnn_news_summary_model_trained_on_reduced_data_nkadoor
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cnn_news_summary_model_trained_on_reduced_data_nkadoor` is a English model originally trained by nkadoor.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cnn_news_summary_model_trained_on_reduced_data_nkadoor_en_5.5.1_3.0_1738074385849.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cnn_news_summary_model_trained_on_reduced_data_nkadoor_en_5.5.1_3.0_1738074385849.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("cnn_news_summary_model_trained_on_reduced_data_nkadoor","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("cnn_news_summary_model_trained_on_reduced_data_nkadoor", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cnn_news_summary_model_trained_on_reduced_data_nkadoor|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|269.4 MB|
+
+## References
+
+https://huggingface.co/nkadoor/cnn_news_summary_model_trained_on_reduced_data
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-cnn_news_summary_model_trained_on_reduced_data_nkadoor_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-cnn_news_summary_model_trained_on_reduced_data_nkadoor_pipeline_en.md
new file mode 100644
index 00000000000000..c244f21f7272fe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-cnn_news_summary_model_trained_on_reduced_data_nkadoor_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English cnn_news_summary_model_trained_on_reduced_data_nkadoor_pipeline pipeline T5Transformer from nkadoor
+author: John Snow Labs
+name: cnn_news_summary_model_trained_on_reduced_data_nkadoor_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cnn_news_summary_model_trained_on_reduced_data_nkadoor_pipeline` is a English model originally trained by nkadoor.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cnn_news_summary_model_trained_on_reduced_data_nkadoor_pipeline_en_5.5.1_3.0_1738074402857.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cnn_news_summary_model_trained_on_reduced_data_nkadoor_pipeline_en_5.5.1_3.0_1738074402857.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("cnn_news_summary_model_trained_on_reduced_data_nkadoor_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cnn_news_summary_model_trained_on_reduced_data_nkadoor_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cnn_news_summary_model_trained_on_reduced_data_nkadoor_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|269.4 MB|
+
+## References
+
+https://huggingface.co/nkadoor/cnn_news_summary_model_trained_on_reduced_data
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-colbertgecko_en.md b/docs/_posts/ahmedlone127/2025-01-28-colbertgecko_en.md
new file mode 100644
index 00000000000000..c2c5110b55cfa6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-colbertgecko_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English colbertgecko BertEmbeddings from JoniJoniAl
+author: John Snow Labs
+name: colbertgecko
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`colbertgecko` is a English model originally trained by JoniJoniAl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/colbertgecko_en_5.5.1_3.0_1738084828873.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/colbertgecko_en_5.5.1_3.0_1738084828873.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("colbertgecko","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("colbertgecko","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|colbertgecko|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/JoniJoniAl/ColBERTGecko
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-colbertgecko_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-colbertgecko_pipeline_en.md
new file mode 100644
index 00000000000000..314875d95c0899
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-colbertgecko_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English colbertgecko_pipeline pipeline BertEmbeddings from JoniJoniAl
+author: John Snow Labs
+name: colbertgecko_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`colbertgecko_pipeline` is a English model originally trained by JoniJoniAl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/colbertgecko_pipeline_en_5.5.1_3.0_1738084849470.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/colbertgecko_pipeline_en_5.5.1_3.0_1738084849470.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("colbertgecko_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("colbertgecko_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|colbertgecko_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/JoniJoniAl/ColBERTGecko
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-content_en.md b/docs/_posts/ahmedlone127/2025-01-28-content_en.md
new file mode 100644
index 00000000000000..1fee697046303e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-content_en.md
@@ -0,0 +1,88 @@
+---
+layout: model
+title: English content DistilBertForQuestionAnswering from namnthust
+author: John Snow Labs
+name: content
+date: 2025-01-28
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`content` is a English model originally trained by namnthust.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/content_en_5.5.1_3.0_1738023472651.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/content_en_5.5.1_3.0_1738023472651.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("content","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("content", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|content|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+References
+
+https://huggingface.co/namnthust/content
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-content_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-content_pipeline_en.md
new file mode 100644
index 00000000000000..cba3fe372dbe81
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-content_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English content_pipeline pipeline DistilBertForQuestionAnswering from namnthust
+author: John Snow Labs
+name: content_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`content_pipeline` is a English model originally trained by namnthust.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/content_pipeline_en_5.5.1_3.0_1738023491797.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/content_pipeline_en_5.5.1_3.0_1738023491797.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("content_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("content_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|content_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+References
+
+https://huggingface.co/namnthust/content
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-convbert_base_turkish_mc4_cased_offensive_mlm_pipeline_tr.md b/docs/_posts/ahmedlone127/2025-01-28-convbert_base_turkish_mc4_cased_offensive_mlm_pipeline_tr.md
new file mode 100644
index 00000000000000..9f8313e18b0a95
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-convbert_base_turkish_mc4_cased_offensive_mlm_pipeline_tr.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Turkish convbert_base_turkish_mc4_cased_offensive_mlm_pipeline pipeline BertEmbeddings from Overfit-GM
+author: John Snow Labs
+name: convbert_base_turkish_mc4_cased_offensive_mlm_pipeline
+date: 2025-01-28
+tags: [tr, open_source, pipeline, onnx]
+task: Embeddings
+language: tr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`convbert_base_turkish_mc4_cased_offensive_mlm_pipeline` is a Turkish model originally trained by Overfit-GM.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/convbert_base_turkish_mc4_cased_offensive_mlm_pipeline_tr_5.5.1_3.0_1738035376697.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/convbert_base_turkish_mc4_cased_offensive_mlm_pipeline_tr_5.5.1_3.0_1738035376697.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("convbert_base_turkish_mc4_cased_offensive_mlm_pipeline", lang = "tr")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("convbert_base_turkish_mc4_cased_offensive_mlm_pipeline", lang = "tr")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|convbert_base_turkish_mc4_cased_offensive_mlm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|tr|
+|Size:|400.1 MB|
+
+## References
+
+https://huggingface.co/Overfit-GM/convbert-base-turkish-mc4-cased-offensive-mlm
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-convbert_base_turkish_mc4_cased_offensive_mlm_tr.md b/docs/_posts/ahmedlone127/2025-01-28-convbert_base_turkish_mc4_cased_offensive_mlm_tr.md
new file mode 100644
index 00000000000000..291f896962e68e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-convbert_base_turkish_mc4_cased_offensive_mlm_tr.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Turkish convbert_base_turkish_mc4_cased_offensive_mlm BertEmbeddings from Overfit-GM
+author: John Snow Labs
+name: convbert_base_turkish_mc4_cased_offensive_mlm
+date: 2025-01-28
+tags: [tr, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: tr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`convbert_base_turkish_mc4_cased_offensive_mlm` is a Turkish model originally trained by Overfit-GM.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/convbert_base_turkish_mc4_cased_offensive_mlm_tr_5.5.1_3.0_1738035353063.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/convbert_base_turkish_mc4_cased_offensive_mlm_tr_5.5.1_3.0_1738035353063.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("convbert_base_turkish_mc4_cased_offensive_mlm","tr") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("convbert_base_turkish_mc4_cased_offensive_mlm","tr") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|convbert_base_turkish_mc4_cased_offensive_mlm|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|tr|
+|Size:|400.0 MB|
+
+## References
+
+https://huggingface.co/Overfit-GM/convbert-base-turkish-mc4-cased-offensive-mlm
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-cotton_pests_en.md b/docs/_posts/ahmedlone127/2025-01-28-cotton_pests_en.md
new file mode 100644
index 00000000000000..d144702744808a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-cotton_pests_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English cotton_pests ViTForImageClassification from RohithN2004
+author: John Snow Labs
+name: cotton_pests
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cotton_pests` is a English model originally trained by RohithN2004.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cotton_pests_en_5.5.1_3.0_1738022899946.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cotton_pests_en_5.5.1_3.0_1738022899946.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""cotton_pests","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("cotton_pests","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cotton_pests|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/RohithN2004/Cotton-pests
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-cotton_pests_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-cotton_pests_pipeline_en.md
new file mode 100644
index 00000000000000..faee346d4d09f7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-cotton_pests_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English cotton_pests_pipeline pipeline ViTForImageClassification from RohithN2004
+author: John Snow Labs
+name: cotton_pests_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cotton_pests_pipeline` is a English model originally trained by RohithN2004.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cotton_pests_pipeline_en_5.5.1_3.0_1738022916193.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cotton_pests_pipeline_en_5.5.1_3.0_1738022916193.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("cotton_pests_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cotton_pests_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cotton_pests_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/RohithN2004/Cotton-pests
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-custom_kcbert_en.md b/docs/_posts/ahmedlone127/2025-01-28-custom_kcbert_en.md
new file mode 100644
index 00000000000000..7ffa5068e4eb9d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-custom_kcbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English custom_kcbert BertEmbeddings from fish9903
+author: John Snow Labs
+name: custom_kcbert
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`custom_kcbert` is a English model originally trained by fish9903.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/custom_kcbert_en_5.5.1_3.0_1738084485045.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/custom_kcbert_en_5.5.1_3.0_1738084485045.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("custom_kcbert","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("custom_kcbert","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|custom_kcbert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|406.2 MB|
+
+## References
+
+https://huggingface.co/fish9903/Custom-KcBERT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-custom_kcbert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-custom_kcbert_pipeline_en.md
new file mode 100644
index 00000000000000..6112c1d2c4a1cc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-custom_kcbert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English custom_kcbert_pipeline pipeline BertEmbeddings from fish9903
+author: John Snow Labs
+name: custom_kcbert_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`custom_kcbert_pipeline` is a English model originally trained by fish9903.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/custom_kcbert_pipeline_en_5.5.1_3.0_1738084511447.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/custom_kcbert_pipeline_en_5.5.1_3.0_1738084511447.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("custom_kcbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("custom_kcbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|custom_kcbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.2 MB|
+
+## References
+
+https://huggingface.co/fish9903/Custom-KcBERT
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-custom_t5_small_sbazar_merged_en.md b/docs/_posts/ahmedlone127/2025-01-28-custom_t5_small_sbazar_merged_en.md
new file mode 100644
index 00000000000000..1853c71c54da9c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-custom_t5_small_sbazar_merged_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English custom_t5_small_sbazar_merged T5Transformer from Sbazar
+author: John Snow Labs
+name: custom_t5_small_sbazar_merged
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`custom_t5_small_sbazar_merged` is a English model originally trained by Sbazar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/custom_t5_small_sbazar_merged_en_5.5.1_3.0_1738093888966.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/custom_t5_small_sbazar_merged_en_5.5.1_3.0_1738093888966.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("custom_t5_small_sbazar_merged","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("custom_t5_small_sbazar_merged", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|custom_t5_small_sbazar_merged|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|165.0 MB|
+
+## References
+
+https://huggingface.co/Sbazar/custom-t5-small-sbazar-merged
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-custom_t5_small_sbazar_merged_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-custom_t5_small_sbazar_merged_pipeline_en.md
new file mode 100644
index 00000000000000..8c391186558615
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-custom_t5_small_sbazar_merged_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English custom_t5_small_sbazar_merged_pipeline pipeline T5Transformer from Sbazar
+author: John Snow Labs
+name: custom_t5_small_sbazar_merged_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`custom_t5_small_sbazar_merged_pipeline` is a English model originally trained by Sbazar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/custom_t5_small_sbazar_merged_pipeline_en_5.5.1_3.0_1738093931999.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/custom_t5_small_sbazar_merged_pipeline_en_5.5.1_3.0_1738093931999.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("custom_t5_small_sbazar_merged_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("custom_t5_small_sbazar_merged_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|custom_t5_small_sbazar_merged_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|165.0 MB|
+
+## References
+
+https://huggingface.co/Sbazar/custom-t5-small-sbazar-merged
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-czech_ner_en.md b/docs/_posts/ahmedlone127/2025-01-28-czech_ner_en.md
new file mode 100644
index 00000000000000..207a3b16a5f5a5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-czech_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English czech_ner BertForTokenClassification from adenletchworth
+author: John Snow Labs
+name: czech_ner
+date: 2025-01-28
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`czech_ner` is a English model originally trained by adenletchworth.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/czech_ner_en_5.5.1_3.0_1738045374904.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/czech_ner_en_5.5.1_3.0_1738045374904.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("czech_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("czech_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|czech_ner|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/adenletchworth/CS-NER
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-czech_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-czech_ner_pipeline_en.md
new file mode 100644
index 00000000000000..b4d0b1dc1fb0e9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-czech_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English czech_ner_pipeline pipeline BertForTokenClassification from adenletchworth
+author: John Snow Labs
+name: czech_ner_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`czech_ner_pipeline` is a English model originally trained by adenletchworth.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/czech_ner_pipeline_en_5.5.1_3.0_1738045394840.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/czech_ner_pipeline_en_5.5.1_3.0_1738045394840.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("czech_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("czech_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|czech_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.8 MB|
+
+## References
+
+https://huggingface.co/adenletchworth/CS-NER
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-deberta_v3_base_mrpc_en.md b/docs/_posts/ahmedlone127/2025-01-28-deberta_v3_base_mrpc_en.md
new file mode 100644
index 00000000000000..26b818da283e59
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-deberta_v3_base_mrpc_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_base_mrpc DeBertaForSequenceClassification from cliang1453
+author: John Snow Labs
+name: deberta_v3_base_mrpc
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_mrpc` is a English model originally trained by cliang1453.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_mrpc_en_5.5.1_3.0_1738097704525.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_mrpc_en_5.5.1_3.0_1738097704525.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_base_mrpc","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_mrpc", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_mrpc|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|573.9 MB|
+
+## References
+
+https://huggingface.co/cliang1453/deberta-v3-base-mrpc
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-deberta_v3_base_mrpc_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-deberta_v3_base_mrpc_pipeline_en.md
new file mode 100644
index 00000000000000..ea7f3da0a1b8e5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-deberta_v3_base_mrpc_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_base_mrpc_pipeline pipeline DeBertaForSequenceClassification from cliang1453
+author: John Snow Labs
+name: deberta_v3_base_mrpc_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_mrpc_pipeline` is a English model originally trained by cliang1453.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_base_mrpc_pipeline_en_5.5.1_3.0_1738097778753.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_mrpc_pipeline_en_5.5.1_3.0_1738097778753.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_base_mrpc_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_base_mrpc_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_mrpc_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|573.9 MB|
+
+## References
+
+https://huggingface.co/cliang1453/deberta-v3-base-mrpc
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-deberta_v3_xsmall_mrpc_en.md b/docs/_posts/ahmedlone127/2025-01-28-deberta_v3_xsmall_mrpc_en.md
new file mode 100644
index 00000000000000..2edb66081bc63b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-deberta_v3_xsmall_mrpc_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_xsmall_mrpc DeBertaForSequenceClassification from cliang1453
+author: John Snow Labs
+name: deberta_v3_xsmall_mrpc
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_xsmall_mrpc` is a English model originally trained by cliang1453.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_mrpc_en_5.5.1_3.0_1738097659935.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_mrpc_en_5.5.1_3.0_1738097659935.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_xsmall_mrpc","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_xsmall_mrpc", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_xsmall_mrpc|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|207.9 MB|
+
+## References
+
+https://huggingface.co/cliang1453/deberta-v3-xsmall-mrpc
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-deberta_v3_xsmall_mrpc_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-deberta_v3_xsmall_mrpc_pipeline_en.md
new file mode 100644
index 00000000000000..199a2519ce5699
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-deberta_v3_xsmall_mrpc_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_xsmall_mrpc_pipeline pipeline DeBertaForSequenceClassification from cliang1453
+author: John Snow Labs
+name: deberta_v3_xsmall_mrpc_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_xsmall_mrpc_pipeline` is a English model originally trained by cliang1453.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_mrpc_pipeline_en_5.5.1_3.0_1738097692878.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_mrpc_pipeline_en_5.5.1_3.0_1738097692878.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("deberta_v3_xsmall_mrpc_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_xsmall_mrpc_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_xsmall_mrpc_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|207.9 MB|
+
+## References
+
+https://huggingface.co/cliang1453/deberta-v3-xsmall-mrpc
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-detoxifying_yt_en.md b/docs/_posts/ahmedlone127/2025-01-28-detoxifying_yt_en.md
new file mode 100644
index 00000000000000..697c65c17aad21
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-detoxifying_yt_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English detoxifying_yt BertForSequenceClassification from curlyoreki
+author: John Snow Labs
+name: detoxifying_yt
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`detoxifying_yt` is a English model originally trained by curlyoreki.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/detoxifying_yt_en_5.5.1_3.0_1738051393538.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/detoxifying_yt_en_5.5.1_3.0_1738051393538.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("detoxifying_yt","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("detoxifying_yt", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|detoxifying_yt|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/curlyoreki/detoxifying_yt
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-detoxifying_yt_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-detoxifying_yt_pipeline_en.md
new file mode 100644
index 00000000000000..a5221d4925c29b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-detoxifying_yt_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English detoxifying_yt_pipeline pipeline BertForSequenceClassification from curlyoreki
+author: John Snow Labs
+name: detoxifying_yt_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`detoxifying_yt_pipeline` is a English model originally trained by curlyoreki.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/detoxifying_yt_pipeline_en_5.5.1_3.0_1738051414126.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/detoxifying_yt_pipeline_en_5.5.1_3.0_1738051414126.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("detoxifying_yt_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("detoxifying_yt_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|detoxifying_yt_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/curlyoreki/detoxifying_yt
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-dhivehi_bert_mlm_en.md b/docs/_posts/ahmedlone127/2025-01-28-dhivehi_bert_mlm_en.md
new file mode 100644
index 00000000000000..a6eaf115ae7dec
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-dhivehi_bert_mlm_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dhivehi_bert_mlm BertEmbeddings from alakxender
+author: John Snow Labs
+name: dhivehi_bert_mlm
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dhivehi_bert_mlm` is a English model originally trained by alakxender.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dhivehi_bert_mlm_en_5.5.1_3.0_1738057306359.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dhivehi_bert_mlm_en_5.5.1_3.0_1738057306359.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("dhivehi_bert_mlm","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("dhivehi_bert_mlm","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dhivehi_bert_mlm|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|664.0 MB|
+
+## References
+
+https://huggingface.co/alakxender/dhivehi-bert-mlm
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-dhivehi_bert_mlm_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-dhivehi_bert_mlm_pipeline_en.md
new file mode 100644
index 00000000000000..780ee6f14a4bfa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-dhivehi_bert_mlm_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dhivehi_bert_mlm_pipeline pipeline BertEmbeddings from alakxender
+author: John Snow Labs
+name: dhivehi_bert_mlm_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dhivehi_bert_mlm_pipeline` is a English model originally trained by alakxender.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dhivehi_bert_mlm_pipeline_en_5.5.1_3.0_1738057339170.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dhivehi_bert_mlm_pipeline_en_5.5.1_3.0_1738057339170.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dhivehi_bert_mlm_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dhivehi_bert_mlm_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dhivehi_bert_mlm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|664.0 MB|
+
+## References
+
+https://huggingface.co/alakxender/dhivehi-bert-mlm
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-dialogpt_dailydialog_4_4_en.md b/docs/_posts/ahmedlone127/2025-01-28-dialogpt_dailydialog_4_4_en.md
new file mode 100644
index 00000000000000..97cac5b759250d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-dialogpt_dailydialog_4_4_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English dialogpt_dailydialog_4_4 GPT2Transformer from sebastiantrbl
+author: John Snow Labs
+name: dialogpt_dailydialog_4_4
+date: 2025-01-28
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dialogpt_dailydialog_4_4` is a English model originally trained by sebastiantrbl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dialogpt_dailydialog_4_4_en_5.5.1_3.0_1738041631741.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dialogpt_dailydialog_4_4_en_5.5.1_3.0_1738041631741.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("dialogpt_dailydialog_4_4","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("dialogpt_dailydialog_4_4","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dialogpt_dailydialog_4_4|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/sebastiantrbl/DialoGPT-dailydialog-4-4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-dialogpt_dailydialog_4_4_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-dialogpt_dailydialog_4_4_pipeline_en.md
new file mode 100644
index 00000000000000..fe38ccc8a2116c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-dialogpt_dailydialog_4_4_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English dialogpt_dailydialog_4_4_pipeline pipeline GPT2Transformer from sebastiantrbl
+author: John Snow Labs
+name: dialogpt_dailydialog_4_4_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dialogpt_dailydialog_4_4_pipeline` is a English model originally trained by sebastiantrbl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dialogpt_dailydialog_4_4_pipeline_en_5.5.1_3.0_1738041700078.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dialogpt_dailydialog_4_4_pipeline_en_5.5.1_3.0_1738041700078.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dialogpt_dailydialog_4_4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dialogpt_dailydialog_4_4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dialogpt_dailydialog_4_4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/sebastiantrbl/DialoGPT-dailydialog-4-4
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distil_bert_en.md b/docs/_posts/ahmedlone127/2025-01-28-distil_bert_en.md
new file mode 100644
index 00000000000000..c3fd81700c9f99
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distil_bert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distil_bert DistilBertForSequenceClassification from sakren
+author: John Snow Labs
+name: distil_bert
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distil_bert` is a English model originally trained by sakren.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distil_bert_en_5.5.1_3.0_1738077651975.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distil_bert_en_5.5.1_3.0_1738077651975.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distil_bert","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distil_bert", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distil_bert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/sakren/distil-bert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distil_bert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-distil_bert_pipeline_en.md
new file mode 100644
index 00000000000000..b43d4c5be16143
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distil_bert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distil_bert_pipeline pipeline DistilBertForSequenceClassification from sakren
+author: John Snow Labs
+name: distil_bert_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distil_bert_pipeline` is a English model originally trained by sakren.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distil_bert_pipeline_en_5.5.1_3.0_1738077664887.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distil_bert_pipeline_en_5.5.1_3.0_1738077664887.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distil_bert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distil_bert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distil_bert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/sakren/distil-bert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilbert_06_3_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilbert_06_3_en.md
new file mode 100644
index 00000000000000..c3b9d6c87663ef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilbert_06_3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_06_3 DistilBertForSequenceClassification from KalaiselvanD
+author: John Snow Labs
+name: distilbert_06_3
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_06_3` is a English model originally trained by KalaiselvanD.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_06_3_en_5.5.1_3.0_1738026211067.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_06_3_en_5.5.1_3.0_1738026211067.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_06_3","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_06_3", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_06_3|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/KalaiselvanD/distilbert_06_3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilbert_06_3_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilbert_06_3_pipeline_en.md
new file mode 100644
index 00000000000000..e808752c642fe0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilbert_06_3_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_06_3_pipeline pipeline DistilBertForSequenceClassification from KalaiselvanD
+author: John Snow Labs
+name: distilbert_06_3_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_06_3_pipeline` is a English model originally trained by KalaiselvanD.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_06_3_pipeline_en_5.5.1_3.0_1738026223733.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_06_3_pipeline_en_5.5.1_3.0_1738026223733.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_06_3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_06_3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_06_3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/KalaiselvanD/distilbert_06_3
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilbert_abstracts_mgt_detector_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilbert_abstracts_mgt_detector_en.md
new file mode 100644
index 00000000000000..fef4433aa96db2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilbert_abstracts_mgt_detector_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_abstracts_mgt_detector DistilBertForSequenceClassification from elozeiri
+author: John Snow Labs
+name: distilbert_abstracts_mgt_detector
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_abstracts_mgt_detector` is a English model originally trained by elozeiri.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_abstracts_mgt_detector_en_5.5.1_3.0_1738077895360.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_abstracts_mgt_detector_en_5.5.1_3.0_1738077895360.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_abstracts_mgt_detector","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_abstracts_mgt_detector", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_abstracts_mgt_detector|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/elozeiri/DistilBERT-Abstracts-MGT-Detector
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilbert_abstracts_mgt_detector_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilbert_abstracts_mgt_detector_pipeline_en.md
new file mode 100644
index 00000000000000..37969872f1a07d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilbert_abstracts_mgt_detector_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_abstracts_mgt_detector_pipeline pipeline DistilBertForSequenceClassification from elozeiri
+author: John Snow Labs
+name: distilbert_abstracts_mgt_detector_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_abstracts_mgt_detector_pipeline` is a English model originally trained by elozeiri.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_abstracts_mgt_detector_pipeline_en_5.5.1_3.0_1738077912142.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_abstracts_mgt_detector_pipeline_en_5.5.1_3.0_1738077912142.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_abstracts_mgt_detector_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_abstracts_mgt_detector_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_abstracts_mgt_detector_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/elozeiri/DistilBERT-Abstracts-MGT-Detector
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_adl_hw1_cwei13_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_adl_hw1_cwei13_en.md
new file mode 100644
index 00000000000000..43871f1d18cc93
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_adl_hw1_cwei13_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_adl_hw1_cwei13 DistilBertForSequenceClassification from cwei13
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_adl_hw1_cwei13
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_adl_hw1_cwei13` is a English model originally trained by cwei13.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_adl_hw1_cwei13_en_5.5.1_3.0_1738077634149.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_adl_hw1_cwei13_en_5.5.1_3.0_1738077634149.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_adl_hw1_cwei13","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_adl_hw1_cwei13", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_adl_hw1_cwei13|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|271.8 MB|
+
+## References
+
+https://huggingface.co/cwei13/distilbert-base-uncased-finetuned-adl_hw1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_adl_hw1_cwei13_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_adl_hw1_cwei13_pipeline_en.md
new file mode 100644
index 00000000000000..b2928fb9850289
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_adl_hw1_cwei13_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_adl_hw1_cwei13_pipeline pipeline DistilBertForSequenceClassification from cwei13
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_adl_hw1_cwei13_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_adl_hw1_cwei13_pipeline` is a English model originally trained by cwei13.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_adl_hw1_cwei13_pipeline_en_5.5.1_3.0_1738077648614.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_adl_hw1_cwei13_pipeline_en_5.5.1_3.0_1738077648614.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_adl_hw1_cwei13_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_adl_hw1_cwei13_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_adl_hw1_cwei13_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|271.8 MB|
+
+## References
+
+https://huggingface.co/cwei13/distilbert-base-uncased-finetuned-adl_hw1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_abhxaxhbshxahxn_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_abhxaxhbshxahxn_en.md
new file mode 100644
index 00000000000000..8afb1b9d557ee6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_abhxaxhbshxahxn_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_abhxaxhbshxahxn DistilBertForSequenceClassification from abhxaxhbshxahxn
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_abhxaxhbshxahxn
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_abhxaxhbshxahxn` is a English model originally trained by abhxaxhbshxahxn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_abhxaxhbshxahxn_en_5.5.1_3.0_1738077626301.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_abhxaxhbshxahxn_en_5.5.1_3.0_1738077626301.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_abhxaxhbshxahxn","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_abhxaxhbshxahxn", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_abhxaxhbshxahxn|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/abhxaxhbshxahxn/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_abhxaxhbshxahxn_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_abhxaxhbshxahxn_pipeline_en.md
new file mode 100644
index 00000000000000..8a363170f0161c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_abhxaxhbshxahxn_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_abhxaxhbshxahxn_pipeline pipeline DistilBertForSequenceClassification from abhxaxhbshxahxn
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_abhxaxhbshxahxn_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_abhxaxhbshxahxn_pipeline` is a English model originally trained by abhxaxhbshxahxn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_abhxaxhbshxahxn_pipeline_en_5.5.1_3.0_1738077638764.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_abhxaxhbshxahxn_pipeline_en_5.5.1_3.0_1738077638764.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_abhxaxhbshxahxn_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_abhxaxhbshxahxn_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_abhxaxhbshxahxn_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/abhxaxhbshxahxn/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_codelorhd_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_codelorhd_en.md
new file mode 100644
index 00000000000000..ee47483a3fa257
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_codelorhd_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_codelorhd DistilBertForSequenceClassification from codelorhd
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_codelorhd
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_codelorhd` is a English model originally trained by codelorhd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_codelorhd_en_5.5.1_3.0_1738077257589.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_codelorhd_en_5.5.1_3.0_1738077257589.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_codelorhd","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_codelorhd", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_codelorhd|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/codelorhd/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_codelorhd_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_codelorhd_pipeline_en.md
new file mode 100644
index 00000000000000..ee1b10a60fcf7e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_codelorhd_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_codelorhd_pipeline pipeline DistilBertForSequenceClassification from codelorhd
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_codelorhd_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_codelorhd_pipeline` is a English model originally trained by codelorhd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_codelorhd_pipeline_en_5.5.1_3.0_1738077272125.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_codelorhd_pipeline_en_5.5.1_3.0_1738077272125.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_codelorhd_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_codelorhd_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_codelorhd_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/codelorhd/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_ethan_ky_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_ethan_ky_pipeline_en.md
new file mode 100644
index 00000000000000..88f7f2998e013d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_ethan_ky_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_ethan_ky_pipeline pipeline DistilBertForSequenceClassification from ethan-ky
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_ethan_ky_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_ethan_ky_pipeline` is a English model originally trained by ethan-ky.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_ethan_ky_pipeline_en_5.5.1_3.0_1738077619614.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_ethan_ky_pipeline_en_5.5.1_3.0_1738077619614.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_ethan_ky_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_ethan_ky_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_ethan_ky_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/ethan-ky/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_hahaha121_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_hahaha121_en.md
new file mode 100644
index 00000000000000..19afb610e7bb41
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_hahaha121_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_hahaha121 DistilBertForSequenceClassification from hahaha121
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_hahaha121
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_hahaha121` is a English model originally trained by hahaha121.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_hahaha121_en_5.5.1_3.0_1738025322969.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_hahaha121_en_5.5.1_3.0_1738025322969.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_hahaha121","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_hahaha121", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_hahaha121|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/hahaha121/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_hahaha121_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_hahaha121_pipeline_en.md
new file mode 100644
index 00000000000000..cf54f62689d762
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_hahaha121_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_hahaha121_pipeline pipeline DistilBertForSequenceClassification from hahaha121
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_hahaha121_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_hahaha121_pipeline` is a English model originally trained by hahaha121.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_hahaha121_pipeline_en_5.5.1_3.0_1738025340995.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_hahaha121_pipeline_en_5.5.1_3.0_1738025340995.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_hahaha121_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_hahaha121_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_hahaha121_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/hahaha121/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_isowa_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_isowa_en.md
new file mode 100644
index 00000000000000..5889015b7f1b7c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_isowa_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_isowa DistilBertForSequenceClassification from isowa
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_isowa
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_isowa` is a English model originally trained by isowa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_isowa_en_5.5.1_3.0_1738077386926.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_isowa_en_5.5.1_3.0_1738077386926.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_isowa","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_isowa", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_isowa|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/isowa/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_isowa_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_isowa_pipeline_en.md
new file mode 100644
index 00000000000000..cc7167eeea0ee4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_isowa_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_isowa_pipeline pipeline DistilBertForSequenceClassification from isowa
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_isowa_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_isowa_pipeline` is a English model originally trained by isowa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_isowa_pipeline_en_5.5.1_3.0_1738077401587.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_isowa_pipeline_en_5.5.1_3.0_1738077401587.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_isowa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_isowa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_isowa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/isowa/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_mapless53_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_mapless53_en.md
new file mode 100644
index 00000000000000..381a1f514de8fc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_mapless53_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_mapless53 DistilBertForSequenceClassification from mapless53
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_mapless53
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_mapless53` is a English model originally trained by mapless53.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_mapless53_en_5.5.1_3.0_1738025641641.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_mapless53_en_5.5.1_3.0_1738025641641.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_mapless53","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_mapless53", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_mapless53|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/mapless53/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_mapless53_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_mapless53_pipeline_en.md
new file mode 100644
index 00000000000000..9fa207f1e52846
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_mapless53_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_mapless53_pipeline pipeline DistilBertForSequenceClassification from mapless53
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_mapless53_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_mapless53_pipeline` is a English model originally trained by mapless53.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_mapless53_pipeline_en_5.5.1_3.0_1738025654279.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_mapless53_pipeline_en_5.5.1_3.0_1738025654279.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_mapless53_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_mapless53_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_mapless53_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/mapless53/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_navdeeps350_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_navdeeps350_en.md
new file mode 100644
index 00000000000000..629582cb344056
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_navdeeps350_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_navdeeps350 DistilBertForSequenceClassification from navdeeps350
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_navdeeps350
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_navdeeps350` is a English model originally trained by navdeeps350.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_navdeeps350_en_5.5.1_3.0_1738077384192.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_navdeeps350_en_5.5.1_3.0_1738077384192.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_navdeeps350","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_navdeeps350", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_navdeeps350|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/navdeeps350/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_navdeeps350_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_navdeeps350_pipeline_en.md
new file mode 100644
index 00000000000000..71fbef57795699
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_navdeeps350_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_navdeeps350_pipeline pipeline DistilBertForSequenceClassification from navdeeps350
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_navdeeps350_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_navdeeps350_pipeline` is a English model originally trained by navdeeps350.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_navdeeps350_pipeline_en_5.5.1_3.0_1738077397662.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_navdeeps350_pipeline_en_5.5.1_3.0_1738077397662.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_navdeeps350_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_navdeeps350_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_navdeeps350_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.6 MB|
+
+## References
+
+https://huggingface.co/navdeeps350/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_osscar0131_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_osscar0131_en.md
new file mode 100644
index 00000000000000..44f36d850e8c9e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_osscar0131_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_osscar0131 DistilBertForSequenceClassification from osscar0131
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_osscar0131
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_osscar0131` is a English model originally trained by osscar0131.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_osscar0131_en_5.5.1_3.0_1738025756871.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_osscar0131_en_5.5.1_3.0_1738025756871.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_osscar0131","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_osscar0131", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_osscar0131|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/osscar0131/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_osscar0131_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_osscar0131_pipeline_en.md
new file mode 100644
index 00000000000000..fac5c1b9cb58fd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_osscar0131_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_osscar0131_pipeline pipeline DistilBertForSequenceClassification from osscar0131
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_osscar0131_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_osscar0131_pipeline` is a English model originally trained by osscar0131.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_osscar0131_pipeline_en_5.5.1_3.0_1738025769940.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_osscar0131_pipeline_en_5.5.1_3.0_1738025769940.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_osscar0131_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_osscar0131_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_osscar0131_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/osscar0131/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_robercg33_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_robercg33_en.md
new file mode 100644
index 00000000000000..afb4638945c93b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_robercg33_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_robercg33 DistilBertForSequenceClassification from robercg33
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_robercg33
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_robercg33` is a English model originally trained by robercg33.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_robercg33_en_5.5.1_3.0_1738077862223.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_robercg33_en_5.5.1_3.0_1738077862223.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_robercg33","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_robercg33", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_robercg33|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/robercg33/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_robercg33_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_robercg33_pipeline_en.md
new file mode 100644
index 00000000000000..2bac01d337475e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_robercg33_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_robercg33_pipeline pipeline DistilBertForSequenceClassification from robercg33
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_robercg33_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_robercg33_pipeline` is a English model originally trained by robercg33.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_robercg33_pipeline_en_5.5.1_3.0_1738077874803.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_robercg33_pipeline_en_5.5.1_3.0_1738077874803.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_robercg33_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_robercg33_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_robercg33_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/robercg33/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_tatsuya_n_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_tatsuya_n_en.md
new file mode 100644
index 00000000000000..4e07b21c72de36
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_tatsuya_n_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_tatsuya_n DistilBertForSequenceClassification from tatsuya-n
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_tatsuya_n
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_tatsuya_n` is a English model originally trained by tatsuya-n.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_tatsuya_n_en_5.5.1_3.0_1738077483934.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_tatsuya_n_en_5.5.1_3.0_1738077483934.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_tatsuya_n","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_tatsuya_n", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_tatsuya_n|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/tatsuya-n/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_tatsuya_n_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_tatsuya_n_pipeline_en.md
new file mode 100644
index 00000000000000..6ff25f4b1ef891
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_emotion_tatsuya_n_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_tatsuya_n_pipeline pipeline DistilBertForSequenceClassification from tatsuya-n
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_tatsuya_n_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_tatsuya_n_pipeline` is a English model originally trained by tatsuya-n.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_tatsuya_n_pipeline_en_5.5.1_3.0_1738077496981.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_tatsuya_n_pipeline_en_5.5.1_3.0_1738077496981.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_tatsuya_n_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_tatsuya_n_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_tatsuya_n_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/tatsuya-n/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_imdb_pandistellina_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_imdb_pandistellina_en.md
new file mode 100644
index 00000000000000..52042640969032
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_imdb_pandistellina_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_pandistellina DistilBertEmbeddings from Pandistellina
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_pandistellina
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_pandistellina` is a English model originally trained by Pandistellina.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_pandistellina_en_5.5.1_3.0_1738102023585.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_pandistellina_en_5.5.1_3.0_1738102023585.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_pandistellina","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_pandistellina","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_pandistellina|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Pandistellina/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_imdb_pandistellina_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_imdb_pandistellina_pipeline_en.md
new file mode 100644
index 00000000000000..38e8dbedce5ead
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_imdb_pandistellina_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_pandistellina_pipeline pipeline DistilBertEmbeddings from Pandistellina
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_pandistellina_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_pandistellina_pipeline` is a English model originally trained by Pandistellina.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_pandistellina_pipeline_en_5.5.1_3.0_1738102036512.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_pandistellina_pipeline_en_5.5.1_3.0_1738102036512.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_pandistellina_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_pandistellina_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_pandistellina_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Pandistellina/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_mnli_danipipe777_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_mnli_danipipe777_en.md
new file mode 100644
index 00000000000000..81e777127ad2ac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_mnli_danipipe777_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_mnli_danipipe777 DistilBertForSequenceClassification from Danipipe777
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_mnli_danipipe777
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_mnli_danipipe777` is a English model originally trained by Danipipe777.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_mnli_danipipe777_en_5.5.1_3.0_1738078188514.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_mnli_danipipe777_en_5.5.1_3.0_1738078188514.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_mnli_danipipe777","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_mnli_danipipe777", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_mnli_danipipe777|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Danipipe777/distilbert-base-uncased-finetuned-mnli
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_mnli_danipipe777_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_mnli_danipipe777_pipeline_en.md
new file mode 100644
index 00000000000000..0cd626af3b042d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_mnli_danipipe777_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_mnli_danipipe777_pipeline pipeline DistilBertForSequenceClassification from Danipipe777
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_mnli_danipipe777_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_mnli_danipipe777_pipeline` is a English model originally trained by Danipipe777.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_mnli_danipipe777_pipeline_en_5.5.1_3.0_1738078201138.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_mnli_danipipe777_pipeline_en_5.5.1_3.0_1738078201138.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_mnli_danipipe777_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_mnli_danipipe777_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_mnli_danipipe777_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Danipipe777/distilbert-base-uncased-finetuned-mnli
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_nostalgia_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_nostalgia_en.md
new file mode 100644
index 00000000000000..f9af66e2ed4ec1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_nostalgia_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_nostalgia DistilBertForSequenceClassification from beja1996
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_nostalgia
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_nostalgia` is a English model originally trained by beja1996.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_nostalgia_en_5.5.1_3.0_1738077788260.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_nostalgia_en_5.5.1_3.0_1738077788260.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_nostalgia","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_nostalgia", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_nostalgia|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/beja1996/distilbert-base-uncased_finetuned_nostalgia
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_nostalgia_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_nostalgia_pipeline_en.md
new file mode 100644
index 00000000000000..e4c3073e8ebe63
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_finetuned_nostalgia_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_nostalgia_pipeline pipeline DistilBertForSequenceClassification from beja1996
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_nostalgia_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_nostalgia_pipeline` is a English model originally trained by beja1996.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_nostalgia_pipeline_en_5.5.1_3.0_1738077801136.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_nostalgia_pipeline_en_5.5.1_3.0_1738077801136.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_nostalgia_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_nostalgia_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_nostalgia_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/beja1996/distilbert-base-uncased_finetuned_nostalgia
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_tripadvisor_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_tripadvisor_en.md
new file mode 100644
index 00000000000000..d07614a6d89c80
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_tripadvisor_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_tripadvisor DistilBertForSequenceClassification from KarlsonAV
+author: John Snow Labs
+name: distilbert_base_uncased_tripadvisor
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_tripadvisor` is a English model originally trained by KarlsonAV.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_tripadvisor_en_5.5.1_3.0_1738025516716.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_tripadvisor_en_5.5.1_3.0_1738025516716.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_tripadvisor","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_tripadvisor", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_tripadvisor|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/KarlsonAV/distilbert-base-uncased-tripadvisor
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_tripadvisor_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_tripadvisor_pipeline_en.md
new file mode 100644
index 00000000000000..6e5cba0a43a222
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilbert_base_uncased_tripadvisor_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_tripadvisor_pipeline pipeline DistilBertForSequenceClassification from KarlsonAV
+author: John Snow Labs
+name: distilbert_base_uncased_tripadvisor_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_tripadvisor_pipeline` is a English model originally trained by KarlsonAV.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_tripadvisor_pipeline_en_5.5.1_3.0_1738025529615.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_tripadvisor_pipeline_en_5.5.1_3.0_1738025529615.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_tripadvisor_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_tripadvisor_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_tripadvisor_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/KarlsonAV/distilbert-base-uncased-tripadvisor
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilbert_emotion_ademakyol_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilbert_emotion_ademakyol_en.md
new file mode 100644
index 00000000000000..8178033368fed1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilbert_emotion_ademakyol_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_emotion_ademakyol DistilBertForSequenceClassification from ademakyol
+author: John Snow Labs
+name: distilbert_emotion_ademakyol
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_emotion_ademakyol` is a English model originally trained by ademakyol.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_emotion_ademakyol_en_5.5.1_3.0_1738025193537.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_emotion_ademakyol_en_5.5.1_3.0_1738025193537.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_emotion_ademakyol","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_emotion_ademakyol", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_emotion_ademakyol|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/ademakyol/distilbert-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilbert_emotion_ademakyol_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilbert_emotion_ademakyol_pipeline_en.md
new file mode 100644
index 00000000000000..02c4e86b55dcac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilbert_emotion_ademakyol_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_emotion_ademakyol_pipeline pipeline DistilBertForSequenceClassification from ademakyol
+author: John Snow Labs
+name: distilbert_emotion_ademakyol_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_emotion_ademakyol_pipeline` is a English model originally trained by ademakyol.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_emotion_ademakyol_pipeline_en_5.5.1_3.0_1738025207400.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_emotion_ademakyol_pipeline_en_5.5.1_3.0_1738025207400.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_emotion_ademakyol_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_emotion_ademakyol_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_emotion_ademakyol_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/ademakyol/distilbert-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilbert_finetuned_ner_gustawb_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilbert_finetuned_ner_gustawb_en.md
new file mode 100644
index 00000000000000..83c2243f240802
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilbert_finetuned_ner_gustawb_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_finetuned_ner_gustawb DistilBertForTokenClassification from GustawB
+author: John Snow Labs
+name: distilbert_finetuned_ner_gustawb
+date: 2025-01-28
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetuned_ner_gustawb` is a English model originally trained by GustawB.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_ner_gustawb_en_5.5.1_3.0_1738101640519.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_ner_gustawb_en_5.5.1_3.0_1738101640519.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_finetuned_ner_gustawb","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_finetuned_ner_gustawb", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_finetuned_ner_gustawb|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/GustawB/distilbert-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilbert_finetuned_ner_gustawb_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilbert_finetuned_ner_gustawb_pipeline_en.md
new file mode 100644
index 00000000000000..e637adbe9e4a34
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilbert_finetuned_ner_gustawb_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_finetuned_ner_gustawb_pipeline pipeline DistilBertForTokenClassification from GustawB
+author: John Snow Labs
+name: distilbert_finetuned_ner_gustawb_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetuned_ner_gustawb_pipeline` is a English model originally trained by GustawB.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_ner_gustawb_pipeline_en_5.5.1_3.0_1738101653033.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_ner_gustawb_pipeline_en_5.5.1_3.0_1738101653033.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_finetuned_ner_gustawb_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_finetuned_ner_gustawb_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_finetuned_ner_gustawb_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/GustawB/distilbert-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilbert_imdb_sentiment_vojtam_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilbert_imdb_sentiment_vojtam_en.md
new file mode 100644
index 00000000000000..cb58687d558dc7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilbert_imdb_sentiment_vojtam_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_imdb_sentiment_vojtam DistilBertForSequenceClassification from vojtam
+author: John Snow Labs
+name: distilbert_imdb_sentiment_vojtam
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_imdb_sentiment_vojtam` is a English model originally trained by vojtam.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_imdb_sentiment_vojtam_en_5.5.1_3.0_1738077876985.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_imdb_sentiment_vojtam_en_5.5.1_3.0_1738077876985.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_imdb_sentiment_vojtam","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_imdb_sentiment_vojtam", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_imdb_sentiment_vojtam|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/vojtam/distilbert_imdb_sentiment
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilbert_imdb_sentiment_vojtam_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilbert_imdb_sentiment_vojtam_pipeline_en.md
new file mode 100644
index 00000000000000..bc857cd796d718
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilbert_imdb_sentiment_vojtam_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_imdb_sentiment_vojtam_pipeline pipeline DistilBertForSequenceClassification from vojtam
+author: John Snow Labs
+name: distilbert_imdb_sentiment_vojtam_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_imdb_sentiment_vojtam_pipeline` is a English model originally trained by vojtam.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_imdb_sentiment_vojtam_pipeline_en_5.5.1_3.0_1738077892494.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_imdb_sentiment_vojtam_pipeline_en_5.5.1_3.0_1738077892494.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_imdb_sentiment_vojtam_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_imdb_sentiment_vojtam_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_imdb_sentiment_vojtam_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/vojtam/distilbert_imdb_sentiment
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilbert_intent_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilbert_intent_en.md
new file mode 100644
index 00000000000000..55003f2030e977
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilbert_intent_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_intent DistilBertForSequenceClassification from dimcel
+author: John Snow Labs
+name: distilbert_intent
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_intent` is a English model originally trained by dimcel.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_intent_en_5.5.1_3.0_1738025935942.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_intent_en_5.5.1_3.0_1738025935942.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_intent","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_intent", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_intent|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/dimcel/distilbert_intent
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilbert_intent_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilbert_intent_pipeline_en.md
new file mode 100644
index 00000000000000..84893142167920
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilbert_intent_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_intent_pipeline pipeline DistilBertForSequenceClassification from dimcel
+author: John Snow Labs
+name: distilbert_intent_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_intent_pipeline` is a English model originally trained by dimcel.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_intent_pipeline_en_5.5.1_3.0_1738025948907.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_intent_pipeline_en_5.5.1_3.0_1738025948907.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_intent_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_intent_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_intent_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.6 MB|
+
+## References
+
+https://huggingface.co/dimcel/distilbert_intent
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilbert_make_believe16_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilbert_make_believe16_en.md
new file mode 100644
index 00000000000000..b2fc767cbf01c2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilbert_make_believe16_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_make_believe16 DistilBertForSequenceClassification from alberto-lorente
+author: John Snow Labs
+name: distilbert_make_believe16
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_make_believe16` is a English model originally trained by alberto-lorente.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_make_believe16_en_5.5.1_3.0_1738025193398.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_make_believe16_en_5.5.1_3.0_1738025193398.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_make_believe16","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_make_believe16", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_make_believe16|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/alberto-lorente/distilbert-make-believe16
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilbert_make_believe16_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilbert_make_believe16_pipeline_en.md
new file mode 100644
index 00000000000000..dc6058a762a707
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilbert_make_believe16_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_make_believe16_pipeline pipeline DistilBertForSequenceClassification from alberto-lorente
+author: John Snow Labs
+name: distilbert_make_believe16_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_make_believe16_pipeline` is a English model originally trained by alberto-lorente.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_make_believe16_pipeline_en_5.5.1_3.0_1738025211321.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_make_believe16_pipeline_en_5.5.1_3.0_1738025211321.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_make_believe16_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_make_believe16_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_make_believe16_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/alberto-lorente/distilbert-make-believe16
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilbert_scam_classifier_v1_3_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilbert_scam_classifier_v1_3_en.md
new file mode 100644
index 00000000000000..d131c83f3e83c1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilbert_scam_classifier_v1_3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_scam_classifier_v1_3 DistilBertForSequenceClassification from BothBosu
+author: John Snow Labs
+name: distilbert_scam_classifier_v1_3
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_scam_classifier_v1_3` is a English model originally trained by BothBosu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_scam_classifier_v1_3_en_5.5.1_3.0_1738077757877.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_scam_classifier_v1_3_en_5.5.1_3.0_1738077757877.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_scam_classifier_v1_3","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_scam_classifier_v1_3", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_scam_classifier_v1_3|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/BothBosu/distilbert-scam-classifier-v1.3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilbert_scam_classifier_v1_3_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilbert_scam_classifier_v1_3_pipeline_en.md
new file mode 100644
index 00000000000000..2ef9a9bcaf847e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilbert_scam_classifier_v1_3_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_scam_classifier_v1_3_pipeline pipeline DistilBertForSequenceClassification from BothBosu
+author: John Snow Labs
+name: distilbert_scam_classifier_v1_3_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_scam_classifier_v1_3_pipeline` is a English model originally trained by BothBosu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_scam_classifier_v1_3_pipeline_en_5.5.1_3.0_1738077770511.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_scam_classifier_v1_3_pipeline_en_5.5.1_3.0_1738077770511.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_scam_classifier_v1_3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_scam_classifier_v1_3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_scam_classifier_v1_3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/BothBosu/distilbert-scam-classifier-v1.3
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilbert_scam_classifier_v1_4_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilbert_scam_classifier_v1_4_en.md
new file mode 100644
index 00000000000000..2aafb4eb5d5a67
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilbert_scam_classifier_v1_4_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_scam_classifier_v1_4 DistilBertForSequenceClassification from BothBosu
+author: John Snow Labs
+name: distilbert_scam_classifier_v1_4
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_scam_classifier_v1_4` is a English model originally trained by BothBosu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_scam_classifier_v1_4_en_5.5.1_3.0_1738025324319.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_scam_classifier_v1_4_en_5.5.1_3.0_1738025324319.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_scam_classifier_v1_4","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_scam_classifier_v1_4", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_scam_classifier_v1_4|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/BothBosu/distilbert-scam-classifier-v1.4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilbert_scam_classifier_v1_4_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilbert_scam_classifier_v1_4_pipeline_en.md
new file mode 100644
index 00000000000000..2d205f3e4a08b6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilbert_scam_classifier_v1_4_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_scam_classifier_v1_4_pipeline pipeline DistilBertForSequenceClassification from BothBosu
+author: John Snow Labs
+name: distilbert_scam_classifier_v1_4_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_scam_classifier_v1_4_pipeline` is a English model originally trained by BothBosu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_scam_classifier_v1_4_pipeline_en_5.5.1_3.0_1738025340804.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_scam_classifier_v1_4_pipeline_en_5.5.1_3.0_1738025340804.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_scam_classifier_v1_4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_scam_classifier_v1_4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_scam_classifier_v1_4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/BothBosu/distilbert-scam-classifier-v1.4
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilbert_sensitive_classification_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilbert_sensitive_classification_en.md
new file mode 100644
index 00000000000000..bab91dfbdeeffe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilbert_sensitive_classification_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_sensitive_classification DistilBertForSequenceClassification from Sharpaxis
+author: John Snow Labs
+name: distilbert_sensitive_classification
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_sensitive_classification` is a English model originally trained by Sharpaxis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_sensitive_classification_en_5.5.1_3.0_1738078013022.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_sensitive_classification_en_5.5.1_3.0_1738078013022.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_sensitive_classification","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_sensitive_classification", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_sensitive_classification|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Sharpaxis/distilbert-sensitive-classification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilbert_sensitive_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilbert_sensitive_classification_pipeline_en.md
new file mode 100644
index 00000000000000..3785f41edbcfd5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilbert_sensitive_classification_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_sensitive_classification_pipeline pipeline DistilBertForSequenceClassification from Sharpaxis
+author: John Snow Labs
+name: distilbert_sensitive_classification_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_sensitive_classification_pipeline` is a English model originally trained by Sharpaxis.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_sensitive_classification_pipeline_en_5.5.1_3.0_1738078025682.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_sensitive_classification_pipeline_en_5.5.1_3.0_1738078025682.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_sensitive_classification_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_sensitive_classification_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_sensitive_classification_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Sharpaxis/distilbert-sensitive-classification
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distill_scibert_scivocab_uncased_en.md b/docs/_posts/ahmedlone127/2025-01-28-distill_scibert_scivocab_uncased_en.md
new file mode 100644
index 00000000000000..21126025128687
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distill_scibert_scivocab_uncased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distill_scibert_scivocab_uncased BertEmbeddings from Chega
+author: John Snow Labs
+name: distill_scibert_scivocab_uncased
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distill_scibert_scivocab_uncased` is a English model originally trained by Chega.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distill_scibert_scivocab_uncased_en_5.5.1_3.0_1738034748705.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distill_scibert_scivocab_uncased_en_5.5.1_3.0_1738034748705.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("distill_scibert_scivocab_uncased","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("distill_scibert_scivocab_uncased","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distill_scibert_scivocab_uncased|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|45.8 MB|
+
+## References
+
+https://huggingface.co/Chega/distill-scibert_scivocab_uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distill_scibert_scivocab_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-distill_scibert_scivocab_uncased_pipeline_en.md
new file mode 100644
index 00000000000000..b567a3216a5b70
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distill_scibert_scivocab_uncased_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distill_scibert_scivocab_uncased_pipeline pipeline BertEmbeddings from Chega
+author: John Snow Labs
+name: distill_scibert_scivocab_uncased_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distill_scibert_scivocab_uncased_pipeline` is a English model originally trained by Chega.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distill_scibert_scivocab_uncased_pipeline_en_5.5.1_3.0_1738034750947.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distill_scibert_scivocab_uncased_pipeline_en_5.5.1_3.0_1738034750947.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distill_scibert_scivocab_uncased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distill_scibert_scivocab_uncased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distill_scibert_scivocab_uncased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|45.8 MB|
+
+## References
+
+https://huggingface.co/Chega/distill-scibert_scivocab_uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilroberta_base_ft_prolife_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilroberta_base_ft_prolife_en.md
new file mode 100644
index 00000000000000..b78ca83f0cd4e1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilroberta_base_ft_prolife_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilroberta_base_ft_prolife RoBertaEmbeddings from jkruk
+author: John Snow Labs
+name: distilroberta_base_ft_prolife
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_ft_prolife` is a English model originally trained by jkruk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_base_ft_prolife_en_5.5.1_3.0_1738103438402.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_ft_prolife_en_5.5.1_3.0_1738103438402.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("distilroberta_base_ft_prolife","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("distilroberta_base_ft_prolife","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_base_ft_prolife|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/jkruk/distilroberta-base-ft-prolife
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilroberta_base_ft_prolife_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilroberta_base_ft_prolife_pipeline_en.md
new file mode 100644
index 00000000000000..49221ee9e73894
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilroberta_base_ft_prolife_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilroberta_base_ft_prolife_pipeline pipeline RoBertaEmbeddings from jkruk
+author: John Snow Labs
+name: distilroberta_base_ft_prolife_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_ft_prolife_pipeline` is a English model originally trained by jkruk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_base_ft_prolife_pipeline_en_5.5.1_3.0_1738103453725.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_ft_prolife_pipeline_en_5.5.1_3.0_1738103453725.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilroberta_base_ft_prolife_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilroberta_base_ft_prolife_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_base_ft_prolife_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/jkruk/distilroberta-base-ft-prolife
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilroberta_base_ft_walkaway_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilroberta_base_ft_walkaway_en.md
new file mode 100644
index 00000000000000..46a9165e1a99d7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilroberta_base_ft_walkaway_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilroberta_base_ft_walkaway RoBertaEmbeddings from jkruk
+author: John Snow Labs
+name: distilroberta_base_ft_walkaway
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_ft_walkaway` is a English model originally trained by jkruk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_base_ft_walkaway_en_5.5.1_3.0_1738102991938.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_ft_walkaway_en_5.5.1_3.0_1738102991938.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("distilroberta_base_ft_walkaway","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("distilroberta_base_ft_walkaway","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_base_ft_walkaway|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/jkruk/distilroberta-base-ft-walkaway
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-distilroberta_base_ft_walkaway_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-distilroberta_base_ft_walkaway_pipeline_en.md
new file mode 100644
index 00000000000000..ac47fd8ab6a431
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-distilroberta_base_ft_walkaway_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilroberta_base_ft_walkaway_pipeline pipeline RoBertaEmbeddings from jkruk
+author: John Snow Labs
+name: distilroberta_base_ft_walkaway_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_ft_walkaway_pipeline` is a English model originally trained by jkruk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_base_ft_walkaway_pipeline_en_5.5.1_3.0_1738103007039.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_ft_walkaway_pipeline_en_5.5.1_3.0_1738103007039.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilroberta_base_ft_walkaway_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilroberta_base_ft_walkaway_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_base_ft_walkaway_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/jkruk/distilroberta-base-ft-walkaway
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-dottor_spatalo_en.md b/docs/_posts/ahmedlone127/2025-01-28-dottor_spatalo_en.md
new file mode 100644
index 00000000000000..34b50fee3792af
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-dottor_spatalo_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dottor_spatalo DistilBertForSequenceClassification from massimoambrosini
+author: John Snow Labs
+name: dottor_spatalo
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dottor_spatalo` is a English model originally trained by massimoambrosini.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dottor_spatalo_en_5.5.1_3.0_1738026104637.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dottor_spatalo_en_5.5.1_3.0_1738026104637.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("dottor_spatalo","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("dottor_spatalo", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dottor_spatalo|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/massimoambrosini/dottor_spatalo
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-dottor_spatalo_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-dottor_spatalo_pipeline_en.md
new file mode 100644
index 00000000000000..636e54bffcb660
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-dottor_spatalo_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dottor_spatalo_pipeline pipeline DistilBertForSequenceClassification from massimoambrosini
+author: John Snow Labs
+name: dottor_spatalo_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dottor_spatalo_pipeline` is a English model originally trained by massimoambrosini.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dottor_spatalo_pipeline_en_5.5.1_3.0_1738026117676.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dottor_spatalo_pipeline_en_5.5.1_3.0_1738026117676.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dottor_spatalo_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dottor_spatalo_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dottor_spatalo_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/massimoambrosini/dottor_spatalo
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-dummy_model_1_en.md b/docs/_posts/ahmedlone127/2025-01-28-dummy_model_1_en.md
new file mode 100644
index 00000000000000..63588bea8ff5f0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-dummy_model_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_1 BertEmbeddings from AbdullahMahmoud
+author: John Snow Labs
+name: dummy_model_1
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_1` is a English model originally trained by AbdullahMahmoud.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_1_en_5.5.1_3.0_1738084401849.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_1_en_5.5.1_3.0_1738084401849.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("dummy_model_1","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("dummy_model_1","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/AbdullahMahmoud/dummy-model-1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-dummy_model_1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-dummy_model_1_pipeline_en.md
new file mode 100644
index 00000000000000..0694f34b1f6fa1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-dummy_model_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_1_pipeline pipeline BertEmbeddings from AbdullahMahmoud
+author: John Snow Labs
+name: dummy_model_1_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_1_pipeline` is a English model originally trained by AbdullahMahmoud.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_1_pipeline_en_5.5.1_3.0_1738084422390.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_1_pipeline_en_5.5.1_3.0_1738084422390.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/AbdullahMahmoud/dummy-model-1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-dummy_model_bigbroo_en.md b/docs/_posts/ahmedlone127/2025-01-28-dummy_model_bigbroo_en.md
new file mode 100644
index 00000000000000..127b273082c9fc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-dummy_model_bigbroo_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_bigbroo BertEmbeddings from BigBroo
+author: John Snow Labs
+name: dummy_model_bigbroo
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_bigbroo` is a English model originally trained by BigBroo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_bigbroo_en_5.5.1_3.0_1738084708871.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_bigbroo_en_5.5.1_3.0_1738084708871.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("dummy_model_bigbroo","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("dummy_model_bigbroo","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_bigbroo|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/BigBroo/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-dummy_model_bigbroo_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-dummy_model_bigbroo_pipeline_en.md
new file mode 100644
index 00000000000000..28aa5eda0115c4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-dummy_model_bigbroo_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_bigbroo_pipeline pipeline BertEmbeddings from BigBroo
+author: John Snow Labs
+name: dummy_model_bigbroo_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_bigbroo_pipeline` is a English model originally trained by BigBroo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_bigbroo_pipeline_en_5.5.1_3.0_1738084730063.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_bigbroo_pipeline_en_5.5.1_3.0_1738084730063.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_bigbroo_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_bigbroo_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_bigbroo_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/BigBroo/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-dummy_model_sleepless_cat_en.md b/docs/_posts/ahmedlone127/2025-01-28-dummy_model_sleepless_cat_en.md
new file mode 100644
index 00000000000000..e837c9f3e886d8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-dummy_model_sleepless_cat_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_sleepless_cat BertEmbeddings from sleepless-cat
+author: John Snow Labs
+name: dummy_model_sleepless_cat
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_sleepless_cat` is a English model originally trained by sleepless-cat.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_sleepless_cat_en_5.5.1_3.0_1738057512344.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_sleepless_cat_en_5.5.1_3.0_1738057512344.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("dummy_model_sleepless_cat","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("dummy_model_sleepless_cat","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_sleepless_cat|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|16.7 MB|
+
+## References
+
+https://huggingface.co/sleepless-cat/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-dummy_model_sleepless_cat_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-dummy_model_sleepless_cat_pipeline_en.md
new file mode 100644
index 00000000000000..bf467207f98a3b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-dummy_model_sleepless_cat_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_sleepless_cat_pipeline pipeline BertEmbeddings from sleepless-cat
+author: John Snow Labs
+name: dummy_model_sleepless_cat_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_sleepless_cat_pipeline` is a English model originally trained by sleepless-cat.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_sleepless_cat_pipeline_en_5.5.1_3.0_1738057513486.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_sleepless_cat_pipeline_en_5.5.1_3.0_1738057513486.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_sleepless_cat_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_sleepless_cat_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_sleepless_cat_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|16.7 MB|
+
+## References
+
+https://huggingface.co/sleepless-cat/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-dutch_query2rest_api_call_en.md b/docs/_posts/ahmedlone127/2025-01-28-dutch_query2rest_api_call_en.md
new file mode 100644
index 00000000000000..fb2b67d969195f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-dutch_query2rest_api_call_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English dutch_query2rest_api_call T5Transformer from mezanass
+author: John Snow Labs
+name: dutch_query2rest_api_call
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dutch_query2rest_api_call` is a English model originally trained by mezanass.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dutch_query2rest_api_call_en_5.5.1_3.0_1738073908733.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dutch_query2rest_api_call_en_5.5.1_3.0_1738073908733.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("dutch_query2rest_api_call","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("dutch_query2rest_api_call", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dutch_query2rest_api_call|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|473.5 MB|
+
+## References
+
+https://huggingface.co/mezanass/nl_query2REST_API_call
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-dutch_query2rest_api_call_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-dutch_query2rest_api_call_pipeline_en.md
new file mode 100644
index 00000000000000..d1134d05fa4733
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-dutch_query2rest_api_call_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English dutch_query2rest_api_call_pipeline pipeline T5Transformer from mezanass
+author: John Snow Labs
+name: dutch_query2rest_api_call_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dutch_query2rest_api_call_pipeline` is a English model originally trained by mezanass.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dutch_query2rest_api_call_pipeline_en_5.5.1_3.0_1738074062743.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dutch_query2rest_api_call_pipeline_en_5.5.1_3.0_1738074062743.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dutch_query2rest_api_call_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dutch_query2rest_api_call_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dutch_query2rest_api_call_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|473.5 MB|
+
+## References
+
+https://huggingface.co/mezanass/nl_query2REST_API_call
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-electrical_classification_distilbert_base_en.md b/docs/_posts/ahmedlone127/2025-01-28-electrical_classification_distilbert_base_en.md
new file mode 100644
index 00000000000000..ee9a2d8caf28b4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-electrical_classification_distilbert_base_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English electrical_classification_distilbert_base DistilBertForSequenceClassification from disham993
+author: John Snow Labs
+name: electrical_classification_distilbert_base
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`electrical_classification_distilbert_base` is a English model originally trained by disham993.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electrical_classification_distilbert_base_en_5.5.1_3.0_1738026207823.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electrical_classification_distilbert_base_en_5.5.1_3.0_1738026207823.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("electrical_classification_distilbert_base","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("electrical_classification_distilbert_base", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electrical_classification_distilbert_base|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/disham993/electrical-classification-distilbert-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-electrical_classification_distilbert_base_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-electrical_classification_distilbert_base_pipeline_en.md
new file mode 100644
index 00000000000000..de17751a99a8ac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-electrical_classification_distilbert_base_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English electrical_classification_distilbert_base_pipeline pipeline DistilBertForSequenceClassification from disham993
+author: John Snow Labs
+name: electrical_classification_distilbert_base_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`electrical_classification_distilbert_base_pipeline` is a English model originally trained by disham993.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/electrical_classification_distilbert_base_pipeline_en_5.5.1_3.0_1738026220545.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electrical_classification_distilbert_base_pipeline_en_5.5.1_3.0_1738026220545.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("electrical_classification_distilbert_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("electrical_classification_distilbert_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electrical_classification_distilbert_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/disham993/electrical-classification-distilbert-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-emotionverse_en.md b/docs/_posts/ahmedlone127/2025-01-28-emotionverse_en.md
new file mode 100644
index 00000000000000..3713e4623ea595
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-emotionverse_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English emotionverse BertForSequenceClassification from ayjays132
+author: John Snow Labs
+name: emotionverse
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`emotionverse` is a English model originally trained by ayjays132.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/emotionverse_en_5.5.1_3.0_1738100601090.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/emotionverse_en_5.5.1_3.0_1738100601090.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("emotionverse","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("emotionverse", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|emotionverse|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|414.9 MB|
+
+## References
+
+https://huggingface.co/ayjays132/EmotionVerse
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-emotionverse_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-emotionverse_pipeline_en.md
new file mode 100644
index 00000000000000..7ee31b57a9f7d6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-emotionverse_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English emotionverse_pipeline pipeline BertForSequenceClassification from ayjays132
+author: John Snow Labs
+name: emotionverse_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`emotionverse_pipeline` is a English model originally trained by ayjays132.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/emotionverse_pipeline_en_5.5.1_3.0_1738100622198.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/emotionverse_pipeline_en_5.5.1_3.0_1738100622198.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("emotionverse_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("emotionverse_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|emotionverse_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|414.9 MB|
+
+## References
+
+https://huggingface.co/ayjays132/EmotionVerse
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-english_afrikaans_sql_training_1727527893_af.md b/docs/_posts/ahmedlone127/2025-01-28-english_afrikaans_sql_training_1727527893_af.md
new file mode 100644
index 00000000000000..305de9caffd928
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-english_afrikaans_sql_training_1727527893_af.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Afrikaans english_afrikaans_sql_training_1727527893 T5Transformer from JsteReubsSoftware
+author: John Snow Labs
+name: english_afrikaans_sql_training_1727527893
+date: 2025-01-28
+tags: [af, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: af
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_afrikaans_sql_training_1727527893` is a Afrikaans model originally trained by JsteReubsSoftware.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/english_afrikaans_sql_training_1727527893_af_5.5.1_3.0_1738032579205.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_afrikaans_sql_training_1727527893_af_5.5.1_3.0_1738032579205.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("english_afrikaans_sql_training_1727527893","af") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("english_afrikaans_sql_training_1727527893", "af")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|english_afrikaans_sql_training_1727527893|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|af|
+|Size:|147.7 MB|
+
+## References
+
+https://huggingface.co/JsteReubsSoftware/en-af-sql-training-1727527893
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-english_afrikaans_sql_training_1727527893_pipeline_af.md b/docs/_posts/ahmedlone127/2025-01-28-english_afrikaans_sql_training_1727527893_pipeline_af.md
new file mode 100644
index 00000000000000..5afcffd8cdcd4a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-english_afrikaans_sql_training_1727527893_pipeline_af.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Afrikaans english_afrikaans_sql_training_1727527893_pipeline pipeline T5Transformer from JsteReubsSoftware
+author: John Snow Labs
+name: english_afrikaans_sql_training_1727527893_pipeline
+date: 2025-01-28
+tags: [af, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: af
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_afrikaans_sql_training_1727527893_pipeline` is a Afrikaans model originally trained by JsteReubsSoftware.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/english_afrikaans_sql_training_1727527893_pipeline_af_5.5.1_3.0_1738032626187.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_afrikaans_sql_training_1727527893_pipeline_af_5.5.1_3.0_1738032626187.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("english_afrikaans_sql_training_1727527893_pipeline", lang = "af")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("english_afrikaans_sql_training_1727527893_pipeline", lang = "af")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|english_afrikaans_sql_training_1727527893_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|af|
+|Size:|147.7 MB|
+
+## References
+
+https://huggingface.co/JsteReubsSoftware/en-af-sql-training-1727527893
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-eowyn_gpt2_medium_x777_en.md b/docs/_posts/ahmedlone127/2025-01-28-eowyn_gpt2_medium_x777_en.md
new file mode 100644
index 00000000000000..70712e3b7f1651
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-eowyn_gpt2_medium_x777_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English eowyn_gpt2_medium_x777 GPT2Transformer from stanford-crfm
+author: John Snow Labs
+name: eowyn_gpt2_medium_x777
+date: 2025-01-28
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`eowyn_gpt2_medium_x777` is a English model originally trained by stanford-crfm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/eowyn_gpt2_medium_x777_en_5.5.1_3.0_1738043190206.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/eowyn_gpt2_medium_x777_en_5.5.1_3.0_1738043190206.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("eowyn_gpt2_medium_x777","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("eowyn_gpt2_medium_x777","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|eowyn_gpt2_medium_x777|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|852.3 MB|
+
+## References
+
+https://huggingface.co/stanford-crfm/eowyn-gpt2-medium-x777
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-eowyn_gpt2_medium_x777_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-eowyn_gpt2_medium_x777_pipeline_en.md
new file mode 100644
index 00000000000000..8e759859c17ba0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-eowyn_gpt2_medium_x777_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English eowyn_gpt2_medium_x777_pipeline pipeline GPT2Transformer from stanford-crfm
+author: John Snow Labs
+name: eowyn_gpt2_medium_x777_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`eowyn_gpt2_medium_x777_pipeline` is a English model originally trained by stanford-crfm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/eowyn_gpt2_medium_x777_pipeline_en_5.5.1_3.0_1738043424504.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/eowyn_gpt2_medium_x777_pipeline_en_5.5.1_3.0_1738043424504.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("eowyn_gpt2_medium_x777_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("eowyn_gpt2_medium_x777_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|eowyn_gpt2_medium_x777_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|852.3 MB|
+
+## References
+
+https://huggingface.co/stanford-crfm/eowyn-gpt2-medium-x777
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-esgi_vchhauv_nlp_en.md b/docs/_posts/ahmedlone127/2025-01-28-esgi_vchhauv_nlp_en.md
new file mode 100644
index 00000000000000..27a723e8bd7476
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-esgi_vchhauv_nlp_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English esgi_vchhauv_nlp CamemBertForTokenClassification from Snoirak
+author: John Snow Labs
+name: esgi_vchhauv_nlp
+date: 2025-01-28
+tags: [en, open_source, onnx, token_classification, camembert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`esgi_vchhauv_nlp` is a English model originally trained by Snoirak.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/esgi_vchhauv_nlp_en_5.5.1_3.0_1738068313753.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/esgi_vchhauv_nlp_en_5.5.1_3.0_1738068313753.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = CamemBertForTokenClassification.pretrained("esgi_vchhauv_nlp","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = CamemBertForTokenClassification.pretrained("esgi_vchhauv_nlp", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|esgi_vchhauv_nlp|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|273.6 MB|
+
+## References
+
+https://huggingface.co/Snoirak/esgi-vchhauv-nlp
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-esgi_vchhauv_nlp_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-esgi_vchhauv_nlp_pipeline_en.md
new file mode 100644
index 00000000000000..068b76461b7128
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-esgi_vchhauv_nlp_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English esgi_vchhauv_nlp_pipeline pipeline CamemBertForTokenClassification from Snoirak
+author: John Snow Labs
+name: esgi_vchhauv_nlp_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`esgi_vchhauv_nlp_pipeline` is a English model originally trained by Snoirak.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/esgi_vchhauv_nlp_pipeline_en_5.5.1_3.0_1738068383949.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/esgi_vchhauv_nlp_pipeline_en_5.5.1_3.0_1738068383949.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("esgi_vchhauv_nlp_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("esgi_vchhauv_nlp_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|esgi_vchhauv_nlp_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|273.6 MB|
+
+## References
+
+https://huggingface.co/Snoirak/esgi-vchhauv-nlp
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-example_classifier_en.md b/docs/_posts/ahmedlone127/2025-01-28-example_classifier_en.md
new file mode 100644
index 00000000000000..bfc4cc6ac058bb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-example_classifier_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English example_classifier DistilBertForSequenceClassification from osanseviero
+author: John Snow Labs
+name: example_classifier
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`example_classifier` is a English model originally trained by osanseviero.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/example_classifier_en_5.5.1_3.0_1738077303417.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/example_classifier_en_5.5.1_3.0_1738077303417.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("example_classifier","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("example_classifier", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|example_classifier|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/osanseviero/example-classifier
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-example_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-example_classifier_pipeline_en.md
new file mode 100644
index 00000000000000..07d091c7e0a1b9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-example_classifier_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English example_classifier_pipeline pipeline DistilBertForSequenceClassification from osanseviero
+author: John Snow Labs
+name: example_classifier_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`example_classifier_pipeline` is a English model originally trained by osanseviero.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/example_classifier_pipeline_en_5.5.1_3.0_1738077316184.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/example_classifier_pipeline_en_5.5.1_3.0_1738077316184.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("example_classifier_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("example_classifier_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|example_classifier_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/osanseviero/example-classifier
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-facial_emotions_image_detection_rafdb_microsoft_vit_en.md b/docs/_posts/ahmedlone127/2025-01-28-facial_emotions_image_detection_rafdb_microsoft_vit_en.md
new file mode 100644
index 00000000000000..c149308aa37696
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-facial_emotions_image_detection_rafdb_microsoft_vit_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English facial_emotions_image_detection_rafdb_microsoft_vit SwinForImageClassification from adhityamw11
+author: John Snow Labs
+name: facial_emotions_image_detection_rafdb_microsoft_vit
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`facial_emotions_image_detection_rafdb_microsoft_vit` is a English model originally trained by adhityamw11.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/facial_emotions_image_detection_rafdb_microsoft_vit_en_5.5.1_3.0_1738095236829.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/facial_emotions_image_detection_rafdb_microsoft_vit_en_5.5.1_3.0_1738095236829.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""facial_emotions_image_detection_rafdb_microsoft_vit","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("facial_emotions_image_detection_rafdb_microsoft_vit","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|facial_emotions_image_detection_rafdb_microsoft_vit|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/adhityamw11/facial_emotions_image_detection_rafdb_microsoft_vit
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-facial_emotions_image_detection_rafdb_microsoft_vit_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-facial_emotions_image_detection_rafdb_microsoft_vit_pipeline_en.md
new file mode 100644
index 00000000000000..af11a54d39ec21
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-facial_emotions_image_detection_rafdb_microsoft_vit_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English facial_emotions_image_detection_rafdb_microsoft_vit_pipeline pipeline SwinForImageClassification from adhityamw11
+author: John Snow Labs
+name: facial_emotions_image_detection_rafdb_microsoft_vit_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`facial_emotions_image_detection_rafdb_microsoft_vit_pipeline` is a English model originally trained by adhityamw11.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/facial_emotions_image_detection_rafdb_microsoft_vit_pipeline_en_5.5.1_3.0_1738095247792.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/facial_emotions_image_detection_rafdb_microsoft_vit_pipeline_en_5.5.1_3.0_1738095247792.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("facial_emotions_image_detection_rafdb_microsoft_vit_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("facial_emotions_image_detection_rafdb_microsoft_vit_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|facial_emotions_image_detection_rafdb_microsoft_vit_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/adhityamw11/facial_emotions_image_detection_rafdb_microsoft_vit
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-felisa_en.md b/docs/_posts/ahmedlone127/2025-01-28-felisa_en.md
new file mode 100644
index 00000000000000..6907acfa54d3d5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-felisa_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English felisa T5Transformer from XFast0
+author: John Snow Labs
+name: felisa
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`felisa` is a English model originally trained by XFast0.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/felisa_en_5.5.1_3.0_1738032965418.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/felisa_en_5.5.1_3.0_1738032965418.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("felisa","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("felisa", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|felisa|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|349.8 MB|
+
+## References
+
+https://huggingface.co/XFast0/Felisa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-felisa_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-felisa_pipeline_en.md
new file mode 100644
index 00000000000000..82c02bb1978b78
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-felisa_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English felisa_pipeline pipeline T5Transformer from XFast0
+author: John Snow Labs
+name: felisa_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`felisa_pipeline` is a English model originally trained by XFast0.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/felisa_pipeline_en_5.5.1_3.0_1738032982672.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/felisa_pipeline_en_5.5.1_3.0_1738032982672.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("felisa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("felisa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|felisa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|349.8 MB|
+
+## References
+
+https://huggingface.co/XFast0/Felisa
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-ffpp_raw_1fps_faces_expand_0_aligned_augmentation_normalize_image_mean_std_en.md b/docs/_posts/ahmedlone127/2025-01-28-ffpp_raw_1fps_faces_expand_0_aligned_augmentation_normalize_image_mean_std_en.md
new file mode 100644
index 00000000000000..5269aedd9f44b9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-ffpp_raw_1fps_faces_expand_0_aligned_augmentation_normalize_image_mean_std_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ffpp_raw_1fps_faces_expand_0_aligned_augmentation_normalize_image_mean_std SwinForImageClassification from hchcsuim
+author: John Snow Labs
+name: ffpp_raw_1fps_faces_expand_0_aligned_augmentation_normalize_image_mean_std
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ffpp_raw_1fps_faces_expand_0_aligned_augmentation_normalize_image_mean_std` is a English model originally trained by hchcsuim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ffpp_raw_1fps_faces_expand_0_aligned_augmentation_normalize_image_mean_std_en_5.5.1_3.0_1738095678302.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ffpp_raw_1fps_faces_expand_0_aligned_augmentation_normalize_image_mean_std_en_5.5.1_3.0_1738095678302.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""ffpp_raw_1fps_faces_expand_0_aligned_augmentation_normalize_image_mean_std","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("ffpp_raw_1fps_faces_expand_0_aligned_augmentation_normalize_image_mean_std","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ffpp_raw_1fps_faces_expand_0_aligned_augmentation_normalize_image_mean_std|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/hchcsuim/FFPP-Raw_1FPS_faces-expand-0-aligned_augmentation-normalize-image-mean-std
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-ffpp_raw_1fps_faces_expand_0_aligned_augmentation_normalize_image_mean_std_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-ffpp_raw_1fps_faces_expand_0_aligned_augmentation_normalize_image_mean_std_pipeline_en.md
new file mode 100644
index 00000000000000..1b3b25cb4e83e8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-ffpp_raw_1fps_faces_expand_0_aligned_augmentation_normalize_image_mean_std_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English ffpp_raw_1fps_faces_expand_0_aligned_augmentation_normalize_image_mean_std_pipeline pipeline SwinForImageClassification from hchcsuim
+author: John Snow Labs
+name: ffpp_raw_1fps_faces_expand_0_aligned_augmentation_normalize_image_mean_std_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ffpp_raw_1fps_faces_expand_0_aligned_augmentation_normalize_image_mean_std_pipeline` is a English model originally trained by hchcsuim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ffpp_raw_1fps_faces_expand_0_aligned_augmentation_normalize_image_mean_std_pipeline_en_5.5.1_3.0_1738095693413.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ffpp_raw_1fps_faces_expand_0_aligned_augmentation_normalize_image_mean_std_pipeline_en_5.5.1_3.0_1738095693413.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ffpp_raw_1fps_faces_expand_0_aligned_augmentation_normalize_image_mean_std_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ffpp_raw_1fps_faces_expand_0_aligned_augmentation_normalize_image_mean_std_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ffpp_raw_1fps_faces_expand_0_aligned_augmentation_normalize_image_mean_std_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/hchcsuim/FFPP-Raw_1FPS_faces-expand-0-aligned_augmentation-normalize-image-mean-std
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-finalgpt2trained_en.md b/docs/_posts/ahmedlone127/2025-01-28-finalgpt2trained_en.md
new file mode 100644
index 00000000000000..d678ffd519e98f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-finalgpt2trained_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English finalgpt2trained GPT2Transformer from BhavaishKumar112
+author: John Snow Labs
+name: finalgpt2trained
+date: 2025-01-28
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finalgpt2trained` is a English model originally trained by BhavaishKumar112.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finalgpt2trained_en_5.5.1_3.0_1738042774973.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finalgpt2trained_en_5.5.1_3.0_1738042774973.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("finalgpt2trained","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("finalgpt2trained","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finalgpt2trained|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/BhavaishKumar112/finalgpt2trained
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-finalgpt2trained_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-finalgpt2trained_pipeline_en.md
new file mode 100644
index 00000000000000..bb9d023591fd51
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-finalgpt2trained_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English finalgpt2trained_pipeline pipeline GPT2Transformer from BhavaishKumar112
+author: John Snow Labs
+name: finalgpt2trained_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finalgpt2trained_pipeline` is a English model originally trained by BhavaishKumar112.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finalgpt2trained_pipeline_en_5.5.1_3.0_1738042797632.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finalgpt2trained_pipeline_en_5.5.1_3.0_1738042797632.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finalgpt2trained_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finalgpt2trained_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finalgpt2trained_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/BhavaishKumar112/finalgpt2trained
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-finbert_cn_en.md b/docs/_posts/ahmedlone127/2025-01-28-finbert_cn_en.md
new file mode 100644
index 00000000000000..a1a81ae22d2b27
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-finbert_cn_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finbert_cn BertForSequenceClassification from hw2942
+author: John Snow Labs
+name: finbert_cn
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finbert_cn` is a English model originally trained by hw2942.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finbert_cn_en_5.5.1_3.0_1738101002625.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finbert_cn_en_5.5.1_3.0_1738101002625.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("finbert_cn","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("finbert_cn", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finbert_cn|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|383.7 MB|
+
+## References
+
+https://huggingface.co/hw2942/FinBERT_CN
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-finbert_cn_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-finbert_cn_pipeline_en.md
new file mode 100644
index 00000000000000..04784cc538cb36
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-finbert_cn_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finbert_cn_pipeline pipeline BertForSequenceClassification from hw2942
+author: John Snow Labs
+name: finbert_cn_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finbert_cn_pipeline` is a English model originally trained by hw2942.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finbert_cn_pipeline_en_5.5.1_3.0_1738101021658.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finbert_cn_pipeline_en_5.5.1_3.0_1738101021658.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finbert_cn_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finbert_cn_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finbert_cn_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|383.7 MB|
+
+## References
+
+https://huggingface.co/hw2942/FinBERT_CN
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-fine_tuned_flan_t5_mrblack117_en.md b/docs/_posts/ahmedlone127/2025-01-28-fine_tuned_flan_t5_mrblack117_en.md
new file mode 100644
index 00000000000000..fa53eb6f031144
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-fine_tuned_flan_t5_mrblack117_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English fine_tuned_flan_t5_mrblack117 T5Transformer from MrBlack117
+author: John Snow Labs
+name: fine_tuned_flan_t5_mrblack117
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_flan_t5_mrblack117` is a English model originally trained by MrBlack117.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_flan_t5_mrblack117_en_5.5.1_3.0_1738074292183.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_flan_t5_mrblack117_en_5.5.1_3.0_1738074292183.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("fine_tuned_flan_t5_mrblack117","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("fine_tuned_flan_t5_mrblack117", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_flan_t5_mrblack117|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/MrBlack117/fine-tuned-flan-t5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-fine_tuned_flan_t5_mrblack117_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-fine_tuned_flan_t5_mrblack117_pipeline_en.md
new file mode 100644
index 00000000000000..80beb7a6b2904f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-fine_tuned_flan_t5_mrblack117_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English fine_tuned_flan_t5_mrblack117_pipeline pipeline T5Transformer from MrBlack117
+author: John Snow Labs
+name: fine_tuned_flan_t5_mrblack117_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_flan_t5_mrblack117_pipeline` is a English model originally trained by MrBlack117.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_flan_t5_mrblack117_pipeline_en_5.5.1_3.0_1738074343479.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_flan_t5_mrblack117_pipeline_en_5.5.1_3.0_1738074343479.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fine_tuned_flan_t5_mrblack117_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fine_tuned_flan_t5_mrblack117_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_flan_t5_mrblack117_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/MrBlack117/fine-tuned-flan-t5
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-fine_tuned_flan_t5_zugzwan9_en.md b/docs/_posts/ahmedlone127/2025-01-28-fine_tuned_flan_t5_zugzwan9_en.md
new file mode 100644
index 00000000000000..509a38f5a3558c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-fine_tuned_flan_t5_zugzwan9_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English fine_tuned_flan_t5_zugzwan9 T5Transformer from Zugzwan9
+author: John Snow Labs
+name: fine_tuned_flan_t5_zugzwan9
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_flan_t5_zugzwan9` is a English model originally trained by Zugzwan9.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_flan_t5_zugzwan9_en_5.5.1_3.0_1738091512994.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_flan_t5_zugzwan9_en_5.5.1_3.0_1738091512994.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("fine_tuned_flan_t5_zugzwan9","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("fine_tuned_flan_t5_zugzwan9", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_flan_t5_zugzwan9|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Zugzwan9/fine-tuned-flan-t5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-fine_tuned_flan_t5_zugzwan9_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-fine_tuned_flan_t5_zugzwan9_pipeline_en.md
new file mode 100644
index 00000000000000..7329e450bcad6a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-fine_tuned_flan_t5_zugzwan9_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English fine_tuned_flan_t5_zugzwan9_pipeline pipeline T5Transformer from Zugzwan9
+author: John Snow Labs
+name: fine_tuned_flan_t5_zugzwan9_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_flan_t5_zugzwan9_pipeline` is a English model originally trained by Zugzwan9.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_flan_t5_zugzwan9_pipeline_en_5.5.1_3.0_1738091563024.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_flan_t5_zugzwan9_pipeline_en_5.5.1_3.0_1738091563024.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fine_tuned_flan_t5_zugzwan9_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fine_tuned_flan_t5_zugzwan9_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_flan_t5_zugzwan9_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Zugzwan9/fine-tuned-flan-t5
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-fine_tuned_model_en.md b/docs/_posts/ahmedlone127/2025-01-28-fine_tuned_model_en.md
new file mode 100644
index 00000000000000..6512d8e0c2326c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-fine_tuned_model_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English fine_tuned_model T5Transformer from Rakshith0808
+author: John Snow Labs
+name: fine_tuned_model
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_model` is a English model originally trained by Rakshith0808.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_model_en_5.5.1_3.0_1738032363421.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_model_en_5.5.1_3.0_1738032363421.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("fine_tuned_model","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("fine_tuned_model", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|867.0 MB|
+
+## References
+
+https://huggingface.co/Rakshith0808/fine_tuned_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-fine_tuned_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-fine_tuned_model_pipeline_en.md
new file mode 100644
index 00000000000000..65a72e43e9725b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-fine_tuned_model_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English fine_tuned_model_pipeline pipeline T5Transformer from Rakshith0808
+author: John Snow Labs
+name: fine_tuned_model_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_model_pipeline` is a English model originally trained by Rakshith0808.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_model_pipeline_en_5.5.1_3.0_1738032433443.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_model_pipeline_en_5.5.1_3.0_1738032433443.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fine_tuned_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fine_tuned_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|867.0 MB|
+
+## References
+
+https://huggingface.co/Rakshith0808/fine_tuned_model
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-fine_tuned_opus_maltese_english_french_en.md b/docs/_posts/ahmedlone127/2025-01-28-fine_tuned_opus_maltese_english_french_en.md
new file mode 100644
index 00000000000000..9dc93ebf53e21e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-fine_tuned_opus_maltese_english_french_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English fine_tuned_opus_maltese_english_french MarianTransformer from p06pratibha
+author: John Snow Labs
+name: fine_tuned_opus_maltese_english_french
+date: 2025-01-28
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_opus_maltese_english_french` is a English model originally trained by p06pratibha.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_opus_maltese_english_french_en_5.5.1_3.0_1738107322598.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_opus_maltese_english_french_en_5.5.1_3.0_1738107322598.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("fine_tuned_opus_maltese_english_french","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("fine_tuned_opus_maltese_english_french","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_opus_maltese_english_french|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|397.1 MB|
+
+## References
+
+https://huggingface.co/p06pratibha/fine-tuned-opus-mt-en-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-fine_tuned_opus_maltese_english_french_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-fine_tuned_opus_maltese_english_french_pipeline_en.md
new file mode 100644
index 00000000000000..5d6f2f96f3d258
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-fine_tuned_opus_maltese_english_french_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English fine_tuned_opus_maltese_english_french_pipeline pipeline MarianTransformer from p06pratibha
+author: John Snow Labs
+name: fine_tuned_opus_maltese_english_french_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_opus_maltese_english_french_pipeline` is a English model originally trained by p06pratibha.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_opus_maltese_english_french_pipeline_en_5.5.1_3.0_1738107342221.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_opus_maltese_english_french_pipeline_en_5.5.1_3.0_1738107342221.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fine_tuned_opus_maltese_english_french_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fine_tuned_opus_maltese_english_french_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_opus_maltese_english_french_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|397.7 MB|
+
+## References
+
+https://huggingface.co/p06pratibha/fine-tuned-opus-mt-en-fr
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-fine_tuned_t5_small_model_naive_firstapproach_en.md b/docs/_posts/ahmedlone127/2025-01-28-fine_tuned_t5_small_model_naive_firstapproach_en.md
new file mode 100644
index 00000000000000..9521f988eb67ed
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-fine_tuned_t5_small_model_naive_firstapproach_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English fine_tuned_t5_small_model_naive_firstapproach T5Transformer from ariW
+author: John Snow Labs
+name: fine_tuned_t5_small_model_naive_firstapproach
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_t5_small_model_naive_firstapproach` is a English model originally trained by ariW.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_small_model_naive_firstapproach_en_5.5.1_3.0_1738092747271.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_small_model_naive_firstapproach_en_5.5.1_3.0_1738092747271.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("fine_tuned_t5_small_model_naive_firstapproach","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("fine_tuned_t5_small_model_naive_firstapproach", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_t5_small_model_naive_firstapproach|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|267.3 MB|
+
+## References
+
+https://huggingface.co/ariW/fine_tuned_t5_small_model-naive-firstapproach
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-fine_tuned_t5_small_model_naive_firstapproach_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-fine_tuned_t5_small_model_naive_firstapproach_pipeline_en.md
new file mode 100644
index 00000000000000..bd52b1b9c22190
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-fine_tuned_t5_small_model_naive_firstapproach_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English fine_tuned_t5_small_model_naive_firstapproach_pipeline pipeline T5Transformer from ariW
+author: John Snow Labs
+name: fine_tuned_t5_small_model_naive_firstapproach_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_t5_small_model_naive_firstapproach_pipeline` is a English model originally trained by ariW.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_small_model_naive_firstapproach_pipeline_en_5.5.1_3.0_1738092765388.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_small_model_naive_firstapproach_pipeline_en_5.5.1_3.0_1738092765388.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fine_tuned_t5_small_model_naive_firstapproach_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fine_tuned_t5_small_model_naive_firstapproach_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_t5_small_model_naive_firstapproach_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|267.3 MB|
+
+## References
+
+https://huggingface.co/ariW/fine_tuned_t5_small_model-naive-firstapproach
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-fine_tuned_t5_small_model_sec_5_en.md b/docs/_posts/ahmedlone127/2025-01-28-fine_tuned_t5_small_model_sec_5_en.md
new file mode 100644
index 00000000000000..b4092e171de258
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-fine_tuned_t5_small_model_sec_5_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English fine_tuned_t5_small_model_sec_5 T5Transformer from miasetya
+author: John Snow Labs
+name: fine_tuned_t5_small_model_sec_5
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_t5_small_model_sec_5` is a English model originally trained by miasetya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_small_model_sec_5_en_5.5.1_3.0_1738030506807.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_small_model_sec_5_en_5.5.1_3.0_1738030506807.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("fine_tuned_t5_small_model_sec_5","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("fine_tuned_t5_small_model_sec_5", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_t5_small_model_sec_5|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|271.6 MB|
+
+## References
+
+https://huggingface.co/miasetya/fine_tuned_t5_small_model_sec_5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-fine_tuned_t5_small_model_sec_5_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-fine_tuned_t5_small_model_sec_5_pipeline_en.md
new file mode 100644
index 00000000000000..47e79ec74d1712
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-fine_tuned_t5_small_model_sec_5_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English fine_tuned_t5_small_model_sec_5_pipeline pipeline T5Transformer from miasetya
+author: John Snow Labs
+name: fine_tuned_t5_small_model_sec_5_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_t5_small_model_sec_5_pipeline` is a English model originally trained by miasetya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_small_model_sec_5_pipeline_en_5.5.1_3.0_1738030524504.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_small_model_sec_5_pipeline_en_5.5.1_3.0_1738030524504.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fine_tuned_t5_small_model_sec_5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fine_tuned_t5_small_model_sec_5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_t5_small_model_sec_5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|271.6 MB|
+
+## References
+
+https://huggingface.co/miasetya/fine_tuned_t5_small_model_sec_5
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-fine_tuned_t5_small_model_sec_5_v13_en.md b/docs/_posts/ahmedlone127/2025-01-28-fine_tuned_t5_small_model_sec_5_v13_en.md
new file mode 100644
index 00000000000000..1a1286a7ca5ab4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-fine_tuned_t5_small_model_sec_5_v13_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English fine_tuned_t5_small_model_sec_5_v13 T5Transformer from miasetya
+author: John Snow Labs
+name: fine_tuned_t5_small_model_sec_5_v13
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_t5_small_model_sec_5_v13` is a English model originally trained by miasetya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_small_model_sec_5_v13_en_5.5.1_3.0_1738072035583.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_small_model_sec_5_v13_en_5.5.1_3.0_1738072035583.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("fine_tuned_t5_small_model_sec_5_v13","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("fine_tuned_t5_small_model_sec_5_v13", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_t5_small_model_sec_5_v13|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|267.4 MB|
+
+## References
+
+https://huggingface.co/miasetya/fine_tuned_t5_small_model_sec_5_v13
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-fine_tuned_t5_small_model_sec_5_v13_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-fine_tuned_t5_small_model_sec_5_v13_pipeline_en.md
new file mode 100644
index 00000000000000..2aff7224faed1b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-fine_tuned_t5_small_model_sec_5_v13_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English fine_tuned_t5_small_model_sec_5_v13_pipeline pipeline T5Transformer from miasetya
+author: John Snow Labs
+name: fine_tuned_t5_small_model_sec_5_v13_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_t5_small_model_sec_5_v13_pipeline` is a English model originally trained by miasetya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_small_model_sec_5_v13_pipeline_en_5.5.1_3.0_1738072053196.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_small_model_sec_5_v13_pipeline_en_5.5.1_3.0_1738072053196.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fine_tuned_t5_small_model_sec_5_v13_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fine_tuned_t5_small_model_sec_5_v13_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_t5_small_model_sec_5_v13_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|267.4 MB|
+
+## References
+
+https://huggingface.co/miasetya/fine_tuned_t5_small_model_sec_5_v13
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-fine_tuned_t5_small_model_sec_5_v5_en.md b/docs/_posts/ahmedlone127/2025-01-28-fine_tuned_t5_small_model_sec_5_v5_en.md
new file mode 100644
index 00000000000000..5f7f57e3ee7217
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-fine_tuned_t5_small_model_sec_5_v5_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English fine_tuned_t5_small_model_sec_5_v5 T5Transformer from miasetya
+author: John Snow Labs
+name: fine_tuned_t5_small_model_sec_5_v5
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_t5_small_model_sec_5_v5` is a English model originally trained by miasetya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_small_model_sec_5_v5_en_5.5.1_3.0_1738094220807.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_small_model_sec_5_v5_en_5.5.1_3.0_1738094220807.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("fine_tuned_t5_small_model_sec_5_v5","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("fine_tuned_t5_small_model_sec_5_v5", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_t5_small_model_sec_5_v5|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|268.8 MB|
+
+## References
+
+https://huggingface.co/miasetya/fine_tuned_t5_small_model_sec_5_v5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-fine_tuned_t5_small_model_sec_5_v5_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-fine_tuned_t5_small_model_sec_5_v5_pipeline_en.md
new file mode 100644
index 00000000000000..58b2ab8c0c58b3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-fine_tuned_t5_small_model_sec_5_v5_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English fine_tuned_t5_small_model_sec_5_v5_pipeline pipeline T5Transformer from miasetya
+author: John Snow Labs
+name: fine_tuned_t5_small_model_sec_5_v5_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_t5_small_model_sec_5_v5_pipeline` is a English model originally trained by miasetya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_small_model_sec_5_v5_pipeline_en_5.5.1_3.0_1738094238474.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_t5_small_model_sec_5_v5_pipeline_en_5.5.1_3.0_1738094238474.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fine_tuned_t5_small_model_sec_5_v5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fine_tuned_t5_small_model_sec_5_v5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_t5_small_model_sec_5_v5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|268.8 MB|
+
+## References
+
+https://huggingface.co/miasetya/fine_tuned_t5_small_model_sec_5_v5
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-fine_tuning_distilbert_en.md b/docs/_posts/ahmedlone127/2025-01-28-fine_tuning_distilbert_en.md
new file mode 100644
index 00000000000000..b7d55b91ff0898
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-fine_tuning_distilbert_en.md
@@ -0,0 +1,96 @@
+---
+layout: model
+title: English fine_tuning_distilbert DistilBertEmbeddings from Nguyens
+author: John Snow Labs
+name: fine_tuning_distilbert
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuning_distilbert` is a English model originally trained by Nguyens.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuning_distilbert_en_5.5.1_3.0_1738025322985.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuning_distilbert_en_5.5.1_3.0_1738025322985.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("fine_tuning_distilbert","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("fine_tuning_distilbert","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuning_distilbert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+References
+
+https://huggingface.co/Nguyens/fine-tuning-distilbert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-fine_tuning_distilbert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-fine_tuning_distilbert_pipeline_en.md
new file mode 100644
index 00000000000000..840f8240114aae
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-fine_tuning_distilbert_pipeline_en.md
@@ -0,0 +1,72 @@
+---
+layout: model
+title: English fine_tuning_distilbert_pipeline pipeline DistilBertEmbeddings from Nguyens
+author: John Snow Labs
+name: fine_tuning_distilbert_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuning_distilbert_pipeline` is a English model originally trained by Nguyens.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuning_distilbert_pipeline_en_5.5.1_3.0_1738025337075.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuning_distilbert_pipeline_en_5.5.1_3.0_1738025337075.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("fine_tuning_distilbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("fine_tuning_distilbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuning_distilbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+References
+
+https://huggingface.co/Nguyens/fine-tuning-distilbert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-finetune_rugec_msu_en.md b/docs/_posts/ahmedlone127/2025-01-28-finetune_rugec_msu_en.md
new file mode 100644
index 00000000000000..023daf52d6e807
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-finetune_rugec_msu_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English finetune_rugec_msu T5Transformer from mika5883
+author: John Snow Labs
+name: finetune_rugec_msu
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetune_rugec_msu` is a English model originally trained by mika5883.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetune_rugec_msu_en_5.5.1_3.0_1738092197189.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetune_rugec_msu_en_5.5.1_3.0_1738092197189.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("finetune_rugec_msu","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("finetune_rugec_msu", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetune_rugec_msu|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|927.2 MB|
+
+## References
+
+https://huggingface.co/mika5883/finetune_rugec_msu
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-finetune_rugec_msu_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-finetune_rugec_msu_pipeline_en.md
new file mode 100644
index 00000000000000..83e45605526a5b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-finetune_rugec_msu_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English finetune_rugec_msu_pipeline pipeline T5Transformer from mika5883
+author: John Snow Labs
+name: finetune_rugec_msu_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetune_rugec_msu_pipeline` is a English model originally trained by mika5883.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetune_rugec_msu_pipeline_en_5.5.1_3.0_1738092242764.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetune_rugec_msu_pipeline_en_5.5.1_3.0_1738092242764.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetune_rugec_msu_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetune_rugec_msu_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetune_rugec_msu_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|927.2 MB|
+
+## References
+
+https://huggingface.co/mika5883/finetune_rugec_msu
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-finetuned__beto_clinical_wl_spanish__augmented_ultrasounds_en.md b/docs/_posts/ahmedlone127/2025-01-28-finetuned__beto_clinical_wl_spanish__augmented_ultrasounds_en.md
new file mode 100644
index 00000000000000..69428e7220b5d6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-finetuned__beto_clinical_wl_spanish__augmented_ultrasounds_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuned__beto_clinical_wl_spanish__augmented_ultrasounds BertEmbeddings from manucos
+author: John Snow Labs
+name: finetuned__beto_clinical_wl_spanish__augmented_ultrasounds
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned__beto_clinical_wl_spanish__augmented_ultrasounds` is a English model originally trained by manucos.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned__beto_clinical_wl_spanish__augmented_ultrasounds_en_5.5.1_3.0_1738098475474.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned__beto_clinical_wl_spanish__augmented_ultrasounds_en_5.5.1_3.0_1738098475474.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("finetuned__beto_clinical_wl_spanish__augmented_ultrasounds","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("finetuned__beto_clinical_wl_spanish__augmented_ultrasounds","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned__beto_clinical_wl_spanish__augmented_ultrasounds|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/manucos/finetuned__beto-clinical-wl-es__augmented-ultrasounds
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-finetuned__beto_clinical_wl_spanish__augmented_ultrasounds_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-finetuned__beto_clinical_wl_spanish__augmented_ultrasounds_pipeline_en.md
new file mode 100644
index 00000000000000..6828a9ab2f23b1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-finetuned__beto_clinical_wl_spanish__augmented_ultrasounds_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuned__beto_clinical_wl_spanish__augmented_ultrasounds_pipeline pipeline BertEmbeddings from manucos
+author: John Snow Labs
+name: finetuned__beto_clinical_wl_spanish__augmented_ultrasounds_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned__beto_clinical_wl_spanish__augmented_ultrasounds_pipeline` is a English model originally trained by manucos.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned__beto_clinical_wl_spanish__augmented_ultrasounds_pipeline_en_5.5.1_3.0_1738098496175.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned__beto_clinical_wl_spanish__augmented_ultrasounds_pipeline_en_5.5.1_3.0_1738098496175.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuned__beto_clinical_wl_spanish__augmented_ultrasounds_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuned__beto_clinical_wl_spanish__augmented_ultrasounds_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned__beto_clinical_wl_spanish__augmented_ultrasounds_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/manucos/finetuned__beto-clinical-wl-es__augmented-ultrasounds
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-finetuned_billsum_t5_en.md b/docs/_posts/ahmedlone127/2025-01-28-finetuned_billsum_t5_en.md
new file mode 100644
index 00000000000000..1ccafbdbf6b297
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-finetuned_billsum_t5_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English finetuned_billsum_t5 T5Transformer from rahul28122002
+author: John Snow Labs
+name: finetuned_billsum_t5
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_billsum_t5` is a English model originally trained by rahul28122002.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_billsum_t5_en_5.5.1_3.0_1738030870028.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_billsum_t5_en_5.5.1_3.0_1738030870028.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("finetuned_billsum_t5","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("finetuned_billsum_t5", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_billsum_t5|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|266.1 MB|
+
+## References
+
+https://huggingface.co/rahul28122002/finetuned_billsum_t5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-finetuned_billsum_t5_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-finetuned_billsum_t5_pipeline_en.md
new file mode 100644
index 00000000000000..434025a689281e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-finetuned_billsum_t5_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English finetuned_billsum_t5_pipeline pipeline T5Transformer from rahul28122002
+author: John Snow Labs
+name: finetuned_billsum_t5_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_billsum_t5_pipeline` is a English model originally trained by rahul28122002.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_billsum_t5_pipeline_en_5.5.1_3.0_1738030887826.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_billsum_t5_pipeline_en_5.5.1_3.0_1738030887826.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuned_billsum_t5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuned_billsum_t5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_billsum_t5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|266.1 MB|
+
+## References
+
+https://huggingface.co/rahul28122002/finetuned_billsum_t5
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-finetuned_mlm__english_french_german_en.md b/docs/_posts/ahmedlone127/2025-01-28-finetuned_mlm__english_french_german_en.md
new file mode 100644
index 00000000000000..6e5a0a6d1f8df0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-finetuned_mlm__english_french_german_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English finetuned_mlm__english_french_german T5Transformer from amiraMamdouh
+author: John Snow Labs
+name: finetuned_mlm__english_french_german
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_mlm__english_french_german` is a English model originally trained by amiraMamdouh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_mlm__english_french_german_en_5.5.1_3.0_1738092637338.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_mlm__english_french_german_en_5.5.1_3.0_1738092637338.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("finetuned_mlm__english_french_german","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("finetuned_mlm__english_french_german", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_mlm__english_french_german|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|283.6 MB|
+
+## References
+
+https://huggingface.co/amiraMamdouh/finetuned_MLM__English_French_German
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-finetuned_mlm__english_french_german_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-finetuned_mlm__english_french_german_pipeline_en.md
new file mode 100644
index 00000000000000..97ca0e29828ca8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-finetuned_mlm__english_french_german_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English finetuned_mlm__english_french_german_pipeline pipeline T5Transformer from amiraMamdouh
+author: John Snow Labs
+name: finetuned_mlm__english_french_german_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_mlm__english_french_german_pipeline` is a English model originally trained by amiraMamdouh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_mlm__english_french_german_pipeline_en_5.5.1_3.0_1738092652967.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_mlm__english_french_german_pipeline_en_5.5.1_3.0_1738092652967.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuned_mlm__english_french_german_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuned_mlm__english_french_german_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_mlm__english_french_german_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|283.6 MB|
+
+## References
+
+https://huggingface.co/amiraMamdouh/finetuned_MLM__English_French_German
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-finetuned_mlm_french_en.md b/docs/_posts/ahmedlone127/2025-01-28-finetuned_mlm_french_en.md
new file mode 100644
index 00000000000000..1a973f2af6543f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-finetuned_mlm_french_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English finetuned_mlm_french T5Transformer from amiraMamdouh
+author: John Snow Labs
+name: finetuned_mlm_french
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_mlm_french` is a English model originally trained by amiraMamdouh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_mlm_french_en_5.5.1_3.0_1738072678353.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_mlm_french_en_5.5.1_3.0_1738072678353.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("finetuned_mlm_french","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("finetuned_mlm_french", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_mlm_french|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|284.2 MB|
+
+## References
+
+https://huggingface.co/amiraMamdouh/finetuned_MLM_French
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-finetuned_mlm_french_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-finetuned_mlm_french_pipeline_en.md
new file mode 100644
index 00000000000000..3d20e1d7f187ee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-finetuned_mlm_french_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English finetuned_mlm_french_pipeline pipeline T5Transformer from amiraMamdouh
+author: John Snow Labs
+name: finetuned_mlm_french_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_mlm_french_pipeline` is a English model originally trained by amiraMamdouh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_mlm_french_pipeline_en_5.5.1_3.0_1738072694021.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_mlm_french_pipeline_en_5.5.1_3.0_1738072694021.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuned_mlm_french_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuned_mlm_french_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_mlm_french_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|284.2 MB|
+
+## References
+
+https://huggingface.co/amiraMamdouh/finetuned_MLM_French
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-finetuned_parkinson_classification_en.md b/docs/_posts/ahmedlone127/2025-01-28-finetuned_parkinson_classification_en.md
new file mode 100644
index 00000000000000..aa01cbbc981b04
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-finetuned_parkinson_classification_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuned_parkinson_classification SwinForImageClassification from skohli01
+author: John Snow Labs
+name: finetuned_parkinson_classification
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_parkinson_classification` is a English model originally trained by skohli01.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_parkinson_classification_en_5.5.1_3.0_1738095522112.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_parkinson_classification_en_5.5.1_3.0_1738095522112.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""finetuned_parkinson_classification","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("finetuned_parkinson_classification","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_parkinson_classification|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/skohli01/finetuned-parkinson-classification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-finetuned_parkinson_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-finetuned_parkinson_classification_pipeline_en.md
new file mode 100644
index 00000000000000..a317f1ac6fa432
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-finetuned_parkinson_classification_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English finetuned_parkinson_classification_pipeline pipeline SwinForImageClassification from skohli01
+author: John Snow Labs
+name: finetuned_parkinson_classification_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_parkinson_classification_pipeline` is a English model originally trained by skohli01.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_parkinson_classification_pipeline_en_5.5.1_3.0_1738095532964.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_parkinson_classification_pipeline_en_5.5.1_3.0_1738095532964.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuned_parkinson_classification_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuned_parkinson_classification_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_parkinson_classification_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/skohli01/finetuned-parkinson-classification
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-finetuned_t5_1_epoch_4_batches_en.md b/docs/_posts/ahmedlone127/2025-01-28-finetuned_t5_1_epoch_4_batches_en.md
new file mode 100644
index 00000000000000..b62b8f23c65270
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-finetuned_t5_1_epoch_4_batches_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English finetuned_t5_1_epoch_4_batches T5Transformer from mitra-mir
+author: John Snow Labs
+name: finetuned_t5_1_epoch_4_batches
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_t5_1_epoch_4_batches` is a English model originally trained by mitra-mir.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_t5_1_epoch_4_batches_en_5.5.1_3.0_1738072341293.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_t5_1_epoch_4_batches_en_5.5.1_3.0_1738072341293.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("finetuned_t5_1_epoch_4_batches","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("finetuned_t5_1_epoch_4_batches", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_t5_1_epoch_4_batches|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|3.1 GB|
+
+## References
+
+https://huggingface.co/mitra-mir/finetuned_t5-1-epoch-4_batches
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-finetuned_t5_1_epoch_4_batches_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-finetuned_t5_1_epoch_4_batches_pipeline_en.md
new file mode 100644
index 00000000000000..46a4f07bf81503
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-finetuned_t5_1_epoch_4_batches_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English finetuned_t5_1_epoch_4_batches_pipeline pipeline T5Transformer from mitra-mir
+author: John Snow Labs
+name: finetuned_t5_1_epoch_4_batches_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_t5_1_epoch_4_batches_pipeline` is a English model originally trained by mitra-mir.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_t5_1_epoch_4_batches_pipeline_en_5.5.1_3.0_1738072514477.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_t5_1_epoch_4_batches_pipeline_en_5.5.1_3.0_1738072514477.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuned_t5_1_epoch_4_batches_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuned_t5_1_epoch_4_batches_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_t5_1_epoch_4_batches_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|3.1 GB|
+
+## References
+
+https://huggingface.co/mitra-mir/finetuned_t5-1-epoch-4_batches
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-finetuned_t5_financial_qa_en.md b/docs/_posts/ahmedlone127/2025-01-28-finetuned_t5_financial_qa_en.md
new file mode 100644
index 00000000000000..5fb4d2b4597c56
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-finetuned_t5_financial_qa_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English finetuned_t5_financial_qa T5Transformer from ntatiit
+author: John Snow Labs
+name: finetuned_t5_financial_qa
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_t5_financial_qa` is a English model originally trained by ntatiit.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_t5_financial_qa_en_5.5.1_3.0_1738093198705.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_t5_financial_qa_en_5.5.1_3.0_1738093198705.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("finetuned_t5_financial_qa","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("finetuned_t5_financial_qa", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_t5_financial_qa|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|911.6 MB|
+
+## References
+
+https://huggingface.co/ntatiit/finetuned-t5-financial-qa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-finetuned_t5_financial_qa_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-finetuned_t5_financial_qa_pipeline_en.md
new file mode 100644
index 00000000000000..3f568d990c2ad9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-finetuned_t5_financial_qa_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English finetuned_t5_financial_qa_pipeline pipeline T5Transformer from ntatiit
+author: John Snow Labs
+name: finetuned_t5_financial_qa_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_t5_financial_qa_pipeline` is a English model originally trained by ntatiit.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_t5_financial_qa_pipeline_en_5.5.1_3.0_1738093248110.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_t5_financial_qa_pipeline_en_5.5.1_3.0_1738093248110.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuned_t5_financial_qa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuned_t5_financial_qa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_t5_financial_qa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|911.6 MB|
+
+## References
+
+https://huggingface.co/ntatiit/finetuned-t5-financial-qa
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-finetuned_text_class_en.md b/docs/_posts/ahmedlone127/2025-01-28-finetuned_text_class_en.md
new file mode 100644
index 00000000000000..0c54303862bf37
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-finetuned_text_class_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuned_text_class DistilBertForSequenceClassification from Luca-Engel
+author: John Snow Labs
+name: finetuned_text_class
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_text_class` is a English model originally trained by Luca-Engel.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_text_class_en_5.5.1_3.0_1738077503000.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_text_class_en_5.5.1_3.0_1738077503000.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuned_text_class","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuned_text_class", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_text_class|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Luca-Engel/finetuned_text_class
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-finetuned_text_class_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-finetuned_text_class_pipeline_en.md
new file mode 100644
index 00000000000000..668cb240bfdf0e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-finetuned_text_class_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuned_text_class_pipeline pipeline DistilBertForSequenceClassification from Luca-Engel
+author: John Snow Labs
+name: finetuned_text_class_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_text_class_pipeline` is a English model originally trained by Luca-Engel.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_text_class_pipeline_en_5.5.1_3.0_1738077515573.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_text_class_pipeline_en_5.5.1_3.0_1738077515573.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuned_text_class_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuned_text_class_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_text_class_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Luca-Engel/finetuned_text_class
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-finetuned_thamed_chowdhury_en.md b/docs/_posts/ahmedlone127/2025-01-28-finetuned_thamed_chowdhury_en.md
new file mode 100644
index 00000000000000..adc26bc8ddf3c0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-finetuned_thamed_chowdhury_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English finetuned_thamed_chowdhury T5Transformer from Thamed-Chowdhury
+author: John Snow Labs
+name: finetuned_thamed_chowdhury
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_thamed_chowdhury` is a English model originally trained by Thamed-Chowdhury.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_thamed_chowdhury_en_5.5.1_3.0_1738030733331.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_thamed_chowdhury_en_5.5.1_3.0_1738030733331.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("finetuned_thamed_chowdhury","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("finetuned_thamed_chowdhury", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_thamed_chowdhury|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Thamed-Chowdhury/finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-finetuned_thamed_chowdhury_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-finetuned_thamed_chowdhury_pipeline_en.md
new file mode 100644
index 00000000000000..498f39f50f712d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-finetuned_thamed_chowdhury_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English finetuned_thamed_chowdhury_pipeline pipeline T5Transformer from Thamed-Chowdhury
+author: John Snow Labs
+name: finetuned_thamed_chowdhury_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_thamed_chowdhury_pipeline` is a English model originally trained by Thamed-Chowdhury.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_thamed_chowdhury_pipeline_en_5.5.1_3.0_1738030788933.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_thamed_chowdhury_pipeline_en_5.5.1_3.0_1738030788933.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuned_thamed_chowdhury_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuned_thamed_chowdhury_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_thamed_chowdhury_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Thamed-Chowdhury/finetuned
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-finetuning_sentiment_model_3000_samples_jinjinj_en.md b/docs/_posts/ahmedlone127/2025-01-28-finetuning_sentiment_model_3000_samples_jinjinj_en.md
new file mode 100644
index 00000000000000..8de9bf692e3bf2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-finetuning_sentiment_model_3000_samples_jinjinj_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_jinjinj DistilBertForSequenceClassification from jinjinj
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_jinjinj
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_jinjinj` is a English model originally trained by jinjinj.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_jinjinj_en_5.5.1_3.0_1738077371963.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_jinjinj_en_5.5.1_3.0_1738077371963.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_jinjinj","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_jinjinj", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_jinjinj|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/jinjinj/finetuning-sentiment-model-3000-samples
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-finetuning_sentiment_model_3000_samples_jinjinj_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-finetuning_sentiment_model_3000_samples_jinjinj_pipeline_en.md
new file mode 100644
index 00000000000000..58d4d57f2082cb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-finetuning_sentiment_model_3000_samples_jinjinj_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_jinjinj_pipeline pipeline DistilBertForSequenceClassification from jinjinj
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_jinjinj_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_jinjinj_pipeline` is a English model originally trained by jinjinj.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_jinjinj_pipeline_en_5.5.1_3.0_1738077385119.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_jinjinj_pipeline_en_5.5.1_3.0_1738077385119.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuning_sentiment_model_3000_samples_jinjinj_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuning_sentiment_model_3000_samples_jinjinj_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_jinjinj_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/jinjinj/finetuning-sentiment-model-3000-samples
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-finetuning_sentiment_model_3000_samples_kctrupa_en.md b/docs/_posts/ahmedlone127/2025-01-28-finetuning_sentiment_model_3000_samples_kctrupa_en.md
new file mode 100644
index 00000000000000..a2adf94c0dd315
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-finetuning_sentiment_model_3000_samples_kctrupa_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_kctrupa DistilBertForSequenceClassification from KCTRUPA
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_kctrupa
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_kctrupa` is a English model originally trained by KCTRUPA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_kctrupa_en_5.5.1_3.0_1738025633862.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_kctrupa_en_5.5.1_3.0_1738025633862.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_kctrupa","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_kctrupa", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_kctrupa|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|246.0 MB|
+
+## References
+
+https://huggingface.co/KCTRUPA/finetuning-sentiment-model-3000-samples
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-finetuning_sentiment_model_3000_samples_kctrupa_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-finetuning_sentiment_model_3000_samples_kctrupa_pipeline_en.md
new file mode 100644
index 00000000000000..eda56a04be17ad
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-finetuning_sentiment_model_3000_samples_kctrupa_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_kctrupa_pipeline pipeline DistilBertForSequenceClassification from KCTRUPA
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_kctrupa_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_kctrupa_pipeline` is a English model originally trained by KCTRUPA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_kctrupa_pipeline_en_5.5.1_3.0_1738025647976.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_kctrupa_pipeline_en_5.5.1_3.0_1738025647976.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuning_sentiment_model_3000_samples_kctrupa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuning_sentiment_model_3000_samples_kctrupa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_kctrupa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|246.0 MB|
+
+## References
+
+https://huggingface.co/KCTRUPA/finetuning-sentiment-model-3000-samples
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-finetuning_sentiment_model_gpt_samples_bert_20_en.md b/docs/_posts/ahmedlone127/2025-01-28-finetuning_sentiment_model_gpt_samples_bert_20_en.md
new file mode 100644
index 00000000000000..76cc6b3dbb8eee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-finetuning_sentiment_model_gpt_samples_bert_20_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuning_sentiment_model_gpt_samples_bert_20 DistilBertForSequenceClassification from vinith1502
+author: John Snow Labs
+name: finetuning_sentiment_model_gpt_samples_bert_20
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_gpt_samples_bert_20` is a English model originally trained by vinith1502.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_gpt_samples_bert_20_en_5.5.1_3.0_1738078130403.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_gpt_samples_bert_20_en_5.5.1_3.0_1738078130403.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_gpt_samples_bert_20","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_gpt_samples_bert_20", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_gpt_samples_bert_20|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/vinith1502/finetuning-sentiment-model-gpt-samples-bert-20
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-finetuning_sentiment_model_gpt_samples_bert_20_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-finetuning_sentiment_model_gpt_samples_bert_20_pipeline_en.md
new file mode 100644
index 00000000000000..c750ee8257777b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-finetuning_sentiment_model_gpt_samples_bert_20_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuning_sentiment_model_gpt_samples_bert_20_pipeline pipeline DistilBertForSequenceClassification from vinith1502
+author: John Snow Labs
+name: finetuning_sentiment_model_gpt_samples_bert_20_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_gpt_samples_bert_20_pipeline` is a English model originally trained by vinith1502.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_gpt_samples_bert_20_pipeline_en_5.5.1_3.0_1738078143628.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_gpt_samples_bert_20_pipeline_en_5.5.1_3.0_1738078143628.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuning_sentiment_model_gpt_samples_bert_20_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuning_sentiment_model_gpt_samples_bert_20_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_gpt_samples_bert_20_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/vinith1502/finetuning-sentiment-model-gpt-samples-bert-20
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-finetuning_t5_paraphrase_generation_en.md b/docs/_posts/ahmedlone127/2025-01-28-finetuning_t5_paraphrase_generation_en.md
new file mode 100644
index 00000000000000..82b15104dd502a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-finetuning_t5_paraphrase_generation_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English finetuning_t5_paraphrase_generation T5Transformer from ahmed792002
+author: John Snow Labs
+name: finetuning_t5_paraphrase_generation
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_t5_paraphrase_generation` is a English model originally trained by ahmed792002.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_t5_paraphrase_generation_en_5.5.1_3.0_1738032858074.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_t5_paraphrase_generation_en_5.5.1_3.0_1738032858074.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("finetuning_t5_paraphrase_generation","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("finetuning_t5_paraphrase_generation", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_t5_paraphrase_generation|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|904.8 MB|
+
+## References
+
+https://huggingface.co/ahmed792002/Finetuning_T5_Paraphrase_Generation
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-finetuning_t5_paraphrase_generation_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-finetuning_t5_paraphrase_generation_pipeline_en.md
new file mode 100644
index 00000000000000..e0aa9ce94fcf12
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-finetuning_t5_paraphrase_generation_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English finetuning_t5_paraphrase_generation_pipeline pipeline T5Transformer from ahmed792002
+author: John Snow Labs
+name: finetuning_t5_paraphrase_generation_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_t5_paraphrase_generation_pipeline` is a English model originally trained by ahmed792002.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_t5_paraphrase_generation_pipeline_en_5.5.1_3.0_1738032907393.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_t5_paraphrase_generation_pipeline_en_5.5.1_3.0_1738032907393.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuning_t5_paraphrase_generation_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuning_t5_paraphrase_generation_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_t5_paraphrase_generation_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|904.8 MB|
+
+## References
+
+https://huggingface.co/ahmed792002/Finetuning_T5_Paraphrase_Generation
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-first_try_poke_en.md b/docs/_posts/ahmedlone127/2025-01-28-first_try_poke_en.md
new file mode 100644
index 00000000000000..6cf70be060b774
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-first_try_poke_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English first_try_poke DistilBertForSequenceClassification from GawdSB
+author: John Snow Labs
+name: first_try_poke
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`first_try_poke` is a English model originally trained by GawdSB.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/first_try_poke_en_5.5.1_3.0_1738025622010.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/first_try_poke_en_5.5.1_3.0_1738025622010.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("first_try_poke","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("first_try_poke", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|first_try_poke|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/GawdSB/first-try-poke
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-first_try_poke_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-first_try_poke_pipeline_en.md
new file mode 100644
index 00000000000000..e8c9c8fa1e5ff6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-first_try_poke_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English first_try_poke_pipeline pipeline DistilBertForSequenceClassification from GawdSB
+author: John Snow Labs
+name: first_try_poke_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`first_try_poke_pipeline` is a English model originally trained by GawdSB.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/first_try_poke_pipeline_en_5.5.1_3.0_1738025635235.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/first_try_poke_pipeline_en_5.5.1_3.0_1738025635235.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("first_try_poke_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("first_try_poke_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|first_try_poke_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/GawdSB/first-try-poke
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-flan_t5_base_lora_wind_energy_v4_2_advanced_en.md b/docs/_posts/ahmedlone127/2025-01-28-flan_t5_base_lora_wind_energy_v4_2_advanced_en.md
new file mode 100644
index 00000000000000..bb09d486712bb6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-flan_t5_base_lora_wind_energy_v4_2_advanced_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English flan_t5_base_lora_wind_energy_v4_2_advanced T5Transformer from nell123
+author: John Snow Labs
+name: flan_t5_base_lora_wind_energy_v4_2_advanced
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_base_lora_wind_energy_v4_2_advanced` is a English model originally trained by nell123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_base_lora_wind_energy_v4_2_advanced_en_5.5.1_3.0_1738030724293.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_base_lora_wind_energy_v4_2_advanced_en_5.5.1_3.0_1738030724293.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("flan_t5_base_lora_wind_energy_v4_2_advanced","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("flan_t5_base_lora_wind_energy_v4_2_advanced", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_base_lora_wind_energy_v4_2_advanced|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/nell123/flan_t5_base-lora_wind_energy-v4.2_advanced
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-flan_t5_base_lora_wind_energy_v4_2_advanced_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-flan_t5_base_lora_wind_energy_v4_2_advanced_pipeline_en.md
new file mode 100644
index 00000000000000..2c8f790062792b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-flan_t5_base_lora_wind_energy_v4_2_advanced_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English flan_t5_base_lora_wind_energy_v4_2_advanced_pipeline pipeline T5Transformer from nell123
+author: John Snow Labs
+name: flan_t5_base_lora_wind_energy_v4_2_advanced_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_base_lora_wind_energy_v4_2_advanced_pipeline` is a English model originally trained by nell123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_base_lora_wind_energy_v4_2_advanced_pipeline_en_5.5.1_3.0_1738030773999.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_base_lora_wind_energy_v4_2_advanced_pipeline_en_5.5.1_3.0_1738030773999.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("flan_t5_base_lora_wind_energy_v4_2_advanced_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("flan_t5_base_lora_wind_energy_v4_2_advanced_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_base_lora_wind_energy_v4_2_advanced_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/nell123/flan_t5_base-lora_wind_energy-v4.2_advanced
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-flan_t5_base_lora_wind_energy_v4_3_advanced_en.md b/docs/_posts/ahmedlone127/2025-01-28-flan_t5_base_lora_wind_energy_v4_3_advanced_en.md
new file mode 100644
index 00000000000000..2a7d786c81dc12
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-flan_t5_base_lora_wind_energy_v4_3_advanced_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English flan_t5_base_lora_wind_energy_v4_3_advanced T5Transformer from nell123
+author: John Snow Labs
+name: flan_t5_base_lora_wind_energy_v4_3_advanced
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_base_lora_wind_energy_v4_3_advanced` is a English model originally trained by nell123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_base_lora_wind_energy_v4_3_advanced_en_5.5.1_3.0_1738031215200.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_base_lora_wind_energy_v4_3_advanced_en_5.5.1_3.0_1738031215200.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("flan_t5_base_lora_wind_energy_v4_3_advanced","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("flan_t5_base_lora_wind_energy_v4_3_advanced", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_base_lora_wind_energy_v4_3_advanced|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/nell123/flan_t5_base-lora_wind_energy-v4.3_advanced
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-flan_t5_base_lora_wind_energy_v4_3_advanced_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-flan_t5_base_lora_wind_energy_v4_3_advanced_pipeline_en.md
new file mode 100644
index 00000000000000..e0ab21faa56da7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-flan_t5_base_lora_wind_energy_v4_3_advanced_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English flan_t5_base_lora_wind_energy_v4_3_advanced_pipeline pipeline T5Transformer from nell123
+author: John Snow Labs
+name: flan_t5_base_lora_wind_energy_v4_3_advanced_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_base_lora_wind_energy_v4_3_advanced_pipeline` is a English model originally trained by nell123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_base_lora_wind_energy_v4_3_advanced_pipeline_en_5.5.1_3.0_1738031264751.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_base_lora_wind_energy_v4_3_advanced_pipeline_en_5.5.1_3.0_1738031264751.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("flan_t5_base_lora_wind_energy_v4_3_advanced_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("flan_t5_base_lora_wind_energy_v4_3_advanced_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_base_lora_wind_energy_v4_3_advanced_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/nell123/flan_t5_base-lora_wind_energy-v4.3_advanced
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-flan_t5_finetuned_galalewida_en.md b/docs/_posts/ahmedlone127/2025-01-28-flan_t5_finetuned_galalewida_en.md
new file mode 100644
index 00000000000000..17f82ea2b958f3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-flan_t5_finetuned_galalewida_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English flan_t5_finetuned_galalewida T5Transformer from GalalEwida
+author: John Snow Labs
+name: flan_t5_finetuned_galalewida
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_finetuned_galalewida` is a English model originally trained by GalalEwida.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_finetuned_galalewida_en_5.5.1_3.0_1738092237900.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_finetuned_galalewida_en_5.5.1_3.0_1738092237900.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("flan_t5_finetuned_galalewida","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("flan_t5_finetuned_galalewida", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_finetuned_galalewida|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|349.8 MB|
+
+## References
+
+https://huggingface.co/GalalEwida/flan-t5-finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-flan_t5_finetuned_galalewida_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-flan_t5_finetuned_galalewida_pipeline_en.md
new file mode 100644
index 00000000000000..913be17eeadf95
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-flan_t5_finetuned_galalewida_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English flan_t5_finetuned_galalewida_pipeline pipeline T5Transformer from GalalEwida
+author: John Snow Labs
+name: flan_t5_finetuned_galalewida_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_finetuned_galalewida_pipeline` is a English model originally trained by GalalEwida.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_finetuned_galalewida_pipeline_en_5.5.1_3.0_1738092258025.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_finetuned_galalewida_pipeline_en_5.5.1_3.0_1738092258025.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("flan_t5_finetuned_galalewida_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("flan_t5_finetuned_galalewida_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_finetuned_galalewida_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|349.8 MB|
+
+## References
+
+https://huggingface.co/GalalEwida/flan-t5-finetuned
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-flan_t5_rouge_durga_q5_clean_3_en.md b/docs/_posts/ahmedlone127/2025-01-28-flan_t5_rouge_durga_q5_clean_3_en.md
new file mode 100644
index 00000000000000..a2125cef2b5907
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-flan_t5_rouge_durga_q5_clean_3_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English flan_t5_rouge_durga_q5_clean_3 T5Transformer from devagonal
+author: John Snow Labs
+name: flan_t5_rouge_durga_q5_clean_3
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_rouge_durga_q5_clean_3` is a English model originally trained by devagonal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_rouge_durga_q5_clean_3_en_5.5.1_3.0_1738074768914.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_rouge_durga_q5_clean_3_en_5.5.1_3.0_1738074768914.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("flan_t5_rouge_durga_q5_clean_3","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("flan_t5_rouge_durga_q5_clean_3", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_rouge_durga_q5_clean_3|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/devagonal/flan-t5-rouge-durga-q5-clean-3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-flan_t5_rouge_durga_q5_clean_3_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-flan_t5_rouge_durga_q5_clean_3_pipeline_en.md
new file mode 100644
index 00000000000000..ebe60c6b278ae8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-flan_t5_rouge_durga_q5_clean_3_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English flan_t5_rouge_durga_q5_clean_3_pipeline pipeline T5Transformer from devagonal
+author: John Snow Labs
+name: flan_t5_rouge_durga_q5_clean_3_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_rouge_durga_q5_clean_3_pipeline` is a English model originally trained by devagonal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_rouge_durga_q5_clean_3_pipeline_en_5.5.1_3.0_1738074828769.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_rouge_durga_q5_clean_3_pipeline_en_5.5.1_3.0_1738074828769.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("flan_t5_rouge_durga_q5_clean_3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("flan_t5_rouge_durga_q5_clean_3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_rouge_durga_q5_clean_3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/devagonal/flan-t5-rouge-durga-q5-clean-3
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-flan_t5_rouge_squad_qg_120c_en.md b/docs/_posts/ahmedlone127/2025-01-28-flan_t5_rouge_squad_qg_120c_en.md
new file mode 100644
index 00000000000000..347a3c3d3cef70
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-flan_t5_rouge_squad_qg_120c_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English flan_t5_rouge_squad_qg_120c T5Transformer from devagonal
+author: John Snow Labs
+name: flan_t5_rouge_squad_qg_120c
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_rouge_squad_qg_120c` is a English model originally trained by devagonal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_rouge_squad_qg_120c_en_5.5.1_3.0_1738031854272.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_rouge_squad_qg_120c_en_5.5.1_3.0_1738031854272.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("flan_t5_rouge_squad_qg_120c","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("flan_t5_rouge_squad_qg_120c", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_rouge_squad_qg_120c|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/devagonal/flan-t5-rouge-squad-qg-120c
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-flan_t5_rouge_squad_qg_120c_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-flan_t5_rouge_squad_qg_120c_pipeline_en.md
new file mode 100644
index 00000000000000..9337141bc91b36
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-flan_t5_rouge_squad_qg_120c_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English flan_t5_rouge_squad_qg_120c_pipeline pipeline T5Transformer from devagonal
+author: John Snow Labs
+name: flan_t5_rouge_squad_qg_120c_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_rouge_squad_qg_120c_pipeline` is a English model originally trained by devagonal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_rouge_squad_qg_120c_pipeline_en_5.5.1_3.0_1738031905619.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_rouge_squad_qg_120c_pipeline_en_5.5.1_3.0_1738031905619.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("flan_t5_rouge_squad_qg_120c_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("flan_t5_rouge_squad_qg_120c_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_rouge_squad_qg_120c_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/devagonal/flan-t5-rouge-squad-qg-120c
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-flan_t5_rouge_squad_qg_120d_en.md b/docs/_posts/ahmedlone127/2025-01-28-flan_t5_rouge_squad_qg_120d_en.md
new file mode 100644
index 00000000000000..4ca28d30e3c188
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-flan_t5_rouge_squad_qg_120d_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English flan_t5_rouge_squad_qg_120d T5Transformer from devagonal
+author: John Snow Labs
+name: flan_t5_rouge_squad_qg_120d
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_rouge_squad_qg_120d` is a English model originally trained by devagonal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_rouge_squad_qg_120d_en_5.5.1_3.0_1738032364178.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_rouge_squad_qg_120d_en_5.5.1_3.0_1738032364178.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("flan_t5_rouge_squad_qg_120d","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("flan_t5_rouge_squad_qg_120d", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_rouge_squad_qg_120d|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/devagonal/flan-t5-rouge-squad-qg-120d
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-flan_t5_rouge_squad_qg_120d_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-flan_t5_rouge_squad_qg_120d_pipeline_en.md
new file mode 100644
index 00000000000000..4a12a41f90c892
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-flan_t5_rouge_squad_qg_120d_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English flan_t5_rouge_squad_qg_120d_pipeline pipeline T5Transformer from devagonal
+author: John Snow Labs
+name: flan_t5_rouge_squad_qg_120d_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_rouge_squad_qg_120d_pipeline` is a English model originally trained by devagonal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_rouge_squad_qg_120d_pipeline_en_5.5.1_3.0_1738032423498.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_rouge_squad_qg_120d_pipeline_en_5.5.1_3.0_1738032423498.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("flan_t5_rouge_squad_qg_120d_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("flan_t5_rouge_squad_qg_120d_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_rouge_squad_qg_120d_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/devagonal/flan-t5-rouge-squad-qg-120d
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-flan_t5_rouge_squad_qg_90_en.md b/docs/_posts/ahmedlone127/2025-01-28-flan_t5_rouge_squad_qg_90_en.md
new file mode 100644
index 00000000000000..4f405398a26e89
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-flan_t5_rouge_squad_qg_90_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English flan_t5_rouge_squad_qg_90 T5Transformer from devagonal
+author: John Snow Labs
+name: flan_t5_rouge_squad_qg_90
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_rouge_squad_qg_90` is a English model originally trained by devagonal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_rouge_squad_qg_90_en_5.5.1_3.0_1738032870085.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_rouge_squad_qg_90_en_5.5.1_3.0_1738032870085.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("flan_t5_rouge_squad_qg_90","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("flan_t5_rouge_squad_qg_90", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_rouge_squad_qg_90|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/devagonal/flan-t5-rouge-squad-qg-90
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-flan_t5_rouge_squad_qg_90_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-flan_t5_rouge_squad_qg_90_pipeline_en.md
new file mode 100644
index 00000000000000..306fb806906145
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-flan_t5_rouge_squad_qg_90_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English flan_t5_rouge_squad_qg_90_pipeline pipeline T5Transformer from devagonal
+author: John Snow Labs
+name: flan_t5_rouge_squad_qg_90_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_rouge_squad_qg_90_pipeline` is a English model originally trained by devagonal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_rouge_squad_qg_90_pipeline_en_5.5.1_3.0_1738032919871.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_rouge_squad_qg_90_pipeline_en_5.5.1_3.0_1738032919871.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("flan_t5_rouge_squad_qg_90_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("flan_t5_rouge_squad_qg_90_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_rouge_squad_qg_90_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/devagonal/flan-t5-rouge-squad-qg-90
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-flan_t5_small_gsm8k_en.md b/docs/_posts/ahmedlone127/2025-01-28-flan_t5_small_gsm8k_en.md
new file mode 100644
index 00000000000000..6210e768700eb6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-flan_t5_small_gsm8k_en.md
@@ -0,0 +1,88 @@
+---
+layout: model
+title: English flan_t5_small_gsm8k T5Transformer from fiveflow
+author: John Snow Labs
+name: flan_t5_small_gsm8k
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_small_gsm8k` is a English model originally trained by fiveflow.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_small_gsm8k_en_5.5.1_3.0_1738073889042.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_small_gsm8k_en_5.5.1_3.0_1738073889042.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("flan_t5_small_gsm8k","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("flan_t5_small_gsm8k", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_small_gsm8k|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|349.8 MB|
+
+## References
+
+References
+
+https://huggingface.co/fiveflow/flan-t5-small-gsm8k
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-flan_t5_small_gsm8k_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-flan_t5_small_gsm8k_pipeline_en.md
new file mode 100644
index 00000000000000..fd44ffc2f1e8a7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-flan_t5_small_gsm8k_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English flan_t5_small_gsm8k_pipeline pipeline T5Transformer from fiveflow
+author: John Snow Labs
+name: flan_t5_small_gsm8k_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_small_gsm8k_pipeline` is a English model originally trained by fiveflow.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_small_gsm8k_pipeline_en_5.5.1_3.0_1738073906800.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_small_gsm8k_pipeline_en_5.5.1_3.0_1738073906800.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("flan_t5_small_gsm8k_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("flan_t5_small_gsm8k_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_small_gsm8k_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|349.8 MB|
+
+## References
+
+References
+
+https://huggingface.co/fiveflow/flan-t5-small-gsm8k
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-flant5_small_sufficiency_classifier_en.md b/docs/_posts/ahmedlone127/2025-01-28-flant5_small_sufficiency_classifier_en.md
new file mode 100644
index 00000000000000..4e6e14216f31fb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-flant5_small_sufficiency_classifier_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English flant5_small_sufficiency_classifier T5Transformer from yjmsvma
+author: John Snow Labs
+name: flant5_small_sufficiency_classifier
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flant5_small_sufficiency_classifier` is a English model originally trained by yjmsvma.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flant5_small_sufficiency_classifier_en_5.5.1_3.0_1738091384914.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flant5_small_sufficiency_classifier_en_5.5.1_3.0_1738091384914.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("flant5_small_sufficiency_classifier","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("flant5_small_sufficiency_classifier", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flant5_small_sufficiency_classifier|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|349.8 MB|
+
+## References
+
+https://huggingface.co/yjmsvma/flant5-small-sufficiency-classifier
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-flant5_small_sufficiency_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-flant5_small_sufficiency_classifier_pipeline_en.md
new file mode 100644
index 00000000000000..75b01fbd3365c8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-flant5_small_sufficiency_classifier_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English flant5_small_sufficiency_classifier_pipeline pipeline T5Transformer from yjmsvma
+author: John Snow Labs
+name: flant5_small_sufficiency_classifier_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flant5_small_sufficiency_classifier_pipeline` is a English model originally trained by yjmsvma.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flant5_small_sufficiency_classifier_pipeline_en_5.5.1_3.0_1738091402505.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flant5_small_sufficiency_classifier_pipeline_en_5.5.1_3.0_1738091402505.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("flant5_small_sufficiency_classifier_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("flant5_small_sufficiency_classifier_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flant5_small_sufficiency_classifier_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|349.8 MB|
+
+## References
+
+https://huggingface.co/yjmsvma/flant5-small-sufficiency-classifier
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-flowertune_llm_google_t5_small_fedavgm_en.md b/docs/_posts/ahmedlone127/2025-01-28-flowertune_llm_google_t5_small_fedavgm_en.md
new file mode 100644
index 00000000000000..ae90ddefdaa3b9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-flowertune_llm_google_t5_small_fedavgm_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English flowertune_llm_google_t5_small_fedavgm T5Transformer from layonsan
+author: John Snow Labs
+name: flowertune_llm_google_t5_small_fedavgm
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flowertune_llm_google_t5_small_fedavgm` is a English model originally trained by layonsan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flowertune_llm_google_t5_small_fedavgm_en_5.5.1_3.0_1738033320273.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flowertune_llm_google_t5_small_fedavgm_en_5.5.1_3.0_1738033320273.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("flowertune_llm_google_t5_small_fedavgm","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("flowertune_llm_google_t5_small_fedavgm", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flowertune_llm_google_t5_small_fedavgm|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|165.4 MB|
+
+## References
+
+https://huggingface.co/layonsan/flowertune-llm-google-t5-small-fedavgm
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-flowertune_llm_google_t5_small_fedavgm_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-flowertune_llm_google_t5_small_fedavgm_pipeline_en.md
new file mode 100644
index 00000000000000..18232c8d3a8a1d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-flowertune_llm_google_t5_small_fedavgm_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English flowertune_llm_google_t5_small_fedavgm_pipeline pipeline T5Transformer from layonsan
+author: John Snow Labs
+name: flowertune_llm_google_t5_small_fedavgm_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flowertune_llm_google_t5_small_fedavgm_pipeline` is a English model originally trained by layonsan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flowertune_llm_google_t5_small_fedavgm_pipeline_en_5.5.1_3.0_1738033362647.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flowertune_llm_google_t5_small_fedavgm_pipeline_en_5.5.1_3.0_1738033362647.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("flowertune_llm_google_t5_small_fedavgm_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("flowertune_llm_google_t5_small_fedavgm_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flowertune_llm_google_t5_small_fedavgm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|165.4 MB|
+
+## References
+
+https://huggingface.co/layonsan/flowertune-llm-google-t5-small-fedavgm
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-frozenlast_8epoch_bert_multilingual_finetuned_cefr_ner_3000news_pipeline_xx.md b/docs/_posts/ahmedlone127/2025-01-28-frozenlast_8epoch_bert_multilingual_finetuned_cefr_ner_3000news_pipeline_xx.md
new file mode 100644
index 00000000000000..d1485d011a2661
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-frozenlast_8epoch_bert_multilingual_finetuned_cefr_ner_3000news_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual frozenlast_8epoch_bert_multilingual_finetuned_cefr_ner_3000news_pipeline pipeline BertForTokenClassification from DioBot2000
+author: John Snow Labs
+name: frozenlast_8epoch_bert_multilingual_finetuned_cefr_ner_3000news_pipeline
+date: 2025-01-28
+tags: [xx, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`frozenlast_8epoch_bert_multilingual_finetuned_cefr_ner_3000news_pipeline` is a Multilingual model originally trained by DioBot2000.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/frozenlast_8epoch_bert_multilingual_finetuned_cefr_ner_3000news_pipeline_xx_5.5.1_3.0_1738044536880.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/frozenlast_8epoch_bert_multilingual_finetuned_cefr_ner_3000news_pipeline_xx_5.5.1_3.0_1738044536880.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("frozenlast_8epoch_bert_multilingual_finetuned_cefr_ner_3000news_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("frozenlast_8epoch_bert_multilingual_finetuned_cefr_ner_3000news_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|frozenlast_8epoch_bert_multilingual_finetuned_cefr_ner_3000news_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/DioBot2000/FrozenLAST-8epoch-BERT-multilingual-finetuned-CEFR_ner-3000news
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-frozenlast_8epoch_bert_multilingual_finetuned_cefr_ner_3000news_xx.md b/docs/_posts/ahmedlone127/2025-01-28-frozenlast_8epoch_bert_multilingual_finetuned_cefr_ner_3000news_xx.md
new file mode 100644
index 00000000000000..ddef6a439622fc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-frozenlast_8epoch_bert_multilingual_finetuned_cefr_ner_3000news_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual frozenlast_8epoch_bert_multilingual_finetuned_cefr_ner_3000news BertForTokenClassification from DioBot2000
+author: John Snow Labs
+name: frozenlast_8epoch_bert_multilingual_finetuned_cefr_ner_3000news
+date: 2025-01-28
+tags: [xx, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`frozenlast_8epoch_bert_multilingual_finetuned_cefr_ner_3000news` is a Multilingual model originally trained by DioBot2000.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/frozenlast_8epoch_bert_multilingual_finetuned_cefr_ner_3000news_xx_5.5.1_3.0_1738044504476.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/frozenlast_8epoch_bert_multilingual_finetuned_cefr_ner_3000news_xx_5.5.1_3.0_1738044504476.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("frozenlast_8epoch_bert_multilingual_finetuned_cefr_ner_3000news","xx") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("frozenlast_8epoch_bert_multilingual_finetuned_cefr_ner_3000news", "xx")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|frozenlast_8epoch_bert_multilingual_finetuned_cefr_ner_3000news|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|xx|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/DioBot2000/FrozenLAST-8epoch-BERT-multilingual-finetuned-CEFR_ner-3000news
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-ft5_bleu_durga_q1_clean_en.md b/docs/_posts/ahmedlone127/2025-01-28-ft5_bleu_durga_q1_clean_en.md
new file mode 100644
index 00000000000000..380bc397f36663
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-ft5_bleu_durga_q1_clean_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English ft5_bleu_durga_q1_clean T5Transformer from devagonal
+author: John Snow Labs
+name: ft5_bleu_durga_q1_clean
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ft5_bleu_durga_q1_clean` is a English model originally trained by devagonal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ft5_bleu_durga_q1_clean_en_5.5.1_3.0_1738072709262.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ft5_bleu_durga_q1_clean_en_5.5.1_3.0_1738072709262.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("ft5_bleu_durga_q1_clean","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("ft5_bleu_durga_q1_clean", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ft5_bleu_durga_q1_clean|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/devagonal/ft5-bleu-durga-q1-clean
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-ft5_bleu_durga_q1_clean_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-ft5_bleu_durga_q1_clean_pipeline_en.md
new file mode 100644
index 00000000000000..9ffecd792faaed
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-ft5_bleu_durga_q1_clean_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English ft5_bleu_durga_q1_clean_pipeline pipeline T5Transformer from devagonal
+author: John Snow Labs
+name: ft5_bleu_durga_q1_clean_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ft5_bleu_durga_q1_clean_pipeline` is a English model originally trained by devagonal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ft5_bleu_durga_q1_clean_pipeline_en_5.5.1_3.0_1738072778947.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ft5_bleu_durga_q1_clean_pipeline_en_5.5.1_3.0_1738072778947.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ft5_bleu_durga_q1_clean_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ft5_bleu_durga_q1_clean_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ft5_bleu_durga_q1_clean_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/devagonal/ft5-bleu-durga-q1-clean
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-ft_distilbert_base_uncased_rnribeiro_en.md b/docs/_posts/ahmedlone127/2025-01-28-ft_distilbert_base_uncased_rnribeiro_en.md
new file mode 100644
index 00000000000000..0a64c0281da4cb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-ft_distilbert_base_uncased_rnribeiro_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ft_distilbert_base_uncased_rnribeiro DistilBertForSequenceClassification from rnribeiro
+author: John Snow Labs
+name: ft_distilbert_base_uncased_rnribeiro
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ft_distilbert_base_uncased_rnribeiro` is a English model originally trained by rnribeiro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ft_distilbert_base_uncased_rnribeiro_en_5.5.1_3.0_1738077598949.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ft_distilbert_base_uncased_rnribeiro_en_5.5.1_3.0_1738077598949.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("ft_distilbert_base_uncased_rnribeiro","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("ft_distilbert_base_uncased_rnribeiro", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ft_distilbert_base_uncased_rnribeiro|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/rnribeiro/FT-distilbert-base-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-ft_distilbert_base_uncased_rnribeiro_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-ft_distilbert_base_uncased_rnribeiro_pipeline_en.md
new file mode 100644
index 00000000000000..b4eee6714322e3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-ft_distilbert_base_uncased_rnribeiro_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ft_distilbert_base_uncased_rnribeiro_pipeline pipeline DistilBertForSequenceClassification from rnribeiro
+author: John Snow Labs
+name: ft_distilbert_base_uncased_rnribeiro_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ft_distilbert_base_uncased_rnribeiro_pipeline` is a English model originally trained by rnribeiro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ft_distilbert_base_uncased_rnribeiro_pipeline_en_5.5.1_3.0_1738077612180.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ft_distilbert_base_uncased_rnribeiro_pipeline_en_5.5.1_3.0_1738077612180.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ft_distilbert_base_uncased_rnribeiro_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ft_distilbert_base_uncased_rnribeiro_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ft_distilbert_base_uncased_rnribeiro_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/rnribeiro/FT-distilbert-base-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-ft_t5_small_dutch_2_fol_v1_en.md b/docs/_posts/ahmedlone127/2025-01-28-ft_t5_small_dutch_2_fol_v1_en.md
new file mode 100644
index 00000000000000..d6cd88ee9621a2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-ft_t5_small_dutch_2_fol_v1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English ft_t5_small_dutch_2_fol_v1 T5Transformer from tuanbc88
+author: John Snow Labs
+name: ft_t5_small_dutch_2_fol_v1
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ft_t5_small_dutch_2_fol_v1` is a English model originally trained by tuanbc88.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ft_t5_small_dutch_2_fol_v1_en_5.5.1_3.0_1738074318780.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ft_t5_small_dutch_2_fol_v1_en_5.5.1_3.0_1738074318780.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("ft_t5_small_dutch_2_fol_v1","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("ft_t5_small_dutch_2_fol_v1", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ft_t5_small_dutch_2_fol_v1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|147.2 MB|
+
+## References
+
+https://huggingface.co/tuanbc88/ft-t5-small-nl-2-fol-v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-ft_t5_small_dutch_2_fol_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-ft_t5_small_dutch_2_fol_v1_pipeline_en.md
new file mode 100644
index 00000000000000..bba84a72b61cab
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-ft_t5_small_dutch_2_fol_v1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English ft_t5_small_dutch_2_fol_v1_pipeline pipeline T5Transformer from tuanbc88
+author: John Snow Labs
+name: ft_t5_small_dutch_2_fol_v1_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ft_t5_small_dutch_2_fol_v1_pipeline` is a English model originally trained by tuanbc88.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ft_t5_small_dutch_2_fol_v1_pipeline_en_5.5.1_3.0_1738074365812.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ft_t5_small_dutch_2_fol_v1_pipeline_en_5.5.1_3.0_1738074365812.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ft_t5_small_dutch_2_fol_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ft_t5_small_dutch_2_fol_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ft_t5_small_dutch_2_fol_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|147.2 MB|
+
+## References
+
+https://huggingface.co/tuanbc88/ft-t5-small-nl-2-fol-v1
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-gendered_dataset_en.md b/docs/_posts/ahmedlone127/2025-01-28-gendered_dataset_en.md
new file mode 100644
index 00000000000000..3657c69f7798d4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-gendered_dataset_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English gendered_dataset DistilBertForSequenceClassification from C-Lo
+author: John Snow Labs
+name: gendered_dataset
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gendered_dataset` is a English model originally trained by C-Lo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gendered_dataset_en_5.5.1_3.0_1738025512521.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gendered_dataset_en_5.5.1_3.0_1738025512521.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("gendered_dataset","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("gendered_dataset", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gendered_dataset|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/C-Lo/gendered-dataset
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-gendered_dataset_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-gendered_dataset_pipeline_en.md
new file mode 100644
index 00000000000000..a96ad85b3e13c4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-gendered_dataset_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English gendered_dataset_pipeline pipeline DistilBertForSequenceClassification from C-Lo
+author: John Snow Labs
+name: gendered_dataset_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gendered_dataset_pipeline` is a English model originally trained by C-Lo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gendered_dataset_pipeline_en_5.5.1_3.0_1738025525174.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gendered_dataset_pipeline_en_5.5.1_3.0_1738025525174.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gendered_dataset_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gendered_dataset_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gendered_dataset_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/C-Lo/gendered-dataset
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-geobertje_base_dutch_uncased_nl.md b/docs/_posts/ahmedlone127/2025-01-28-geobertje_base_dutch_uncased_nl.md
new file mode 100644
index 00000000000000..7a9b0bd9ec3fba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-geobertje_base_dutch_uncased_nl.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Dutch, Flemish geobertje_base_dutch_uncased BertEmbeddings from hghcomphys
+author: John Snow Labs
+name: geobertje_base_dutch_uncased
+date: 2025-01-28
+tags: [nl, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: nl
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`geobertje_base_dutch_uncased` is a Dutch, Flemish model originally trained by hghcomphys.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/geobertje_base_dutch_uncased_nl_5.5.1_3.0_1738039577621.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/geobertje_base_dutch_uncased_nl_5.5.1_3.0_1738039577621.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("geobertje_base_dutch_uncased","nl") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("geobertje_base_dutch_uncased","nl") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|geobertje_base_dutch_uncased|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|nl|
+|Size:|406.4 MB|
+
+## References
+
+https://huggingface.co/hghcomphys/geobertje-base-dutch-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-geobertje_base_dutch_uncased_pipeline_nl.md b/docs/_posts/ahmedlone127/2025-01-28-geobertje_base_dutch_uncased_pipeline_nl.md
new file mode 100644
index 00000000000000..8d3e35ec963da5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-geobertje_base_dutch_uncased_pipeline_nl.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Dutch, Flemish geobertje_base_dutch_uncased_pipeline pipeline BertEmbeddings from hghcomphys
+author: John Snow Labs
+name: geobertje_base_dutch_uncased_pipeline
+date: 2025-01-28
+tags: [nl, open_source, pipeline, onnx]
+task: Embeddings
+language: nl
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`geobertje_base_dutch_uncased_pipeline` is a Dutch, Flemish model originally trained by hghcomphys.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/geobertje_base_dutch_uncased_pipeline_nl_5.5.1_3.0_1738039598086.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/geobertje_base_dutch_uncased_pipeline_nl_5.5.1_3.0_1738039598086.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("geobertje_base_dutch_uncased_pipeline", lang = "nl")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("geobertje_base_dutch_uncased_pipeline", lang = "nl")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|geobertje_base_dutch_uncased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|nl|
+|Size:|406.4 MB|
+
+## References
+
+https://huggingface.co/hghcomphys/geobertje-base-dutch-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-geoplantbert_fill_mask_model_en.md b/docs/_posts/ahmedlone127/2025-01-28-geoplantbert_fill_mask_model_en.md
new file mode 100644
index 00000000000000..ec3c001d1de7c7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-geoplantbert_fill_mask_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English geoplantbert_fill_mask_model BertEmbeddings from CesarLeblanc
+author: John Snow Labs
+name: geoplantbert_fill_mask_model
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`geoplantbert_fill_mask_model` is a English model originally trained by CesarLeblanc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/geoplantbert_fill_mask_model_en_5.5.1_3.0_1738096663790.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/geoplantbert_fill_mask_model_en_5.5.1_3.0_1738096663790.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("geoplantbert_fill_mask_model","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("geoplantbert_fill_mask_model","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|geoplantbert_fill_mask_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/CesarLeblanc/geoplantbert_fill_mask_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-geoplantbert_fill_mask_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-geoplantbert_fill_mask_model_pipeline_en.md
new file mode 100644
index 00000000000000..a92772c8e5a8b6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-geoplantbert_fill_mask_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English geoplantbert_fill_mask_model_pipeline pipeline BertEmbeddings from CesarLeblanc
+author: John Snow Labs
+name: geoplantbert_fill_mask_model_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`geoplantbert_fill_mask_model_pipeline` is a English model originally trained by CesarLeblanc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/geoplantbert_fill_mask_model_pipeline_en_5.5.1_3.0_1738096726771.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/geoplantbert_fill_mask_model_pipeline_en_5.5.1_3.0_1738096726771.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("geoplantbert_fill_mask_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("geoplantbert_fill_mask_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|geoplantbert_fill_mask_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/CesarLeblanc/geoplantbert_fill_mask_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-giecom_vit_model_clasification_waste_en.md b/docs/_posts/ahmedlone127/2025-01-28-giecom_vit_model_clasification_waste_en.md
new file mode 100644
index 00000000000000..9535855cb75f1e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-giecom_vit_model_clasification_waste_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English giecom_vit_model_clasification_waste ViTForImageClassification from Giecom
+author: John Snow Labs
+name: giecom_vit_model_clasification_waste
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`giecom_vit_model_clasification_waste` is a English model originally trained by Giecom.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/giecom_vit_model_clasification_waste_en_5.5.1_3.0_1738023201758.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/giecom_vit_model_clasification_waste_en_5.5.1_3.0_1738023201758.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""giecom_vit_model_clasification_waste","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("giecom_vit_model_clasification_waste","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|giecom_vit_model_clasification_waste|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/Giecom/giecom-vit-model-clasification-waste
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-giecom_vit_model_clasification_waste_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-giecom_vit_model_clasification_waste_pipeline_en.md
new file mode 100644
index 00000000000000..174042037553a2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-giecom_vit_model_clasification_waste_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English giecom_vit_model_clasification_waste_pipeline pipeline ViTForImageClassification from Giecom
+author: John Snow Labs
+name: giecom_vit_model_clasification_waste_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`giecom_vit_model_clasification_waste_pipeline` is a English model originally trained by Giecom.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/giecom_vit_model_clasification_waste_pipeline_en_5.5.1_3.0_1738023218892.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/giecom_vit_model_clasification_waste_pipeline_en_5.5.1_3.0_1738023218892.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("giecom_vit_model_clasification_waste_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("giecom_vit_model_clasification_waste_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|giecom_vit_model_clasification_waste_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/Giecom/giecom-vit-model-clasification-waste
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-gpt2_id.md b/docs/_posts/ahmedlone127/2025-01-28-gpt2_id.md
new file mode 100644
index 00000000000000..8851528c1684a8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-gpt2_id.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Indonesian gpt2 GPT2Transformer from indonesian-nlp
+author: John Snow Labs
+name: gpt2
+date: 2025-01-28
+tags: [id, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: id
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2` is a Indonesian model originally trained by indonesian-nlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_id_5.5.1_3.0_1738041642420.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_id_5.5.1_3.0_1738041642420.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("gpt2","id") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("gpt2","id") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|id|
+|Size:|467.4 MB|
+
+## References
+
+https://huggingface.co/indonesian-nlp/gpt2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-gpt2_pipeline_id.md b/docs/_posts/ahmedlone127/2025-01-28-gpt2_pipeline_id.md
new file mode 100644
index 00000000000000..97c0dbe2304c0c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-gpt2_pipeline_id.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Indonesian gpt2_pipeline pipeline GPT2Transformer from indonesian-nlp
+author: John Snow Labs
+name: gpt2_pipeline
+date: 2025-01-28
+tags: [id, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: id
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_pipeline` is a Indonesian model originally trained by indonesian-nlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_pipeline_id_5.5.1_3.0_1738041667445.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_pipeline_id_5.5.1_3.0_1738041667445.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpt2_pipeline", lang = "id")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpt2_pipeline", lang = "id")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|id|
+|Size:|467.4 MB|
+
+## References
+
+https://huggingface.co/indonesian-nlp/gpt2
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-gpt2_product_description_generator_en.md b/docs/_posts/ahmedlone127/2025-01-28-gpt2_product_description_generator_en.md
new file mode 100644
index 00000000000000..0778a701565b56
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-gpt2_product_description_generator_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English gpt2_product_description_generator GPT2Transformer from HamidRezaAttar
+author: John Snow Labs
+name: gpt2_product_description_generator
+date: 2025-01-28
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_product_description_generator` is a English model originally trained by HamidRezaAttar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_product_description_generator_en_5.5.1_3.0_1738043533033.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_product_description_generator_en_5.5.1_3.0_1738043533033.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("gpt2_product_description_generator","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("gpt2_product_description_generator","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_product_description_generator|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.9 MB|
+
+## References
+
+https://huggingface.co/HamidRezaAttar/gpt2-product-description-generator
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-gpt2_product_description_generator_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-gpt2_product_description_generator_pipeline_en.md
new file mode 100644
index 00000000000000..98e2db13678784
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-gpt2_product_description_generator_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English gpt2_product_description_generator_pipeline pipeline GPT2Transformer from HamidRezaAttar
+author: John Snow Labs
+name: gpt2_product_description_generator_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_product_description_generator_pipeline` is a English model originally trained by HamidRezaAttar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_product_description_generator_pipeline_en_5.5.1_3.0_1738043556064.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_product_description_generator_pipeline_en_5.5.1_3.0_1738043556064.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpt2_product_description_generator_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpt2_product_description_generator_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2_product_description_generator_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.9 MB|
+
+## References
+
+https://huggingface.co/HamidRezaAttar/gpt2-product-description-generator
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-gpt2medium_text_tonga_tonga_islands_sql_en.md b/docs/_posts/ahmedlone127/2025-01-28-gpt2medium_text_tonga_tonga_islands_sql_en.md
new file mode 100644
index 00000000000000..8fc82a5158d23f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-gpt2medium_text_tonga_tonga_islands_sql_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English gpt2medium_text_tonga_tonga_islands_sql GPT2Transformer from rakeshkiriyath
+author: John Snow Labs
+name: gpt2medium_text_tonga_tonga_islands_sql
+date: 2025-01-28
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2medium_text_tonga_tonga_islands_sql` is a English model originally trained by rakeshkiriyath.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2medium_text_tonga_tonga_islands_sql_en_5.5.1_3.0_1738042358796.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2medium_text_tonga_tonga_islands_sql_en_5.5.1_3.0_1738042358796.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("gpt2medium_text_tonga_tonga_islands_sql","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("gpt2medium_text_tonga_tonga_islands_sql","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2medium_text_tonga_tonga_islands_sql|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/rakeshkiriyath/gpt2Medium_text_to_sql
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-gpt2medium_text_tonga_tonga_islands_sql_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-gpt2medium_text_tonga_tonga_islands_sql_pipeline_en.md
new file mode 100644
index 00000000000000..8dc5e787b0f4bc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-gpt2medium_text_tonga_tonga_islands_sql_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English gpt2medium_text_tonga_tonga_islands_sql_pipeline pipeline GPT2Transformer from rakeshkiriyath
+author: John Snow Labs
+name: gpt2medium_text_tonga_tonga_islands_sql_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2medium_text_tonga_tonga_islands_sql_pipeline` is a English model originally trained by rakeshkiriyath.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2medium_text_tonga_tonga_islands_sql_pipeline_en_5.5.1_3.0_1738042422627.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2medium_text_tonga_tonga_islands_sql_pipeline_en_5.5.1_3.0_1738042422627.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpt2medium_text_tonga_tonga_islands_sql_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpt2medium_text_tonga_tonga_islands_sql_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt2medium_text_tonga_tonga_islands_sql_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/rakeshkiriyath/gpt2Medium_text_to_sql
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-gpt_2_tamil_abinayam_pipeline_ta.md b/docs/_posts/ahmedlone127/2025-01-28-gpt_2_tamil_abinayam_pipeline_ta.md
new file mode 100644
index 00000000000000..378d45715a9011
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-gpt_2_tamil_abinayam_pipeline_ta.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Tamil gpt_2_tamil_abinayam_pipeline pipeline GPT2Transformer from abinayam
+author: John Snow Labs
+name: gpt_2_tamil_abinayam_pipeline
+date: 2025-01-28
+tags: [ta, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: ta
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt_2_tamil_abinayam_pipeline` is a Tamil model originally trained by abinayam.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt_2_tamil_abinayam_pipeline_ta_5.5.1_3.0_1738043298102.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt_2_tamil_abinayam_pipeline_ta_5.5.1_3.0_1738043298102.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpt_2_tamil_abinayam_pipeline", lang = "ta")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpt_2_tamil_abinayam_pipeline", lang = "ta")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt_2_tamil_abinayam_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ta|
+|Size:|467.2 MB|
+
+## References
+
+https://huggingface.co/abinayam/gpt-2-tamil
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-gpt_2_tamil_abinayam_ta.md b/docs/_posts/ahmedlone127/2025-01-28-gpt_2_tamil_abinayam_ta.md
new file mode 100644
index 00000000000000..63f53d36cf2ad2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-gpt_2_tamil_abinayam_ta.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Tamil gpt_2_tamil_abinayam GPT2Transformer from abinayam
+author: John Snow Labs
+name: gpt_2_tamil_abinayam
+date: 2025-01-28
+tags: [ta, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: ta
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt_2_tamil_abinayam` is a Tamil model originally trained by abinayam.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt_2_tamil_abinayam_ta_5.5.1_3.0_1738043275133.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt_2_tamil_abinayam_ta_5.5.1_3.0_1738043275133.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("gpt_2_tamil_abinayam","ta") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("gpt_2_tamil_abinayam","ta") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt_2_tamil_abinayam|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|ta|
+|Size:|467.2 MB|
+
+## References
+
+https://huggingface.co/abinayam/gpt-2-tamil
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-gpt_czech_poet_cs.md b/docs/_posts/ahmedlone127/2025-01-28-gpt_czech_poet_cs.md
new file mode 100644
index 00000000000000..eaca3b3e333dfa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-gpt_czech_poet_cs.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Czech gpt_czech_poet GPT2Transformer from jinymusim
+author: John Snow Labs
+name: gpt_czech_poet
+date: 2025-01-28
+tags: [cs, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: cs
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt_czech_poet` is a Czech model originally trained by jinymusim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt_czech_poet_cs_5.5.1_3.0_1738042053179.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt_czech_poet_cs_5.5.1_3.0_1738042053179.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("gpt_czech_poet","cs") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("gpt_czech_poet","cs") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt_czech_poet|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|cs|
+|Size:|467.1 MB|
+
+## References
+
+https://huggingface.co/jinymusim/gpt-czech-poet
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-gpt_czech_poet_pipeline_cs.md b/docs/_posts/ahmedlone127/2025-01-28-gpt_czech_poet_pipeline_cs.md
new file mode 100644
index 00000000000000..1127f6fafc8101
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-gpt_czech_poet_pipeline_cs.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Czech gpt_czech_poet_pipeline pipeline GPT2Transformer from jinymusim
+author: John Snow Labs
+name: gpt_czech_poet_pipeline
+date: 2025-01-28
+tags: [cs, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: cs
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt_czech_poet_pipeline` is a Czech model originally trained by jinymusim.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt_czech_poet_pipeline_cs_5.5.1_3.0_1738042076598.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt_czech_poet_pipeline_cs_5.5.1_3.0_1738042076598.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gpt_czech_poet_pipeline", lang = "cs")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gpt_czech_poet_pipeline", lang = "cs")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gpt_czech_poet_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|cs|
+|Size:|467.1 MB|
+
+## References
+
+https://huggingface.co/jinymusim/gpt-czech-poet
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-group12_mlm_distilled_roberta_ft_en.md b/docs/_posts/ahmedlone127/2025-01-28-group12_mlm_distilled_roberta_ft_en.md
new file mode 100644
index 00000000000000..b59b923cca90e0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-group12_mlm_distilled_roberta_ft_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English group12_mlm_distilled_roberta_ft RoBertaEmbeddings from twburns
+author: John Snow Labs
+name: group12_mlm_distilled_roberta_ft
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`group12_mlm_distilled_roberta_ft` is a English model originally trained by twburns.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/group12_mlm_distilled_roberta_ft_en_5.5.1_3.0_1738103368459.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/group12_mlm_distilled_roberta_ft_en_5.5.1_3.0_1738103368459.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("group12_mlm_distilled_roberta_ft","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("group12_mlm_distilled_roberta_ft","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|group12_mlm_distilled_roberta_ft|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|306.4 MB|
+
+## References
+
+https://huggingface.co/twburns/group12_mlm_Distilled_Roberta-ft
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-group12_mlm_distilled_roberta_ft_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-group12_mlm_distilled_roberta_ft_pipeline_en.md
new file mode 100644
index 00000000000000..d75fa99a19b91e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-group12_mlm_distilled_roberta_ft_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English group12_mlm_distilled_roberta_ft_pipeline pipeline RoBertaEmbeddings from twburns
+author: John Snow Labs
+name: group12_mlm_distilled_roberta_ft_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`group12_mlm_distilled_roberta_ft_pipeline` is a English model originally trained by twburns.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/group12_mlm_distilled_roberta_ft_pipeline_en_5.5.1_3.0_1738103383837.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/group12_mlm_distilled_roberta_ft_pipeline_en_5.5.1_3.0_1738103383837.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("group12_mlm_distilled_roberta_ft_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("group12_mlm_distilled_roberta_ft_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|group12_mlm_distilled_roberta_ft_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/twburns/group12_mlm_Distilled_Roberta-ft
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-group_model_yunbora_v_3_bert_en.md b/docs/_posts/ahmedlone127/2025-01-28-group_model_yunbora_v_3_bert_en.md
new file mode 100644
index 00000000000000..7415bb9edb0aa4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-group_model_yunbora_v_3_bert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English group_model_yunbora_v_3_bert BertForSequenceClassification from Inna432
+author: John Snow Labs
+name: group_model_yunbora_v_3_bert
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`group_model_yunbora_v_3_bert` is a English model originally trained by Inna432.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/group_model_yunbora_v_3_bert_en_5.5.1_3.0_1738051895172.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/group_model_yunbora_v_3_bert_en_5.5.1_3.0_1738051895172.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("group_model_yunbora_v_3_bert","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("group_model_yunbora_v_3_bert", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|group_model_yunbora_v_3_bert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/Inna432/group_model_yunbora-v.3-bert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-group_model_yunbora_v_3_bert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-group_model_yunbora_v_3_bert_pipeline_en.md
new file mode 100644
index 00000000000000..fc13e54a644ba0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-group_model_yunbora_v_3_bert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English group_model_yunbora_v_3_bert_pipeline pipeline BertForSequenceClassification from Inna432
+author: John Snow Labs
+name: group_model_yunbora_v_3_bert_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`group_model_yunbora_v_3_bert_pipeline` is a English model originally trained by Inna432.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/group_model_yunbora_v_3_bert_pipeline_en_5.5.1_3.0_1738051915697.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/group_model_yunbora_v_3_bert_pipeline_en_5.5.1_3.0_1738051915697.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("group_model_yunbora_v_3_bert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("group_model_yunbora_v_3_bert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|group_model_yunbora_v_3_bert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/Inna432/group_model_yunbora-v.3-bert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-gtsrb_model_en.md b/docs/_posts/ahmedlone127/2025-01-28-gtsrb_model_en.md
new file mode 100644
index 00000000000000..a3243d6db92bb4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-gtsrb_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English gtsrb_model ViTForImageClassification from bazyl
+author: John Snow Labs
+name: gtsrb_model
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gtsrb_model` is a English model originally trained by bazyl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gtsrb_model_en_5.5.1_3.0_1738022726422.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gtsrb_model_en_5.5.1_3.0_1738022726422.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""gtsrb_model","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("gtsrb_model","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gtsrb_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.4 MB|
+
+## References
+
+https://huggingface.co/bazyl/gtsrb-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-gtsrb_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-gtsrb_model_pipeline_en.md
new file mode 100644
index 00000000000000..04f368f13c3da1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-gtsrb_model_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English gtsrb_model_pipeline pipeline ViTForImageClassification from bazyl
+author: John Snow Labs
+name: gtsrb_model_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gtsrb_model_pipeline` is a English model originally trained by bazyl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gtsrb_model_pipeline_en_5.5.1_3.0_1738022746976.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gtsrb_model_pipeline_en_5.5.1_3.0_1738022746976.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("gtsrb_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gtsrb_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gtsrb_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.4 MB|
+
+## References
+
+https://huggingface.co/bazyl/gtsrb-model
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-hanyundudddd_en.md b/docs/_posts/ahmedlone127/2025-01-28-hanyundudddd_en.md
new file mode 100644
index 00000000000000..51e63e23f1278f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-hanyundudddd_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English hanyundudddd DistilBertForSequenceClassification from hanyundudddd
+author: John Snow Labs
+name: hanyundudddd
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hanyundudddd` is a English model originally trained by hanyundudddd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hanyundudddd_en_5.5.1_3.0_1738026043424.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hanyundudddd_en_5.5.1_3.0_1738026043424.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("hanyundudddd","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("hanyundudddd", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hanyundudddd|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/hanyundudddd/hanyundudddd
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-hanyundudddd_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-hanyundudddd_pipeline_en.md
new file mode 100644
index 00000000000000..cafcf7b2c280f4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-hanyundudddd_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English hanyundudddd_pipeline pipeline DistilBertForSequenceClassification from hanyundudddd
+author: John Snow Labs
+name: hanyundudddd_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hanyundudddd_pipeline` is a English model originally trained by hanyundudddd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hanyundudddd_pipeline_en_5.5.1_3.0_1738026056648.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hanyundudddd_pipeline_en_5.5.1_3.0_1738026056648.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("hanyundudddd_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hanyundudddd_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hanyundudddd_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/hanyundudddd/hanyundudddd
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-heart_bert_en.md b/docs/_posts/ahmedlone127/2025-01-28-heart_bert_en.md
new file mode 100644
index 00000000000000..c92023c9996525
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-heart_bert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English heart_bert BertEmbeddings from fuyingw
+author: John Snow Labs
+name: heart_bert
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`heart_bert` is a English model originally trained by fuyingw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/heart_bert_en_5.5.1_3.0_1738085214528.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/heart_bert_en_5.5.1_3.0_1738085214528.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("heart_bert","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("heart_bert","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|heart_bert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|408.1 MB|
+
+## References
+
+https://huggingface.co/fuyingw/heart_bert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-heart_bert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-heart_bert_pipeline_en.md
new file mode 100644
index 00000000000000..f257adf51210a8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-heart_bert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English heart_bert_pipeline pipeline BertEmbeddings from fuyingw
+author: John Snow Labs
+name: heart_bert_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`heart_bert_pipeline` is a English model originally trained by fuyingw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/heart_bert_pipeline_en_5.5.1_3.0_1738085235269.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/heart_bert_pipeline_en_5.5.1_3.0_1738085235269.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("heart_bert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("heart_bert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|heart_bert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|408.1 MB|
+
+## References
+
+https://huggingface.co/fuyingw/heart_bert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-hfmodels_en.md b/docs/_posts/ahmedlone127/2025-01-28-hfmodels_en.md
new file mode 100644
index 00000000000000..0d6123bbb0a658
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-hfmodels_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English hfmodels T5Transformer from AbdallahElraey
+author: John Snow Labs
+name: hfmodels
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hfmodels` is a English model originally trained by AbdallahElraey.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hfmodels_en_5.5.1_3.0_1738074252363.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hfmodels_en_5.5.1_3.0_1738074252363.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("hfmodels","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("hfmodels", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hfmodels|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|238.8 MB|
+
+## References
+
+https://huggingface.co/AbdallahElraey/HFmodels
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-hfmodels_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-hfmodels_pipeline_en.md
new file mode 100644
index 00000000000000..7f96fb141318c7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-hfmodels_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English hfmodels_pipeline pipeline T5Transformer from AbdallahElraey
+author: John Snow Labs
+name: hfmodels_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hfmodels_pipeline` is a English model originally trained by AbdallahElraey.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hfmodels_pipeline_en_5.5.1_3.0_1738074274838.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hfmodels_pipeline_en_5.5.1_3.0_1738074274838.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("hfmodels_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hfmodels_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hfmodels_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|238.8 MB|
+
+## References
+
+https://huggingface.co/AbdallahElraey/HFmodels
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-high_0_en.md b/docs/_posts/ahmedlone127/2025-01-28-high_0_en.md
new file mode 100644
index 00000000000000..d6dfed115e5727
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-high_0_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English high_0 BertForQuestionAnswering from Jing24
+author: John Snow Labs
+name: high_0
+date: 2025-01-28
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`high_0` is a English model originally trained by Jing24.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/high_0_en_5.5.1_3.0_1738062576336.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/high_0_en_5.5.1_3.0_1738062576336.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("high_0","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("high_0", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|high_0|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/Jing24/high-0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-high_0_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-high_0_pipeline_en.md
new file mode 100644
index 00000000000000..ea62844fb63336
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-high_0_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English high_0_pipeline pipeline BertForQuestionAnswering from Jing24
+author: John Snow Labs
+name: high_0_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`high_0_pipeline` is a English model originally trained by Jing24.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/high_0_pipeline_en_5.5.1_3.0_1738062596431.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/high_0_pipeline_en_5.5.1_3.0_1738062596431.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("high_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("high_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|high_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/Jing24/high-0
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-hupd_mlm_distilroberta_en.md b/docs/_posts/ahmedlone127/2025-01-28-hupd_mlm_distilroberta_en.md
new file mode 100644
index 00000000000000..bbcd9069546127
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-hupd_mlm_distilroberta_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English hupd_mlm_distilroberta RoBertaEmbeddings from cfcooney
+author: John Snow Labs
+name: hupd_mlm_distilroberta
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hupd_mlm_distilroberta` is a English model originally trained by cfcooney.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hupd_mlm_distilroberta_en_5.5.1_3.0_1738102995732.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hupd_mlm_distilroberta_en_5.5.1_3.0_1738102995732.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("hupd_mlm_distilroberta","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("hupd_mlm_distilroberta","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hupd_mlm_distilroberta|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/cfcooney/hupd_mlm_distilroberta
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-hupd_mlm_distilroberta_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-hupd_mlm_distilroberta_pipeline_en.md
new file mode 100644
index 00000000000000..74610e92296051
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-hupd_mlm_distilroberta_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English hupd_mlm_distilroberta_pipeline pipeline RoBertaEmbeddings from cfcooney
+author: John Snow Labs
+name: hupd_mlm_distilroberta_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hupd_mlm_distilroberta_pipeline` is a English model originally trained by cfcooney.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hupd_mlm_distilroberta_pipeline_en_5.5.1_3.0_1738103011711.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hupd_mlm_distilroberta_pipeline_en_5.5.1_3.0_1738103011711.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("hupd_mlm_distilroberta_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hupd_mlm_distilroberta_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hupd_mlm_distilroberta_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/cfcooney/hupd_mlm_distilroberta
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-idt5_base_qaqg_v1_0_en.md b/docs/_posts/ahmedlone127/2025-01-28-idt5_base_qaqg_v1_0_en.md
new file mode 100644
index 00000000000000..d300df8616c7c7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-idt5_base_qaqg_v1_0_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English idt5_base_qaqg_v1_0 T5Transformer from hawalurahman
+author: John Snow Labs
+name: idt5_base_qaqg_v1_0
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`idt5_base_qaqg_v1_0` is a English model originally trained by hawalurahman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/idt5_base_qaqg_v1_0_en_5.5.1_3.0_1738074480687.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/idt5_base_qaqg_v1_0_en_5.5.1_3.0_1738074480687.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("idt5_base_qaqg_v1_0","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("idt5_base_qaqg_v1_0", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|idt5_base_qaqg_v1_0|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|986.7 MB|
+
+## References
+
+https://huggingface.co/hawalurahman/idt5-base-qaqg_v1-0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-idt5_base_qaqg_v1_0_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-idt5_base_qaqg_v1_0_pipeline_en.md
new file mode 100644
index 00000000000000..0faf160b4f4ec9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-idt5_base_qaqg_v1_0_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English idt5_base_qaqg_v1_0_pipeline pipeline T5Transformer from hawalurahman
+author: John Snow Labs
+name: idt5_base_qaqg_v1_0_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`idt5_base_qaqg_v1_0_pipeline` is a English model originally trained by hawalurahman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/idt5_base_qaqg_v1_0_pipeline_en_5.5.1_3.0_1738074535320.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/idt5_base_qaqg_v1_0_pipeline_en_5.5.1_3.0_1738074535320.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("idt5_base_qaqg_v1_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("idt5_base_qaqg_v1_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|idt5_base_qaqg_v1_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|986.7 MB|
+
+## References
+
+https://huggingface.co/hawalurahman/idt5-base-qaqg_v1-0
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-image_classifier_swin_base_patch4_window7_224_in22k_en.md b/docs/_posts/ahmedlone127/2025-01-28-image_classifier_swin_base_patch4_window7_224_in22k_en.md
new file mode 100644
index 00000000000000..c77b04044acaca
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-image_classifier_swin_base_patch4_window7_224_in22k_en.md
@@ -0,0 +1,96 @@
+---
+layout: model
+title: SwinForImageClassification - image_classifier_swin_base_patch4_window7_224_in22k
+author: John Snow Labs
+name: image_classifier_swin_base_patch4_window7_224_in22k
+date: 2025-01-28
+tags: [open_source, swin, image, en, english, image_classification, imagenet, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Swin model for Image Classification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.
+
+Swin Transformer was introduced in the paper [Swin Transformer: Hierarchical Vision Transformer using Shifted Windows](https://arxiv.org/abs/2103.14030) by Liu et al.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/image_classifier_swin_base_patch4_window7_224_in22k_en_5.5.1_3.0_1738095546583.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/image_classifier_swin_base_patch4_window7_224_in22k_en_5.5.1_3.0_1738095546583.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained("image_classifier_swin_base_patch4_window7_224_in22k", "en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+```
+```scala
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier = SwinForImageClassification
+    .pretrained("image_classifier_swin_base_patch4_window7_224_in22k", "en")
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|image_classifier_swin_base_patch4_window7_224_in22k|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|817.8 MB|
+
+## References
+
+References
+
+[https://huggingface.co/microsoft/swin-base-patch4-window7-224-in22k](https://huggingface.co/microsoft/swin-base-patch4-window7-224-in22k)
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-image_classifier_swin_base_patch4_window7_224_in22k_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-image_classifier_swin_base_patch4_window7_224_in22k_pipeline_en.md
new file mode 100644
index 00000000000000..f80b76046c2bc1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-image_classifier_swin_base_patch4_window7_224_in22k_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English image_classifier_swin_base_patch4_window7_224_in22k_pipeline pipeline SwinForImageClassification from microsoft
+author: John Snow Labs
+name: image_classifier_swin_base_patch4_window7_224_in22k_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`image_classifier_swin_base_patch4_window7_224_in22k_pipeline` is a English model originally trained by microsoft.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/image_classifier_swin_base_patch4_window7_224_in22k_pipeline_en_5.5.1_3.0_1738095589355.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/image_classifier_swin_base_patch4_window7_224_in22k_pipeline_en_5.5.1_3.0_1738095589355.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("image_classifier_swin_base_patch4_window7_224_in22k_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("image_classifier_swin_base_patch4_window7_224_in22k_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|image_classifier_swin_base_patch4_window7_224_in22k_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|817.8 MB|
+
+## References
+
+https://huggingface.co/microsoft/swin-base-patch4-window7-224-in22k
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-incel_bert_base_uncased_1000k_english_en.md b/docs/_posts/ahmedlone127/2025-01-28-incel_bert_base_uncased_1000k_english_en.md
new file mode 100644
index 00000000000000..88c83d37dcf040
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-incel_bert_base_uncased_1000k_english_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English incel_bert_base_uncased_1000k_english BertEmbeddings from pgajo
+author: John Snow Labs
+name: incel_bert_base_uncased_1000k_english
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`incel_bert_base_uncased_1000k_english` is a English model originally trained by pgajo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/incel_bert_base_uncased_1000k_english_en_5.5.1_3.0_1738035145350.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/incel_bert_base_uncased_1000k_english_en_5.5.1_3.0_1738035145350.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("incel_bert_base_uncased_1000k_english","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("incel_bert_base_uncased_1000k_english","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|incel_bert_base_uncased_1000k_english|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/pgajo/incel-bert-base-uncased-1000k_english
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-incel_bert_base_uncased_1000k_english_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-incel_bert_base_uncased_1000k_english_pipeline_en.md
new file mode 100644
index 00000000000000..42023f8ef038bf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-incel_bert_base_uncased_1000k_english_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English incel_bert_base_uncased_1000k_english_pipeline pipeline BertEmbeddings from pgajo
+author: John Snow Labs
+name: incel_bert_base_uncased_1000k_english_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`incel_bert_base_uncased_1000k_english_pipeline` is a English model originally trained by pgajo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/incel_bert_base_uncased_1000k_english_pipeline_en_5.5.1_3.0_1738035165648.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/incel_bert_base_uncased_1000k_english_pipeline_en_5.5.1_3.0_1738035165648.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("incel_bert_base_uncased_1000k_english_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("incel_bert_base_uncased_1000k_english_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|incel_bert_base_uncased_1000k_english_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/pgajo/incel-bert-base-uncased-1000k_english
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-inisw08_robert_mlm_adamw_torch_bs16_en.md b/docs/_posts/ahmedlone127/2025-01-28-inisw08_robert_mlm_adamw_torch_bs16_en.md
new file mode 100644
index 00000000000000..9a40e8b48d943a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-inisw08_robert_mlm_adamw_torch_bs16_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English inisw08_robert_mlm_adamw_torch_bs16 RoBertaEmbeddings from ugiugi
+author: John Snow Labs
+name: inisw08_robert_mlm_adamw_torch_bs16
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`inisw08_robert_mlm_adamw_torch_bs16` is a English model originally trained by ugiugi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/inisw08_robert_mlm_adamw_torch_bs16_en_5.5.1_3.0_1738103120860.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/inisw08_robert_mlm_adamw_torch_bs16_en_5.5.1_3.0_1738103120860.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("inisw08_robert_mlm_adamw_torch_bs16","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("inisw08_robert_mlm_adamw_torch_bs16","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|inisw08_robert_mlm_adamw_torch_bs16|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|466.2 MB|
+
+## References
+
+https://huggingface.co/ugiugi/inisw08-RoBERT-mlm-adamw_torch_bs16
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-inisw08_robert_mlm_adamw_torch_bs16_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-inisw08_robert_mlm_adamw_torch_bs16_pipeline_en.md
new file mode 100644
index 00000000000000..eeced57fc18f7f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-inisw08_robert_mlm_adamw_torch_bs16_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English inisw08_robert_mlm_adamw_torch_bs16_pipeline pipeline RoBertaEmbeddings from ugiugi
+author: John Snow Labs
+name: inisw08_robert_mlm_adamw_torch_bs16_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`inisw08_robert_mlm_adamw_torch_bs16_pipeline` is a English model originally trained by ugiugi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/inisw08_robert_mlm_adamw_torch_bs16_pipeline_en_5.5.1_3.0_1738103144188.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/inisw08_robert_mlm_adamw_torch_bs16_pipeline_en_5.5.1_3.0_1738103144188.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("inisw08_robert_mlm_adamw_torch_bs16_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("inisw08_robert_mlm_adamw_torch_bs16_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|inisw08_robert_mlm_adamw_torch_bs16_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.3 MB|
+
+## References
+
+https://huggingface.co/ugiugi/inisw08-RoBERT-mlm-adamw_torch_bs16
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-iotnation_qa_model_3_0_bert_original_3e_5_512_length_3_epoch_en.md b/docs/_posts/ahmedlone127/2025-01-28-iotnation_qa_model_3_0_bert_original_3e_5_512_length_3_epoch_en.md
new file mode 100644
index 00000000000000..58d38dfbebc403
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-iotnation_qa_model_3_0_bert_original_3e_5_512_length_3_epoch_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English iotnation_qa_model_3_0_bert_original_3e_5_512_length_3_epoch BertForQuestionAnswering from chriskim2273
+author: John Snow Labs
+name: iotnation_qa_model_3_0_bert_original_3e_5_512_length_3_epoch
+date: 2025-01-28
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`iotnation_qa_model_3_0_bert_original_3e_5_512_length_3_epoch` is a English model originally trained by chriskim2273.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/iotnation_qa_model_3_0_bert_original_3e_5_512_length_3_epoch_en_5.5.1_3.0_1738062098219.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/iotnation_qa_model_3_0_bert_original_3e_5_512_length_3_epoch_en_5.5.1_3.0_1738062098219.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("iotnation_qa_model_3_0_bert_original_3e_5_512_length_3_epoch","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("iotnation_qa_model_3_0_bert_original_3e_5_512_length_3_epoch", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|iotnation_qa_model_3_0_bert_original_3e_5_512_length_3_epoch|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/chriskim2273/IOTNation_QA_Model_3.0_BERT_ORIGINAL_3e-5_512_LENGTH_3_EPOCH
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-iotnation_qa_model_3_0_bert_original_3e_5_512_length_3_epoch_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-iotnation_qa_model_3_0_bert_original_3e_5_512_length_3_epoch_pipeline_en.md
new file mode 100644
index 00000000000000..e788d2b74cbed6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-iotnation_qa_model_3_0_bert_original_3e_5_512_length_3_epoch_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English iotnation_qa_model_3_0_bert_original_3e_5_512_length_3_epoch_pipeline pipeline BertForQuestionAnswering from chriskim2273
+author: John Snow Labs
+name: iotnation_qa_model_3_0_bert_original_3e_5_512_length_3_epoch_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`iotnation_qa_model_3_0_bert_original_3e_5_512_length_3_epoch_pipeline` is a English model originally trained by chriskim2273.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/iotnation_qa_model_3_0_bert_original_3e_5_512_length_3_epoch_pipeline_en_5.5.1_3.0_1738062119187.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/iotnation_qa_model_3_0_bert_original_3e_5_512_length_3_epoch_pipeline_en_5.5.1_3.0_1738062119187.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("iotnation_qa_model_3_0_bert_original_3e_5_512_length_3_epoch_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("iotnation_qa_model_3_0_bert_original_3e_5_512_length_3_epoch_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|iotnation_qa_model_3_0_bert_original_3e_5_512_length_3_epoch_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/chriskim2273/IOTNation_QA_Model_3.0_BERT_ORIGINAL_3e-5_512_LENGTH_3_EPOCH
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-issuebert_base_en.md b/docs/_posts/ahmedlone127/2025-01-28-issuebert_base_en.md
new file mode 100644
index 00000000000000..36e3b2ff4c4e5e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-issuebert_base_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English issuebert_base BertEmbeddings from gbkwon
+author: John Snow Labs
+name: issuebert_base
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`issuebert_base` is a English model originally trained by gbkwon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/issuebert_base_en_5.5.1_3.0_1738057742412.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/issuebert_base_en_5.5.1_3.0_1738057742412.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("issuebert_base","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("issuebert_base","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|issuebert_base|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|408.3 MB|
+
+## References
+
+https://huggingface.co/gbkwon/issueBERT-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-issuebert_base_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-issuebert_base_pipeline_en.md
new file mode 100644
index 00000000000000..04e52c1b71b4b8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-issuebert_base_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English issuebert_base_pipeline pipeline BertEmbeddings from gbkwon
+author: John Snow Labs
+name: issuebert_base_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`issuebert_base_pipeline` is a English model originally trained by gbkwon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/issuebert_base_pipeline_en_5.5.1_3.0_1738057762921.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/issuebert_base_pipeline_en_5.5.1_3.0_1738057762921.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("issuebert_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("issuebert_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|issuebert_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|408.3 MB|
+
+## References
+
+https://huggingface.co/gbkwon/issueBERT-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-jaberv2_6l_en.md b/docs/_posts/ahmedlone127/2025-01-28-jaberv2_6l_en.md
new file mode 100644
index 00000000000000..dad1b1f1cac81f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-jaberv2_6l_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English jaberv2_6l BertEmbeddings from huawei-noah
+author: John Snow Labs
+name: jaberv2_6l
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`jaberv2_6l` is a English model originally trained by huawei-noah.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/jaberv2_6l_en_5.5.1_3.0_1738057566454.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/jaberv2_6l_en_5.5.1_3.0_1738057566454.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("jaberv2_6l","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("jaberv2_6l","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|jaberv2_6l|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|344.8 MB|
+
+## References
+
+https://huggingface.co/huawei-noah/JABERv2-6L
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-jaberv2_6l_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-jaberv2_6l_pipeline_en.md
new file mode 100644
index 00000000000000..0b63f7358c9f4d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-jaberv2_6l_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English jaberv2_6l_pipeline pipeline BertEmbeddings from huawei-noah
+author: John Snow Labs
+name: jaberv2_6l_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`jaberv2_6l_pipeline` is a English model originally trained by huawei-noah.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/jaberv2_6l_pipeline_en_5.5.1_3.0_1738057584011.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/jaberv2_6l_pipeline_en_5.5.1_3.0_1738057584011.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("jaberv2_6l_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("jaberv2_6l_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|jaberv2_6l_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|344.8 MB|
+
+## References
+
+https://huggingface.co/huawei-noah/JABERv2-6L
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-jeep_oriya_toyota_en.md b/docs/_posts/ahmedlone127/2025-01-28-jeep_oriya_toyota_en.md
new file mode 100644
index 00000000000000..967505744871b5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-jeep_oriya_toyota_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English jeep_oriya_toyota ViTForImageClassification from tielur
+author: John Snow Labs
+name: jeep_oriya_toyota
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`jeep_oriya_toyota` is a English model originally trained by tielur.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/jeep_oriya_toyota_en_5.5.1_3.0_1738023292114.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/jeep_oriya_toyota_en_5.5.1_3.0_1738023292114.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""jeep_oriya_toyota","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("jeep_oriya_toyota","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|jeep_oriya_toyota|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/tielur/jeep-or-toyota
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-jeep_oriya_toyota_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-jeep_oriya_toyota_pipeline_en.md
new file mode 100644
index 00000000000000..4e4db758118a0e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-jeep_oriya_toyota_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English jeep_oriya_toyota_pipeline pipeline ViTForImageClassification from tielur
+author: John Snow Labs
+name: jeep_oriya_toyota_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`jeep_oriya_toyota_pipeline` is a English model originally trained by tielur.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/jeep_oriya_toyota_pipeline_en_5.5.1_3.0_1738023309085.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/jeep_oriya_toyota_pipeline_en_5.5.1_3.0_1738023309085.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("jeep_oriya_toyota_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("jeep_oriya_toyota_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|jeep_oriya_toyota_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/tielur/jeep-or-toyota
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-kitchen_design_en.md b/docs/_posts/ahmedlone127/2025-01-28-kitchen_design_en.md
new file mode 100644
index 00000000000000..36608b18d1561f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-kitchen_design_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English kitchen_design ViTForImageClassification from alialaydrus
+author: John Snow Labs
+name: kitchen_design
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kitchen_design` is a English model originally trained by alialaydrus.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kitchen_design_en_5.5.1_3.0_1738023314772.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kitchen_design_en_5.5.1_3.0_1738023314772.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""kitchen_design","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("kitchen_design","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|kitchen_design|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/alialaydrus/kitchen_design
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-kitchen_design_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-kitchen_design_pipeline_en.md
new file mode 100644
index 00000000000000..49fe7acf3c919f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-kitchen_design_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English kitchen_design_pipeline pipeline ViTForImageClassification from alialaydrus
+author: John Snow Labs
+name: kitchen_design_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kitchen_design_pipeline` is a English model originally trained by alialaydrus.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kitchen_design_pipeline_en_5.5.1_3.0_1738023331224.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kitchen_design_pipeline_en_5.5.1_3.0_1738023331224.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("kitchen_design_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("kitchen_design_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|kitchen_design_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/alialaydrus/kitchen_design
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-knt5_base_kn.md b/docs/_posts/ahmedlone127/2025-01-28-knt5_base_kn.md
new file mode 100644
index 00000000000000..dc5252583c20a3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-knt5_base_kn.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Kannada knt5_base T5Transformer from shraajan
+author: John Snow Labs
+name: knt5_base
+date: 2025-01-28
+tags: [kn, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: kn
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`knt5_base` is a Kannada model originally trained by shraajan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/knt5_base_kn_5.5.1_3.0_1738094468162.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/knt5_base_kn_5.5.1_3.0_1738094468162.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("knt5_base","kn") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("knt5_base", "kn")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|knt5_base|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|kn|
+|Size:|475.9 MB|
+
+## References
+
+https://huggingface.co/shraajan/knt5-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-knt5_base_pipeline_kn.md b/docs/_posts/ahmedlone127/2025-01-28-knt5_base_pipeline_kn.md
new file mode 100644
index 00000000000000..ee327a8529a789
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-knt5_base_pipeline_kn.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Kannada knt5_base_pipeline pipeline T5Transformer from shraajan
+author: John Snow Labs
+name: knt5_base_pipeline
+date: 2025-01-28
+tags: [kn, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: kn
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`knt5_base_pipeline` is a Kannada model originally trained by shraajan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/knt5_base_pipeline_kn_5.5.1_3.0_1738094619983.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/knt5_base_pipeline_kn_5.5.1_3.0_1738094619983.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("knt5_base_pipeline", lang = "kn")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("knt5_base_pipeline", lang = "kn")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|knt5_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|kn|
+|Size:|475.9 MB|
+
+## References
+
+https://huggingface.co/shraajan/knt5-base
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-kobert_family_en.md b/docs/_posts/ahmedlone127/2025-01-28-kobert_family_en.md
new file mode 100644
index 00000000000000..31fffaaaf5ed58
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-kobert_family_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English kobert_family BertEmbeddings from JuneKo
+author: John Snow Labs
+name: kobert_family
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kobert_family` is a English model originally trained by JuneKo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kobert_family_en_5.5.1_3.0_1738039708846.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kobert_family_en_5.5.1_3.0_1738039708846.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("kobert_family","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("kobert_family","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|kobert_family|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|406.2 MB|
+
+## References
+
+https://huggingface.co/JuneKo/koBERT_family
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-kobert_family_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-kobert_family_pipeline_en.md
new file mode 100644
index 00000000000000..4e3c3155c70447
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-kobert_family_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English kobert_family_pipeline pipeline BertEmbeddings from JuneKo
+author: John Snow Labs
+name: kobert_family_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kobert_family_pipeline` is a English model originally trained by JuneKo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kobert_family_pipeline_en_5.5.1_3.0_1738039729389.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kobert_family_pipeline_en_5.5.1_3.0_1738039729389.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("kobert_family_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("kobert_family_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|kobert_family_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.2 MB|
+
+## References
+
+https://huggingface.co/JuneKo/koBERT_family
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-learn_hf_food_not_food_text_classifier_distilbert_base_uncased_ainasiddiqui_en.md b/docs/_posts/ahmedlone127/2025-01-28-learn_hf_food_not_food_text_classifier_distilbert_base_uncased_ainasiddiqui_en.md
new file mode 100644
index 00000000000000..79ec1c710196a9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-learn_hf_food_not_food_text_classifier_distilbert_base_uncased_ainasiddiqui_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English learn_hf_food_not_food_text_classifier_distilbert_base_uncased_ainasiddiqui DistilBertForSequenceClassification from AinaSiddiqui
+author: John Snow Labs
+name: learn_hf_food_not_food_text_classifier_distilbert_base_uncased_ainasiddiqui
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`learn_hf_food_not_food_text_classifier_distilbert_base_uncased_ainasiddiqui` is a English model originally trained by AinaSiddiqui.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/learn_hf_food_not_food_text_classifier_distilbert_base_uncased_ainasiddiqui_en_5.5.1_3.0_1738025605026.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/learn_hf_food_not_food_text_classifier_distilbert_base_uncased_ainasiddiqui_en_5.5.1_3.0_1738025605026.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("learn_hf_food_not_food_text_classifier_distilbert_base_uncased_ainasiddiqui","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("learn_hf_food_not_food_text_classifier_distilbert_base_uncased_ainasiddiqui", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|learn_hf_food_not_food_text_classifier_distilbert_base_uncased_ainasiddiqui|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/AinaSiddiqui/learn_hf_food_not_food_text_classifier-distilbert-base-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-learn_hf_food_not_food_text_classifier_distilbert_base_uncased_ainasiddiqui_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-learn_hf_food_not_food_text_classifier_distilbert_base_uncased_ainasiddiqui_pipeline_en.md
new file mode 100644
index 00000000000000..bff6c2e38e2653
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-learn_hf_food_not_food_text_classifier_distilbert_base_uncased_ainasiddiqui_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English learn_hf_food_not_food_text_classifier_distilbert_base_uncased_ainasiddiqui_pipeline pipeline DistilBertForSequenceClassification from AinaSiddiqui
+author: John Snow Labs
+name: learn_hf_food_not_food_text_classifier_distilbert_base_uncased_ainasiddiqui_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`learn_hf_food_not_food_text_classifier_distilbert_base_uncased_ainasiddiqui_pipeline` is a English model originally trained by AinaSiddiqui.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/learn_hf_food_not_food_text_classifier_distilbert_base_uncased_ainasiddiqui_pipeline_en_5.5.1_3.0_1738025617777.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/learn_hf_food_not_food_text_classifier_distilbert_base_uncased_ainasiddiqui_pipeline_en_5.5.1_3.0_1738025617777.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("learn_hf_food_not_food_text_classifier_distilbert_base_uncased_ainasiddiqui_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("learn_hf_food_not_food_text_classifier_distilbert_base_uncased_ainasiddiqui_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|learn_hf_food_not_food_text_classifier_distilbert_base_uncased_ainasiddiqui_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/AinaSiddiqui/learn_hf_food_not_food_text_classifier-distilbert-base-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-living_spaces_classification_scraper_balanced_clean_en.md b/docs/_posts/ahmedlone127/2025-01-28-living_spaces_classification_scraper_balanced_clean_en.md
new file mode 100644
index 00000000000000..a3d0674444cf53
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-living_spaces_classification_scraper_balanced_clean_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English living_spaces_classification_scraper_balanced_clean ViTForImageClassification from chris32
+author: John Snow Labs
+name: living_spaces_classification_scraper_balanced_clean
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`living_spaces_classification_scraper_balanced_clean` is a English model originally trained by chris32.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/living_spaces_classification_scraper_balanced_clean_en_5.5.1_3.0_1738022590204.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/living_spaces_classification_scraper_balanced_clean_en_5.5.1_3.0_1738022590204.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""living_spaces_classification_scraper_balanced_clean","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("living_spaces_classification_scraper_balanced_clean","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|living_spaces_classification_scraper_balanced_clean|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/chris32/living-spaces-classification_scraper_balanced_clean
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-living_spaces_classification_scraper_balanced_clean_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-living_spaces_classification_scraper_balanced_clean_pipeline_en.md
new file mode 100644
index 00000000000000..8f6d909d0df772
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-living_spaces_classification_scraper_balanced_clean_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English living_spaces_classification_scraper_balanced_clean_pipeline pipeline ViTForImageClassification from chris32
+author: John Snow Labs
+name: living_spaces_classification_scraper_balanced_clean_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`living_spaces_classification_scraper_balanced_clean_pipeline` is a English model originally trained by chris32.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/living_spaces_classification_scraper_balanced_clean_pipeline_en_5.5.1_3.0_1738022610644.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/living_spaces_classification_scraper_balanced_clean_pipeline_en_5.5.1_3.0_1738022610644.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("living_spaces_classification_scraper_balanced_clean_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("living_spaces_classification_scraper_balanced_clean_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|living_spaces_classification_scraper_balanced_clean_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/chris32/living-spaces-classification_scraper_balanced_clean
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-lora_flan_t5_large_chat_ajithnarayanan_en.md b/docs/_posts/ahmedlone127/2025-01-28-lora_flan_t5_large_chat_ajithnarayanan_en.md
new file mode 100644
index 00000000000000..d978841d302c87
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-lora_flan_t5_large_chat_ajithnarayanan_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English lora_flan_t5_large_chat_ajithnarayanan T5Transformer from ajithnarayanan
+author: John Snow Labs
+name: lora_flan_t5_large_chat_ajithnarayanan
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lora_flan_t5_large_chat_ajithnarayanan` is a English model originally trained by ajithnarayanan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lora_flan_t5_large_chat_ajithnarayanan_en_5.5.1_3.0_1738033705013.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lora_flan_t5_large_chat_ajithnarayanan_en_5.5.1_3.0_1738033705013.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("lora_flan_t5_large_chat_ajithnarayanan","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("lora_flan_t5_large_chat_ajithnarayanan", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lora_flan_t5_large_chat_ajithnarayanan|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|3.1 GB|
+
+## References
+
+https://huggingface.co/ajithnarayanan/lora-flan-t5-large-chat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-lora_flan_t5_large_chat_ajithnarayanan_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-lora_flan_t5_large_chat_ajithnarayanan_pipeline_en.md
new file mode 100644
index 00000000000000..cad594d9db8aba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-lora_flan_t5_large_chat_ajithnarayanan_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English lora_flan_t5_large_chat_ajithnarayanan_pipeline pipeline T5Transformer from ajithnarayanan
+author: John Snow Labs
+name: lora_flan_t5_large_chat_ajithnarayanan_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lora_flan_t5_large_chat_ajithnarayanan_pipeline` is a English model originally trained by ajithnarayanan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lora_flan_t5_large_chat_ajithnarayanan_pipeline_en_5.5.1_3.0_1738033843426.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lora_flan_t5_large_chat_ajithnarayanan_pipeline_en_5.5.1_3.0_1738033843426.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("lora_flan_t5_large_chat_ajithnarayanan_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("lora_flan_t5_large_chat_ajithnarayanan_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lora_flan_t5_large_chat_ajithnarayanan_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|3.1 GB|
+
+## References
+
+https://huggingface.co/ajithnarayanan/lora-flan-t5-large-chat
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-lora_flan_t5_medical_chatbot_en.md b/docs/_posts/ahmedlone127/2025-01-28-lora_flan_t5_medical_chatbot_en.md
new file mode 100644
index 00000000000000..86053de8672e0a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-lora_flan_t5_medical_chatbot_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English lora_flan_t5_medical_chatbot T5Transformer from Amjad123
+author: John Snow Labs
+name: lora_flan_t5_medical_chatbot
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lora_flan_t5_medical_chatbot` is a English model originally trained by Amjad123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lora_flan_t5_medical_chatbot_en_5.5.1_3.0_1738032451110.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lora_flan_t5_medical_chatbot_en_5.5.1_3.0_1738032451110.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("lora_flan_t5_medical_chatbot","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("lora_flan_t5_medical_chatbot", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lora_flan_t5_medical_chatbot|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|3.1 GB|
+
+## References
+
+https://huggingface.co/Amjad123/lora-flan-t5-medical-chatbot
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-lora_flan_t5_medical_chatbot_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-lora_flan_t5_medical_chatbot_pipeline_en.md
new file mode 100644
index 00000000000000..0eb705478e17ee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-lora_flan_t5_medical_chatbot_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English lora_flan_t5_medical_chatbot_pipeline pipeline T5Transformer from Amjad123
+author: John Snow Labs
+name: lora_flan_t5_medical_chatbot_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lora_flan_t5_medical_chatbot_pipeline` is a English model originally trained by Amjad123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lora_flan_t5_medical_chatbot_pipeline_en_5.5.1_3.0_1738032593136.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lora_flan_t5_medical_chatbot_pipeline_en_5.5.1_3.0_1738032593136.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("lora_flan_t5_medical_chatbot_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("lora_flan_t5_medical_chatbot_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lora_flan_t5_medical_chatbot_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|3.1 GB|
+
+## References
+
+https://huggingface.co/Amjad123/lora-flan-t5-medical-chatbot
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-macdonaldsnegative_reason_model_en.md b/docs/_posts/ahmedlone127/2025-01-28-macdonaldsnegative_reason_model_en.md
new file mode 100644
index 00000000000000..fe21b89a28bf24
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-macdonaldsnegative_reason_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English macdonaldsnegative_reason_model DistilBertForSequenceClassification from Liuxuanxi
+author: John Snow Labs
+name: macdonaldsnegative_reason_model
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`macdonaldsnegative_reason_model` is a English model originally trained by Liuxuanxi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/macdonaldsnegative_reason_model_en_5.5.1_3.0_1738077463264.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/macdonaldsnegative_reason_model_en_5.5.1_3.0_1738077463264.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("macdonaldsnegative_reason_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("macdonaldsnegative_reason_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|macdonaldsnegative_reason_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Liuxuanxi/macdonaldsnegative_Reason_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-macdonaldsnegative_reason_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-macdonaldsnegative_reason_model_pipeline_en.md
new file mode 100644
index 00000000000000..a4e0d211bcde2a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-macdonaldsnegative_reason_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English macdonaldsnegative_reason_model_pipeline pipeline DistilBertForSequenceClassification from Liuxuanxi
+author: John Snow Labs
+name: macdonaldsnegative_reason_model_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`macdonaldsnegative_reason_model_pipeline` is a English model originally trained by Liuxuanxi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/macdonaldsnegative_reason_model_pipeline_en_5.5.1_3.0_1738077476774.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/macdonaldsnegative_reason_model_pipeline_en_5.5.1_3.0_1738077476774.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("macdonaldsnegative_reason_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("macdonaldsnegative_reason_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|macdonaldsnegative_reason_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Liuxuanxi/macdonaldsnegative_Reason_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-main_file_en.md b/docs/_posts/ahmedlone127/2025-01-28-main_file_en.md
new file mode 100644
index 00000000000000..5aae143d29d959
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-main_file_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English main_file DistilBertForSequenceClassification from smasher2801
+author: John Snow Labs
+name: main_file
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`main_file` is a English model originally trained by smasher2801.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/main_file_en_5.5.1_3.0_1738077257441.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/main_file_en_5.5.1_3.0_1738077257441.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("main_file","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("main_file", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|main_file|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|246.2 MB|
+
+## References
+
+https://huggingface.co/smasher2801/main_file
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-main_file_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-main_file_pipeline_en.md
new file mode 100644
index 00000000000000..e6987494387a4d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-main_file_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English main_file_pipeline pipeline DistilBertForSequenceClassification from smasher2801
+author: John Snow Labs
+name: main_file_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`main_file_pipeline` is a English model originally trained by smasher2801.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/main_file_pipeline_en_5.5.1_3.0_1738077272711.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/main_file_pipeline_en_5.5.1_3.0_1738077272711.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("main_file_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("main_file_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|main_file_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|246.2 MB|
+
+## References
+
+https://huggingface.co/smasher2801/main_file
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-markuus_bert_base_multilingual_squad_cqa_l_l_pipeline_xx.md b/docs/_posts/ahmedlone127/2025-01-28-markuus_bert_base_multilingual_squad_cqa_l_l_pipeline_xx.md
new file mode 100644
index 00000000000000..111ae169d956e2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-markuus_bert_base_multilingual_squad_cqa_l_l_pipeline_xx.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Multilingual markuus_bert_base_multilingual_squad_cqa_l_l_pipeline pipeline BertForQuestionAnswering from imrazaa
+author: John Snow Labs
+name: markuus_bert_base_multilingual_squad_cqa_l_l_pipeline
+date: 2025-01-28
+tags: [xx, open_source, pipeline, onnx]
+task: Question Answering
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`markuus_bert_base_multilingual_squad_cqa_l_l_pipeline` is a Multilingual model originally trained by imrazaa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/markuus_bert_base_multilingual_squad_cqa_l_l_pipeline_xx_5.5.1_3.0_1738061828798.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/markuus_bert_base_multilingual_squad_cqa_l_l_pipeline_xx_5.5.1_3.0_1738061828798.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("markuus_bert_base_multilingual_squad_cqa_l_l_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("markuus_bert_base_multilingual_squad_cqa_l_l_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|markuus_bert_base_multilingual_squad_cqa_l_l_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|625.5 MB|
+
+## References
+
+https://huggingface.co/imrazaa/markuus-bert-base-multilingual-squad_cqa_L-L
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-markuus_bert_base_multilingual_squad_cqa_l_l_xx.md b/docs/_posts/ahmedlone127/2025-01-28-markuus_bert_base_multilingual_squad_cqa_l_l_xx.md
new file mode 100644
index 00000000000000..fa02b1a8187dac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-markuus_bert_base_multilingual_squad_cqa_l_l_xx.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Multilingual markuus_bert_base_multilingual_squad_cqa_l_l BertForQuestionAnswering from imrazaa
+author: John Snow Labs
+name: markuus_bert_base_multilingual_squad_cqa_l_l
+date: 2025-01-28
+tags: [xx, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`markuus_bert_base_multilingual_squad_cqa_l_l` is a Multilingual model originally trained by imrazaa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/markuus_bert_base_multilingual_squad_cqa_l_l_xx_5.5.1_3.0_1738061798237.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/markuus_bert_base_multilingual_squad_cqa_l_l_xx_5.5.1_3.0_1738061798237.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("markuus_bert_base_multilingual_squad_cqa_l_l","xx") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("markuus_bert_base_multilingual_squad_cqa_l_l", "xx")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|markuus_bert_base_multilingual_squad_cqa_l_l|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|xx|
+|Size:|625.5 MB|
+
+## References
+
+https://huggingface.co/imrazaa/markuus-bert-base-multilingual-squad_cqa_L-L
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-mbert_ottoman_raw_en.md b/docs/_posts/ahmedlone127/2025-01-28-mbert_ottoman_raw_en.md
new file mode 100644
index 00000000000000..a3653e858d28d5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-mbert_ottoman_raw_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mbert_ottoman_raw BertEmbeddings from onurkeles
+author: John Snow Labs
+name: mbert_ottoman_raw
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mbert_ottoman_raw` is a English model originally trained by onurkeles.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mbert_ottoman_raw_en_5.5.1_3.0_1738084449268.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mbert_ottoman_raw_en_5.5.1_3.0_1738084449268.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("mbert_ottoman_raw","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("mbert_ottoman_raw","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mbert_ottoman_raw|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|663.7 MB|
+
+## References
+
+https://huggingface.co/onurkeles/mbert-ottoman-raw
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-mbert_ottoman_raw_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-mbert_ottoman_raw_pipeline_en.md
new file mode 100644
index 00000000000000..0605e77a09c5f5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-mbert_ottoman_raw_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mbert_ottoman_raw_pipeline pipeline BertEmbeddings from onurkeles
+author: John Snow Labs
+name: mbert_ottoman_raw_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mbert_ottoman_raw_pipeline` is a English model originally trained by onurkeles.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mbert_ottoman_raw_pipeline_en_5.5.1_3.0_1738084482416.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mbert_ottoman_raw_pipeline_en_5.5.1_3.0_1738084482416.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mbert_ottoman_raw_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mbert_ottoman_raw_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mbert_ottoman_raw_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|663.7 MB|
+
+## References
+
+https://huggingface.co/onurkeles/mbert-ottoman-raw
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-meat_calssify_fresh_crop_fixed_epoch100_v_0_8_best_en.md b/docs/_posts/ahmedlone127/2025-01-28-meat_calssify_fresh_crop_fixed_epoch100_v_0_8_best_en.md
new file mode 100644
index 00000000000000..9535c4236aaa55
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-meat_calssify_fresh_crop_fixed_epoch100_v_0_8_best_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English meat_calssify_fresh_crop_fixed_epoch100_v_0_8_best ViTForImageClassification from talli96123
+author: John Snow Labs
+name: meat_calssify_fresh_crop_fixed_epoch100_v_0_8_best
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`meat_calssify_fresh_crop_fixed_epoch100_v_0_8_best` is a English model originally trained by talli96123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/meat_calssify_fresh_crop_fixed_epoch100_v_0_8_best_en_5.5.1_3.0_1738022437131.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/meat_calssify_fresh_crop_fixed_epoch100_v_0_8_best_en_5.5.1_3.0_1738022437131.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""meat_calssify_fresh_crop_fixed_epoch100_v_0_8_best","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("meat_calssify_fresh_crop_fixed_epoch100_v_0_8_best","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|meat_calssify_fresh_crop_fixed_epoch100_v_0_8_best|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/talli96123/meat_calssify_fresh_crop_fixed_epoch100_V_0_8_best
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-meat_calssify_fresh_crop_fixed_epoch100_v_0_8_best_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-meat_calssify_fresh_crop_fixed_epoch100_v_0_8_best_pipeline_en.md
new file mode 100644
index 00000000000000..52be5f29676545
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-meat_calssify_fresh_crop_fixed_epoch100_v_0_8_best_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English meat_calssify_fresh_crop_fixed_epoch100_v_0_8_best_pipeline pipeline ViTForImageClassification from talli96123
+author: John Snow Labs
+name: meat_calssify_fresh_crop_fixed_epoch100_v_0_8_best_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`meat_calssify_fresh_crop_fixed_epoch100_v_0_8_best_pipeline` is a English model originally trained by talli96123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/meat_calssify_fresh_crop_fixed_epoch100_v_0_8_best_pipeline_en_5.5.1_3.0_1738022453502.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/meat_calssify_fresh_crop_fixed_epoch100_v_0_8_best_pipeline_en_5.5.1_3.0_1738022453502.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("meat_calssify_fresh_crop_fixed_epoch100_v_0_8_best_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("meat_calssify_fresh_crop_fixed_epoch100_v_0_8_best_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|meat_calssify_fresh_crop_fixed_epoch100_v_0_8_best_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/talli96123/meat_calssify_fresh_crop_fixed_epoch100_V_0_8_best
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-med_complication_classifaction_en.md b/docs/_posts/ahmedlone127/2025-01-28-med_complication_classifaction_en.md
new file mode 100644
index 00000000000000..57e4848d8ec989
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-med_complication_classifaction_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English med_complication_classifaction ViTForImageClassification from Cem13
+author: John Snow Labs
+name: med_complication_classifaction
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`med_complication_classifaction` is a English model originally trained by Cem13.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/med_complication_classifaction_en_5.5.1_3.0_1738023722494.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/med_complication_classifaction_en_5.5.1_3.0_1738023722494.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""med_complication_classifaction","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("med_complication_classifaction","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|med_complication_classifaction|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/Cem13/med_complication_classifaction
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-med_complication_classifaction_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-med_complication_classifaction_pipeline_en.md
new file mode 100644
index 00000000000000..d442aa5dc3f7d9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-med_complication_classifaction_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English med_complication_classifaction_pipeline pipeline ViTForImageClassification from Cem13
+author: John Snow Labs
+name: med_complication_classifaction_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`med_complication_classifaction_pipeline` is a English model originally trained by Cem13.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/med_complication_classifaction_pipeline_en_5.5.1_3.0_1738023778026.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/med_complication_classifaction_pipeline_en_5.5.1_3.0_1738023778026.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("med_complication_classifaction_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("med_complication_classifaction_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|med_complication_classifaction_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/Cem13/med_complication_classifaction
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-med_model_en.md b/docs/_posts/ahmedlone127/2025-01-28-med_model_en.md
new file mode 100644
index 00000000000000..232363a1bc746a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-med_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English med_model BertEmbeddings from kumarme072
+author: John Snow Labs
+name: med_model
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`med_model` is a English model originally trained by kumarme072.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/med_model_en_5.5.1_3.0_1738085476129.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/med_model_en_5.5.1_3.0_1738085476129.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("med_model","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("med_model","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|med_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|486.3 MB|
+
+## References
+
+https://huggingface.co/kumarme072/med_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-med_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-med_model_pipeline_en.md
new file mode 100644
index 00000000000000..f5641c5effd826
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-med_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English med_model_pipeline pipeline BertEmbeddings from kumarme072
+author: John Snow Labs
+name: med_model_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`med_model_pipeline` is a English model originally trained by kumarme072.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/med_model_pipeline_en_5.5.1_3.0_1738085502606.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/med_model_pipeline_en_5.5.1_3.0_1738085502606.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("med_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("med_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|med_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|486.3 MB|
+
+## References
+
+https://huggingface.co/kumarme072/med_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-mental_health_response_model_en.md b/docs/_posts/ahmedlone127/2025-01-28-mental_health_response_model_en.md
new file mode 100644
index 00000000000000..224f4251a646c2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-mental_health_response_model_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mental_health_response_model T5Transformer from ctopuz3
+author: John Snow Labs
+name: mental_health_response_model
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mental_health_response_model` is a English model originally trained by ctopuz3.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mental_health_response_model_en_5.5.1_3.0_1738092848091.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mental_health_response_model_en_5.5.1_3.0_1738092848091.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("mental_health_response_model","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("mental_health_response_model", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mental_health_response_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|270.3 MB|
+
+## References
+
+https://huggingface.co/ctopuz3/mental-health-response-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-mental_health_response_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-mental_health_response_model_pipeline_en.md
new file mode 100644
index 00000000000000..9f243f10ed4827
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-mental_health_response_model_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mental_health_response_model_pipeline pipeline T5Transformer from ctopuz3
+author: John Snow Labs
+name: mental_health_response_model_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mental_health_response_model_pipeline` is a English model originally trained by ctopuz3.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mental_health_response_model_pipeline_en_5.5.1_3.0_1738092866328.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mental_health_response_model_pipeline_en_5.5.1_3.0_1738092866328.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mental_health_response_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mental_health_response_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mental_health_response_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|270.3 MB|
+
+## References
+
+https://huggingface.co/ctopuz3/mental-health-response-model
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-mentalhealthchatbot_en.md b/docs/_posts/ahmedlone127/2025-01-28-mentalhealthchatbot_en.md
new file mode 100644
index 00000000000000..dd84b537accaa7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-mentalhealthchatbot_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mentalhealthchatbot T5Transformer from wesberg05
+author: John Snow Labs
+name: mentalhealthchatbot
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mentalhealthchatbot` is a English model originally trained by wesberg05.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mentalhealthchatbot_en_5.5.1_3.0_1738093988867.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mentalhealthchatbot_en_5.5.1_3.0_1738093988867.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("mentalhealthchatbot","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("mentalhealthchatbot", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mentalhealthchatbot|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|349.8 MB|
+
+## References
+
+https://huggingface.co/wesberg05/MentalHealthChatbot
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-mentalhealthchatbot_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-mentalhealthchatbot_pipeline_en.md
new file mode 100644
index 00000000000000..4e7ed7b7cf8b75
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-mentalhealthchatbot_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mentalhealthchatbot_pipeline pipeline T5Transformer from wesberg05
+author: John Snow Labs
+name: mentalhealthchatbot_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mentalhealthchatbot_pipeline` is a English model originally trained by wesberg05.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mentalhealthchatbot_pipeline_en_5.5.1_3.0_1738094006505.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mentalhealthchatbot_pipeline_en_5.5.1_3.0_1738094006505.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mentalhealthchatbot_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mentalhealthchatbot_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mentalhealthchatbot_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|349.8 MB|
+
+## References
+
+https://huggingface.co/wesberg05/MentalHealthChatbot
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-mergedistill_maltese_arabic_128_v2_en.md b/docs/_posts/ahmedlone127/2025-01-28-mergedistill_maltese_arabic_128_v2_en.md
new file mode 100644
index 00000000000000..44a736f0644a21
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-mergedistill_maltese_arabic_128_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mergedistill_maltese_arabic_128_v2 BertEmbeddings from amitness
+author: John Snow Labs
+name: mergedistill_maltese_arabic_128_v2
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mergedistill_maltese_arabic_128_v2` is a English model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_arabic_128_v2_en_5.5.1_3.0_1738034852619.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_arabic_128_v2_en_5.5.1_3.0_1738034852619.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("mergedistill_maltese_arabic_128_v2","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("mergedistill_maltese_arabic_128_v2","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mergedistill_maltese_arabic_128_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|646.9 MB|
+
+## References
+
+https://huggingface.co/amitness/mergedistill-mt-ar-128-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-mergedistill_maltese_arabic_128_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-mergedistill_maltese_arabic_128_v2_pipeline_en.md
new file mode 100644
index 00000000000000..abfbf43020763e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-mergedistill_maltese_arabic_128_v2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mergedistill_maltese_arabic_128_v2_pipeline pipeline BertEmbeddings from amitness
+author: John Snow Labs
+name: mergedistill_maltese_arabic_128_v2_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mergedistill_maltese_arabic_128_v2_pipeline` is a English model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_arabic_128_v2_pipeline_en_5.5.1_3.0_1738034884778.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_arabic_128_v2_pipeline_en_5.5.1_3.0_1738034884778.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mergedistill_maltese_arabic_128_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mergedistill_maltese_arabic_128_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mergedistill_maltese_arabic_128_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|647.0 MB|
+
+## References
+
+https://huggingface.co/amitness/mergedistill-mt-ar-128-v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-mergedistill_maltese_arabic_512_en.md b/docs/_posts/ahmedlone127/2025-01-28-mergedistill_maltese_arabic_512_en.md
new file mode 100644
index 00000000000000..dd5a52f8e8c440
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-mergedistill_maltese_arabic_512_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mergedistill_maltese_arabic_512 BertEmbeddings from amitness
+author: John Snow Labs
+name: mergedistill_maltese_arabic_512
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mergedistill_maltese_arabic_512` is a English model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_arabic_512_en_5.5.1_3.0_1738057884824.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_arabic_512_en_5.5.1_3.0_1738057884824.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("mergedistill_maltese_arabic_512","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("mergedistill_maltese_arabic_512","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mergedistill_maltese_arabic_512|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|647.0 MB|
+
+## References
+
+https://huggingface.co/amitness/mergedistill-mt-ar-512
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-mergedistill_maltese_arabic_512_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-mergedistill_maltese_arabic_512_pipeline_en.md
new file mode 100644
index 00000000000000..b5c8bf6bf0662c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-mergedistill_maltese_arabic_512_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mergedistill_maltese_arabic_512_pipeline pipeline BertEmbeddings from amitness
+author: John Snow Labs
+name: mergedistill_maltese_arabic_512_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mergedistill_maltese_arabic_512_pipeline` is a English model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_arabic_512_pipeline_en_5.5.1_3.0_1738057916675.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_arabic_512_pipeline_en_5.5.1_3.0_1738057916675.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mergedistill_maltese_arabic_512_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mergedistill_maltese_arabic_512_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mergedistill_maltese_arabic_512_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|647.0 MB|
+
+## References
+
+https://huggingface.co/amitness/mergedistill-mt-ar-512
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-mergedistill_maltese_english_128_v2_en.md b/docs/_posts/ahmedlone127/2025-01-28-mergedistill_maltese_english_128_v2_en.md
new file mode 100644
index 00000000000000..ba5244af314e44
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-mergedistill_maltese_english_128_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mergedistill_maltese_english_128_v2 BertEmbeddings from amitness
+author: John Snow Labs
+name: mergedistill_maltese_english_128_v2
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mergedistill_maltese_english_128_v2` is a English model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_english_128_v2_en_5.5.1_3.0_1738035222949.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_english_128_v2_en_5.5.1_3.0_1738035222949.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("mergedistill_maltese_english_128_v2","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("mergedistill_maltese_english_128_v2","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mergedistill_maltese_english_128_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|532.6 MB|
+
+## References
+
+https://huggingface.co/amitness/mergedistill-mt-en-128-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-mergedistill_maltese_english_128_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-mergedistill_maltese_english_128_v2_pipeline_en.md
new file mode 100644
index 00000000000000..f117cc547efa59
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-mergedistill_maltese_english_128_v2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mergedistill_maltese_english_128_v2_pipeline pipeline BertEmbeddings from amitness
+author: John Snow Labs
+name: mergedistill_maltese_english_128_v2_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mergedistill_maltese_english_128_v2_pipeline` is a English model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_english_128_v2_pipeline_en_5.5.1_3.0_1738035249348.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mergedistill_maltese_english_128_v2_pipeline_en_5.5.1_3.0_1738035249348.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mergedistill_maltese_english_128_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mergedistill_maltese_english_128_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mergedistill_maltese_english_128_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|532.6 MB|
+
+## References
+
+https://huggingface.co/amitness/mergedistill-mt-en-128-v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-mitre_v15_tactic_bert_case_based_en.md b/docs/_posts/ahmedlone127/2025-01-28-mitre_v15_tactic_bert_case_based_en.md
new file mode 100644
index 00000000000000..47174ecd3196c7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-mitre_v15_tactic_bert_case_based_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mitre_v15_tactic_bert_case_based BertForSequenceClassification from sarahwei
+author: John Snow Labs
+name: mitre_v15_tactic_bert_case_based
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mitre_v15_tactic_bert_case_based` is a English model originally trained by sarahwei.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mitre_v15_tactic_bert_case_based_en_5.5.1_3.0_1738027886708.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mitre_v15_tactic_bert_case_based_en_5.5.1_3.0_1738027886708.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("mitre_v15_tactic_bert_case_based","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("mitre_v15_tactic_bert_case_based", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mitre_v15_tactic_bert_case_based|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|408.2 MB|
+
+## References
+
+https://huggingface.co/sarahwei/MITRE-v15-tactic-bert-case-based
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-mitre_v15_tactic_bert_case_based_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-mitre_v15_tactic_bert_case_based_pipeline_en.md
new file mode 100644
index 00000000000000..e50ca6c4825a07
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-mitre_v15_tactic_bert_case_based_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mitre_v15_tactic_bert_case_based_pipeline pipeline BertForSequenceClassification from sarahwei
+author: John Snow Labs
+name: mitre_v15_tactic_bert_case_based_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mitre_v15_tactic_bert_case_based_pipeline` is a English model originally trained by sarahwei.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mitre_v15_tactic_bert_case_based_pipeline_en_5.5.1_3.0_1738027906229.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mitre_v15_tactic_bert_case_based_pipeline_en_5.5.1_3.0_1738027906229.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mitre_v15_tactic_bert_case_based_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mitre_v15_tactic_bert_case_based_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mitre_v15_tactic_bert_case_based_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|408.2 MB|
+
+## References
+
+https://huggingface.co/sarahwei/MITRE-v15-tactic-bert-case-based
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-mlm_bert_persian_en.md b/docs/_posts/ahmedlone127/2025-01-28-mlm_bert_persian_en.md
new file mode 100644
index 00000000000000..2c4f797f3a5590
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-mlm_bert_persian_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mlm_bert_persian BertEmbeddings from zeifar
+author: John Snow Labs
+name: mlm_bert_persian
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mlm_bert_persian` is a English model originally trained by zeifar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mlm_bert_persian_en_5.5.1_3.0_1738085057430.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mlm_bert_persian_en_5.5.1_3.0_1738085057430.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("mlm_bert_persian","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("mlm_bert_persian","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mlm_bert_persian|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|625.5 MB|
+
+## References
+
+https://huggingface.co/zeifar/mlm-bert-persian
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-mlm_bert_persian_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-mlm_bert_persian_pipeline_en.md
new file mode 100644
index 00000000000000..6a0b52d98db038
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-mlm_bert_persian_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mlm_bert_persian_pipeline pipeline BertEmbeddings from zeifar
+author: John Snow Labs
+name: mlm_bert_persian_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mlm_bert_persian_pipeline` is a English model originally trained by zeifar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mlm_bert_persian_pipeline_en_5.5.1_3.0_1738085089073.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mlm_bert_persian_pipeline_en_5.5.1_3.0_1738085089073.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mlm_bert_persian_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mlm_bert_persian_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mlm_bert_persian_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|625.5 MB|
+
+## References
+
+https://huggingface.co/zeifar/mlm-bert-persian
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-mlm_personality_en.md b/docs/_posts/ahmedlone127/2025-01-28-mlm_personality_en.md
new file mode 100644
index 00000000000000..30631d399383b3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-mlm_personality_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mlm_personality BertEmbeddings from mjavadmt
+author: John Snow Labs
+name: mlm_personality
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mlm_personality` is a English model originally trained by mjavadmt.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mlm_personality_en_5.5.1_3.0_1738098736914.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mlm_personality_en_5.5.1_3.0_1738098736914.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("mlm_personality","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("mlm_personality","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mlm_personality|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.3 MB|
+
+## References
+
+https://huggingface.co/mjavadmt/MLM_Personality
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-mlm_personality_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-mlm_personality_pipeline_en.md
new file mode 100644
index 00000000000000..a4180dfbfd12ab
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-mlm_personality_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mlm_personality_pipeline pipeline BertEmbeddings from mjavadmt
+author: John Snow Labs
+name: mlm_personality_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mlm_personality_pipeline` is a English model originally trained by mjavadmt.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mlm_personality_pipeline_en_5.5.1_3.0_1738098757971.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mlm_personality_pipeline_en_5.5.1_3.0_1738098757971.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mlm_personality_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mlm_personality_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mlm_personality_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.3 MB|
+
+## References
+
+https://huggingface.co/mjavadmt/MLM_Personality
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-model_bert_check_1_en.md b/docs/_posts/ahmedlone127/2025-01-28-model_bert_check_1_en.md
new file mode 100644
index 00000000000000..0fa975ea0cb913
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-model_bert_check_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English model_bert_check_1 AlbertForSequenceClassification from KalaiselvanD
+author: John Snow Labs
+name: model_bert_check_1
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, albert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_bert_check_1` is a English model originally trained by KalaiselvanD.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_bert_check_1_en_5.5.1_3.0_1738066418005.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_bert_check_1_en_5.5.1_3.0_1738066418005.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = AlbertForSequenceClassification.pretrained("model_bert_check_1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = AlbertForSequenceClassification.pretrained("model_bert_check_1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|model_bert_check_1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/KalaiselvanD/model_bert_check_1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-model_bert_check_1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-model_bert_check_1_pipeline_en.md
new file mode 100644
index 00000000000000..de48f41de4c91e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-model_bert_check_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English model_bert_check_1_pipeline pipeline AlbertForSequenceClassification from KalaiselvanD
+author: John Snow Labs
+name: model_bert_check_1_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_bert_check_1_pipeline` is a English model originally trained by KalaiselvanD.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_bert_check_1_pipeline_en_5.5.1_3.0_1738066420300.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_bert_check_1_pipeline_en_5.5.1_3.0_1738066420300.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("model_bert_check_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("model_bert_check_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|model_bert_check_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/KalaiselvanD/model_bert_check_1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-model_en.md b/docs/_posts/ahmedlone127/2025-01-28-model_en.md
new file mode 100644
index 00000000000000..f3c7830e7a6ea7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-model_en.md
@@ -0,0 +1,96 @@
+---
+layout: model
+title: English model DistilBertEmbeddings from Dinithi
+author: John Snow Labs
+name: model
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model` is a English model originally trained by Dinithi.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_en_5.5.1_3.0_1738068306805.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_en_5.5.1_3.0_1738068306805.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("model","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("model","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|292.7 MB|
+
+## References
+
+References
+
+https://huggingface.co/Dinithi/Model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-model_leofn3_en.md b/docs/_posts/ahmedlone127/2025-01-28-model_leofn3_en.md
new file mode 100644
index 00000000000000..ada15ea09bd658
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-model_leofn3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English model_leofn3 BertEmbeddings from leofn3
+author: John Snow Labs
+name: model_leofn3
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_leofn3` is a English model originally trained by leofn3.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_leofn3_en_5.5.1_3.0_1738057858538.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_leofn3_en_5.5.1_3.0_1738057858538.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("model_leofn3","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("model_leofn3","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|model_leofn3|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|206.0 MB|
+
+## References
+
+https://huggingface.co/leofn3/model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-model_leofn3_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-model_leofn3_pipeline_en.md
new file mode 100644
index 00000000000000..0e1219a5e1cc95
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-model_leofn3_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English model_leofn3_pipeline pipeline BertEmbeddings from leofn3
+author: John Snow Labs
+name: model_leofn3_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_leofn3_pipeline` is a English model originally trained by leofn3.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_leofn3_pipeline_en_5.5.1_3.0_1738057869023.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_leofn3_pipeline_en_5.5.1_3.0_1738057869023.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("model_leofn3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("model_leofn3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|model_leofn3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.0 MB|
+
+## References
+
+https://huggingface.co/leofn3/model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-model_pipeline_en.md
new file mode 100644
index 00000000000000..6e19e9c084d1fb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-model_pipeline_en.md
@@ -0,0 +1,72 @@
+---
+layout: model
+title: English model_pipeline pipeline DistilBertEmbeddings from Dinithi
+author: John Snow Labs
+name: model_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_pipeline` is a English model originally trained by Dinithi.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_pipeline_en_5.5.1_3.0_1738068373880.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_pipeline_en_5.5.1_3.0_1738068373880.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|292.8 MB|
+
+## References
+
+References
+
+https://huggingface.co/Dinithi/Model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-model_polish_vizwiz_bert_uncased_en.md b/docs/_posts/ahmedlone127/2025-01-28-model_polish_vizwiz_bert_uncased_en.md
new file mode 100644
index 00000000000000..5a0d4aa0051b6c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-model_polish_vizwiz_bert_uncased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English model_polish_vizwiz_bert_uncased BertEmbeddings from nanom
+author: John Snow Labs
+name: model_polish_vizwiz_bert_uncased
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_polish_vizwiz_bert_uncased` is a English model originally trained by nanom.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_polish_vizwiz_bert_uncased_en_5.5.1_3.0_1738035539506.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_polish_vizwiz_bert_uncased_en_5.5.1_3.0_1738035539506.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("model_polish_vizwiz_bert_uncased","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("model_polish_vizwiz_bert_uncased","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|model_polish_vizwiz_bert_uncased|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/nanom/model-pl-vizwiz-bert-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-model_polish_vizwiz_bert_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-model_polish_vizwiz_bert_uncased_pipeline_en.md
new file mode 100644
index 00000000000000..4cca16746b71c8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-model_polish_vizwiz_bert_uncased_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English model_polish_vizwiz_bert_uncased_pipeline pipeline BertEmbeddings from nanom
+author: John Snow Labs
+name: model_polish_vizwiz_bert_uncased_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_polish_vizwiz_bert_uncased_pipeline` is a English model originally trained by nanom.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_polish_vizwiz_bert_uncased_pipeline_en_5.5.1_3.0_1738035559436.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_polish_vizwiz_bert_uncased_pipeline_en_5.5.1_3.0_1738035559436.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("model_polish_vizwiz_bert_uncased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("model_polish_vizwiz_bert_uncased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|model_polish_vizwiz_bert_uncased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/nanom/model-pl-vizwiz-bert-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-model_td3_en.md b/docs/_posts/ahmedlone127/2025-01-28-model_td3_en.md
new file mode 100644
index 00000000000000..e9aae6fca10e84
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-model_td3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English model_td3 CamemBertForTokenClassification from slounaci
+author: John Snow Labs
+name: model_td3
+date: 2025-01-28
+tags: [en, open_source, onnx, token_classification, camembert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_td3` is a English model originally trained by slounaci.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_td3_en_5.5.1_3.0_1738068306785.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_td3_en_5.5.1_3.0_1738068306785.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = CamemBertForTokenClassification.pretrained("model_td3","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = CamemBertForTokenClassification.pretrained("model_td3", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|model_td3|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|292.7 MB|
+
+## References
+
+https://huggingface.co/slounaci/model_td3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-model_td3_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-model_td3_pipeline_en.md
new file mode 100644
index 00000000000000..e3f3a4c8303419
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-model_td3_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English model_td3_pipeline pipeline CamemBertForTokenClassification from slounaci
+author: John Snow Labs
+name: model_td3_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_td3_pipeline` is a English model originally trained by slounaci.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_td3_pipeline_en_5.5.1_3.0_1738068373876.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_td3_pipeline_en_5.5.1_3.0_1738068373876.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("model_td3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("model_td3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|model_td3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|292.8 MB|
+
+## References
+
+https://huggingface.co/slounaci/model_td3
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-model_upgrade_en.md b/docs/_posts/ahmedlone127/2025-01-28-model_upgrade_en.md
new file mode 100644
index 00000000000000..329c1ec41d1186
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-model_upgrade_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English model_upgrade DistilBertForSequenceClassification from bellge
+author: John Snow Labs
+name: model_upgrade
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_upgrade` is a English model originally trained by bellge.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_upgrade_en_5.5.1_3.0_1738025879027.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_upgrade_en_5.5.1_3.0_1738025879027.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("model_upgrade","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("model_upgrade", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|model_upgrade|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/bellge/model_upgrade
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-model_upgrade_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-model_upgrade_pipeline_en.md
new file mode 100644
index 00000000000000..62e108a45ca0d9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-model_upgrade_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English model_upgrade_pipeline pipeline DistilBertForSequenceClassification from bellge
+author: John Snow Labs
+name: model_upgrade_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_upgrade_pipeline` is a English model originally trained by bellge.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_upgrade_pipeline_en_5.5.1_3.0_1738025891672.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_upgrade_pipeline_en_5.5.1_3.0_1738025891672.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("model_upgrade_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("model_upgrade_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|model_upgrade_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/bellge/model_upgrade
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-modeltest_en.md b/docs/_posts/ahmedlone127/2025-01-28-modeltest_en.md
new file mode 100644
index 00000000000000..7687f5c8e3d8bd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-modeltest_en.md
@@ -0,0 +1,96 @@
+---
+layout: model
+title: English modeltest DistilBertForSequenceClassification from pranay143342
+author: John Snow Labs
+name: modeltest
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`modeltest` is a English model originally trained by pranay143342.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/modeltest_en_5.5.1_3.0_1738057612667.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/modeltest_en_5.5.1_3.0_1738057612667.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("modeltest","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("modeltest", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|modeltest|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|464.7 MB|
+
+## References
+
+References
+
+https://huggingface.co/pranay143342/modeltest
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-modeltest_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-modeltest_pipeline_en.md
new file mode 100644
index 00000000000000..d57f24f3f32672
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-modeltest_pipeline_en.md
@@ -0,0 +1,72 @@
+---
+layout: model
+title: English modeltest_pipeline pipeline DistilBertForSequenceClassification from pranay143342
+author: John Snow Labs
+name: modeltest_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`modeltest_pipeline` is a English model originally trained by pranay143342.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/modeltest_pipeline_en_5.5.1_3.0_1738057636016.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/modeltest_pipeline_en_5.5.1_3.0_1738057636016.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("modeltest_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("modeltest_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|modeltest_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|464.7 MB|
+
+## References
+
+References
+
+https://huggingface.co/pranay143342/modeltest
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-mold_strawberry_detection_en.md b/docs/_posts/ahmedlone127/2025-01-28-mold_strawberry_detection_en.md
new file mode 100644
index 00000000000000..6609ffc08f324a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-mold_strawberry_detection_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mold_strawberry_detection ViTForImageClassification from heyitsjearbear
+author: John Snow Labs
+name: mold_strawberry_detection
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mold_strawberry_detection` is a English model originally trained by heyitsjearbear.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mold_strawberry_detection_en_5.5.1_3.0_1738022752808.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mold_strawberry_detection_en_5.5.1_3.0_1738022752808.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""mold_strawberry_detection","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("mold_strawberry_detection","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mold_strawberry_detection|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/heyitsjearbear/mold-strawberry-detection
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-mold_strawberry_detection_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-mold_strawberry_detection_pipeline_en.md
new file mode 100644
index 00000000000000..d154be03bdf3e4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-mold_strawberry_detection_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mold_strawberry_detection_pipeline pipeline ViTForImageClassification from heyitsjearbear
+author: John Snow Labs
+name: mold_strawberry_detection_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mold_strawberry_detection_pipeline` is a English model originally trained by heyitsjearbear.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mold_strawberry_detection_pipeline_en_5.5.1_3.0_1738022770155.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mold_strawberry_detection_pipeline_en_5.5.1_3.0_1738022770155.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mold_strawberry_detection_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mold_strawberry_detection_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mold_strawberry_detection_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/heyitsjearbear/mold-strawberry-detection
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-moldy_strawberries_en.md b/docs/_posts/ahmedlone127/2025-01-28-moldy_strawberries_en.md
new file mode 100644
index 00000000000000..e8d29020f91bde
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-moldy_strawberries_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English moldy_strawberries ViTForImageClassification from heyitsjearbear
+author: John Snow Labs
+name: moldy_strawberries
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`moldy_strawberries` is a English model originally trained by heyitsjearbear.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/moldy_strawberries_en_5.5.1_3.0_1738023473713.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/moldy_strawberries_en_5.5.1_3.0_1738023473713.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""moldy_strawberries","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("moldy_strawberries","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|moldy_strawberries|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/heyitsjearbear/moldy-strawberries
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-moldy_strawberries_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-moldy_strawberries_pipeline_en.md
new file mode 100644
index 00000000000000..0ed771c18fab9d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-moldy_strawberries_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English moldy_strawberries_pipeline pipeline ViTForImageClassification from heyitsjearbear
+author: John Snow Labs
+name: moldy_strawberries_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`moldy_strawberries_pipeline` is a English model originally trained by heyitsjearbear.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/moldy_strawberries_pipeline_en_5.5.1_3.0_1738023491484.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/moldy_strawberries_pipeline_en_5.5.1_3.0_1738023491484.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("moldy_strawberries_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("moldy_strawberries_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|moldy_strawberries_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/heyitsjearbear/moldy-strawberries
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-movie_title_ocr_corrector_t5_en.md b/docs/_posts/ahmedlone127/2025-01-28-movie_title_ocr_corrector_t5_en.md
new file mode 100644
index 00000000000000..75df87b34cb802
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-movie_title_ocr_corrector_t5_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English movie_title_ocr_corrector_t5 T5Transformer from yashvoladoddi37
+author: John Snow Labs
+name: movie_title_ocr_corrector_t5
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`movie_title_ocr_corrector_t5` is a English model originally trained by yashvoladoddi37.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/movie_title_ocr_corrector_t5_en_5.5.1_3.0_1738073356566.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/movie_title_ocr_corrector_t5_en_5.5.1_3.0_1738073356566.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("movie_title_ocr_corrector_t5","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("movie_title_ocr_corrector_t5", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|movie_title_ocr_corrector_t5|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|917.6 MB|
+
+## References
+
+https://huggingface.co/yashvoladoddi37/movie-title-OCR-corrector-t5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-movie_title_ocr_corrector_t5_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-movie_title_ocr_corrector_t5_pipeline_en.md
new file mode 100644
index 00000000000000..8206c364303fcd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-movie_title_ocr_corrector_t5_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English movie_title_ocr_corrector_t5_pipeline pipeline T5Transformer from yashvoladoddi37
+author: John Snow Labs
+name: movie_title_ocr_corrector_t5_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`movie_title_ocr_corrector_t5_pipeline` is a English model originally trained by yashvoladoddi37.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/movie_title_ocr_corrector_t5_pipeline_en_5.5.1_3.0_1738073404420.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/movie_title_ocr_corrector_t5_pipeline_en_5.5.1_3.0_1738073404420.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("movie_title_ocr_corrector_t5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("movie_title_ocr_corrector_t5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|movie_title_ocr_corrector_t5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|917.6 MB|
+
+## References
+
+https://huggingface.co/yashvoladoddi37/movie-title-OCR-corrector-t5
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-mt5_base_binary_czech_iiia_cs.md b/docs/_posts/ahmedlone127/2025-01-28-mt5_base_binary_czech_iiia_cs.md
new file mode 100644
index 00000000000000..b1bf34fb60cf70
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-mt5_base_binary_czech_iiia_cs.md
@@ -0,0 +1,88 @@
+---
+layout: model
+title: Czech mt5_base_binary_czech_iiia T5Transformer from chi2024
+author: John Snow Labs
+name: mt5_base_binary_czech_iiia
+date: 2025-01-28
+tags: [cs, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: cs
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_base_binary_czech_iiia` is a Czech model originally trained by chi2024.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_base_binary_czech_iiia_cs_5.5.1_3.0_1738074461240.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_base_binary_czech_iiia_cs_5.5.1_3.0_1738074461240.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("mt5_base_binary_czech_iiia","cs") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("mt5_base_binary_czech_iiia", "cs")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_base_binary_czech_iiia|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|cs|
+|Size:|2.3 GB|
+
+## References
+
+References
+
+https://huggingface.co/chi2024/mt5-base-binary-cs-iiia
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-mt5_base_binary_czech_iiia_pipeline_cs.md b/docs/_posts/ahmedlone127/2025-01-28-mt5_base_binary_czech_iiia_pipeline_cs.md
new file mode 100644
index 00000000000000..dda0d1a85264cb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-mt5_base_binary_czech_iiia_pipeline_cs.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Czech mt5_base_binary_czech_iiia_pipeline pipeline T5Transformer from chi2024
+author: John Snow Labs
+name: mt5_base_binary_czech_iiia_pipeline
+date: 2025-01-28
+tags: [cs, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: cs
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_base_binary_czech_iiia_pipeline` is a Czech model originally trained by chi2024.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_base_binary_czech_iiia_pipeline_cs_5.5.1_3.0_1738074754691.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_base_binary_czech_iiia_pipeline_cs_5.5.1_3.0_1738074754691.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("mt5_base_binary_czech_iiia_pipeline", lang = "cs")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("mt5_base_binary_czech_iiia_pipeline", lang = "cs")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_base_binary_czech_iiia_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|cs|
+|Size:|2.3 GB|
+
+## References
+
+References
+
+https://huggingface.co/chi2024/mt5-base-binary-cs-iiia
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-mt5_base_finetuned_xsum_en.md b/docs/_posts/ahmedlone127/2025-01-28-mt5_base_finetuned_xsum_en.md
new file mode 100644
index 00000000000000..ba090eb622ed81
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-mt5_base_finetuned_xsum_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mt5_base_finetuned_xsum T5Transformer from guan06
+author: John Snow Labs
+name: mt5_base_finetuned_xsum
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_base_finetuned_xsum` is a English model originally trained by guan06.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_base_finetuned_xsum_en_5.5.1_3.0_1738093587294.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_base_finetuned_xsum_en_5.5.1_3.0_1738093587294.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("mt5_base_finetuned_xsum","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("mt5_base_finetuned_xsum", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_base_finetuned_xsum|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/guan06/mt5-base-finetuned-xsum
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-mt5_base_finetuned_xsum_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-mt5_base_finetuned_xsum_pipeline_en.md
new file mode 100644
index 00000000000000..b8d91edfaaa90f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-mt5_base_finetuned_xsum_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mt5_base_finetuned_xsum_pipeline pipeline T5Transformer from guan06
+author: John Snow Labs
+name: mt5_base_finetuned_xsum_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_base_finetuned_xsum_pipeline` is a English model originally trained by guan06.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_base_finetuned_xsum_pipeline_en_5.5.1_3.0_1738094068841.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_base_finetuned_xsum_pipeline_en_5.5.1_3.0_1738094068841.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mt5_base_finetuned_xsum_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mt5_base_finetuned_xsum_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_base_finetuned_xsum_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/guan06/mt5-base-finetuned-xsum
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-mt5_base_multi_label_czech_iiib_cs.md b/docs/_posts/ahmedlone127/2025-01-28-mt5_base_multi_label_czech_iiib_cs.md
new file mode 100644
index 00000000000000..bb8d5eb8bccb4f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-mt5_base_multi_label_czech_iiib_cs.md
@@ -0,0 +1,88 @@
+---
+layout: model
+title: Czech mt5_base_multi_label_czech_iiib T5Transformer from chi2024
+author: John Snow Labs
+name: mt5_base_multi_label_czech_iiib
+date: 2025-01-28
+tags: [cs, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: cs
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_base_multi_label_czech_iiib` is a Czech model originally trained by chi2024.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_base_multi_label_czech_iiib_cs_5.5.1_3.0_1738073856124.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_base_multi_label_czech_iiib_cs_5.5.1_3.0_1738073856124.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("mt5_base_multi_label_czech_iiib","cs") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("mt5_base_multi_label_czech_iiib", "cs")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_base_multi_label_czech_iiib|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|cs|
+|Size:|2.3 GB|
+
+## References
+
+References
+
+https://huggingface.co/chi2024/mt5-base-multi-label-cs-iiib
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-mt5_base_multi_label_czech_iiib_pipeline_cs.md b/docs/_posts/ahmedlone127/2025-01-28-mt5_base_multi_label_czech_iiib_pipeline_cs.md
new file mode 100644
index 00000000000000..7d156245d4766b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-mt5_base_multi_label_czech_iiib_pipeline_cs.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Czech mt5_base_multi_label_czech_iiib_pipeline pipeline T5Transformer from chi2024
+author: John Snow Labs
+name: mt5_base_multi_label_czech_iiib_pipeline
+date: 2025-01-28
+tags: [cs, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: cs
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_base_multi_label_czech_iiib_pipeline` is a Czech model originally trained by chi2024.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_base_multi_label_czech_iiib_pipeline_cs_5.5.1_3.0_1738074138263.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_base_multi_label_czech_iiib_pipeline_cs_5.5.1_3.0_1738074138263.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("mt5_base_multi_label_czech_iiib_pipeline", lang = "cs")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("mt5_base_multi_label_czech_iiib_pipeline", lang = "cs")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_base_multi_label_czech_iiib_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|cs|
+|Size:|2.3 GB|
+
+## References
+
+References
+
+https://huggingface.co/chi2024/mt5-base-multi-label-cs-iiib
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-mt5_small_finetuned_xsum_shubhangi21_en.md b/docs/_posts/ahmedlone127/2025-01-28-mt5_small_finetuned_xsum_shubhangi21_en.md
new file mode 100644
index 00000000000000..502e090c18c01a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-mt5_small_finetuned_xsum_shubhangi21_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mt5_small_finetuned_xsum_shubhangi21 T5Transformer from Shubhangi21
+author: John Snow Labs
+name: mt5_small_finetuned_xsum_shubhangi21
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_small_finetuned_xsum_shubhangi21` is a English model originally trained by Shubhangi21.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_small_finetuned_xsum_shubhangi21_en_5.5.1_3.0_1738031054798.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_small_finetuned_xsum_shubhangi21_en_5.5.1_3.0_1738031054798.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("mt5_small_finetuned_xsum_shubhangi21","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("mt5_small_finetuned_xsum_shubhangi21", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_small_finetuned_xsum_shubhangi21|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/Shubhangi21/mt5-small-finetuned-xsum
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-mt5_small_finetuned_xsum_shubhangi21_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-mt5_small_finetuned_xsum_shubhangi21_pipeline_en.md
new file mode 100644
index 00000000000000..2139260f0f1aba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-mt5_small_finetuned_xsum_shubhangi21_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mt5_small_finetuned_xsum_shubhangi21_pipeline pipeline T5Transformer from Shubhangi21
+author: John Snow Labs
+name: mt5_small_finetuned_xsum_shubhangi21_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_small_finetuned_xsum_shubhangi21_pipeline` is a English model originally trained by Shubhangi21.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_small_finetuned_xsum_shubhangi21_pipeline_en_5.5.1_3.0_1738031226988.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_small_finetuned_xsum_shubhangi21_pipeline_en_5.5.1_3.0_1738031226988.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mt5_small_finetuned_xsum_shubhangi21_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mt5_small_finetuned_xsum_shubhangi21_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_small_finetuned_xsum_shubhangi21_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/Shubhangi21/mt5-small-finetuned-xsum
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-mt5_sports_french_spanish_en.md b/docs/_posts/ahmedlone127/2025-01-28-mt5_sports_french_spanish_en.md
new file mode 100644
index 00000000000000..c04c67109fafde
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-mt5_sports_french_spanish_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mt5_sports_french_spanish T5Transformer from Dari2000
+author: John Snow Labs
+name: mt5_sports_french_spanish
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_sports_french_spanish` is a English model originally trained by Dari2000.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_sports_french_spanish_en_5.5.1_3.0_1738093692916.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_sports_french_spanish_en_5.5.1_3.0_1738093692916.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("mt5_sports_french_spanish","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("mt5_sports_french_spanish", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_sports_french_spanish|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/Dari2000/mt5-sports-fr-es
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-mt5_sports_french_spanish_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-mt5_sports_french_spanish_pipeline_en.md
new file mode 100644
index 00000000000000..36ccb4ba61ef79
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-mt5_sports_french_spanish_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mt5_sports_french_spanish_pipeline pipeline T5Transformer from Dari2000
+author: John Snow Labs
+name: mt5_sports_french_spanish_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_sports_french_spanish_pipeline` is a English model originally trained by Dari2000.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mt5_sports_french_spanish_pipeline_en_5.5.1_3.0_1738093836593.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_sports_french_spanish_pipeline_en_5.5.1_3.0_1738093836593.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mt5_sports_french_spanish_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mt5_sports_french_spanish_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_sports_french_spanish_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/Dari2000/mt5-sports-fr-es
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-musique_shqg_ft_en.md b/docs/_posts/ahmedlone127/2025-01-28-musique_shqg_ft_en.md
new file mode 100644
index 00000000000000..f35c3d16cd1bcd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-musique_shqg_ft_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English musique_shqg_ft T5Transformer from abiantonio
+author: John Snow Labs
+name: musique_shqg_ft
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`musique_shqg_ft` is a English model originally trained by abiantonio.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/musique_shqg_ft_en_5.5.1_3.0_1738072542072.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/musique_shqg_ft_en_5.5.1_3.0_1738072542072.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("musique_shqg_ft","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("musique_shqg_ft", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|musique_shqg_ft|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|3.1 GB|
+
+## References
+
+https://huggingface.co/abiantonio/musique-shqg-ft
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-musique_shqg_ft_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-musique_shqg_ft_pipeline_en.md
new file mode 100644
index 00000000000000..23b2218b725dda
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-musique_shqg_ft_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English musique_shqg_ft_pipeline pipeline T5Transformer from abiantonio
+author: John Snow Labs
+name: musique_shqg_ft_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`musique_shqg_ft_pipeline` is a English model originally trained by abiantonio.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/musique_shqg_ft_pipeline_en_5.5.1_3.0_1738072685597.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/musique_shqg_ft_pipeline_en_5.5.1_3.0_1738072685597.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("musique_shqg_ft_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("musique_shqg_ft_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|musique_shqg_ft_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|3.1 GB|
+
+## References
+
+https://huggingface.co/abiantonio/musique-shqg-ft
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-nepal_bhasa_t5_slim_en.md b/docs/_posts/ahmedlone127/2025-01-28-nepal_bhasa_t5_slim_en.md
new file mode 100644
index 00000000000000..0424722e580b15
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-nepal_bhasa_t5_slim_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English nepal_bhasa_t5_slim T5Transformer from Jawaker
+author: John Snow Labs
+name: nepal_bhasa_t5_slim
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nepal_bhasa_t5_slim` is a English model originally trained by Jawaker.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nepal_bhasa_t5_slim_en_5.5.1_3.0_1738092395720.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nepal_bhasa_t5_slim_en_5.5.1_3.0_1738092395720.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("nepal_bhasa_t5_slim","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("nepal_bhasa_t5_slim", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nepal_bhasa_t5_slim|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|166.8 MB|
+
+## References
+
+https://huggingface.co/Jawaker/new-t5-slim
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-nepal_bhasa_t5_slim_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-nepal_bhasa_t5_slim_pipeline_en.md
new file mode 100644
index 00000000000000..1a57ea814c269a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-nepal_bhasa_t5_slim_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English nepal_bhasa_t5_slim_pipeline pipeline T5Transformer from Jawaker
+author: John Snow Labs
+name: nepal_bhasa_t5_slim_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nepal_bhasa_t5_slim_pipeline` is a English model originally trained by Jawaker.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nepal_bhasa_t5_slim_pipeline_en_5.5.1_3.0_1738092404721.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nepal_bhasa_t5_slim_pipeline_en_5.5.1_3.0_1738092404721.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("nepal_bhasa_t5_slim_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("nepal_bhasa_t5_slim_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nepal_bhasa_t5_slim_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|166.8 MB|
+
+## References
+
+https://huggingface.co/Jawaker/new-t5-slim
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-nepali_ner_bert_ne.md b/docs/_posts/ahmedlone127/2025-01-28-nepali_ner_bert_ne.md
new file mode 100644
index 00000000000000..51445064da8b45
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-nepali_ner_bert_ne.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Nepali (macrolanguage) nepali_ner_bert BertEmbeddings from debabrata-ai
+author: John Snow Labs
+name: nepali_ner_bert
+date: 2025-01-28
+tags: [ne, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: ne
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nepali_ner_bert` is a Nepali (macrolanguage) model originally trained by debabrata-ai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nepali_ner_bert_ne_5.5.1_3.0_1738098742947.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nepali_ner_bert_ne_5.5.1_3.0_1738098742947.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("nepali_ner_bert","ne") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("nepali_ner_bert","ne") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nepali_ner_bert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|ne|
+|Size:|663.2 MB|
+
+## References
+
+https://huggingface.co/debabrata-ai/Nepali-NER-BERT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-nepali_ner_bert_pipeline_ne.md b/docs/_posts/ahmedlone127/2025-01-28-nepali_ner_bert_pipeline_ne.md
new file mode 100644
index 00000000000000..e6fcb6c9c6b9cb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-nepali_ner_bert_pipeline_ne.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Nepali (macrolanguage) nepali_ner_bert_pipeline pipeline BertEmbeddings from debabrata-ai
+author: John Snow Labs
+name: nepali_ner_bert_pipeline
+date: 2025-01-28
+tags: [ne, open_source, pipeline, onnx]
+task: Embeddings
+language: ne
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nepali_ner_bert_pipeline` is a Nepali (macrolanguage) model originally trained by debabrata-ai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nepali_ner_bert_pipeline_ne_5.5.1_3.0_1738098776123.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nepali_ner_bert_pipeline_ne_5.5.1_3.0_1738098776123.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("nepali_ner_bert_pipeline", lang = "ne")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("nepali_ner_bert_pipeline", lang = "ne")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nepali_ner_bert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ne|
+|Size:|663.2 MB|
+
+## References
+
+https://huggingface.co/debabrata-ai/Nepali-NER-BERT
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-ner_model_amhyr_en.md b/docs/_posts/ahmedlone127/2025-01-28-ner_model_amhyr_en.md
new file mode 100644
index 00000000000000..f80d308bd7de60
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-ner_model_amhyr_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ner_model_amhyr BertForTokenClassification from Amhyr
+author: John Snow Labs
+name: ner_model_amhyr
+date: 2025-01-28
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_model_amhyr` is a English model originally trained by Amhyr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_model_amhyr_en_5.5.1_3.0_1738044481667.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_model_amhyr_en_5.5.1_3.0_1738044481667.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("ner_model_amhyr","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("ner_model_amhyr", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_model_amhyr|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/Amhyr/ner-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-ner_model_amhyr_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-ner_model_amhyr_pipeline_en.md
new file mode 100644
index 00000000000000..adb70387d3c31f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-ner_model_amhyr_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ner_model_amhyr_pipeline pipeline BertForTokenClassification from Amhyr
+author: John Snow Labs
+name: ner_model_amhyr_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_model_amhyr_pipeline` is a English model originally trained by Amhyr.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_model_amhyr_pipeline_en_5.5.1_3.0_1738044514167.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_model_amhyr_pipeline_en_5.5.1_3.0_1738044514167.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ner_model_amhyr_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ner_model_amhyr_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_model_amhyr_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/Amhyr/ner-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-ner_model_roberta_en.md b/docs/_posts/ahmedlone127/2025-01-28-ner_model_roberta_en.md
new file mode 100644
index 00000000000000..c453c31536d8d6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-ner_model_roberta_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ner_model_roberta XlmRoBertaForTokenClassification from alexia-allal
+author: John Snow Labs
+name: ner_model_roberta
+date: 2025-01-28
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_model_roberta` is a English model originally trained by alexia-allal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_model_roberta_en_5.5.1_3.0_1738064221319.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_model_roberta_en_5.5.1_3.0_1738064221319.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("ner_model_roberta","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("ner_model_roberta", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_model_roberta|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|790.7 MB|
+
+## References
+
+https://huggingface.co/alexia-allal/ner-model-roberta
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-ner_model_roberta_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-ner_model_roberta_pipeline_en.md
new file mode 100644
index 00000000000000..9b6991f4f2c364
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-ner_model_roberta_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ner_model_roberta_pipeline pipeline XlmRoBertaForTokenClassification from alexia-allal
+author: John Snow Labs
+name: ner_model_roberta_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_model_roberta_pipeline` is a English model originally trained by alexia-allal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_model_roberta_pipeline_en_5.5.1_3.0_1738064343348.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_model_roberta_pipeline_en_5.5.1_3.0_1738064343348.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ner_model_roberta_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ner_model_roberta_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_model_roberta_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|790.7 MB|
+
+## References
+
+https://huggingface.co/alexia-allal/ner-model-roberta
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-newsbert_en.md b/docs/_posts/ahmedlone127/2025-01-28-newsbert_en.md
new file mode 100644
index 00000000000000..192ff0691dfd58
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-newsbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English newsbert BertEmbeddings from uclanlp
+author: John Snow Labs
+name: newsbert
+date: 2025-01-28
+tags: [bert, en, open_source, fill_mask, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings  model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`newsbert` is a English model originally trained by uclanlp.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/newsbert_en_5.5.1_3.0_1738035128297.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/newsbert_en_5.5.1_3.0_1738035128297.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+document_assembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("documents")
+    
+    
+embeddings =BertEmbeddings.pretrained("newsbert","en") \
+            .setInputCols(["documents","token"]) \
+            .setOutputCol("embeddings")
+
+pipeline = Pipeline().setStages([document_assembler, embeddings])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val document_assembler = new DocumentAssembler()
+    .setInputCol("text") 
+    .setOutputCol("embeddings")
+    
+val embeddings = BertEmbeddings 
+    .pretrained("newsbert", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("embeddings") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|newsbert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+References
+
+References
+
+https://huggingface.co/uclanlp/newsbert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-newsbert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-newsbert_pipeline_en.md
new file mode 100644
index 00000000000000..7ea0ac51ffd0a3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-newsbert_pipeline_en.md
@@ -0,0 +1,72 @@
+---
+layout: model
+title: English newsbert_pipeline pipeline BertEmbeddings from psmeros
+author: John Snow Labs
+name: newsbert_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`newsbert_pipeline` is a English model originally trained by psmeros.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/newsbert_pipeline_en_5.5.1_3.0_1738035156220.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/newsbert_pipeline_en_5.5.1_3.0_1738035156220.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("newsbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("newsbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|newsbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+References
+
+https://huggingface.co/psmeros/NewsBERT
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-nhs_distilbert_multi_en.md b/docs/_posts/ahmedlone127/2025-01-28-nhs_distilbert_multi_en.md
new file mode 100644
index 00000000000000..d9ae06d4a690a1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-nhs_distilbert_multi_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English nhs_distilbert_multi DistilBertForSequenceClassification from intermezzo672
+author: John Snow Labs
+name: nhs_distilbert_multi
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nhs_distilbert_multi` is a English model originally trained by intermezzo672.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nhs_distilbert_multi_en_5.5.1_3.0_1738078228858.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nhs_distilbert_multi_en_5.5.1_3.0_1738078228858.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("nhs_distilbert_multi","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("nhs_distilbert_multi", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nhs_distilbert_multi|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/intermezzo672/NHS-distilbert-multi
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-nhs_distilbert_multi_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-nhs_distilbert_multi_pipeline_en.md
new file mode 100644
index 00000000000000..475b412ef01f6c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-nhs_distilbert_multi_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English nhs_distilbert_multi_pipeline pipeline DistilBertForSequenceClassification from intermezzo672
+author: John Snow Labs
+name: nhs_distilbert_multi_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nhs_distilbert_multi_pipeline` is a English model originally trained by intermezzo672.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nhs_distilbert_multi_pipeline_en_5.5.1_3.0_1738078241378.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nhs_distilbert_multi_pipeline_en_5.5.1_3.0_1738078241378.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("nhs_distilbert_multi_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("nhs_distilbert_multi_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nhs_distilbert_multi_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/intermezzo672/NHS-distilbert-multi
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-none_en.md b/docs/_posts/ahmedlone127/2025-01-28-none_en.md
new file mode 100644
index 00000000000000..cb540e5edc6db0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-none_en.md
@@ -0,0 +1,96 @@
+---
+layout: model
+title: English none RoBertaForSequenceClassification from rose-e-wang
+author: John Snow Labs
+name: none
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`none` is a English model originally trained by rose-e-wang.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/none_en_5.5.1_3.0_1738094059455.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/none_en_5.5.1_3.0_1738094059455.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("none","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("none", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|none|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|266.1 MB|
+
+## References
+
+References
+
+https://huggingface.co/rose-e-wang/None
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-none_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-none_pipeline_en.md
new file mode 100644
index 00000000000000..f047df811e486f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-none_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English none_pipeline pipeline RoBertaForSequenceClassification from rose-e-wang
+author: John Snow Labs
+name: none_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`none_pipeline` is a English model originally trained by rose-e-wang.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/none_pipeline_en_5.5.1_3.0_1738094078327.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/none_pipeline_en_5.5.1_3.0_1738094078327.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("none_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("none_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|none_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|266.1 MB|
+
+## References
+
+References
+
+https://huggingface.co/rose-e-wang/None
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-ownmodel_en.md b/docs/_posts/ahmedlone127/2025-01-28-ownmodel_en.md
new file mode 100644
index 00000000000000..2d5d18eb1ae83d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-ownmodel_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ownmodel DistilBertForSequenceClassification from chinahbcq
+author: John Snow Labs
+name: ownmodel
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ownmodel` is a English model originally trained by chinahbcq.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ownmodel_en_5.5.1_3.0_1738077749866.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ownmodel_en_5.5.1_3.0_1738077749866.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("ownmodel","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("ownmodel", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ownmodel|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/chinahbcq/ownmodel
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-ownmodel_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-ownmodel_pipeline_en.md
new file mode 100644
index 00000000000000..3781f8b50e9b0d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-ownmodel_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ownmodel_pipeline pipeline DistilBertForSequenceClassification from chinahbcq
+author: John Snow Labs
+name: ownmodel_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ownmodel_pipeline` is a English model originally trained by chinahbcq.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ownmodel_pipeline_en_5.5.1_3.0_1738077762487.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ownmodel_pipeline_en_5.5.1_3.0_1738077762487.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ownmodel_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ownmodel_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ownmodel_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/chinahbcq/ownmodel
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-phishing_detection_fine_tuned_bert_en.md b/docs/_posts/ahmedlone127/2025-01-28-phishing_detection_fine_tuned_bert_en.md
new file mode 100644
index 00000000000000..b731a7b4c51998
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-phishing_detection_fine_tuned_bert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English phishing_detection_fine_tuned_bert BertForSequenceClassification from osei1819
+author: John Snow Labs
+name: phishing_detection_fine_tuned_bert
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`phishing_detection_fine_tuned_bert` is a English model originally trained by osei1819.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/phishing_detection_fine_tuned_bert_en_5.5.1_3.0_1738052143154.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/phishing_detection_fine_tuned_bert_en_5.5.1_3.0_1738052143154.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("phishing_detection_fine_tuned_bert","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("phishing_detection_fine_tuned_bert", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|phishing_detection_fine_tuned_bert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/osei1819/phishing_detection_fine_tuned_bert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-phishing_detection_fine_tuned_bert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-phishing_detection_fine_tuned_bert_pipeline_en.md
new file mode 100644
index 00000000000000..8fcd9ab2224749
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-phishing_detection_fine_tuned_bert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English phishing_detection_fine_tuned_bert_pipeline pipeline BertForSequenceClassification from osei1819
+author: John Snow Labs
+name: phishing_detection_fine_tuned_bert_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`phishing_detection_fine_tuned_bert_pipeline` is a English model originally trained by osei1819.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/phishing_detection_fine_tuned_bert_pipeline_en_5.5.1_3.0_1738052163256.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/phishing_detection_fine_tuned_bert_pipeline_en_5.5.1_3.0_1738052163256.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("phishing_detection_fine_tuned_bert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("phishing_detection_fine_tuned_bert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|phishing_detection_fine_tuned_bert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/osei1819/phishing_detection_fine_tuned_bert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-pii_detection_en.md b/docs/_posts/ahmedlone127/2025-01-28-pii_detection_en.md
new file mode 100644
index 00000000000000..2eecffde20bfee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-pii_detection_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English pii_detection DistilBertForTokenClassification from deepaksiloka
+author: John Snow Labs
+name: pii_detection
+date: 2025-01-28
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pii_detection` is a English model originally trained by deepaksiloka.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pii_detection_en_5.5.1_3.0_1738101629601.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pii_detection_en_5.5.1_3.0_1738101629601.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("pii_detection","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("pii_detection", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pii_detection|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.6 MB|
+
+## References
+
+https://huggingface.co/deepaksiloka/PII-Detection
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-pii_detection_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-pii_detection_pipeline_en.md
new file mode 100644
index 00000000000000..bca86ecbc6f136
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-pii_detection_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English pii_detection_pipeline pipeline DistilBertForTokenClassification from deepaksiloka
+author: John Snow Labs
+name: pii_detection_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pii_detection_pipeline` is a English model originally trained by deepaksiloka.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pii_detection_pipeline_en_5.5.1_3.0_1738101645909.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pii_detection_pipeline_en_5.5.1_3.0_1738101645909.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("pii_detection_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("pii_detection_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pii_detection_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.6 MB|
+
+## References
+
+https://huggingface.co/deepaksiloka/PII-Detection
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-plant_model_en.md b/docs/_posts/ahmedlone127/2025-01-28-plant_model_en.md
new file mode 100644
index 00000000000000..1ca1724f30b75b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-plant_model_en.md
@@ -0,0 +1,96 @@
+---
+layout: model
+title: English plant_model DistilBertForTokenClassification from KHEYH
+author: John Snow Labs
+name: plant_model
+date: 2025-01-28
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`plant_model` is a English model originally trained by KHEYH.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/plant_model_en_5.5.1_3.0_1738095988062.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/plant_model_en_5.5.1_3.0_1738095988062.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("plant_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("plant_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|plant_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+References
+
+https://huggingface.co/KHEYH/plant_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-plant_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-plant_model_pipeline_en.md
new file mode 100644
index 00000000000000..24fae64ee523f6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-plant_model_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English plant_model_pipeline pipeline DistilBertForTokenClassification from KHEYH
+author: John Snow Labs
+name: plant_model_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`plant_model_pipeline` is a English model originally trained by KHEYH.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/plant_model_pipeline_en_5.5.1_3.0_1738095998720.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/plant_model_pipeline_en_5.5.1_3.0_1738095998720.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("plant_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("plant_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|plant_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+References
+
+https://huggingface.co/KHEYH/plant_model
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-plastic_recycling_codes_en.md b/docs/_posts/ahmedlone127/2025-01-28-plastic_recycling_codes_en.md
new file mode 100644
index 00000000000000..bd6f483343684d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-plastic_recycling_codes_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English plastic_recycling_codes SwinForImageClassification from DamarJati
+author: John Snow Labs
+name: plastic_recycling_codes
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`plastic_recycling_codes` is a English model originally trained by DamarJati.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/plastic_recycling_codes_en_5.5.1_3.0_1738095232060.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/plastic_recycling_codes_en_5.5.1_3.0_1738095232060.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""plastic_recycling_codes","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("plastic_recycling_codes","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|plastic_recycling_codes|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/DamarJati/plastic-recycling-codes
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-plastic_recycling_codes_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-plastic_recycling_codes_pipeline_en.md
new file mode 100644
index 00000000000000..3ed7d380f606e0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-plastic_recycling_codes_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English plastic_recycling_codes_pipeline pipeline SwinForImageClassification from DamarJati
+author: John Snow Labs
+name: plastic_recycling_codes_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`plastic_recycling_codes_pipeline` is a English model originally trained by DamarJati.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/plastic_recycling_codes_pipeline_en_5.5.1_3.0_1738095242807.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/plastic_recycling_codes_pipeline_en_5.5.1_3.0_1738095242807.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("plastic_recycling_codes_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("plastic_recycling_codes_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|plastic_recycling_codes_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/DamarJati/plastic-recycling-codes
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-pokemon_classifier_gen9_1025_en.md b/docs/_posts/ahmedlone127/2025-01-28-pokemon_classifier_gen9_1025_en.md
new file mode 100644
index 00000000000000..d945623859a474
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-pokemon_classifier_gen9_1025_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English pokemon_classifier_gen9_1025 ViTForImageClassification from skshmjn
+author: John Snow Labs
+name: pokemon_classifier_gen9_1025
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pokemon_classifier_gen9_1025` is a English model originally trained by skshmjn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pokemon_classifier_gen9_1025_en_5.5.1_3.0_1738022888047.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pokemon_classifier_gen9_1025_en_5.5.1_3.0_1738022888047.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""pokemon_classifier_gen9_1025","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("pokemon_classifier_gen9_1025","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pokemon_classifier_gen9_1025|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|324.3 MB|
+
+## References
+
+https://huggingface.co/skshmjn/Pokemon-classifier-gen9-1025
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-pokemon_classifier_gen9_1025_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-pokemon_classifier_gen9_1025_pipeline_en.md
new file mode 100644
index 00000000000000..7d06699dd76a28
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-pokemon_classifier_gen9_1025_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English pokemon_classifier_gen9_1025_pipeline pipeline ViTForImageClassification from skshmjn
+author: John Snow Labs
+name: pokemon_classifier_gen9_1025_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pokemon_classifier_gen9_1025_pipeline` is a English model originally trained by skshmjn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pokemon_classifier_gen9_1025_pipeline_en_5.5.1_3.0_1738022905911.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pokemon_classifier_gen9_1025_pipeline_en_5.5.1_3.0_1738022905911.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("pokemon_classifier_gen9_1025_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("pokemon_classifier_gen9_1025_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pokemon_classifier_gen9_1025_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|324.3 MB|
+
+## References
+
+https://huggingface.co/skshmjn/Pokemon-classifier-gen9-1025
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-pretrained_clickbait_1078k_banglabert_base_epoch_10_en.md b/docs/_posts/ahmedlone127/2025-01-28-pretrained_clickbait_1078k_banglabert_base_epoch_10_en.md
new file mode 100644
index 00000000000000..bbf04762085594
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-pretrained_clickbait_1078k_banglabert_base_epoch_10_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English pretrained_clickbait_1078k_banglabert_base_epoch_10 BertEmbeddings from samanjoy2
+author: John Snow Labs
+name: pretrained_clickbait_1078k_banglabert_base_epoch_10
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pretrained_clickbait_1078k_banglabert_base_epoch_10` is a English model originally trained by samanjoy2.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pretrained_clickbait_1078k_banglabert_base_epoch_10_en_5.5.1_3.0_1738035479262.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pretrained_clickbait_1078k_banglabert_base_epoch_10_en_5.5.1_3.0_1738035479262.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("pretrained_clickbait_1078k_banglabert_base_epoch_10","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("pretrained_clickbait_1078k_banglabert_base_epoch_10","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pretrained_clickbait_1078k_banglabert_base_epoch_10|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|412.1 MB|
+
+## References
+
+https://huggingface.co/samanjoy2/pretrained_clickbait_1078k_banglabert_base_epoch_10
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-pretrained_clickbait_1078k_banglabert_base_epoch_10_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-pretrained_clickbait_1078k_banglabert_base_epoch_10_pipeline_en.md
new file mode 100644
index 00000000000000..60857abed0b44c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-pretrained_clickbait_1078k_banglabert_base_epoch_10_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English pretrained_clickbait_1078k_banglabert_base_epoch_10_pipeline pipeline BertEmbeddings from samanjoy2
+author: John Snow Labs
+name: pretrained_clickbait_1078k_banglabert_base_epoch_10_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pretrained_clickbait_1078k_banglabert_base_epoch_10_pipeline` is a English model originally trained by samanjoy2.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pretrained_clickbait_1078k_banglabert_base_epoch_10_pipeline_en_5.5.1_3.0_1738035499558.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pretrained_clickbait_1078k_banglabert_base_epoch_10_pipeline_en_5.5.1_3.0_1738035499558.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("pretrained_clickbait_1078k_banglabert_base_epoch_10_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("pretrained_clickbait_1078k_banglabert_base_epoch_10_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pretrained_clickbait_1078k_banglabert_base_epoch_10_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|412.2 MB|
+
+## References
+
+https://huggingface.co/samanjoy2/pretrained_clickbait_1078k_banglabert_base_epoch_10
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-pts_bart_large_cnn_en.md b/docs/_posts/ahmedlone127/2025-01-28-pts_bart_large_cnn_en.md
new file mode 100644
index 00000000000000..0484948a36280d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-pts_bart_large_cnn_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English pts_bart_large_cnn BartTransformer from ahmedmbutt
+author: John Snow Labs
+name: pts_bart_large_cnn
+date: 2025-01-28
+tags: [en, open_source, onnx, text_generation, bart]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BartTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pts_bart_large_cnn` is a English model originally trained by ahmedmbutt.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pts_bart_large_cnn_en_5.5.1_3.0_1738080183208.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pts_bart_large_cnn_en_5.5.1_3.0_1738080183208.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = BartTransformer.pretrained("pts_bart_large_cnn","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = BartTransformer.pretrained("pts_bart_large_cnn","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pts_bart_large_cnn|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.9 GB|
+
+## References
+
+https://huggingface.co/ahmedmbutt/PTS-Bart-Large-CNN
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-pts_bart_large_cnn_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-pts_bart_large_cnn_pipeline_en.md
new file mode 100644
index 00000000000000..f3a0bfeaf79f6f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-pts_bart_large_cnn_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English pts_bart_large_cnn_pipeline pipeline BartTransformer from ahmedmbutt
+author: John Snow Labs
+name: pts_bart_large_cnn_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pts_bart_large_cnn_pipeline` is a English model originally trained by ahmedmbutt.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pts_bart_large_cnn_pipeline_en_5.5.1_3.0_1738080274186.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pts_bart_large_cnn_pipeline_en_5.5.1_3.0_1738080274186.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("pts_bart_large_cnn_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("pts_bart_large_cnn_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pts_bart_large_cnn_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.9 GB|
+
+## References
+
+https://huggingface.co/ahmedmbutt/PTS-Bart-Large-CNN
+
+## Included Models
+
+- DocumentAssembler
+- BartTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-pubchem10m_smiles_bpe_396_250_safetensors_en.md b/docs/_posts/ahmedlone127/2025-01-28-pubchem10m_smiles_bpe_396_250_safetensors_en.md
new file mode 100644
index 00000000000000..a92c2a11d30141
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-pubchem10m_smiles_bpe_396_250_safetensors_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English pubchem10m_smiles_bpe_396_250_safetensors RoBertaEmbeddings from yzimmermann
+author: John Snow Labs
+name: pubchem10m_smiles_bpe_396_250_safetensors
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pubchem10m_smiles_bpe_396_250_safetensors` is a English model originally trained by yzimmermann.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pubchem10m_smiles_bpe_396_250_safetensors_en_5.5.1_3.0_1738102788612.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pubchem10m_smiles_bpe_396_250_safetensors_en_5.5.1_3.0_1738102788612.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("pubchem10m_smiles_bpe_396_250_safetensors","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("pubchem10m_smiles_bpe_396_250_safetensors","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pubchem10m_smiles_bpe_396_250_safetensors|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|311.0 MB|
+
+## References
+
+https://huggingface.co/yzimmermann/PubChem10M_SMILES_BPE_396_250-safetensors
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-pubchem10m_smiles_bpe_396_250_safetensors_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-pubchem10m_smiles_bpe_396_250_safetensors_pipeline_en.md
new file mode 100644
index 00000000000000..0e76d62e8fa697
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-pubchem10m_smiles_bpe_396_250_safetensors_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English pubchem10m_smiles_bpe_396_250_safetensors_pipeline pipeline RoBertaEmbeddings from yzimmermann
+author: John Snow Labs
+name: pubchem10m_smiles_bpe_396_250_safetensors_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pubchem10m_smiles_bpe_396_250_safetensors_pipeline` is a English model originally trained by yzimmermann.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pubchem10m_smiles_bpe_396_250_safetensors_pipeline_en_5.5.1_3.0_1738102803988.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pubchem10m_smiles_bpe_396_250_safetensors_pipeline_en_5.5.1_3.0_1738102803988.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("pubchem10m_smiles_bpe_396_250_safetensors_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("pubchem10m_smiles_bpe_396_250_safetensors_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pubchem10m_smiles_bpe_396_250_safetensors_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|311.0 MB|
+
+## References
+
+https://huggingface.co/yzimmermann/PubChem10M_SMILES_BPE_396_250-safetensors
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-qsaf_propositional_v2_en.md b/docs/_posts/ahmedlone127/2025-01-28-qsaf_propositional_v2_en.md
new file mode 100644
index 00000000000000..44dd3f8b271bd1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-qsaf_propositional_v2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English qsaf_propositional_v2 T5Transformer from ryusangwon
+author: John Snow Labs
+name: qsaf_propositional_v2
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qsaf_propositional_v2` is a English model originally trained by ryusangwon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qsaf_propositional_v2_en_5.5.1_3.0_1738032057625.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qsaf_propositional_v2_en_5.5.1_3.0_1738032057625.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("qsaf_propositional_v2","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("qsaf_propositional_v2", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qsaf_propositional_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|3.1 GB|
+
+## References
+
+https://huggingface.co/ryusangwon/qsaf_propositional_v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-qsaf_propositional_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-qsaf_propositional_v2_pipeline_en.md
new file mode 100644
index 00000000000000..59c8e88befc24e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-qsaf_propositional_v2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English qsaf_propositional_v2_pipeline pipeline T5Transformer from ryusangwon
+author: John Snow Labs
+name: qsaf_propositional_v2_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qsaf_propositional_v2_pipeline` is a English model originally trained by ryusangwon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qsaf_propositional_v2_pipeline_en_5.5.1_3.0_1738032202195.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qsaf_propositional_v2_pipeline_en_5.5.1_3.0_1738032202195.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("qsaf_propositional_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("qsaf_propositional_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qsaf_propositional_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|3.1 GB|
+
+## References
+
+https://huggingface.co/ryusangwon/qsaf_propositional_v2
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-qsaf_t5_en.md b/docs/_posts/ahmedlone127/2025-01-28-qsaf_t5_en.md
new file mode 100644
index 00000000000000..2b63645ca798a8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-qsaf_t5_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English qsaf_t5 T5Transformer from ryusangwon
+author: John Snow Labs
+name: qsaf_t5
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qsaf_t5` is a English model originally trained by ryusangwon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qsaf_t5_en_5.5.1_3.0_1738072220244.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qsaf_t5_en_5.5.1_3.0_1738072220244.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("qsaf_t5","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("qsaf_t5", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qsaf_t5|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|2.9 GB|
+
+## References
+
+https://huggingface.co/ryusangwon/qsaf_t5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-qsaf_t5_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-qsaf_t5_pipeline_en.md
new file mode 100644
index 00000000000000..ea89b1651d74d1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-qsaf_t5_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English qsaf_t5_pipeline pipeline T5Transformer from ryusangwon
+author: John Snow Labs
+name: qsaf_t5_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qsaf_t5_pipeline` is a English model originally trained by ryusangwon.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qsaf_t5_pipeline_en_5.5.1_3.0_1738072386055.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qsaf_t5_pipeline_en_5.5.1_3.0_1738072386055.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("qsaf_t5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("qsaf_t5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qsaf_t5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|2.9 GB|
+
+## References
+
+https://huggingface.co/ryusangwon/qsaf_t5
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-question_classification_en.md b/docs/_posts/ahmedlone127/2025-01-28-question_classification_en.md
new file mode 100644
index 00000000000000..f0f9ee09e2c6ba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-question_classification_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English question_classification BertForSequenceClassification from smerchi
+author: John Snow Labs
+name: question_classification
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`question_classification` is a English model originally trained by smerchi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/question_classification_en_5.5.1_3.0_1738027517057.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/question_classification_en_5.5.1_3.0_1738027517057.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("question_classification","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("question_classification", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|question_classification|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|553.7 MB|
+
+## References
+
+https://huggingface.co/smerchi/question_classification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-question_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-question_classification_pipeline_en.md
new file mode 100644
index 00000000000000..cd660a4ef2c945
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-question_classification_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English question_classification_pipeline pipeline BertForSequenceClassification from smerchi
+author: John Snow Labs
+name: question_classification_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`question_classification_pipeline` is a English model originally trained by smerchi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/question_classification_pipeline_en_5.5.1_3.0_1738027544508.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/question_classification_pipeline_en_5.5.1_3.0_1738027544508.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("question_classification_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("question_classification_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|question_classification_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|553.7 MB|
+
+## References
+
+https://huggingface.co/smerchi/question_classification
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-qwen_textgen_model15ggg_en.md b/docs/_posts/ahmedlone127/2025-01-28-qwen_textgen_model15ggg_en.md
new file mode 100644
index 00000000000000..7c5579235ee7c2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-qwen_textgen_model15ggg_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English qwen_textgen_model15ggg BertEmbeddings from JeloH
+author: John Snow Labs
+name: qwen_textgen_model15ggg
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qwen_textgen_model15ggg` is a English model originally trained by JeloH.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qwen_textgen_model15ggg_en_5.5.1_3.0_1738084580621.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qwen_textgen_model15ggg_en_5.5.1_3.0_1738084580621.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("qwen_textgen_model15ggg","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("qwen_textgen_model15ggg","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qwen_textgen_model15ggg|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/JeloH/qwen-textgen-model15ggg
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-qwen_textgen_model15ggg_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-qwen_textgen_model15ggg_pipeline_en.md
new file mode 100644
index 00000000000000..3a6ef3987ac9ad
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-qwen_textgen_model15ggg_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English qwen_textgen_model15ggg_pipeline pipeline BertEmbeddings from JeloH
+author: John Snow Labs
+name: qwen_textgen_model15ggg_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qwen_textgen_model15ggg_pipeline` is a English model originally trained by JeloH.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qwen_textgen_model15ggg_pipeline_en_5.5.1_3.0_1738084601770.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qwen_textgen_model15ggg_pipeline_en_5.5.1_3.0_1738084601770.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("qwen_textgen_model15ggg_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("qwen_textgen_model15ggg_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qwen_textgen_model15ggg_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/JeloH/qwen-textgen-model15ggg
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-randeng_bart_139m_summary_pipeline_zh.md b/docs/_posts/ahmedlone127/2025-01-28-randeng_bart_139m_summary_pipeline_zh.md
new file mode 100644
index 00000000000000..c2821d4910638b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-randeng_bart_139m_summary_pipeline_zh.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Chinese randeng_bart_139m_summary_pipeline pipeline BartTransformer from IDEA-CCNL
+author: John Snow Labs
+name: randeng_bart_139m_summary_pipeline
+date: 2025-01-28
+tags: [zh, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: zh
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`randeng_bart_139m_summary_pipeline` is a Chinese model originally trained by IDEA-CCNL.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/randeng_bart_139m_summary_pipeline_zh_5.5.1_3.0_1738079780343.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/randeng_bart_139m_summary_pipeline_zh_5.5.1_3.0_1738079780343.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("randeng_bart_139m_summary_pipeline", lang = "zh")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("randeng_bart_139m_summary_pipeline", lang = "zh")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|randeng_bart_139m_summary_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|zh|
+|Size:|514.4 MB|
+
+## References
+
+https://huggingface.co/IDEA-CCNL/Randeng-BART-139M-SUMMARY
+
+## Included Models
+
+- DocumentAssembler
+- BartTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-randeng_bart_139m_summary_zh.md b/docs/_posts/ahmedlone127/2025-01-28-randeng_bart_139m_summary_zh.md
new file mode 100644
index 00000000000000..3978df8263e277
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-randeng_bart_139m_summary_zh.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Chinese randeng_bart_139m_summary BartTransformer from IDEA-CCNL
+author: John Snow Labs
+name: randeng_bart_139m_summary
+date: 2025-01-28
+tags: [zh, open_source, onnx, text_generation, bart]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: zh
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BartTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`randeng_bart_139m_summary` is a Chinese model originally trained by IDEA-CCNL.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/randeng_bart_139m_summary_zh_5.5.1_3.0_1738079634839.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/randeng_bart_139m_summary_zh_5.5.1_3.0_1738079634839.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = BartTransformer.pretrained("randeng_bart_139m_summary","zh") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = BartTransformer.pretrained("randeng_bart_139m_summary","zh") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|randeng_bart_139m_summary|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|zh|
+|Size:|514.4 MB|
+
+## References
+
+https://huggingface.co/IDEA-CCNL/Randeng-BART-139M-SUMMARY
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-randomly_pruned_99_model_en.md b/docs/_posts/ahmedlone127/2025-01-28-randomly_pruned_99_model_en.md
new file mode 100644
index 00000000000000..8b11f43881651b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-randomly_pruned_99_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English randomly_pruned_99_model DistilBertForSequenceClassification from andygoh5
+author: John Snow Labs
+name: randomly_pruned_99_model
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`randomly_pruned_99_model` is a English model originally trained by andygoh5.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/randomly_pruned_99_model_en_5.5.1_3.0_1738078008873.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/randomly_pruned_99_model_en_5.5.1_3.0_1738078008873.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("randomly_pruned_99_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("randomly_pruned_99_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|randomly_pruned_99_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/andygoh5/randomly-pruned-99-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-randomly_pruned_99_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-randomly_pruned_99_model_pipeline_en.md
new file mode 100644
index 00000000000000..e02f561d69c13e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-randomly_pruned_99_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English randomly_pruned_99_model_pipeline pipeline DistilBertForSequenceClassification from andygoh5
+author: John Snow Labs
+name: randomly_pruned_99_model_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`randomly_pruned_99_model_pipeline` is a English model originally trained by andygoh5.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/randomly_pruned_99_model_pipeline_en_5.5.1_3.0_1738078021590.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/randomly_pruned_99_model_pipeline_en_5.5.1_3.0_1738078021590.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("randomly_pruned_99_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("randomly_pruned_99_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|randomly_pruned_99_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/andygoh5/randomly-pruned-99-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-rare_puppers_khalilou_en.md b/docs/_posts/ahmedlone127/2025-01-28-rare_puppers_khalilou_en.md
new file mode 100644
index 00000000000000..88ddd2f471a547
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-rare_puppers_khalilou_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English rare_puppers_khalilou ViTForImageClassification from khalilou
+author: John Snow Labs
+name: rare_puppers_khalilou
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rare_puppers_khalilou` is a English model originally trained by khalilou.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rare_puppers_khalilou_en_5.5.1_3.0_1738022856130.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rare_puppers_khalilou_en_5.5.1_3.0_1738022856130.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""rare_puppers_khalilou","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("rare_puppers_khalilou","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rare_puppers_khalilou|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/khalilou/rare-puppers
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-rare_puppers_khalilou_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-rare_puppers_khalilou_pipeline_en.md
new file mode 100644
index 00000000000000..aa65970e39bf15
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-rare_puppers_khalilou_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English rare_puppers_khalilou_pipeline pipeline ViTForImageClassification from khalilou
+author: John Snow Labs
+name: rare_puppers_khalilou_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rare_puppers_khalilou_pipeline` is a English model originally trained by khalilou.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rare_puppers_khalilou_pipeline_en_5.5.1_3.0_1738022872801.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rare_puppers_khalilou_pipeline_en_5.5.1_3.0_1738022872801.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("rare_puppers_khalilou_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("rare_puppers_khalilou_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rare_puppers_khalilou_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/khalilou/rare-puppers
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-rare_puppers_zairae_en.md b/docs/_posts/ahmedlone127/2025-01-28-rare_puppers_zairae_en.md
new file mode 100644
index 00000000000000..6a0d12926ca762
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-rare_puppers_zairae_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English rare_puppers_zairae ViTForImageClassification from ZairaE
+author: John Snow Labs
+name: rare_puppers_zairae
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rare_puppers_zairae` is a English model originally trained by ZairaE.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rare_puppers_zairae_en_5.5.1_3.0_1738023048531.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rare_puppers_zairae_en_5.5.1_3.0_1738023048531.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""rare_puppers_zairae","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("rare_puppers_zairae","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rare_puppers_zairae|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/ZairaE/rare-puppers
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-rare_puppers_zairae_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-rare_puppers_zairae_pipeline_en.md
new file mode 100644
index 00000000000000..74485e00abf241
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-rare_puppers_zairae_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English rare_puppers_zairae_pipeline pipeline ViTForImageClassification from ZairaE
+author: John Snow Labs
+name: rare_puppers_zairae_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rare_puppers_zairae_pipeline` is a English model originally trained by ZairaE.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rare_puppers_zairae_pipeline_en_5.5.1_3.0_1738023066597.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rare_puppers_zairae_pipeline_en_5.5.1_3.0_1738023066597.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("rare_puppers_zairae_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("rare_puppers_zairae_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rare_puppers_zairae_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/ZairaE/rare-puppers
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-results_dadrshan_en.md b/docs/_posts/ahmedlone127/2025-01-28-results_dadrshan_en.md
new file mode 100644
index 00000000000000..ccb9cf2e947539
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-results_dadrshan_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English results_dadrshan T5Transformer from dadrshan
+author: John Snow Labs
+name: results_dadrshan
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_dadrshan` is a English model originally trained by dadrshan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_dadrshan_en_5.5.1_3.0_1738030426417.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_dadrshan_en_5.5.1_3.0_1738030426417.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("results_dadrshan","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("results_dadrshan", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_dadrshan|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|287.4 MB|
+
+## References
+
+https://huggingface.co/dadrshan/results
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-results_dadrshan_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-results_dadrshan_pipeline_en.md
new file mode 100644
index 00000000000000..e2d968854214b8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-results_dadrshan_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English results_dadrshan_pipeline pipeline T5Transformer from dadrshan
+author: John Snow Labs
+name: results_dadrshan_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_dadrshan_pipeline` is a English model originally trained by dadrshan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_dadrshan_pipeline_en_5.5.1_3.0_1738030447878.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_dadrshan_pipeline_en_5.5.1_3.0_1738030447878.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("results_dadrshan_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("results_dadrshan_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_dadrshan_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|287.4 MB|
+
+## References
+
+https://huggingface.co/dadrshan/results
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-results_muratsimsek003_en.md b/docs/_posts/ahmedlone127/2025-01-28-results_muratsimsek003_en.md
new file mode 100644
index 00000000000000..c5a4b14e667275
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-results_muratsimsek003_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English results_muratsimsek003 T5Transformer from muratsimsek003
+author: John Snow Labs
+name: results_muratsimsek003
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_muratsimsek003` is a English model originally trained by muratsimsek003.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_muratsimsek003_en_5.5.1_3.0_1738072983150.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_muratsimsek003_en_5.5.1_3.0_1738072983150.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("results_muratsimsek003","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("results_muratsimsek003", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_muratsimsek003|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/muratsimsek003/results
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-results_muratsimsek003_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-results_muratsimsek003_pipeline_en.md
new file mode 100644
index 00000000000000..fd0c314d04f83d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-results_muratsimsek003_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English results_muratsimsek003_pipeline pipeline T5Transformer from muratsimsek003
+author: John Snow Labs
+name: results_muratsimsek003_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_muratsimsek003_pipeline` is a English model originally trained by muratsimsek003.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_muratsimsek003_pipeline_en_5.5.1_3.0_1738073032941.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_muratsimsek003_pipeline_en_5.5.1_3.0_1738073032941.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("results_muratsimsek003_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("results_muratsimsek003_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_muratsimsek003_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/muratsimsek003/results
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-road_conditions_en.md b/docs/_posts/ahmedlone127/2025-01-28-road_conditions_en.md
new file mode 100644
index 00000000000000..8670a169b123bc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-road_conditions_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English road_conditions ViTForImageClassification from SaketR1
+author: John Snow Labs
+name: road_conditions
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`road_conditions` is a English model originally trained by SaketR1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/road_conditions_en_5.5.1_3.0_1738023324298.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/road_conditions_en_5.5.1_3.0_1738023324298.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""road_conditions","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("road_conditions","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|road_conditions|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/SaketR1/road-conditions
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-road_conditions_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-road_conditions_pipeline_en.md
new file mode 100644
index 00000000000000..5759a6c06140b8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-road_conditions_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English road_conditions_pipeline pipeline ViTForImageClassification from SaketR1
+author: John Snow Labs
+name: road_conditions_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`road_conditions_pipeline` is a English model originally trained by SaketR1.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/road_conditions_pipeline_en_5.5.1_3.0_1738023341184.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/road_conditions_pipeline_en_5.5.1_3.0_1738023341184.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("road_conditions_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("road_conditions_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|road_conditions_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/SaketR1/road-conditions
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-roberta_biobert1_en.md b/docs/_posts/ahmedlone127/2025-01-28-roberta_biobert1_en.md
new file mode 100644
index 00000000000000..f3d7229e3b2533
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-roberta_biobert1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_biobert1 XlmRoBertaForTokenClassification from stivenacua17
+author: John Snow Labs
+name: roberta_biobert1
+date: 2025-01-28
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_biobert1` is a English model originally trained by stivenacua17.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_biobert1_en_5.5.1_3.0_1738065222979.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_biobert1_en_5.5.1_3.0_1738065222979.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("roberta_biobert1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("roberta_biobert1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_biobert1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.5 MB|
+
+## References
+
+https://huggingface.co/stivenacua17/roberta-biobert1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-roberta_biobert1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-roberta_biobert1_pipeline_en.md
new file mode 100644
index 00000000000000..ad4b3673e7ddfd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-roberta_biobert1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_biobert1_pipeline pipeline XlmRoBertaForTokenClassification from stivenacua17
+author: John Snow Labs
+name: roberta_biobert1_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_biobert1_pipeline` is a English model originally trained by stivenacua17.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_biobert1_pipeline_en_5.5.1_3.0_1738065294533.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_biobert1_pipeline_en_5.5.1_3.0_1738065294533.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_biobert1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_biobert1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_biobert1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.5 MB|
+
+## References
+
+https://huggingface.co/stivenacua17/roberta-biobert1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-roberta_news_en.md b/docs/_posts/ahmedlone127/2025-01-28-roberta_news_en.md
new file mode 100644
index 00000000000000..be93021a66fd59
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-roberta_news_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_news RoBertaEmbeddings from AndyReas
+author: John Snow Labs
+name: roberta_news
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_news` is a English model originally trained by AndyReas.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_news_en_5.5.1_3.0_1738103004944.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_news_en_5.5.1_3.0_1738103004944.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("roberta_news","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("roberta_news","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_news|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|460.0 MB|
+
+## References
+
+https://huggingface.co/AndyReas/roberta-news
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-roberta_news_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-roberta_news_pipeline_en.md
new file mode 100644
index 00000000000000..98916d90d17c42
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-roberta_news_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_news_pipeline pipeline RoBertaEmbeddings from AndyReas
+author: John Snow Labs
+name: roberta_news_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_news_pipeline` is a English model originally trained by AndyReas.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_news_pipeline_en_5.5.1_3.0_1738103036124.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_news_pipeline_en_5.5.1_3.0_1738103036124.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_news_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_news_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_news_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|460.0 MB|
+
+## References
+
+https://huggingface.co/AndyReas/roberta-news
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-robust_agnews_en.md b/docs/_posts/ahmedlone127/2025-01-28-robust_agnews_en.md
new file mode 100644
index 00000000000000..742856b1359d5e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-robust_agnews_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English robust_agnews BertForSequenceClassification from JungleLee
+author: John Snow Labs
+name: robust_agnews
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`robust_agnews` is a English model originally trained by JungleLee.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/robust_agnews_en_5.5.1_3.0_1738058989820.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/robust_agnews_en_5.5.1_3.0_1738058989820.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("robust_agnews","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("robust_agnews", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|robust_agnews|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/JungleLee/robust-agnews
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-robust_agnews_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-robust_agnews_pipeline_en.md
new file mode 100644
index 00000000000000..4f28d586b0b365
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-robust_agnews_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English robust_agnews_pipeline pipeline BertForSequenceClassification from JungleLee
+author: John Snow Labs
+name: robust_agnews_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`robust_agnews_pipeline` is a English model originally trained by JungleLee.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/robust_agnews_pipeline_en_5.5.1_3.0_1738059010169.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/robust_agnews_pipeline_en_5.5.1_3.0_1738059010169.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("robust_agnews_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("robust_agnews_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|robust_agnews_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/JungleLee/robust-agnews
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-rubert_russian_qa_sberquad_pipeline_ru.md b/docs/_posts/ahmedlone127/2025-01-28-rubert_russian_qa_sberquad_pipeline_ru.md
new file mode 100644
index 00000000000000..f5866093a1ff31
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-rubert_russian_qa_sberquad_pipeline_ru.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Russian rubert_russian_qa_sberquad_pipeline pipeline BertForQuestionAnswering from milyausha2801
+author: John Snow Labs
+name: rubert_russian_qa_sberquad_pipeline
+date: 2025-01-28
+tags: [ru, open_source, pipeline, onnx]
+task: Question Answering
+language: ru
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_russian_qa_sberquad_pipeline` is a Russian model originally trained by milyausha2801.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_russian_qa_sberquad_pipeline_ru_5.5.1_3.0_1738062076380.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_russian_qa_sberquad_pipeline_ru_5.5.1_3.0_1738062076380.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("rubert_russian_qa_sberquad_pipeline", lang = "ru")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("rubert_russian_qa_sberquad_pipeline", lang = "ru")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rubert_russian_qa_sberquad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ru|
+|Size:|664.3 MB|
+
+## References
+
+References
+
+https://huggingface.co/milyausha2801/rubert-russian-qa-sberquad
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-rubert_russian_qa_sberquad_ru.md b/docs/_posts/ahmedlone127/2025-01-28-rubert_russian_qa_sberquad_ru.md
new file mode 100644
index 00000000000000..61d832915dae73
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-rubert_russian_qa_sberquad_ru.md
@@ -0,0 +1,88 @@
+---
+layout: model
+title: Russian rubert_russian_qa_sberquad BertForQuestionAnswering from milyausha2801
+author: John Snow Labs
+name: rubert_russian_qa_sberquad
+date: 2025-01-28
+tags: [ru, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: ru
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_russian_qa_sberquad` is a Russian model originally trained by milyausha2801.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_russian_qa_sberquad_ru_5.5.1_3.0_1738062042888.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_russian_qa_sberquad_ru_5.5.1_3.0_1738062042888.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("rubert_russian_qa_sberquad","ru") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("rubert_russian_qa_sberquad", "ru")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rubert_russian_qa_sberquad|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|ru|
+|Size:|664.3 MB|
+
+## References
+
+References
+
+https://huggingface.co/milyausha2801/rubert-russian-qa-sberquad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-rubert_tiny2_odonata_extended_ner_en.md b/docs/_posts/ahmedlone127/2025-01-28-rubert_tiny2_odonata_extended_ner_en.md
new file mode 100644
index 00000000000000..20bd09170fe579
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-rubert_tiny2_odonata_extended_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English rubert_tiny2_odonata_extended_ner BertForTokenClassification from Ilya-Nazimov
+author: John Snow Labs
+name: rubert_tiny2_odonata_extended_ner
+date: 2025-01-28
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_tiny2_odonata_extended_ner` is a English model originally trained by Ilya-Nazimov.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_tiny2_odonata_extended_ner_en_5.5.1_3.0_1738045160698.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_tiny2_odonata_extended_ner_en_5.5.1_3.0_1738045160698.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("rubert_tiny2_odonata_extended_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("rubert_tiny2_odonata_extended_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rubert_tiny2_odonata_extended_ner|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|109.1 MB|
+
+## References
+
+https://huggingface.co/Ilya-Nazimov/rubert-tiny2-odonata-extended-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-rubert_tiny2_odonata_extended_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-rubert_tiny2_odonata_extended_ner_pipeline_en.md
new file mode 100644
index 00000000000000..7e687bf4e4fda3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-rubert_tiny2_odonata_extended_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English rubert_tiny2_odonata_extended_ner_pipeline pipeline BertForTokenClassification from Ilya-Nazimov
+author: John Snow Labs
+name: rubert_tiny2_odonata_extended_ner_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_tiny2_odonata_extended_ner_pipeline` is a English model originally trained by Ilya-Nazimov.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_tiny2_odonata_extended_ner_pipeline_en_5.5.1_3.0_1738045165948.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_tiny2_odonata_extended_ner_pipeline_en_5.5.1_3.0_1738045165948.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("rubert_tiny2_odonata_extended_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("rubert_tiny2_odonata_extended_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rubert_tiny2_odonata_extended_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|109.2 MB|
+
+## References
+
+https://huggingface.co/Ilya-Nazimov/rubert-tiny2-odonata-extended-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-rwbk_sentiment_en.md b/docs/_posts/ahmedlone127/2025-01-28-rwbk_sentiment_en.md
new file mode 100644
index 00000000000000..1b7d8f7ead7dff
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-rwbk_sentiment_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English rwbk_sentiment BertForSequenceClassification from vinh120203
+author: John Snow Labs
+name: rwbk_sentiment
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rwbk_sentiment` is a English model originally trained by vinh120203.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rwbk_sentiment_en_5.5.1_3.0_1738028261738.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rwbk_sentiment_en_5.5.1_3.0_1738028261738.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("rwbk_sentiment","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("rwbk_sentiment", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rwbk_sentiment|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/vinh120203/rwBK-sentiment
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-rwbk_sentiment_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-rwbk_sentiment_pipeline_en.md
new file mode 100644
index 00000000000000..965f96a369f340
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-rwbk_sentiment_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English rwbk_sentiment_pipeline pipeline BertForSequenceClassification from vinh120203
+author: John Snow Labs
+name: rwbk_sentiment_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rwbk_sentiment_pipeline` is a English model originally trained by vinh120203.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rwbk_sentiment_pipeline_en_5.5.1_3.0_1738028281917.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rwbk_sentiment_pipeline_en_5.5.1_3.0_1738028281917.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("rwbk_sentiment_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("rwbk_sentiment_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rwbk_sentiment_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/vinh120203/rwBK-sentiment
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-s19_en.md b/docs/_posts/ahmedlone127/2025-01-28-s19_en.md
new file mode 100644
index 00000000000000..7dbed388086cf2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-s19_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English s19 BertForQuestionAnswering from ShynBui
+author: John Snow Labs
+name: s19
+date: 2025-01-28
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`s19` is a English model originally trained by ShynBui.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/s19_en_5.5.1_3.0_1738062661215.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/s19_en_5.5.1_3.0_1738062661215.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("s19","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("s19", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|s19|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|915.5 KB|
+
+## References
+
+https://huggingface.co/ShynBui/s19
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-s19_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-s19_pipeline_en.md
new file mode 100644
index 00000000000000..540b79af4a8eb7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-s19_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English s19_pipeline pipeline BertForQuestionAnswering from ShynBui
+author: John Snow Labs
+name: s19_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`s19_pipeline` is a English model originally trained by ShynBui.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/s19_pipeline_en_5.5.1_3.0_1738062662934.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/s19_pipeline_en_5.5.1_3.0_1738062662934.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("s19_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("s19_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|s19_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|922.0 KB|
+
+## References
+
+https://huggingface.co/ShynBui/s19
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sample_finetuned_model_en.md b/docs/_posts/ahmedlone127/2025-01-28-sample_finetuned_model_en.md
new file mode 100644
index 00000000000000..fc0346ac53a946
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sample_finetuned_model_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English sample_finetuned_model T5Transformer from yam3333
+author: John Snow Labs
+name: sample_finetuned_model
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sample_finetuned_model` is a English model originally trained by yam3333.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sample_finetuned_model_en_5.5.1_3.0_1738094341637.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sample_finetuned_model_en_5.5.1_3.0_1738094341637.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("sample_finetuned_model","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("sample_finetuned_model", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sample_finetuned_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|165.0 MB|
+
+## References
+
+https://huggingface.co/yam3333/sample_finetuned_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sample_finetuned_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-sample_finetuned_model_pipeline_en.md
new file mode 100644
index 00000000000000..e782c23b844646
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sample_finetuned_model_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English sample_finetuned_model_pipeline pipeline T5Transformer from yam3333
+author: John Snow Labs
+name: sample_finetuned_model_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sample_finetuned_model_pipeline` is a English model originally trained by yam3333.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sample_finetuned_model_pipeline_en_5.5.1_3.0_1738094384088.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sample_finetuned_model_pipeline_en_5.5.1_3.0_1738094384088.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sample_finetuned_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sample_finetuned_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sample_finetuned_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|165.0 MB|
+
+## References
+
+https://huggingface.co/yam3333/sample_finetuned_model
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-scenario_context_en.md b/docs/_posts/ahmedlone127/2025-01-28-scenario_context_en.md
new file mode 100644
index 00000000000000..53c8ea0ace94c1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-scenario_context_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English scenario_context T5Transformer from enoriega
+author: John Snow Labs
+name: scenario_context
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scenario_context` is a English model originally trained by enoriega.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/scenario_context_en_5.5.1_3.0_1738091644645.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scenario_context_en_5.5.1_3.0_1738091644645.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("scenario_context","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("scenario_context", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|scenario_context|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|887.1 MB|
+
+## References
+
+https://huggingface.co/enoriega/scenario_context
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-scenario_context_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-scenario_context_pipeline_en.md
new file mode 100644
index 00000000000000..2d66eae6658024
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-scenario_context_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English scenario_context_pipeline pipeline T5Transformer from enoriega
+author: John Snow Labs
+name: scenario_context_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scenario_context_pipeline` is a English model originally trained by enoriega.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/scenario_context_pipeline_en_5.5.1_3.0_1738091691746.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scenario_context_pipeline_en_5.5.1_3.0_1738091691746.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("scenario_context_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("scenario_context_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|scenario_context_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|887.1 MB|
+
+## References
+
+https://huggingface.co/enoriega/scenario_context
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-scrolls7_en.md b/docs/_posts/ahmedlone127/2025-01-28-scrolls7_en.md
new file mode 100644
index 00000000000000..8fe2e735cf4715
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-scrolls7_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English scrolls7 T5Transformer from yal27
+author: John Snow Labs
+name: scrolls7
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scrolls7` is a English model originally trained by yal27.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/scrolls7_en_5.5.1_3.0_1738030429653.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scrolls7_en_5.5.1_3.0_1738030429653.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("scrolls7","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("scrolls7", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|scrolls7|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|272.0 MB|
+
+## References
+
+https://huggingface.co/yal27/scrolls7
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-scrolls7_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-scrolls7_pipeline_en.md
new file mode 100644
index 00000000000000..ea142b38ed2fbb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-scrolls7_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English scrolls7_pipeline pipeline T5Transformer from yal27
+author: John Snow Labs
+name: scrolls7_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scrolls7_pipeline` is a English model originally trained by yal27.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/scrolls7_pipeline_en_5.5.1_3.0_1738030449094.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scrolls7_pipeline_en_5.5.1_3.0_1738030449094.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("scrolls7_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("scrolls7_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|scrolls7_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|272.0 MB|
+
+## References
+
+https://huggingface.co/yal27/scrolls7
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_20k_token_model_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_20k_token_model_en.md
new file mode 100644
index 00000000000000..84ecae1db77a56
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_20k_token_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_20k_token_model BertSentenceEmbeddings from kumarme072
+author: John Snow Labs
+name: sent_20k_token_model
+date: 2025-01-28
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_20k_token_model` is a English model originally trained by kumarme072.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_20k_token_model_en_5.5.1_3.0_1738049424955.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_20k_token_model_en_5.5.1_3.0_1738049424955.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_20k_token_model","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_20k_token_model","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_20k_token_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|409.8 MB|
+
+## References
+
+https://huggingface.co/kumarme072/20k_token_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_20k_token_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_20k_token_model_pipeline_en.md
new file mode 100644
index 00000000000000..95b1b9301603a1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_20k_token_model_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_20k_token_model_pipeline pipeline BertSentenceEmbeddings from kumarme072
+author: John Snow Labs
+name: sent_20k_token_model_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_20k_token_model_pipeline` is a English model originally trained by kumarme072.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_20k_token_model_pipeline_en_5.5.1_3.0_1738049445547.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_20k_token_model_pipeline_en_5.5.1_3.0_1738049445547.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_20k_token_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_20k_token_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_20k_token_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.4 MB|
+
+## References
+
+https://huggingface.co/kumarme072/20k_token_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_all_minilm_l6_v2_personal_project_default_2024_06_17_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_all_minilm_l6_v2_personal_project_default_2024_06_17_en.md
new file mode 100644
index 00000000000000..79b393f2ba7e3b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_all_minilm_l6_v2_personal_project_default_2024_06_17_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_all_minilm_l6_v2_personal_project_default_2024_06_17 BertSentenceEmbeddings from brugmark
+author: John Snow Labs
+name: sent_all_minilm_l6_v2_personal_project_default_2024_06_17
+date: 2025-01-28
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_all_minilm_l6_v2_personal_project_default_2024_06_17` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_default_2024_06_17_en_5.5.1_3.0_1738047853281.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_default_2024_06_17_en_5.5.1_3.0_1738047853281.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_all_minilm_l6_v2_personal_project_default_2024_06_17","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_all_minilm_l6_v2_personal_project_default_2024_06_17","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_all_minilm_l6_v2_personal_project_default_2024_06_17|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|83.9 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-default-2024-06-17
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_all_minilm_l6_v2_personal_project_default_2024_06_17_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_all_minilm_l6_v2_personal_project_default_2024_06_17_pipeline_en.md
new file mode 100644
index 00000000000000..15ad54fdc0cf55
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_all_minilm_l6_v2_personal_project_default_2024_06_17_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_all_minilm_l6_v2_personal_project_default_2024_06_17_pipeline pipeline BertSentenceEmbeddings from brugmark
+author: John Snow Labs
+name: sent_all_minilm_l6_v2_personal_project_default_2024_06_17_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_all_minilm_l6_v2_personal_project_default_2024_06_17_pipeline` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_default_2024_06_17_pipeline_en_5.5.1_3.0_1738047857475.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_default_2024_06_17_pipeline_en_5.5.1_3.0_1738047857475.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_all_minilm_l6_v2_personal_project_default_2024_06_17_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_all_minilm_l6_v2_personal_project_default_2024_06_17_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_all_minilm_l6_v2_personal_project_default_2024_06_17_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|84.5 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-default-2024-06-17
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_antismetisim1_finetuned_mlm_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_antismetisim1_finetuned_mlm_en.md
new file mode 100644
index 00000000000000..f7399595c5d576
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_antismetisim1_finetuned_mlm_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_antismetisim1_finetuned_mlm BertSentenceEmbeddings from Dhanush66
+author: John Snow Labs
+name: sent_antismetisim1_finetuned_mlm
+date: 2025-01-28
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_antismetisim1_finetuned_mlm` is a English model originally trained by Dhanush66.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_antismetisim1_finetuned_mlm_en_5.5.1_3.0_1738048758200.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_antismetisim1_finetuned_mlm_en_5.5.1_3.0_1738048758200.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_antismetisim1_finetuned_mlm","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_antismetisim1_finetuned_mlm","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_antismetisim1_finetuned_mlm|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/Dhanush66/Antismetisim1-finetuned-MLM
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_antismetisim1_finetuned_mlm_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_antismetisim1_finetuned_mlm_pipeline_en.md
new file mode 100644
index 00000000000000..5339487181868b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_antismetisim1_finetuned_mlm_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_antismetisim1_finetuned_mlm_pipeline pipeline BertSentenceEmbeddings from Dhanush66
+author: John Snow Labs
+name: sent_antismetisim1_finetuned_mlm_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_antismetisim1_finetuned_mlm_pipeline` is a English model originally trained by Dhanush66.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_antismetisim1_finetuned_mlm_pipeline_en_5.5.1_3.0_1738048791741.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_antismetisim1_finetuned_mlm_pipeline_en_5.5.1_3.0_1738048791741.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_antismetisim1_finetuned_mlm_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_antismetisim1_finetuned_mlm_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_antismetisim1_finetuned_mlm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.7 MB|
+
+## References
+
+https://huggingface.co/Dhanush66/Antismetisim1-finetuned-MLM
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_arabert_dialect_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_arabert_dialect_en.md
new file mode 100644
index 00000000000000..fced3ce60f3ef2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_arabert_dialect_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_arabert_dialect BertSentenceEmbeddings from HossamElsafty
+author: John Snow Labs
+name: sent_arabert_dialect
+date: 2025-01-28
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_arabert_dialect` is a English model originally trained by HossamElsafty.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_arabert_dialect_en_5.5.1_3.0_1738049055575.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_arabert_dialect_en_5.5.1_3.0_1738049055575.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_arabert_dialect","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_arabert_dialect","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_arabert_dialect|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|604.6 MB|
+
+## References
+
+https://huggingface.co/HossamElsafty/AraBERT_Dialect
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_arabert_dialect_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_arabert_dialect_pipeline_en.md
new file mode 100644
index 00000000000000..e4fd32439da823
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_arabert_dialect_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_arabert_dialect_pipeline pipeline BertSentenceEmbeddings from HossamElsafty
+author: John Snow Labs
+name: sent_arabert_dialect_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_arabert_dialect_pipeline` is a English model originally trained by HossamElsafty.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_arabert_dialect_pipeline_en_5.5.1_3.0_1738049086282.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_arabert_dialect_pipeline_en_5.5.1_3.0_1738049086282.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_arabert_dialect_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_arabert_dialect_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_arabert_dialect_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|605.1 MB|
+
+## References
+
+https://huggingface.co/HossamElsafty/AraBERT_Dialect
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_bert_adaptation_martin_fierro_dbarsotti_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_adaptation_martin_fierro_dbarsotti_en.md
new file mode 100644
index 00000000000000..519ddc0c20012f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_adaptation_martin_fierro_dbarsotti_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_adaptation_martin_fierro_dbarsotti BertSentenceEmbeddings from dbarsotti
+author: John Snow Labs
+name: sent_bert_adaptation_martin_fierro_dbarsotti
+date: 2025-01-28
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_adaptation_martin_fierro_dbarsotti` is a English model originally trained by dbarsotti.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_martin_fierro_dbarsotti_en_5.5.1_3.0_1738048879807.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_martin_fierro_dbarsotti_en_5.5.1_3.0_1738048879807.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_adaptation_martin_fierro_dbarsotti","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_adaptation_martin_fierro_dbarsotti","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_adaptation_martin_fierro_dbarsotti|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/dbarsotti/bert_adaptation_martin_fierro
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_bert_adaptation_martin_fierro_dbarsotti_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_adaptation_martin_fierro_dbarsotti_pipeline_en.md
new file mode 100644
index 00000000000000..03a1a33ad226ac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_adaptation_martin_fierro_dbarsotti_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_adaptation_martin_fierro_dbarsotti_pipeline pipeline BertSentenceEmbeddings from dbarsotti
+author: John Snow Labs
+name: sent_bert_adaptation_martin_fierro_dbarsotti_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_adaptation_martin_fierro_dbarsotti_pipeline` is a English model originally trained by dbarsotti.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_martin_fierro_dbarsotti_pipeline_en_5.5.1_3.0_1738048900545.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_adaptation_martin_fierro_dbarsotti_pipeline_en_5.5.1_3.0_1738048900545.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_adaptation_martin_fierro_dbarsotti_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_adaptation_martin_fierro_dbarsotti_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_adaptation_martin_fierro_dbarsotti_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.2 MB|
+
+## References
+
+https://huggingface.co/dbarsotti/bert_adaptation_martin_fierro
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_bert_after_pcgu_finetuned_imdb_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_after_pcgu_finetuned_imdb_en.md
new file mode 100644
index 00000000000000..73c7758a725155
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_after_pcgu_finetuned_imdb_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_after_pcgu_finetuned_imdb BertSentenceEmbeddings from cmzheng
+author: John Snow Labs
+name: sent_bert_after_pcgu_finetuned_imdb
+date: 2025-01-28
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_after_pcgu_finetuned_imdb` is a English model originally trained by cmzheng.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_after_pcgu_finetuned_imdb_en_5.5.1_3.0_1738048958257.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_after_pcgu_finetuned_imdb_en_5.5.1_3.0_1738048958257.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_after_pcgu_finetuned_imdb","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_after_pcgu_finetuned_imdb","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_after_pcgu_finetuned_imdb|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/cmzheng/bert_after_PCGU-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_bert_after_pcgu_finetuned_imdb_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_after_pcgu_finetuned_imdb_pipeline_en.md
new file mode 100644
index 00000000000000..9b492a1750bae1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_after_pcgu_finetuned_imdb_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_after_pcgu_finetuned_imdb_pipeline pipeline BertSentenceEmbeddings from cmzheng
+author: John Snow Labs
+name: sent_bert_after_pcgu_finetuned_imdb_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_after_pcgu_finetuned_imdb_pipeline` is a English model originally trained by cmzheng.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_after_pcgu_finetuned_imdb_pipeline_en_5.5.1_3.0_1738048980391.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_after_pcgu_finetuned_imdb_pipeline_en_5.5.1_3.0_1738048980391.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_after_pcgu_finetuned_imdb_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_after_pcgu_finetuned_imdb_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_after_pcgu_finetuned_imdb_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.7 MB|
+
+## References
+
+https://huggingface.co/cmzheng/bert_after_PCGU-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_bert_base_german_cased_domain_adaptation_accelerate_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_base_german_cased_domain_adaptation_accelerate_en.md
new file mode 100644
index 00000000000000..9f88d4dc70bbdd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_base_german_cased_domain_adaptation_accelerate_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_base_german_cased_domain_adaptation_accelerate BertSentenceEmbeddings from rodrigotuna
+author: John Snow Labs
+name: sent_bert_base_german_cased_domain_adaptation_accelerate
+date: 2025-01-28
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_german_cased_domain_adaptation_accelerate` is a English model originally trained by rodrigotuna.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_german_cased_domain_adaptation_accelerate_en_5.5.1_3.0_1738048788434.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_german_cased_domain_adaptation_accelerate_en_5.5.1_3.0_1738048788434.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_german_cased_domain_adaptation_accelerate","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_german_cased_domain_adaptation_accelerate","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_german_cased_domain_adaptation_accelerate|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/rodrigotuna/bert-base-german-cased-domain-adaptation-accelerate
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_bert_base_german_cased_domain_adaptation_accelerate_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_base_german_cased_domain_adaptation_accelerate_pipeline_en.md
new file mode 100644
index 00000000000000..febfedda4eed93
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_base_german_cased_domain_adaptation_accelerate_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_base_german_cased_domain_adaptation_accelerate_pipeline pipeline BertSentenceEmbeddings from rodrigotuna
+author: John Snow Labs
+name: sent_bert_base_german_cased_domain_adaptation_accelerate_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_german_cased_domain_adaptation_accelerate_pipeline` is a English model originally trained by rodrigotuna.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_german_cased_domain_adaptation_accelerate_pipeline_en_5.5.1_3.0_1738048808590.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_german_cased_domain_adaptation_accelerate_pipeline_en_5.5.1_3.0_1738048808590.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_base_german_cased_domain_adaptation_accelerate_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_german_cased_domain_adaptation_accelerate_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_german_cased_domain_adaptation_accelerate_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.4 MB|
+
+## References
+
+https://huggingface.co/rodrigotuna/bert-base-german-cased-domain-adaptation-accelerate
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_bert_base_uncased_finetuned_mlm_nef_20240320_test_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_base_uncased_finetuned_mlm_nef_20240320_test_en.md
new file mode 100644
index 00000000000000..952401ade3c412
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_base_uncased_finetuned_mlm_nef_20240320_test_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_base_uncased_finetuned_mlm_nef_20240320_test BertSentenceEmbeddings from JTh34
+author: John Snow Labs
+name: sent_bert_base_uncased_finetuned_mlm_nef_20240320_test
+date: 2025-01-28
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_uncased_finetuned_mlm_nef_20240320_test` is a English model originally trained by JTh34.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_finetuned_mlm_nef_20240320_test_en_5.5.1_3.0_1738048955904.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_finetuned_mlm_nef_20240320_test_en_5.5.1_3.0_1738048955904.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_uncased_finetuned_mlm_nef_20240320_test","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_uncased_finetuned_mlm_nef_20240320_test","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_uncased_finetuned_mlm_nef_20240320_test|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|417.5 MB|
+
+## References
+
+https://huggingface.co/JTh34/bert-base-uncased-finetuned-mlm-nef-20240320-test
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_bert_base_uncased_finetuned_mlm_nef_20240320_test_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_base_uncased_finetuned_mlm_nef_20240320_test_pipeline_en.md
new file mode 100644
index 00000000000000..d8e914386f29b0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_base_uncased_finetuned_mlm_nef_20240320_test_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_base_uncased_finetuned_mlm_nef_20240320_test_pipeline pipeline BertSentenceEmbeddings from JTh34
+author: John Snow Labs
+name: sent_bert_base_uncased_finetuned_mlm_nef_20240320_test_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_uncased_finetuned_mlm_nef_20240320_test_pipeline` is a English model originally trained by JTh34.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_finetuned_mlm_nef_20240320_test_pipeline_en_5.5.1_3.0_1738048978596.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_finetuned_mlm_nef_20240320_test_pipeline_en_5.5.1_3.0_1738048978596.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_base_uncased_finetuned_mlm_nef_20240320_test_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_uncased_finetuned_mlm_nef_20240320_test_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_uncased_finetuned_mlm_nef_20240320_test_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|418.0 MB|
+
+## References
+
+https://huggingface.co/JTh34/bert-base-uncased-finetuned-mlm-nef-20240320-test
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_bert_base_uncased_issues_128_pradeepiisc_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_base_uncased_issues_128_pradeepiisc_en.md
new file mode 100644
index 00000000000000..6671dd5c0936ab
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_base_uncased_issues_128_pradeepiisc_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_base_uncased_issues_128_pradeepiisc BertSentenceEmbeddings from pradeepiisc
+author: John Snow Labs
+name: sent_bert_base_uncased_issues_128_pradeepiisc
+date: 2025-01-28
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_uncased_issues_128_pradeepiisc` is a English model originally trained by pradeepiisc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_issues_128_pradeepiisc_en_5.5.1_3.0_1738048140331.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_issues_128_pradeepiisc_en_5.5.1_3.0_1738048140331.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_uncased_issues_128_pradeepiisc","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_uncased_issues_128_pradeepiisc","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_uncased_issues_128_pradeepiisc|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/pradeepiisc/bert-base-uncased-issues-128
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_bert_base_uncased_issues_128_pradeepiisc_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_base_uncased_issues_128_pradeepiisc_pipeline_en.md
new file mode 100644
index 00000000000000..b41421f3f36573
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_base_uncased_issues_128_pradeepiisc_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_base_uncased_issues_128_pradeepiisc_pipeline pipeline BertSentenceEmbeddings from pradeepiisc
+author: John Snow Labs
+name: sent_bert_base_uncased_issues_128_pradeepiisc_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_uncased_issues_128_pradeepiisc_pipeline` is a English model originally trained by pradeepiisc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_issues_128_pradeepiisc_pipeline_en_5.5.1_3.0_1738048160156.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_issues_128_pradeepiisc_pipeline_en_5.5.1_3.0_1738048160156.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_base_uncased_issues_128_pradeepiisc_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_uncased_issues_128_pradeepiisc_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_uncased_issues_128_pradeepiisc_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.7 MB|
+
+## References
+
+https://huggingface.co/pradeepiisc/bert-base-uncased-issues-128
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_bert_base_uncased_pal4_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_base_uncased_pal4_en.md
new file mode 100644
index 00000000000000..1d3d15f961087e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_base_uncased_pal4_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_base_uncased_pal4 BertSentenceEmbeddings from anthony-lemurian
+author: John Snow Labs
+name: sent_bert_base_uncased_pal4
+date: 2025-01-28
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_uncased_pal4` is a English model originally trained by anthony-lemurian.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_pal4_en_5.5.1_3.0_1738049336678.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_pal4_en_5.5.1_3.0_1738049336678.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_uncased_pal4","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_uncased_pal4","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_uncased_pal4|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|332.7 MB|
+
+## References
+
+https://huggingface.co/anthony-lemurian/bert-base-uncased-pal4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_bert_base_uncased_pal4_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_base_uncased_pal4_pipeline_en.md
new file mode 100644
index 00000000000000..37f8b7cc3ded8c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_base_uncased_pal4_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_base_uncased_pal4_pipeline pipeline BertSentenceEmbeddings from anthony-lemurian
+author: John Snow Labs
+name: sent_bert_base_uncased_pal4_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_uncased_pal4_pipeline` is a English model originally trained by anthony-lemurian.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_pal4_pipeline_en_5.5.1_3.0_1738049359242.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_pal4_pipeline_en_5.5.1_3.0_1738049359242.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_base_uncased_pal4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_uncased_pal4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_uncased_pal4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|333.2 MB|
+
+## References
+
+https://huggingface.co/anthony-lemurian/bert-base-uncased-pal4
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_bert_base_uncased_test_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_base_uncased_test_en.md
new file mode 100644
index 00000000000000..cb594ddfedf62a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_base_uncased_test_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_base_uncased_test BertSentenceEmbeddings from Contents
+author: John Snow Labs
+name: sent_bert_base_uncased_test
+date: 2025-01-28
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_uncased_test` is a English model originally trained by Contents.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_test_en_5.5.1_3.0_1738048744396.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_test_en_5.5.1_3.0_1738048744396.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_uncased_test","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_uncased_test","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_uncased_test|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/Contents/bert-base-uncased-test
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_bert_base_uncased_test_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_base_uncased_test_pipeline_en.md
new file mode 100644
index 00000000000000..2dbfb2d389e93c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_base_uncased_test_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_base_uncased_test_pipeline pipeline BertSentenceEmbeddings from Contents
+author: John Snow Labs
+name: sent_bert_base_uncased_test_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_uncased_test_pipeline` is a English model originally trained by Contents.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_test_pipeline_en_5.5.1_3.0_1738048765465.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_test_pipeline_en_5.5.1_3.0_1738048765465.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_base_uncased_test_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_uncased_test_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_uncased_test_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.7 MB|
+
+## References
+
+https://huggingface.co/Contents/bert-base-uncased-test
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_bert_clinical_scratch_wl_spanish_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_clinical_scratch_wl_spanish_en.md
new file mode 100644
index 00000000000000..2f3abb3d22cbe3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_clinical_scratch_wl_spanish_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_clinical_scratch_wl_spanish BertSentenceEmbeddings from plncmm
+author: John Snow Labs
+name: sent_bert_clinical_scratch_wl_spanish
+date: 2025-01-28
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_clinical_scratch_wl_spanish` is a English model originally trained by plncmm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_clinical_scratch_wl_spanish_en_5.5.1_3.0_1738047522214.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_clinical_scratch_wl_spanish_en_5.5.1_3.0_1738047522214.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_clinical_scratch_wl_spanish","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_clinical_scratch_wl_spanish","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_clinical_scratch_wl_spanish|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/plncmm/bert-clinical-scratch-wl-es
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_bert_clinical_scratch_wl_spanish_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_clinical_scratch_wl_spanish_pipeline_en.md
new file mode 100644
index 00000000000000..0bd4aaa38c42cb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_clinical_scratch_wl_spanish_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_clinical_scratch_wl_spanish_pipeline pipeline BertSentenceEmbeddings from plncmm
+author: John Snow Labs
+name: sent_bert_clinical_scratch_wl_spanish_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_clinical_scratch_wl_spanish_pipeline` is a English model originally trained by plncmm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_clinical_scratch_wl_spanish_pipeline_en_5.5.1_3.0_1738047543108.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_clinical_scratch_wl_spanish_pipeline_en_5.5.1_3.0_1738047543108.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_clinical_scratch_wl_spanish_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_clinical_scratch_wl_spanish_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_clinical_scratch_wl_spanish_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.0 MB|
+
+## References
+
+https://huggingface.co/plncmm/bert-clinical-scratch-wl-es
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_bert_english_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_english_en.md
new file mode 100644
index 00000000000000..a53e9e7b200ce6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_english_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_english BertSentenceEmbeddings from lzhang472
+author: John Snow Labs
+name: sent_bert_english
+date: 2025-01-28
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_english` is a English model originally trained by lzhang472.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_english_en_5.5.1_3.0_1738047692161.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_english_en_5.5.1_3.0_1738047692161.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_english","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_english","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_english|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|406.5 MB|
+
+## References
+
+https://huggingface.co/lzhang472/bert-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_bert_english_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_english_pipeline_en.md
new file mode 100644
index 00000000000000..bb6e9798e68969
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_english_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_english_pipeline pipeline BertSentenceEmbeddings from lzhang472
+author: John Snow Labs
+name: sent_bert_english_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_english_pipeline` is a English model originally trained by lzhang472.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_english_pipeline_en_5.5.1_3.0_1738047712889.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_english_pipeline_en_5.5.1_3.0_1738047712889.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_english_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_english_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_english_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.0 MB|
+
+## References
+
+https://huggingface.co/lzhang472/bert-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_bert_large_portuguese_cased_legal_mlm_pipeline_pt.md b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_large_portuguese_cased_legal_mlm_pipeline_pt.md
new file mode 100644
index 00000000000000..6d64b047aff911
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_large_portuguese_cased_legal_mlm_pipeline_pt.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Portuguese sent_bert_large_portuguese_cased_legal_mlm_pipeline pipeline BertSentenceEmbeddings from stjiris
+author: John Snow Labs
+name: sent_bert_large_portuguese_cased_legal_mlm_pipeline
+date: 2025-01-28
+tags: [pt, open_source, pipeline, onnx]
+task: Embeddings
+language: pt
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_large_portuguese_cased_legal_mlm_pipeline` is a Portuguese model originally trained by stjiris.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_large_portuguese_cased_legal_mlm_pipeline_pt_5.5.1_3.0_1738048751579.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_large_portuguese_cased_legal_mlm_pipeline_pt_5.5.1_3.0_1738048751579.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_large_portuguese_cased_legal_mlm_pipeline", lang = "pt")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_large_portuguese_cased_legal_mlm_pipeline", lang = "pt")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_large_portuguese_cased_legal_mlm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|pt|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/stjiris/bert-large-portuguese-cased-legal-mlm
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_bert_large_portuguese_cased_legal_mlm_pt.md b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_large_portuguese_cased_legal_mlm_pt.md
new file mode 100644
index 00000000000000..32162da4f7de23
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_large_portuguese_cased_legal_mlm_pt.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Portuguese sent_bert_large_portuguese_cased_legal_mlm BertSentenceEmbeddings from stjiris
+author: John Snow Labs
+name: sent_bert_large_portuguese_cased_legal_mlm
+date: 2025-01-28
+tags: [pt, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: pt
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_large_portuguese_cased_legal_mlm` is a Portuguese model originally trained by stjiris.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_large_portuguese_cased_legal_mlm_pt_5.5.1_3.0_1738048678541.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_large_portuguese_cased_legal_mlm_pt_5.5.1_3.0_1738048678541.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_large_portuguese_cased_legal_mlm","pt") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_large_portuguese_cased_legal_mlm","pt") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_large_portuguese_cased_legal_mlm|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|pt|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/stjiris/bert-large-portuguese-cased-legal-mlm
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_bert_pretrained_litcov200_paraphrased_all_shuffled_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_pretrained_litcov200_paraphrased_all_shuffled_en.md
new file mode 100644
index 00000000000000..c05c5e97e6b3ff
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_pretrained_litcov200_paraphrased_all_shuffled_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_pretrained_litcov200_paraphrased_all_shuffled BertSentenceEmbeddings from IneG
+author: John Snow Labs
+name: sent_bert_pretrained_litcov200_paraphrased_all_shuffled
+date: 2025-01-28
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_pretrained_litcov200_paraphrased_all_shuffled` is a English model originally trained by IneG.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_pretrained_litcov200_paraphrased_all_shuffled_en_5.5.1_3.0_1738049121749.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_pretrained_litcov200_paraphrased_all_shuffled_en_5.5.1_3.0_1738049121749.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_pretrained_litcov200_paraphrased_all_shuffled","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_pretrained_litcov200_paraphrased_all_shuffled","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_pretrained_litcov200_paraphrased_all_shuffled|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/IneG/BERT_pretrained_litcov200_paraphrased_all-shuffled
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_bert_pretrained_litcov200_paraphrased_all_shuffled_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_pretrained_litcov200_paraphrased_all_shuffled_pipeline_en.md
new file mode 100644
index 00000000000000..79b77246767c54
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_pretrained_litcov200_paraphrased_all_shuffled_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_pretrained_litcov200_paraphrased_all_shuffled_pipeline pipeline BertSentenceEmbeddings from IneG
+author: John Snow Labs
+name: sent_bert_pretrained_litcov200_paraphrased_all_shuffled_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_pretrained_litcov200_paraphrased_all_shuffled_pipeline` is a English model originally trained by IneG.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_pretrained_litcov200_paraphrased_all_shuffled_pipeline_en_5.5.1_3.0_1738049142656.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_pretrained_litcov200_paraphrased_all_shuffled_pipeline_en_5.5.1_3.0_1738049142656.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_pretrained_litcov200_paraphrased_all_shuffled_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_pretrained_litcov200_paraphrased_all_shuffled_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_pretrained_litcov200_paraphrased_all_shuffled_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.7 MB|
+
+## References
+
+https://huggingface.co/IneG/BERT_pretrained_litcov200_paraphrased_all-shuffled
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_bert_tiny_finetuned_nan_labels_nepal_bhasa_longer_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_tiny_finetuned_nan_labels_nepal_bhasa_longer_en.md
new file mode 100644
index 00000000000000..e075e8af4eb80b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_tiny_finetuned_nan_labels_nepal_bhasa_longer_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_tiny_finetuned_nan_labels_nepal_bhasa_longer BertSentenceEmbeddings from muhtasham
+author: John Snow Labs
+name: sent_bert_tiny_finetuned_nan_labels_nepal_bhasa_longer
+date: 2025-01-28
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_tiny_finetuned_nan_labels_nepal_bhasa_longer` is a English model originally trained by muhtasham.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_tiny_finetuned_nan_labels_nepal_bhasa_longer_en_5.5.1_3.0_1738048640206.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_tiny_finetuned_nan_labels_nepal_bhasa_longer_en_5.5.1_3.0_1738048640206.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_tiny_finetuned_nan_labels_nepal_bhasa_longer","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_tiny_finetuned_nan_labels_nepal_bhasa_longer","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_tiny_finetuned_nan_labels_nepal_bhasa_longer|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|16.7 MB|
+
+## References
+
+https://huggingface.co/muhtasham/bert-tiny-finetuned-nan-labels-new-longer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_bert_tiny_finetuned_nan_labels_nepal_bhasa_longer_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_tiny_finetuned_nan_labels_nepal_bhasa_longer_pipeline_en.md
new file mode 100644
index 00000000000000..539293d42e2873
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_tiny_finetuned_nan_labels_nepal_bhasa_longer_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_tiny_finetuned_nan_labels_nepal_bhasa_longer_pipeline pipeline BertSentenceEmbeddings from muhtasham
+author: John Snow Labs
+name: sent_bert_tiny_finetuned_nan_labels_nepal_bhasa_longer_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_tiny_finetuned_nan_labels_nepal_bhasa_longer_pipeline` is a English model originally trained by muhtasham.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_tiny_finetuned_nan_labels_nepal_bhasa_longer_pipeline_en_5.5.1_3.0_1738048641372.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_tiny_finetuned_nan_labels_nepal_bhasa_longer_pipeline_en_5.5.1_3.0_1738048641372.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_tiny_finetuned_nan_labels_nepal_bhasa_longer_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_tiny_finetuned_nan_labels_nepal_bhasa_longer_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_tiny_finetuned_nan_labels_nepal_bhasa_longer_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|17.2 MB|
+
+## References
+
+https://huggingface.co/muhtasham/bert-tiny-finetuned-nan-labels-new-longer
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_bert_uncased_tiny_2xthicc_multi_emails_hq_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_uncased_tiny_2xthicc_multi_emails_hq_en.md
new file mode 100644
index 00000000000000..3020f29e5c2e3f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_uncased_tiny_2xthicc_multi_emails_hq_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_uncased_tiny_2xthicc_multi_emails_hq BertSentenceEmbeddings from postbot
+author: John Snow Labs
+name: sent_bert_uncased_tiny_2xthicc_multi_emails_hq
+date: 2025-01-28
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_uncased_tiny_2xthicc_multi_emails_hq` is a English model originally trained by postbot.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_uncased_tiny_2xthicc_multi_emails_hq_en_5.5.1_3.0_1738049391919.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_uncased_tiny_2xthicc_multi_emails_hq_en_5.5.1_3.0_1738049391919.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_uncased_tiny_2xthicc_multi_emails_hq","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_uncased_tiny_2xthicc_multi_emails_hq","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_uncased_tiny_2xthicc_multi_emails_hq|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|18.1 MB|
+
+## References
+
+https://huggingface.co/postbot/bert_uncased_tiny_2xthicc-multi-emails-hq
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_bert_uncased_tiny_2xthicc_multi_emails_hq_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_uncased_tiny_2xthicc_multi_emails_hq_pipeline_en.md
new file mode 100644
index 00000000000000..f7ac950f319ebf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_bert_uncased_tiny_2xthicc_multi_emails_hq_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_uncased_tiny_2xthicc_multi_emails_hq_pipeline pipeline BertSentenceEmbeddings from postbot
+author: John Snow Labs
+name: sent_bert_uncased_tiny_2xthicc_multi_emails_hq_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_uncased_tiny_2xthicc_multi_emails_hq_pipeline` is a English model originally trained by postbot.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_uncased_tiny_2xthicc_multi_emails_hq_pipeline_en_5.5.1_3.0_1738049393117.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_uncased_tiny_2xthicc_multi_emails_hq_pipeline_en_5.5.1_3.0_1738049393117.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_uncased_tiny_2xthicc_multi_emails_hq_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_uncased_tiny_2xthicc_multi_emails_hq_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_uncased_tiny_2xthicc_multi_emails_hq_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|18.7 MB|
+
+## References
+
+https://huggingface.co/postbot/bert_uncased_tiny_2xthicc-multi-emails-hq
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_berttest_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_berttest_en.md
new file mode 100644
index 00000000000000..183206f6e75531
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_berttest_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_berttest BertSentenceEmbeddings from hiert
+author: John Snow Labs
+name: sent_berttest
+date: 2025-01-28
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_berttest` is a English model originally trained by hiert.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_berttest_en_5.5.1_3.0_1738049691036.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_berttest_en_5.5.1_3.0_1738049691036.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_berttest","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_berttest","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_berttest|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/hiert/berttest
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_berttest_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_berttest_pipeline_en.md
new file mode 100644
index 00000000000000..bb17837dc4f4b2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_berttest_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_berttest_pipeline pipeline BertSentenceEmbeddings from hiert
+author: John Snow Labs
+name: sent_berttest_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_berttest_pipeline` is a English model originally trained by hiert.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_berttest_pipeline_en_5.5.1_3.0_1738049723952.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_berttest_pipeline_en_5.5.1_3.0_1738049723952.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_berttest_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_berttest_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_berttest_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|665.6 MB|
+
+## References
+
+https://huggingface.co/hiert/berttest
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_burmesebert_my.md b/docs/_posts/ahmedlone127/2025-01-28-sent_burmesebert_my.md
new file mode 100644
index 00000000000000..7fe9b48e73deec
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_burmesebert_my.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Burmese sent_burmesebert BertSentenceEmbeddings from jojo-ai-mst
+author: John Snow Labs
+name: sent_burmesebert
+date: 2025-01-28
+tags: [my, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: my
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_burmesebert` is a Burmese model originally trained by jojo-ai-mst.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_burmesebert_my_5.5.1_3.0_1738049785726.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_burmesebert_my_5.5.1_3.0_1738049785726.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_burmesebert","my") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_burmesebert","my") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_burmesebert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|my|
+|Size:|1.4 GB|
+
+## References
+
+https://huggingface.co/jojo-ai-mst/BurmeseBert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_burmesebert_pipeline_my.md b/docs/_posts/ahmedlone127/2025-01-28-sent_burmesebert_pipeline_my.md
new file mode 100644
index 00000000000000..bee7c9e3e24e78
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_burmesebert_pipeline_my.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Burmese sent_burmesebert_pipeline pipeline BertSentenceEmbeddings from jojo-ai-mst
+author: John Snow Labs
+name: sent_burmesebert_pipeline
+date: 2025-01-28
+tags: [my, open_source, pipeline, onnx]
+task: Embeddings
+language: my
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_burmesebert_pipeline` is a Burmese model originally trained by jojo-ai-mst.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_burmesebert_pipeline_my_5.5.1_3.0_1738049852921.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_burmesebert_pipeline_my_5.5.1_3.0_1738049852921.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_burmesebert_pipeline", lang = "my")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_burmesebert_pipeline", lang = "my")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_burmesebert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|my|
+|Size:|1.4 GB|
+
+## References
+
+https://huggingface.co/jojo-ai-mst/BurmeseBert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_canadian_address_checker_on_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_canadian_address_checker_on_en.md
new file mode 100644
index 00000000000000..a6095a2a1dc933
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_canadian_address_checker_on_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_canadian_address_checker_on BertSentenceEmbeddings from Hythcliff
+author: John Snow Labs
+name: sent_canadian_address_checker_on
+date: 2025-01-28
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_canadian_address_checker_on` is a English model originally trained by Hythcliff.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_canadian_address_checker_on_en_5.5.1_3.0_1738047433880.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_canadian_address_checker_on_en_5.5.1_3.0_1738047433880.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_canadian_address_checker_on","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_canadian_address_checker_on","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_canadian_address_checker_on|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|406.2 MB|
+
+## References
+
+https://huggingface.co/Hythcliff/canadian-address-checker-on
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_canadian_address_checker_on_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_canadian_address_checker_on_pipeline_en.md
new file mode 100644
index 00000000000000..7c0f6fb5eabb91
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_canadian_address_checker_on_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_canadian_address_checker_on_pipeline pipeline BertSentenceEmbeddings from Hythcliff
+author: John Snow Labs
+name: sent_canadian_address_checker_on_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_canadian_address_checker_on_pipeline` is a English model originally trained by Hythcliff.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_canadian_address_checker_on_pipeline_en_5.5.1_3.0_1738047454155.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_canadian_address_checker_on_pipeline_en_5.5.1_3.0_1738047454155.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_canadian_address_checker_on_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_canadian_address_checker_on_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_canadian_address_checker_on_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/Hythcliff/canadian-address-checker-on
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_cdgp_chilean_sign_language_scibert_cloth_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_cdgp_chilean_sign_language_scibert_cloth_en.md
new file mode 100644
index 00000000000000..59bf30b856012b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_cdgp_chilean_sign_language_scibert_cloth_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_cdgp_chilean_sign_language_scibert_cloth BertSentenceEmbeddings from AndyChiang
+author: John Snow Labs
+name: sent_cdgp_chilean_sign_language_scibert_cloth
+date: 2025-01-28
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_cdgp_chilean_sign_language_scibert_cloth` is a English model originally trained by AndyChiang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_cdgp_chilean_sign_language_scibert_cloth_en_5.5.1_3.0_1738049145773.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_cdgp_chilean_sign_language_scibert_cloth_en_5.5.1_3.0_1738049145773.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_cdgp_chilean_sign_language_scibert_cloth","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_cdgp_chilean_sign_language_scibert_cloth","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_cdgp_chilean_sign_language_scibert_cloth|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|410.0 MB|
+
+## References
+
+https://huggingface.co/AndyChiang/cdgp-csg-scibert-cloth
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_cdgp_chilean_sign_language_scibert_cloth_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_cdgp_chilean_sign_language_scibert_cloth_pipeline_en.md
new file mode 100644
index 00000000000000..e0d86bf8942cec
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_cdgp_chilean_sign_language_scibert_cloth_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_cdgp_chilean_sign_language_scibert_cloth_pipeline pipeline BertSentenceEmbeddings from AndyChiang
+author: John Snow Labs
+name: sent_cdgp_chilean_sign_language_scibert_cloth_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_cdgp_chilean_sign_language_scibert_cloth_pipeline` is a English model originally trained by AndyChiang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_cdgp_chilean_sign_language_scibert_cloth_pipeline_en_5.5.1_3.0_1738049167682.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_cdgp_chilean_sign_language_scibert_cloth_pipeline_en_5.5.1_3.0_1738049167682.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_cdgp_chilean_sign_language_scibert_cloth_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_cdgp_chilean_sign_language_scibert_cloth_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_cdgp_chilean_sign_language_scibert_cloth_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.5 MB|
+
+## References
+
+https://huggingface.co/AndyChiang/cdgp-csg-scibert-cloth
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_coronasentana_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_coronasentana_en.md
new file mode 100644
index 00000000000000..374481ab46ad50
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_coronasentana_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_coronasentana BertSentenceEmbeddings from Peed911
+author: John Snow Labs
+name: sent_coronasentana
+date: 2025-01-28
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_coronasentana` is a English model originally trained by Peed911.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_coronasentana_en_5.5.1_3.0_1738049232421.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_coronasentana_en_5.5.1_3.0_1738049232421.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_coronasentana","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_coronasentana","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_coronasentana|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|402.3 MB|
+
+## References
+
+https://huggingface.co/Peed911/CoronaSentAna
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_coronasentana_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_coronasentana_pipeline_en.md
new file mode 100644
index 00000000000000..46d7c58e3e92b4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_coronasentana_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_coronasentana_pipeline pipeline BertSentenceEmbeddings from Peed911
+author: John Snow Labs
+name: sent_coronasentana_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_coronasentana_pipeline` is a English model originally trained by Peed911.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_coronasentana_pipeline_en_5.5.1_3.0_1738049253401.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_coronasentana_pipeline_en_5.5.1_3.0_1738049253401.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_coronasentana_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_coronasentana_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_coronasentana_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|402.9 MB|
+
+## References
+
+https://huggingface.co/Peed911/CoronaSentAna
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_gbert_job_extended_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_gbert_job_extended_en.md
new file mode 100644
index 00000000000000..90867bc508f4d4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_gbert_job_extended_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_gbert_job_extended BertSentenceEmbeddings from dathi103
+author: John Snow Labs
+name: sent_gbert_job_extended
+date: 2025-01-28
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_gbert_job_extended` is a English model originally trained by dathi103.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_gbert_job_extended_en_5.5.1_3.0_1738047309742.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_gbert_job_extended_en_5.5.1_3.0_1738047309742.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_gbert_job_extended","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_gbert_job_extended","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_gbert_job_extended|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|420.0 MB|
+
+## References
+
+https://huggingface.co/dathi103/gbert-job-extended
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_gbert_job_extended_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_gbert_job_extended_pipeline_en.md
new file mode 100644
index 00000000000000..7daa3158dc13d1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_gbert_job_extended_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_gbert_job_extended_pipeline pipeline BertSentenceEmbeddings from dathi103
+author: John Snow Labs
+name: sent_gbert_job_extended_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_gbert_job_extended_pipeline` is a English model originally trained by dathi103.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_gbert_job_extended_pipeline_en_5.5.1_3.0_1738047330755.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_gbert_job_extended_pipeline_en_5.5.1_3.0_1738047330755.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_gbert_job_extended_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_gbert_job_extended_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_gbert_job_extended_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|420.6 MB|
+
+## References
+
+https://huggingface.co/dathi103/gbert-job-extended
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_gepabert_de.md b/docs/_posts/ahmedlone127/2025-01-28-sent_gepabert_de.md
new file mode 100644
index 00000000000000..7b68f5f661a251
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_gepabert_de.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: German sent_gepabert BertSentenceEmbeddings from aehrm
+author: John Snow Labs
+name: sent_gepabert
+date: 2025-01-28
+tags: [de, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: de
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_gepabert` is a German model originally trained by aehrm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_gepabert_de_5.5.1_3.0_1738048610993.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_gepabert_de_5.5.1_3.0_1738048610993.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_gepabert","de") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_gepabert","de") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_gepabert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|de|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/aehrm/gepabert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_gepabert_pipeline_de.md b/docs/_posts/ahmedlone127/2025-01-28-sent_gepabert_pipeline_de.md
new file mode 100644
index 00000000000000..9e735998a86da5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_gepabert_pipeline_de.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: German sent_gepabert_pipeline pipeline BertSentenceEmbeddings from aehrm
+author: John Snow Labs
+name: sent_gepabert_pipeline
+date: 2025-01-28
+tags: [de, open_source, pipeline, onnx]
+task: Embeddings
+language: de
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_gepabert_pipeline` is a German model originally trained by aehrm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_gepabert_pipeline_de_5.5.1_3.0_1738048671751.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_gepabert_pipeline_de_5.5.1_3.0_1738048671751.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_gepabert_pipeline", lang = "de")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_gepabert_pipeline", lang = "de")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_gepabert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|de|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/aehrm/gepabert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_incel_bert_base_multilingual_cased_1000k_multi_pipeline_xx.md b/docs/_posts/ahmedlone127/2025-01-28-sent_incel_bert_base_multilingual_cased_1000k_multi_pipeline_xx.md
new file mode 100644
index 00000000000000..d346870bcb7f66
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_incel_bert_base_multilingual_cased_1000k_multi_pipeline_xx.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Multilingual sent_incel_bert_base_multilingual_cased_1000k_multi_pipeline pipeline BertSentenceEmbeddings from pgajo
+author: John Snow Labs
+name: sent_incel_bert_base_multilingual_cased_1000k_multi_pipeline
+date: 2025-01-28
+tags: [xx, open_source, pipeline, onnx]
+task: Embeddings
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_incel_bert_base_multilingual_cased_1000k_multi_pipeline` is a Multilingual model originally trained by pgajo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_incel_bert_base_multilingual_cased_1000k_multi_pipeline_xx_5.5.1_3.0_1738049310844.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_incel_bert_base_multilingual_cased_1000k_multi_pipeline_xx_5.5.1_3.0_1738049310844.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_incel_bert_base_multilingual_cased_1000k_multi_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_incel_bert_base_multilingual_cased_1000k_multi_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_incel_bert_base_multilingual_cased_1000k_multi_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|665.6 MB|
+
+## References
+
+https://huggingface.co/pgajo/incel-bert-base-multilingual-cased-1000k_multi
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_incel_bert_base_multilingual_cased_1000k_multi_xx.md b/docs/_posts/ahmedlone127/2025-01-28-sent_incel_bert_base_multilingual_cased_1000k_multi_xx.md
new file mode 100644
index 00000000000000..58e0b8d92710a1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_incel_bert_base_multilingual_cased_1000k_multi_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual sent_incel_bert_base_multilingual_cased_1000k_multi BertSentenceEmbeddings from pgajo
+author: John Snow Labs
+name: sent_incel_bert_base_multilingual_cased_1000k_multi
+date: 2025-01-28
+tags: [xx, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_incel_bert_base_multilingual_cased_1000k_multi` is a Multilingual model originally trained by pgajo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_incel_bert_base_multilingual_cased_1000k_multi_xx_5.5.1_3.0_1738049274357.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_incel_bert_base_multilingual_cased_1000k_multi_xx_5.5.1_3.0_1738049274357.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_incel_bert_base_multilingual_cased_1000k_multi","xx") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_incel_bert_base_multilingual_cased_1000k_multi","xx") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_incel_bert_base_multilingual_cased_1000k_multi|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|xx|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/pgajo/incel-bert-base-multilingual-cased-1000k_multi
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_indicbertv2_mlm_only_finetuned_imdb_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_indicbertv2_mlm_only_finetuned_imdb_en.md
new file mode 100644
index 00000000000000..4b0f4465ec1517
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_indicbertv2_mlm_only_finetuned_imdb_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_indicbertv2_mlm_only_finetuned_imdb BertSentenceEmbeddings from varshith0101
+author: John Snow Labs
+name: sent_indicbertv2_mlm_only_finetuned_imdb
+date: 2025-01-28
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_indicbertv2_mlm_only_finetuned_imdb` is a English model originally trained by varshith0101.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_indicbertv2_mlm_only_finetuned_imdb_en_5.5.1_3.0_1738049545464.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_indicbertv2_mlm_only_finetuned_imdb_en_5.5.1_3.0_1738049545464.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_indicbertv2_mlm_only_finetuned_imdb","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_indicbertv2_mlm_only_finetuned_imdb","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_indicbertv2_mlm_only_finetuned_imdb|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/varshith0101/IndicBERTv2-MLM-only-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_indicbertv2_mlm_only_finetuned_imdb_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_indicbertv2_mlm_only_finetuned_imdb_pipeline_en.md
new file mode 100644
index 00000000000000..80002f0f6c7add
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_indicbertv2_mlm_only_finetuned_imdb_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_indicbertv2_mlm_only_finetuned_imdb_pipeline pipeline BertSentenceEmbeddings from varshith0101
+author: John Snow Labs
+name: sent_indicbertv2_mlm_only_finetuned_imdb_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_indicbertv2_mlm_only_finetuned_imdb_pipeline` is a English model originally trained by varshith0101.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_indicbertv2_mlm_only_finetuned_imdb_pipeline_en_5.5.1_3.0_1738049597452.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_indicbertv2_mlm_only_finetuned_imdb_pipeline_en_5.5.1_3.0_1738049597452.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_indicbertv2_mlm_only_finetuned_imdb_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_indicbertv2_mlm_only_finetuned_imdb_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_indicbertv2_mlm_only_finetuned_imdb_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/varshith0101/IndicBERTv2-MLM-only-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_m2_bert_128_retrieval_encoder_v1_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_m2_bert_128_retrieval_encoder_v1_en.md
new file mode 100644
index 00000000000000..eab54a5754f2e5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_m2_bert_128_retrieval_encoder_v1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_m2_bert_128_retrieval_encoder_v1 BertSentenceEmbeddings from hazyresearch
+author: John Snow Labs
+name: sent_m2_bert_128_retrieval_encoder_v1
+date: 2025-01-28
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_m2_bert_128_retrieval_encoder_v1` is a English model originally trained by hazyresearch.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_m2_bert_128_retrieval_encoder_v1_en_5.5.1_3.0_1738047738476.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_m2_bert_128_retrieval_encoder_v1_en_5.5.1_3.0_1738047738476.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_m2_bert_128_retrieval_encoder_v1","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_m2_bert_128_retrieval_encoder_v1","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_m2_bert_128_retrieval_encoder_v1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|405.6 MB|
+
+## References
+
+https://huggingface.co/hazyresearch/M2-BERT-128-Retrieval-Encoder-V1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_m2_bert_128_retrieval_encoder_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_m2_bert_128_retrieval_encoder_v1_pipeline_en.md
new file mode 100644
index 00000000000000..2384130e43b8b7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_m2_bert_128_retrieval_encoder_v1_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_m2_bert_128_retrieval_encoder_v1_pipeline pipeline BertSentenceEmbeddings from hazyresearch
+author: John Snow Labs
+name: sent_m2_bert_128_retrieval_encoder_v1_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_m2_bert_128_retrieval_encoder_v1_pipeline` is a English model originally trained by hazyresearch.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_m2_bert_128_retrieval_encoder_v1_pipeline_en_5.5.1_3.0_1738047758851.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_m2_bert_128_retrieval_encoder_v1_pipeline_en_5.5.1_3.0_1738047758851.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_m2_bert_128_retrieval_encoder_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_m2_bert_128_retrieval_encoder_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_m2_bert_128_retrieval_encoder_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.2 MB|
+
+## References
+
+https://huggingface.co/hazyresearch/M2-BERT-128-Retrieval-Encoder-V1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_meda_bert_jannikskytt_da.md b/docs/_posts/ahmedlone127/2025-01-28-sent_meda_bert_jannikskytt_da.md
new file mode 100644
index 00000000000000..4ead44446acd13
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_meda_bert_jannikskytt_da.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Danish sent_meda_bert_jannikskytt BertSentenceEmbeddings from jannikskytt
+author: John Snow Labs
+name: sent_meda_bert_jannikskytt
+date: 2025-01-28
+tags: [da, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: da
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_meda_bert_jannikskytt` is a Danish model originally trained by jannikskytt.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_meda_bert_jannikskytt_da_5.5.1_3.0_1738049092763.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_meda_bert_jannikskytt_da_5.5.1_3.0_1738049092763.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_meda_bert_jannikskytt","da") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_meda_bert_jannikskytt","da") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_meda_bert_jannikskytt|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|da|
+|Size:|412.3 MB|
+
+## References
+
+https://huggingface.co/jannikskytt/MeDa-Bert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_meda_bert_jannikskytt_pipeline_da.md b/docs/_posts/ahmedlone127/2025-01-28-sent_meda_bert_jannikskytt_pipeline_da.md
new file mode 100644
index 00000000000000..d90b75088ebbd4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_meda_bert_jannikskytt_pipeline_da.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Danish sent_meda_bert_jannikskytt_pipeline pipeline BertSentenceEmbeddings from jannikskytt
+author: John Snow Labs
+name: sent_meda_bert_jannikskytt_pipeline
+date: 2025-01-28
+tags: [da, open_source, pipeline, onnx]
+task: Embeddings
+language: da
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_meda_bert_jannikskytt_pipeline` is a Danish model originally trained by jannikskytt.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_meda_bert_jannikskytt_pipeline_da_5.5.1_3.0_1738049116773.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_meda_bert_jannikskytt_pipeline_da_5.5.1_3.0_1738049116773.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_meda_bert_jannikskytt_pipeline", lang = "da")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_meda_bert_jannikskytt_pipeline", lang = "da")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_meda_bert_jannikskytt_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|da|
+|Size:|412.8 MB|
+
+## References
+
+https://huggingface.co/jannikskytt/MeDa-Bert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_mergedistill_maltese_italian_128_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_mergedistill_maltese_italian_128_en.md
new file mode 100644
index 00000000000000..09f522415e756d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_mergedistill_maltese_italian_128_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_mergedistill_maltese_italian_128 BertSentenceEmbeddings from amitness
+author: John Snow Labs
+name: sent_mergedistill_maltese_italian_128
+date: 2025-01-28
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_mergedistill_maltese_italian_128` is a English model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_mergedistill_maltese_italian_128_en_5.5.1_3.0_1738049809271.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_mergedistill_maltese_italian_128_en_5.5.1_3.0_1738049809271.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_mergedistill_maltese_italian_128","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_mergedistill_maltese_italian_128","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_mergedistill_maltese_italian_128|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|538.8 MB|
+
+## References
+
+https://huggingface.co/amitness/mergedistill-mt-it-128
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_mergedistill_maltese_italian_128_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_mergedistill_maltese_italian_128_pipeline_en.md
new file mode 100644
index 00000000000000..178abe11d837e9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_mergedistill_maltese_italian_128_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_mergedistill_maltese_italian_128_pipeline pipeline BertSentenceEmbeddings from amitness
+author: John Snow Labs
+name: sent_mergedistill_maltese_italian_128_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_mergedistill_maltese_italian_128_pipeline` is a English model originally trained by amitness.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_mergedistill_maltese_italian_128_pipeline_en_5.5.1_3.0_1738049835413.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_mergedistill_maltese_italian_128_pipeline_en_5.5.1_3.0_1738049835413.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_mergedistill_maltese_italian_128_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_mergedistill_maltese_italian_128_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_mergedistill_maltese_italian_128_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|539.3 MB|
+
+## References
+
+https://huggingface.co/amitness/mergedistill-mt-it-128
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_mlm_drugcl_descreption_epochs_5_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_mlm_drugcl_descreption_epochs_5_en.md
new file mode 100644
index 00000000000000..cb0fa7c350a0c3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_mlm_drugcl_descreption_epochs_5_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_mlm_drugcl_descreption_epochs_5 BertSentenceEmbeddings from Milad1b
+author: John Snow Labs
+name: sent_mlm_drugcl_descreption_epochs_5
+date: 2025-01-28
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_mlm_drugcl_descreption_epochs_5` is a English model originally trained by Milad1b.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_mlm_drugcl_descreption_epochs_5_en_5.5.1_3.0_1738049254766.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_mlm_drugcl_descreption_epochs_5_en_5.5.1_3.0_1738049254766.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_mlm_drugcl_descreption_epochs_5","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_mlm_drugcl_descreption_epochs_5","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_mlm_drugcl_descreption_epochs_5|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|403.5 MB|
+
+## References
+
+https://huggingface.co/Milad1b/MLM_drugcl_descreption_epochs-5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_mlm_drugcl_descreption_epochs_5_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_mlm_drugcl_descreption_epochs_5_pipeline_en.md
new file mode 100644
index 00000000000000..339a1557352306
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_mlm_drugcl_descreption_epochs_5_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_mlm_drugcl_descreption_epochs_5_pipeline pipeline BertSentenceEmbeddings from Milad1b
+author: John Snow Labs
+name: sent_mlm_drugcl_descreption_epochs_5_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_mlm_drugcl_descreption_epochs_5_pipeline` is a English model originally trained by Milad1b.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_mlm_drugcl_descreption_epochs_5_pipeline_en_5.5.1_3.0_1738049278761.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_mlm_drugcl_descreption_epochs_5_pipeline_en_5.5.1_3.0_1738049278761.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_mlm_drugcl_descreption_epochs_5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_mlm_drugcl_descreption_epochs_5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_mlm_drugcl_descreption_epochs_5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|404.1 MB|
+
+## References
+
+https://huggingface.co/Milad1b/MLM_drugcl_descreption_epochs-5
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_model_leofn3_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_model_leofn3_en.md
new file mode 100644
index 00000000000000..f20a7940604ab1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_model_leofn3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_model_leofn3 BertSentenceEmbeddings from leofn3
+author: John Snow Labs
+name: sent_model_leofn3
+date: 2025-01-28
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_model_leofn3` is a English model originally trained by leofn3.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_model_leofn3_en_5.5.1_3.0_1738048965360.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_model_leofn3_en_5.5.1_3.0_1738048965360.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_model_leofn3","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_model_leofn3","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_model_leofn3|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|206.0 MB|
+
+## References
+
+https://huggingface.co/leofn3/model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_model_leofn3_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_model_leofn3_pipeline_en.md
new file mode 100644
index 00000000000000..b6f327a01447f8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_model_leofn3_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_model_leofn3_pipeline pipeline BertSentenceEmbeddings from leofn3
+author: John Snow Labs
+name: sent_model_leofn3_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_model_leofn3_pipeline` is a English model originally trained by leofn3.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_model_leofn3_pipeline_en_5.5.1_3.0_1738048975582.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_model_leofn3_pipeline_en_5.5.1_3.0_1738048975582.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_model_leofn3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_model_leofn3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_model_leofn3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.5 MB|
+
+## References
+
+https://huggingface.co/leofn3/model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_model_med_195_e_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_model_med_195_e_en.md
new file mode 100644
index 00000000000000..8bc7359fd24a5f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_model_med_195_e_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_model_med_195_e BertSentenceEmbeddings from kumarme072
+author: John Snow Labs
+name: sent_model_med_195_e
+date: 2025-01-28
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_model_med_195_e` is a English model originally trained by kumarme072.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_model_med_195_e_en_5.5.1_3.0_1738047678441.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_model_med_195_e_en_5.5.1_3.0_1738047678441.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_model_med_195_e","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_model_med_195_e","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_model_med_195_e|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|486.4 MB|
+
+## References
+
+https://huggingface.co/kumarme072/model_med_195_E
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_model_med_195_e_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_model_med_195_e_pipeline_en.md
new file mode 100644
index 00000000000000..9b96f9a5a7c5d8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_model_med_195_e_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_model_med_195_e_pipeline pipeline BertSentenceEmbeddings from kumarme072
+author: John Snow Labs
+name: sent_model_med_195_e_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_model_med_195_e_pipeline` is a English model originally trained by kumarme072.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_model_med_195_e_pipeline_en_5.5.1_3.0_1738047705197.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_model_med_195_e_pipeline_en_5.5.1_3.0_1738047705197.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_model_med_195_e_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_model_med_195_e_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_model_med_195_e_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|486.9 MB|
+
+## References
+
+https://huggingface.co/kumarme072/model_med_195_E
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_myrubert_tiny2_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_myrubert_tiny2_en.md
new file mode 100644
index 00000000000000..469658665c2858
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_myrubert_tiny2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_myrubert_tiny2 BertSentenceEmbeddings from nlp-testing
+author: John Snow Labs
+name: sent_myrubert_tiny2
+date: 2025-01-28
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_myrubert_tiny2` is a English model originally trained by nlp-testing.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_myrubert_tiny2_en_5.5.1_3.0_1738047230783.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_myrubert_tiny2_en_5.5.1_3.0_1738047230783.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_myrubert_tiny2","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_myrubert_tiny2","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_myrubert_tiny2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|109.0 MB|
+
+## References
+
+https://huggingface.co/nlp-testing/myrubert-tiny2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_myrubert_tiny2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_myrubert_tiny2_pipeline_en.md
new file mode 100644
index 00000000000000..1eac2e8a2e5192
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_myrubert_tiny2_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_myrubert_tiny2_pipeline pipeline BertSentenceEmbeddings from nlp-testing
+author: John Snow Labs
+name: sent_myrubert_tiny2_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_myrubert_tiny2_pipeline` is a English model originally trained by nlp-testing.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_myrubert_tiny2_pipeline_en_5.5.1_3.0_1738047236031.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_myrubert_tiny2_pipeline_en_5.5.1_3.0_1738047236031.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_myrubert_tiny2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_myrubert_tiny2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_myrubert_tiny2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|109.5 MB|
+
+## References
+
+https://huggingface.co/nlp-testing/myrubert-tiny2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_qwen_textgen_model15nnn_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_qwen_textgen_model15nnn_en.md
new file mode 100644
index 00000000000000..37ce33060f3c8a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_qwen_textgen_model15nnn_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_qwen_textgen_model15nnn BertSentenceEmbeddings from JeloH
+author: John Snow Labs
+name: sent_qwen_textgen_model15nnn
+date: 2025-01-28
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_qwen_textgen_model15nnn` is a English model originally trained by JeloH.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_qwen_textgen_model15nnn_en_5.5.1_3.0_1738049479983.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_qwen_textgen_model15nnn_en_5.5.1_3.0_1738049479983.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_qwen_textgen_model15nnn","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_qwen_textgen_model15nnn","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_qwen_textgen_model15nnn|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/JeloH/qwen-textgen-model15nnn
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_qwen_textgen_model15nnn_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_qwen_textgen_model15nnn_pipeline_en.md
new file mode 100644
index 00000000000000..1a77724a352989
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_qwen_textgen_model15nnn_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_qwen_textgen_model15nnn_pipeline pipeline BertSentenceEmbeddings from JeloH
+author: John Snow Labs
+name: sent_qwen_textgen_model15nnn_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_qwen_textgen_model15nnn_pipeline` is a English model originally trained by JeloH.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_qwen_textgen_model15nnn_pipeline_en_5.5.1_3.0_1738049501058.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_qwen_textgen_model15nnn_pipeline_en_5.5.1_3.0_1738049501058.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_qwen_textgen_model15nnn_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_qwen_textgen_model15nnn_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_qwen_textgen_model15nnn_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.7 MB|
+
+## References
+
+https://huggingface.co/JeloH/qwen-textgen-model15nnn
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_topic_erica_bert_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_topic_erica_bert_en.md
new file mode 100644
index 00000000000000..772fad77f57d9a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_topic_erica_bert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_topic_erica_bert BertSentenceEmbeddings from Kdogs
+author: John Snow Labs
+name: sent_topic_erica_bert
+date: 2025-01-28
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_topic_erica_bert` is a English model originally trained by Kdogs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_topic_erica_bert_en_5.5.1_3.0_1738049632394.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_topic_erica_bert_en_5.5.1_3.0_1738049632394.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_topic_erica_bert","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_topic_erica_bert","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_topic_erica_bert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|412.4 MB|
+
+## References
+
+https://huggingface.co/Kdogs/topic_erica_bert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_topic_erica_bert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_topic_erica_bert_pipeline_en.md
new file mode 100644
index 00000000000000..c3eb81d1619d5f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_topic_erica_bert_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_topic_erica_bert_pipeline pipeline BertSentenceEmbeddings from Kdogs
+author: John Snow Labs
+name: sent_topic_erica_bert_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_topic_erica_bert_pipeline` is a English model originally trained by Kdogs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_topic_erica_bert_pipeline_en_5.5.1_3.0_1738049653175.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_topic_erica_bert_pipeline_en_5.5.1_3.0_1738049653175.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_topic_erica_bert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_topic_erica_bert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_topic_erica_bert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|413.0 MB|
+
+## References
+
+https://huggingface.co/Kdogs/topic_erica_bert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_xlm_v_base_trimmed_french_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_xlm_v_base_trimmed_french_en.md
new file mode 100644
index 00000000000000..85a6c932f4fbe3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_xlm_v_base_trimmed_french_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_xlm_v_base_trimmed_french XlmRoBertaSentenceEmbeddings from vocabtrimmer
+author: John Snow Labs
+name: sent_xlm_v_base_trimmed_french
+date: 2025-01-28
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_v_base_trimmed_french` is a English model originally trained by vocabtrimmer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_v_base_trimmed_french_en_5.5.1_3.0_1738046593729.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_v_base_trimmed_french_en_5.5.1_3.0_1738046593729.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_v_base_trimmed_french","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_v_base_trimmed_french","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_v_base_trimmed_french|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|584.0 MB|
+
+## References
+
+https://huggingface.co/vocabtrimmer/xlm-v-base-trimmed-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_xlm_v_base_trimmed_french_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_xlm_v_base_trimmed_french_pipeline_en.md
new file mode 100644
index 00000000000000..689ab908ce4132
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_xlm_v_base_trimmed_french_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_xlm_v_base_trimmed_french_pipeline pipeline XlmRoBertaSentenceEmbeddings from vocabtrimmer
+author: John Snow Labs
+name: sent_xlm_v_base_trimmed_french_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_v_base_trimmed_french_pipeline` is a English model originally trained by vocabtrimmer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_v_base_trimmed_french_pipeline_en_5.5.1_3.0_1738046755349.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_v_base_trimmed_french_pipeline_en_5.5.1_3.0_1738046755349.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_xlm_v_base_trimmed_french_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_xlm_v_base_trimmed_french_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_v_base_trimmed_french_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|584.5 MB|
+
+## References
+
+https://huggingface.co/vocabtrimmer/xlm-v-base-trimmed-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_xlm_v_base_trimmed_german_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_xlm_v_base_trimmed_german_en.md
new file mode 100644
index 00000000000000..5e4407f4e56903
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_xlm_v_base_trimmed_german_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_xlm_v_base_trimmed_german XlmRoBertaSentenceEmbeddings from vocabtrimmer
+author: John Snow Labs
+name: sent_xlm_v_base_trimmed_german
+date: 2025-01-28
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_v_base_trimmed_german` is a English model originally trained by vocabtrimmer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_v_base_trimmed_german_en_5.5.1_3.0_1738075742694.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_v_base_trimmed_german_en_5.5.1_3.0_1738075742694.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_v_base_trimmed_german","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_v_base_trimmed_german","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_v_base_trimmed_german|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|618.6 MB|
+
+## References
+
+https://huggingface.co/vocabtrimmer/xlm-v-base-trimmed-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_xlm_v_base_trimmed_german_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_xlm_v_base_trimmed_german_pipeline_en.md
new file mode 100644
index 00000000000000..51fedae4a59e0a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_xlm_v_base_trimmed_german_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_xlm_v_base_trimmed_german_pipeline pipeline XlmRoBertaSentenceEmbeddings from vocabtrimmer
+author: John Snow Labs
+name: sent_xlm_v_base_trimmed_german_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_v_base_trimmed_german_pipeline` is a English model originally trained by vocabtrimmer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_v_base_trimmed_german_pipeline_en_5.5.1_3.0_1738075914550.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_v_base_trimmed_german_pipeline_en_5.5.1_3.0_1738075914550.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_xlm_v_base_trimmed_german_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_xlm_v_base_trimmed_german_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_v_base_trimmed_german_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|619.1 MB|
+
+## References
+
+https://huggingface.co/vocabtrimmer/xlm-v-base-trimmed-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_xlm_v_base_trimmed_portuguese_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_xlm_v_base_trimmed_portuguese_en.md
new file mode 100644
index 00000000000000..bbe96b0762eb27
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_xlm_v_base_trimmed_portuguese_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_xlm_v_base_trimmed_portuguese XlmRoBertaSentenceEmbeddings from vocabtrimmer
+author: John Snow Labs
+name: sent_xlm_v_base_trimmed_portuguese
+date: 2025-01-28
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_v_base_trimmed_portuguese` is a English model originally trained by vocabtrimmer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_v_base_trimmed_portuguese_en_5.5.1_3.0_1738046542808.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_v_base_trimmed_portuguese_en_5.5.1_3.0_1738046542808.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_v_base_trimmed_portuguese","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_v_base_trimmed_portuguese","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_v_base_trimmed_portuguese|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|520.4 MB|
+
+## References
+
+https://huggingface.co/vocabtrimmer/xlm-v-base-trimmed-pt
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_xlm_v_base_trimmed_portuguese_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_xlm_v_base_trimmed_portuguese_pipeline_en.md
new file mode 100644
index 00000000000000..b223c7f5e47ee4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_xlm_v_base_trimmed_portuguese_pipeline_en.md
@@ -0,0 +1,73 @@
+---
+layout: model
+title: English sent_xlm_v_base_trimmed_portuguese_pipeline pipeline XlmRoBertaSentenceEmbeddings from vocabtrimmer
+author: John Snow Labs
+name: sent_xlm_v_base_trimmed_portuguese_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_v_base_trimmed_portuguese_pipeline` is a English model originally trained by vocabtrimmer.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_v_base_trimmed_portuguese_pipeline_en_5.5.1_3.0_1738046688546.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_v_base_trimmed_portuguese_pipeline_en_5.5.1_3.0_1738046688546.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("sent_xlm_v_base_trimmed_portuguese_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("sent_xlm_v_base_trimmed_portuguese_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_v_base_trimmed_portuguese_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|521.0 MB|
+
+## References
+
+References
+
+https://huggingface.co/vocabtrimmer/xlm-v-base-trimmed-pt
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_xlm_v_base_trimmed_spanish_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_xlm_v_base_trimmed_spanish_en.md
new file mode 100644
index 00000000000000..a32795de2ad6ff
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_xlm_v_base_trimmed_spanish_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_xlm_v_base_trimmed_spanish XlmRoBertaSentenceEmbeddings from vocabtrimmer
+author: John Snow Labs
+name: sent_xlm_v_base_trimmed_spanish
+date: 2025-01-28
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_v_base_trimmed_spanish` is a English model originally trained by vocabtrimmer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_v_base_trimmed_spanish_en_5.5.1_3.0_1738046615110.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_v_base_trimmed_spanish_en_5.5.1_3.0_1738046615110.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_v_base_trimmed_spanish","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_v_base_trimmed_spanish","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_v_base_trimmed_spanish|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|624.5 MB|
+
+## References
+
+https://huggingface.co/vocabtrimmer/xlm-v-base-trimmed-es
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sent_xlm_v_base_trimmed_spanish_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-sent_xlm_v_base_trimmed_spanish_pipeline_en.md
new file mode 100644
index 00000000000000..5b1f1fd8477542
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sent_xlm_v_base_trimmed_spanish_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_xlm_v_base_trimmed_spanish_pipeline pipeline XlmRoBertaSentenceEmbeddings from vocabtrimmer
+author: John Snow Labs
+name: sent_xlm_v_base_trimmed_spanish_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_v_base_trimmed_spanish_pipeline` is a English model originally trained by vocabtrimmer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_v_base_trimmed_spanish_pipeline_en_5.5.1_3.0_1738046789900.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_v_base_trimmed_spanish_pipeline_en_5.5.1_3.0_1738046789900.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_xlm_v_base_trimmed_spanish_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_xlm_v_base_trimmed_spanish_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_v_base_trimmed_spanish_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|625.0 MB|
+
+## References
+
+https://huggingface.co/vocabtrimmer/xlm-v-base-trimmed-es
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sentiment_analysis_model_team_28_alejndrojavier_en.md b/docs/_posts/ahmedlone127/2025-01-28-sentiment_analysis_model_team_28_alejndrojavier_en.md
new file mode 100644
index 00000000000000..adfc5a8ef9847c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sentiment_analysis_model_team_28_alejndrojavier_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sentiment_analysis_model_team_28_alejndrojavier DistilBertForSequenceClassification from alejndrojavier
+author: John Snow Labs
+name: sentiment_analysis_model_team_28_alejndrojavier
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentiment_analysis_model_team_28_alejndrojavier` is a English model originally trained by alejndrojavier.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentiment_analysis_model_team_28_alejndrojavier_en_5.5.1_3.0_1738077741574.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentiment_analysis_model_team_28_alejndrojavier_en_5.5.1_3.0_1738077741574.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("sentiment_analysis_model_team_28_alejndrojavier","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("sentiment_analysis_model_team_28_alejndrojavier", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sentiment_analysis_model_team_28_alejndrojavier|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/alejndrojavier/sentiment-analysis-model-team-28
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sentiment_analysis_model_team_28_alejndrojavier_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-sentiment_analysis_model_team_28_alejndrojavier_pipeline_en.md
new file mode 100644
index 00000000000000..2e718dcf8761bc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sentiment_analysis_model_team_28_alejndrojavier_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English sentiment_analysis_model_team_28_alejndrojavier_pipeline pipeline DistilBertForSequenceClassification from alejndrojavier
+author: John Snow Labs
+name: sentiment_analysis_model_team_28_alejndrojavier_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentiment_analysis_model_team_28_alejndrojavier_pipeline` is a English model originally trained by alejndrojavier.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentiment_analysis_model_team_28_alejndrojavier_pipeline_en_5.5.1_3.0_1738077754327.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentiment_analysis_model_team_28_alejndrojavier_pipeline_en_5.5.1_3.0_1738077754327.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sentiment_analysis_model_team_28_alejndrojavier_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sentiment_analysis_model_team_28_alejndrojavier_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sentiment_analysis_model_team_28_alejndrojavier_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/alejndrojavier/sentiment-analysis-model-team-28
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sft_mt5_base_pile_ner_type_en.md b/docs/_posts/ahmedlone127/2025-01-28-sft_mt5_base_pile_ner_type_en.md
new file mode 100644
index 00000000000000..c9531157f0111a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sft_mt5_base_pile_ner_type_en.md
@@ -0,0 +1,88 @@
+---
+layout: model
+title: English sft_mt5_base_pile_ner_type T5Transformer from nqv2291
+author: John Snow Labs
+name: sft_mt5_base_pile_ner_type
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sft_mt5_base_pile_ner_type` is a English model originally trained by nqv2291.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sft_mt5_base_pile_ner_type_en_5.5.1_3.0_1738094080884.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sft_mt5_base_pile_ner_type_en_5.5.1_3.0_1738094080884.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("sft_mt5_base_pile_ner_type","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("sft_mt5_base_pile_ner_type", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sft_mt5_base_pile_ner_type|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|2.5 GB|
+
+## References
+
+References
+
+https://huggingface.co/nqv2291/sft_mt5-base_Pile-NER-type
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sft_mt5_base_pile_ner_type_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-sft_mt5_base_pile_ner_type_pipeline_en.md
new file mode 100644
index 00000000000000..e7b91ddf4c7f8c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sft_mt5_base_pile_ner_type_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sft_mt5_base_pile_ner_type_pipeline pipeline T5Transformer from nqv2291
+author: John Snow Labs
+name: sft_mt5_base_pile_ner_type_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sft_mt5_base_pile_ner_type_pipeline` is a English model originally trained by nqv2291.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sft_mt5_base_pile_ner_type_pipeline_en_5.5.1_3.0_1738094307872.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sft_mt5_base_pile_ner_type_pipeline_en_5.5.1_3.0_1738094307872.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("sft_mt5_base_pile_ner_type_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("sft_mt5_base_pile_ner_type_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sft_mt5_base_pile_ner_type_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|2.5 GB|
+
+## References
+
+References
+
+https://huggingface.co/nqv2291/sft_mt5-base_Pile-NER-type
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-simple_digital_chess_pieces_limited_styles_en.md b/docs/_posts/ahmedlone127/2025-01-28-simple_digital_chess_pieces_limited_styles_en.md
new file mode 100644
index 00000000000000..884d25b89bc134
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-simple_digital_chess_pieces_limited_styles_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English simple_digital_chess_pieces_limited_styles ViTForImageClassification from deglaus
+author: John Snow Labs
+name: simple_digital_chess_pieces_limited_styles
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`simple_digital_chess_pieces_limited_styles` is a English model originally trained by deglaus.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/simple_digital_chess_pieces_limited_styles_en_5.5.1_3.0_1738022608785.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/simple_digital_chess_pieces_limited_styles_en_5.5.1_3.0_1738022608785.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""simple_digital_chess_pieces_limited_styles","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("simple_digital_chess_pieces_limited_styles","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|simple_digital_chess_pieces_limited_styles|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/deglaus/simple_digital_chess_pieces_limited_styles
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-simple_digital_chess_pieces_limited_styles_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-simple_digital_chess_pieces_limited_styles_pipeline_en.md
new file mode 100644
index 00000000000000..fa4da0781b46b1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-simple_digital_chess_pieces_limited_styles_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English simple_digital_chess_pieces_limited_styles_pipeline pipeline ViTForImageClassification from deglaus
+author: John Snow Labs
+name: simple_digital_chess_pieces_limited_styles_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`simple_digital_chess_pieces_limited_styles_pipeline` is a English model originally trained by deglaus.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/simple_digital_chess_pieces_limited_styles_pipeline_en_5.5.1_3.0_1738022628793.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/simple_digital_chess_pieces_limited_styles_pipeline_en_5.5.1_3.0_1738022628793.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("simple_digital_chess_pieces_limited_styles_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("simple_digital_chess_pieces_limited_styles_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|simple_digital_chess_pieces_limited_styles_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.4 MB|
+
+## References
+
+https://huggingface.co/deglaus/simple_digital_chess_pieces_limited_styles
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sinonombert_en.md b/docs/_posts/ahmedlone127/2025-01-28-sinonombert_en.md
new file mode 100644
index 00000000000000..33e4957b6638cc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sinonombert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sinonombert BertEmbeddings from btqkhai
+author: John Snow Labs
+name: sinonombert
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sinonombert` is a English model originally trained by btqkhai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sinonombert_en_5.5.1_3.0_1738058356725.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sinonombert_en_5.5.1_3.0_1738058356725.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("sinonombert","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("sinonombert","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sinonombert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|465.6 MB|
+
+## References
+
+https://huggingface.co/btqkhai/SinoNomBERT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-sinonombert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-sinonombert_pipeline_en.md
new file mode 100644
index 00000000000000..d089aa580e6358
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-sinonombert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English sinonombert_pipeline pipeline BertEmbeddings from btqkhai
+author: John Snow Labs
+name: sinonombert_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sinonombert_pipeline` is a English model originally trained by btqkhai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sinonombert_pipeline_en_5.5.1_3.0_1738058379628.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sinonombert_pipeline_en_5.5.1_3.0_1738058379628.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sinonombert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sinonombert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sinonombert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|465.6 MB|
+
+## References
+
+https://huggingface.co/btqkhai/SinoNomBERT
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-skintelligent_acne_en.md b/docs/_posts/ahmedlone127/2025-01-28-skintelligent_acne_en.md
new file mode 100644
index 00000000000000..9354464e3b7f8f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-skintelligent_acne_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English skintelligent_acne ViTForImageClassification from imfarzanansari
+author: John Snow Labs
+name: skintelligent_acne
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`skintelligent_acne` is a English model originally trained by imfarzanansari.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/skintelligent_acne_en_5.5.1_3.0_1738022755523.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/skintelligent_acne_en_5.5.1_3.0_1738022755523.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""skintelligent_acne","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("skintelligent_acne","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|skintelligent_acne|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/imfarzanansari/skintelligent-acne
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-skintelligent_acne_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-skintelligent_acne_pipeline_en.md
new file mode 100644
index 00000000000000..31c0fd53c15712
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-skintelligent_acne_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English skintelligent_acne_pipeline pipeline ViTForImageClassification from imfarzanansari
+author: John Snow Labs
+name: skintelligent_acne_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`skintelligent_acne_pipeline` is a English model originally trained by imfarzanansari.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/skintelligent_acne_pipeline_en_5.5.1_3.0_1738022775031.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/skintelligent_acne_pipeline_en_5.5.1_3.0_1738022775031.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("skintelligent_acne_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("skintelligent_acne_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|skintelligent_acne_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/imfarzanansari/skintelligent-acne
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-slm_custom_model_20k_en.md b/docs/_posts/ahmedlone127/2025-01-28-slm_custom_model_20k_en.md
new file mode 100644
index 00000000000000..bdc4ca73fc0eeb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-slm_custom_model_20k_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English slm_custom_model_20k T5Transformer from karthikeyan-r
+author: John Snow Labs
+name: slm_custom_model_20k
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`slm_custom_model_20k` is a English model originally trained by karthikeyan-r.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/slm_custom_model_20k_en_5.5.1_3.0_1738071064460.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/slm_custom_model_20k_en_5.5.1_3.0_1738071064460.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("slm_custom_model_20k","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("slm_custom_model_20k", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|slm_custom_model_20k|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|278.3 MB|
+
+## References
+
+https://huggingface.co/karthikeyan-r/slm-custom-model_20k
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-slm_custom_model_20k_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-slm_custom_model_20k_pipeline_en.md
new file mode 100644
index 00000000000000..4cb9e2c58454a1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-slm_custom_model_20k_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English slm_custom_model_20k_pipeline pipeline T5Transformer from karthikeyan-r
+author: John Snow Labs
+name: slm_custom_model_20k_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`slm_custom_model_20k_pipeline` is a English model originally trained by karthikeyan-r.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/slm_custom_model_20k_pipeline_en_5.5.1_3.0_1738071079755.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/slm_custom_model_20k_pipeline_en_5.5.1_3.0_1738071079755.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("slm_custom_model_20k_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("slm_custom_model_20k_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|slm_custom_model_20k_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|278.3 MB|
+
+## References
+
+https://huggingface.co/karthikeyan-r/slm-custom-model_20k
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-slm_custom_model_5_rk_en.md b/docs/_posts/ahmedlone127/2025-01-28-slm_custom_model_5_rk_en.md
new file mode 100644
index 00000000000000..5b0ba80d7a2024
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-slm_custom_model_5_rk_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English slm_custom_model_5_rk T5Transformer from karthikeyan-r
+author: John Snow Labs
+name: slm_custom_model_5_rk
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`slm_custom_model_5_rk` is a English model originally trained by karthikeyan-r.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/slm_custom_model_5_rk_en_5.5.1_3.0_1738091379175.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/slm_custom_model_5_rk_en_5.5.1_3.0_1738091379175.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("slm_custom_model_5_rk","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("slm_custom_model_5_rk", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|slm_custom_model_5_rk|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|277.5 MB|
+
+## References
+
+https://huggingface.co/karthikeyan-r/slm-custom-model_5_RK
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-slm_custom_model_5_rk_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-slm_custom_model_5_rk_pipeline_en.md
new file mode 100644
index 00000000000000..28addef805a6fc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-slm_custom_model_5_rk_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English slm_custom_model_5_rk_pipeline pipeline T5Transformer from karthikeyan-r
+author: John Snow Labs
+name: slm_custom_model_5_rk_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`slm_custom_model_5_rk_pipeline` is a English model originally trained by karthikeyan-r.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/slm_custom_model_5_rk_pipeline_en_5.5.1_3.0_1738091394845.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/slm_custom_model_5_rk_pipeline_en_5.5.1_3.0_1738091394845.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("slm_custom_model_5_rk_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("slm_custom_model_5_rk_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|slm_custom_model_5_rk_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|277.5 MB|
+
+## References
+
+https://huggingface.co/karthikeyan-r/slm-custom-model_5_RK
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-smaller_albert_base_geo_en.md b/docs/_posts/ahmedlone127/2025-01-28-smaller_albert_base_geo_en.md
new file mode 100644
index 00000000000000..99124947c79dd0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-smaller_albert_base_geo_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English smaller_albert_base_geo BertEmbeddings from ZurabDz
+author: John Snow Labs
+name: smaller_albert_base_geo
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`smaller_albert_base_geo` is a English model originally trained by ZurabDz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/smaller_albert_base_geo_en_5.5.1_3.0_1738085098364.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/smaller_albert_base_geo_en_5.5.1_3.0_1738085098364.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("smaller_albert_base_geo","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("smaller_albert_base_geo","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|smaller_albert_base_geo|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|41.6 MB|
+
+## References
+
+https://huggingface.co/ZurabDz/smaller_albert_base_geo
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-smaller_albert_base_geo_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-smaller_albert_base_geo_pipeline_en.md
new file mode 100644
index 00000000000000..1ccda163b10e23
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-smaller_albert_base_geo_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English smaller_albert_base_geo_pipeline pipeline BertEmbeddings from ZurabDz
+author: John Snow Labs
+name: smaller_albert_base_geo_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`smaller_albert_base_geo_pipeline` is a English model originally trained by ZurabDz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/smaller_albert_base_geo_pipeline_en_5.5.1_3.0_1738085100723.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/smaller_albert_base_geo_pipeline_en_5.5.1_3.0_1738085100723.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("smaller_albert_base_geo_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("smaller_albert_base_geo_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|smaller_albert_base_geo_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|41.6 MB|
+
+## References
+
+https://huggingface.co/ZurabDz/smaller_albert_base_geo
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-spamhunter_en.md b/docs/_posts/ahmedlone127/2025-01-28-spamhunter_en.md
new file mode 100644
index 00000000000000..9fa69b6355b003
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-spamhunter_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English spamhunter BertForSequenceClassification from ar4min
+author: John Snow Labs
+name: spamhunter
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`spamhunter` is a English model originally trained by ar4min.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/spamhunter_en_5.5.1_3.0_1738051212207.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/spamhunter_en_5.5.1_3.0_1738051212207.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("spamhunter","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("spamhunter", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|spamhunter|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/ar4min/SpamHunter
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-spamhunter_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-spamhunter_pipeline_en.md
new file mode 100644
index 00000000000000..d4d88053ebe728
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-spamhunter_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English spamhunter_pipeline pipeline BertForSequenceClassification from ar4min
+author: John Snow Labs
+name: spamhunter_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`spamhunter_pipeline` is a English model originally trained by ar4min.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/spamhunter_pipeline_en_5.5.1_3.0_1738051232872.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/spamhunter_pipeline_en_5.5.1_3.0_1738051232872.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("spamhunter_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("spamhunter_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|spamhunter_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/ar4min/SpamHunter
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-summarize_model_sudarshan00_en.md b/docs/_posts/ahmedlone127/2025-01-28-summarize_model_sudarshan00_en.md
new file mode 100644
index 00000000000000..a55773b56394dc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-summarize_model_sudarshan00_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English summarize_model_sudarshan00 T5Transformer from Sudarshan00
+author: John Snow Labs
+name: summarize_model_sudarshan00
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`summarize_model_sudarshan00` is a English model originally trained by Sudarshan00.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/summarize_model_sudarshan00_en_5.5.1_3.0_1738033076274.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/summarize_model_sudarshan00_en_5.5.1_3.0_1738033076274.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("summarize_model_sudarshan00","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("summarize_model_sudarshan00", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|summarize_model_sudarshan00|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|275.7 MB|
+
+## References
+
+https://huggingface.co/Sudarshan00/summarize_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-summarize_model_sudarshan00_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-summarize_model_sudarshan00_pipeline_en.md
new file mode 100644
index 00000000000000..1f0f625c1e313f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-summarize_model_sudarshan00_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English summarize_model_sudarshan00_pipeline pipeline T5Transformer from Sudarshan00
+author: John Snow Labs
+name: summarize_model_sudarshan00_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`summarize_model_sudarshan00_pipeline` is a English model originally trained by Sudarshan00.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/summarize_model_sudarshan00_pipeline_en_5.5.1_3.0_1738033091925.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/summarize_model_sudarshan00_pipeline_en_5.5.1_3.0_1738033091925.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("summarize_model_sudarshan00_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("summarize_model_sudarshan00_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|summarize_model_sudarshan00_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|275.7 MB|
+
+## References
+
+https://huggingface.co/Sudarshan00/summarize_model
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-summary_vn_en.md b/docs/_posts/ahmedlone127/2025-01-28-summary_vn_en.md
new file mode 100644
index 00000000000000..29090447e5352c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-summary_vn_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English summary_vn T5Transformer from ChiHieuNguyen
+author: John Snow Labs
+name: summary_vn
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`summary_vn` is a English model originally trained by ChiHieuNguyen.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/summary_vn_en_5.5.1_3.0_1738074796915.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/summary_vn_en_5.5.1_3.0_1738074796915.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("summary_vn","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("summary_vn", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|summary_vn|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/ChiHieuNguyen/summary_vn
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-summary_vn_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-summary_vn_pipeline_en.md
new file mode 100644
index 00000000000000..d3b4778a5cee7b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-summary_vn_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English summary_vn_pipeline pipeline T5Transformer from ChiHieuNguyen
+author: John Snow Labs
+name: summary_vn_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`summary_vn_pipeline` is a English model originally trained by ChiHieuNguyen.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/summary_vn_pipeline_en_5.5.1_3.0_1738074933382.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/summary_vn_pipeline_en_5.5.1_3.0_1738074933382.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("summary_vn_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("summary_vn_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|summary_vn_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/ChiHieuNguyen/summary_vn
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_03_en.md b/docs/_posts/ahmedlone127/2025-01-28-swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_03_en.md
new file mode 100644
index 00000000000000..6778c4c9902f36
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_03_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_03 SwinForImageClassification from amjadfqs
+author: John Snow Labs
+name: swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_03
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_03` is a English model originally trained by amjadfqs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_03_en_5.5.1_3.0_1738095185226.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_03_en_5.5.1_3.0_1738095185226.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_03","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_03","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_03|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|649.8 MB|
+
+## References
+
+https://huggingface.co/amjadfqs/swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-skullStrippded_03
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_03_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_03_pipeline_en.md
new file mode 100644
index 00000000000000..dfa58212b6bdbc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_03_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_03_pipeline pipeline SwinForImageClassification from amjadfqs
+author: John Snow Labs
+name: swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_03_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_03_pipeline` is a English model originally trained by amjadfqs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_03_pipeline_en_5.5.1_3.0_1738095217531.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_03_pipeline_en_5.5.1_3.0_1738095217531.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_03_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_03_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_base_patch4_window7_224_in22k_finetuned_brain_tumor_skullstrippded_03_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|649.8 MB|
+
+## References
+
+https://huggingface.co/amjadfqs/swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-skullStrippded_03
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-swin_base_patch4_window7_224_rawdata_finetuned_skindisease_en.md b/docs/_posts/ahmedlone127/2025-01-28-swin_base_patch4_window7_224_rawdata_finetuned_skindisease_en.md
new file mode 100644
index 00000000000000..55f3e74ca75ae0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-swin_base_patch4_window7_224_rawdata_finetuned_skindisease_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_base_patch4_window7_224_rawdata_finetuned_skindisease SwinForImageClassification from Jayanth2002
+author: John Snow Labs
+name: swin_base_patch4_window7_224_rawdata_finetuned_skindisease
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_base_patch4_window7_224_rawdata_finetuned_skindisease` is a English model originally trained by Jayanth2002.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_rawdata_finetuned_skindisease_en_5.5.1_3.0_1738095275515.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_rawdata_finetuned_skindisease_en_5.5.1_3.0_1738095275515.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_base_patch4_window7_224_rawdata_finetuned_skindisease","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_base_patch4_window7_224_rawdata_finetuned_skindisease","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_base_patch4_window7_224_rawdata_finetuned_skindisease|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|650.0 MB|
+
+## References
+
+https://huggingface.co/Jayanth2002/swin-base-patch4-window7-224-rawdata-finetuned-SkinDisease
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-swin_base_patch4_window7_224_rawdata_finetuned_skindisease_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-swin_base_patch4_window7_224_rawdata_finetuned_skindisease_pipeline_en.md
new file mode 100644
index 00000000000000..0fbc3d0606d6fa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-swin_base_patch4_window7_224_rawdata_finetuned_skindisease_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_base_patch4_window7_224_rawdata_finetuned_skindisease_pipeline pipeline SwinForImageClassification from Jayanth2002
+author: John Snow Labs
+name: swin_base_patch4_window7_224_rawdata_finetuned_skindisease_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_base_patch4_window7_224_rawdata_finetuned_skindisease_pipeline` is a English model originally trained by Jayanth2002.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_rawdata_finetuned_skindisease_pipeline_en_5.5.1_3.0_1738095308572.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_base_patch4_window7_224_rawdata_finetuned_skindisease_pipeline_en_5.5.1_3.0_1738095308572.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_base_patch4_window7_224_rawdata_finetuned_skindisease_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_base_patch4_window7_224_rawdata_finetuned_skindisease_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_base_patch4_window7_224_rawdata_finetuned_skindisease_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|650.0 MB|
+
+## References
+
+https://huggingface.co/Jayanth2002/swin-base-patch4-window7-224-rawdata-finetuned-SkinDisease
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-swin_muppet_faces_en.md b/docs/_posts/ahmedlone127/2025-01-28-swin_muppet_faces_en.md
new file mode 100644
index 00000000000000..c02391761b4ebb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-swin_muppet_faces_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_muppet_faces SwinForImageClassification from Norod78
+author: John Snow Labs
+name: swin_muppet_faces
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_muppet_faces` is a English model originally trained by Norod78.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_muppet_faces_en_5.5.1_3.0_1738095670776.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_muppet_faces_en_5.5.1_3.0_1738095670776.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_muppet_faces","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_muppet_faces","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_muppet_faces|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|649.9 MB|
+
+## References
+
+https://huggingface.co/Norod78/swin-muppet-faces
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-swin_muppet_faces_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-swin_muppet_faces_pipeline_en.md
new file mode 100644
index 00000000000000..7697099a3a3c47
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-swin_muppet_faces_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_muppet_faces_pipeline pipeline SwinForImageClassification from Norod78
+author: John Snow Labs
+name: swin_muppet_faces_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_muppet_faces_pipeline` is a English model originally trained by Norod78.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_muppet_faces_pipeline_en_5.5.1_3.0_1738095706181.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_muppet_faces_pipeline_en_5.5.1_3.0_1738095706181.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_muppet_faces_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_muppet_faces_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_muppet_faces_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|649.9 MB|
+
+## References
+
+https://huggingface.co/Norod78/swin-muppet-faces
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_cifar10_en.md b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_cifar10_en.md
new file mode 100644
index 00000000000000..48210d1c22ad4b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_cifar10_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_cifar10 SwinForImageClassification from Skafu
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_cifar10
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_cifar10` is a English model originally trained by Skafu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_cifar10_en_5.5.1_3.0_1738095547469.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_cifar10_en_5.5.1_3.0_1738095547469.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_cifar10","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_cifar10","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_cifar10|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/Skafu/swin-tiny-patch4-window7-224-cifar10
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_cifar10_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_cifar10_pipeline_en.md
new file mode 100644
index 00000000000000..2184b2efe54b52
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_cifar10_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_cifar10_pipeline pipeline SwinForImageClassification from Skafu
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_cifar10_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_cifar10_pipeline` is a English model originally trained by Skafu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_cifar10_pipeline_en_5.5.1_3.0_1738095568289.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_cifar10_pipeline_en_5.5.1_3.0_1738095568289.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_cifar10_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_cifar10_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_cifar10_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/Skafu/swin-tiny-patch4-window7-224-cifar10
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_files_en.md b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_files_en.md
new file mode 100644
index 00000000000000..92c19774e0be5b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_files_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_files SwinForImageClassification from Mira200
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_files
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_files` is a English model originally trained by Mira200.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_files_en_5.5.1_3.0_1738095351379.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_files_en_5.5.1_3.0_1738095351379.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_files","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_files","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_files|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/Mira200/swin-tiny-patch4-window7-224-files
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_files_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_files_pipeline_en.md
new file mode 100644
index 00000000000000..5e45af4bf0271c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_files_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_files_pipeline pipeline SwinForImageClassification from Mira200
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_files_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_files_pipeline` is a English model originally trained by Mira200.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_files_pipeline_en_5.5.1_3.0_1738095363593.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_files_pipeline_en_5.5.1_3.0_1738095363593.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_files_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_files_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_files_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/Mira200/swin-tiny-patch4-window7-224-files
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_car0003_test0_2_en.md b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_car0003_test0_2_en.md
new file mode 100644
index 00000000000000..aaa3bfa434835d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_car0003_test0_2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_car0003_test0_2 SwinForImageClassification from tsware
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_car0003_test0_2
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_car0003_test0_2` is a English model originally trained by tsware.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_car0003_test0_2_en_5.5.1_3.0_1738095037249.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_car0003_test0_2_en_5.5.1_3.0_1738095037249.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_car0003_test0_2","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_car0003_test0_2","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_car0003_test0_2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/tsware/swin-tiny-patch4-window7-224-finetuned-car0003-test0.2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_car0003_test0_2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_car0003_test0_2_pipeline_en.md
new file mode 100644
index 00000000000000..d67cec41504d06
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_car0003_test0_2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_car0003_test0_2_pipeline pipeline SwinForImageClassification from tsware
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_car0003_test0_2_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_car0003_test0_2_pipeline` is a English model originally trained by tsware.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_car0003_test0_2_pipeline_en_5.5.1_3.0_1738095053074.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_car0003_test0_2_pipeline_en_5.5.1_3.0_1738095053074.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_car0003_test0_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_car0003_test0_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_car0003_test0_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/tsware/swin-tiny-patch4-window7-224-finetuned-car0003-test0.2
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_ddc_en.md b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_ddc_en.md
new file mode 100644
index 00000000000000..7a0d6378a2f8bb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_ddc_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_ddc SwinForImageClassification from iayrots
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_ddc
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_ddc` is a English model originally trained by iayrots.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_ddc_en_5.5.1_3.0_1738095037745.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_ddc_en_5.5.1_3.0_1738095037745.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_ddc","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_ddc","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_ddc|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/iayrots/swin-tiny-patch4-window7-224-finetuned-ddc
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_ddc_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_ddc_pipeline_en.md
new file mode 100644
index 00000000000000..cd7541eccabe92
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_ddc_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_ddc_pipeline pipeline SwinForImageClassification from iayrots
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_ddc_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_ddc_pipeline` is a English model originally trained by iayrots.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_ddc_pipeline_en_5.5.1_3.0_1738095054914.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_ddc_pipeline_en_5.5.1_3.0_1738095054914.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_ddc_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_ddc_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_ddc_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/iayrots/swin-tiny-patch4-window7-224-finetuned-ddc
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_2_en.md b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_2_en.md
new file mode 100644
index 00000000000000..1864c827661a8c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_2 SwinForImageClassification from HITMYM
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_2
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_2` is a English model originally trained by HITMYM.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_2_en_5.5.1_3.0_1738095537339.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_2_en_5.5.1_3.0_1738095537339.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_2","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_2","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/HITMYM/swin-tiny-patch4-window7-224-finetuned-eurosat-2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_2_pipeline_en.md
new file mode 100644
index 00000000000000..3bd3c6b0ff990c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_2_pipeline pipeline SwinForImageClassification from HITMYM
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_2_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_2_pipeline` is a English model originally trained by HITMYM.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_2_pipeline_en_5.5.1_3.0_1738095547499.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_2_pipeline_en_5.5.1_3.0_1738095547499.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/HITMYM/swin-tiny-patch4-window7-224-finetuned-eurosat-2
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_adhisetiawan_en.md b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_adhisetiawan_en.md
new file mode 100644
index 00000000000000..6a8e282442421e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_adhisetiawan_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_adhisetiawan SwinForImageClassification from adhisetiawan
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_adhisetiawan
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_adhisetiawan` is a English model originally trained by adhisetiawan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_adhisetiawan_en_5.5.1_3.0_1738095732509.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_adhisetiawan_en_5.5.1_3.0_1738095732509.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_adhisetiawan","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_adhisetiawan","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_adhisetiawan|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.9 MB|
+
+## References
+
+https://huggingface.co/adhisetiawan/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_adhisetiawan_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_adhisetiawan_pipeline_en.md
new file mode 100644
index 00000000000000..60d07ea553de6b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_adhisetiawan_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_adhisetiawan_pipeline pipeline SwinForImageClassification from adhisetiawan
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_adhisetiawan_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_adhisetiawan_pipeline` is a English model originally trained by adhisetiawan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_adhisetiawan_pipeline_en_5.5.1_3.0_1738095742966.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_adhisetiawan_pipeline_en_5.5.1_3.0_1738095742966.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_adhisetiawan_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_adhisetiawan_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_adhisetiawan_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.9 MB|
+
+## References
+
+https://huggingface.co/adhisetiawan/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_atunass_en.md b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_atunass_en.md
new file mode 100644
index 00000000000000..f822cfb61a62ad
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_atunass_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_atunass SwinForImageClassification from aTunass
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_atunass
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_atunass` is a English model originally trained by aTunass.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_atunass_en_5.5.1_3.0_1738095316101.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_atunass_en_5.5.1_3.0_1738095316101.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_atunass","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_atunass","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_atunass|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/aTunass/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_atunass_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_atunass_pipeline_en.md
new file mode 100644
index 00000000000000..468b201e684288
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_atunass_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_atunass_pipeline pipeline SwinForImageClassification from aTunass
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_atunass_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_atunass_pipeline` is a English model originally trained by aTunass.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_atunass_pipeline_en_5.5.1_3.0_1738095328887.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_atunass_pipeline_en_5.5.1_3.0_1738095328887.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_atunass_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_atunass_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_atunass_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/aTunass/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_bison_en.md b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_bison_en.md
new file mode 100644
index 00000000000000..873c17b209224d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_bison_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_bison SwinForImageClassification from bison
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_bison
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_bison` is a English model originally trained by bison.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_bison_en_5.5.1_3.0_1738095904668.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_bison_en_5.5.1_3.0_1738095904668.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_bison","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_bison","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_bison|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/bison/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_bison_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_bison_pipeline_en.md
new file mode 100644
index 00000000000000..72b1a2d23ca6cc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_bison_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_bison_pipeline pipeline SwinForImageClassification from bison
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_bison_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_bison_pipeline` is a English model originally trained by bison.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_bison_pipeline_en_5.5.1_3.0_1738095914999.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_bison_pipeline_en_5.5.1_3.0_1738095914999.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_bison_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_bison_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_bison_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/bison/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_caiban123bo_en.md b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_caiban123bo_en.md
new file mode 100644
index 00000000000000..0f4a5f835338e9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_caiban123bo_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_caiban123bo SwinForImageClassification from caiban123bo
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_caiban123bo
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_caiban123bo` is a English model originally trained by caiban123bo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_caiban123bo_en_5.5.1_3.0_1738095612616.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_caiban123bo_en_5.5.1_3.0_1738095612616.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_caiban123bo","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_caiban123bo","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_caiban123bo|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/caiban123bo/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_caiban123bo_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_caiban123bo_pipeline_en.md
new file mode 100644
index 00000000000000..782ae5728d069a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_caiban123bo_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_caiban123bo_pipeline pipeline SwinForImageClassification from caiban123bo
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_caiban123bo_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_caiban123bo_pipeline` is a English model originally trained by caiban123bo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_caiban123bo_pipeline_en_5.5.1_3.0_1738095623151.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_caiban123bo_pipeline_en_5.5.1_3.0_1738095623151.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_caiban123bo_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_caiban123bo_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_caiban123bo_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/caiban123bo/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_jmcfadden_en.md b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_jmcfadden_en.md
new file mode 100644
index 00000000000000..0a1fa121e17d9c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_jmcfadden_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_jmcfadden SwinForImageClassification from jmcfadden
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_jmcfadden
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_jmcfadden` is a English model originally trained by jmcfadden.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_jmcfadden_en_5.5.1_3.0_1738095135076.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_jmcfadden_en_5.5.1_3.0_1738095135076.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_jmcfadden","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_jmcfadden","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_jmcfadden|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/jmcfadden/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_jmcfadden_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_jmcfadden_pipeline_en.md
new file mode 100644
index 00000000000000..83e3771ab25d9e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_jmcfadden_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_jmcfadden_pipeline pipeline SwinForImageClassification from jmcfadden
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_jmcfadden_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_jmcfadden_pipeline` is a English model originally trained by jmcfadden.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_jmcfadden_pipeline_en_5.5.1_3.0_1738095145466.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_jmcfadden_pipeline_en_5.5.1_3.0_1738095145466.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_jmcfadden_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_jmcfadden_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_jmcfadden_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/jmcfadden/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_lu5_en.md b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_lu5_en.md
new file mode 100644
index 00000000000000..7d954f26fa95c4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_lu5_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_lu5 SwinForImageClassification from lu5
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_lu5
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_lu5` is a English model originally trained by lu5.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_lu5_en_5.5.1_3.0_1738095640417.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_lu5_en_5.5.1_3.0_1738095640417.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_lu5","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_lu5","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_lu5|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.9 MB|
+
+## References
+
+https://huggingface.co/lu5/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_lu5_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_lu5_pipeline_en.md
new file mode 100644
index 00000000000000..6110824127f4df
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_lu5_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_lu5_pipeline pipeline SwinForImageClassification from lu5
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_lu5_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_lu5_pipeline` is a English model originally trained by lu5.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_lu5_pipeline_en_5.5.1_3.0_1738095651111.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_lu5_pipeline_en_5.5.1_3.0_1738095651111.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_lu5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_lu5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_lu5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.9 MB|
+
+## References
+
+https://huggingface.co/lu5/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_marthakk_en.md b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_marthakk_en.md
new file mode 100644
index 00000000000000..1cd8b2d112d437
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_marthakk_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_marthakk SwinForImageClassification from marthakk
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_marthakk
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_marthakk` is a English model originally trained by marthakk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_marthakk_en_5.5.1_3.0_1738095036371.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_marthakk_en_5.5.1_3.0_1738095036371.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_marthakk","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_marthakk","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_marthakk|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/marthakk/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_marthakk_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_marthakk_pipeline_en.md
new file mode 100644
index 00000000000000..9775d04ee6f129
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_marthakk_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_marthakk_pipeline pipeline SwinForImageClassification from marthakk
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_marthakk_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_marthakk_pipeline` is a English model originally trained by marthakk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_marthakk_pipeline_en_5.5.1_3.0_1738095047393.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_marthakk_pipeline_en_5.5.1_3.0_1738095047393.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_marthakk_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_marthakk_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_marthakk_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/marthakk/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_taohu88_en.md b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_taohu88_en.md
new file mode 100644
index 00000000000000..3cf24e0134b0cc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_taohu88_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_taohu88 SwinForImageClassification from taohu88
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_taohu88
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_taohu88` is a English model originally trained by taohu88.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_taohu88_en_5.5.1_3.0_1738095248817.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_taohu88_en_5.5.1_3.0_1738095248817.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_taohu88","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_taohu88","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_taohu88|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/taohu88/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_taohu88_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_taohu88_pipeline_en.md
new file mode 100644
index 00000000000000..445b67be4b9135
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_taohu88_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_taohu88_pipeline pipeline SwinForImageClassification from taohu88
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_taohu88_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_taohu88_pipeline` is a English model originally trained by taohu88.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_taohu88_pipeline_en_5.5.1_3.0_1738095260283.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_taohu88_pipeline_en_5.5.1_3.0_1738095260283.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_taohu88_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_taohu88_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_taohu88_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/taohu88/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_tdhcuong_en.md b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_tdhcuong_en.md
new file mode 100644
index 00000000000000..142c112d2e5530
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_tdhcuong_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_tdhcuong SwinForImageClassification from tdhcuong
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_tdhcuong
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_tdhcuong` is a English model originally trained by tdhcuong.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_tdhcuong_en_5.5.1_3.0_1738095449903.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_tdhcuong_en_5.5.1_3.0_1738095449903.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_eurosat_tdhcuong","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_eurosat_tdhcuong","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_tdhcuong|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/tdhcuong/swin-tiny-patch4-window7-224-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_tdhcuong_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_tdhcuong_pipeline_en.md
new file mode 100644
index 00000000000000..aa0e2753991e8d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_eurosat_tdhcuong_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_eurosat_tdhcuong_pipeline pipeline SwinForImageClassification from tdhcuong
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_eurosat_tdhcuong_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_eurosat_tdhcuong_pipeline` is a English model originally trained by tdhcuong.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_tdhcuong_pipeline_en_5.5.1_3.0_1738095460804.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_eurosat_tdhcuong_pipeline_en_5.5.1_3.0_1738095460804.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_tdhcuong_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_eurosat_tdhcuong_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_eurosat_tdhcuong_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/tdhcuong/swin-tiny-patch4-window7-224-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_karim155_en.md b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_karim155_en.md
new file mode 100644
index 00000000000000..9061461937ae3f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_karim155_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_karim155 SwinForImageClassification from karim155
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_karim155
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_karim155` is a English model originally trained by karim155.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_karim155_en_5.5.1_3.0_1738095819535.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_karim155_en_5.5.1_3.0_1738095819535.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_karim155","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_karim155","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_karim155|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/karim155/swin-tiny-patch4-window7-224-finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_karim155_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_karim155_pipeline_en.md
new file mode 100644
index 00000000000000..c48f67669dfa6c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_karim155_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_karim155_pipeline pipeline SwinForImageClassification from karim155
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_karim155_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_karim155_pipeline` is a English model originally trained by karim155.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_karim155_pipeline_en_5.5.1_3.0_1738095829691.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_karim155_pipeline_en_5.5.1_3.0_1738095829691.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_karim155_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_karim155_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_karim155_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/karim155/swin-tiny-patch4-window7-224-finetuned
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_plot_images_en.md b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_plot_images_en.md
new file mode 100644
index 00000000000000..678e8b8d3410ce
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_plot_images_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_plot_images SwinForImageClassification from qzheng75
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_plot_images
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_plot_images` is a English model originally trained by qzheng75.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_plot_images_en_5.5.1_3.0_1738095844911.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_plot_images_en_5.5.1_3.0_1738095844911.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_plot_images","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_plot_images","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_plot_images|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/qzheng75/swin-tiny-patch4-window7-224-finetuned-plot-images
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_plot_images_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_plot_images_pipeline_en.md
new file mode 100644
index 00000000000000..f7402d1e492edb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_plot_images_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_plot_images_pipeline pipeline SwinForImageClassification from qzheng75
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_plot_images_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_plot_images_pipeline` is a English model originally trained by qzheng75.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_plot_images_pipeline_en_5.5.1_3.0_1738095855193.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_plot_images_pipeline_en_5.5.1_3.0_1738095855193.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_plot_images_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_plot_images_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_plot_images_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/qzheng75/swin-tiny-patch4-window7-224-finetuned-plot-images
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_skin_cancer_funkeys2_en.md b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_skin_cancer_funkeys2_en.md
new file mode 100644
index 00000000000000..8e25e8ae99f62a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_skin_cancer_funkeys2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_skin_cancer_funkeys2 SwinForImageClassification from funkeys2
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_skin_cancer_funkeys2
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_skin_cancer_funkeys2` is a English model originally trained by funkeys2.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_skin_cancer_funkeys2_en_5.5.1_3.0_1738095393516.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_skin_cancer_funkeys2_en_5.5.1_3.0_1738095393516.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_skin_cancer_funkeys2","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_skin_cancer_funkeys2","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_skin_cancer_funkeys2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/funkeys2/swin-tiny-patch4-window7-224-finetuned-skin-cancer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_skin_cancer_funkeys2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_skin_cancer_funkeys2_pipeline_en.md
new file mode 100644
index 00000000000000..32af8374235b55
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_skin_cancer_funkeys2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_skin_cancer_funkeys2_pipeline pipeline SwinForImageClassification from funkeys2
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_skin_cancer_funkeys2_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_skin_cancer_funkeys2_pipeline` is a English model originally trained by funkeys2.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_skin_cancer_funkeys2_pipeline_en_5.5.1_3.0_1738095404102.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_skin_cancer_funkeys2_pipeline_en_5.5.1_3.0_1738095404102.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_skin_cancer_funkeys2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_skin_cancer_funkeys2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_skin_cancer_funkeys2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/funkeys2/swin-tiny-patch4-window7-224-finetuned-skin-cancer
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_woody_en.md b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_woody_en.md
new file mode 100644
index 00000000000000..c40cf7397e29ba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_woody_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_woody SwinForImageClassification from Alex-VisTas
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_woody
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_woody` is a English model originally trained by Alex-VisTas.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_woody_en_5.5.1_3.0_1738095036151.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_woody_en_5.5.1_3.0_1738095036151.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_finetuned_woody","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_finetuned_woody","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_woody|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/Alex-VisTas/swin-tiny-patch4-window7-224-finetuned-woody
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_woody_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_woody_pipeline_en.md
new file mode 100644
index 00000000000000..c3af137566b99e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_finetuned_woody_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_finetuned_woody_pipeline pipeline SwinForImageClassification from Alex-VisTas
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_finetuned_woody_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_finetuned_woody_pipeline` is a English model originally trained by Alex-VisTas.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_woody_pipeline_en_5.5.1_3.0_1738095053002.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_finetuned_woody_pipeline_en_5.5.1_3.0_1738095053002.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_woody_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_finetuned_woody_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_finetuned_woody_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/Alex-VisTas/swin-tiny-patch4-window7-224-finetuned-woody
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_pruned_0_4_finetuned_eurosat_en.md b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_pruned_0_4_finetuned_eurosat_en.md
new file mode 100644
index 00000000000000..c65af3f3a9183d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_pruned_0_4_finetuned_eurosat_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_pruned_0_4_finetuned_eurosat SwinForImageClassification from 2022happy
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_pruned_0_4_finetuned_eurosat
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_pruned_0_4_finetuned_eurosat` is a English model originally trained by 2022happy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_pruned_0_4_finetuned_eurosat_en_5.5.1_3.0_1738095717834.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_pruned_0_4_finetuned_eurosat_en_5.5.1_3.0_1738095717834.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_tiny_patch4_window7_224_pruned_0_4_finetuned_eurosat","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_tiny_patch4_window7_224_pruned_0_4_finetuned_eurosat","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_pruned_0_4_finetuned_eurosat|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.1 MB|
+
+## References
+
+https://huggingface.co/2022happy/swin-tiny-patch4-window7-224-pruned-0.4-finetuned-eurosat
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_pruned_0_4_finetuned_eurosat_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_pruned_0_4_finetuned_eurosat_pipeline_en.md
new file mode 100644
index 00000000000000..ef36b700f95ffe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-swin_tiny_patch4_window7_224_pruned_0_4_finetuned_eurosat_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_tiny_patch4_window7_224_pruned_0_4_finetuned_eurosat_pipeline pipeline SwinForImageClassification from 2022happy
+author: John Snow Labs
+name: swin_tiny_patch4_window7_224_pruned_0_4_finetuned_eurosat_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_tiny_patch4_window7_224_pruned_0_4_finetuned_eurosat_pipeline` is a English model originally trained by 2022happy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_pruned_0_4_finetuned_eurosat_pipeline_en_5.5.1_3.0_1738095728775.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_tiny_patch4_window7_224_pruned_0_4_finetuned_eurosat_pipeline_en_5.5.1_3.0_1738095728775.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_tiny_patch4_window7_224_pruned_0_4_finetuned_eurosat_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_tiny_patch4_window7_224_pruned_0_4_finetuned_eurosat_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_tiny_patch4_window7_224_pruned_0_4_finetuned_eurosat_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.1 MB|
+
+## References
+
+https://huggingface.co/2022happy/swin-tiny-patch4-window7-224-pruned-0.4-finetuned-eurosat
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-swin_transformer_results_en.md b/docs/_posts/ahmedlone127/2025-01-28-swin_transformer_results_en.md
new file mode 100644
index 00000000000000..733163a83ac217
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-swin_transformer_results_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_transformer_results SwinForImageClassification from hamnabint
+author: John Snow Labs
+name: swin_transformer_results
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_transformer_results` is a English model originally trained by hamnabint.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_transformer_results_en_5.5.1_3.0_1738095349959.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_transformer_results_en_5.5.1_3.0_1738095349959.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_transformer_results","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_transformer_results","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_transformer_results|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/hamnabint/swin-transformer-results
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-swin_transformer_results_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-swin_transformer_results_pipeline_en.md
new file mode 100644
index 00000000000000..34ede6a014cff2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-swin_transformer_results_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_transformer_results_pipeline pipeline SwinForImageClassification from hamnabint
+author: John Snow Labs
+name: swin_transformer_results_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_transformer_results_pipeline` is a English model originally trained by hamnabint.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_transformer_results_pipeline_en_5.5.1_3.0_1738095360381.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_transformer_results_pipeline_en_5.5.1_3.0_1738095360381.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_transformer_results_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_transformer_results_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_transformer_results_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/hamnabint/swin-transformer-results
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-swin_try_en.md b/docs/_posts/ahmedlone127/2025-01-28-swin_try_en.md
new file mode 100644
index 00000000000000..563e27e85fafe9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-swin_try_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swin_try SwinForImageClassification from HITMYM
+author: John Snow Labs
+name: swin_try
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_try` is a English model originally trained by HITMYM.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_try_en_5.5.1_3.0_1738095772262.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_try_en_5.5.1_3.0_1738095772262.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swin_try","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swin_try","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_try|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|206.3 MB|
+
+## References
+
+https://huggingface.co/HITMYM/swin_try
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-swin_try_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-swin_try_pipeline_en.md
new file mode 100644
index 00000000000000..95bdee002bc582
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-swin_try_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swin_try_pipeline pipeline SwinForImageClassification from HITMYM
+author: John Snow Labs
+name: swin_try_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swin_try_pipeline` is a English model originally trained by HITMYM.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swin_try_pipeline_en_5.5.1_3.0_1738095783541.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swin_try_pipeline_en_5.5.1_3.0_1738095783541.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swin_try_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swin_try_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swin_try_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.4 MB|
+
+## References
+
+https://huggingface.co/HITMYM/swin_try
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-swint_en.md b/docs/_posts/ahmedlone127/2025-01-28-swint_en.md
new file mode 100644
index 00000000000000..a546082aba0045
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-swint_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English swint SwinForImageClassification from bucuralexandra
+author: John Snow Labs
+name: swint
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swint` is a English model originally trained by bucuralexandra.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swint_en_5.5.1_3.0_1738095761886.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swint_en_5.5.1_3.0_1738095761886.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""swint","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("swint","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swint|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|212.1 MB|
+
+## References
+
+https://huggingface.co/bucuralexandra/SwinT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-swint_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-swint_pipeline_en.md
new file mode 100644
index 00000000000000..724873fc87a751
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-swint_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English swint_pipeline pipeline SwinForImageClassification from bucuralexandra
+author: John Snow Labs
+name: swint_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swint_pipeline` is a English model originally trained by bucuralexandra.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swint_pipeline_en_5.5.1_3.0_1738095772708.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swint_pipeline_en_5.5.1_3.0_1738095772708.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("swint_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swint_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swint_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|212.1 MB|
+
+## References
+
+https://huggingface.co/bucuralexandra/SwinT
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-t5_advanced_paraphrase_model_v2_en.md b/docs/_posts/ahmedlone127/2025-01-28-t5_advanced_paraphrase_model_v2_en.md
new file mode 100644
index 00000000000000..091cb1ca5b921f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-t5_advanced_paraphrase_model_v2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_advanced_paraphrase_model_v2 T5Transformer from HariModelMaven
+author: John Snow Labs
+name: t5_advanced_paraphrase_model_v2
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_advanced_paraphrase_model_v2` is a English model originally trained by HariModelMaven.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_advanced_paraphrase_model_v2_en_5.5.1_3.0_1738073115510.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_advanced_paraphrase_model_v2_en_5.5.1_3.0_1738073115510.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_advanced_paraphrase_model_v2","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_advanced_paraphrase_model_v2", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_advanced_paraphrase_model_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|288.6 MB|
+
+## References
+
+https://huggingface.co/HariModelMaven/T5-Advanced_Paraphrase_Model_V2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-t5_advanced_paraphrase_model_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-t5_advanced_paraphrase_model_v2_pipeline_en.md
new file mode 100644
index 00000000000000..1880a7ed502d36
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-t5_advanced_paraphrase_model_v2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_advanced_paraphrase_model_v2_pipeline pipeline T5Transformer from HariModelMaven
+author: John Snow Labs
+name: t5_advanced_paraphrase_model_v2_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_advanced_paraphrase_model_v2_pipeline` is a English model originally trained by HariModelMaven.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_advanced_paraphrase_model_v2_pipeline_en_5.5.1_3.0_1738073129748.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_advanced_paraphrase_model_v2_pipeline_en_5.5.1_3.0_1738073129748.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_advanced_paraphrase_model_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_advanced_paraphrase_model_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_advanced_paraphrase_model_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|288.6 MB|
+
+## References
+
+https://huggingface.co/HariModelMaven/T5-Advanced_Paraphrase_Model_V2
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-t5_base_ecom_qa_en.md b/docs/_posts/ahmedlone127/2025-01-28-t5_base_ecom_qa_en.md
new file mode 100644
index 00000000000000..0861518c7d225b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-t5_base_ecom_qa_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_base_ecom_qa T5Transformer from Vinayak1699
+author: John Snow Labs
+name: t5_base_ecom_qa
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_base_ecom_qa` is a English model originally trained by Vinayak1699.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_base_ecom_qa_en_5.5.1_3.0_1738032761765.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_base_ecom_qa_en_5.5.1_3.0_1738032761765.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_base_ecom_qa","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_base_ecom_qa", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_base_ecom_qa|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|911.7 MB|
+
+## References
+
+https://huggingface.co/Vinayak1699/t5-base-ecom-qa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-t5_base_ecom_qa_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-t5_base_ecom_qa_pipeline_en.md
new file mode 100644
index 00000000000000..1fa41fd3aa5fdc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-t5_base_ecom_qa_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_base_ecom_qa_pipeline pipeline T5Transformer from Vinayak1699
+author: John Snow Labs
+name: t5_base_ecom_qa_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_base_ecom_qa_pipeline` is a English model originally trained by Vinayak1699.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_base_ecom_qa_pipeline_en_5.5.1_3.0_1738032808234.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_base_ecom_qa_pipeline_en_5.5.1_3.0_1738032808234.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_base_ecom_qa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_base_ecom_qa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_base_ecom_qa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|911.7 MB|
+
+## References
+
+https://huggingface.co/Vinayak1699/t5-base-ecom-qa
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-t5_base_mixsub_tsonga_en.md b/docs/_posts/ahmedlone127/2025-01-28-t5_base_mixsub_tsonga_en.md
new file mode 100644
index 00000000000000..10e16a7a13c537
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-t5_base_mixsub_tsonga_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_base_mixsub_tsonga T5Transformer from TRnlp
+author: John Snow Labs
+name: t5_base_mixsub_tsonga
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_base_mixsub_tsonga` is a English model originally trained by TRnlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_base_mixsub_tsonga_en_5.5.1_3.0_1738092819033.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_base_mixsub_tsonga_en_5.5.1_3.0_1738092819033.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_base_mixsub_tsonga","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_base_mixsub_tsonga", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_base_mixsub_tsonga|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|907.5 MB|
+
+## References
+
+https://huggingface.co/TRnlp/T5-base-MixSub-TS
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-t5_base_mixsub_tsonga_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-t5_base_mixsub_tsonga_pipeline_en.md
new file mode 100644
index 00000000000000..90dd025cf365bc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-t5_base_mixsub_tsonga_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_base_mixsub_tsonga_pipeline pipeline T5Transformer from TRnlp
+author: John Snow Labs
+name: t5_base_mixsub_tsonga_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_base_mixsub_tsonga_pipeline` is a English model originally trained by TRnlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_base_mixsub_tsonga_pipeline_en_5.5.1_3.0_1738092867299.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_base_mixsub_tsonga_pipeline_en_5.5.1_3.0_1738092867299.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_base_mixsub_tsonga_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_base_mixsub_tsonga_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_base_mixsub_tsonga_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|907.5 MB|
+
+## References
+
+https://huggingface.co/TRnlp/T5-base-MixSub-TS
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-t5_fine_tuned_jfleg_en.md b/docs/_posts/ahmedlone127/2025-01-28-t5_fine_tuned_jfleg_en.md
new file mode 100644
index 00000000000000..ef56a0ec925726
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-t5_fine_tuned_jfleg_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_fine_tuned_jfleg T5Transformer from buketugurlu
+author: John Snow Labs
+name: t5_fine_tuned_jfleg
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_fine_tuned_jfleg` is a English model originally trained by buketugurlu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_fine_tuned_jfleg_en_5.5.1_3.0_1738094489078.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_fine_tuned_jfleg_en_5.5.1_3.0_1738094489078.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_fine_tuned_jfleg","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_fine_tuned_jfleg", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_fine_tuned_jfleg|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|474.1 MB|
+
+## References
+
+https://huggingface.co/buketugurlu/t5-fine-tuned-jfleg
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-t5_fine_tuned_jfleg_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-t5_fine_tuned_jfleg_pipeline_en.md
new file mode 100644
index 00000000000000..f72626d5eaf939
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-t5_fine_tuned_jfleg_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_fine_tuned_jfleg_pipeline pipeline T5Transformer from buketugurlu
+author: John Snow Labs
+name: t5_fine_tuned_jfleg_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_fine_tuned_jfleg_pipeline` is a English model originally trained by buketugurlu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_fine_tuned_jfleg_pipeline_en_5.5.1_3.0_1738094639255.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_fine_tuned_jfleg_pipeline_en_5.5.1_3.0_1738094639255.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_fine_tuned_jfleg_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_fine_tuned_jfleg_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_fine_tuned_jfleg_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|474.1 MB|
+
+## References
+
+https://huggingface.co/buketugurlu/t5-fine-tuned-jfleg
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-t5_keyphrase_extraction_en.md b/docs/_posts/ahmedlone127/2025-01-28-t5_keyphrase_extraction_en.md
new file mode 100644
index 00000000000000..d30fc1c97cb249
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-t5_keyphrase_extraction_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_keyphrase_extraction T5Transformer from breadbowl
+author: John Snow Labs
+name: t5_keyphrase_extraction
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_keyphrase_extraction` is a English model originally trained by breadbowl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_keyphrase_extraction_en_5.5.1_3.0_1738093526086.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_keyphrase_extraction_en_5.5.1_3.0_1738093526086.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_keyphrase_extraction","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_keyphrase_extraction", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_keyphrase_extraction|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|474.1 MB|
+
+## References
+
+https://huggingface.co/breadbowl/t5-keyphrase-extraction
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-t5_keyphrase_extraction_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-t5_keyphrase_extraction_pipeline_en.md
new file mode 100644
index 00000000000000..d19f65bfa8ec5d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-t5_keyphrase_extraction_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_keyphrase_extraction_pipeline pipeline T5Transformer from breadbowl
+author: John Snow Labs
+name: t5_keyphrase_extraction_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_keyphrase_extraction_pipeline` is a English model originally trained by breadbowl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_keyphrase_extraction_pipeline_en_5.5.1_3.0_1738093678397.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_keyphrase_extraction_pipeline_en_5.5.1_3.0_1738093678397.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_keyphrase_extraction_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_keyphrase_extraction_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_keyphrase_extraction_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|474.1 MB|
+
+## References
+
+https://huggingface.co/breadbowl/t5-keyphrase-extraction
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-t5_large_inf2for_music_en.md b/docs/_posts/ahmedlone127/2025-01-28-t5_large_inf2for_music_en.md
new file mode 100644
index 00000000000000..faa95faa40f488
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-t5_large_inf2for_music_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_large_inf2for_music T5Transformer from ggallipoli
+author: John Snow Labs
+name: t5_large_inf2for_music
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_large_inf2for_music` is a English model originally trained by ggallipoli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_large_inf2for_music_en_5.5.1_3.0_1738092381824.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_large_inf2for_music_en_5.5.1_3.0_1738092381824.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_large_inf2for_music","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_large_inf2for_music", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_large_inf2for_music|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|2.9 GB|
+
+## References
+
+https://huggingface.co/ggallipoli/t5-large_inf2for_music
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-t5_large_inf2for_music_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-t5_large_inf2for_music_pipeline_en.md
new file mode 100644
index 00000000000000..9948e3e76af546
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-t5_large_inf2for_music_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_large_inf2for_music_pipeline pipeline T5Transformer from ggallipoli
+author: John Snow Labs
+name: t5_large_inf2for_music_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_large_inf2for_music_pipeline` is a English model originally trained by ggallipoli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_large_inf2for_music_pipeline_en_5.5.1_3.0_1738092516584.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_large_inf2for_music_pipeline_en_5.5.1_3.0_1738092516584.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_large_inf2for_music_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_large_inf2for_music_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_large_inf2for_music_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|2.9 GB|
+
+## References
+
+https://huggingface.co/ggallipoli/t5-large_inf2for_music
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-t5_meid3v2_afterpretrainthennoisybt_maltese_english_2_en.md b/docs/_posts/ahmedlone127/2025-01-28-t5_meid3v2_afterpretrainthennoisybt_maltese_english_2_en.md
new file mode 100644
index 00000000000000..f70bd5785ccb16
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-t5_meid3v2_afterpretrainthennoisybt_maltese_english_2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_meid3v2_afterpretrainthennoisybt_maltese_english_2 T5Transformer from mateiaassAI
+author: John Snow Labs
+name: t5_meid3v2_afterpretrainthennoisybt_maltese_english_2
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_meid3v2_afterpretrainthennoisybt_maltese_english_2` is a English model originally trained by mateiaassAI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_meid3v2_afterpretrainthennoisybt_maltese_english_2_en_5.5.1_3.0_1738073679190.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_meid3v2_afterpretrainthennoisybt_maltese_english_2_en_5.5.1_3.0_1738073679190.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_meid3v2_afterpretrainthennoisybt_maltese_english_2","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_meid3v2_afterpretrainthennoisybt_maltese_english_2", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_meid3v2_afterpretrainthennoisybt_maltese_english_2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/mateiaassAI/T5_MEID3v2-AfterPreTrainThenNoisyBT_MT_EN_2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-t5_meid3v2_afterpretrainthennoisybt_maltese_english_2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-t5_meid3v2_afterpretrainthennoisybt_maltese_english_2_pipeline_en.md
new file mode 100644
index 00000000000000..81d0fbc05f552c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-t5_meid3v2_afterpretrainthennoisybt_maltese_english_2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_meid3v2_afterpretrainthennoisybt_maltese_english_2_pipeline pipeline T5Transformer from mateiaassAI
+author: John Snow Labs
+name: t5_meid3v2_afterpretrainthennoisybt_maltese_english_2_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_meid3v2_afterpretrainthennoisybt_maltese_english_2_pipeline` is a English model originally trained by mateiaassAI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_meid3v2_afterpretrainthennoisybt_maltese_english_2_pipeline_en_5.5.1_3.0_1738073742231.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_meid3v2_afterpretrainthennoisybt_maltese_english_2_pipeline_en_5.5.1_3.0_1738073742231.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_meid3v2_afterpretrainthennoisybt_maltese_english_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_meid3v2_afterpretrainthennoisybt_maltese_english_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_meid3v2_afterpretrainthennoisybt_maltese_english_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/mateiaassAI/T5_MEID3v2-AfterPreTrainThenNoisyBT_MT_EN_2
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-t5_meid3v2_afterptthennoisybt_maltese_english_ronacc_16_en.md b/docs/_posts/ahmedlone127/2025-01-28-t5_meid3v2_afterptthennoisybt_maltese_english_ronacc_16_en.md
new file mode 100644
index 00000000000000..22e8a7f6b26b60
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-t5_meid3v2_afterptthennoisybt_maltese_english_ronacc_16_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_meid3v2_afterptthennoisybt_maltese_english_ronacc_16 T5Transformer from mateiaassAI
+author: John Snow Labs
+name: t5_meid3v2_afterptthennoisybt_maltese_english_ronacc_16
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_meid3v2_afterptthennoisybt_maltese_english_ronacc_16` is a English model originally trained by mateiaassAI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_meid3v2_afterptthennoisybt_maltese_english_ronacc_16_en_5.5.1_3.0_1738073134686.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_meid3v2_afterptthennoisybt_maltese_english_ronacc_16_en_5.5.1_3.0_1738073134686.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_meid3v2_afterptthennoisybt_maltese_english_ronacc_16","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_meid3v2_afterptthennoisybt_maltese_english_ronacc_16", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_meid3v2_afterptthennoisybt_maltese_english_ronacc_16|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/mateiaassAI/T5_MEID3v2-AfterPTThenNoisyBT_MT_EN-RONACC-16
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-t5_meid3v2_afterptthennoisybt_maltese_english_ronacc_16_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-t5_meid3v2_afterptthennoisybt_maltese_english_ronacc_16_pipeline_en.md
new file mode 100644
index 00000000000000..73bd53089af600
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-t5_meid3v2_afterptthennoisybt_maltese_english_ronacc_16_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_meid3v2_afterptthennoisybt_maltese_english_ronacc_16_pipeline pipeline T5Transformer from mateiaassAI
+author: John Snow Labs
+name: t5_meid3v2_afterptthennoisybt_maltese_english_ronacc_16_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_meid3v2_afterptthennoisybt_maltese_english_ronacc_16_pipeline` is a English model originally trained by mateiaassAI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_meid3v2_afterptthennoisybt_maltese_english_ronacc_16_pipeline_en_5.5.1_3.0_1738073196931.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_meid3v2_afterptthennoisybt_maltese_english_ronacc_16_pipeline_en_5.5.1_3.0_1738073196931.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_meid3v2_afterptthennoisybt_maltese_english_ronacc_16_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_meid3v2_afterptthennoisybt_maltese_english_ronacc_16_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_meid3v2_afterptthennoisybt_maltese_english_ronacc_16_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/mateiaassAI/T5_MEID3v2-AfterPTThenNoisyBT_MT_EN-RONACC-16
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-t5_samsum_model_sam_en.md b/docs/_posts/ahmedlone127/2025-01-28-t5_samsum_model_sam_en.md
new file mode 100644
index 00000000000000..6c1f19df8e0535
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-t5_samsum_model_sam_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_samsum_model_sam T5Transformer from SamZzzzz
+author: John Snow Labs
+name: t5_samsum_model_sam
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_samsum_model_sam` is a English model originally trained by SamZzzzz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_samsum_model_sam_en_5.5.1_3.0_1738070968788.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_samsum_model_sam_en_5.5.1_3.0_1738070968788.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_samsum_model_sam","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_samsum_model_sam", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_samsum_model_sam|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|260.0 MB|
+
+## References
+
+https://huggingface.co/SamZzzzz/t5_samsum_model_sam
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-t5_samsum_model_sam_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-t5_samsum_model_sam_pipeline_en.md
new file mode 100644
index 00000000000000..1e2f8215deae14
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-t5_samsum_model_sam_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_samsum_model_sam_pipeline pipeline T5Transformer from SamZzzzz
+author: John Snow Labs
+name: t5_samsum_model_sam_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_samsum_model_sam_pipeline` is a English model originally trained by SamZzzzz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_samsum_model_sam_pipeline_en_5.5.1_3.0_1738070987374.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_samsum_model_sam_pipeline_en_5.5.1_3.0_1738070987374.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_samsum_model_sam_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_samsum_model_sam_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_samsum_model_sam_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|260.0 MB|
+
+## References
+
+https://huggingface.co/SamZzzzz/t5_samsum_model_sam
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-t5_seqtoseq_en.md b/docs/_posts/ahmedlone127/2025-01-28-t5_seqtoseq_en.md
new file mode 100644
index 00000000000000..badfea46b06a99
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-t5_seqtoseq_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_seqtoseq T5Transformer from evelynkol
+author: John Snow Labs
+name: t5_seqtoseq
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_seqtoseq` is a English model originally trained by evelynkol.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_seqtoseq_en_5.5.1_3.0_1738071881353.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_seqtoseq_en_5.5.1_3.0_1738071881353.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_seqtoseq","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_seqtoseq", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_seqtoseq|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|279.2 MB|
+
+## References
+
+https://huggingface.co/evelynkol/t5_seqtoseq
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-t5_seqtoseq_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-t5_seqtoseq_pipeline_en.md
new file mode 100644
index 00000000000000..57229aa5bce1ab
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-t5_seqtoseq_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_seqtoseq_pipeline pipeline T5Transformer from evelynkol
+author: John Snow Labs
+name: t5_seqtoseq_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_seqtoseq_pipeline` is a English model originally trained by evelynkol.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_seqtoseq_pipeline_en_5.5.1_3.0_1738071896603.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_seqtoseq_pipeline_en_5.5.1_3.0_1738071896603.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_seqtoseq_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_seqtoseq_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_seqtoseq_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|279.2 MB|
+
+## References
+
+https://huggingface.co/evelynkol/t5_seqtoseq
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-t5_small_fine_tuned_bbc_en.md b/docs/_posts/ahmedlone127/2025-01-28-t5_small_fine_tuned_bbc_en.md
new file mode 100644
index 00000000000000..e1a0927c278e8b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-t5_small_fine_tuned_bbc_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_small_fine_tuned_bbc T5Transformer from BRUNOKRISTI
+author: John Snow Labs
+name: t5_small_fine_tuned_bbc
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_fine_tuned_bbc` is a English model originally trained by BRUNOKRISTI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_fine_tuned_bbc_en_5.5.1_3.0_1738033412656.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_fine_tuned_bbc_en_5.5.1_3.0_1738033412656.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_small_fine_tuned_bbc","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_small_fine_tuned_bbc", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_fine_tuned_bbc|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|287.1 MB|
+
+## References
+
+https://huggingface.co/BRUNOKRISTI/t5-small-fine-tuned-bbc
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-t5_small_fine_tuned_bbc_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-t5_small_fine_tuned_bbc_pipeline_en.md
new file mode 100644
index 00000000000000..15fa769114e95c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-t5_small_fine_tuned_bbc_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_small_fine_tuned_bbc_pipeline pipeline T5Transformer from BRUNOKRISTI
+author: John Snow Labs
+name: t5_small_fine_tuned_bbc_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_fine_tuned_bbc_pipeline` is a English model originally trained by BRUNOKRISTI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_fine_tuned_bbc_pipeline_en_5.5.1_3.0_1738033427413.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_fine_tuned_bbc_pipeline_en_5.5.1_3.0_1738033427413.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_small_fine_tuned_bbc_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_small_fine_tuned_bbc_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_fine_tuned_bbc_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|287.1 MB|
+
+## References
+
+https://huggingface.co/BRUNOKRISTI/t5-small-fine-tuned-bbc
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-t5_small_fine_tuned_merged_mixed_dataset_en.md b/docs/_posts/ahmedlone127/2025-01-28-t5_small_fine_tuned_merged_mixed_dataset_en.md
new file mode 100644
index 00000000000000..bd95fdbdecaba6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-t5_small_fine_tuned_merged_mixed_dataset_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_small_fine_tuned_merged_mixed_dataset T5Transformer from BRUNOKRISTI
+author: John Snow Labs
+name: t5_small_fine_tuned_merged_mixed_dataset
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_fine_tuned_merged_mixed_dataset` is a English model originally trained by BRUNOKRISTI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_fine_tuned_merged_mixed_dataset_en_5.5.1_3.0_1738091574286.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_fine_tuned_merged_mixed_dataset_en_5.5.1_3.0_1738091574286.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_small_fine_tuned_merged_mixed_dataset","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_small_fine_tuned_merged_mixed_dataset", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_fine_tuned_merged_mixed_dataset|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|286.4 MB|
+
+## References
+
+https://huggingface.co/BRUNOKRISTI/t5-small-fine-tuned-merged-mixed-dataset
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-t5_small_fine_tuned_merged_mixed_dataset_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-t5_small_fine_tuned_merged_mixed_dataset_pipeline_en.md
new file mode 100644
index 00000000000000..3626a1acd1d852
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-t5_small_fine_tuned_merged_mixed_dataset_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_small_fine_tuned_merged_mixed_dataset_pipeline pipeline T5Transformer from BRUNOKRISTI
+author: John Snow Labs
+name: t5_small_fine_tuned_merged_mixed_dataset_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_fine_tuned_merged_mixed_dataset_pipeline` is a English model originally trained by BRUNOKRISTI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_fine_tuned_merged_mixed_dataset_pipeline_en_5.5.1_3.0_1738091590499.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_fine_tuned_merged_mixed_dataset_pipeline_en_5.5.1_3.0_1738091590499.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_small_fine_tuned_merged_mixed_dataset_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_small_fine_tuned_merged_mixed_dataset_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_fine_tuned_merged_mixed_dataset_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|286.4 MB|
+
+## References
+
+https://huggingface.co/BRUNOKRISTI/t5-small-fine-tuned-merged-mixed-dataset
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-t5_small_fine_tuned_model_2_en.md b/docs/_posts/ahmedlone127/2025-01-28-t5_small_fine_tuned_model_2_en.md
new file mode 100644
index 00000000000000..fbefe53c55a46e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-t5_small_fine_tuned_model_2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_small_fine_tuned_model_2 T5Transformer from imhereforthememes
+author: John Snow Labs
+name: t5_small_fine_tuned_model_2
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_fine_tuned_model_2` is a English model originally trained by imhereforthememes.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_fine_tuned_model_2_en_5.5.1_3.0_1738093942334.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_fine_tuned_model_2_en_5.5.1_3.0_1738093942334.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_small_fine_tuned_model_2","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_small_fine_tuned_model_2", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_fine_tuned_model_2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|837.9 KB|
+
+## References
+
+https://huggingface.co/imhereforthememes/t5-small-fine-tuned_model_2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-t5_small_fine_tuned_model_2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-t5_small_fine_tuned_model_2_pipeline_en.md
new file mode 100644
index 00000000000000..bd127425226783
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-t5_small_fine_tuned_model_2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_small_fine_tuned_model_2_pipeline pipeline T5Transformer from imhereforthememes
+author: John Snow Labs
+name: t5_small_fine_tuned_model_2_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_fine_tuned_model_2_pipeline` is a English model originally trained by imhereforthememes.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_fine_tuned_model_2_pipeline_en_5.5.1_3.0_1738093943571.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_fine_tuned_model_2_pipeline_en_5.5.1_3.0_1738093943571.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_small_fine_tuned_model_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_small_fine_tuned_model_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_fine_tuned_model_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|841.1 KB|
+
+## References
+
+https://huggingface.co/imhereforthememes/t5-small-fine-tuned_model_2
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-t5_small_finetuned_cnndaily_en.md b/docs/_posts/ahmedlone127/2025-01-28-t5_small_finetuned_cnndaily_en.md
new file mode 100644
index 00000000000000..643b7fd02b7010
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-t5_small_finetuned_cnndaily_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_small_finetuned_cnndaily T5Transformer from SteadySurfdom
+author: John Snow Labs
+name: t5_small_finetuned_cnndaily
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_finetuned_cnndaily` is a English model originally trained by SteadySurfdom.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_finetuned_cnndaily_en_5.5.1_3.0_1738070998713.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_finetuned_cnndaily_en_5.5.1_3.0_1738070998713.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_small_finetuned_cnndaily","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_small_finetuned_cnndaily", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_finetuned_cnndaily|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|148.0 MB|
+
+## References
+
+https://huggingface.co/SteadySurfdom/t5-small-finetuned-cnndaily
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-t5_small_finetuned_cnndaily_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-t5_small_finetuned_cnndaily_pipeline_en.md
new file mode 100644
index 00000000000000..216941d2a56943
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-t5_small_finetuned_cnndaily_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_small_finetuned_cnndaily_pipeline pipeline T5Transformer from SteadySurfdom
+author: John Snow Labs
+name: t5_small_finetuned_cnndaily_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_finetuned_cnndaily_pipeline` is a English model originally trained by SteadySurfdom.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_finetuned_cnndaily_pipeline_en_5.5.1_3.0_1738071045489.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_finetuned_cnndaily_pipeline_en_5.5.1_3.0_1738071045489.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_small_finetuned_cnndaily_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_small_finetuned_cnndaily_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_finetuned_cnndaily_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|148.0 MB|
+
+## References
+
+https://huggingface.co/SteadySurfdom/t5-small-finetuned-cnndaily
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-t5_small_finetuned_samsum_ncantalupa_en.md b/docs/_posts/ahmedlone127/2025-01-28-t5_small_finetuned_samsum_ncantalupa_en.md
new file mode 100644
index 00000000000000..80b261a2c92e54
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-t5_small_finetuned_samsum_ncantalupa_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_small_finetuned_samsum_ncantalupa T5Transformer from ncantalupa
+author: John Snow Labs
+name: t5_small_finetuned_samsum_ncantalupa
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_finetuned_samsum_ncantalupa` is a English model originally trained by ncantalupa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_finetuned_samsum_ncantalupa_en_5.5.1_3.0_1738092897367.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_finetuned_samsum_ncantalupa_en_5.5.1_3.0_1738092897367.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_small_finetuned_samsum_ncantalupa","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_small_finetuned_samsum_ncantalupa", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_finetuned_samsum_ncantalupa|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|279.1 MB|
+
+## References
+
+https://huggingface.co/ncantalupa/t5-small-finetuned-samsum
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-t5_small_finetuned_samsum_ncantalupa_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-t5_small_finetuned_samsum_ncantalupa_pipeline_en.md
new file mode 100644
index 00000000000000..58442a0f7bf543
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-t5_small_finetuned_samsum_ncantalupa_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_small_finetuned_samsum_ncantalupa_pipeline pipeline T5Transformer from ncantalupa
+author: John Snow Labs
+name: t5_small_finetuned_samsum_ncantalupa_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_finetuned_samsum_ncantalupa_pipeline` is a English model originally trained by ncantalupa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_finetuned_samsum_ncantalupa_pipeline_en_5.5.1_3.0_1738092913865.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_finetuned_samsum_ncantalupa_pipeline_en_5.5.1_3.0_1738092913865.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_small_finetuned_samsum_ncantalupa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_small_finetuned_samsum_ncantalupa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_finetuned_samsum_ncantalupa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|279.1 MB|
+
+## References
+
+https://huggingface.co/ncantalupa/t5-small-finetuned-samsum
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-t5_small_finetuned_titlegen_en.md b/docs/_posts/ahmedlone127/2025-01-28-t5_small_finetuned_titlegen_en.md
new file mode 100644
index 00000000000000..5a6587cb9e6ee5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-t5_small_finetuned_titlegen_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_small_finetuned_titlegen T5Transformer from itskavya
+author: John Snow Labs
+name: t5_small_finetuned_titlegen
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_finetuned_titlegen` is a English model originally trained by itskavya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_finetuned_titlegen_en_5.5.1_3.0_1738030426950.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_finetuned_titlegen_en_5.5.1_3.0_1738030426950.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_small_finetuned_titlegen","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_small_finetuned_titlegen", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_finetuned_titlegen|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|284.5 MB|
+
+## References
+
+https://huggingface.co/itskavya/t5-small-finetuned-titlegen
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-t5_small_finetuned_titlegen_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-t5_small_finetuned_titlegen_pipeline_en.md
new file mode 100644
index 00000000000000..779e1d79be4dd5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-t5_small_finetuned_titlegen_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_small_finetuned_titlegen_pipeline pipeline T5Transformer from itskavya
+author: John Snow Labs
+name: t5_small_finetuned_titlegen_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_finetuned_titlegen_pipeline` is a English model originally trained by itskavya.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_finetuned_titlegen_pipeline_en_5.5.1_3.0_1738030448072.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_finetuned_titlegen_pipeline_en_5.5.1_3.0_1738030448072.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_small_finetuned_titlegen_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_small_finetuned_titlegen_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_finetuned_titlegen_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|284.5 MB|
+
+## References
+
+https://huggingface.co/itskavya/t5-small-finetuned-titlegen
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-t5_small_inf2for_family_en.md b/docs/_posts/ahmedlone127/2025-01-28-t5_small_inf2for_family_en.md
new file mode 100644
index 00000000000000..0829367152a2e9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-t5_small_inf2for_family_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_small_inf2for_family T5Transformer from ggallipoli
+author: John Snow Labs
+name: t5_small_inf2for_family
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_inf2for_family` is a English model originally trained by ggallipoli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_inf2for_family_en_5.5.1_3.0_1738032579972.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_inf2for_family_en_5.5.1_3.0_1738032579972.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_small_inf2for_family","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_small_inf2for_family", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_inf2for_family|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|287.7 MB|
+
+## References
+
+https://huggingface.co/ggallipoli/t5-small_inf2for_family
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-t5_small_inf2for_family_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-t5_small_inf2for_family_pipeline_en.md
new file mode 100644
index 00000000000000..94d39351df8f7f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-t5_small_inf2for_family_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_small_inf2for_family_pipeline pipeline T5Transformer from ggallipoli
+author: John Snow Labs
+name: t5_small_inf2for_family_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_inf2for_family_pipeline` is a English model originally trained by ggallipoli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_inf2for_family_pipeline_en_5.5.1_3.0_1738032594789.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_inf2for_family_pipeline_en_5.5.1_3.0_1738032594789.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_small_inf2for_family_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_small_inf2for_family_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_inf2for_family_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|287.7 MB|
+
+## References
+
+https://huggingface.co/ggallipoli/t5-small_inf2for_family
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-t5_small_neg2pos_en.md b/docs/_posts/ahmedlone127/2025-01-28-t5_small_neg2pos_en.md
new file mode 100644
index 00000000000000..6e7a1560ed358f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-t5_small_neg2pos_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_small_neg2pos T5Transformer from ggallipoli
+author: John Snow Labs
+name: t5_small_neg2pos
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_neg2pos` is a English model originally trained by ggallipoli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_neg2pos_en_5.5.1_3.0_1738093445177.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_neg2pos_en_5.5.1_3.0_1738093445177.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_small_neg2pos","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_small_neg2pos", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_neg2pos|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|288.6 MB|
+
+## References
+
+https://huggingface.co/ggallipoli/t5-small_neg2pos
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-t5_small_neg2pos_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-t5_small_neg2pos_pipeline_en.md
new file mode 100644
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--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-t5_small_neg2pos_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_small_neg2pos_pipeline pipeline T5Transformer from ggallipoli
+author: John Snow Labs
+name: t5_small_neg2pos_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_neg2pos_pipeline` is a English model originally trained by ggallipoli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_neg2pos_pipeline_en_5.5.1_3.0_1738093459630.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_neg2pos_pipeline_en_5.5.1_3.0_1738093459630.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_small_neg2pos_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_small_neg2pos_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_neg2pos_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|288.6 MB|
+
+## References
+
+https://huggingface.co/ggallipoli/t5-small_neg2pos
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-t5_small_rafahorn03_en.md b/docs/_posts/ahmedlone127/2025-01-28-t5_small_rafahorn03_en.md
new file mode 100644
index 00000000000000..03a2d1cfa1acb3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-t5_small_rafahorn03_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_small_rafahorn03 T5Transformer from rafahorn03
+author: John Snow Labs
+name: t5_small_rafahorn03
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_rafahorn03` is a English model originally trained by rafahorn03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_rafahorn03_en_5.5.1_3.0_1738032396867.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_rafahorn03_en_5.5.1_3.0_1738032396867.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_small_rafahorn03","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_small_rafahorn03", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_rafahorn03|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|278.2 MB|
+
+## References
+
+https://huggingface.co/rafahorn03/t5-small
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-t5_small_rafahorn03_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-t5_small_rafahorn03_pipeline_en.md
new file mode 100644
index 00000000000000..f24a5d2a2a47e8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-t5_small_rafahorn03_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_small_rafahorn03_pipeline pipeline T5Transformer from rafahorn03
+author: John Snow Labs
+name: t5_small_rafahorn03_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_rafahorn03_pipeline` is a English model originally trained by rafahorn03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_rafahorn03_pipeline_en_5.5.1_3.0_1738032411938.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_rafahorn03_pipeline_en_5.5.1_3.0_1738032411938.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_small_rafahorn03_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_small_rafahorn03_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_rafahorn03_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|278.2 MB|
+
+## References
+
+https://huggingface.co/rafahorn03/t5-small
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-t5_small_sum_dpo_177k_16_1ep_en.md b/docs/_posts/ahmedlone127/2025-01-28-t5_small_sum_dpo_177k_16_1ep_en.md
new file mode 100644
index 00000000000000..49f782be047c19
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-t5_small_sum_dpo_177k_16_1ep_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_small_sum_dpo_177k_16_1ep T5Transformer from Muadil
+author: John Snow Labs
+name: t5_small_sum_dpo_177k_16_1ep
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_sum_dpo_177k_16_1ep` is a English model originally trained by Muadil.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_177k_16_1ep_en_5.5.1_3.0_1738093154939.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_177k_16_1ep_en_5.5.1_3.0_1738093154939.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_small_sum_dpo_177k_16_1ep","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_small_sum_dpo_177k_16_1ep", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_sum_dpo_177k_16_1ep|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|156.4 MB|
+
+## References
+
+https://huggingface.co/Muadil/t5-small_sum_DPO_177k_16_1ep
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-t5_small_sum_dpo_177k_16_1ep_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-t5_small_sum_dpo_177k_16_1ep_pipeline_en.md
new file mode 100644
index 00000000000000..02a0b87e158290
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-t5_small_sum_dpo_177k_16_1ep_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_small_sum_dpo_177k_16_1ep_pipeline pipeline T5Transformer from Muadil
+author: John Snow Labs
+name: t5_small_sum_dpo_177k_16_1ep_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_sum_dpo_177k_16_1ep_pipeline` is a English model originally trained by Muadil.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_177k_16_1ep_pipeline_en_5.5.1_3.0_1738093202859.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_177k_16_1ep_pipeline_en_5.5.1_3.0_1738093202859.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_small_sum_dpo_177k_16_1ep_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_small_sum_dpo_177k_16_1ep_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_sum_dpo_177k_16_1ep_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|156.4 MB|
+
+## References
+
+https://huggingface.co/Muadil/t5-small_sum_DPO_177k_16_1ep
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-t5_small_sum_dpo_50k_2_1ep_en.md b/docs/_posts/ahmedlone127/2025-01-28-t5_small_sum_dpo_50k_2_1ep_en.md
new file mode 100644
index 00000000000000..b84bcd599f854e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-t5_small_sum_dpo_50k_2_1ep_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_small_sum_dpo_50k_2_1ep T5Transformer from Muadil
+author: John Snow Labs
+name: t5_small_sum_dpo_50k_2_1ep
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_sum_dpo_50k_2_1ep` is a English model originally trained by Muadil.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_50k_2_1ep_en_5.5.1_3.0_1738033227120.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_50k_2_1ep_en_5.5.1_3.0_1738033227120.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_small_sum_dpo_50k_2_1ep","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_small_sum_dpo_50k_2_1ep", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_sum_dpo_50k_2_1ep|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|156.5 MB|
+
+## References
+
+https://huggingface.co/Muadil/t5-small_sum_DPO_50k_2_1ep
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-t5_small_sum_dpo_50k_2_1ep_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-t5_small_sum_dpo_50k_2_1ep_pipeline_en.md
new file mode 100644
index 00000000000000..549ad028e259d6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-t5_small_sum_dpo_50k_2_1ep_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_small_sum_dpo_50k_2_1ep_pipeline pipeline T5Transformer from Muadil
+author: John Snow Labs
+name: t5_small_sum_dpo_50k_2_1ep_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_sum_dpo_50k_2_1ep_pipeline` is a English model originally trained by Muadil.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_50k_2_1ep_pipeline_en_5.5.1_3.0_1738033275423.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_50k_2_1ep_pipeline_en_5.5.1_3.0_1738033275423.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_small_sum_dpo_50k_2_1ep_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_small_sum_dpo_50k_2_1ep_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_sum_dpo_50k_2_1ep_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|156.5 MB|
+
+## References
+
+https://huggingface.co/Muadil/t5-small_sum_DPO_50k_2_1ep
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-t5_small_sum_dpo_50k_32_1ep_en.md b/docs/_posts/ahmedlone127/2025-01-28-t5_small_sum_dpo_50k_32_1ep_en.md
new file mode 100644
index 00000000000000..0b66ef65d20c94
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-t5_small_sum_dpo_50k_32_1ep_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_small_sum_dpo_50k_32_1ep T5Transformer from Muadil
+author: John Snow Labs
+name: t5_small_sum_dpo_50k_32_1ep
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_sum_dpo_50k_32_1ep` is a English model originally trained by Muadil.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_50k_32_1ep_en_5.5.1_3.0_1738033231864.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_50k_32_1ep_en_5.5.1_3.0_1738033231864.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_small_sum_dpo_50k_32_1ep","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_small_sum_dpo_50k_32_1ep", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_sum_dpo_50k_32_1ep|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|155.3 MB|
+
+## References
+
+https://huggingface.co/Muadil/t5-small_sum_DPO_50k_32_1ep
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-t5_small_sum_dpo_50k_32_1ep_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-t5_small_sum_dpo_50k_32_1ep_pipeline_en.md
new file mode 100644
index 00000000000000..a4e3c46e2ebbf1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-t5_small_sum_dpo_50k_32_1ep_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_small_sum_dpo_50k_32_1ep_pipeline pipeline T5Transformer from Muadil
+author: John Snow Labs
+name: t5_small_sum_dpo_50k_32_1ep_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_sum_dpo_50k_32_1ep_pipeline` is a English model originally trained by Muadil.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_50k_32_1ep_pipeline_en_5.5.1_3.0_1738033280313.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_sum_dpo_50k_32_1ep_pipeline_en_5.5.1_3.0_1738033280313.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_small_sum_dpo_50k_32_1ep_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_small_sum_dpo_50k_32_1ep_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_sum_dpo_50k_32_1ep_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|155.3 MB|
+
+## References
+
+https://huggingface.co/Muadil/t5-small_sum_DPO_50k_32_1ep
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-t5_spell_checker_en.md b/docs/_posts/ahmedlone127/2025-01-28-t5_spell_checker_en.md
new file mode 100644
index 00000000000000..839e885cda7ba4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-t5_spell_checker_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English t5_spell_checker T5Transformer from yanagriw
+author: John Snow Labs
+name: t5_spell_checker
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_spell_checker` is a English model originally trained by yanagriw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_spell_checker_en_5.5.1_3.0_1738093826253.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_spell_checker_en_5.5.1_3.0_1738093826253.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("t5_spell_checker","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("t5_spell_checker", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_spell_checker|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|924.2 MB|
+
+## References
+
+https://huggingface.co/yanagriw/T5-spell-checker
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-t5_spell_checker_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-t5_spell_checker_pipeline_en.md
new file mode 100644
index 00000000000000..45fcb5f7a8fca3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-t5_spell_checker_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_spell_checker_pipeline pipeline T5Transformer from yanagriw
+author: John Snow Labs
+name: t5_spell_checker_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_spell_checker_pipeline` is a English model originally trained by yanagriw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_spell_checker_pipeline_en_5.5.1_3.0_1738093872833.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_spell_checker_pipeline_en_5.5.1_3.0_1738093872833.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_spell_checker_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_spell_checker_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_spell_checker_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|924.2 MB|
+
+## References
+
+https://huggingface.co/yanagriw/T5-spell-checker
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-taiyi_vit_87m_d_en.md b/docs/_posts/ahmedlone127/2025-01-28-taiyi_vit_87m_d_en.md
new file mode 100644
index 00000000000000..9bee57b113df61
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-taiyi_vit_87m_d_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English taiyi_vit_87m_d ViTForImageClassification from IDEA-CCNL
+author: John Snow Labs
+name: taiyi_vit_87m_d
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`taiyi_vit_87m_d` is a English model originally trained by IDEA-CCNL.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/taiyi_vit_87m_d_en_5.5.1_3.0_1738022725162.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/taiyi_vit_87m_d_en_5.5.1_3.0_1738022725162.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""taiyi_vit_87m_d","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("taiyi_vit_87m_d","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|taiyi_vit_87m_d|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|324.2 MB|
+
+## References
+
+https://huggingface.co/IDEA-CCNL/Taiyi-vit-87M-D
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-taiyi_vit_87m_d_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-taiyi_vit_87m_d_pipeline_en.md
new file mode 100644
index 00000000000000..ed6b15467fc1c0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-taiyi_vit_87m_d_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English taiyi_vit_87m_d_pipeline pipeline ViTForImageClassification from IDEA-CCNL
+author: John Snow Labs
+name: taiyi_vit_87m_d_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`taiyi_vit_87m_d_pipeline` is a English model originally trained by IDEA-CCNL.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/taiyi_vit_87m_d_pipeline_en_5.5.1_3.0_1738022743678.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/taiyi_vit_87m_d_pipeline_en_5.5.1_3.0_1738022743678.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("taiyi_vit_87m_d_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("taiyi_vit_87m_d_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|taiyi_vit_87m_d_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|324.2 MB|
+
+## References
+
+https://huggingface.co/IDEA-CCNL/Taiyi-vit-87M-D
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-tapt_bb_v1_1_epoch1_en.md b/docs/_posts/ahmedlone127/2025-01-28-tapt_bb_v1_1_epoch1_en.md
new file mode 100644
index 00000000000000..191d071b198119
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-tapt_bb_v1_1_epoch1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English tapt_bb_v1_1_epoch1 BertEmbeddings from hyoo14
+author: John Snow Labs
+name: tapt_bb_v1_1_epoch1
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tapt_bb_v1_1_epoch1` is a English model originally trained by hyoo14.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tapt_bb_v1_1_epoch1_en_5.5.1_3.0_1738096531658.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tapt_bb_v1_1_epoch1_en_5.5.1_3.0_1738096531658.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("tapt_bb_v1_1_epoch1","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("tapt_bb_v1_1_epoch1","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tapt_bb_v1_1_epoch1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|403.1 MB|
+
+## References
+
+https://huggingface.co/hyoo14/TAPT_BB-v1.1_epoch1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-tapt_bb_v1_1_epoch1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-tapt_bb_v1_1_epoch1_pipeline_en.md
new file mode 100644
index 00000000000000..afa2d0879437f8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-tapt_bb_v1_1_epoch1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English tapt_bb_v1_1_epoch1_pipeline pipeline BertEmbeddings from hyoo14
+author: John Snow Labs
+name: tapt_bb_v1_1_epoch1_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tapt_bb_v1_1_epoch1_pipeline` is a English model originally trained by hyoo14.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tapt_bb_v1_1_epoch1_pipeline_en_5.5.1_3.0_1738096551729.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tapt_bb_v1_1_epoch1_pipeline_en_5.5.1_3.0_1738096551729.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("tapt_bb_v1_1_epoch1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("tapt_bb_v1_1_epoch1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tapt_bb_v1_1_epoch1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.1 MB|
+
+## References
+
+https://huggingface.co/hyoo14/TAPT_BB-v1.1_epoch1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-test_jennyc_en.md b/docs/_posts/ahmedlone127/2025-01-28-test_jennyc_en.md
new file mode 100644
index 00000000000000..06235e6fa8b225
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-test_jennyc_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English test_jennyc BertForQuestionAnswering from jennyc
+author: John Snow Labs
+name: test_jennyc
+date: 2025-01-28
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_jennyc` is a English model originally trained by jennyc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_jennyc_en_5.5.1_3.0_1738062450025.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_jennyc_en_5.5.1_3.0_1738062450025.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("test_jennyc","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("test_jennyc", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_jennyc|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/jennyc/test
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-test_jennyc_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-test_jennyc_pipeline_en.md
new file mode 100644
index 00000000000000..c66ff768ad28aa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-test_jennyc_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English test_jennyc_pipeline pipeline BertForQuestionAnswering from jennyc
+author: John Snow Labs
+name: test_jennyc_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_jennyc_pipeline` is a English model originally trained by jennyc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_jennyc_pipeline_en_5.5.1_3.0_1738062470239.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_jennyc_pipeline_en_5.5.1_3.0_1738062470239.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("test_jennyc_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("test_jennyc_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_jennyc_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/jennyc/test
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-test_ninja_en.md b/docs/_posts/ahmedlone127/2025-01-28-test_ninja_en.md
new file mode 100644
index 00000000000000..77a20823962667
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-test_ninja_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English test_ninja BertEmbeddings from ninja
+author: John Snow Labs
+name: test_ninja
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_ninja` is a English model originally trained by ninja.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_ninja_en_5.5.1_3.0_1738057635545.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_ninja_en_5.5.1_3.0_1738057635545.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("test_ninja","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("test_ninja","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_ninja|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/ninja/test
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-test_ninja_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-test_ninja_pipeline_en.md
new file mode 100644
index 00000000000000..078b219bc0ae50
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-test_ninja_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English test_ninja_pipeline pipeline BertEmbeddings from ninja
+author: John Snow Labs
+name: test_ninja_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_ninja_pipeline` is a English model originally trained by ninja.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_ninja_pipeline_en_5.5.1_3.0_1738057661214.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_ninja_pipeline_en_5.5.1_3.0_1738057661214.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("test_ninja_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("test_ninja_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_ninja_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/ninja/test
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-test_training_distbert_en.md b/docs/_posts/ahmedlone127/2025-01-28-test_training_distbert_en.md
new file mode 100644
index 00000000000000..e4f5fa5f32a0e3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-test_training_distbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English test_training_distbert DistilBertForSequenceClassification from hiNik
+author: John Snow Labs
+name: test_training_distbert
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_training_distbert` is a English model originally trained by hiNik.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_training_distbert_en_5.5.1_3.0_1738077876255.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_training_distbert_en_5.5.1_3.0_1738077876255.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("test_training_distbert","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("test_training_distbert", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_training_distbert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/hiNik/test_training_distbert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-test_training_distbert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-test_training_distbert_pipeline_en.md
new file mode 100644
index 00000000000000..4b7e375a915d4b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-test_training_distbert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English test_training_distbert_pipeline pipeline DistilBertForSequenceClassification from hiNik
+author: John Snow Labs
+name: test_training_distbert_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_training_distbert_pipeline` is a English model originally trained by hiNik.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_training_distbert_pipeline_en_5.5.1_3.0_1738077892344.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_training_distbert_pipeline_en_5.5.1_3.0_1738077892344.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("test_training_distbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("test_training_distbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_training_distbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/hiNik/test_training_distbert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-test_triage_en.md b/docs/_posts/ahmedlone127/2025-01-28-test_triage_en.md
new file mode 100644
index 00000000000000..9befe3050f7fae
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-test_triage_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English test_triage SwinForImageClassification from arunboss
+author: John Snow Labs
+name: test_triage
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, swin]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: SwinForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_triage` is a English model originally trained by arunboss.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_triage_en_5.5.1_3.0_1738095147582.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_triage_en_5.5.1_3.0_1738095147582.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = SwinForImageClassification.pretrained(""test_triage","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  SwinForImageClassification.pretrained("test_triage","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_triage|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|207.0 MB|
+
+## References
+
+https://huggingface.co/arunboss/test_triage
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-test_triage_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-test_triage_pipeline_en.md
new file mode 100644
index 00000000000000..1d82f8c85ac0a3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-test_triage_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English test_triage_pipeline pipeline SwinForImageClassification from arunboss
+author: John Snow Labs
+name: test_triage_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained SwinForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_triage_pipeline` is a English model originally trained by arunboss.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_triage_pipeline_en_5.5.1_3.0_1738095159509.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_triage_pipeline_en_5.5.1_3.0_1738095159509.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("test_triage_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("test_triage_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_triage_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|207.0 MB|
+
+## References
+
+https://huggingface.co/arunboss/test_triage
+
+## Included Models
+
+- ImageAssembler
+- SwinForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-the_soft_scum_delerizome_machine_a_thousand_guattaris_en.md b/docs/_posts/ahmedlone127/2025-01-28-the_soft_scum_delerizome_machine_a_thousand_guattaris_en.md
new file mode 100644
index 00000000000000..94e8318b809128
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-the_soft_scum_delerizome_machine_a_thousand_guattaris_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English the_soft_scum_delerizome_machine_a_thousand_guattaris GPT2Transformer from genaforvena
+author: John Snow Labs
+name: the_soft_scum_delerizome_machine_a_thousand_guattaris
+date: 2025-01-28
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`the_soft_scum_delerizome_machine_a_thousand_guattaris` is a English model originally trained by genaforvena.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/the_soft_scum_delerizome_machine_a_thousand_guattaris_en_5.5.1_3.0_1738041920802.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/the_soft_scum_delerizome_machine_a_thousand_guattaris_en_5.5.1_3.0_1738041920802.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("the_soft_scum_delerizome_machine_a_thousand_guattaris","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = GPT2Transformer.pretrained("the_soft_scum_delerizome_machine_a_thousand_guattaris","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|the_soft_scum_delerizome_machine_a_thousand_guattaris|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/genaforvena/the_soft_scum_delerizome_machine_a_thousand_guattaris
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-the_soft_scum_delerizome_machine_a_thousand_guattaris_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-the_soft_scum_delerizome_machine_a_thousand_guattaris_pipeline_en.md
new file mode 100644
index 00000000000000..0d5b59e035d76d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-the_soft_scum_delerizome_machine_a_thousand_guattaris_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English the_soft_scum_delerizome_machine_a_thousand_guattaris_pipeline pipeline GPT2Transformer from genaforvena
+author: John Snow Labs
+name: the_soft_scum_delerizome_machine_a_thousand_guattaris_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`the_soft_scum_delerizome_machine_a_thousand_guattaris_pipeline` is a English model originally trained by genaforvena.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/the_soft_scum_delerizome_machine_a_thousand_guattaris_pipeline_en_5.5.1_3.0_1738041943835.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/the_soft_scum_delerizome_machine_a_thousand_guattaris_pipeline_en_5.5.1_3.0_1738041943835.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("the_soft_scum_delerizome_machine_a_thousand_guattaris_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("the_soft_scum_delerizome_machine_a_thousand_guattaris_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|the_soft_scum_delerizome_machine_a_thousand_guattaris_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.8 MB|
+
+## References
+
+https://huggingface.co/genaforvena/the_soft_scum_delerizome_machine_a_thousand_guattaris
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-tmp_trainer_en.md b/docs/_posts/ahmedlone127/2025-01-28-tmp_trainer_en.md
new file mode 100644
index 00000000000000..ab993e0ee66fae
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-tmp_trainer_en.md
@@ -0,0 +1,96 @@
+---
+layout: model
+title: English tmp_trainer DistilBertForTokenClassification from anyuanay
+author: John Snow Labs
+name: tmp_trainer
+date: 2025-01-28
+tags: [bert, en, open_source, token_classification, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tmp_trainer` is a English model originally trained by anyuanay.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tmp_trainer_en_5.5.1_3.0_1738102031078.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tmp_trainer_en_5.5.1_3.0_1738102031078.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("documents")
+    
+    
+tokenClassifier = DistilBertForTokenClassification.pretrained("tmp_trainer","en") \
+            .setInputCols(["documents","token"]) \
+            .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCol("text") 
+    .setOutputCol("embeddings")
+    
+val tokenClassifier = DistilBertForTokenClassification  
+    .pretrained("tmp_trainer", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tmp_trainer|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+References
+
+References
+
+References
+
+https://huggingface.co/anyuanay/tmp_trainer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-tmp_trainer_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-tmp_trainer_pipeline_en.md
new file mode 100644
index 00000000000000..dfbdc31daa2080
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-tmp_trainer_pipeline_en.md
@@ -0,0 +1,72 @@
+---
+layout: model
+title: English tmp_trainer_pipeline pipeline MarianTransformer from saksornr
+author: John Snow Labs
+name: tmp_trainer_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tmp_trainer_pipeline` is a English model originally trained by saksornr.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tmp_trainer_pipeline_en_5.5.1_3.0_1738102043954.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tmp_trainer_pipeline_en_5.5.1_3.0_1738102043954.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+pipeline = PretrainedPipeline("tmp_trainer_pipeline", lang = "en")
+annotations =  pipeline.transform(df)
+```
+```scala
+val pipeline = new PretrainedPipeline("tmp_trainer_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tmp_trainer_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+References
+
+https://huggingface.co/saksornr/tmp_trainer
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-train_bart_base_en.md b/docs/_posts/ahmedlone127/2025-01-28-train_bart_base_en.md
new file mode 100644
index 00000000000000..961ee3f7dc7d9c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-train_bart_base_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English train_bart_base BartTransformer from dtruong46me
+author: John Snow Labs
+name: train_bart_base
+date: 2025-01-28
+tags: [en, open_source, onnx, text_generation, bart]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BartTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`train_bart_base` is a English model originally trained by dtruong46me.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/train_bart_base_en_5.5.1_3.0_1738086206067.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/train_bart_base_en_5.5.1_3.0_1738086206067.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = BartTransformer.pretrained("train_bart_base","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = BartTransformer.pretrained("train_bart_base","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|train_bart_base|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|810.5 MB|
+
+## References
+
+https://huggingface.co/dtruong46me/train-bart-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-train_bart_base_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-train_bart_base_pipeline_en.md
new file mode 100644
index 00000000000000..15fd9270825d00
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-train_bart_base_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English train_bart_base_pipeline pipeline BartTransformer from dtruong46me
+author: John Snow Labs
+name: train_bart_base_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`train_bart_base_pipeline` is a English model originally trained by dtruong46me.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/train_bart_base_pipeline_en_5.5.1_3.0_1738086246308.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/train_bart_base_pipeline_en_5.5.1_3.0_1738086246308.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("train_bart_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("train_bart_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|train_bart_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|810.5 MB|
+
+## References
+
+https://huggingface.co/dtruong46me/train-bart-base
+
+## Included Models
+
+- DocumentAssembler
+- BartTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-trained_dilibert_sentiment_analysis_en.md b/docs/_posts/ahmedlone127/2025-01-28-trained_dilibert_sentiment_analysis_en.md
new file mode 100644
index 00000000000000..2e3bf4e148dd76
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-trained_dilibert_sentiment_analysis_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English trained_dilibert_sentiment_analysis DistilBertForSequenceClassification from dmo0798
+author: John Snow Labs
+name: trained_dilibert_sentiment_analysis
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`trained_dilibert_sentiment_analysis` is a English model originally trained by dmo0798.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/trained_dilibert_sentiment_analysis_en_5.5.1_3.0_1738077249942.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/trained_dilibert_sentiment_analysis_en_5.5.1_3.0_1738077249942.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("trained_dilibert_sentiment_analysis","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("trained_dilibert_sentiment_analysis", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|trained_dilibert_sentiment_analysis|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/dmo0798/trained_dilibert_sentiment_analysis
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-trained_dilibert_sentiment_analysis_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-trained_dilibert_sentiment_analysis_pipeline_en.md
new file mode 100644
index 00000000000000..d898768acaf99b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-trained_dilibert_sentiment_analysis_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English trained_dilibert_sentiment_analysis_pipeline pipeline DistilBertForSequenceClassification from dmo0798
+author: John Snow Labs
+name: trained_dilibert_sentiment_analysis_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`trained_dilibert_sentiment_analysis_pipeline` is a English model originally trained by dmo0798.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/trained_dilibert_sentiment_analysis_pipeline_en_5.5.1_3.0_1738077262943.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/trained_dilibert_sentiment_analysis_pipeline_en_5.5.1_3.0_1738077262943.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("trained_dilibert_sentiment_analysis_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("trained_dilibert_sentiment_analysis_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|trained_dilibert_sentiment_analysis_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/dmo0798/trained_dilibert_sentiment_analysis
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-travel_t5_small_abraraqeel_en.md b/docs/_posts/ahmedlone127/2025-01-28-travel_t5_small_abraraqeel_en.md
new file mode 100644
index 00000000000000..ba7f62dbad50de
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-travel_t5_small_abraraqeel_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English travel_t5_small_abraraqeel T5Transformer from AbrarAqeel
+author: John Snow Labs
+name: travel_t5_small_abraraqeel
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`travel_t5_small_abraraqeel` is a English model originally trained by AbrarAqeel.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/travel_t5_small_abraraqeel_en_5.5.1_3.0_1738030661498.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/travel_t5_small_abraraqeel_en_5.5.1_3.0_1738030661498.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("travel_t5_small_abraraqeel","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("travel_t5_small_abraraqeel", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|travel_t5_small_abraraqeel|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|275.9 MB|
+
+## References
+
+https://huggingface.co/AbrarAqeel/travel_t5-small
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-travel_t5_small_abraraqeel_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-travel_t5_small_abraraqeel_pipeline_en.md
new file mode 100644
index 00000000000000..d61625ddcce8b7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-travel_t5_small_abraraqeel_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English travel_t5_small_abraraqeel_pipeline pipeline T5Transformer from AbrarAqeel
+author: John Snow Labs
+name: travel_t5_small_abraraqeel_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`travel_t5_small_abraraqeel_pipeline` is a English model originally trained by AbrarAqeel.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/travel_t5_small_abraraqeel_pipeline_en_5.5.1_3.0_1738030677595.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/travel_t5_small_abraraqeel_pipeline_en_5.5.1_3.0_1738030677595.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("travel_t5_small_abraraqeel_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("travel_t5_small_abraraqeel_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|travel_t5_small_abraraqeel_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|275.9 MB|
+
+## References
+
+https://huggingface.co/AbrarAqeel/travel_t5-small
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-udpos_mbert_base_vanilla_en.md b/docs/_posts/ahmedlone127/2025-01-28-udpos_mbert_base_vanilla_en.md
new file mode 100644
index 00000000000000..e128744230d430
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-udpos_mbert_base_vanilla_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English udpos_mbert_base_vanilla BertEmbeddings from boleima
+author: John Snow Labs
+name: udpos_mbert_base_vanilla
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`udpos_mbert_base_vanilla` is a English model originally trained by boleima.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/udpos_mbert_base_vanilla_en_5.5.1_3.0_1738035129690.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/udpos_mbert_base_vanilla_en_5.5.1_3.0_1738035129690.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("udpos_mbert_base_vanilla","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("udpos_mbert_base_vanilla","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|udpos_mbert_base_vanilla|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/boleima/udpos-mbert-base-vanilla
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-udpos_mbert_base_vanilla_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-udpos_mbert_base_vanilla_pipeline_en.md
new file mode 100644
index 00000000000000..a2c306618f3ca7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-udpos_mbert_base_vanilla_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English udpos_mbert_base_vanilla_pipeline pipeline BertEmbeddings from boleima
+author: John Snow Labs
+name: udpos_mbert_base_vanilla_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`udpos_mbert_base_vanilla_pipeline` is a English model originally trained by boleima.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/udpos_mbert_base_vanilla_pipeline_en_5.5.1_3.0_1738035164898.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/udpos_mbert_base_vanilla_pipeline_en_5.5.1_3.0_1738035164898.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("udpos_mbert_base_vanilla_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("udpos_mbert_base_vanilla_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|udpos_mbert_base_vanilla_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/boleima/udpos-mbert-base-vanilla
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-uit_deberta_v3_base_finetuned_en.md b/docs/_posts/ahmedlone127/2025-01-28-uit_deberta_v3_base_finetuned_en.md
new file mode 100644
index 00000000000000..25b1976cc42a11
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-uit_deberta_v3_base_finetuned_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English uit_deberta_v3_base_finetuned DeBertaForSequenceClassification from sercetexam9
+author: John Snow Labs
+name: uit_deberta_v3_base_finetuned
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`uit_deberta_v3_base_finetuned` is a English model originally trained by sercetexam9.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/uit_deberta_v3_base_finetuned_en_5.5.1_3.0_1738041169533.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/uit_deberta_v3_base_finetuned_en_5.5.1_3.0_1738041169533.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("uit_deberta_v3_base_finetuned","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("uit_deberta_v3_base_finetuned", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|uit_deberta_v3_base_finetuned|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|575.2 MB|
+
+## References
+
+https://huggingface.co/sercetexam9/UIT-deberta-v3-base-finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-uit_deberta_v3_base_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-uit_deberta_v3_base_finetuned_pipeline_en.md
new file mode 100644
index 00000000000000..03f7f6850b1b2b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-uit_deberta_v3_base_finetuned_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English uit_deberta_v3_base_finetuned_pipeline pipeline DeBertaForSequenceClassification from sercetexam9
+author: John Snow Labs
+name: uit_deberta_v3_base_finetuned_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`uit_deberta_v3_base_finetuned_pipeline` is a English model originally trained by sercetexam9.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/uit_deberta_v3_base_finetuned_pipeline_en_5.5.1_3.0_1738041232306.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/uit_deberta_v3_base_finetuned_pipeline_en_5.5.1_3.0_1738041232306.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("uit_deberta_v3_base_finetuned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("uit_deberta_v3_base_finetuned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|uit_deberta_v3_base_finetuned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|575.2 MB|
+
+## References
+
+https://huggingface.co/sercetexam9/UIT-deberta-v3-base-finetuned
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-vit5_base_align_translate_en.md b/docs/_posts/ahmedlone127/2025-01-28-vit5_base_align_translate_en.md
new file mode 100644
index 00000000000000..e740055e04c2b0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-vit5_base_align_translate_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English vit5_base_align_translate T5Transformer from phuongntc
+author: John Snow Labs
+name: vit5_base_align_translate
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit5_base_align_translate` is a English model originally trained by phuongntc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit5_base_align_translate_en_5.5.1_3.0_1738073022547.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit5_base_align_translate_en_5.5.1_3.0_1738073022547.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("vit5_base_align_translate","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("vit5_base_align_translate", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit5_base_align_translate|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|922.0 MB|
+
+## References
+
+https://huggingface.co/phuongntc/vit5_base_align_translate
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-vit5_base_align_translate_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-vit5_base_align_translate_pipeline_en.md
new file mode 100644
index 00000000000000..95969a922a3ccc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-vit5_base_align_translate_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit5_base_align_translate_pipeline pipeline T5Transformer from phuongntc
+author: John Snow Labs
+name: vit5_base_align_translate_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit5_base_align_translate_pipeline` is a English model originally trained by phuongntc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit5_base_align_translate_pipeline_en_5.5.1_3.0_1738073075021.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit5_base_align_translate_pipeline_en_5.5.1_3.0_1738073075021.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit5_base_align_translate_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit5_base_align_translate_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit5_base_align_translate_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|922.0 MB|
+
+## References
+
+https://huggingface.co/phuongntc/vit5_base_align_translate
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-vit5_large_align_translate2000_en.md b/docs/_posts/ahmedlone127/2025-01-28-vit5_large_align_translate2000_en.md
new file mode 100644
index 00000000000000..50ffdb6a16f65a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-vit5_large_align_translate2000_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English vit5_large_align_translate2000 T5Transformer from phuongntc
+author: John Snow Labs
+name: vit5_large_align_translate2000
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit5_large_align_translate2000` is a English model originally trained by phuongntc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit5_large_align_translate2000_en_5.5.1_3.0_1738092501996.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit5_large_align_translate2000_en_5.5.1_3.0_1738092501996.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("vit5_large_align_translate2000","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("vit5_large_align_translate2000", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit5_large_align_translate2000|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|3.0 GB|
+
+## References
+
+https://huggingface.co/phuongntc/vit5_large_align_translate2000
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-vit5_large_align_translate2000_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-vit5_large_align_translate2000_pipeline_en.md
new file mode 100644
index 00000000000000..aacb6aa01640a7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-vit5_large_align_translate2000_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit5_large_align_translate2000_pipeline pipeline T5Transformer from phuongntc
+author: John Snow Labs
+name: vit5_large_align_translate2000_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit5_large_align_translate2000_pipeline` is a English model originally trained by phuongntc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit5_large_align_translate2000_pipeline_en_5.5.1_3.0_1738092692355.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit5_large_align_translate2000_pipeline_en_5.5.1_3.0_1738092692355.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit5_large_align_translate2000_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit5_large_align_translate2000_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit5_large_align_translate2000_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|3.0 GB|
+
+## References
+
+https://huggingface.co/phuongntc/vit5_large_align_translate2000
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-vit5_large_dpo_en.md b/docs/_posts/ahmedlone127/2025-01-28-vit5_large_dpo_en.md
new file mode 100644
index 00000000000000..4e4b2b5ec45fba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-vit5_large_dpo_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English vit5_large_dpo T5Transformer from phuongntc
+author: John Snow Labs
+name: vit5_large_dpo
+date: 2025-01-28
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit5_large_dpo` is a English model originally trained by phuongntc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit5_large_dpo_en_5.5.1_3.0_1738031825279.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit5_large_dpo_en_5.5.1_3.0_1738031825279.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("vit5_large_dpo","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("vit5_large_dpo", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit5_large_dpo|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/phuongntc/vit5_large_DPO
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-vit5_large_dpo_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-vit5_large_dpo_pipeline_en.md
new file mode 100644
index 00000000000000..92e23686b9a439
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-vit5_large_dpo_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit5_large_dpo_pipeline pipeline T5Transformer from phuongntc
+author: John Snow Labs
+name: vit5_large_dpo_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit5_large_dpo_pipeline` is a English model originally trained by phuongntc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit5_large_dpo_pipeline_en_5.5.1_3.0_1738032340590.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit5_large_dpo_pipeline_en_5.5.1_3.0_1738032340590.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit5_large_dpo_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit5_large_dpo_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit5_large_dpo_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/phuongntc/vit5_large_DPO
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-vit_384_tongue_image_segmented_augmented_en.md b/docs/_posts/ahmedlone127/2025-01-28-vit_384_tongue_image_segmented_augmented_en.md
new file mode 100644
index 00000000000000..1fca421349d99f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-vit_384_tongue_image_segmented_augmented_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_384_tongue_image_segmented_augmented ViTForImageClassification from e1010101
+author: John Snow Labs
+name: vit_384_tongue_image_segmented_augmented
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_384_tongue_image_segmented_augmented` is a English model originally trained by e1010101.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_384_tongue_image_segmented_augmented_en_5.5.1_3.0_1738022592530.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_384_tongue_image_segmented_augmented_en_5.5.1_3.0_1738022592530.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vit_384_tongue_image_segmented_augmented","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vit_384_tongue_image_segmented_augmented","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_384_tongue_image_segmented_augmented|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|322.4 MB|
+
+## References
+
+https://huggingface.co/e1010101/vit-384-tongue-image-segmented-augmented
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-vit_384_tongue_image_segmented_augmented_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-vit_384_tongue_image_segmented_augmented_pipeline_en.md
new file mode 100644
index 00000000000000..4290dff5367e75
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-vit_384_tongue_image_segmented_augmented_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_384_tongue_image_segmented_augmented_pipeline pipeline ViTForImageClassification from e1010101
+author: John Snow Labs
+name: vit_384_tongue_image_segmented_augmented_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_384_tongue_image_segmented_augmented_pipeline` is a English model originally trained by e1010101.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_384_tongue_image_segmented_augmented_pipeline_en_5.5.1_3.0_1738022616151.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_384_tongue_image_segmented_augmented_pipeline_en_5.5.1_3.0_1738022616151.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_384_tongue_image_segmented_augmented_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_384_tongue_image_segmented_augmented_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_384_tongue_image_segmented_augmented_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|322.4 MB|
+
+## References
+
+https://huggingface.co/e1010101/vit-384-tongue-image-segmented-augmented
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-vit_accident_image_en.md b/docs/_posts/ahmedlone127/2025-01-28-vit_accident_image_en.md
new file mode 100644
index 00000000000000..86725742b9ba7b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-vit_accident_image_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_accident_image ViTForImageClassification from tiya1012
+author: John Snow Labs
+name: vit_accident_image
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_accident_image` is a English model originally trained by tiya1012.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_accident_image_en_5.5.1_3.0_1738023190494.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_accident_image_en_5.5.1_3.0_1738023190494.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vit_accident_image","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vit_accident_image","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_accident_image|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/tiya1012/vit-accident-image
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-vit_accident_image_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-vit_accident_image_pipeline_en.md
new file mode 100644
index 00000000000000..02c999584a5b5b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-vit_accident_image_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_accident_image_pipeline pipeline ViTForImageClassification from tiya1012
+author: John Snow Labs
+name: vit_accident_image_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_accident_image_pipeline` is a English model originally trained by tiya1012.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_accident_image_pipeline_en_5.5.1_3.0_1738023208674.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_accident_image_pipeline_en_5.5.1_3.0_1738023208674.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_accident_image_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_accident_image_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_accident_image_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/tiya1012/vit-accident-image
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-vit_base_25ep_en.md b/docs/_posts/ahmedlone127/2025-01-28-vit_base_25ep_en.md
new file mode 100644
index 00000000000000..0656bc5de88e83
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-vit_base_25ep_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_base_25ep ViTForImageClassification from vuongnhathien
+author: John Snow Labs
+name: vit_base_25ep
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_25ep` is a English model originally trained by vuongnhathien.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_25ep_en_5.5.1_3.0_1738023045327.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_25ep_en_5.5.1_3.0_1738023045327.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vit_base_25ep","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vit_base_25ep","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_25ep|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.4 MB|
+
+## References
+
+https://huggingface.co/vuongnhathien/vit-base-25ep
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-vit_base_25ep_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-vit_base_25ep_pipeline_en.md
new file mode 100644
index 00000000000000..9cb1a0ec596756
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-vit_base_25ep_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_base_25ep_pipeline pipeline ViTForImageClassification from vuongnhathien
+author: John Snow Labs
+name: vit_base_25ep_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_25ep_pipeline` is a English model originally trained by vuongnhathien.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_25ep_pipeline_en_5.5.1_3.0_1738023067903.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_25ep_pipeline_en_5.5.1_3.0_1738023067903.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_base_25ep_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_base_25ep_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_25ep_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.4 MB|
+
+## References
+
+https://huggingface.co/vuongnhathien/vit-base-25ep
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-vit_base_aihub_model_py_en.md b/docs/_posts/ahmedlone127/2025-01-28-vit_base_aihub_model_py_en.md
new file mode 100644
index 00000000000000..ae1818c51ff146
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-vit_base_aihub_model_py_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_base_aihub_model_py ViTForImageClassification from hyeongjin99
+author: John Snow Labs
+name: vit_base_aihub_model_py
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_aihub_model_py` is a English model originally trained by hyeongjin99.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_aihub_model_py_en_5.5.1_3.0_1738023327306.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_aihub_model_py_en_5.5.1_3.0_1738023327306.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vit_base_aihub_model_py","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vit_base_aihub_model_py","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_aihub_model_py|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/hyeongjin99/vit_base_aihub_model_py
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-vit_base_aihub_model_py_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-vit_base_aihub_model_py_pipeline_en.md
new file mode 100644
index 00000000000000..43fc0e94fb6fbf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-vit_base_aihub_model_py_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_base_aihub_model_py_pipeline pipeline ViTForImageClassification from hyeongjin99
+author: John Snow Labs
+name: vit_base_aihub_model_py_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_aihub_model_py_pipeline` is a English model originally trained by hyeongjin99.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_aihub_model_py_pipeline_en_5.5.1_3.0_1738023343997.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_aihub_model_py_pipeline_en_5.5.1_3.0_1738023343997.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_base_aihub_model_py_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_base_aihub_model_py_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_aihub_model_py_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/hyeongjin99/vit_base_aihub_model_py
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-vit_base_mri_ftghz_en.md b/docs/_posts/ahmedlone127/2025-01-28-vit_base_mri_ftghz_en.md
new file mode 100644
index 00000000000000..038a69fb754e83
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-vit_base_mri_ftghz_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_base_mri_ftghz ViTForImageClassification from ftghz
+author: John Snow Labs
+name: vit_base_mri_ftghz
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_mri_ftghz` is a English model originally trained by ftghz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_mri_ftghz_en_5.5.1_3.0_1738022443649.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_mri_ftghz_en_5.5.1_3.0_1738022443649.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vit_base_mri_ftghz","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vit_base_mri_ftghz","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_mri_ftghz|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/ftghz/vit-base-mri
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-vit_base_mri_ftghz_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-vit_base_mri_ftghz_pipeline_en.md
new file mode 100644
index 00000000000000..9c036d40550aab
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-vit_base_mri_ftghz_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_base_mri_ftghz_pipeline pipeline ViTForImageClassification from ftghz
+author: John Snow Labs
+name: vit_base_mri_ftghz_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_mri_ftghz_pipeline` is a English model originally trained by ftghz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_mri_ftghz_pipeline_en_5.5.1_3.0_1738022460156.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_mri_ftghz_pipeline_en_5.5.1_3.0_1738022460156.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_base_mri_ftghz_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_base_mri_ftghz_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_mri_ftghz_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/ftghz/vit-base-mri
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-vit_base_oxford_iiit_pets_shikun_en.md b/docs/_posts/ahmedlone127/2025-01-28-vit_base_oxford_iiit_pets_shikun_en.md
new file mode 100644
index 00000000000000..0e85e2aaccd1f6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-vit_base_oxford_iiit_pets_shikun_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_base_oxford_iiit_pets_shikun ViTForImageClassification from Shikun
+author: John Snow Labs
+name: vit_base_oxford_iiit_pets_shikun
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_oxford_iiit_pets_shikun` is a English model originally trained by Shikun.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_oxford_iiit_pets_shikun_en_5.5.1_3.0_1738022595164.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_oxford_iiit_pets_shikun_en_5.5.1_3.0_1738022595164.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vit_base_oxford_iiit_pets_shikun","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vit_base_oxford_iiit_pets_shikun","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_oxford_iiit_pets_shikun|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.4 MB|
+
+## References
+
+https://huggingface.co/Shikun/vit-base-oxford-iiit-pets
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-vit_base_oxford_iiit_pets_shikun_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-vit_base_oxford_iiit_pets_shikun_pipeline_en.md
new file mode 100644
index 00000000000000..23798a9c10a01f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-vit_base_oxford_iiit_pets_shikun_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_base_oxford_iiit_pets_shikun_pipeline pipeline ViTForImageClassification from Shikun
+author: John Snow Labs
+name: vit_base_oxford_iiit_pets_shikun_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_oxford_iiit_pets_shikun_pipeline` is a English model originally trained by Shikun.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_oxford_iiit_pets_shikun_pipeline_en_5.5.1_3.0_1738022614437.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_oxford_iiit_pets_shikun_pipeline_en_5.5.1_3.0_1738022614437.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_base_oxford_iiit_pets_shikun_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_base_oxford_iiit_pets_shikun_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_oxford_iiit_pets_shikun_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.4 MB|
+
+## References
+
+https://huggingface.co/Shikun/vit-base-oxford-iiit-pets
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-vit_base_oxford_iiit_pets_tranvancuong2597_en.md b/docs/_posts/ahmedlone127/2025-01-28-vit_base_oxford_iiit_pets_tranvancuong2597_en.md
new file mode 100644
index 00000000000000..ee2182bb203fd6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-vit_base_oxford_iiit_pets_tranvancuong2597_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_base_oxford_iiit_pets_tranvancuong2597 ViTForImageClassification from tranvancuong2597
+author: John Snow Labs
+name: vit_base_oxford_iiit_pets_tranvancuong2597
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_oxford_iiit_pets_tranvancuong2597` is a English model originally trained by tranvancuong2597.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_oxford_iiit_pets_tranvancuong2597_en_5.5.1_3.0_1738022987060.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_oxford_iiit_pets_tranvancuong2597_en_5.5.1_3.0_1738022987060.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vit_base_oxford_iiit_pets_tranvancuong2597","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vit_base_oxford_iiit_pets_tranvancuong2597","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_oxford_iiit_pets_tranvancuong2597|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.4 MB|
+
+## References
+
+https://huggingface.co/tranvancuong2597/vit-base-oxford-iiit-pets
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-vit_base_oxford_iiit_pets_tranvancuong2597_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-vit_base_oxford_iiit_pets_tranvancuong2597_pipeline_en.md
new file mode 100644
index 00000000000000..2017f603b8f9b5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-vit_base_oxford_iiit_pets_tranvancuong2597_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_base_oxford_iiit_pets_tranvancuong2597_pipeline pipeline ViTForImageClassification from tranvancuong2597
+author: John Snow Labs
+name: vit_base_oxford_iiit_pets_tranvancuong2597_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_oxford_iiit_pets_tranvancuong2597_pipeline` is a English model originally trained by tranvancuong2597.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_oxford_iiit_pets_tranvancuong2597_pipeline_en_5.5.1_3.0_1738023003266.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_oxford_iiit_pets_tranvancuong2597_pipeline_en_5.5.1_3.0_1738023003266.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_base_oxford_iiit_pets_tranvancuong2597_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_base_oxford_iiit_pets_tranvancuong2597_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_oxford_iiit_pets_tranvancuong2597_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.4 MB|
+
+## References
+
+https://huggingface.co/tranvancuong2597/vit-base-oxford-iiit-pets
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-vit_base_oxford_iiit_pets_uisikdag_en.md b/docs/_posts/ahmedlone127/2025-01-28-vit_base_oxford_iiit_pets_uisikdag_en.md
new file mode 100644
index 00000000000000..fdfa91e030b243
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-vit_base_oxford_iiit_pets_uisikdag_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_base_oxford_iiit_pets_uisikdag ViTForImageClassification from uisikdag
+author: John Snow Labs
+name: vit_base_oxford_iiit_pets_uisikdag
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_oxford_iiit_pets_uisikdag` is a English model originally trained by uisikdag.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_oxford_iiit_pets_uisikdag_en_5.5.1_3.0_1738023233911.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_oxford_iiit_pets_uisikdag_en_5.5.1_3.0_1738023233911.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vit_base_oxford_iiit_pets_uisikdag","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vit_base_oxford_iiit_pets_uisikdag","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_oxford_iiit_pets_uisikdag|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.4 MB|
+
+## References
+
+https://huggingface.co/uisikdag/vit-base-oxford-iiit-pets
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-vit_base_oxford_iiit_pets_uisikdag_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-vit_base_oxford_iiit_pets_uisikdag_pipeline_en.md
new file mode 100644
index 00000000000000..a300007163c210
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-vit_base_oxford_iiit_pets_uisikdag_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_base_oxford_iiit_pets_uisikdag_pipeline pipeline ViTForImageClassification from uisikdag
+author: John Snow Labs
+name: vit_base_oxford_iiit_pets_uisikdag_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_oxford_iiit_pets_uisikdag_pipeline` is a English model originally trained by uisikdag.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_oxford_iiit_pets_uisikdag_pipeline_en_5.5.1_3.0_1738023250490.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_oxford_iiit_pets_uisikdag_pipeline_en_5.5.1_3.0_1738023250490.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_base_oxford_iiit_pets_uisikdag_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_base_oxford_iiit_pets_uisikdag_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_oxford_iiit_pets_uisikdag_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.4 MB|
+
+## References
+
+https://huggingface.co/uisikdag/vit-base-oxford-iiit-pets
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-vit_base_patch16_224_blur_vs_clean_mansee_en.md b/docs/_posts/ahmedlone127/2025-01-28-vit_base_patch16_224_blur_vs_clean_mansee_en.md
new file mode 100644
index 00000000000000..f5d1cd37b3556b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-vit_base_patch16_224_blur_vs_clean_mansee_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_base_patch16_224_blur_vs_clean_mansee ViTForImageClassification from mansee
+author: John Snow Labs
+name: vit_base_patch16_224_blur_vs_clean_mansee
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_patch16_224_blur_vs_clean_mansee` is a English model originally trained by mansee.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_blur_vs_clean_mansee_en_5.5.1_3.0_1738023172259.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_blur_vs_clean_mansee_en_5.5.1_3.0_1738023172259.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vit_base_patch16_224_blur_vs_clean_mansee","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vit_base_patch16_224_blur_vs_clean_mansee","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_patch16_224_blur_vs_clean_mansee|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/mansee/vit-base-patch16-224-blur_vs_clean
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-vit_base_patch16_224_blur_vs_clean_mansee_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-vit_base_patch16_224_blur_vs_clean_mansee_pipeline_en.md
new file mode 100644
index 00000000000000..71a1f01a16ac86
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-vit_base_patch16_224_blur_vs_clean_mansee_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_base_patch16_224_blur_vs_clean_mansee_pipeline pipeline ViTForImageClassification from mansee
+author: John Snow Labs
+name: vit_base_patch16_224_blur_vs_clean_mansee_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_patch16_224_blur_vs_clean_mansee_pipeline` is a English model originally trained by mansee.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_blur_vs_clean_mansee_pipeline_en_5.5.1_3.0_1738023188707.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_blur_vs_clean_mansee_pipeline_en_5.5.1_3.0_1738023188707.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_base_patch16_224_blur_vs_clean_mansee_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_base_patch16_224_blur_vs_clean_mansee_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_patch16_224_blur_vs_clean_mansee_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/mansee/vit-base-patch16-224-blur_vs_clean
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-vit_base_patch16_224_chest_x_ray_en.md b/docs/_posts/ahmedlone127/2025-01-28-vit_base_patch16_224_chest_x_ray_en.md
new file mode 100644
index 00000000000000..a8ec9c70aa8d9a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-vit_base_patch16_224_chest_x_ray_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_base_patch16_224_chest_x_ray ViTForImageClassification from chanelcolgate
+author: John Snow Labs
+name: vit_base_patch16_224_chest_x_ray
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_patch16_224_chest_x_ray` is a English model originally trained by chanelcolgate.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_chest_x_ray_en_5.5.1_3.0_1738023434774.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_chest_x_ray_en_5.5.1_3.0_1738023434774.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vit_base_patch16_224_chest_x_ray","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vit_base_patch16_224_chest_x_ray","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_patch16_224_chest_x_ray|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/chanelcolgate/vit-base-patch16-224-chest-x-ray
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-vit_base_patch16_224_chest_x_ray_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-vit_base_patch16_224_chest_x_ray_pipeline_en.md
new file mode 100644
index 00000000000000..ed2fb7adb2e8ae
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-vit_base_patch16_224_chest_x_ray_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_base_patch16_224_chest_x_ray_pipeline pipeline ViTForImageClassification from chanelcolgate
+author: John Snow Labs
+name: vit_base_patch16_224_chest_x_ray_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_patch16_224_chest_x_ray_pipeline` is a English model originally trained by chanelcolgate.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_chest_x_ray_pipeline_en_5.5.1_3.0_1738023451407.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_chest_x_ray_pipeline_en_5.5.1_3.0_1738023451407.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_base_patch16_224_chest_x_ray_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_base_patch16_224_chest_x_ray_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_patch16_224_chest_x_ray_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/chanelcolgate/vit-base-patch16-224-chest-x-ray
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-vit_base_patch16_224_futurama_image_multilabel_clf_en.md b/docs/_posts/ahmedlone127/2025-01-28-vit_base_patch16_224_futurama_image_multilabel_clf_en.md
new file mode 100644
index 00000000000000..d24c025627d676
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-vit_base_patch16_224_futurama_image_multilabel_clf_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_base_patch16_224_futurama_image_multilabel_clf ViTForImageClassification from DunnBC22
+author: John Snow Labs
+name: vit_base_patch16_224_futurama_image_multilabel_clf
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_patch16_224_futurama_image_multilabel_clf` is a English model originally trained by DunnBC22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_futurama_image_multilabel_clf_en_5.5.1_3.0_1738022723082.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_futurama_image_multilabel_clf_en_5.5.1_3.0_1738022723082.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vit_base_patch16_224_futurama_image_multilabel_clf","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vit_base_patch16_224_futurama_image_multilabel_clf","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_patch16_224_futurama_image_multilabel_clf|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/DunnBC22/vit-base-patch16-224-Futurama_Image_multilabel_clf
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-vit_base_patch16_224_futurama_image_multilabel_clf_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-vit_base_patch16_224_futurama_image_multilabel_clf_pipeline_en.md
new file mode 100644
index 00000000000000..ddbf9882684901
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-vit_base_patch16_224_futurama_image_multilabel_clf_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_base_patch16_224_futurama_image_multilabel_clf_pipeline pipeline ViTForImageClassification from DunnBC22
+author: John Snow Labs
+name: vit_base_patch16_224_futurama_image_multilabel_clf_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_patch16_224_futurama_image_multilabel_clf_pipeline` is a English model originally trained by DunnBC22.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_futurama_image_multilabel_clf_pipeline_en_5.5.1_3.0_1738022741666.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_futurama_image_multilabel_clf_pipeline_en_5.5.1_3.0_1738022741666.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_base_patch16_224_futurama_image_multilabel_clf_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_base_patch16_224_futurama_image_multilabel_clf_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_patch16_224_futurama_image_multilabel_clf_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/DunnBC22/vit-base-patch16-224-Futurama_Image_multilabel_clf
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-vit_base_patch16_224_in21k_cards_base_classifier_defects_finder_en.md b/docs/_posts/ahmedlone127/2025-01-28-vit_base_patch16_224_in21k_cards_base_classifier_defects_finder_en.md
new file mode 100644
index 00000000000000..e20b75d7f19c58
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-vit_base_patch16_224_in21k_cards_base_classifier_defects_finder_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_base_patch16_224_in21k_cards_base_classifier_defects_finder ViTForImageClassification from ansilmbabl
+author: John Snow Labs
+name: vit_base_patch16_224_in21k_cards_base_classifier_defects_finder
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_patch16_224_in21k_cards_base_classifier_defects_finder` is a English model originally trained by ansilmbabl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_in21k_cards_base_classifier_defects_finder_en_5.5.1_3.0_1738022592145.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_in21k_cards_base_classifier_defects_finder_en_5.5.1_3.0_1738022592145.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vit_base_patch16_224_in21k_cards_base_classifier_defects_finder","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vit_base_patch16_224_in21k_cards_base_classifier_defects_finder","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_patch16_224_in21k_cards_base_classifier_defects_finder|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/ansilmbabl/vit-base-patch16-224-in21k-cards-base-classifier-defects-finder
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-vit_base_patch16_224_in21k_cards_base_classifier_defects_finder_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-vit_base_patch16_224_in21k_cards_base_classifier_defects_finder_pipeline_en.md
new file mode 100644
index 00000000000000..dfcab825947052
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-vit_base_patch16_224_in21k_cards_base_classifier_defects_finder_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_base_patch16_224_in21k_cards_base_classifier_defects_finder_pipeline pipeline ViTForImageClassification from ansilmbabl
+author: John Snow Labs
+name: vit_base_patch16_224_in21k_cards_base_classifier_defects_finder_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_patch16_224_in21k_cards_base_classifier_defects_finder_pipeline` is a English model originally trained by ansilmbabl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_in21k_cards_base_classifier_defects_finder_pipeline_en_5.5.1_3.0_1738022616019.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_in21k_cards_base_classifier_defects_finder_pipeline_en_5.5.1_3.0_1738022616019.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_base_patch16_224_in21k_cards_base_classifier_defects_finder_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_base_patch16_224_in21k_cards_base_classifier_defects_finder_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_patch16_224_in21k_cards_base_classifier_defects_finder_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/ansilmbabl/vit-base-patch16-224-in21k-cards-base-classifier-defects-finder
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-vit_base_patch16_224_in21k_cards_june_05_cropping_unfiltered_en.md b/docs/_posts/ahmedlone127/2025-01-28-vit_base_patch16_224_in21k_cards_june_05_cropping_unfiltered_en.md
new file mode 100644
index 00000000000000..ad128d1aa7337c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-vit_base_patch16_224_in21k_cards_june_05_cropping_unfiltered_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_base_patch16_224_in21k_cards_june_05_cropping_unfiltered ViTForImageClassification from ansilmbabl
+author: John Snow Labs
+name: vit_base_patch16_224_in21k_cards_june_05_cropping_unfiltered
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_patch16_224_in21k_cards_june_05_cropping_unfiltered` is a English model originally trained by ansilmbabl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_in21k_cards_june_05_cropping_unfiltered_en_5.5.1_3.0_1738023041184.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_in21k_cards_june_05_cropping_unfiltered_en_5.5.1_3.0_1738023041184.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vit_base_patch16_224_in21k_cards_june_05_cropping_unfiltered","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vit_base_patch16_224_in21k_cards_june_05_cropping_unfiltered","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_patch16_224_in21k_cards_june_05_cropping_unfiltered|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/ansilmbabl/vit-base-patch16-224-in21k-cards-june-05-cropping-unfiltered
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-vit_base_patch16_224_in21k_cards_june_05_cropping_unfiltered_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-vit_base_patch16_224_in21k_cards_june_05_cropping_unfiltered_pipeline_en.md
new file mode 100644
index 00000000000000..11cd1a4ed78296
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-vit_base_patch16_224_in21k_cards_june_05_cropping_unfiltered_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_base_patch16_224_in21k_cards_june_05_cropping_unfiltered_pipeline pipeline ViTForImageClassification from ansilmbabl
+author: John Snow Labs
+name: vit_base_patch16_224_in21k_cards_june_05_cropping_unfiltered_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_patch16_224_in21k_cards_june_05_cropping_unfiltered_pipeline` is a English model originally trained by ansilmbabl.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_in21k_cards_june_05_cropping_unfiltered_pipeline_en_5.5.1_3.0_1738023060829.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_in21k_cards_june_05_cropping_unfiltered_pipeline_en_5.5.1_3.0_1738023060829.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_base_patch16_224_in21k_cards_june_05_cropping_unfiltered_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_base_patch16_224_in21k_cards_june_05_cropping_unfiltered_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_patch16_224_in21k_cards_june_05_cropping_unfiltered_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/ansilmbabl/vit-base-patch16-224-in21k-cards-june-05-cropping-unfiltered
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-vit_base_patch16_224_in21k_finetuned_ct_en.md b/docs/_posts/ahmedlone127/2025-01-28-vit_base_patch16_224_in21k_finetuned_ct_en.md
new file mode 100644
index 00000000000000..106caaa502aa16
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-vit_base_patch16_224_in21k_finetuned_ct_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_base_patch16_224_in21k_finetuned_ct ViTForImageClassification from Manuel-O
+author: John Snow Labs
+name: vit_base_patch16_224_in21k_finetuned_ct
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_patch16_224_in21k_finetuned_ct` is a English model originally trained by Manuel-O.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_in21k_finetuned_ct_en_5.5.1_3.0_1738023576164.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_in21k_finetuned_ct_en_5.5.1_3.0_1738023576164.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vit_base_patch16_224_in21k_finetuned_ct","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vit_base_patch16_224_in21k_finetuned_ct","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_patch16_224_in21k_finetuned_ct|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/Manuel-O/vit-base-patch16-224-in21k-finetuned-CT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-vit_base_patch16_224_in21k_finetuned_ct_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-vit_base_patch16_224_in21k_finetuned_ct_pipeline_en.md
new file mode 100644
index 00000000000000..33e909285913ec
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-vit_base_patch16_224_in21k_finetuned_ct_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_base_patch16_224_in21k_finetuned_ct_pipeline pipeline ViTForImageClassification from Manuel-O
+author: John Snow Labs
+name: vit_base_patch16_224_in21k_finetuned_ct_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_patch16_224_in21k_finetuned_ct_pipeline` is a English model originally trained by Manuel-O.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_in21k_finetuned_ct_pipeline_en_5.5.1_3.0_1738023592113.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_in21k_finetuned_ct_pipeline_en_5.5.1_3.0_1738023592113.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_base_patch16_224_in21k_finetuned_ct_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_base_patch16_224_in21k_finetuned_ct_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_patch16_224_in21k_finetuned_ct_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/Manuel-O/vit-base-patch16-224-in21k-finetuned-CT
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-vit_base_patch16_224_ru5_10_8_en.md b/docs/_posts/ahmedlone127/2025-01-28-vit_base_patch16_224_ru5_10_8_en.md
new file mode 100644
index 00000000000000..fc980224d734ca
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-vit_base_patch16_224_ru5_10_8_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_base_patch16_224_ru5_10_8 ViTForImageClassification from Augusto777
+author: John Snow Labs
+name: vit_base_patch16_224_ru5_10_8
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_patch16_224_ru5_10_8` is a English model originally trained by Augusto777.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_ru5_10_8_en_5.5.1_3.0_1738023349793.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_ru5_10_8_en_5.5.1_3.0_1738023349793.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vit_base_patch16_224_ru5_10_8","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vit_base_patch16_224_ru5_10_8","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_patch16_224_ru5_10_8|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/Augusto777/vit-base-patch16-224-RU5-10-8
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-vit_base_patch16_224_ru5_10_8_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-vit_base_patch16_224_ru5_10_8_pipeline_en.md
new file mode 100644
index 00000000000000..9965ba85d692da
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-vit_base_patch16_224_ru5_10_8_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_base_patch16_224_ru5_10_8_pipeline pipeline ViTForImageClassification from Augusto777
+author: John Snow Labs
+name: vit_base_patch16_224_ru5_10_8_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_patch16_224_ru5_10_8_pipeline` is a English model originally trained by Augusto777.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_ru5_10_8_pipeline_en_5.5.1_3.0_1738023366348.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_ru5_10_8_pipeline_en_5.5.1_3.0_1738023366348.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_base_patch16_224_ru5_10_8_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_base_patch16_224_ru5_10_8_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_patch16_224_ru5_10_8_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/Augusto777/vit-base-patch16-224-RU5-10-8
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-vit_base_patch16_224_venda_ub_en.md b/docs/_posts/ahmedlone127/2025-01-28-vit_base_patch16_224_venda_ub_en.md
new file mode 100644
index 00000000000000..95495dae40d831
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-vit_base_patch16_224_venda_ub_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_base_patch16_224_venda_ub ViTForImageClassification from Augusto777
+author: John Snow Labs
+name: vit_base_patch16_224_venda_ub
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_patch16_224_venda_ub` is a English model originally trained by Augusto777.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_venda_ub_en_5.5.1_3.0_1738022486957.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_venda_ub_en_5.5.1_3.0_1738022486957.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vit_base_patch16_224_venda_ub","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vit_base_patch16_224_venda_ub","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_patch16_224_venda_ub|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/Augusto777/vit-base-patch16-224-ve-Ub
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-vit_base_patch16_224_venda_ub_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-vit_base_patch16_224_venda_ub_pipeline_en.md
new file mode 100644
index 00000000000000..8a238bf6e0ff88
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-vit_base_patch16_224_venda_ub_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_base_patch16_224_venda_ub_pipeline pipeline ViTForImageClassification from Augusto777
+author: John Snow Labs
+name: vit_base_patch16_224_venda_ub_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_base_patch16_224_venda_ub_pipeline` is a English model originally trained by Augusto777.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_venda_ub_pipeline_en_5.5.1_3.0_1738022503489.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_base_patch16_224_venda_ub_pipeline_en_5.5.1_3.0_1738022503489.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_base_patch16_224_venda_ub_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_base_patch16_224_venda_ub_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_base_patch16_224_venda_ub_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/Augusto777/vit-base-patch16-224-ve-Ub
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-vit_epochs5_batch32_lr5e_05_size224_tiles2_seed2_q3_dropout_v2_en.md b/docs/_posts/ahmedlone127/2025-01-28-vit_epochs5_batch32_lr5e_05_size224_tiles2_seed2_q3_dropout_v2_en.md
new file mode 100644
index 00000000000000..41f7b714fac669
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-vit_epochs5_batch32_lr5e_05_size224_tiles2_seed2_q3_dropout_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_epochs5_batch32_lr5e_05_size224_tiles2_seed2_q3_dropout_v2 ViTForImageClassification from Omriy123
+author: John Snow Labs
+name: vit_epochs5_batch32_lr5e_05_size224_tiles2_seed2_q3_dropout_v2
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_epochs5_batch32_lr5e_05_size224_tiles2_seed2_q3_dropout_v2` is a English model originally trained by Omriy123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_epochs5_batch32_lr5e_05_size224_tiles2_seed2_q3_dropout_v2_en_5.5.1_3.0_1738023179283.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_epochs5_batch32_lr5e_05_size224_tiles2_seed2_q3_dropout_v2_en_5.5.1_3.0_1738023179283.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vit_epochs5_batch32_lr5e_05_size224_tiles2_seed2_q3_dropout_v2","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vit_epochs5_batch32_lr5e_05_size224_tiles2_seed2_q3_dropout_v2","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_epochs5_batch32_lr5e_05_size224_tiles2_seed2_q3_dropout_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/Omriy123/vit_epochs5_batch32_lr5e-05_size224_tiles2_seed2_q3_dropout_v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-vit_epochs5_batch32_lr5e_05_size224_tiles2_seed2_q3_dropout_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-vit_epochs5_batch32_lr5e_05_size224_tiles2_seed2_q3_dropout_v2_pipeline_en.md
new file mode 100644
index 00000000000000..f6c954433e34c2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-vit_epochs5_batch32_lr5e_05_size224_tiles2_seed2_q3_dropout_v2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_epochs5_batch32_lr5e_05_size224_tiles2_seed2_q3_dropout_v2_pipeline pipeline ViTForImageClassification from Omriy123
+author: John Snow Labs
+name: vit_epochs5_batch32_lr5e_05_size224_tiles2_seed2_q3_dropout_v2_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_epochs5_batch32_lr5e_05_size224_tiles2_seed2_q3_dropout_v2_pipeline` is a English model originally trained by Omriy123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_epochs5_batch32_lr5e_05_size224_tiles2_seed2_q3_dropout_v2_pipeline_en_5.5.1_3.0_1738023195972.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_epochs5_batch32_lr5e_05_size224_tiles2_seed2_q3_dropout_v2_pipeline_en_5.5.1_3.0_1738023195972.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_epochs5_batch32_lr5e_05_size224_tiles2_seed2_q3_dropout_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_epochs5_batch32_lr5e_05_size224_tiles2_seed2_q3_dropout_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_epochs5_batch32_lr5e_05_size224_tiles2_seed2_q3_dropout_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/Omriy123/vit_epochs5_batch32_lr5e-05_size224_tiles2_seed2_q3_dropout_v2
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-vit_epochs5_batch32_lr5e_05_size224_tiles4_seed3_q1_en.md b/docs/_posts/ahmedlone127/2025-01-28-vit_epochs5_batch32_lr5e_05_size224_tiles4_seed3_q1_en.md
new file mode 100644
index 00000000000000..eeaef3abb34b85
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-vit_epochs5_batch32_lr5e_05_size224_tiles4_seed3_q1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_epochs5_batch32_lr5e_05_size224_tiles4_seed3_q1 ViTForImageClassification from Omriy123
+author: John Snow Labs
+name: vit_epochs5_batch32_lr5e_05_size224_tiles4_seed3_q1
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_epochs5_batch32_lr5e_05_size224_tiles4_seed3_q1` is a English model originally trained by Omriy123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_epochs5_batch32_lr5e_05_size224_tiles4_seed3_q1_en_5.5.1_3.0_1738023463955.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_epochs5_batch32_lr5e_05_size224_tiles4_seed3_q1_en_5.5.1_3.0_1738023463955.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vit_epochs5_batch32_lr5e_05_size224_tiles4_seed3_q1","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vit_epochs5_batch32_lr5e_05_size224_tiles4_seed3_q1","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_epochs5_batch32_lr5e_05_size224_tiles4_seed3_q1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/Omriy123/vit_epochs5_batch32_lr5e-05_size224_tiles4_seed3_q1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-vit_epochs5_batch32_lr5e_05_size224_tiles4_seed3_q1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-vit_epochs5_batch32_lr5e_05_size224_tiles4_seed3_q1_pipeline_en.md
new file mode 100644
index 00000000000000..fe2b7dfb3feff8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-vit_epochs5_batch32_lr5e_05_size224_tiles4_seed3_q1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_epochs5_batch32_lr5e_05_size224_tiles4_seed3_q1_pipeline pipeline ViTForImageClassification from Omriy123
+author: John Snow Labs
+name: vit_epochs5_batch32_lr5e_05_size224_tiles4_seed3_q1_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_epochs5_batch32_lr5e_05_size224_tiles4_seed3_q1_pipeline` is a English model originally trained by Omriy123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_epochs5_batch32_lr5e_05_size224_tiles4_seed3_q1_pipeline_en_5.5.1_3.0_1738023480082.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_epochs5_batch32_lr5e_05_size224_tiles4_seed3_q1_pipeline_en_5.5.1_3.0_1738023480082.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_epochs5_batch32_lr5e_05_size224_tiles4_seed3_q1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_epochs5_batch32_lr5e_05_size224_tiles4_seed3_q1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_epochs5_batch32_lr5e_05_size224_tiles4_seed3_q1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/Omriy123/vit_epochs5_batch32_lr5e-05_size224_tiles4_seed3_q1
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-vit_epochs5_batch32_lr5e_05_size224_tiles6_seed1_q2_complexity_en.md b/docs/_posts/ahmedlone127/2025-01-28-vit_epochs5_batch32_lr5e_05_size224_tiles6_seed1_q2_complexity_en.md
new file mode 100644
index 00000000000000..26733e01df1a5f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-vit_epochs5_batch32_lr5e_05_size224_tiles6_seed1_q2_complexity_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_epochs5_batch32_lr5e_05_size224_tiles6_seed1_q2_complexity ViTForImageClassification from Omriy123
+author: John Snow Labs
+name: vit_epochs5_batch32_lr5e_05_size224_tiles6_seed1_q2_complexity
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_epochs5_batch32_lr5e_05_size224_tiles6_seed1_q2_complexity` is a English model originally trained by Omriy123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_epochs5_batch32_lr5e_05_size224_tiles6_seed1_q2_complexity_en_5.5.1_3.0_1738022430392.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_epochs5_batch32_lr5e_05_size224_tiles6_seed1_q2_complexity_en_5.5.1_3.0_1738022430392.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vit_epochs5_batch32_lr5e_05_size224_tiles6_seed1_q2_complexity","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vit_epochs5_batch32_lr5e_05_size224_tiles6_seed1_q2_complexity","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_epochs5_batch32_lr5e_05_size224_tiles6_seed1_q2_complexity|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/Omriy123/vit_epochs5_batch32_lr5e-05_size224_tiles6_seed1_q2_complexity
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-vit_epochs5_batch32_lr5e_05_size224_tiles6_seed1_q2_complexity_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-vit_epochs5_batch32_lr5e_05_size224_tiles6_seed1_q2_complexity_pipeline_en.md
new file mode 100644
index 00000000000000..a0cb2e4c68eae2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-vit_epochs5_batch32_lr5e_05_size224_tiles6_seed1_q2_complexity_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_epochs5_batch32_lr5e_05_size224_tiles6_seed1_q2_complexity_pipeline pipeline ViTForImageClassification from Omriy123
+author: John Snow Labs
+name: vit_epochs5_batch32_lr5e_05_size224_tiles6_seed1_q2_complexity_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_epochs5_batch32_lr5e_05_size224_tiles6_seed1_q2_complexity_pipeline` is a English model originally trained by Omriy123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_epochs5_batch32_lr5e_05_size224_tiles6_seed1_q2_complexity_pipeline_en_5.5.1_3.0_1738022447346.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_epochs5_batch32_lr5e_05_size224_tiles6_seed1_q2_complexity_pipeline_en_5.5.1_3.0_1738022447346.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_epochs5_batch32_lr5e_05_size224_tiles6_seed1_q2_complexity_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_epochs5_batch32_lr5e_05_size224_tiles6_seed1_q2_complexity_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_epochs5_batch32_lr5e_05_size224_tiles6_seed1_q2_complexity_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/Omriy123/vit_epochs5_batch32_lr5e-05_size224_tiles6_seed1_q2_complexity
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-vit_model_victorwkey_en.md b/docs/_posts/ahmedlone127/2025-01-28-vit_model_victorwkey_en.md
new file mode 100644
index 00000000000000..463b03046abac9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-vit_model_victorwkey_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_model_victorwkey ViTForImageClassification from victorwkey
+author: John Snow Labs
+name: vit_model_victorwkey
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_model_victorwkey` is a English model originally trained by victorwkey.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_model_victorwkey_en_5.5.1_3.0_1738023040784.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_model_victorwkey_en_5.5.1_3.0_1738023040784.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vit_model_victorwkey","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vit_model_victorwkey","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_model_victorwkey|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/victorwkey/vit_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-vit_model_victorwkey_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-vit_model_victorwkey_pipeline_en.md
new file mode 100644
index 00000000000000..8aa6be7a422867
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-vit_model_victorwkey_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_model_victorwkey_pipeline pipeline ViTForImageClassification from victorwkey
+author: John Snow Labs
+name: vit_model_victorwkey_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_model_victorwkey_pipeline` is a English model originally trained by victorwkey.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_model_victorwkey_pipeline_en_5.5.1_3.0_1738023059344.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_model_victorwkey_pipeline_en_5.5.1_3.0_1738023059344.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_model_victorwkey_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_model_victorwkey_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_model_victorwkey_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/victorwkey/vit_model
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-vit_videogames_en.md b/docs/_posts/ahmedlone127/2025-01-28-vit_videogames_en.md
new file mode 100644
index 00000000000000..c2bb6327f0688a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-vit_videogames_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vit_videogames ViTForImageClassification from victorwkey
+author: John Snow Labs
+name: vit_videogames
+date: 2025-01-28
+tags: [en, open_source, onnx, image_classification, vit]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: ViTForImageClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_videogames` is a English model originally trained by victorwkey.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_videogames_en_5.5.1_3.0_1738023114142.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_videogames_en_5.5.1_3.0_1738023114142.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+		
+		
+
+image_assembler = ImageAssembler()\
+  .setInputCol("image")\
+  .setOutputCol("image_assembler")
+
+imageClassifier = ViTForImageClassification.pretrained(""vit_videogames","en")\
+  .setInputCols("image_assembler")\
+  .setOutputCol("class")
+
+pipeline = Pipeline(stages=[
+  image_assembler,
+  imageClassifier,
+])
+
+pipelineModel = pipeline.fit(imageDF)
+
+pipelineDF = pipelineModel.transform(imageDF)
+
+```
+```scala
+
+val imageAssembler = new ImageAssembler()
+    .setInputCol("image")
+    .setOutputCol("image_assembler")
+
+val imageClassifier =  ViTForImageClassification.pretrained("vit_videogames","en") 
+    .setInputCols("image_assembler") 
+    .setOutputCol("class") 
+
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+
+val pipelineModel = pipeline.fit(imageDF)
+
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_videogames|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/victorwkey/vit-videogames
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-vit_videogames_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-vit_videogames_pipeline_en.md
new file mode 100644
index 00000000000000..76082d3142714b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-vit_videogames_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English vit_videogames_pipeline pipeline ViTForImageClassification from victorwkey
+author: John Snow Labs
+name: vit_videogames_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Image Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained ViTForImageClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vit_videogames_pipeline` is a English model originally trained by victorwkey.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vit_videogames_pipeline_en_5.5.1_3.0_1738023130456.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vit_videogames_pipeline_en_5.5.1_3.0_1738023130456.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("vit_videogames_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vit_videogames_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vit_videogames_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|321.3 MB|
+
+## References
+
+https://huggingface.co/victorwkey/vit-videogames
+
+## Included Models
+
+- ImageAssembler
+- ViTForImageClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-withinapps_ndd_addressbook_test_content_en.md b/docs/_posts/ahmedlone127/2025-01-28-withinapps_ndd_addressbook_test_content_en.md
new file mode 100644
index 00000000000000..ddecd8f59a318d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-withinapps_ndd_addressbook_test_content_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English withinapps_ndd_addressbook_test_content DistilBertForSequenceClassification from lgk03
+author: John Snow Labs
+name: withinapps_ndd_addressbook_test_content
+date: 2025-01-28
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`withinapps_ndd_addressbook_test_content` is a English model originally trained by lgk03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/withinapps_ndd_addressbook_test_content_en_5.5.1_3.0_1738078119592.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/withinapps_ndd_addressbook_test_content_en_5.5.1_3.0_1738078119592.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("withinapps_ndd_addressbook_test_content","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("withinapps_ndd_addressbook_test_content", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|withinapps_ndd_addressbook_test_content|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/lgk03/WITHINAPPS_NDD-addressbook_test-content
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-withinapps_ndd_addressbook_test_content_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-withinapps_ndd_addressbook_test_content_pipeline_en.md
new file mode 100644
index 00000000000000..dfce17ac923db1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-withinapps_ndd_addressbook_test_content_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English withinapps_ndd_addressbook_test_content_pipeline pipeline DistilBertForSequenceClassification from lgk03
+author: John Snow Labs
+name: withinapps_ndd_addressbook_test_content_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`withinapps_ndd_addressbook_test_content_pipeline` is a English model originally trained by lgk03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/withinapps_ndd_addressbook_test_content_pipeline_en_5.5.1_3.0_1738078132282.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/withinapps_ndd_addressbook_test_content_pipeline_en_5.5.1_3.0_1738078132282.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("withinapps_ndd_addressbook_test_content_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("withinapps_ndd_addressbook_test_content_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|withinapps_ndd_addressbook_test_content_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/lgk03/WITHINAPPS_NDD-addressbook_test-content
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_all_abecode_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_all_abecode_en.md
new file mode 100644
index 00000000000000..d93898fe9e0916
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_all_abecode_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_abecode XlmRoBertaForTokenClassification from abecode
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_abecode
+date: 2025-01-28
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_abecode` is a English model originally trained by abecode.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_abecode_en_5.5.1_3.0_1738065899421.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_abecode_en_5.5.1_3.0_1738065899421.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_abecode","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_abecode", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_abecode|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/abecode/xlm-roberta-base-finetuned-panx-all
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_all_abecode_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_all_abecode_pipeline_en.md
new file mode 100644
index 00000000000000..f53e8ff7f87cef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_all_abecode_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_abecode_pipeline pipeline XlmRoBertaForTokenClassification from abecode
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_abecode_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_abecode_pipeline` is a English model originally trained by abecode.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_abecode_pipeline_en_5.5.1_3.0_1738065984072.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_abecode_pipeline_en_5.5.1_3.0_1738065984072.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_abecode_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_abecode_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_abecode_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/abecode/xlm-roberta-base-finetuned-panx-all
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_all_seogu_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_all_seogu_en.md
new file mode 100644
index 00000000000000..2f1963f4d97fd3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_all_seogu_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_seogu XlmRoBertaForTokenClassification from seogu
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_seogu
+date: 2025-01-28
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_seogu` is a English model originally trained by seogu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_seogu_en_5.5.1_3.0_1738063808444.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_seogu_en_5.5.1_3.0_1738063808444.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_seogu","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_seogu", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_seogu|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/seogu/xlm-roberta-base-finetuned-panx-all
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_all_seogu_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_all_seogu_pipeline_en.md
new file mode 100644
index 00000000000000..464ad7d0c4c94b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_all_seogu_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_seogu_pipeline pipeline XlmRoBertaForTokenClassification from seogu
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_seogu_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_seogu_pipeline` is a English model originally trained by seogu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_seogu_pipeline_en_5.5.1_3.0_1738063890416.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_seogu_pipeline_en_5.5.1_3.0_1738063890416.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_seogu_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_seogu_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_seogu_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/seogu/xlm-roberta-base-finetuned-panx-all
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_all_simonmok_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_all_simonmok_en.md
new file mode 100644
index 00000000000000..0233853d208392
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_all_simonmok_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_simonmok XlmRoBertaForTokenClassification from simonmok
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_simonmok
+date: 2025-01-28
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_simonmok` is a English model originally trained by simonmok.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_simonmok_en_5.5.1_3.0_1738064481825.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_simonmok_en_5.5.1_3.0_1738064481825.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_simonmok","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_simonmok", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_simonmok|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/simonmok/xlm-roberta-base-finetuned-panx-all
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_all_simonmok_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_all_simonmok_pipeline_en.md
new file mode 100644
index 00000000000000..b0e826f0092b78
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_all_simonmok_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_simonmok_pipeline pipeline XlmRoBertaForTokenClassification from simonmok
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_simonmok_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_simonmok_pipeline` is a English model originally trained by simonmok.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_simonmok_pipeline_en_5.5.1_3.0_1738064563959.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_simonmok_pipeline_en_5.5.1_3.0_1738064563959.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_simonmok_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_simonmok_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_simonmok_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/simonmok/xlm-roberta-base-finetuned-panx-all
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_chinese_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_chinese_en.md
new file mode 100644
index 00000000000000..ac3a3ea16acc2d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_chinese_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_chinese XlmRoBertaForTokenClassification from jianxun
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_chinese
+date: 2025-01-28
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_chinese` is a English model originally trained by jianxun.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_chinese_en_5.5.1_3.0_1738064100867.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_chinese_en_5.5.1_3.0_1738064100867.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_chinese","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_chinese", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_chinese|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/jianxun/xlm-roberta-base-finetuned-panx-zh
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_chinese_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_chinese_pipeline_en.md
new file mode 100644
index 00000000000000..26d0ac6eabb92d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_chinese_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_chinese_pipeline pipeline XlmRoBertaForTokenClassification from jianxun
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_chinese_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_chinese_pipeline` is a English model originally trained by jianxun.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_chinese_pipeline_en_5.5.1_3.0_1738064170597.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_chinese_pipeline_en_5.5.1_3.0_1738064170597.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_chinese_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_chinese_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_chinese_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/jianxun/xlm-roberta-base-finetuned-panx-zh
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_english_abecode_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_english_abecode_en.md
new file mode 100644
index 00000000000000..4bae595a651478
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_english_abecode_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_abecode XlmRoBertaForTokenClassification from abecode
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_abecode
+date: 2025-01-28
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_abecode` is a English model originally trained by abecode.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_abecode_en_5.5.1_3.0_1738064286319.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_abecode_en_5.5.1_3.0_1738064286319.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_abecode","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_abecode", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_abecode|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/abecode/xlm-roberta-base-finetuned-panx-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_english_abecode_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_english_abecode_pipeline_en.md
new file mode 100644
index 00000000000000..ed82e14c11fdc2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_english_abecode_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_abecode_pipeline pipeline XlmRoBertaForTokenClassification from abecode
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_abecode_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_abecode_pipeline` is a English model originally trained by abecode.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_abecode_pipeline_en_5.5.1_3.0_1738064399798.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_abecode_pipeline_en_5.5.1_3.0_1738064399798.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_abecode_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_abecode_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_abecode_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/abecode/xlm-roberta-base-finetuned-panx-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_english_seogu_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_english_seogu_en.md
new file mode 100644
index 00000000000000..4d3726f028a372
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_english_seogu_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_seogu XlmRoBertaForTokenClassification from seogu
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_seogu
+date: 2025-01-28
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_seogu` is a English model originally trained by seogu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_seogu_en_5.5.1_3.0_1738063831076.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_seogu_en_5.5.1_3.0_1738063831076.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_seogu","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_seogu", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_seogu|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/seogu/xlm-roberta-base-finetuned-panx-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_english_seogu_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_english_seogu_pipeline_en.md
new file mode 100644
index 00000000000000..d3f8e8a3097402
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_english_seogu_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_seogu_pipeline pipeline XlmRoBertaForTokenClassification from seogu
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_seogu_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_seogu_pipeline` is a English model originally trained by seogu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_seogu_pipeline_en_5.5.1_3.0_1738063942396.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_seogu_pipeline_en_5.5.1_3.0_1738063942396.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_seogu_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_seogu_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_seogu_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/seogu/xlm-roberta-base-finetuned-panx-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_english_simonmok_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_english_simonmok_en.md
new file mode 100644
index 00000000000000..6ce64e5b1fb6f7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_english_simonmok_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_simonmok XlmRoBertaForTokenClassification from simonmok
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_simonmok
+date: 2025-01-28
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_simonmok` is a English model originally trained by simonmok.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_simonmok_en_5.5.1_3.0_1738065881912.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_simonmok_en_5.5.1_3.0_1738065881912.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_simonmok","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_simonmok", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_simonmok|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/simonmok/xlm-roberta-base-finetuned-panx-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_english_simonmok_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_english_simonmok_pipeline_en.md
new file mode 100644
index 00000000000000..1161a063b6667d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_english_simonmok_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_simonmok_pipeline pipeline XlmRoBertaForTokenClassification from simonmok
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_simonmok_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_simonmok_pipeline` is a English model originally trained by simonmok.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_simonmok_pipeline_en_5.5.1_3.0_1738065994031.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_simonmok_pipeline_en_5.5.1_3.0_1738065994031.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_simonmok_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_simonmok_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_simonmok_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/simonmok/xlm-roberta-base-finetuned-panx-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_english_stevenpennoyer_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_english_stevenpennoyer_en.md
new file mode 100644
index 00000000000000..d2d284194e84ef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_english_stevenpennoyer_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_stevenpennoyer XlmRoBertaForTokenClassification from StevenPennoyer
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_stevenpennoyer
+date: 2025-01-28
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_stevenpennoyer` is a English model originally trained by StevenPennoyer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_stevenpennoyer_en_5.5.1_3.0_1738064645515.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_stevenpennoyer_en_5.5.1_3.0_1738064645515.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_stevenpennoyer","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_stevenpennoyer", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_stevenpennoyer|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/StevenPennoyer/xlm-roberta-base-finetuned-panx-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_english_stevenpennoyer_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_english_stevenpennoyer_pipeline_en.md
new file mode 100644
index 00000000000000..ba81b39bae0665
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_english_stevenpennoyer_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_stevenpennoyer_pipeline pipeline XlmRoBertaForTokenClassification from StevenPennoyer
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_stevenpennoyer_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_stevenpennoyer_pipeline` is a English model originally trained by StevenPennoyer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_stevenpennoyer_pipeline_en_5.5.1_3.0_1738064749211.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_stevenpennoyer_pipeline_en_5.5.1_3.0_1738064749211.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_stevenpennoyer_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_stevenpennoyer_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_stevenpennoyer_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/StevenPennoyer/xlm-roberta-base-finetuned-panx-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_french_abecode_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_french_abecode_en.md
new file mode 100644
index 00000000000000..5035960d024efb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_french_abecode_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_abecode XlmRoBertaForTokenClassification from abecode
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_abecode
+date: 2025-01-28
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_abecode` is a English model originally trained by abecode.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_abecode_en_5.5.1_3.0_1738065677294.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_abecode_en_5.5.1_3.0_1738065677294.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_abecode","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_abecode", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_abecode|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/abecode/xlm-roberta-base-finetuned-panx-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_french_abecode_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_french_abecode_pipeline_en.md
new file mode 100644
index 00000000000000..23093951c58bfa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_french_abecode_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_abecode_pipeline pipeline XlmRoBertaForTokenClassification from abecode
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_abecode_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_abecode_pipeline` is a English model originally trained by abecode.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_abecode_pipeline_en_5.5.1_3.0_1738065775634.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_abecode_pipeline_en_5.5.1_3.0_1738065775634.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_abecode_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_abecode_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_abecode_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/abecode/xlm-roberta-base-finetuned-panx-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_french_seogu_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_french_seogu_en.md
new file mode 100644
index 00000000000000..82972a14bb2aba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_french_seogu_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_seogu XlmRoBertaForTokenClassification from seogu
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_seogu
+date: 2025-01-28
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_seogu` is a English model originally trained by seogu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_seogu_en_5.5.1_3.0_1738063818530.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_seogu_en_5.5.1_3.0_1738063818530.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_seogu","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_seogu", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_seogu|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/seogu/xlm-roberta-base-finetuned-panx-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_french_seogu_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_french_seogu_pipeline_en.md
new file mode 100644
index 00000000000000..48466245388870
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_french_seogu_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_seogu_pipeline pipeline XlmRoBertaForTokenClassification from seogu
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_seogu_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_seogu_pipeline` is a English model originally trained by seogu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_seogu_pipeline_en_5.5.1_3.0_1738063914711.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_seogu_pipeline_en_5.5.1_3.0_1738063914711.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_seogu_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_seogu_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_seogu_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/seogu/xlm-roberta-base-finetuned-panx-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_french_simonmok_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_french_simonmok_en.md
new file mode 100644
index 00000000000000..1251cda0ae2c32
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_french_simonmok_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_simonmok XlmRoBertaForTokenClassification from simonmok
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_simonmok
+date: 2025-01-28
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_simonmok` is a English model originally trained by simonmok.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_simonmok_en_5.5.1_3.0_1738065053097.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_simonmok_en_5.5.1_3.0_1738065053097.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_simonmok","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_simonmok", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_simonmok|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/simonmok/xlm-roberta-base-finetuned-panx-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_french_simonmok_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_french_simonmok_pipeline_en.md
new file mode 100644
index 00000000000000..f9100d0b3ff1e4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_french_simonmok_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_simonmok_pipeline pipeline XlmRoBertaForTokenClassification from simonmok
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_simonmok_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_simonmok_pipeline` is a English model originally trained by simonmok.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_simonmok_pipeline_en_5.5.1_3.0_1738065144142.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_simonmok_pipeline_en_5.5.1_3.0_1738065144142.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_simonmok_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_simonmok_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_simonmok_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/simonmok/xlm-roberta-base-finetuned-panx-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_french_stevenpennoyer_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_french_stevenpennoyer_en.md
new file mode 100644
index 00000000000000..6eb905c19071ce
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_french_stevenpennoyer_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_stevenpennoyer XlmRoBertaForTokenClassification from StevenPennoyer
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_stevenpennoyer
+date: 2025-01-28
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_stevenpennoyer` is a English model originally trained by StevenPennoyer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_stevenpennoyer_en_5.5.1_3.0_1738063817636.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_stevenpennoyer_en_5.5.1_3.0_1738063817636.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_stevenpennoyer","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_stevenpennoyer", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_stevenpennoyer|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/StevenPennoyer/xlm-roberta-base-finetuned-panx-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_french_stevenpennoyer_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_french_stevenpennoyer_pipeline_en.md
new file mode 100644
index 00000000000000..e51ee168a9ae9e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_french_stevenpennoyer_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_stevenpennoyer_pipeline pipeline XlmRoBertaForTokenClassification from StevenPennoyer
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_stevenpennoyer_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_stevenpennoyer_pipeline` is a English model originally trained by StevenPennoyer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_stevenpennoyer_pipeline_en_5.5.1_3.0_1738063917578.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_stevenpennoyer_pipeline_en_5.5.1_3.0_1738063917578.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_stevenpennoyer_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_stevenpennoyer_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_stevenpennoyer_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/StevenPennoyer/xlm-roberta-base-finetuned-panx-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_abecode_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_abecode_en.md
new file mode 100644
index 00000000000000..7331a5dfb8b7b9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_abecode_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_abecode XlmRoBertaForTokenClassification from abecode
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_abecode
+date: 2025-01-28
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_abecode` is a English model originally trained by abecode.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_abecode_en_5.5.1_3.0_1738063897135.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_abecode_en_5.5.1_3.0_1738063897135.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_abecode","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_abecode", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_abecode|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/abecode/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_abecode_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_abecode_pipeline_en.md
new file mode 100644
index 00000000000000..3b50355a905cd7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_abecode_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_abecode_pipeline pipeline XlmRoBertaForTokenClassification from abecode
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_abecode_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_abecode_pipeline` is a English model originally trained by abecode.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_abecode_pipeline_en_5.5.1_3.0_1738063982980.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_abecode_pipeline_en_5.5.1_3.0_1738063982980.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_abecode_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_abecode_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_abecode_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/abecode/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_ahmedelzayat077_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_ahmedelzayat077_en.md
new file mode 100644
index 00000000000000..e9353ec49bfbda
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_ahmedelzayat077_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_ahmedelzayat077 BertForTokenClassification from ahmedelzayat077
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_ahmedelzayat077
+date: 2025-01-28
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_ahmedelzayat077` is a English model originally trained by ahmedelzayat077.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_ahmedelzayat077_en_5.5.1_3.0_1738045270181.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_ahmedelzayat077_en_5.5.1_3.0_1738045270181.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_ahmedelzayat077","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_ahmedelzayat077", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_ahmedelzayat077|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/ahmedelzayat077/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_ahmedelzayat077_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_ahmedelzayat077_pipeline_en.md
new file mode 100644
index 00000000000000..35a3beca1bfb54
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_ahmedelzayat077_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_ahmedelzayat077_pipeline pipeline BertForTokenClassification from ahmedelzayat077
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_ahmedelzayat077_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_ahmedelzayat077_pipeline` is a English model originally trained by ahmedelzayat077.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_ahmedelzayat077_pipeline_en_5.5.1_3.0_1738045303425.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_ahmedelzayat077_pipeline_en_5.5.1_3.0_1738045303425.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_ahmedelzayat077_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_ahmedelzayat077_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_ahmedelzayat077_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/ahmedelzayat077/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_feic36_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_feic36_en.md
new file mode 100644
index 00000000000000..7c87afa86e7b01
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_feic36_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_feic36 XlmRoBertaForTokenClassification from feic36
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_feic36
+date: 2025-01-28
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_feic36` is a English model originally trained by feic36.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_feic36_en_5.5.1_3.0_1738064943483.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_feic36_en_5.5.1_3.0_1738064943483.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_feic36","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_feic36", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_feic36|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/feic36/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_feic36_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_feic36_pipeline_en.md
new file mode 100644
index 00000000000000..47caff0787cfa4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_feic36_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_feic36_pipeline pipeline XlmRoBertaForTokenClassification from feic36
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_feic36_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_feic36_pipeline` is a English model originally trained by feic36.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_feic36_pipeline_en_5.5.1_3.0_1738065012360.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_feic36_pipeline_en_5.5.1_3.0_1738065012360.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_feic36_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_feic36_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_feic36_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/feic36/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_ferro_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_ferro_en.md
new file mode 100644
index 00000000000000..c7f8d17bc1e734
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_ferro_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_ferro XlmRoBertaForTokenClassification from Ferro
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_ferro
+date: 2025-01-28
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_ferro` is a English model originally trained by Ferro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_ferro_en_5.5.1_3.0_1738064831932.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_ferro_en_5.5.1_3.0_1738064831932.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_ferro","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_ferro", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_ferro|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/Ferro/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_ferro_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_ferro_pipeline_en.md
new file mode 100644
index 00000000000000..16c1cc33f0b348
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_ferro_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_ferro_pipeline pipeline XlmRoBertaForTokenClassification from Ferro
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_ferro_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_ferro_pipeline` is a English model originally trained by Ferro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_ferro_pipeline_en_5.5.1_3.0_1738064900341.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_ferro_pipeline_en_5.5.1_3.0_1738064900341.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_ferro_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_ferro_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_ferro_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/Ferro/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_french_abecode_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_french_abecode_en.md
new file mode 100644
index 00000000000000..1ec73c929614c3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_french_abecode_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_abecode XlmRoBertaForTokenClassification from abecode
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_abecode
+date: 2025-01-28
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_abecode` is a English model originally trained by abecode.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_abecode_en_5.5.1_3.0_1738065677447.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_abecode_en_5.5.1_3.0_1738065677447.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_abecode","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_abecode", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_abecode|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/abecode/xlm-roberta-base-finetuned-panx-de-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_french_abecode_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_french_abecode_pipeline_en.md
new file mode 100644
index 00000000000000..933a09920ee954
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_french_abecode_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_abecode_pipeline pipeline XlmRoBertaForTokenClassification from abecode
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_abecode_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_abecode_pipeline` is a English model originally trained by abecode.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_abecode_pipeline_en_5.5.1_3.0_1738065770605.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_abecode_pipeline_en_5.5.1_3.0_1738065770605.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_abecode_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_abecode_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_abecode_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/abecode/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_french_seogu_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_french_seogu_en.md
new file mode 100644
index 00000000000000..1dfbbe7d3a0c2e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_french_seogu_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_seogu XlmRoBertaForTokenClassification from seogu
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_seogu
+date: 2025-01-28
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_seogu` is a English model originally trained by seogu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_seogu_en_5.5.1_3.0_1738064289129.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_seogu_en_5.5.1_3.0_1738064289129.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_seogu","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_seogu", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_seogu|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/seogu/xlm-roberta-base-finetuned-panx-de-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_french_seogu_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_french_seogu_pipeline_en.md
new file mode 100644
index 00000000000000..762850d56bb727
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_french_seogu_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_seogu_pipeline pipeline XlmRoBertaForTokenClassification from seogu
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_seogu_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_seogu_pipeline` is a English model originally trained by seogu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_seogu_pipeline_en_5.5.1_3.0_1738064380328.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_seogu_pipeline_en_5.5.1_3.0_1738064380328.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_seogu_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_seogu_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_seogu_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/seogu/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_french_simonmok_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_french_simonmok_en.md
new file mode 100644
index 00000000000000..4795ecbd706231
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_french_simonmok_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_simonmok XlmRoBertaForTokenClassification from simonmok
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_simonmok
+date: 2025-01-28
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_simonmok` is a English model originally trained by simonmok.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_simonmok_en_5.5.1_3.0_1738065100800.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_simonmok_en_5.5.1_3.0_1738065100800.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_simonmok","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_simonmok", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_simonmok|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/simonmok/xlm-roberta-base-finetuned-panx-de-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_french_simonmok_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_french_simonmok_pipeline_en.md
new file mode 100644
index 00000000000000..201d1a07c7018e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_french_simonmok_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_simonmok_pipeline pipeline XlmRoBertaForTokenClassification from simonmok
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_simonmok_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_simonmok_pipeline` is a English model originally trained by simonmok.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_simonmok_pipeline_en_5.5.1_3.0_1738065186101.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_simonmok_pipeline_en_5.5.1_3.0_1738065186101.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_simonmok_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_simonmok_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_simonmok_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/simonmok/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_igniter909_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_igniter909_en.md
new file mode 100644
index 00000000000000..ed1a67e7bfc972
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_igniter909_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_igniter909 XlmRoBertaForTokenClassification from Igniter909
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_igniter909
+date: 2025-01-28
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_igniter909` is a English model originally trained by Igniter909.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_igniter909_en_5.5.1_3.0_1738065392920.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_igniter909_en_5.5.1_3.0_1738065392920.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_igniter909","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_igniter909", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_igniter909|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/Igniter909/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_igniter909_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_igniter909_pipeline_en.md
new file mode 100644
index 00000000000000..12ae0d7eda7c8f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_igniter909_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_igniter909_pipeline pipeline XlmRoBertaForTokenClassification from Igniter909
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_igniter909_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_igniter909_pipeline` is a English model originally trained by Igniter909.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_igniter909_pipeline_en_5.5.1_3.0_1738065476456.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_igniter909_pipeline_en_5.5.1_3.0_1738065476456.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_igniter909_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_igniter909_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_igniter909_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/Igniter909/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_ridealist_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_ridealist_en.md
new file mode 100644
index 00000000000000..b1cc630f27b1e6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_ridealist_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_ridealist XlmRoBertaForTokenClassification from Ridealist
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_ridealist
+date: 2025-01-28
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_ridealist` is a English model originally trained by Ridealist.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_ridealist_en_5.5.1_3.0_1738066018528.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_ridealist_en_5.5.1_3.0_1738066018528.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_ridealist","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_ridealist", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_ridealist|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/Ridealist/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_ridealist_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_ridealist_pipeline_en.md
new file mode 100644
index 00000000000000..16a3a9401457e6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_ridealist_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_ridealist_pipeline pipeline XlmRoBertaForTokenClassification from Ridealist
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_ridealist_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_ridealist_pipeline` is a English model originally trained by Ridealist.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_ridealist_pipeline_en_5.5.1_3.0_1738066102041.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_ridealist_pipeline_en_5.5.1_3.0_1738066102041.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_ridealist_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_ridealist_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_ridealist_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/Ridealist/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_simonmok_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_simonmok_en.md
new file mode 100644
index 00000000000000..9220d655eadfef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_simonmok_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_simonmok XlmRoBertaForTokenClassification from simonmok
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_simonmok
+date: 2025-01-28
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_simonmok` is a English model originally trained by simonmok.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_simonmok_en_5.5.1_3.0_1738064669100.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_simonmok_en_5.5.1_3.0_1738064669100.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_simonmok","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_simonmok", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_simonmok|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/simonmok/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_simonmok_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_simonmok_pipeline_en.md
new file mode 100644
index 00000000000000..cde26cfada1bc0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_simonmok_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_simonmok_pipeline pipeline XlmRoBertaForTokenClassification from simonmok
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_simonmok_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_simonmok_pipeline` is a English model originally trained by simonmok.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_simonmok_pipeline_en_5.5.1_3.0_1738064752467.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_simonmok_pipeline_en_5.5.1_3.0_1738064752467.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_simonmok_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_simonmok_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_simonmok_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/simonmok/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_stevenpennoyer_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_stevenpennoyer_en.md
new file mode 100644
index 00000000000000..693d30db08efa6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_stevenpennoyer_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_stevenpennoyer XlmRoBertaForTokenClassification from StevenPennoyer
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_stevenpennoyer
+date: 2025-01-28
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_stevenpennoyer` is a English model originally trained by StevenPennoyer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_stevenpennoyer_en_5.5.1_3.0_1738064809176.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_stevenpennoyer_en_5.5.1_3.0_1738064809176.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_stevenpennoyer","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_stevenpennoyer", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_stevenpennoyer|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/StevenPennoyer/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_stevenpennoyer_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_stevenpennoyer_pipeline_en.md
new file mode 100644
index 00000000000000..73dab117bf1fe0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_stevenpennoyer_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_stevenpennoyer_pipeline pipeline XlmRoBertaForTokenClassification from StevenPennoyer
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_stevenpennoyer_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_stevenpennoyer_pipeline` is a English model originally trained by StevenPennoyer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_stevenpennoyer_pipeline_en_5.5.1_3.0_1738064892791.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_stevenpennoyer_pipeline_en_5.5.1_3.0_1738064892791.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_stevenpennoyer_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_stevenpennoyer_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_stevenpennoyer_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/StevenPennoyer/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_v2_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_v2_en.md
new file mode 100644
index 00000000000000..86e3610f7c8e65
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_v2 XlmRoBertaForTokenClassification from seogu
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_v2
+date: 2025-01-28
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_v2` is a English model originally trained by seogu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_v2_en_5.5.1_3.0_1738065245408.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_v2_en_5.5.1_3.0_1738065245408.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_v2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_v2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/seogu/xlm-roberta-base-finetuned-panx-de-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_v2_pipeline_en.md
new file mode 100644
index 00000000000000..b578521984cbbd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_german_v2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_v2_pipeline pipeline XlmRoBertaForTokenClassification from seogu
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_v2_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_v2_pipeline` is a English model originally trained by seogu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_v2_pipeline_en_5.5.1_3.0_1738065328897.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_v2_pipeline_en_5.5.1_3.0_1738065328897.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/seogu/xlm-roberta-base-finetuned-panx-de-v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_italian_abecode_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_italian_abecode_en.md
new file mode 100644
index 00000000000000..efe8fe5bf86cdb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_italian_abecode_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_abecode XlmRoBertaForTokenClassification from abecode
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_abecode
+date: 2025-01-28
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_abecode` is a English model originally trained by abecode.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_abecode_en_5.5.1_3.0_1738065512349.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_abecode_en_5.5.1_3.0_1738065512349.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_abecode","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_abecode", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_abecode|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|816.7 MB|
+
+## References
+
+https://huggingface.co/abecode/xlm-roberta-base-finetuned-panx-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_italian_abecode_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_italian_abecode_pipeline_en.md
new file mode 100644
index 00000000000000..d92ab7efb9e949
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_italian_abecode_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_abecode_pipeline pipeline XlmRoBertaForTokenClassification from abecode
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_abecode_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_abecode_pipeline` is a English model originally trained by abecode.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_abecode_pipeline_en_5.5.1_3.0_1738065608516.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_abecode_pipeline_en_5.5.1_3.0_1738065608516.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_abecode_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_abecode_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_abecode_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|816.7 MB|
+
+## References
+
+https://huggingface.co/abecode/xlm-roberta-base-finetuned-panx-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_italian_ahmedelzayat077_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_italian_ahmedelzayat077_en.md
new file mode 100644
index 00000000000000..6909e099dcabc6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_italian_ahmedelzayat077_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_ahmedelzayat077 BertForTokenClassification from ahmedelzayat077
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_ahmedelzayat077
+date: 2025-01-28
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_ahmedelzayat077` is a English model originally trained by ahmedelzayat077.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_ahmedelzayat077_en_5.5.1_3.0_1738044419446.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_ahmedelzayat077_en_5.5.1_3.0_1738044419446.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_ahmedelzayat077","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_ahmedelzayat077", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_ahmedelzayat077|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/ahmedelzayat077/xlm-roberta-base-finetuned-panx-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_italian_ahmedelzayat077_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_italian_ahmedelzayat077_pipeline_en.md
new file mode 100644
index 00000000000000..90549e023ebdc9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_italian_ahmedelzayat077_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_ahmedelzayat077_pipeline pipeline BertForTokenClassification from ahmedelzayat077
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_ahmedelzayat077_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_ahmedelzayat077_pipeline` is a English model originally trained by ahmedelzayat077.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_ahmedelzayat077_pipeline_en_5.5.1_3.0_1738044452214.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_ahmedelzayat077_pipeline_en_5.5.1_3.0_1738044452214.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_ahmedelzayat077_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_ahmedelzayat077_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_ahmedelzayat077_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/ahmedelzayat077/xlm-roberta-base-finetuned-panx-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_italian_seogu_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_italian_seogu_en.md
new file mode 100644
index 00000000000000..997665d34263f7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_italian_seogu_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_seogu XlmRoBertaForTokenClassification from seogu
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_seogu
+date: 2025-01-28
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_seogu` is a English model originally trained by seogu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_seogu_en_5.5.1_3.0_1738065784854.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_seogu_en_5.5.1_3.0_1738065784854.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_seogu","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_seogu", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_seogu|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|816.7 MB|
+
+## References
+
+https://huggingface.co/seogu/xlm-roberta-base-finetuned-panx-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_italian_seogu_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_italian_seogu_pipeline_en.md
new file mode 100644
index 00000000000000..4e014f5e96ba44
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_italian_seogu_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_seogu_pipeline pipeline XlmRoBertaForTokenClassification from seogu
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_seogu_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_seogu_pipeline` is a English model originally trained by seogu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_seogu_pipeline_en_5.5.1_3.0_1738065883254.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_seogu_pipeline_en_5.5.1_3.0_1738065883254.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_seogu_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_seogu_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_seogu_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|816.8 MB|
+
+## References
+
+https://huggingface.co/seogu/xlm-roberta-base-finetuned-panx-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_italian_simonmok_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_italian_simonmok_en.md
new file mode 100644
index 00000000000000..9156fe736e6c29
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_italian_simonmok_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_simonmok XlmRoBertaForTokenClassification from simonmok
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_simonmok
+date: 2025-01-28
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_simonmok` is a English model originally trained by simonmok.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_simonmok_en_5.5.1_3.0_1738065439160.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_simonmok_en_5.5.1_3.0_1738065439160.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_simonmok","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_simonmok", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_simonmok|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|816.7 MB|
+
+## References
+
+https://huggingface.co/simonmok/xlm-roberta-base-finetuned-panx-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_italian_simonmok_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_italian_simonmok_pipeline_en.md
new file mode 100644
index 00000000000000..25b7d60f51085b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_italian_simonmok_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_simonmok_pipeline pipeline XlmRoBertaForTokenClassification from simonmok
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_simonmok_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_simonmok_pipeline` is a English model originally trained by simonmok.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_simonmok_pipeline_en_5.5.1_3.0_1738065535308.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_simonmok_pipeline_en_5.5.1_3.0_1738065535308.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_simonmok_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_simonmok_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_simonmok_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|816.8 MB|
+
+## References
+
+https://huggingface.co/simonmok/xlm-roberta-base-finetuned-panx-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_italian_stevenpennoyer_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_italian_stevenpennoyer_en.md
new file mode 100644
index 00000000000000..c5430ab8ab8e6e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_italian_stevenpennoyer_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_stevenpennoyer XlmRoBertaForTokenClassification from StevenPennoyer
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_stevenpennoyer
+date: 2025-01-28
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_stevenpennoyer` is a English model originally trained by StevenPennoyer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_stevenpennoyer_en_5.5.1_3.0_1738064470867.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_stevenpennoyer_en_5.5.1_3.0_1738064470867.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_stevenpennoyer","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_stevenpennoyer", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_stevenpennoyer|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|816.7 MB|
+
+## References
+
+https://huggingface.co/StevenPennoyer/xlm-roberta-base-finetuned-panx-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_italian_stevenpennoyer_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_italian_stevenpennoyer_pipeline_en.md
new file mode 100644
index 00000000000000..cf21b5b66b076c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_roberta_base_finetuned_panx_italian_stevenpennoyer_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_stevenpennoyer_pipeline pipeline XlmRoBertaForTokenClassification from StevenPennoyer
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_stevenpennoyer_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_stevenpennoyer_pipeline` is a English model originally trained by StevenPennoyer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_stevenpennoyer_pipeline_en_5.5.1_3.0_1738064566953.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_stevenpennoyer_pipeline_en_5.5.1_3.0_1738064566953.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_stevenpennoyer_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_italian_stevenpennoyer_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_stevenpennoyer_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|816.8 MB|
+
+## References
+
+https://huggingface.co/StevenPennoyer/xlm-roberta-base-finetuned-panx-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_v_base_trimmed_german_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_v_base_trimmed_german_en.md
new file mode 100644
index 00000000000000..7d565731347ab8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_v_base_trimmed_german_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_v_base_trimmed_german XlmRoBertaEmbeddings from vocabtrimmer
+author: John Snow Labs
+name: xlm_v_base_trimmed_german
+date: 2025-01-28
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_v_base_trimmed_german` is a English model originally trained by vocabtrimmer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_v_base_trimmed_german_en_5.5.1_3.0_1738060861590.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_v_base_trimmed_german_en_5.5.1_3.0_1738060861590.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("xlm_v_base_trimmed_german","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("xlm_v_base_trimmed_german","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_v_base_trimmed_german|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|618.6 MB|
+
+## References
+
+https://huggingface.co/vocabtrimmer/xlm-v-base-trimmed-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-xlm_v_base_trimmed_german_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-xlm_v_base_trimmed_german_pipeline_en.md
new file mode 100644
index 00000000000000..01a2c41bf9a808
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-xlm_v_base_trimmed_german_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_v_base_trimmed_german_pipeline pipeline XlmRoBertaEmbeddings from vocabtrimmer
+author: John Snow Labs
+name: xlm_v_base_trimmed_german_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_v_base_trimmed_german_pipeline` is a English model originally trained by vocabtrimmer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_v_base_trimmed_german_pipeline_en_5.5.1_3.0_1738061033201.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_v_base_trimmed_german_pipeline_en_5.5.1_3.0_1738061033201.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_v_base_trimmed_german_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_v_base_trimmed_german_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_v_base_trimmed_german_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|618.6 MB|
+
+## References
+
+https://huggingface.co/vocabtrimmer/xlm-v-base-trimmed-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-zengq_en.md b/docs/_posts/ahmedlone127/2025-01-28-zengq_en.md
new file mode 100644
index 00000000000000..82f0a07fe35c49
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-zengq_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English zengq BertForQuestionAnswering from prabinpanta0
+author: John Snow Labs
+name: zengq
+date: 2025-01-28
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`zengq` is a English model originally trained by prabinpanta0.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/zengq_en_5.5.1_3.0_1738062383904.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/zengq_en_5.5.1_3.0_1738062383904.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("zengq","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("zengq", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|zengq|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/prabinpanta0/ZenGQ
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-28-zengq_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-28-zengq_pipeline_en.md
new file mode 100644
index 00000000000000..be475183003c82
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-28-zengq_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English zengq_pipeline pipeline BertForQuestionAnswering from prabinpanta0
+author: John Snow Labs
+name: zengq_pipeline
+date: 2025-01-28
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`zengq_pipeline` is a English model originally trained by prabinpanta0.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/zengq_pipeline_en_5.5.1_3.0_1738062404828.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/zengq_pipeline_en_5.5.1_3.0_1738062404828.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("zengq_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("zengq_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|zengq_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/prabinpanta0/ZenGQ
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-10dimensions_identity_en.md b/docs/_posts/ahmedlone127/2025-01-29-10dimensions_identity_en.md
new file mode 100644
index 00000000000000..87a9d0b5bd38ac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-10dimensions_identity_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English 10dimensions_identity BertForSequenceClassification from Blablablab
+author: John Snow Labs
+name: 10dimensions_identity
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`10dimensions_identity` is a English model originally trained by Blablablab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/10dimensions_identity_en_5.5.1_3.0_1738113084142.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/10dimensions_identity_en_5.5.1_3.0_1738113084142.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("10dimensions_identity","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("10dimensions_identity", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|10dimensions_identity|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|405.9 MB|
+
+## References
+
+https://huggingface.co/Blablablab/10dimensions-identity
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-10dimensions_identity_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-10dimensions_identity_pipeline_en.md
new file mode 100644
index 00000000000000..f45b72f8acfe49
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-10dimensions_identity_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English 10dimensions_identity_pipeline pipeline BertForSequenceClassification from Blablablab
+author: John Snow Labs
+name: 10dimensions_identity_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`10dimensions_identity_pipeline` is a English model originally trained by Blablablab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/10dimensions_identity_pipeline_en_5.5.1_3.0_1738113104377.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/10dimensions_identity_pipeline_en_5.5.1_3.0_1738113104377.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("10dimensions_identity_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("10dimensions_identity_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|10dimensions_identity_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|405.9 MB|
+
+## References
+
+https://huggingface.co/Blablablab/10dimensions-identity
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-10dimensions_knowledge_en.md b/docs/_posts/ahmedlone127/2025-01-29-10dimensions_knowledge_en.md
new file mode 100644
index 00000000000000..0767cec15bd3f9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-10dimensions_knowledge_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English 10dimensions_knowledge BertForSequenceClassification from Blablablab
+author: John Snow Labs
+name: 10dimensions_knowledge
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`10dimensions_knowledge` is a English model originally trained by Blablablab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/10dimensions_knowledge_en_5.5.1_3.0_1738113438609.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/10dimensions_knowledge_en_5.5.1_3.0_1738113438609.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("10dimensions_knowledge","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("10dimensions_knowledge", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|10dimensions_knowledge|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|405.9 MB|
+
+## References
+
+https://huggingface.co/Blablablab/10dimensions-knowledge
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-10dimensions_knowledge_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-10dimensions_knowledge_pipeline_en.md
new file mode 100644
index 00000000000000..9b7fe6fbdddc76
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-10dimensions_knowledge_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English 10dimensions_knowledge_pipeline pipeline BertForSequenceClassification from Blablablab
+author: John Snow Labs
+name: 10dimensions_knowledge_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`10dimensions_knowledge_pipeline` is a English model originally trained by Blablablab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/10dimensions_knowledge_pipeline_en_5.5.1_3.0_1738113459768.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/10dimensions_knowledge_pipeline_en_5.5.1_3.0_1738113459768.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("10dimensions_knowledge_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("10dimensions_knowledge_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|10dimensions_knowledge_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|405.9 MB|
+
+## References
+
+https://huggingface.co/Blablablab/10dimensions-knowledge
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-afrikaans_finetuned_demo_2_en.md b/docs/_posts/ahmedlone127/2025-01-29-afrikaans_finetuned_demo_2_en.md
new file mode 100644
index 00000000000000..e2891ce619a214
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-afrikaans_finetuned_demo_2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English afrikaans_finetuned_demo_2 DistilBertForSequenceClassification from afhuggingface
+author: John Snow Labs
+name: afrikaans_finetuned_demo_2
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`afrikaans_finetuned_demo_2` is a English model originally trained by afhuggingface.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/afrikaans_finetuned_demo_2_en_5.5.1_3.0_1738110345883.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/afrikaans_finetuned_demo_2_en_5.5.1_3.0_1738110345883.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("afrikaans_finetuned_demo_2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("afrikaans_finetuned_demo_2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|afrikaans_finetuned_demo_2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|246.0 MB|
+
+## References
+
+https://huggingface.co/afhuggingface/af_finetuned_demo_2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-afrikaans_finetuned_demo_2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-afrikaans_finetuned_demo_2_pipeline_en.md
new file mode 100644
index 00000000000000..a0e03db0d74450
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-afrikaans_finetuned_demo_2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English afrikaans_finetuned_demo_2_pipeline pipeline DistilBertForSequenceClassification from afhuggingface
+author: John Snow Labs
+name: afrikaans_finetuned_demo_2_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`afrikaans_finetuned_demo_2_pipeline` is a English model originally trained by afhuggingface.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/afrikaans_finetuned_demo_2_pipeline_en_5.5.1_3.0_1738110358248.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/afrikaans_finetuned_demo_2_pipeline_en_5.5.1_3.0_1738110358248.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("afrikaans_finetuned_demo_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("afrikaans_finetuned_demo_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|afrikaans_finetuned_demo_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|246.0 MB|
+
+## References
+
+https://huggingface.co/afhuggingface/af_finetuned_demo_2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-anger_finetune_3_en.md b/docs/_posts/ahmedlone127/2025-01-29-anger_finetune_3_en.md
new file mode 100644
index 00000000000000..353f7b9b787a90
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-anger_finetune_3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English anger_finetune_3 XlmRoBertaForSequenceClassification from chengeorge
+author: John Snow Labs
+name: anger_finetune_3
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`anger_finetune_3` is a English model originally trained by chengeorge.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/anger_finetune_3_en_5.5.1_3.0_1738127531236.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/anger_finetune_3_en_5.5.1_3.0_1738127531236.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("anger_finetune_3","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("anger_finetune_3", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|anger_finetune_3|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/chengeorge/Anger_Finetune_3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-anger_finetune_3_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-anger_finetune_3_pipeline_en.md
new file mode 100644
index 00000000000000..9d1ab571e946ee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-anger_finetune_3_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English anger_finetune_3_pipeline pipeline XlmRoBertaForSequenceClassification from chengeorge
+author: John Snow Labs
+name: anger_finetune_3_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`anger_finetune_3_pipeline` is a English model originally trained by chengeorge.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/anger_finetune_3_pipeline_en_5.5.1_3.0_1738127583081.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/anger_finetune_3_pipeline_en_5.5.1_3.0_1738127583081.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("anger_finetune_3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("anger_finetune_3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|anger_finetune_3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/chengeorge/Anger_Finetune_3
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-augmented_model_fast_3_b_en.md b/docs/_posts/ahmedlone127/2025-01-29-augmented_model_fast_3_b_en.md
new file mode 100644
index 00000000000000..29b4279dc1b2de
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-augmented_model_fast_3_b_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English augmented_model_fast_3_b DistilBertForSequenceClassification from LeonardoFettucciari
+author: John Snow Labs
+name: augmented_model_fast_3_b
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`augmented_model_fast_3_b` is a English model originally trained by LeonardoFettucciari.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/augmented_model_fast_3_b_en_5.5.1_3.0_1738110483843.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/augmented_model_fast_3_b_en_5.5.1_3.0_1738110483843.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("augmented_model_fast_3_b","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("augmented_model_fast_3_b", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|augmented_model_fast_3_b|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/LeonardoFettucciari/augmented_model_fast_3_b
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-augmented_model_fast_3_b_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-augmented_model_fast_3_b_pipeline_en.md
new file mode 100644
index 00000000000000..6fbd630cf4d4aa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-augmented_model_fast_3_b_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English augmented_model_fast_3_b_pipeline pipeline DistilBertForSequenceClassification from LeonardoFettucciari
+author: John Snow Labs
+name: augmented_model_fast_3_b_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`augmented_model_fast_3_b_pipeline` is a English model originally trained by LeonardoFettucciari.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/augmented_model_fast_3_b_pipeline_en_5.5.1_3.0_1738110496518.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/augmented_model_fast_3_b_pipeline_en_5.5.1_3.0_1738110496518.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("augmented_model_fast_3_b_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("augmented_model_fast_3_b_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|augmented_model_fast_3_b_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/LeonardoFettucciari/augmented_model_fast_3_b
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-autotrain_okr_iptal_v2_47383116208_en.md b/docs/_posts/ahmedlone127/2025-01-29-autotrain_okr_iptal_v2_47383116208_en.md
new file mode 100644
index 00000000000000..42a1433ec94c35
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-autotrain_okr_iptal_v2_47383116208_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English autotrain_okr_iptal_v2_47383116208 XlmRoBertaForSequenceClassification from ekincanozcelik
+author: John Snow Labs
+name: autotrain_okr_iptal_v2_47383116208
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_okr_iptal_v2_47383116208` is a English model originally trained by ekincanozcelik.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_okr_iptal_v2_47383116208_en_5.5.1_3.0_1738125764260.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_okr_iptal_v2_47383116208_en_5.5.1_3.0_1738125764260.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("autotrain_okr_iptal_v2_47383116208","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("autotrain_okr_iptal_v2_47383116208", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_okr_iptal_v2_47383116208|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|777.6 MB|
+
+## References
+
+https://huggingface.co/ekincanozcelik/autotrain-okr_iptal_v2-47383116208
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-autotrain_okr_iptal_v2_47383116208_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-autotrain_okr_iptal_v2_47383116208_pipeline_en.md
new file mode 100644
index 00000000000000..0612d06fd7fd2f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-autotrain_okr_iptal_v2_47383116208_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English autotrain_okr_iptal_v2_47383116208_pipeline pipeline XlmRoBertaForSequenceClassification from ekincanozcelik
+author: John Snow Labs
+name: autotrain_okr_iptal_v2_47383116208_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_okr_iptal_v2_47383116208_pipeline` is a English model originally trained by ekincanozcelik.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_okr_iptal_v2_47383116208_pipeline_en_5.5.1_3.0_1738125906325.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_okr_iptal_v2_47383116208_pipeline_en_5.5.1_3.0_1738125906325.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("autotrain_okr_iptal_v2_47383116208_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("autotrain_okr_iptal_v2_47383116208_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_okr_iptal_v2_47383116208_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|777.6 MB|
+
+## References
+
+https://huggingface.co/ekincanozcelik/autotrain-okr_iptal_v2-47383116208
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-balanced_augmented_bert_gest_pred_seqeval_partialmatch_en.md b/docs/_posts/ahmedlone127/2025-01-29-balanced_augmented_bert_gest_pred_seqeval_partialmatch_en.md
new file mode 100644
index 00000000000000..44e9df19da5569
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-balanced_augmented_bert_gest_pred_seqeval_partialmatch_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English balanced_augmented_bert_gest_pred_seqeval_partialmatch BertForTokenClassification from Jsevisal
+author: John Snow Labs
+name: balanced_augmented_bert_gest_pred_seqeval_partialmatch
+date: 2025-01-29
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`balanced_augmented_bert_gest_pred_seqeval_partialmatch` is a English model originally trained by Jsevisal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/balanced_augmented_bert_gest_pred_seqeval_partialmatch_en_5.5.1_3.0_1738111668815.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/balanced_augmented_bert_gest_pred_seqeval_partialmatch_en_5.5.1_3.0_1738111668815.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("balanced_augmented_bert_gest_pred_seqeval_partialmatch","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("balanced_augmented_bert_gest_pred_seqeval_partialmatch", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|balanced_augmented_bert_gest_pred_seqeval_partialmatch|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.8 MB|
+
+## References
+
+https://huggingface.co/Jsevisal/balanced-augmented-bert-gest-pred-seqeval-partialmatch
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-balanced_augmented_bert_gest_pred_seqeval_partialmatch_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-balanced_augmented_bert_gest_pred_seqeval_partialmatch_pipeline_en.md
new file mode 100644
index 00000000000000..8b88c1c07c6afc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-balanced_augmented_bert_gest_pred_seqeval_partialmatch_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English balanced_augmented_bert_gest_pred_seqeval_partialmatch_pipeline pipeline BertForTokenClassification from Jsevisal
+author: John Snow Labs
+name: balanced_augmented_bert_gest_pred_seqeval_partialmatch_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`balanced_augmented_bert_gest_pred_seqeval_partialmatch_pipeline` is a English model originally trained by Jsevisal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/balanced_augmented_bert_gest_pred_seqeval_partialmatch_pipeline_en_5.5.1_3.0_1738111693205.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/balanced_augmented_bert_gest_pred_seqeval_partialmatch_pipeline_en_5.5.1_3.0_1738111693205.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("balanced_augmented_bert_gest_pred_seqeval_partialmatch_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("balanced_augmented_bert_gest_pred_seqeval_partialmatch_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|balanced_augmented_bert_gest_pred_seqeval_partialmatch_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.8 MB|
+
+## References
+
+https://huggingface.co/Jsevisal/balanced-augmented-bert-gest-pred-seqeval-partialmatch
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-bart_large_pubmedd_en.md b/docs/_posts/ahmedlone127/2025-01-29-bart_large_pubmedd_en.md
new file mode 100644
index 00000000000000..635c44da1fddd9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-bart_large_pubmedd_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bart_large_pubmedd BartTransformer from pendar02
+author: John Snow Labs
+name: bart_large_pubmedd
+date: 2025-01-29
+tags: [en, open_source, onnx, text_generation, bart]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BartTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bart_large_pubmedd` is a English model originally trained by pendar02.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bart_large_pubmedd_en_5.5.1_3.0_1738121048947.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bart_large_pubmedd_en_5.5.1_3.0_1738121048947.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = BartTransformer.pretrained("bart_large_pubmedd","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = BartTransformer.pretrained("bart_large_pubmedd","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bart_large_pubmedd|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|810.3 MB|
+
+## References
+
+https://huggingface.co/pendar02/bart-large-pubmedd
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-bart_large_pubmedd_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-bart_large_pubmedd_pipeline_en.md
new file mode 100644
index 00000000000000..920868b6a82781
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-bart_large_pubmedd_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bart_large_pubmedd_pipeline pipeline BartTransformer from pendar02
+author: John Snow Labs
+name: bart_large_pubmedd_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bart_large_pubmedd_pipeline` is a English model originally trained by pendar02.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bart_large_pubmedd_pipeline_en_5.5.1_3.0_1738121090285.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bart_large_pubmedd_pipeline_en_5.5.1_3.0_1738121090285.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bart_large_pubmedd_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bart_large_pubmedd_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bart_large_pubmedd_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|810.3 MB|
+
+## References
+
+https://huggingface.co/pendar02/bart-large-pubmedd
+
+## Included Models
+
+- DocumentAssembler
+- BartTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-base_full_v0_200_en.md b/docs/_posts/ahmedlone127/2025-01-29-base_full_v0_200_en.md
new file mode 100644
index 00000000000000..a26abc2bece2d3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-base_full_v0_200_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English base_full_v0_200 XlmRoBertaForSequenceClassification from sreddy109
+author: John Snow Labs
+name: base_full_v0_200
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`base_full_v0_200` is a English model originally trained by sreddy109.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/base_full_v0_200_en_5.5.1_3.0_1738126532732.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/base_full_v0_200_en_5.5.1_3.0_1738126532732.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("base_full_v0_200","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("base_full_v0_200", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|base_full_v0_200|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|993.9 MB|
+
+## References
+
+https://huggingface.co/sreddy109/base-full-v0-200
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-base_full_v0_200_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-base_full_v0_200_pipeline_en.md
new file mode 100644
index 00000000000000..b531882c2d2fc5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-base_full_v0_200_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English base_full_v0_200_pipeline pipeline XlmRoBertaForSequenceClassification from sreddy109
+author: John Snow Labs
+name: base_full_v0_200_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`base_full_v0_200_pipeline` is a English model originally trained by sreddy109.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/base_full_v0_200_pipeline_en_5.5.1_3.0_1738126588967.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/base_full_v0_200_pipeline_en_5.5.1_3.0_1738126588967.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("base_full_v0_200_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("base_full_v0_200_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|base_full_v0_200_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|993.9 MB|
+
+## References
+
+https://huggingface.co/sreddy109/base-full-v0-200
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-bert_adaptation_peppa_pig_valentinbrodsky_en.md b/docs/_posts/ahmedlone127/2025-01-29-bert_adaptation_peppa_pig_valentinbrodsky_en.md
new file mode 100644
index 00000000000000..f6af4e417075ec
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-bert_adaptation_peppa_pig_valentinbrodsky_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_adaptation_peppa_pig_valentinbrodsky BertEmbeddings from valentinbrodsky
+author: John Snow Labs
+name: bert_adaptation_peppa_pig_valentinbrodsky
+date: 2025-01-29
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_peppa_pig_valentinbrodsky` is a English model originally trained by valentinbrodsky.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_peppa_pig_valentinbrodsky_en_5.5.1_3.0_1738119606220.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_peppa_pig_valentinbrodsky_en_5.5.1_3.0_1738119606220.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_adaptation_peppa_pig_valentinbrodsky","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_adaptation_peppa_pig_valentinbrodsky","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_peppa_pig_valentinbrodsky|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/valentinbrodsky/bert_adaptation_peppa_pig
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-bert_adaptation_peppa_pig_valentinbrodsky_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-bert_adaptation_peppa_pig_valentinbrodsky_pipeline_en.md
new file mode 100644
index 00000000000000..21e68ce5805593
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-bert_adaptation_peppa_pig_valentinbrodsky_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_adaptation_peppa_pig_valentinbrodsky_pipeline pipeline BertEmbeddings from valentinbrodsky
+author: John Snow Labs
+name: bert_adaptation_peppa_pig_valentinbrodsky_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_adaptation_peppa_pig_valentinbrodsky_pipeline` is a English model originally trained by valentinbrodsky.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_adaptation_peppa_pig_valentinbrodsky_pipeline_en_5.5.1_3.0_1738119627725.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_adaptation_peppa_pig_valentinbrodsky_pipeline_en_5.5.1_3.0_1738119627725.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_adaptation_peppa_pig_valentinbrodsky_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_adaptation_peppa_pig_valentinbrodsky_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_adaptation_peppa_pig_valentinbrodsky_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/valentinbrodsky/bert_adaptation_peppa_pig
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-bert_base_german_cased_mlm_chemistry_en.md b/docs/_posts/ahmedlone127/2025-01-29-bert_base_german_cased_mlm_chemistry_en.md
new file mode 100644
index 00000000000000..4d155b9893f29d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-bert_base_german_cased_mlm_chemistry_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_german_cased_mlm_chemistry BertEmbeddings from jonas-luehrs
+author: John Snow Labs
+name: bert_base_german_cased_mlm_chemistry
+date: 2025-01-29
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_german_cased_mlm_chemistry` is a English model originally trained by jonas-luehrs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_german_cased_mlm_chemistry_en_5.5.1_3.0_1738120175191.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_german_cased_mlm_chemistry_en_5.5.1_3.0_1738120175191.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_base_german_cased_mlm_chemistry","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_base_german_cased_mlm_chemistry","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_german_cased_mlm_chemistry|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/jonas-luehrs/bert-base-german-cased-MLM-chemistry
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-bert_base_german_cased_mlm_chemistry_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-bert_base_german_cased_mlm_chemistry_pipeline_en.md
new file mode 100644
index 00000000000000..bb7bb81ebd0804
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-bert_base_german_cased_mlm_chemistry_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_german_cased_mlm_chemistry_pipeline pipeline BertEmbeddings from jonas-luehrs
+author: John Snow Labs
+name: bert_base_german_cased_mlm_chemistry_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_german_cased_mlm_chemistry_pipeline` is a English model originally trained by jonas-luehrs.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_german_cased_mlm_chemistry_pipeline_en_5.5.1_3.0_1738120195957.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_german_cased_mlm_chemistry_pipeline_en_5.5.1_3.0_1738120195957.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_german_cased_mlm_chemistry_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_german_cased_mlm_chemistry_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_german_cased_mlm_chemistry_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/jonas-luehrs/bert-base-german-cased-MLM-chemistry
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-bert_base_turkish_cased_finetuned_downstreamed_en.md b/docs/_posts/ahmedlone127/2025-01-29-bert_base_turkish_cased_finetuned_downstreamed_en.md
new file mode 100644
index 00000000000000..f2eeb3fb1aeb1e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-bert_base_turkish_cased_finetuned_downstreamed_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_turkish_cased_finetuned_downstreamed BertEmbeddings from cahmetcan
+author: John Snow Labs
+name: bert_base_turkish_cased_finetuned_downstreamed
+date: 2025-01-29
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_turkish_cased_finetuned_downstreamed` is a English model originally trained by cahmetcan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_turkish_cased_finetuned_downstreamed_en_5.5.1_3.0_1738120270729.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_turkish_cased_finetuned_downstreamed_en_5.5.1_3.0_1738120270729.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_base_turkish_cased_finetuned_downstreamed","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_base_turkish_cased_finetuned_downstreamed","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_turkish_cased_finetuned_downstreamed|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|412.3 MB|
+
+## References
+
+https://huggingface.co/cahmetcan/bert-base-turkish-cased-finetuned-downstreamed
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-bert_base_turkish_cased_finetuned_downstreamed_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-bert_base_turkish_cased_finetuned_downstreamed_pipeline_en.md
new file mode 100644
index 00000000000000..ff7d206f302d88
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-bert_base_turkish_cased_finetuned_downstreamed_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_turkish_cased_finetuned_downstreamed_pipeline pipeline BertEmbeddings from cahmetcan
+author: John Snow Labs
+name: bert_base_turkish_cased_finetuned_downstreamed_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_turkish_cased_finetuned_downstreamed_pipeline` is a English model originally trained by cahmetcan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_turkish_cased_finetuned_downstreamed_pipeline_en_5.5.1_3.0_1738120291298.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_turkish_cased_finetuned_downstreamed_pipeline_en_5.5.1_3.0_1738120291298.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_turkish_cased_finetuned_downstreamed_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_turkish_cased_finetuned_downstreamed_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_turkish_cased_finetuned_downstreamed_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|412.3 MB|
+
+## References
+
+https://huggingface.co/cahmetcan/bert-base-turkish-cased-finetuned-downstreamed
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-bert_base_uncased_jackmin108_en.md b/docs/_posts/ahmedlone127/2025-01-29-bert_base_uncased_jackmin108_en.md
new file mode 100644
index 00000000000000..1654b4bb72a2c2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-bert_base_uncased_jackmin108_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_uncased_jackmin108 BertEmbeddings from Jackmin108
+author: John Snow Labs
+name: bert_base_uncased_jackmin108
+date: 2025-01-29
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_jackmin108` is a English model originally trained by Jackmin108.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_jackmin108_en_5.5.1_3.0_1738120359801.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_jackmin108_en_5.5.1_3.0_1738120359801.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_base_uncased_jackmin108","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_base_uncased_jackmin108","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_jackmin108|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/Jackmin108/bert-base-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-bert_base_uncased_jackmin108_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-bert_base_uncased_jackmin108_pipeline_en.md
new file mode 100644
index 00000000000000..dad6ffadc503f7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-bert_base_uncased_jackmin108_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_uncased_jackmin108_pipeline pipeline BertEmbeddings from Jackmin108
+author: John Snow Labs
+name: bert_base_uncased_jackmin108_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_jackmin108_pipeline` is a English model originally trained by Jackmin108.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_jackmin108_pipeline_en_5.5.1_3.0_1738120380494.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_jackmin108_pipeline_en_5.5.1_3.0_1738120380494.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_base_uncased_jackmin108_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_jackmin108_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_jackmin108_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/Jackmin108/bert-base-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-bert_distilled_en.md b/docs/_posts/ahmedlone127/2025-01-29-bert_distilled_en.md
new file mode 100644
index 00000000000000..73d57650812dff
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-bert_distilled_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_distilled DistilBertForSequenceClassification from adjohn1313
+author: John Snow Labs
+name: bert_distilled
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_distilled` is a English model originally trained by adjohn1313.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_distilled_en_5.5.1_3.0_1738109958733.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_distilled_en_5.5.1_3.0_1738109958733.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("bert_distilled","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("bert_distilled", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_distilled|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/adjohn1313/bert-distilled
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-bert_distilled_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-bert_distilled_pipeline_en.md
new file mode 100644
index 00000000000000..c0353ca8d3c656
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-bert_distilled_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_distilled_pipeline pipeline DistilBertForSequenceClassification from adjohn1313
+author: John Snow Labs
+name: bert_distilled_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_distilled_pipeline` is a English model originally trained by adjohn1313.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_distilled_pipeline_en_5.5.1_3.0_1738109971712.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_distilled_pipeline_en_5.5.1_3.0_1738109971712.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_distilled_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_distilled_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_distilled_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/adjohn1313/bert-distilled
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-bert_finetuned_ner_a1_a2_a3_a4_tok_1k_10k_e6_v1_en.md b/docs/_posts/ahmedlone127/2025-01-29-bert_finetuned_ner_a1_a2_a3_a4_tok_1k_10k_e6_v1_en.md
new file mode 100644
index 00000000000000..1ef838dc3b1bee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-bert_finetuned_ner_a1_a2_a3_a4_tok_1k_10k_e6_v1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_finetuned_ner_a1_a2_a3_a4_tok_1k_10k_e6_v1 BertForTokenClassification from divya1111
+author: John Snow Labs
+name: bert_finetuned_ner_a1_a2_a3_a4_tok_1k_10k_e6_v1
+date: 2025-01-29
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_a1_a2_a3_a4_tok_1k_10k_e6_v1` is a English model originally trained by divya1111.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_a1_a2_a3_a4_tok_1k_10k_e6_v1_en_5.5.1_3.0_1738111863470.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_a1_a2_a3_a4_tok_1k_10k_e6_v1_en_5.5.1_3.0_1738111863470.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_finetuned_ner_a1_a2_a3_a4_tok_1k_10k_e6_v1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner_a1_a2_a3_a4_tok_1k_10k_e6_v1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_a1_a2_a3_a4_tok_1k_10k_e6_v1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/divya1111/bert-finetuned-ner-a1-a2-a3-a4-tok-1k-10k-e6-v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-bert_finetuned_ner_a1_a2_a3_a4_tok_1k_10k_e6_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-bert_finetuned_ner_a1_a2_a3_a4_tok_1k_10k_e6_v1_pipeline_en.md
new file mode 100644
index 00000000000000..5fd1eba2710e5e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-bert_finetuned_ner_a1_a2_a3_a4_tok_1k_10k_e6_v1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_finetuned_ner_a1_a2_a3_a4_tok_1k_10k_e6_v1_pipeline pipeline BertForTokenClassification from divya1111
+author: John Snow Labs
+name: bert_finetuned_ner_a1_a2_a3_a4_tok_1k_10k_e6_v1_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_a1_a2_a3_a4_tok_1k_10k_e6_v1_pipeline` is a English model originally trained by divya1111.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_a1_a2_a3_a4_tok_1k_10k_e6_v1_pipeline_en_5.5.1_3.0_1738111923125.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_a1_a2_a3_a4_tok_1k_10k_e6_v1_pipeline_en_5.5.1_3.0_1738111923125.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_ner_a1_a2_a3_a4_tok_1k_10k_e6_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_ner_a1_a2_a3_a4_tok_1k_10k_e6_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_a1_a2_a3_a4_tok_1k_10k_e6_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/divya1111/bert-finetuned-ner-a1-a2-a3-a4-tok-1k-10k-e6-v1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-bert_finetuned_ner_clinical_plncmm_large_23_en.md b/docs/_posts/ahmedlone127/2025-01-29-bert_finetuned_ner_clinical_plncmm_large_23_en.md
new file mode 100644
index 00000000000000..9b523358e14b71
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-bert_finetuned_ner_clinical_plncmm_large_23_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_finetuned_ner_clinical_plncmm_large_23 BertForTokenClassification from crisU8
+author: John Snow Labs
+name: bert_finetuned_ner_clinical_plncmm_large_23
+date: 2025-01-29
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_clinical_plncmm_large_23` is a English model originally trained by crisU8.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_clinical_plncmm_large_23_en_5.5.1_3.0_1738112454952.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_clinical_plncmm_large_23_en_5.5.1_3.0_1738112454952.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_finetuned_ner_clinical_plncmm_large_23","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner_clinical_plncmm_large_23", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_clinical_plncmm_large_23|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/crisU8/bert-finetuned-ner-clinical-plncmm-large-23
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-bert_finetuned_ner_clinical_plncmm_large_23_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-bert_finetuned_ner_clinical_plncmm_large_23_pipeline_en.md
new file mode 100644
index 00000000000000..688cd4fcf39fbd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-bert_finetuned_ner_clinical_plncmm_large_23_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_finetuned_ner_clinical_plncmm_large_23_pipeline pipeline BertForTokenClassification from crisU8
+author: John Snow Labs
+name: bert_finetuned_ner_clinical_plncmm_large_23_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_clinical_plncmm_large_23_pipeline` is a English model originally trained by crisU8.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_clinical_plncmm_large_23_pipeline_en_5.5.1_3.0_1738112476192.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_clinical_plncmm_large_23_pipeline_en_5.5.1_3.0_1738112476192.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_ner_clinical_plncmm_large_23_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_ner_clinical_plncmm_large_23_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_clinical_plncmm_large_23_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/crisU8/bert-finetuned-ner-clinical-plncmm-large-23
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-bert_finetuned_ner_grace_pro_en.md b/docs/_posts/ahmedlone127/2025-01-29-bert_finetuned_ner_grace_pro_en.md
new file mode 100644
index 00000000000000..1285fa724a6c36
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-bert_finetuned_ner_grace_pro_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_finetuned_ner_grace_pro BertForTokenClassification from grace-pro
+author: John Snow Labs
+name: bert_finetuned_ner_grace_pro
+date: 2025-01-29
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_grace_pro` is a English model originally trained by grace-pro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_grace_pro_en_5.5.1_3.0_1738112187359.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_grace_pro_en_5.5.1_3.0_1738112187359.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_finetuned_ner_grace_pro","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner_grace_pro", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_grace_pro|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/grace-pro/bert-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-bert_finetuned_ner_grace_pro_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-bert_finetuned_ner_grace_pro_pipeline_en.md
new file mode 100644
index 00000000000000..fd9a34f47ca620
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-bert_finetuned_ner_grace_pro_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_finetuned_ner_grace_pro_pipeline pipeline BertForTokenClassification from grace-pro
+author: John Snow Labs
+name: bert_finetuned_ner_grace_pro_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_grace_pro_pipeline` is a English model originally trained by grace-pro.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_grace_pro_pipeline_en_5.5.1_3.0_1738112207397.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_grace_pro_pipeline_en_5.5.1_3.0_1738112207397.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_ner_grace_pro_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_ner_grace_pro_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_grace_pro_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/grace-pro/bert-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-bert_finetuned_ner_mariafogh_en.md b/docs/_posts/ahmedlone127/2025-01-29-bert_finetuned_ner_mariafogh_en.md
new file mode 100644
index 00000000000000..af5e66dd096c88
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-bert_finetuned_ner_mariafogh_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_finetuned_ner_mariafogh BertForTokenClassification from MariaFogh
+author: John Snow Labs
+name: bert_finetuned_ner_mariafogh
+date: 2025-01-29
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_mariafogh` is a English model originally trained by MariaFogh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_mariafogh_en_5.5.1_3.0_1738111913720.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_mariafogh_en_5.5.1_3.0_1738111913720.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_finetuned_ner_mariafogh","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner_mariafogh", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_mariafogh|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/MariaFogh/bert-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-bert_finetuned_ner_mariafogh_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-bert_finetuned_ner_mariafogh_pipeline_en.md
new file mode 100644
index 00000000000000..d3f7eb76898785
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-bert_finetuned_ner_mariafogh_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_finetuned_ner_mariafogh_pipeline pipeline BertForTokenClassification from MariaFogh
+author: John Snow Labs
+name: bert_finetuned_ner_mariafogh_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_mariafogh_pipeline` is a English model originally trained by MariaFogh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_mariafogh_pipeline_en_5.5.1_3.0_1738111933716.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_mariafogh_pipeline_en_5.5.1_3.0_1738111933716.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_finetuned_ner_mariafogh_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_ner_mariafogh_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_mariafogh_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/MariaFogh/bert-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-bert_ner_sadashiv_en.md b/docs/_posts/ahmedlone127/2025-01-29-bert_ner_sadashiv_en.md
new file mode 100644
index 00000000000000..c6904a80bf210e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-bert_ner_sadashiv_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_ner_sadashiv BertForTokenClassification from Sadashiv
+author: John Snow Labs
+name: bert_ner_sadashiv
+date: 2025-01-29
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ner_sadashiv` is a English model originally trained by Sadashiv.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ner_sadashiv_en_5.5.1_3.0_1738112254942.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ner_sadashiv_en_5.5.1_3.0_1738112254942.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_ner_sadashiv","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_ner_sadashiv", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_ner_sadashiv|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/Sadashiv/BERT-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-bert_ner_sadashiv_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-bert_ner_sadashiv_pipeline_en.md
new file mode 100644
index 00000000000000..2f43e41d1f7fef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-bert_ner_sadashiv_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_ner_sadashiv_pipeline pipeline BertForTokenClassification from Sadashiv
+author: John Snow Labs
+name: bert_ner_sadashiv_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ner_sadashiv_pipeline` is a English model originally trained by Sadashiv.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ner_sadashiv_pipeline_en_5.5.1_3.0_1738112275488.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ner_sadashiv_pipeline_en_5.5.1_3.0_1738112275488.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("bert_ner_sadashiv_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_ner_sadashiv_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_ner_sadashiv_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/Sadashiv/BERT-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-berttest_en.md b/docs/_posts/ahmedlone127/2025-01-29-berttest_en.md
new file mode 100644
index 00000000000000..b7c996dc4648df
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-berttest_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English berttest BertForTokenClassification from RtwC
+author: John Snow Labs
+name: berttest
+date: 2025-01-29
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`berttest` is a English model originally trained by RtwC.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/berttest_en_5.5.1_3.0_1738112596101.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/berttest_en_5.5.1_3.0_1738112596101.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("berttest","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("berttest", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|berttest|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/RtwC/berttest
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-berttest_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-berttest_pipeline_en.md
new file mode 100644
index 00000000000000..c2f6dbdcea1ed2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-berttest_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English berttest_pipeline pipeline BertForTokenClassification from RtwC
+author: John Snow Labs
+name: berttest_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`berttest_pipeline` is a English model originally trained by RtwC.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/berttest_pipeline_en_5.5.1_3.0_1738112617404.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/berttest_pipeline_en_5.5.1_3.0_1738112617404.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("berttest_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("berttest_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|berttest_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/RtwC/berttest
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-biobert_all_deep_en.md b/docs/_posts/ahmedlone127/2025-01-29-biobert_all_deep_en.md
new file mode 100644
index 00000000000000..3275c9207e9902
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-biobert_all_deep_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English biobert_all_deep BertForTokenClassification from jialinselenasong
+author: John Snow Labs
+name: biobert_all_deep
+date: 2025-01-29
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biobert_all_deep` is a English model originally trained by jialinselenasong.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biobert_all_deep_en_5.5.1_3.0_1738112339343.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biobert_all_deep_en_5.5.1_3.0_1738112339343.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("biobert_all_deep","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("biobert_all_deep", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|biobert_all_deep|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.2 MB|
+
+## References
+
+https://huggingface.co/jialinselenasong/biobert-all-deep
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-biobert_all_deep_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-biobert_all_deep_pipeline_en.md
new file mode 100644
index 00000000000000..aef9988d55909e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-biobert_all_deep_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English biobert_all_deep_pipeline pipeline BertForTokenClassification from jialinselenasong
+author: John Snow Labs
+name: biobert_all_deep_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biobert_all_deep_pipeline` is a English model originally trained by jialinselenasong.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biobert_all_deep_pipeline_en_5.5.1_3.0_1738112360499.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biobert_all_deep_pipeline_en_5.5.1_3.0_1738112360499.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("biobert_all_deep_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("biobert_all_deep_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|biobert_all_deep_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.2 MB|
+
+## References
+
+https://huggingface.co/jialinselenasong/biobert-all-deep
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_eli5_mlm_model_brandonooinyp_en.md b/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_eli5_mlm_model_brandonooinyp_en.md
new file mode 100644
index 00000000000000..ec66bcd2c9a760
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_eli5_mlm_model_brandonooinyp_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_eli5_mlm_model_brandonooinyp RoBertaEmbeddings from brandonooinyp
+author: John Snow Labs
+name: burmese_awesome_eli5_mlm_model_brandonooinyp
+date: 2025-01-29
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_eli5_mlm_model_brandonooinyp` is a English model originally trained by brandonooinyp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_brandonooinyp_en_5.5.1_3.0_1738134409766.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_brandonooinyp_en_5.5.1_3.0_1738134409766.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("burmese_awesome_eli5_mlm_model_brandonooinyp","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("burmese_awesome_eli5_mlm_model_brandonooinyp","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_eli5_mlm_model_brandonooinyp|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/brandonooinyp/my_awesome_eli5_mlm_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_eli5_mlm_model_brandonooinyp_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_eli5_mlm_model_brandonooinyp_pipeline_en.md
new file mode 100644
index 00000000000000..45fa3193ca2f35
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_eli5_mlm_model_brandonooinyp_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_eli5_mlm_model_brandonooinyp_pipeline pipeline RoBertaEmbeddings from brandonooinyp
+author: John Snow Labs
+name: burmese_awesome_eli5_mlm_model_brandonooinyp_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_eli5_mlm_model_brandonooinyp_pipeline` is a English model originally trained by brandonooinyp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_brandonooinyp_pipeline_en_5.5.1_3.0_1738134425644.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_eli5_mlm_model_brandonooinyp_pipeline_en_5.5.1_3.0_1738134425644.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_eli5_mlm_model_brandonooinyp_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_eli5_mlm_model_brandonooinyp_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_eli5_mlm_model_brandonooinyp_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/brandonooinyp/my_awesome_eli5_mlm_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_model_basmaelhoseny01_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_model_basmaelhoseny01_pipeline_en.md
new file mode 100644
index 00000000000000..039ac256572dfa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_model_basmaelhoseny01_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_basmaelhoseny01_pipeline pipeline DistilBertForSequenceClassification from basmaelhoseny01
+author: John Snow Labs
+name: burmese_awesome_model_basmaelhoseny01_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_basmaelhoseny01_pipeline` is a English model originally trained by basmaelhoseny01.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_basmaelhoseny01_pipeline_en_5.5.1_3.0_1738130929196.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_basmaelhoseny01_pipeline_en_5.5.1_3.0_1738130929196.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_basmaelhoseny01_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_basmaelhoseny01_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_basmaelhoseny01_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/basmaelhoseny01/my_awesome_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_model_derf989_en.md b/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_model_derf989_en.md
new file mode 100644
index 00000000000000..bfa30611fdedcc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_model_derf989_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_derf989 DistilBertForSequenceClassification from Derf989
+author: John Snow Labs
+name: burmese_awesome_model_derf989
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_derf989` is a English model originally trained by Derf989.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_derf989_en_5.5.1_3.0_1738131563212.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_derf989_en_5.5.1_3.0_1738131563212.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_derf989","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_derf989", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_derf989|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Derf989/my_awesome_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_model_derf989_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_model_derf989_pipeline_en.md
new file mode 100644
index 00000000000000..0c7ee684a7223e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_model_derf989_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_derf989_pipeline pipeline DistilBertForSequenceClassification from Derf989
+author: John Snow Labs
+name: burmese_awesome_model_derf989_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_derf989_pipeline` is a English model originally trained by Derf989.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_derf989_pipeline_en_5.5.1_3.0_1738131580390.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_derf989_pipeline_en_5.5.1_3.0_1738131580390.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_derf989_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_derf989_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_derf989_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Derf989/my_awesome_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_model_luminar9_en.md b/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_model_luminar9_en.md
new file mode 100644
index 00000000000000..4686eb325cdfe3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_model_luminar9_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_luminar9 DistilBertForSequenceClassification from luminar9
+author: John Snow Labs
+name: burmese_awesome_model_luminar9
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_luminar9` is a English model originally trained by luminar9.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_luminar9_en_5.5.1_3.0_1738110808339.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_luminar9_en_5.5.1_3.0_1738110808339.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_luminar9","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_luminar9", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_luminar9|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/luminar9/my_awesome_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_model_luminar9_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_model_luminar9_pipeline_en.md
new file mode 100644
index 00000000000000..8606a4641e7c60
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_model_luminar9_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_luminar9_pipeline pipeline DistilBertForSequenceClassification from luminar9
+author: John Snow Labs
+name: burmese_awesome_model_luminar9_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_luminar9_pipeline` is a English model originally trained by luminar9.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_luminar9_pipeline_en_5.5.1_3.0_1738110820844.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_luminar9_pipeline_en_5.5.1_3.0_1738110820844.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_luminar9_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_luminar9_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_luminar9_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/luminar9/my_awesome_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_model_pradhyumnaporalla_en.md b/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_model_pradhyumnaporalla_en.md
new file mode 100644
index 00000000000000..c3e862ee7c78d2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_model_pradhyumnaporalla_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_pradhyumnaporalla DistilBertForSequenceClassification from PradhyumnaPoralla
+author: John Snow Labs
+name: burmese_awesome_model_pradhyumnaporalla
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_pradhyumnaporalla` is a English model originally trained by PradhyumnaPoralla.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_pradhyumnaporalla_en_5.5.1_3.0_1738131284353.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_pradhyumnaporalla_en_5.5.1_3.0_1738131284353.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_pradhyumnaporalla","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_pradhyumnaporalla", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_pradhyumnaporalla|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/PradhyumnaPoralla/my_awesome_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_model_pradhyumnaporalla_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_model_pradhyumnaporalla_pipeline_en.md
new file mode 100644
index 00000000000000..bc3630123a94ea
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_model_pradhyumnaporalla_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_pradhyumnaporalla_pipeline pipeline DistilBertForSequenceClassification from PradhyumnaPoralla
+author: John Snow Labs
+name: burmese_awesome_model_pradhyumnaporalla_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_pradhyumnaporalla_pipeline` is a English model originally trained by PradhyumnaPoralla.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_pradhyumnaporalla_pipeline_en_5.5.1_3.0_1738131298475.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_pradhyumnaporalla_pipeline_en_5.5.1_3.0_1738131298475.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_pradhyumnaporalla_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_pradhyumnaporalla_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_pradhyumnaporalla_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/PradhyumnaPoralla/my_awesome_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_model_sebikoda_en.md b/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_model_sebikoda_en.md
new file mode 100644
index 00000000000000..b15ba441b110ef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_model_sebikoda_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_sebikoda DistilBertForSequenceClassification from sebikOda
+author: John Snow Labs
+name: burmese_awesome_model_sebikoda
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_sebikoda` is a English model originally trained by sebikOda.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_sebikoda_en_5.5.1_3.0_1738110215569.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_sebikoda_en_5.5.1_3.0_1738110215569.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_sebikoda","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_sebikoda", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_sebikoda|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/sebikOda/my_awesome_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_model_sebikoda_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_model_sebikoda_pipeline_en.md
new file mode 100644
index 00000000000000..c6adb4091f75f6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_model_sebikoda_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_sebikoda_pipeline pipeline DistilBertForSequenceClassification from sebikOda
+author: John Snow Labs
+name: burmese_awesome_model_sebikoda_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_sebikoda_pipeline` is a English model originally trained by sebikOda.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_sebikoda_pipeline_en_5.5.1_3.0_1738110229043.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_sebikoda_pipeline_en_5.5.1_3.0_1738110229043.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_sebikoda_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_sebikoda_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_sebikoda_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/sebikOda/my_awesome_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_model_tikasah84_en.md b/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_model_tikasah84_en.md
new file mode 100644
index 00000000000000..f5f457bafa3872
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_model_tikasah84_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_tikasah84 DistilBertForSequenceClassification from tikasah84
+author: John Snow Labs
+name: burmese_awesome_model_tikasah84
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_tikasah84` is a English model originally trained by tikasah84.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_tikasah84_en_5.5.1_3.0_1738110154589.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_tikasah84_en_5.5.1_3.0_1738110154589.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_tikasah84","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_tikasah84", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_tikasah84|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/tikasah84/my_awesome_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_model_tikasah84_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_model_tikasah84_pipeline_en.md
new file mode 100644
index 00000000000000..61bfc336d35129
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_model_tikasah84_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_tikasah84_pipeline pipeline DistilBertForSequenceClassification from tikasah84
+author: John Snow Labs
+name: burmese_awesome_model_tikasah84_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_tikasah84_pipeline` is a English model originally trained by tikasah84.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_tikasah84_pipeline_en_5.5.1_3.0_1738110167871.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_tikasah84_pipeline_en_5.5.1_3.0_1738110167871.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_model_tikasah84_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_tikasah84_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_tikasah84_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/tikasah84/my_awesome_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_opus_books_model_2_en.md b/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_opus_books_model_2_en.md
new file mode 100644
index 00000000000000..5d10b8287b9406
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_opus_books_model_2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_opus_books_model_2 T5Transformer from figuepants
+author: John Snow Labs
+name: burmese_awesome_opus_books_model_2
+date: 2025-01-29
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_opus_books_model_2` is a English model originally trained by figuepants.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_2_en_5.5.1_3.0_1738137045736.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_2_en_5.5.1_3.0_1738137045736.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("burmese_awesome_opus_books_model_2","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("burmese_awesome_opus_books_model_2", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_opus_books_model_2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|282.2 MB|
+
+## References
+
+https://huggingface.co/figuepants/my_awesome_opus_books_model-2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_opus_books_model_2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_opus_books_model_2_pipeline_en.md
new file mode 100644
index 00000000000000..c92a1fb86064eb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_opus_books_model_2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_opus_books_model_2_pipeline pipeline T5Transformer from figuepants
+author: John Snow Labs
+name: burmese_awesome_opus_books_model_2_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_opus_books_model_2_pipeline` is a English model originally trained by figuepants.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_2_pipeline_en_5.5.1_3.0_1738137061314.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_opus_books_model_2_pipeline_en_5.5.1_3.0_1738137061314.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_opus_books_model_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_opus_books_model_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_opus_books_model_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|282.2 MB|
+
+## References
+
+https://huggingface.co/figuepants/my_awesome_opus_books_model-2
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_text_classification_en.md b/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_text_classification_en.md
new file mode 100644
index 00000000000000..a238e6dfaa1851
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_text_classification_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_text_classification XlmRoBertaForSequenceClassification from lilyyellow
+author: John Snow Labs
+name: burmese_awesome_text_classification
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_text_classification` is a English model originally trained by lilyyellow.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_text_classification_en_5.5.1_3.0_1738126526394.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_text_classification_en_5.5.1_3.0_1738126526394.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("burmese_awesome_text_classification","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("burmese_awesome_text_classification", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_text_classification|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|816.6 MB|
+
+## References
+
+https://huggingface.co/lilyyellow/my_awesome_text_classification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_text_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_text_classification_pipeline_en.md
new file mode 100644
index 00000000000000..e5a96cd3f8c77e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-burmese_awesome_text_classification_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_text_classification_pipeline pipeline XlmRoBertaForSequenceClassification from lilyyellow
+author: John Snow Labs
+name: burmese_awesome_text_classification_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_text_classification_pipeline` is a English model originally trained by lilyyellow.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_text_classification_pipeline_en_5.5.1_3.0_1738126645388.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_text_classification_pipeline_en_5.5.1_3.0_1738126645388.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("burmese_awesome_text_classification_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_text_classification_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_text_classification_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|816.6 MB|
+
+## References
+
+https://huggingface.co/lilyyellow/my_awesome_text_classification
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-code_search_codebert_base_random_trimmed_with_g_en.md b/docs/_posts/ahmedlone127/2025-01-29-code_search_codebert_base_random_trimmed_with_g_en.md
new file mode 100644
index 00000000000000..1d7cc870ec0b56
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-code_search_codebert_base_random_trimmed_with_g_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English code_search_codebert_base_random_trimmed_with_g RoBertaForTokenClassification from DianaIulia
+author: John Snow Labs
+name: code_search_codebert_base_random_trimmed_with_g
+date: 2025-01-29
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`code_search_codebert_base_random_trimmed_with_g` is a English model originally trained by DianaIulia.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/code_search_codebert_base_random_trimmed_with_g_en_5.5.1_3.0_1738117096593.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/code_search_codebert_base_random_trimmed_with_g_en_5.5.1_3.0_1738117096593.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("code_search_codebert_base_random_trimmed_with_g","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("code_search_codebert_base_random_trimmed_with_g", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|code_search_codebert_base_random_trimmed_with_g|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|466.1 MB|
+
+## References
+
+https://huggingface.co/DianaIulia/code_search_codebert_base_random_trimmed_with_g
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-code_search_codebert_base_random_trimmed_with_g_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-code_search_codebert_base_random_trimmed_with_g_pipeline_en.md
new file mode 100644
index 00000000000000..c7c9d24bd2e05b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-code_search_codebert_base_random_trimmed_with_g_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English code_search_codebert_base_random_trimmed_with_g_pipeline pipeline RoBertaForTokenClassification from DianaIulia
+author: John Snow Labs
+name: code_search_codebert_base_random_trimmed_with_g_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`code_search_codebert_base_random_trimmed_with_g_pipeline` is a English model originally trained by DianaIulia.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/code_search_codebert_base_random_trimmed_with_g_pipeline_en_5.5.1_3.0_1738117120323.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/code_search_codebert_base_random_trimmed_with_g_pipeline_en_5.5.1_3.0_1738117120323.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("code_search_codebert_base_random_trimmed_with_g_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("code_search_codebert_base_random_trimmed_with_g_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|code_search_codebert_base_random_trimmed_with_g_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.1 MB|
+
+## References
+
+https://huggingface.co/DianaIulia/code_search_codebert_base_random_trimmed_with_g
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-cross_encoder_test_en.md b/docs/_posts/ahmedlone127/2025-01-29-cross_encoder_test_en.md
new file mode 100644
index 00000000000000..88658ea0c57bc3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-cross_encoder_test_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English cross_encoder_test XlmRoBertaForSequenceClassification from jongmyung
+author: John Snow Labs
+name: cross_encoder_test
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cross_encoder_test` is a English model originally trained by jongmyung.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cross_encoder_test_en_5.5.1_3.0_1738125546263.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cross_encoder_test_en_5.5.1_3.0_1738125546263.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("cross_encoder_test","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("cross_encoder_test", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cross_encoder_test|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|402.2 MB|
+
+## References
+
+https://huggingface.co/jongmyung/cross-encoder-test
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-cross_encoder_test_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-cross_encoder_test_pipeline_en.md
new file mode 100644
index 00000000000000..571c3e589f4041
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-cross_encoder_test_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English cross_encoder_test_pipeline pipeline XlmRoBertaForSequenceClassification from jongmyung
+author: John Snow Labs
+name: cross_encoder_test_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cross_encoder_test_pipeline` is a English model originally trained by jongmyung.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cross_encoder_test_pipeline_en_5.5.1_3.0_1738125577916.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cross_encoder_test_pipeline_en_5.5.1_3.0_1738125577916.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("cross_encoder_test_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cross_encoder_test_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cross_encoder_test_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|402.2 MB|
+
+## References
+
+https://huggingface.co/jongmyung/cross-encoder-test
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-customer_reviews_classification_en.md b/docs/_posts/ahmedlone127/2025-01-29-customer_reviews_classification_en.md
new file mode 100644
index 00000000000000..79113788131667
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-customer_reviews_classification_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English customer_reviews_classification DistilBertForSequenceClassification from dnzblgn
+author: John Snow Labs
+name: customer_reviews_classification
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`customer_reviews_classification` is a English model originally trained by dnzblgn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/customer_reviews_classification_en_5.5.1_3.0_1738110849764.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/customer_reviews_classification_en_5.5.1_3.0_1738110849764.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("customer_reviews_classification","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("customer_reviews_classification", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|customer_reviews_classification|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/dnzblgn/Customer-Reviews-Classification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-customer_reviews_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-customer_reviews_classification_pipeline_en.md
new file mode 100644
index 00000000000000..d28d21311d0039
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-customer_reviews_classification_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English customer_reviews_classification_pipeline pipeline DistilBertForSequenceClassification from dnzblgn
+author: John Snow Labs
+name: customer_reviews_classification_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`customer_reviews_classification_pipeline` is a English model originally trained by dnzblgn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/customer_reviews_classification_pipeline_en_5.5.1_3.0_1738110862663.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/customer_reviews_classification_pipeline_en_5.5.1_3.0_1738110862663.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("customer_reviews_classification_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("customer_reviews_classification_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|customer_reviews_classification_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/dnzblgn/Customer-Reviews-Classification
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-custommodel_disney_sentiment_3_en.md b/docs/_posts/ahmedlone127/2025-01-29-custommodel_disney_sentiment_3_en.md
new file mode 100644
index 00000000000000..6105e6c8da98de
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-custommodel_disney_sentiment_3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English custommodel_disney_sentiment_3 DistilBertForSequenceClassification from Lena2024
+author: John Snow Labs
+name: custommodel_disney_sentiment_3
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`custommodel_disney_sentiment_3` is a English model originally trained by Lena2024.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/custommodel_disney_sentiment_3_en_5.5.1_3.0_1738131811815.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/custommodel_disney_sentiment_3_en_5.5.1_3.0_1738131811815.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("custommodel_disney_sentiment_3","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("custommodel_disney_sentiment_3", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|custommodel_disney_sentiment_3|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Lena2024/CustomModel_disney_sentiment_3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-custommodel_disney_sentiment_3_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-custommodel_disney_sentiment_3_pipeline_en.md
new file mode 100644
index 00000000000000..356fd8b9cf32fe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-custommodel_disney_sentiment_3_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English custommodel_disney_sentiment_3_pipeline pipeline DistilBertForSequenceClassification from Lena2024
+author: John Snow Labs
+name: custommodel_disney_sentiment_3_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`custommodel_disney_sentiment_3_pipeline` is a English model originally trained by Lena2024.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/custommodel_disney_sentiment_3_pipeline_en_5.5.1_3.0_1738131824941.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/custommodel_disney_sentiment_3_pipeline_en_5.5.1_3.0_1738131824941.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("custommodel_disney_sentiment_3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("custommodel_disney_sentiment_3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|custommodel_disney_sentiment_3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Lena2024/CustomModel_disney_sentiment_3
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-custommodel_yelp_lena2024_en.md b/docs/_posts/ahmedlone127/2025-01-29-custommodel_yelp_lena2024_en.md
new file mode 100644
index 00000000000000..6a3e5ff09b51a8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-custommodel_yelp_lena2024_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English custommodel_yelp_lena2024 DistilBertForSequenceClassification from Lena2024
+author: John Snow Labs
+name: custommodel_yelp_lena2024
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`custommodel_yelp_lena2024` is a English model originally trained by Lena2024.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/custommodel_yelp_lena2024_en_5.5.1_3.0_1738131701581.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/custommodel_yelp_lena2024_en_5.5.1_3.0_1738131701581.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("custommodel_yelp_lena2024","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("custommodel_yelp_lena2024", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|custommodel_yelp_lena2024|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Lena2024/CustomModel_yelp
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-custommodel_yelp_lena2024_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-custommodel_yelp_lena2024_pipeline_en.md
new file mode 100644
index 00000000000000..96573ec684423c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-custommodel_yelp_lena2024_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English custommodel_yelp_lena2024_pipeline pipeline DistilBertForSequenceClassification from Lena2024
+author: John Snow Labs
+name: custommodel_yelp_lena2024_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`custommodel_yelp_lena2024_pipeline` is a English model originally trained by Lena2024.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/custommodel_yelp_lena2024_pipeline_en_5.5.1_3.0_1738131714443.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/custommodel_yelp_lena2024_pipeline_en_5.5.1_3.0_1738131714443.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("custommodel_yelp_lena2024_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("custommodel_yelp_lena2024_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|custommodel_yelp_lena2024_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Lena2024/CustomModel_yelp
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-d4data_on_babe_on_pranjali_en.md b/docs/_posts/ahmedlone127/2025-01-29-d4data_on_babe_on_pranjali_en.md
new file mode 100644
index 00000000000000..eab865e621c642
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-d4data_on_babe_on_pranjali_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English d4data_on_babe_on_pranjali DistilBertForSequenceClassification from Onunes
+author: John Snow Labs
+name: d4data_on_babe_on_pranjali
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`d4data_on_babe_on_pranjali` is a English model originally trained by Onunes.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/d4data_on_babe_on_pranjali_en_5.5.1_3.0_1738110210271.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/d4data_on_babe_on_pranjali_en_5.5.1_3.0_1738110210271.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("d4data_on_babe_on_pranjali","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("d4data_on_babe_on_pranjali", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|d4data_on_babe_on_pranjali|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.4 MB|
+
+## References
+
+https://huggingface.co/Onunes/D4DATA-on-BABE-on-PRANJALI
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-d4data_on_babe_on_pranjali_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-d4data_on_babe_on_pranjali_pipeline_en.md
new file mode 100644
index 00000000000000..a21619758ea9a2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-d4data_on_babe_on_pranjali_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English d4data_on_babe_on_pranjali_pipeline pipeline DistilBertForSequenceClassification from Onunes
+author: John Snow Labs
+name: d4data_on_babe_on_pranjali_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`d4data_on_babe_on_pranjali_pipeline` is a English model originally trained by Onunes.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/d4data_on_babe_on_pranjali_pipeline_en_5.5.1_3.0_1738110223359.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/d4data_on_babe_on_pranjali_pipeline_en_5.5.1_3.0_1738110223359.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("d4data_on_babe_on_pranjali_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("d4data_on_babe_on_pranjali_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|d4data_on_babe_on_pranjali_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Onunes/D4DATA-on-BABE-on-PRANJALI
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-d4data_on_pranjali_en.md b/docs/_posts/ahmedlone127/2025-01-29-d4data_on_pranjali_en.md
new file mode 100644
index 00000000000000..dfeeca84c654d9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-d4data_on_pranjali_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English d4data_on_pranjali DistilBertForSequenceClassification from Onunes
+author: John Snow Labs
+name: d4data_on_pranjali
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`d4data_on_pranjali` is a English model originally trained by Onunes.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/d4data_on_pranjali_en_5.5.1_3.0_1738110360117.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/d4data_on_pranjali_en_5.5.1_3.0_1738110360117.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("d4data_on_pranjali","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("d4data_on_pranjali", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|d4data_on_pranjali|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.4 MB|
+
+## References
+
+https://huggingface.co/Onunes/D4DATA-on-PRANJALI
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-d4data_on_pranjali_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-d4data_on_pranjali_pipeline_en.md
new file mode 100644
index 00000000000000..09528b54001f7f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-d4data_on_pranjali_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English d4data_on_pranjali_pipeline pipeline DistilBertForSequenceClassification from Onunes
+author: John Snow Labs
+name: d4data_on_pranjali_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`d4data_on_pranjali_pipeline` is a English model originally trained by Onunes.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/d4data_on_pranjali_pipeline_en_5.5.1_3.0_1738110376323.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/d4data_on_pranjali_pipeline_en_5.5.1_3.0_1738110376323.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("d4data_on_pranjali_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("d4data_on_pranjali_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|d4data_on_pranjali_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Onunes/D4DATA-on-PRANJALI
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-danskbert_ed_en.md b/docs/_posts/ahmedlone127/2025-01-29-danskbert_ed_en.md
new file mode 100644
index 00000000000000..7d891af08a9945
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-danskbert_ed_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English danskbert_ed XlmRoBertaForSequenceClassification from yemen2016
+author: John Snow Labs
+name: danskbert_ed
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`danskbert_ed` is a English model originally trained by yemen2016.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/danskbert_ed_en_5.5.1_3.0_1738125465973.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/danskbert_ed_en_5.5.1_3.0_1738125465973.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("danskbert_ed","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("danskbert_ed", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|danskbert_ed|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|423.0 MB|
+
+## References
+
+https://huggingface.co/yemen2016/danskbert_ED
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-danskbert_ed_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-danskbert_ed_pipeline_en.md
new file mode 100644
index 00000000000000..ce6ebf99c93153
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-danskbert_ed_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English danskbert_ed_pipeline pipeline XlmRoBertaForSequenceClassification from yemen2016
+author: John Snow Labs
+name: danskbert_ed_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`danskbert_ed_pipeline` is a English model originally trained by yemen2016.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/danskbert_ed_pipeline_en_5.5.1_3.0_1738125505334.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/danskbert_ed_pipeline_en_5.5.1_3.0_1738125505334.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("danskbert_ed_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("danskbert_ed_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|danskbert_ed_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|423.0 MB|
+
+## References
+
+https://huggingface.co/yemen2016/danskbert_ED
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-db_aca_4_2_en.md b/docs/_posts/ahmedlone127/2025-01-29-db_aca_4_2_en.md
new file mode 100644
index 00000000000000..32a65d3acfdc5d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-db_aca_4_2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English db_aca_4_2 DistilBertForSequenceClassification from exala
+author: John Snow Labs
+name: db_aca_4_2
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`db_aca_4_2` is a English model originally trained by exala.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/db_aca_4_2_en_5.5.1_3.0_1738131555330.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/db_aca_4_2_en_5.5.1_3.0_1738131555330.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("db_aca_4_2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("db_aca_4_2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|db_aca_4_2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.6 MB|
+
+## References
+
+https://huggingface.co/exala/db_aca_4.2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-db_aca_4_2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-db_aca_4_2_pipeline_en.md
new file mode 100644
index 00000000000000..924509c87d5284
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-db_aca_4_2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English db_aca_4_2_pipeline pipeline DistilBertForSequenceClassification from exala
+author: John Snow Labs
+name: db_aca_4_2_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`db_aca_4_2_pipeline` is a English model originally trained by exala.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/db_aca_4_2_pipeline_en_5.5.1_3.0_1738131568643.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/db_aca_4_2_pipeline_en_5.5.1_3.0_1738131568643.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("db_aca_4_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("db_aca_4_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|db_aca_4_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.6 MB|
+
+## References
+
+https://huggingface.co/exala/db_aca_4.2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-db_mc2_9_1_en.md b/docs/_posts/ahmedlone127/2025-01-29-db_mc2_9_1_en.md
new file mode 100644
index 00000000000000..20101275e5174c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-db_mc2_9_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English db_mc2_9_1 DistilBertForSequenceClassification from exala
+author: John Snow Labs
+name: db_mc2_9_1
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`db_mc2_9_1` is a English model originally trained by exala.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/db_mc2_9_1_en_5.5.1_3.0_1738131361353.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/db_mc2_9_1_en_5.5.1_3.0_1738131361353.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("db_mc2_9_1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("db_mc2_9_1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|db_mc2_9_1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.7 MB|
+
+## References
+
+https://huggingface.co/exala/db_mc2_9.1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-db_mc2_9_1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-db_mc2_9_1_pipeline_en.md
new file mode 100644
index 00000000000000..7746939a75d1a3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-db_mc2_9_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English db_mc2_9_1_pipeline pipeline DistilBertForSequenceClassification from exala
+author: John Snow Labs
+name: db_mc2_9_1_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`db_mc2_9_1_pipeline` is a English model originally trained by exala.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/db_mc2_9_1_pipeline_en_5.5.1_3.0_1738131373808.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/db_mc2_9_1_pipeline_en_5.5.1_3.0_1738131373808.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("db_mc2_9_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("db_mc2_9_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|db_mc2_9_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.7 MB|
+
+## References
+
+https://huggingface.co/exala/db_mc2_9.1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-db_mc2_9_2_1_en.md b/docs/_posts/ahmedlone127/2025-01-29-db_mc2_9_2_1_en.md
new file mode 100644
index 00000000000000..61fbf790491a73
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-db_mc2_9_2_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English db_mc2_9_2_1 DistilBertForSequenceClassification from exala
+author: John Snow Labs
+name: db_mc2_9_2_1
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`db_mc2_9_2_1` is a English model originally trained by exala.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/db_mc2_9_2_1_en_5.5.1_3.0_1738131169004.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/db_mc2_9_2_1_en_5.5.1_3.0_1738131169004.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("db_mc2_9_2_1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("db_mc2_9_2_1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|db_mc2_9_2_1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.7 MB|
+
+## References
+
+https://huggingface.co/exala/db_mc2_9.2.1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-db_mc2_9_2_1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-db_mc2_9_2_1_pipeline_en.md
new file mode 100644
index 00000000000000..492d11890b6712
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-db_mc2_9_2_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English db_mc2_9_2_1_pipeline pipeline DistilBertForSequenceClassification from exala
+author: John Snow Labs
+name: db_mc2_9_2_1_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`db_mc2_9_2_1_pipeline` is a English model originally trained by exala.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/db_mc2_9_2_1_pipeline_en_5.5.1_3.0_1738131185395.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/db_mc2_9_2_1_pipeline_en_5.5.1_3.0_1738131185395.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("db_mc2_9_2_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("db_mc2_9_2_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|db_mc2_9_2_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.7 MB|
+
+## References
+
+https://huggingface.co/exala/db_mc2_9.2.1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-db_mc2_9_2_en.md b/docs/_posts/ahmedlone127/2025-01-29-db_mc2_9_2_en.md
new file mode 100644
index 00000000000000..06636e7bde3d50
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-db_mc2_9_2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English db_mc2_9_2 DistilBertForSequenceClassification from exala
+author: John Snow Labs
+name: db_mc2_9_2
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`db_mc2_9_2` is a English model originally trained by exala.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/db_mc2_9_2_en_5.5.1_3.0_1738110649124.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/db_mc2_9_2_en_5.5.1_3.0_1738110649124.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("db_mc2_9_2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("db_mc2_9_2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|db_mc2_9_2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.7 MB|
+
+## References
+
+https://huggingface.co/exala/db_mc2_9.2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-db_mc2_9_2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-db_mc2_9_2_pipeline_en.md
new file mode 100644
index 00000000000000..36c93d2c8f78b0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-db_mc2_9_2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English db_mc2_9_2_pipeline pipeline DistilBertForSequenceClassification from exala
+author: John Snow Labs
+name: db_mc2_9_2_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`db_mc2_9_2_pipeline` is a English model originally trained by exala.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/db_mc2_9_2_pipeline_en_5.5.1_3.0_1738110661797.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/db_mc2_9_2_pipeline_en_5.5.1_3.0_1738110661797.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("db_mc2_9_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("db_mc2_9_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|db_mc2_9_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.7 MB|
+
+## References
+
+https://huggingface.co/exala/db_mc2_9.2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbart_xsum_12_3_sshleifer_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbart_xsum_12_3_sshleifer_en.md
new file mode 100644
index 00000000000000..22c65f88f21303
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbart_xsum_12_3_sshleifer_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilbart_xsum_12_3_sshleifer BartTransformer from sshleifer
+author: John Snow Labs
+name: distilbart_xsum_12_3_sshleifer
+date: 2025-01-29
+tags: [en, open_source, onnx, text_generation, bart]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BartTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbart_xsum_12_3_sshleifer` is a English model originally trained by sshleifer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbart_xsum_12_3_sshleifer_en_5.5.1_3.0_1738121121275.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbart_xsum_12_3_sshleifer_en_5.5.1_3.0_1738121121275.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = BartTransformer.pretrained("distilbart_xsum_12_3_sshleifer","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = BartTransformer.pretrained("distilbart_xsum_12_3_sshleifer","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbart_xsum_12_3_sshleifer|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|857.2 MB|
+
+## References
+
+https://huggingface.co/sshleifer/distilbart-xsum-12-3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbart_xsum_12_3_sshleifer_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbart_xsum_12_3_sshleifer_pipeline_en.md
new file mode 100644
index 00000000000000..ad8c5784bfee9c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbart_xsum_12_3_sshleifer_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbart_xsum_12_3_sshleifer_pipeline pipeline BartTransformer from sshleifer
+author: John Snow Labs
+name: distilbart_xsum_12_3_sshleifer_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbart_xsum_12_3_sshleifer_pipeline` is a English model originally trained by sshleifer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbart_xsum_12_3_sshleifer_pipeline_en_5.5.1_3.0_1738121363001.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbart_xsum_12_3_sshleifer_pipeline_en_5.5.1_3.0_1738121363001.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbart_xsum_12_3_sshleifer_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbart_xsum_12_3_sshleifer_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbart_xsum_12_3_sshleifer_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|857.2 MB|
+
+## References
+
+https://huggingface.co/sshleifer/distilbart-xsum-12-3
+
+## Included Models
+
+- DocumentAssembler
+- BartTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_06_1_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_06_1_en.md
new file mode 100644
index 00000000000000..968eba73bda4d1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_06_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_06_1 DistilBertForSequenceClassification from KalaiselvanD
+author: John Snow Labs
+name: distilbert_06_1
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_06_1` is a English model originally trained by KalaiselvanD.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_06_1_en_5.5.1_3.0_1738109884042.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_06_1_en_5.5.1_3.0_1738109884042.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_06_1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_06_1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_06_1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/KalaiselvanD/distilbert_06_1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_06_1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_06_1_pipeline_en.md
new file mode 100644
index 00000000000000..c5967c2cd9c0f1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_06_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_06_1_pipeline pipeline DistilBertForSequenceClassification from KalaiselvanD
+author: John Snow Labs
+name: distilbert_06_1_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_06_1_pipeline` is a English model originally trained by KalaiselvanD.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_06_1_pipeline_en_5.5.1_3.0_1738109900055.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_06_1_pipeline_en_5.5.1_3.0_1738109900055.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_06_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_06_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_06_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/KalaiselvanD/distilbert_06_1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_absa_finetuned_turkish_pipeline_tr.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_absa_finetuned_turkish_pipeline_tr.md
new file mode 100644
index 00000000000000..4c5df539b7f7c5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_absa_finetuned_turkish_pipeline_tr.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Turkish distilbert_absa_finetuned_turkish_pipeline pipeline DistilBertForSequenceClassification from ebrukilic
+author: John Snow Labs
+name: distilbert_absa_finetuned_turkish_pipeline
+date: 2025-01-29
+tags: [tr, open_source, pipeline, onnx]
+task: Text Classification
+language: tr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_absa_finetuned_turkish_pipeline` is a Turkish model originally trained by ebrukilic.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_absa_finetuned_turkish_pipeline_tr_5.5.1_3.0_1738110763526.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_absa_finetuned_turkish_pipeline_tr_5.5.1_3.0_1738110763526.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_absa_finetuned_turkish_pipeline", lang = "tr")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_absa_finetuned_turkish_pipeline", lang = "tr")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_absa_finetuned_turkish_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|tr|
+|Size:|254.1 MB|
+
+## References
+
+https://huggingface.co/ebrukilic/distilbert-absa-finetuned-tr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_absa_finetuned_turkish_tr.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_absa_finetuned_turkish_tr.md
new file mode 100644
index 00000000000000..ba6f3a78c09037
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_absa_finetuned_turkish_tr.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Turkish distilbert_absa_finetuned_turkish DistilBertForSequenceClassification from ebrukilic
+author: John Snow Labs
+name: distilbert_absa_finetuned_turkish
+date: 2025-01-29
+tags: [tr, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: tr
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_absa_finetuned_turkish` is a Turkish model originally trained by ebrukilic.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_absa_finetuned_turkish_tr_5.5.1_3.0_1738110750628.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_absa_finetuned_turkish_tr_5.5.1_3.0_1738110750628.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_absa_finetuned_turkish","tr") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_absa_finetuned_turkish", "tr")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_absa_finetuned_turkish|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|tr|
+|Size:|254.1 MB|
+
+## References
+
+https://huggingface.co/ebrukilic/distilbert-absa-finetuned-tr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_emotion_ft_0403_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_emotion_ft_0403_en.md
new file mode 100644
index 00000000000000..9bf2bcc33272e4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_emotion_ft_0403_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_emotion_ft_0403 DistilBertForSequenceClassification from Rw1nd
+author: John Snow Labs
+name: distilbert_base_uncased_emotion_ft_0403
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_emotion_ft_0403` is a English model originally trained by Rw1nd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_emotion_ft_0403_en_5.5.1_3.0_1738110405746.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_emotion_ft_0403_en_5.5.1_3.0_1738110405746.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_emotion_ft_0403","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_emotion_ft_0403", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_emotion_ft_0403|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Rw1nd/distilbert-base-uncased_emotion_ft_0403
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_emotion_ft_0403_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_emotion_ft_0403_pipeline_en.md
new file mode 100644
index 00000000000000..8f30576eb84dcc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_emotion_ft_0403_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_emotion_ft_0403_pipeline pipeline DistilBertForSequenceClassification from Rw1nd
+author: John Snow Labs
+name: distilbert_base_uncased_emotion_ft_0403_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_emotion_ft_0403_pipeline` is a English model originally trained by Rw1nd.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_emotion_ft_0403_pipeline_en_5.5.1_3.0_1738110418429.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_emotion_ft_0403_pipeline_en_5.5.1_3.0_1738110418429.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_emotion_ft_0403_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_emotion_ft_0403_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_emotion_ft_0403_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Rw1nd/distilbert-base-uncased_emotion_ft_0403
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_cola_dstripli_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_cola_dstripli_en.md
new file mode 100644
index 00000000000000..dde97da26d3d76
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_cola_dstripli_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_cola_dstripli DistilBertForSequenceClassification from dstripli
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_cola_dstripli
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_cola_dstripli` is a English model originally trained by dstripli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_cola_dstripli_en_5.5.1_3.0_1738131185469.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_cola_dstripli_en_5.5.1_3.0_1738131185469.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_cola_dstripli","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_cola_dstripli", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_cola_dstripli|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/dstripli/distilbert-base-uncased-finetuned-cola
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_cola_dstripli_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_cola_dstripli_pipeline_en.md
new file mode 100644
index 00000000000000..c0d6ef87b201c0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_cola_dstripli_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_cola_dstripli_pipeline pipeline DistilBertForSequenceClassification from dstripli
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_cola_dstripli_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_cola_dstripli_pipeline` is a English model originally trained by dstripli.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_cola_dstripli_pipeline_en_5.5.1_3.0_1738131202080.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_cola_dstripli_pipeline_en_5.5.1_3.0_1738131202080.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_cola_dstripli_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_cola_dstripli_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_cola_dstripli_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/dstripli/distilbert-base-uncased-finetuned-cola
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_cola_ghxm_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_cola_ghxm_en.md
new file mode 100644
index 00000000000000..24739ab0e15147
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_cola_ghxm_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_cola_ghxm DistilBertForSequenceClassification from ghxm
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_cola_ghxm
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_cola_ghxm` is a English model originally trained by ghxm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_cola_ghxm_en_5.5.1_3.0_1738131563156.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_cola_ghxm_en_5.5.1_3.0_1738131563156.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_cola_ghxm","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_cola_ghxm", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_cola_ghxm|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/ghxm/distilbert-base-uncased-finetuned-cola
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_cola_ghxm_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_cola_ghxm_pipeline_en.md
new file mode 100644
index 00000000000000..5b55d2223f0034
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_cola_ghxm_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_cola_ghxm_pipeline pipeline DistilBertForSequenceClassification from ghxm
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_cola_ghxm_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_cola_ghxm_pipeline` is a English model originally trained by ghxm.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_cola_ghxm_pipeline_en_5.5.1_3.0_1738131580411.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_cola_ghxm_pipeline_en_5.5.1_3.0_1738131580411.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_cola_ghxm_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_cola_ghxm_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_cola_ghxm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/ghxm/distilbert-base-uncased-finetuned-cola
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_cola_mcmanuschen_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_cola_mcmanuschen_en.md
new file mode 100644
index 00000000000000..2a7ec2139c2562
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_cola_mcmanuschen_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_cola_mcmanuschen DistilBertForSequenceClassification from McmanusChen
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_cola_mcmanuschen
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_cola_mcmanuschen` is a English model originally trained by McmanusChen.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_cola_mcmanuschen_en_5.5.1_3.0_1738131450360.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_cola_mcmanuschen_en_5.5.1_3.0_1738131450360.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_cola_mcmanuschen","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_cola_mcmanuschen", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_cola_mcmanuschen|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/McmanusChen/distilbert-base-uncased-finetuned-cola
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_cola_mcmanuschen_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_cola_mcmanuschen_pipeline_en.md
new file mode 100644
index 00000000000000..4dc3d8e1240e05
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_cola_mcmanuschen_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_cola_mcmanuschen_pipeline pipeline DistilBertForSequenceClassification from McmanusChen
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_cola_mcmanuschen_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_cola_mcmanuschen_pipeline` is a English model originally trained by McmanusChen.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_cola_mcmanuschen_pipeline_en_5.5.1_3.0_1738131463802.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_cola_mcmanuschen_pipeline_en_5.5.1_3.0_1738131463802.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_cola_mcmanuschen_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_cola_mcmanuschen_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_cola_mcmanuschen_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/McmanusChen/distilbert-base-uncased-finetuned-cola
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_angeljb_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_angeljb_en.md
new file mode 100644
index 00000000000000..54f320946616e0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_angeljb_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_angeljb DistilBertForSequenceClassification from AngelJB
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_angeljb
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_angeljb` is a English model originally trained by AngelJB.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_angeljb_en_5.5.1_3.0_1738131303410.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_angeljb_en_5.5.1_3.0_1738131303410.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_angeljb","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_angeljb", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_angeljb|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/AngelJB/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_angeljb_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_angeljb_pipeline_en.md
new file mode 100644
index 00000000000000..9838168703458d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_angeljb_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_angeljb_pipeline pipeline DistilBertForSequenceClassification from AngelJB
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_angeljb_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_angeljb_pipeline` is a English model originally trained by AngelJB.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_angeljb_pipeline_en_5.5.1_3.0_1738131316891.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_angeljb_pipeline_en_5.5.1_3.0_1738131316891.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_angeljb_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_angeljb_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_angeljb_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/AngelJB/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_astin1225_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_astin1225_en.md
new file mode 100644
index 00000000000000..b0ded1ebe29560
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_astin1225_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_astin1225 DistilBertForSequenceClassification from astin1225
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_astin1225
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_astin1225` is a English model originally trained by astin1225.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_astin1225_en_5.5.1_3.0_1738110398906.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_astin1225_en_5.5.1_3.0_1738110398906.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_astin1225","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_astin1225", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_astin1225|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/astin1225/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_astin1225_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_astin1225_pipeline_en.md
new file mode 100644
index 00000000000000..fef6d9a73b4753
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_astin1225_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_astin1225_pipeline pipeline DistilBertForSequenceClassification from astin1225
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_astin1225_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_astin1225_pipeline` is a English model originally trained by astin1225.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_astin1225_pipeline_en_5.5.1_3.0_1738110411381.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_astin1225_pipeline_en_5.5.1_3.0_1738110411381.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_astin1225_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_astin1225_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_astin1225_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/astin1225/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_bbeunikong_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_bbeunikong_en.md
new file mode 100644
index 00000000000000..5b0097e350481c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_bbeunikong_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_bbeunikong DistilBertForSequenceClassification from bbeunikong
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_bbeunikong
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_bbeunikong` is a English model originally trained by bbeunikong.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_bbeunikong_en_5.5.1_3.0_1738110104729.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_bbeunikong_en_5.5.1_3.0_1738110104729.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_bbeunikong","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_bbeunikong", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_bbeunikong|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/bbeunikong/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_bbeunikong_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_bbeunikong_pipeline_en.md
new file mode 100644
index 00000000000000..9900f6002ae89d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_bbeunikong_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_bbeunikong_pipeline pipeline DistilBertForSequenceClassification from bbeunikong
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_bbeunikong_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_bbeunikong_pipeline` is a English model originally trained by bbeunikong.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_bbeunikong_pipeline_en_5.5.1_3.0_1738110117623.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_bbeunikong_pipeline_en_5.5.1_3.0_1738110117623.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_bbeunikong_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_bbeunikong_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_bbeunikong_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/bbeunikong/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_cindyangelira_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_cindyangelira_en.md
new file mode 100644
index 00000000000000..b739aee8aa4d30
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_cindyangelira_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_cindyangelira DistilBertForSequenceClassification from cindyangelira
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_cindyangelira
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_cindyangelira` is a English model originally trained by cindyangelira.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_cindyangelira_en_5.5.1_3.0_1738110456185.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_cindyangelira_en_5.5.1_3.0_1738110456185.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_cindyangelira","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_cindyangelira", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_cindyangelira|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/cindyangelira/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_cindyangelira_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_cindyangelira_pipeline_en.md
new file mode 100644
index 00000000000000..45ceb6f74033ad
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_cindyangelira_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_cindyangelira_pipeline pipeline DistilBertForSequenceClassification from cindyangelira
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_cindyangelira_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_cindyangelira_pipeline` is a English model originally trained by cindyangelira.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_cindyangelira_pipeline_en_5.5.1_3.0_1738110468875.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_cindyangelira_pipeline_en_5.5.1_3.0_1738110468875.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_cindyangelira_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_cindyangelira_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_cindyangelira_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/cindyangelira/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_clmrie_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_clmrie_en.md
new file mode 100644
index 00000000000000..7832085754c22b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_clmrie_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_clmrie DistilBertForSequenceClassification from clmrie
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_clmrie
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_clmrie` is a English model originally trained by clmrie.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_clmrie_en_5.5.1_3.0_1738109996702.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_clmrie_en_5.5.1_3.0_1738109996702.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_clmrie","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_clmrie", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_clmrie|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/clmrie/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_clmrie_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_clmrie_pipeline_en.md
new file mode 100644
index 00000000000000..b562f00e43af08
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_clmrie_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_clmrie_pipeline pipeline DistilBertForSequenceClassification from clmrie
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_clmrie_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_clmrie_pipeline` is a English model originally trained by clmrie.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_clmrie_pipeline_en_5.5.1_3.0_1738110010018.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_clmrie_pipeline_en_5.5.1_3.0_1738110010018.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_clmrie_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_clmrie_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_clmrie_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/clmrie/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_danielber_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_danielber_en.md
new file mode 100644
index 00000000000000..a1eef758007f75
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_danielber_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_danielber DistilBertForSequenceClassification from Danielber
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_danielber
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_danielber` is a English model originally trained by Danielber.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_danielber_en_5.5.1_3.0_1738109882648.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_danielber_en_5.5.1_3.0_1738109882648.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_danielber","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_danielber", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_danielber|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Danielber/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_danielber_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_danielber_pipeline_en.md
new file mode 100644
index 00000000000000..6b0840a16c3f6e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_danielber_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_danielber_pipeline pipeline DistilBertForSequenceClassification from Danielber
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_danielber_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_danielber_pipeline` is a English model originally trained by Danielber.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_danielber_pipeline_en_5.5.1_3.0_1738109901450.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_danielber_pipeline_en_5.5.1_3.0_1738109901450.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_danielber_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_danielber_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_danielber_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Danielber/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_didsuaclzls_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_didsuaclzls_en.md
new file mode 100644
index 00000000000000..c0382654eea7c1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_didsuaclzls_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_didsuaclzls DistilBertForSequenceClassification from didsuaclzls
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_didsuaclzls
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_didsuaclzls` is a English model originally trained by didsuaclzls.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_didsuaclzls_en_5.5.1_3.0_1738131695475.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_didsuaclzls_en_5.5.1_3.0_1738131695475.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_didsuaclzls","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_didsuaclzls", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_didsuaclzls|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/didsuaclzls/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_didsuaclzls_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_didsuaclzls_pipeline_en.md
new file mode 100644
index 00000000000000..58191e8008835d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_didsuaclzls_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_didsuaclzls_pipeline pipeline DistilBertForSequenceClassification from didsuaclzls
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_didsuaclzls_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_didsuaclzls_pipeline` is a English model originally trained by didsuaclzls.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_didsuaclzls_pipeline_en_5.5.1_3.0_1738131710582.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_didsuaclzls_pipeline_en_5.5.1_3.0_1738131710582.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_didsuaclzls_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_didsuaclzls_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_didsuaclzls_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/didsuaclzls/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_donghuna_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_donghuna_en.md
new file mode 100644
index 00000000000000..5dc23b2c5375d3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_donghuna_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_donghuna DistilBertForSequenceClassification from donghuna
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_donghuna
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_donghuna` is a English model originally trained by donghuna.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_donghuna_en_5.5.1_3.0_1738131038070.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_donghuna_en_5.5.1_3.0_1738131038070.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_donghuna","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_donghuna", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_donghuna|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/donghuna/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_donghuna_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_donghuna_pipeline_en.md
new file mode 100644
index 00000000000000..86bdbd76f6107e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_donghuna_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_donghuna_pipeline pipeline DistilBertForSequenceClassification from donghuna
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_donghuna_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_donghuna_pipeline` is a English model originally trained by donghuna.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_donghuna_pipeline_en_5.5.1_3.0_1738131050835.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_donghuna_pipeline_en_5.5.1_3.0_1738131050835.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_donghuna_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_donghuna_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_donghuna_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/donghuna/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_dro14_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_dro14_en.md
new file mode 100644
index 00000000000000..66a1537f2194f1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_dro14_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_dro14 DistilBertForSequenceClassification from dro14
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_dro14
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_dro14` is a English model originally trained by dro14.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_dro14_en_5.5.1_3.0_1738130987123.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_dro14_en_5.5.1_3.0_1738130987123.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_dro14","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_dro14", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_dro14|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/dro14/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_dro14_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_dro14_pipeline_en.md
new file mode 100644
index 00000000000000..2efd717918dae7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_dro14_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_dro14_pipeline pipeline DistilBertForSequenceClassification from dro14
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_dro14_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_dro14_pipeline` is a English model originally trained by dro14.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_dro14_pipeline_en_5.5.1_3.0_1738130999933.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_dro14_pipeline_en_5.5.1_3.0_1738130999933.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_dro14_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_dro14_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_dro14_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/dro14/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_hanjisu_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_hanjisu_en.md
new file mode 100644
index 00000000000000..50c9a72b65c11b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_hanjisu_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_hanjisu DistilBertForSequenceClassification from HanJisu
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_hanjisu
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_hanjisu` is a English model originally trained by HanJisu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_hanjisu_en_5.5.1_3.0_1738131446262.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_hanjisu_en_5.5.1_3.0_1738131446262.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_hanjisu","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_hanjisu", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_hanjisu|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/HanJisu/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_hanjisu_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_hanjisu_pipeline_en.md
new file mode 100644
index 00000000000000..5412e5e76b0cf4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_hanjisu_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_hanjisu_pipeline pipeline DistilBertForSequenceClassification from HanJisu
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_hanjisu_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_hanjisu_pipeline` is a English model originally trained by HanJisu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_hanjisu_pipeline_en_5.5.1_3.0_1738131459712.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_hanjisu_pipeline_en_5.5.1_3.0_1738131459712.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_hanjisu_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_hanjisu_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_hanjisu_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/HanJisu/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_juhyun76_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_juhyun76_en.md
new file mode 100644
index 00000000000000..4bce3f86cac857
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_juhyun76_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_juhyun76 DistilBertForSequenceClassification from juhyun76
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_juhyun76
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_juhyun76` is a English model originally trained by juhyun76.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_juhyun76_en_5.5.1_3.0_1738131167168.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_juhyun76_en_5.5.1_3.0_1738131167168.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_juhyun76","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_juhyun76", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_juhyun76|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/juhyun76/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_juhyun76_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_juhyun76_pipeline_en.md
new file mode 100644
index 00000000000000..3ee7f8301cd301
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_juhyun76_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_juhyun76_pipeline pipeline DistilBertForSequenceClassification from juhyun76
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_juhyun76_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_juhyun76_pipeline` is a English model originally trained by juhyun76.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_juhyun76_pipeline_en_5.5.1_3.0_1738131185350.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_juhyun76_pipeline_en_5.5.1_3.0_1738131185350.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_juhyun76_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_juhyun76_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_juhyun76_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/juhyun76/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_kpedidogodonou_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_kpedidogodonou_en.md
new file mode 100644
index 00000000000000..4be7a0ed324d79
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_kpedidogodonou_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_kpedidogodonou DistilBertForSequenceClassification from kpedidogodonou
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_kpedidogodonou
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_kpedidogodonou` is a English model originally trained by kpedidogodonou.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_kpedidogodonou_en_5.5.1_3.0_1738131269501.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_kpedidogodonou_en_5.5.1_3.0_1738131269501.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_kpedidogodonou","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_kpedidogodonou", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_kpedidogodonou|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/kpedidogodonou/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_kpedidogodonou_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_kpedidogodonou_pipeline_en.md
new file mode 100644
index 00000000000000..7935836b37b77f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_kpedidogodonou_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_kpedidogodonou_pipeline pipeline DistilBertForSequenceClassification from kpedidogodonou
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_kpedidogodonou_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_kpedidogodonou_pipeline` is a English model originally trained by kpedidogodonou.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_kpedidogodonou_pipeline_en_5.5.1_3.0_1738131282785.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_kpedidogodonou_pipeline_en_5.5.1_3.0_1738131282785.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_kpedidogodonou_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_kpedidogodonou_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_kpedidogodonou_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/kpedidogodonou/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_ljsilverstar_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_ljsilverstar_en.md
new file mode 100644
index 00000000000000..176eae8bf16d8b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_ljsilverstar_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_ljsilverstar DistilBertForSequenceClassification from ljsilverstar
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_ljsilverstar
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_ljsilverstar` is a English model originally trained by ljsilverstar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_ljsilverstar_en_5.5.1_3.0_1738110234829.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_ljsilverstar_en_5.5.1_3.0_1738110234829.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_ljsilverstar","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_ljsilverstar", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_ljsilverstar|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/ljsilverstar/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_ljsilverstar_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_ljsilverstar_pipeline_en.md
new file mode 100644
index 00000000000000..574bd1ba89051d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_ljsilverstar_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_ljsilverstar_pipeline pipeline DistilBertForSequenceClassification from ljsilverstar
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_ljsilverstar_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_ljsilverstar_pipeline` is a English model originally trained by ljsilverstar.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_ljsilverstar_pipeline_en_5.5.1_3.0_1738110247768.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_ljsilverstar_pipeline_en_5.5.1_3.0_1738110247768.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_ljsilverstar_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_ljsilverstar_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_ljsilverstar_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/ljsilverstar/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_mouhebmehdoui_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_mouhebmehdoui_en.md
new file mode 100644
index 00000000000000..7ff50d075802e2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_mouhebmehdoui_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_mouhebmehdoui DistilBertForSequenceClassification from mouhebMehdoui
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_mouhebmehdoui
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_mouhebmehdoui` is a English model originally trained by mouhebMehdoui.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_mouhebmehdoui_en_5.5.1_3.0_1738130910993.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_mouhebmehdoui_en_5.5.1_3.0_1738130910993.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_mouhebmehdoui","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_mouhebmehdoui", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_mouhebmehdoui|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/mouhebMehdoui/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_mouhebmehdoui_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_mouhebmehdoui_pipeline_en.md
new file mode 100644
index 00000000000000..84f1488e163169
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_mouhebmehdoui_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_mouhebmehdoui_pipeline pipeline DistilBertForSequenceClassification from mouhebMehdoui
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_mouhebmehdoui_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_mouhebmehdoui_pipeline` is a English model originally trained by mouhebMehdoui.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_mouhebmehdoui_pipeline_en_5.5.1_3.0_1738130929057.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_mouhebmehdoui_pipeline_en_5.5.1_3.0_1738130929057.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_mouhebmehdoui_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_mouhebmehdoui_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_mouhebmehdoui_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/mouhebMehdoui/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_placeo_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_placeo_en.md
new file mode 100644
index 00000000000000..33ffc189e298e0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_placeo_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_placeo DistilBertForSequenceClassification from placeo
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_placeo
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_placeo` is a English model originally trained by placeo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_placeo_en_5.5.1_3.0_1738131379985.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_placeo_en_5.5.1_3.0_1738131379985.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_placeo","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_placeo", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_placeo|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/placeo/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_placeo_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_placeo_pipeline_en.md
new file mode 100644
index 00000000000000..abfea99f88451e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_placeo_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_placeo_pipeline pipeline DistilBertForSequenceClassification from placeo
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_placeo_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_placeo_pipeline` is a English model originally trained by placeo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_placeo_pipeline_en_5.5.1_3.0_1738131393803.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_placeo_pipeline_en_5.5.1_3.0_1738131393803.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_placeo_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_placeo_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_placeo_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/placeo/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_rathohan_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_rathohan_en.md
new file mode 100644
index 00000000000000..877622ac965b7e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_rathohan_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_rathohan DistilBertForSequenceClassification from Rathohan
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_rathohan
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_rathohan` is a English model originally trained by Rathohan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_rathohan_en_5.5.1_3.0_1738109883099.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_rathohan_en_5.5.1_3.0_1738109883099.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_rathohan","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_rathohan", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_rathohan|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Rathohan/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_rathohan_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_rathohan_pipeline_en.md
new file mode 100644
index 00000000000000..6d06f621a50f29
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_rathohan_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_rathohan_pipeline pipeline DistilBertForSequenceClassification from Rathohan
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_rathohan_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_rathohan_pipeline` is a English model originally trained by Rathohan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_rathohan_pipeline_en_5.5.1_3.0_1738109901395.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_rathohan_pipeline_en_5.5.1_3.0_1738109901395.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_rathohan_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_rathohan_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_rathohan_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Rathohan/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_siripa_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_siripa_en.md
new file mode 100644
index 00000000000000..dd1ee6c6947d63
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_siripa_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_siripa DistilBertForSequenceClassification from Siripa
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_siripa
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_siripa` is a English model originally trained by Siripa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_siripa_en_5.5.1_3.0_1738110811984.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_siripa_en_5.5.1_3.0_1738110811984.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_siripa","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_siripa", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_siripa|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Siripa/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_siripa_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_siripa_pipeline_en.md
new file mode 100644
index 00000000000000..40aca99a249c7a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_siripa_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_siripa_pipeline pipeline DistilBertForSequenceClassification from Siripa
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_siripa_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_siripa_pipeline` is a English model originally trained by Siripa.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_siripa_pipeline_en_5.5.1_3.0_1738110824392.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_siripa_pipeline_en_5.5.1_3.0_1738110824392.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_siripa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_siripa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_siripa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Siripa/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_zameera_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_zameera_en.md
new file mode 100644
index 00000000000000..3e50e0da7f77b5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_zameera_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_zameera DistilBertForSequenceClassification from Zameera
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_zameera
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_zameera` is a English model originally trained by Zameera.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_zameera_en_5.5.1_3.0_1738131930352.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_zameera_en_5.5.1_3.0_1738131930352.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_zameera","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_zameera", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_zameera|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Zameera/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_zameera_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_zameera_pipeline_en.md
new file mode 100644
index 00000000000000..1d5d09d6ad06f1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotion_zameera_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_zameera_pipeline pipeline DistilBertForSequenceClassification from Zameera
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_zameera_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_zameera_pipeline` is a English model originally trained by Zameera.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_zameera_pipeline_en_5.5.1_3.0_1738131943208.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_zameera_pipeline_en_5.5.1_3.0_1738131943208.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_zameera_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_zameera_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_zameera_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Zameera/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotions_kuhm209_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotions_kuhm209_en.md
new file mode 100644
index 00000000000000..74dfcaeaca29a2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotions_kuhm209_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotions_kuhm209 DistilBertForSequenceClassification from kuhm209
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotions_kuhm209
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotions_kuhm209` is a English model originally trained by kuhm209.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotions_kuhm209_en_5.5.1_3.0_1738131832478.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotions_kuhm209_en_5.5.1_3.0_1738131832478.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotions_kuhm209","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotions_kuhm209", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotions_kuhm209|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/kuhm209/distilbert-base-uncased-finetuned-emotions
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotions_kuhm209_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotions_kuhm209_pipeline_en.md
new file mode 100644
index 00000000000000..d429d916efdc40
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_finetuned_emotions_kuhm209_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotions_kuhm209_pipeline pipeline DistilBertForSequenceClassification from kuhm209
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotions_kuhm209_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotions_kuhm209_pipeline` is a English model originally trained by kuhm209.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotions_kuhm209_pipeline_en_5.5.1_3.0_1738131845744.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotions_kuhm209_pipeline_en_5.5.1_3.0_1738131845744.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotions_kuhm209_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotions_kuhm209_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotions_kuhm209_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/kuhm209/distilbert-base-uncased-finetuned-emotions
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_kdd2020_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_kdd2020_en.md
new file mode 100644
index 00000000000000..8a6afbbe75e2b3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_kdd2020_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_kdd2020 DistilBertForSequenceClassification from LittleFish-Coder
+author: John Snow Labs
+name: distilbert_base_uncased_kdd2020
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_kdd2020` is a English model originally trained by LittleFish-Coder.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_kdd2020_en_5.5.1_3.0_1738131403360.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_kdd2020_en_5.5.1_3.0_1738131403360.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_kdd2020","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_kdd2020", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_kdd2020|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/LittleFish-Coder/distilbert-base-uncased-kdd2020
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_kdd2020_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_kdd2020_pipeline_en.md
new file mode 100644
index 00000000000000..3d640fe4eef65e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_kdd2020_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_kdd2020_pipeline pipeline DistilBertForSequenceClassification from LittleFish-Coder
+author: John Snow Labs
+name: distilbert_base_uncased_kdd2020_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_kdd2020_pipeline` is a English model originally trained by LittleFish-Coder.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_kdd2020_pipeline_en_5.5.1_3.0_1738131416351.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_kdd2020_pipeline_en_5.5.1_3.0_1738131416351.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_kdd2020_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_kdd2020_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_kdd2020_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/LittleFish-Coder/distilbert-base-uncased-kdd2020
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_medical_valid_term_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_medical_valid_term_en.md
new file mode 100644
index 00000000000000..42cb69134c26f2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_medical_valid_term_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_medical_valid_term DistilBertForSequenceClassification from samant
+author: John Snow Labs
+name: distilbert_base_uncased_medical_valid_term
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_medical_valid_term` is a English model originally trained by samant.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_medical_valid_term_en_5.5.1_3.0_1738110743538.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_medical_valid_term_en_5.5.1_3.0_1738110743538.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_medical_valid_term","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_medical_valid_term", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_medical_valid_term|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/samant/distilbert-base-uncased-medical-valid-term
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_medical_valid_term_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_medical_valid_term_pipeline_en.md
new file mode 100644
index 00000000000000..208b1edc6014b7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_medical_valid_term_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_medical_valid_term_pipeline pipeline DistilBertForSequenceClassification from samant
+author: John Snow Labs
+name: distilbert_base_uncased_medical_valid_term_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_medical_valid_term_pipeline` is a English model originally trained by samant.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_medical_valid_term_pipeline_en_5.5.1_3.0_1738110756221.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_medical_valid_term_pipeline_en_5.5.1_3.0_1738110756221.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_medical_valid_term_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_medical_valid_term_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_medical_valid_term_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/samant/distilbert-base-uncased-medical-valid-term
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_sgd_zphr_0st42sd_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_sgd_zphr_0st42sd_en.md
new file mode 100644
index 00000000000000..ae498d78652bda
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_sgd_zphr_0st42sd_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_sgd_zphr_0st42sd DistilBertForSequenceClassification from tom192180
+author: John Snow Labs
+name: distilbert_base_uncased_sgd_zphr_0st42sd
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_sgd_zphr_0st42sd` is a English model originally trained by tom192180.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_sgd_zphr_0st42sd_en_5.5.1_3.0_1738110513825.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_sgd_zphr_0st42sd_en_5.5.1_3.0_1738110513825.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_sgd_zphr_0st42sd","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_sgd_zphr_0st42sd", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_sgd_zphr_0st42sd|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.6 MB|
+
+## References
+
+https://huggingface.co/tom192180/distilbert-base-uncased_sgd_zphr_0st42sd
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_sgd_zphr_0st42sd_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_sgd_zphr_0st42sd_pipeline_en.md
new file mode 100644
index 00000000000000..3273e1bfbea652
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_base_uncased_sgd_zphr_0st42sd_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_sgd_zphr_0st42sd_pipeline pipeline DistilBertForSequenceClassification from tom192180
+author: John Snow Labs
+name: distilbert_base_uncased_sgd_zphr_0st42sd_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_sgd_zphr_0st42sd_pipeline` is a English model originally trained by tom192180.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_sgd_zphr_0st42sd_pipeline_en_5.5.1_3.0_1738110526920.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_sgd_zphr_0st42sd_pipeline_en_5.5.1_3.0_1738110526920.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_sgd_zphr_0st42sd_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_sgd_zphr_0st42sd_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_sgd_zphr_0st42sd_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.6 MB|
+
+## References
+
+https://huggingface.co/tom192180/distilbert-base-uncased_sgd_zphr_0st42sd
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_finetune_araproje_turkish_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_finetune_araproje_turkish_en.md
new file mode 100644
index 00000000000000..ec56aa87376a8c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_finetune_araproje_turkish_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_finetune_araproje_turkish DistilBertForSequenceClassification from rmysysv
+author: John Snow Labs
+name: distilbert_finetune_araproje_turkish
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetune_araproje_turkish` is a English model originally trained by rmysysv.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_finetune_araproje_turkish_en_5.5.1_3.0_1738110603552.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetune_araproje_turkish_en_5.5.1_3.0_1738110603552.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_finetune_araproje_turkish","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_finetune_araproje_turkish", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_finetune_araproje_turkish|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|254.1 MB|
+
+## References
+
+https://huggingface.co/rmysysv/distilbert-finetune-araproje-tr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_finetune_araproje_turkish_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_finetune_araproje_turkish_pipeline_en.md
new file mode 100644
index 00000000000000..30fac47b6acfe9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_finetune_araproje_turkish_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_finetune_araproje_turkish_pipeline pipeline DistilBertForSequenceClassification from rmysysv
+author: John Snow Labs
+name: distilbert_finetune_araproje_turkish_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetune_araproje_turkish_pipeline` is a English model originally trained by rmysysv.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_finetune_araproje_turkish_pipeline_en_5.5.1_3.0_1738110617242.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetune_araproje_turkish_pipeline_en_5.5.1_3.0_1738110617242.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_finetune_araproje_turkish_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_finetune_araproje_turkish_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_finetune_araproje_turkish_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|254.1 MB|
+
+## References
+
+https://huggingface.co/rmysysv/distilbert-finetune-araproje-tr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_finetuned_on_emotion_waniabbeer_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_finetuned_on_emotion_waniabbeer_en.md
new file mode 100644
index 00000000000000..1fb9231b0a6b10
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_finetuned_on_emotion_waniabbeer_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_finetuned_on_emotion_waniabbeer DistilBertForSequenceClassification from waniabbeer
+author: John Snow Labs
+name: distilbert_finetuned_on_emotion_waniabbeer
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetuned_on_emotion_waniabbeer` is a English model originally trained by waniabbeer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_on_emotion_waniabbeer_en_5.5.1_3.0_1738109925408.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_on_emotion_waniabbeer_en_5.5.1_3.0_1738109925408.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_finetuned_on_emotion_waniabbeer","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_finetuned_on_emotion_waniabbeer", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_finetuned_on_emotion_waniabbeer|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/waniabbeer/DistilBERT-finetuned-on-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_finetuned_on_emotion_waniabbeer_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_finetuned_on_emotion_waniabbeer_pipeline_en.md
new file mode 100644
index 00000000000000..0515e648e9724a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_finetuned_on_emotion_waniabbeer_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_finetuned_on_emotion_waniabbeer_pipeline pipeline DistilBertForSequenceClassification from waniabbeer
+author: John Snow Labs
+name: distilbert_finetuned_on_emotion_waniabbeer_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetuned_on_emotion_waniabbeer_pipeline` is a English model originally trained by waniabbeer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_on_emotion_waniabbeer_pipeline_en_5.5.1_3.0_1738109938016.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_on_emotion_waniabbeer_pipeline_en_5.5.1_3.0_1738109938016.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_finetuned_on_emotion_waniabbeer_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_finetuned_on_emotion_waniabbeer_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_finetuned_on_emotion_waniabbeer_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/waniabbeer/DistilBERT-finetuned-on-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_qlora_finetuned_merged_imdb_sentiment_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_qlora_finetuned_merged_imdb_sentiment_en.md
new file mode 100644
index 00000000000000..cff7977e76eda5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_qlora_finetuned_merged_imdb_sentiment_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_qlora_finetuned_merged_imdb_sentiment DistilBertForSequenceClassification from dipanjanS
+author: John Snow Labs
+name: distilbert_qlora_finetuned_merged_imdb_sentiment
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_qlora_finetuned_merged_imdb_sentiment` is a English model originally trained by dipanjanS.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_qlora_finetuned_merged_imdb_sentiment_en_5.5.1_3.0_1738131040692.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_qlora_finetuned_merged_imdb_sentiment_en_5.5.1_3.0_1738131040692.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_qlora_finetuned_merged_imdb_sentiment","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_qlora_finetuned_merged_imdb_sentiment", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_qlora_finetuned_merged_imdb_sentiment|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/dipanjanS/distilbert-qlora-finetuned-merged-imdb-sentiment
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilbert_qlora_finetuned_merged_imdb_sentiment_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilbert_qlora_finetuned_merged_imdb_sentiment_pipeline_en.md
new file mode 100644
index 00000000000000..98c2e885961955
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilbert_qlora_finetuned_merged_imdb_sentiment_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_qlora_finetuned_merged_imdb_sentiment_pipeline pipeline DistilBertForSequenceClassification from dipanjanS
+author: John Snow Labs
+name: distilbert_qlora_finetuned_merged_imdb_sentiment_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_qlora_finetuned_merged_imdb_sentiment_pipeline` is a English model originally trained by dipanjanS.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_qlora_finetuned_merged_imdb_sentiment_pipeline_en_5.5.1_3.0_1738131053686.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_qlora_finetuned_merged_imdb_sentiment_pipeline_en_5.5.1_3.0_1738131053686.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilbert_qlora_finetuned_merged_imdb_sentiment_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_qlora_finetuned_merged_imdb_sentiment_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_qlora_finetuned_merged_imdb_sentiment_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/dipanjanS/distilbert-qlora-finetuned-merged-imdb-sentiment
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilroberta_base_ft_nfl_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilroberta_base_ft_nfl_en.md
new file mode 100644
index 00000000000000..c3c5cd49aa2e9c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilroberta_base_ft_nfl_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilroberta_base_ft_nfl RoBertaEmbeddings from jkruk
+author: John Snow Labs
+name: distilroberta_base_ft_nfl
+date: 2025-01-29
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_ft_nfl` is a English model originally trained by jkruk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_base_ft_nfl_en_5.5.1_3.0_1738134860808.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_ft_nfl_en_5.5.1_3.0_1738134860808.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("distilroberta_base_ft_nfl","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("distilroberta_base_ft_nfl","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_base_ft_nfl|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/jkruk/distilroberta-base-ft-nfl
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-distilroberta_base_ft_nfl_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-distilroberta_base_ft_nfl_pipeline_en.md
new file mode 100644
index 00000000000000..93ad08dfdb0e50
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-distilroberta_base_ft_nfl_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilroberta_base_ft_nfl_pipeline pipeline RoBertaEmbeddings from jkruk
+author: John Snow Labs
+name: distilroberta_base_ft_nfl_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_ft_nfl_pipeline` is a English model originally trained by jkruk.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_base_ft_nfl_pipeline_en_5.5.1_3.0_1738134876650.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_ft_nfl_pipeline_en_5.5.1_3.0_1738134876650.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("distilroberta_base_ft_nfl_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilroberta_base_ft_nfl_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_base_ft_nfl_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/jkruk/distilroberta-base-ft-nfl
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-dummy_model_laochengzi_en.md b/docs/_posts/ahmedlone127/2025-01-29-dummy_model_laochengzi_en.md
new file mode 100644
index 00000000000000..cdf42ca37b8241
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-dummy_model_laochengzi_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_laochengzi CamemBertEmbeddings from laochengzi
+author: John Snow Labs
+name: dummy_model_laochengzi
+date: 2025-01-29
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_laochengzi` is a English model originally trained by laochengzi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_laochengzi_en_5.5.1_3.0_1738123555406.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_laochengzi_en_5.5.1_3.0_1738123555406.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_laochengzi","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_laochengzi","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_laochengzi|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/laochengzi/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-dummy_model_laochengzi_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-dummy_model_laochengzi_pipeline_en.md
new file mode 100644
index 00000000000000..d50aff611d181f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-dummy_model_laochengzi_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_laochengzi_pipeline pipeline CamemBertEmbeddings from laochengzi
+author: John Snow Labs
+name: dummy_model_laochengzi_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_laochengzi_pipeline` is a English model originally trained by laochengzi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_laochengzi_pipeline_en_5.5.1_3.0_1738123630767.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_laochengzi_pipeline_en_5.5.1_3.0_1738123630767.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_laochengzi_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_laochengzi_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_laochengzi_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/laochengzi/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-dummy_model_plasmatech8_en.md b/docs/_posts/ahmedlone127/2025-01-29-dummy_model_plasmatech8_en.md
new file mode 100644
index 00000000000000..50c29ffa6fa74b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-dummy_model_plasmatech8_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_plasmatech8 CamemBertEmbeddings from plasmatech8
+author: John Snow Labs
+name: dummy_model_plasmatech8
+date: 2025-01-29
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_plasmatech8` is a English model originally trained by plasmatech8.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_plasmatech8_en_5.5.1_3.0_1738123555687.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_plasmatech8_en_5.5.1_3.0_1738123555687.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_plasmatech8","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_plasmatech8","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_plasmatech8|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/plasmatech8/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-dummy_model_plasmatech8_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-dummy_model_plasmatech8_pipeline_en.md
new file mode 100644
index 00000000000000..0116da6c6ac437
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-dummy_model_plasmatech8_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_plasmatech8_pipeline pipeline CamemBertEmbeddings from plasmatech8
+author: John Snow Labs
+name: dummy_model_plasmatech8_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_plasmatech8_pipeline` is a English model originally trained by plasmatech8.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_plasmatech8_pipeline_en_5.5.1_3.0_1738123629471.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_plasmatech8_pipeline_en_5.5.1_3.0_1738123629471.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("dummy_model_plasmatech8_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_plasmatech8_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_plasmatech8_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/plasmatech8/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-fake_review_detection_1_en.md b/docs/_posts/ahmedlone127/2025-01-29-fake_review_detection_1_en.md
new file mode 100644
index 00000000000000..1572ea59df2187
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-fake_review_detection_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English fake_review_detection_1 DistilBertForSequenceClassification from Sathwik-kom
+author: John Snow Labs
+name: fake_review_detection_1
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fake_review_detection_1` is a English model originally trained by Sathwik-kom.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fake_review_detection_1_en_5.5.1_3.0_1738110710242.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fake_review_detection_1_en_5.5.1_3.0_1738110710242.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("fake_review_detection_1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("fake_review_detection_1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fake_review_detection_1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Sathwik-kom/fake-review-detection_1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-fake_review_detection_1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-fake_review_detection_1_pipeline_en.md
new file mode 100644
index 00000000000000..67b155d0bcea35
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-fake_review_detection_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English fake_review_detection_1_pipeline pipeline DistilBertForSequenceClassification from Sathwik-kom
+author: John Snow Labs
+name: fake_review_detection_1_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fake_review_detection_1_pipeline` is a English model originally trained by Sathwik-kom.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fake_review_detection_1_pipeline_en_5.5.1_3.0_1738110722928.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fake_review_detection_1_pipeline_en_5.5.1_3.0_1738110722928.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("fake_review_detection_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fake_review_detection_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fake_review_detection_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Sathwik-kom/fake-review-detection_1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-finbert_lm_finetuned_tweets_en.md b/docs/_posts/ahmedlone127/2025-01-29-finbert_lm_finetuned_tweets_en.md
new file mode 100644
index 00000000000000..9e7b942c648ab6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-finbert_lm_finetuned_tweets_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finbert_lm_finetuned_tweets BertEmbeddings from HoseinPanahi
+author: John Snow Labs
+name: finbert_lm_finetuned_tweets
+date: 2025-01-29
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finbert_lm_finetuned_tweets` is a English model originally trained by HoseinPanahi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finbert_lm_finetuned_tweets_en_5.5.1_3.0_1738120071455.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finbert_lm_finetuned_tweets_en_5.5.1_3.0_1738120071455.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("finbert_lm_finetuned_tweets","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("finbert_lm_finetuned_tweets","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finbert_lm_finetuned_tweets|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/HoseinPanahi/finbert-lm-finetuned-tweets
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-finbert_lm_finetuned_tweets_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-finbert_lm_finetuned_tweets_pipeline_en.md
new file mode 100644
index 00000000000000..22ddcb2f77a142
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-finbert_lm_finetuned_tweets_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finbert_lm_finetuned_tweets_pipeline pipeline BertEmbeddings from HoseinPanahi
+author: John Snow Labs
+name: finbert_lm_finetuned_tweets_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finbert_lm_finetuned_tweets_pipeline` is a English model originally trained by HoseinPanahi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finbert_lm_finetuned_tweets_pipeline_en_5.5.1_3.0_1738120091771.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finbert_lm_finetuned_tweets_pipeline_en_5.5.1_3.0_1738120091771.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finbert_lm_finetuned_tweets_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finbert_lm_finetuned_tweets_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finbert_lm_finetuned_tweets_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/HoseinPanahi/finbert-lm-finetuned-tweets
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-finetuned_yarn_en.md b/docs/_posts/ahmedlone127/2025-01-29-finetuned_yarn_en.md
new file mode 100644
index 00000000000000..106d220c564b4d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-finetuned_yarn_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuned_yarn DistilBertForSequenceClassification from Yarn
+author: John Snow Labs
+name: finetuned_yarn
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_yarn` is a English model originally trained by Yarn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_yarn_en_5.5.1_3.0_1738109992867.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_yarn_en_5.5.1_3.0_1738109992867.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuned_yarn","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuned_yarn", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_yarn|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Yarn/finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-finetuned_yarn_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-finetuned_yarn_pipeline_en.md
new file mode 100644
index 00000000000000..ac656b849bf2f4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-finetuned_yarn_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuned_yarn_pipeline pipeline DistilBertForSequenceClassification from Yarn
+author: John Snow Labs
+name: finetuned_yarn_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_yarn_pipeline` is a English model originally trained by Yarn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_yarn_pipeline_en_5.5.1_3.0_1738110005811.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_yarn_pipeline_en_5.5.1_3.0_1738110005811.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuned_yarn_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuned_yarn_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_yarn_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Yarn/finetuned
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-finetuning_emotion_model_mashxd_en.md b/docs/_posts/ahmedlone127/2025-01-29-finetuning_emotion_model_mashxd_en.md
new file mode 100644
index 00000000000000..0841684dae176e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-finetuning_emotion_model_mashxd_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuning_emotion_model_mashxd DistilBertForSequenceClassification from MASHXD
+author: John Snow Labs
+name: finetuning_emotion_model_mashxd
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_emotion_model_mashxd` is a English model originally trained by MASHXD.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_emotion_model_mashxd_en_5.5.1_3.0_1738110564600.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_emotion_model_mashxd_en_5.5.1_3.0_1738110564600.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuning_emotion_model_mashxd","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_emotion_model_mashxd", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_emotion_model_mashxd|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/MASHXD/finetuning-emotion-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-finetuning_emotion_model_mashxd_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-finetuning_emotion_model_mashxd_pipeline_en.md
new file mode 100644
index 00000000000000..15ea67c35da3f0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-finetuning_emotion_model_mashxd_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuning_emotion_model_mashxd_pipeline pipeline DistilBertForSequenceClassification from MASHXD
+author: John Snow Labs
+name: finetuning_emotion_model_mashxd_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_emotion_model_mashxd_pipeline` is a English model originally trained by MASHXD.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_emotion_model_mashxd_pipeline_en_5.5.1_3.0_1738110577104.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_emotion_model_mashxd_pipeline_en_5.5.1_3.0_1738110577104.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuning_emotion_model_mashxd_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuning_emotion_model_mashxd_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_emotion_model_mashxd_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/MASHXD/finetuning-emotion-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-finetuning_sentiment_model_3000_samples_andygoh5_en.md b/docs/_posts/ahmedlone127/2025-01-29-finetuning_sentiment_model_3000_samples_andygoh5_en.md
new file mode 100644
index 00000000000000..e1fd8516d47cf7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-finetuning_sentiment_model_3000_samples_andygoh5_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_andygoh5 DistilBertForSequenceClassification from andygoh5
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_andygoh5
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_andygoh5` is a English model originally trained by andygoh5.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_andygoh5_en_5.5.1_3.0_1738110611305.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_andygoh5_en_5.5.1_3.0_1738110611305.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_andygoh5","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_andygoh5", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_andygoh5|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/andygoh5/finetuning-sentiment-model-3000-samples
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-finetuning_sentiment_model_3000_samples_andygoh5_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-finetuning_sentiment_model_3000_samples_andygoh5_pipeline_en.md
new file mode 100644
index 00000000000000..63f848d2701ed7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-finetuning_sentiment_model_3000_samples_andygoh5_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_andygoh5_pipeline pipeline DistilBertForSequenceClassification from andygoh5
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_andygoh5_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_andygoh5_pipeline` is a English model originally trained by andygoh5.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_andygoh5_pipeline_en_5.5.1_3.0_1738110625193.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_andygoh5_pipeline_en_5.5.1_3.0_1738110625193.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuning_sentiment_model_3000_samples_andygoh5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuning_sentiment_model_3000_samples_andygoh5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_andygoh5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/andygoh5/finetuning-sentiment-model-3000-samples
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-finetuning_sentiment_model_3000_samples_maurya123ritesh47_en.md b/docs/_posts/ahmedlone127/2025-01-29-finetuning_sentiment_model_3000_samples_maurya123ritesh47_en.md
new file mode 100644
index 00000000000000..dac62e6c951790
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-finetuning_sentiment_model_3000_samples_maurya123ritesh47_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_maurya123ritesh47 DistilBertForSequenceClassification from maurya123ritesh47
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_maurya123ritesh47
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_maurya123ritesh47` is a English model originally trained by maurya123ritesh47.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_maurya123ritesh47_en_5.5.1_3.0_1738110349062.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_maurya123ritesh47_en_5.5.1_3.0_1738110349062.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_maurya123ritesh47","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_maurya123ritesh47", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_maurya123ritesh47|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/maurya123ritesh47/finetuning-sentiment-model-3000-samples
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-finetuning_sentiment_model_3000_samples_maurya123ritesh47_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-finetuning_sentiment_model_3000_samples_maurya123ritesh47_pipeline_en.md
new file mode 100644
index 00000000000000..5c20e6d0661374
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-finetuning_sentiment_model_3000_samples_maurya123ritesh47_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_maurya123ritesh47_pipeline pipeline DistilBertForSequenceClassification from maurya123ritesh47
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_maurya123ritesh47_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_maurya123ritesh47_pipeline` is a English model originally trained by maurya123ritesh47.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_maurya123ritesh47_pipeline_en_5.5.1_3.0_1738110362485.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_maurya123ritesh47_pipeline_en_5.5.1_3.0_1738110362485.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuning_sentiment_model_3000_samples_maurya123ritesh47_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuning_sentiment_model_3000_samples_maurya123ritesh47_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_maurya123ritesh47_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/maurya123ritesh47/finetuning-sentiment-model-3000-samples
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-finetuning_sentiment_model_3000_samples_suddz_en.md b/docs/_posts/ahmedlone127/2025-01-29-finetuning_sentiment_model_3000_samples_suddz_en.md
new file mode 100644
index 00000000000000..c0a3143abe59a9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-finetuning_sentiment_model_3000_samples_suddz_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_suddz DistilBertForSequenceClassification from SuddZ
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_suddz
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_suddz` is a English model originally trained by SuddZ.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_suddz_en_5.5.1_3.0_1738131647900.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_suddz_en_5.5.1_3.0_1738131647900.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_suddz","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_suddz", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_suddz|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/SuddZ/finetuning-sentiment-model-3000-samples
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-finetuning_sentiment_model_3000_samples_suddz_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-finetuning_sentiment_model_3000_samples_suddz_pipeline_en.md
new file mode 100644
index 00000000000000..9599f1097c556f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-finetuning_sentiment_model_3000_samples_suddz_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_suddz_pipeline pipeline DistilBertForSequenceClassification from SuddZ
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_suddz_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_suddz_pipeline` is a English model originally trained by SuddZ.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_suddz_pipeline_en_5.5.1_3.0_1738131660994.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_suddz_pipeline_en_5.5.1_3.0_1738131660994.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuning_sentiment_model_3000_samples_suddz_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuning_sentiment_model_3000_samples_suddz_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_suddz_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/SuddZ/finetuning-sentiment-model-3000-samples
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-finetuning_sentiment_model_bank_reviews_otherbank_en.md b/docs/_posts/ahmedlone127/2025-01-29-finetuning_sentiment_model_bank_reviews_otherbank_en.md
new file mode 100644
index 00000000000000..ae9a31b52b189c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-finetuning_sentiment_model_bank_reviews_otherbank_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuning_sentiment_model_bank_reviews_otherbank DistilBertForSequenceClassification from ajiayi
+author: John Snow Labs
+name: finetuning_sentiment_model_bank_reviews_otherbank
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_bank_reviews_otherbank` is a English model originally trained by ajiayi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_bank_reviews_otherbank_en_5.5.1_3.0_1738110113981.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_bank_reviews_otherbank_en_5.5.1_3.0_1738110113981.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_bank_reviews_otherbank","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_bank_reviews_otherbank", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_bank_reviews_otherbank|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/ajiayi/finetuning-sentiment-model-bank_reviews-otherbank
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-finetuning_sentiment_model_bank_reviews_otherbank_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-finetuning_sentiment_model_bank_reviews_otherbank_pipeline_en.md
new file mode 100644
index 00000000000000..26d33155790ef8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-finetuning_sentiment_model_bank_reviews_otherbank_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuning_sentiment_model_bank_reviews_otherbank_pipeline pipeline DistilBertForSequenceClassification from ajiayi
+author: John Snow Labs
+name: finetuning_sentiment_model_bank_reviews_otherbank_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_bank_reviews_otherbank_pipeline` is a English model originally trained by ajiayi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_bank_reviews_otherbank_pipeline_en_5.5.1_3.0_1738110126839.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_bank_reviews_otherbank_pipeline_en_5.5.1_3.0_1738110126839.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("finetuning_sentiment_model_bank_reviews_otherbank_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuning_sentiment_model_bank_reviews_otherbank_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_bank_reviews_otherbank_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/ajiayi/finetuning-sentiment-model-bank_reviews-otherbank
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-flan_t5_rouge_squad_qg_testd_en.md b/docs/_posts/ahmedlone127/2025-01-29-flan_t5_rouge_squad_qg_testd_en.md
new file mode 100644
index 00000000000000..3bac96975dd988
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-flan_t5_rouge_squad_qg_testd_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English flan_t5_rouge_squad_qg_testd T5Transformer from devagonal
+author: John Snow Labs
+name: flan_t5_rouge_squad_qg_testd
+date: 2025-01-29
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flan_t5_rouge_squad_qg_testd` is a English model originally trained by devagonal.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flan_t5_rouge_squad_qg_testd_en_5.5.1_3.0_1738136886582.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flan_t5_rouge_squad_qg_testd_en_5.5.1_3.0_1738136886582.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("flan_t5_rouge_squad_qg_testd","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("flan_t5_rouge_squad_qg_testd", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flan_t5_rouge_squad_qg_testd|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|349.8 MB|
+
+## References
+
+https://huggingface.co/devagonal/flan-t5-rouge-squad-qg-testd
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-ft_distilbert_base_uncased_tancredimatteo_en.md b/docs/_posts/ahmedlone127/2025-01-29-ft_distilbert_base_uncased_tancredimatteo_en.md
new file mode 100644
index 00000000000000..31fcb3c77609cb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-ft_distilbert_base_uncased_tancredimatteo_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ft_distilbert_base_uncased_tancredimatteo DistilBertForSequenceClassification from tancredimatteo
+author: John Snow Labs
+name: ft_distilbert_base_uncased_tancredimatteo
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ft_distilbert_base_uncased_tancredimatteo` is a English model originally trained by tancredimatteo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ft_distilbert_base_uncased_tancredimatteo_en_5.5.1_3.0_1738131153592.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ft_distilbert_base_uncased_tancredimatteo_en_5.5.1_3.0_1738131153592.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("ft_distilbert_base_uncased_tancredimatteo","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("ft_distilbert_base_uncased_tancredimatteo", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ft_distilbert_base_uncased_tancredimatteo|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/tancredimatteo/FT-distilbert-base-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-ft_distilbert_base_uncased_tancredimatteo_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-ft_distilbert_base_uncased_tancredimatteo_pipeline_en.md
new file mode 100644
index 00000000000000..08aa211b006ea7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-ft_distilbert_base_uncased_tancredimatteo_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ft_distilbert_base_uncased_tancredimatteo_pipeline pipeline DistilBertForSequenceClassification from tancredimatteo
+author: John Snow Labs
+name: ft_distilbert_base_uncased_tancredimatteo_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ft_distilbert_base_uncased_tancredimatteo_pipeline` is a English model originally trained by tancredimatteo.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ft_distilbert_base_uncased_tancredimatteo_pipeline_en_5.5.1_3.0_1738131166659.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ft_distilbert_base_uncased_tancredimatteo_pipeline_en_5.5.1_3.0_1738131166659.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ft_distilbert_base_uncased_tancredimatteo_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ft_distilbert_base_uncased_tancredimatteo_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ft_distilbert_base_uncased_tancredimatteo_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/tancredimatteo/FT-distilbert-base-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-grammar_correction_en.md b/docs/_posts/ahmedlone127/2025-01-29-grammar_correction_en.md
new file mode 100644
index 00000000000000..c8f13619e374d3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-grammar_correction_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English grammar_correction T5Transformer from amanuelyh
+author: John Snow Labs
+name: grammar_correction
+date: 2025-01-29
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`grammar_correction` is a English model originally trained by amanuelyh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/grammar_correction_en_5.5.1_3.0_1738136838025.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/grammar_correction_en_5.5.1_3.0_1738136838025.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("grammar_correction","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("grammar_correction", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|grammar_correction|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|909.8 MB|
+
+## References
+
+https://huggingface.co/amanuelyh/grammar_correction
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-grammar_correction_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-grammar_correction_pipeline_en.md
new file mode 100644
index 00000000000000..26833299af4f03
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-grammar_correction_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English grammar_correction_pipeline pipeline T5Transformer from amanuelyh
+author: John Snow Labs
+name: grammar_correction_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`grammar_correction_pipeline` is a English model originally trained by amanuelyh.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/grammar_correction_pipeline_en_5.5.1_3.0_1738136888330.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/grammar_correction_pipeline_en_5.5.1_3.0_1738136888330.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("grammar_correction_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("grammar_correction_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|grammar_correction_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|909.8 MB|
+
+## References
+
+https://huggingface.co/amanuelyh/grammar_correction
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-hubert_kakeiken_w_reverbed_clean_en.md b/docs/_posts/ahmedlone127/2025-01-29-hubert_kakeiken_w_reverbed_clean_en.md
new file mode 100644
index 00000000000000..35b5d333473d06
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-hubert_kakeiken_w_reverbed_clean_en.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: English hubert_kakeiken_w_reverbed_clean HubertForCTC from utakumi
+author: John Snow Labs
+name: hubert_kakeiken_w_reverbed_clean
+date: 2025-01-29
+tags: [en, open_source, onnx, asr, hubert]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: HubertForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_kakeiken_w_reverbed_clean` is a English model originally trained by utakumi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_kakeiken_w_reverbed_clean_en_5.5.1_3.0_1738129353088.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_kakeiken_w_reverbed_clean_en_5.5.1_3.0_1738129353088.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = HubertForCTC.pretrained("hubert_kakeiken_w_reverbed_clean","en") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = HubertForCTC.pretrained("hubert_kakeiken_w_reverbed_clean", "en")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hubert_kakeiken_w_reverbed_clean|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|en|
+|Size:|697.9 MB|
+
+## References
+
+https://huggingface.co/utakumi/Hubert-kakeiken-W-reverbed_clean
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-hubert_kakeiken_w_reverbed_clean_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-hubert_kakeiken_w_reverbed_clean_pipeline_en.md
new file mode 100644
index 00000000000000..7e28c8f4aa0b71
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-hubert_kakeiken_w_reverbed_clean_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English hubert_kakeiken_w_reverbed_clean_pipeline pipeline HubertForCTC from utakumi
+author: John Snow Labs
+name: hubert_kakeiken_w_reverbed_clean_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained HubertForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_kakeiken_w_reverbed_clean_pipeline` is a English model originally trained by utakumi.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_kakeiken_w_reverbed_clean_pipeline_en_5.5.1_3.0_1738129392150.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_kakeiken_w_reverbed_clean_pipeline_en_5.5.1_3.0_1738129392150.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("hubert_kakeiken_w_reverbed_clean_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hubert_kakeiken_w_reverbed_clean_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hubert_kakeiken_w_reverbed_clean_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|697.9 MB|
+
+## References
+
+https://huggingface.co/utakumi/Hubert-kakeiken-W-reverbed_clean
+
+## Included Models
+
+- AudioAssembler
+- HubertForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-imdb_distilbert_base_uncased_prgckwb_en.md b/docs/_posts/ahmedlone127/2025-01-29-imdb_distilbert_base_uncased_prgckwb_en.md
new file mode 100644
index 00000000000000..53ee7e2f688984
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-imdb_distilbert_base_uncased_prgckwb_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English imdb_distilbert_base_uncased_prgckwb DistilBertForSequenceClassification from Prgckwb
+author: John Snow Labs
+name: imdb_distilbert_base_uncased_prgckwb
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`imdb_distilbert_base_uncased_prgckwb` is a English model originally trained by Prgckwb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/imdb_distilbert_base_uncased_prgckwb_en_5.5.1_3.0_1738131579037.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/imdb_distilbert_base_uncased_prgckwb_en_5.5.1_3.0_1738131579037.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("imdb_distilbert_base_uncased_prgckwb","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("imdb_distilbert_base_uncased_prgckwb", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|imdb_distilbert_base_uncased_prgckwb|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Prgckwb/imdb-distilbert-base-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-imdb_distilbert_base_uncased_prgckwb_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-imdb_distilbert_base_uncased_prgckwb_pipeline_en.md
new file mode 100644
index 00000000000000..c7d9af56d6c54e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-imdb_distilbert_base_uncased_prgckwb_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English imdb_distilbert_base_uncased_prgckwb_pipeline pipeline DistilBertForSequenceClassification from Prgckwb
+author: John Snow Labs
+name: imdb_distilbert_base_uncased_prgckwb_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`imdb_distilbert_base_uncased_prgckwb_pipeline` is a English model originally trained by Prgckwb.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/imdb_distilbert_base_uncased_prgckwb_pipeline_en_5.5.1_3.0_1738131597890.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/imdb_distilbert_base_uncased_prgckwb_pipeline_en_5.5.1_3.0_1738131597890.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("imdb_distilbert_base_uncased_prgckwb_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("imdb_distilbert_base_uncased_prgckwb_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|imdb_distilbert_base_uncased_prgckwb_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Prgckwb/imdb-distilbert-base-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-intent_analysis_xml_5ep_v1_spanish_catalan_en.md b/docs/_posts/ahmedlone127/2025-01-29-intent_analysis_xml_5ep_v1_spanish_catalan_en.md
new file mode 100644
index 00000000000000..596c682cd40d2a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-intent_analysis_xml_5ep_v1_spanish_catalan_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English intent_analysis_xml_5ep_v1_spanish_catalan XlmRoBertaForSequenceClassification from adriansanz
+author: John Snow Labs
+name: intent_analysis_xml_5ep_v1_spanish_catalan
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`intent_analysis_xml_5ep_v1_spanish_catalan` is a English model originally trained by adriansanz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/intent_analysis_xml_5ep_v1_spanish_catalan_en_5.5.1_3.0_1738127769157.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/intent_analysis_xml_5ep_v1_spanish_catalan_en_5.5.1_3.0_1738127769157.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("intent_analysis_xml_5ep_v1_spanish_catalan","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("intent_analysis_xml_5ep_v1_spanish_catalan", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|intent_analysis_xml_5ep_v1_spanish_catalan|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|777.4 MB|
+
+## References
+
+https://huggingface.co/adriansanz/intent_analysis_xml_5ep_v1_es_ca
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-intent_analysis_xml_5ep_v1_spanish_catalan_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-intent_analysis_xml_5ep_v1_spanish_catalan_pipeline_en.md
new file mode 100644
index 00000000000000..3756df2a6677f1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-intent_analysis_xml_5ep_v1_spanish_catalan_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English intent_analysis_xml_5ep_v1_spanish_catalan_pipeline pipeline XlmRoBertaForSequenceClassification from adriansanz
+author: John Snow Labs
+name: intent_analysis_xml_5ep_v1_spanish_catalan_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`intent_analysis_xml_5ep_v1_spanish_catalan_pipeline` is a English model originally trained by adriansanz.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/intent_analysis_xml_5ep_v1_spanish_catalan_pipeline_en_5.5.1_3.0_1738127909831.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/intent_analysis_xml_5ep_v1_spanish_catalan_pipeline_en_5.5.1_3.0_1738127909831.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("intent_analysis_xml_5ep_v1_spanish_catalan_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("intent_analysis_xml_5ep_v1_spanish_catalan_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|intent_analysis_xml_5ep_v1_spanish_catalan_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|777.4 MB|
+
+## References
+
+https://huggingface.co/adriansanz/intent_analysis_xml_5ep_v1_es_ca
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-isaac_model_en.md b/docs/_posts/ahmedlone127/2025-01-29-isaac_model_en.md
new file mode 100644
index 00000000000000..4f67916044e2ab
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-isaac_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English isaac_model BertEmbeddings from Saffy
+author: John Snow Labs
+name: isaac_model
+date: 2025-01-29
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`isaac_model` is a English model originally trained by Saffy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/isaac_model_en_5.5.1_3.0_1738119641201.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/isaac_model_en_5.5.1_3.0_1738119641201.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("isaac_model","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("isaac_model","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|isaac_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/Saffy/Isaac-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-isaac_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-isaac_model_pipeline_en.md
new file mode 100644
index 00000000000000..83dc720e18836d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-isaac_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English isaac_model_pipeline pipeline BertEmbeddings from Saffy
+author: John Snow Labs
+name: isaac_model_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`isaac_model_pipeline` is a English model originally trained by Saffy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/isaac_model_pipeline_en_5.5.1_3.0_1738119661726.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/isaac_model_pipeline_en_5.5.1_3.0_1738119661726.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("isaac_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("isaac_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|isaac_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/Saffy/Isaac-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-isy503_sentiment_analysis2_en.md b/docs/_posts/ahmedlone127/2025-01-29-isy503_sentiment_analysis2_en.md
new file mode 100644
index 00000000000000..90e886d14e70ad
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-isy503_sentiment_analysis2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English isy503_sentiment_analysis2 DistilBertForSequenceClassification from jayllan23
+author: John Snow Labs
+name: isy503_sentiment_analysis2
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`isy503_sentiment_analysis2` is a English model originally trained by jayllan23.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/isy503_sentiment_analysis2_en_5.5.1_3.0_1738110624579.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/isy503_sentiment_analysis2_en_5.5.1_3.0_1738110624579.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("isy503_sentiment_analysis2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("isy503_sentiment_analysis2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|isy503_sentiment_analysis2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/jayllan23/ISY503-sentiment_analysis2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-isy503_sentiment_analysis2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-isy503_sentiment_analysis2_pipeline_en.md
new file mode 100644
index 00000000000000..7b0e5be42c874c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-isy503_sentiment_analysis2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English isy503_sentiment_analysis2_pipeline pipeline DistilBertForSequenceClassification from jayllan23
+author: John Snow Labs
+name: isy503_sentiment_analysis2_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`isy503_sentiment_analysis2_pipeline` is a English model originally trained by jayllan23.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/isy503_sentiment_analysis2_pipeline_en_5.5.1_3.0_1738110640290.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/isy503_sentiment_analysis2_pipeline_en_5.5.1_3.0_1738110640290.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("isy503_sentiment_analysis2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("isy503_sentiment_analysis2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|isy503_sentiment_analysis2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/jayllan23/ISY503-sentiment_analysis2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-keywordextractor_en.md b/docs/_posts/ahmedlone127/2025-01-29-keywordextractor_en.md
new file mode 100644
index 00000000000000..d5639c6c2aa513
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-keywordextractor_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English keywordextractor BartTransformer from transformer3
+author: John Snow Labs
+name: keywordextractor
+date: 2025-01-29
+tags: [en, open_source, onnx, text_generation, bart]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BartTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`keywordextractor` is a English model originally trained by transformer3.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/keywordextractor_en_5.5.1_3.0_1738121895205.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/keywordextractor_en_5.5.1_3.0_1738121895205.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = BartTransformer.pretrained("keywordextractor","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+        
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val seq2seq = BartTransformer.pretrained("keywordextractor","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|keywordextractor|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.9 GB|
+
+## References
+
+https://huggingface.co/transformer3/keywordextractor
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-keywordextractor_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-keywordextractor_pipeline_en.md
new file mode 100644
index 00000000000000..7c50c86b1360ac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-keywordextractor_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English keywordextractor_pipeline pipeline BartTransformer from transformer3
+author: John Snow Labs
+name: keywordextractor_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BartTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`keywordextractor_pipeline` is a English model originally trained by transformer3.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/keywordextractor_pipeline_en_5.5.1_3.0_1738121985833.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/keywordextractor_pipeline_en_5.5.1_3.0_1738121985833.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("keywordextractor_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("keywordextractor_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|keywordextractor_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.9 GB|
+
+## References
+
+https://huggingface.co/transformer3/keywordextractor
+
+## Included Models
+
+- DocumentAssembler
+- BartTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-m365_h2_text_processing_and_summarization_en.md b/docs/_posts/ahmedlone127/2025-01-29-m365_h2_text_processing_and_summarization_en.md
new file mode 100644
index 00000000000000..7c86e63b25739c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-m365_h2_text_processing_and_summarization_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English m365_h2_text_processing_and_summarization DistilBertForSequenceClassification from marklicata
+author: John Snow Labs
+name: m365_h2_text_processing_and_summarization
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`m365_h2_text_processing_and_summarization` is a English model originally trained by marklicata.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/m365_h2_text_processing_and_summarization_en_5.5.1_3.0_1738131513776.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/m365_h2_text_processing_and_summarization_en_5.5.1_3.0_1738131513776.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("m365_h2_text_processing_and_summarization","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("m365_h2_text_processing_and_summarization", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|m365_h2_text_processing_and_summarization|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/marklicata/M365_h2_Text_Processing_and_Summarization
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-m365_h2_text_processing_and_summarization_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-m365_h2_text_processing_and_summarization_pipeline_en.md
new file mode 100644
index 00000000000000..f6a4cf4888db78
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-m365_h2_text_processing_and_summarization_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English m365_h2_text_processing_and_summarization_pipeline pipeline DistilBertForSequenceClassification from marklicata
+author: John Snow Labs
+name: m365_h2_text_processing_and_summarization_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`m365_h2_text_processing_and_summarization_pipeline` is a English model originally trained by marklicata.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/m365_h2_text_processing_and_summarization_pipeline_en_5.5.1_3.0_1738131526842.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/m365_h2_text_processing_and_summarization_pipeline_en_5.5.1_3.0_1738131526842.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("m365_h2_text_processing_and_summarization_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("m365_h2_text_processing_and_summarization_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|m365_h2_text_processing_and_summarization_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/marklicata/M365_h2_Text_Processing_and_Summarization
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-memo_bert_wsd_before_last_da.md b/docs/_posts/ahmedlone127/2025-01-29-memo_bert_wsd_before_last_da.md
new file mode 100644
index 00000000000000..552356ab453524
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-memo_bert_wsd_before_last_da.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Danish memo_bert_wsd_before_last XlmRoBertaForSequenceClassification from yemen2016
+author: John Snow Labs
+name: memo_bert_wsd_before_last
+date: 2025-01-29
+tags: [da, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: da
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`memo_bert_wsd_before_last` is a Danish model originally trained by yemen2016.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/memo_bert_wsd_before_last_da_5.5.1_3.0_1738125449792.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/memo_bert_wsd_before_last_da_5.5.1_3.0_1738125449792.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("memo_bert_wsd_before_last","da") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("memo_bert_wsd_before_last", "da")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|memo_bert_wsd_before_last|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|da|
+|Size:|466.6 MB|
+
+## References
+
+https://huggingface.co/yemen2016/MeMo-BERT-WSD_before_last
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-memo_bert_wsd_before_last_pipeline_da.md b/docs/_posts/ahmedlone127/2025-01-29-memo_bert_wsd_before_last_pipeline_da.md
new file mode 100644
index 00000000000000..eab60fcbb04829
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-memo_bert_wsd_before_last_pipeline_da.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Danish memo_bert_wsd_before_last_pipeline pipeline XlmRoBertaForSequenceClassification from yemen2016
+author: John Snow Labs
+name: memo_bert_wsd_before_last_pipeline
+date: 2025-01-29
+tags: [da, open_source, pipeline, onnx]
+task: Text Classification
+language: da
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`memo_bert_wsd_before_last_pipeline` is a Danish model originally trained by yemen2016.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/memo_bert_wsd_before_last_pipeline_da_5.5.1_3.0_1738125473251.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/memo_bert_wsd_before_last_pipeline_da_5.5.1_3.0_1738125473251.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("memo_bert_wsd_before_last_pipeline", lang = "da")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("memo_bert_wsd_before_last_pipeline", lang = "da")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|memo_bert_wsd_before_last_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|da|
+|Size:|466.6 MB|
+
+## References
+
+https://huggingface.co/yemen2016/MeMo-BERT-WSD_before_last
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-mlm_biobert_diseases_ner_psnod_en.md b/docs/_posts/ahmedlone127/2025-01-29-mlm_biobert_diseases_ner_psnod_en.md
new file mode 100644
index 00000000000000..595bb299f40608
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-mlm_biobert_diseases_ner_psnod_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mlm_biobert_diseases_ner_psnod BertEmbeddings from Milad1b
+author: John Snow Labs
+name: mlm_biobert_diseases_ner_psnod
+date: 2025-01-29
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mlm_biobert_diseases_ner_psnod` is a English model originally trained by Milad1b.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mlm_biobert_diseases_ner_psnod_en_5.5.1_3.0_1738119865673.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mlm_biobert_diseases_ner_psnod_en_5.5.1_3.0_1738119865673.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("mlm_biobert_diseases_ner_psnod","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("mlm_biobert_diseases_ner_psnod","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mlm_biobert_diseases_ner_psnod|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|403.1 MB|
+
+## References
+
+https://huggingface.co/Milad1b/MLM_biobert_diseases_ner_PsnoD
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-mlm_biobert_diseases_ner_psnod_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-mlm_biobert_diseases_ner_psnod_pipeline_en.md
new file mode 100644
index 00000000000000..378f50fc0d7950
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-mlm_biobert_diseases_ner_psnod_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mlm_biobert_diseases_ner_psnod_pipeline pipeline BertEmbeddings from Milad1b
+author: John Snow Labs
+name: mlm_biobert_diseases_ner_psnod_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mlm_biobert_diseases_ner_psnod_pipeline` is a English model originally trained by Milad1b.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mlm_biobert_diseases_ner_psnod_pipeline_en_5.5.1_3.0_1738119886079.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mlm_biobert_diseases_ner_psnod_pipeline_en_5.5.1_3.0_1738119886079.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mlm_biobert_diseases_ner_psnod_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mlm_biobert_diseases_ner_psnod_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mlm_biobert_diseases_ner_psnod_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.2 MB|
+
+## References
+
+https://huggingface.co/Milad1b/MLM_biobert_diseases_ner_PsnoD
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-mount_ner_model_en.md b/docs/_posts/ahmedlone127/2025-01-29-mount_ner_model_en.md
new file mode 100644
index 00000000000000..d3eae86a6ac7fb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-mount_ner_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mount_ner_model BertForTokenClassification from sskyisthelimit
+author: John Snow Labs
+name: mount_ner_model
+date: 2025-01-29
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mount_ner_model` is a English model originally trained by sskyisthelimit.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mount_ner_model_en_5.5.1_3.0_1738111669958.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mount_ner_model_en_5.5.1_3.0_1738111669958.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("mount_ner_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("mount_ner_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mount_ner_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/sskyisthelimit/mount-ner-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-mount_ner_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-mount_ner_model_pipeline_en.md
new file mode 100644
index 00000000000000..211a4d196512de
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-mount_ner_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mount_ner_model_pipeline pipeline BertForTokenClassification from sskyisthelimit
+author: John Snow Labs
+name: mount_ner_model_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mount_ner_model_pipeline` is a English model originally trained by sskyisthelimit.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mount_ner_model_pipeline_en_5.5.1_3.0_1738111696291.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mount_ner_model_pipeline_en_5.5.1_3.0_1738111696291.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("mount_ner_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mount_ner_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mount_ner_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/sskyisthelimit/mount-ner-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-ndd_pagekit_test_tags_en.md b/docs/_posts/ahmedlone127/2025-01-29-ndd_pagekit_test_tags_en.md
new file mode 100644
index 00000000000000..f09a715aa0f24a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-ndd_pagekit_test_tags_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ndd_pagekit_test_tags DistilBertForSequenceClassification from lgk03
+author: John Snow Labs
+name: ndd_pagekit_test_tags
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ndd_pagekit_test_tags` is a English model originally trained by lgk03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ndd_pagekit_test_tags_en_5.5.1_3.0_1738131467447.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ndd_pagekit_test_tags_en_5.5.1_3.0_1738131467447.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("ndd_pagekit_test_tags","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("ndd_pagekit_test_tags", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ndd_pagekit_test_tags|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/lgk03/NDD-pagekit_test-tags
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-ndd_pagekit_test_tags_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-ndd_pagekit_test_tags_pipeline_en.md
new file mode 100644
index 00000000000000..a726274929c273
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-ndd_pagekit_test_tags_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ndd_pagekit_test_tags_pipeline pipeline DistilBertForSequenceClassification from lgk03
+author: John Snow Labs
+name: ndd_pagekit_test_tags_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ndd_pagekit_test_tags_pipeline` is a English model originally trained by lgk03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ndd_pagekit_test_tags_pipeline_en_5.5.1_3.0_1738131480383.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ndd_pagekit_test_tags_pipeline_en_5.5.1_3.0_1738131480383.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ndd_pagekit_test_tags_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ndd_pagekit_test_tags_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ndd_pagekit_test_tags_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/lgk03/NDD-pagekit_test-tags
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-ndd_petclinic_test_tags_en.md b/docs/_posts/ahmedlone127/2025-01-29-ndd_petclinic_test_tags_en.md
new file mode 100644
index 00000000000000..fab8604960687f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-ndd_petclinic_test_tags_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ndd_petclinic_test_tags DistilBertForSequenceClassification from lgk03
+author: John Snow Labs
+name: ndd_petclinic_test_tags
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ndd_petclinic_test_tags` is a English model originally trained by lgk03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ndd_petclinic_test_tags_en_5.5.1_3.0_1738130909153.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ndd_petclinic_test_tags_en_5.5.1_3.0_1738130909153.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("ndd_petclinic_test_tags","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("ndd_petclinic_test_tags", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ndd_petclinic_test_tags|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/lgk03/NDD-petclinic_test-tags
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-ndd_petclinic_test_tags_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-ndd_petclinic_test_tags_pipeline_en.md
new file mode 100644
index 00000000000000..7ccbd9507adf23
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-ndd_petclinic_test_tags_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ndd_petclinic_test_tags_pipeline pipeline DistilBertForSequenceClassification from lgk03
+author: John Snow Labs
+name: ndd_petclinic_test_tags_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ndd_petclinic_test_tags_pipeline` is a English model originally trained by lgk03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ndd_petclinic_test_tags_pipeline_en_5.5.1_3.0_1738130922365.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ndd_petclinic_test_tags_pipeline_en_5.5.1_3.0_1738130922365.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("ndd_petclinic_test_tags_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ndd_petclinic_test_tags_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ndd_petclinic_test_tags_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/lgk03/NDD-petclinic_test-tags
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-news_demo_trainingrisk_multilingual_cased_v2_pipeline_xx.md b/docs/_posts/ahmedlone127/2025-01-29-news_demo_trainingrisk_multilingual_cased_v2_pipeline_xx.md
new file mode 100644
index 00000000000000..ac8a4c87e60f53
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-news_demo_trainingrisk_multilingual_cased_v2_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual news_demo_trainingrisk_multilingual_cased_v2_pipeline pipeline DistilBertForSequenceClassification from yeelou
+author: John Snow Labs
+name: news_demo_trainingrisk_multilingual_cased_v2_pipeline
+date: 2025-01-29
+tags: [xx, open_source, pipeline, onnx]
+task: Text Classification
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`news_demo_trainingrisk_multilingual_cased_v2_pipeline` is a Multilingual model originally trained by yeelou.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/news_demo_trainingrisk_multilingual_cased_v2_pipeline_xx_5.5.1_3.0_1738110761347.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/news_demo_trainingrisk_multilingual_cased_v2_pipeline_xx_5.5.1_3.0_1738110761347.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("news_demo_trainingrisk_multilingual_cased_v2_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("news_demo_trainingrisk_multilingual_cased_v2_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|news_demo_trainingrisk_multilingual_cased_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|509.8 MB|
+
+## References
+
+https://huggingface.co/yeelou/news-demo-trainingrisk-multilingual-cased-v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-news_demo_trainingrisk_multilingual_cased_v2_xx.md b/docs/_posts/ahmedlone127/2025-01-29-news_demo_trainingrisk_multilingual_cased_v2_xx.md
new file mode 100644
index 00000000000000..0c314356924bb6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-news_demo_trainingrisk_multilingual_cased_v2_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual news_demo_trainingrisk_multilingual_cased_v2 DistilBertForSequenceClassification from yeelou
+author: John Snow Labs
+name: news_demo_trainingrisk_multilingual_cased_v2
+date: 2025-01-29
+tags: [xx, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: xx
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`news_demo_trainingrisk_multilingual_cased_v2` is a Multilingual model originally trained by yeelou.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/news_demo_trainingrisk_multilingual_cased_v2_xx_5.5.1_3.0_1738110735941.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/news_demo_trainingrisk_multilingual_cased_v2_xx_5.5.1_3.0_1738110735941.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("news_demo_trainingrisk_multilingual_cased_v2","xx") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("news_demo_trainingrisk_multilingual_cased_v2", "xx")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|news_demo_trainingrisk_multilingual_cased_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|xx|
+|Size:|509.8 MB|
+
+## References
+
+https://huggingface.co/yeelou/news-demo-trainingrisk-multilingual-cased-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-output_dir_anik5099_en.md b/docs/_posts/ahmedlone127/2025-01-29-output_dir_anik5099_en.md
new file mode 100644
index 00000000000000..c7420321c0ed99
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-output_dir_anik5099_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English output_dir_anik5099 DistilBertForSequenceClassification from anik5099
+author: John Snow Labs
+name: output_dir_anik5099
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`output_dir_anik5099` is a English model originally trained by anik5099.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/output_dir_anik5099_en_5.5.1_3.0_1738131046286.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/output_dir_anik5099_en_5.5.1_3.0_1738131046286.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("output_dir_anik5099","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("output_dir_anik5099", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|output_dir_anik5099|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/anik5099/output_dir
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-output_dir_anik5099_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-output_dir_anik5099_pipeline_en.md
new file mode 100644
index 00000000000000..a216f932318acd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-output_dir_anik5099_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English output_dir_anik5099_pipeline pipeline DistilBertForSequenceClassification from anik5099
+author: John Snow Labs
+name: output_dir_anik5099_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`output_dir_anik5099_pipeline` is a English model originally trained by anik5099.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/output_dir_anik5099_pipeline_en_5.5.1_3.0_1738131059035.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/output_dir_anik5099_pipeline_en_5.5.1_3.0_1738131059035.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("output_dir_anik5099_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("output_dir_anik5099_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|output_dir_anik5099_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/anik5099/output_dir
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-pebblo_classifier_v2_en.md b/docs/_posts/ahmedlone127/2025-01-29-pebblo_classifier_v2_en.md
new file mode 100644
index 00000000000000..452e8e7b6dcda1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-pebblo_classifier_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English pebblo_classifier_v2 DistilBertForSequenceClassification from daxa-ai
+author: John Snow Labs
+name: pebblo_classifier_v2
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pebblo_classifier_v2` is a English model originally trained by daxa-ai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pebblo_classifier_v2_en_5.5.1_3.0_1738110188536.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pebblo_classifier_v2_en_5.5.1_3.0_1738110188536.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("pebblo_classifier_v2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("pebblo_classifier_v2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pebblo_classifier_v2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/daxa-ai/pebblo-classifier-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-pebblo_classifier_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-pebblo_classifier_v2_pipeline_en.md
new file mode 100644
index 00000000000000..581fa42a7ad0ed
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-pebblo_classifier_v2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English pebblo_classifier_v2_pipeline pipeline DistilBertForSequenceClassification from daxa-ai
+author: John Snow Labs
+name: pebblo_classifier_v2_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pebblo_classifier_v2_pipeline` is a English model originally trained by daxa-ai.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pebblo_classifier_v2_pipeline_en_5.5.1_3.0_1738110201923.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pebblo_classifier_v2_pipeline_en_5.5.1_3.0_1738110201923.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("pebblo_classifier_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("pebblo_classifier_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pebblo_classifier_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/daxa-ai/pebblo-classifier-v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-repo_en.md b/docs/_posts/ahmedlone127/2025-01-29-repo_en.md
new file mode 100644
index 00000000000000..4be60b2c4d3153
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-repo_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English repo DistilBertForSequenceClassification from lfrp82
+author: John Snow Labs
+name: repo
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`repo` is a English model originally trained by lfrp82.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/repo_en_5.5.1_3.0_1738110487879.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/repo_en_5.5.1_3.0_1738110487879.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("repo","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("repo", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|repo|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/lfrp82/repo
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-repo_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-repo_pipeline_en.md
new file mode 100644
index 00000000000000..4c0b6d24d8204c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-repo_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English repo_pipeline pipeline DistilBertForSequenceClassification from lfrp82
+author: John Snow Labs
+name: repo_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`repo_pipeline` is a English model originally trained by lfrp82.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/repo_pipeline_en_5.5.1_3.0_1738110503109.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/repo_pipeline_en_5.5.1_3.0_1738110503109.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("repo_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("repo_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|repo_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/lfrp82/repo
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-results_armandoicg_en.md b/docs/_posts/ahmedlone127/2025-01-29-results_armandoicg_en.md
new file mode 100644
index 00000000000000..2768cc007c4da8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-results_armandoicg_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English results_armandoicg DistilBertForSequenceClassification from ArmandoICG
+author: John Snow Labs
+name: results_armandoicg
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_armandoicg` is a English model originally trained by ArmandoICG.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_armandoicg_en_5.5.1_3.0_1738131804198.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_armandoicg_en_5.5.1_3.0_1738131804198.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("results_armandoicg","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("results_armandoicg", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_armandoicg|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/ArmandoICG/results
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-results_armandoicg_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-results_armandoicg_pipeline_en.md
new file mode 100644
index 00000000000000..cc11008f167799
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-results_armandoicg_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English results_armandoicg_pipeline pipeline DistilBertForSequenceClassification from ArmandoICG
+author: John Snow Labs
+name: results_armandoicg_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_armandoicg_pipeline` is a English model originally trained by ArmandoICG.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_armandoicg_pipeline_en_5.5.1_3.0_1738131817087.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_armandoicg_pipeline_en_5.5.1_3.0_1738131817087.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("results_armandoicg_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("results_armandoicg_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_armandoicg_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/ArmandoICG/results
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-results_luasmontesinos_en.md b/docs/_posts/ahmedlone127/2025-01-29-results_luasmontesinos_en.md
new file mode 100644
index 00000000000000..2d670c87e8fcdd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-results_luasmontesinos_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English results_luasmontesinos BertForTokenClassification from Luasmontesinos
+author: John Snow Labs
+name: results_luasmontesinos
+date: 2025-01-29
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_luasmontesinos` is a English model originally trained by Luasmontesinos.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_luasmontesinos_en_5.5.1_3.0_1738112819151.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_luasmontesinos_en_5.5.1_3.0_1738112819151.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("results_luasmontesinos","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("results_luasmontesinos", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_luasmontesinos|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/Luasmontesinos/results
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-results_luasmontesinos_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-results_luasmontesinos_pipeline_en.md
new file mode 100644
index 00000000000000..d58fbfdc58e17f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-results_luasmontesinos_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English results_luasmontesinos_pipeline pipeline BertForTokenClassification from Luasmontesinos
+author: John Snow Labs
+name: results_luasmontesinos_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_luasmontesinos_pipeline` is a English model originally trained by Luasmontesinos.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_luasmontesinos_pipeline_en_5.5.1_3.0_1738112839493.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_luasmontesinos_pipeline_en_5.5.1_3.0_1738112839493.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("results_luasmontesinos_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("results_luasmontesinos_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_luasmontesinos_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/Luasmontesinos/results
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-results_tarekziade_en.md b/docs/_posts/ahmedlone127/2025-01-29-results_tarekziade_en.md
new file mode 100644
index 00000000000000..ad380a5fbee13b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-results_tarekziade_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English results_tarekziade DistilBertForSequenceClassification from tarekziade
+author: John Snow Labs
+name: results_tarekziade
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_tarekziade` is a English model originally trained by tarekziade.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_tarekziade_en_5.5.1_3.0_1738131782934.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_tarekziade_en_5.5.1_3.0_1738131782934.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("results_tarekziade","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("results_tarekziade", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_tarekziade|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/tarekziade/results
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-results_tarekziade_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-results_tarekziade_pipeline_en.md
new file mode 100644
index 00000000000000..96e29eaa42878c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-results_tarekziade_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English results_tarekziade_pipeline pipeline DistilBertForSequenceClassification from tarekziade
+author: John Snow Labs
+name: results_tarekziade_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_tarekziade_pipeline` is a English model originally trained by tarekziade.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_tarekziade_pipeline_en_5.5.1_3.0_1738131796747.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_tarekziade_pipeline_en_5.5.1_3.0_1738131796747.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("results_tarekziade_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("results_tarekziade_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_tarekziade_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/tarekziade/results
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-roberta_empai_definitivo_en.md b/docs/_posts/ahmedlone127/2025-01-29-roberta_empai_definitivo_en.md
new file mode 100644
index 00000000000000..6b153790cf2579
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-roberta_empai_definitivo_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_empai_definitivo RoBertaEmbeddings from LuangMV97
+author: John Snow Labs
+name: roberta_empai_definitivo
+date: 2025-01-29
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_empai_definitivo` is a English model originally trained by LuangMV97.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_empai_definitivo_en_5.5.1_3.0_1738135026477.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_empai_definitivo_en_5.5.1_3.0_1738135026477.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("roberta_empai_definitivo","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("roberta_empai_definitivo","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_empai_definitivo|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|466.3 MB|
+
+## References
+
+https://huggingface.co/LuangMV97/RoBERTa_EmpAI_Definitivo
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-roberta_empai_definitivo_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-roberta_empai_definitivo_pipeline_en.md
new file mode 100644
index 00000000000000..f8beb67836258d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-roberta_empai_definitivo_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_empai_definitivo_pipeline pipeline RoBertaEmbeddings from LuangMV97
+author: John Snow Labs
+name: roberta_empai_definitivo_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_empai_definitivo_pipeline` is a English model originally trained by LuangMV97.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_empai_definitivo_pipeline_en_5.5.1_3.0_1738135050304.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_empai_definitivo_pipeline_en_5.5.1_3.0_1738135050304.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_empai_definitivo_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_empai_definitivo_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_empai_definitivo_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.3 MB|
+
+## References
+
+https://huggingface.co/LuangMV97/RoBERTa_EmpAI_Definitivo
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-roberta_empai_finetuned_en.md b/docs/_posts/ahmedlone127/2025-01-29-roberta_empai_finetuned_en.md
new file mode 100644
index 00000000000000..01bf022f6349e2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-roberta_empai_finetuned_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_empai_finetuned RoBertaEmbeddings from LuangMV97
+author: John Snow Labs
+name: roberta_empai_finetuned
+date: 2025-01-29
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_empai_finetuned` is a English model originally trained by LuangMV97.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_empai_finetuned_en_5.5.1_3.0_1738135058807.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_empai_finetuned_en_5.5.1_3.0_1738135058807.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("roberta_empai_finetuned","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("roberta_empai_finetuned","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_empai_finetuned|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|466.4 MB|
+
+## References
+
+https://huggingface.co/LuangMV97/RoBERTa_EmpAI_FineTuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-roberta_empai_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-roberta_empai_finetuned_pipeline_en.md
new file mode 100644
index 00000000000000..67d3f84fc13c5a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-roberta_empai_finetuned_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_empai_finetuned_pipeline pipeline RoBertaEmbeddings from LuangMV97
+author: John Snow Labs
+name: roberta_empai_finetuned_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_empai_finetuned_pipeline` is a English model originally trained by LuangMV97.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_empai_finetuned_pipeline_en_5.5.1_3.0_1738135082016.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_empai_finetuned_pipeline_en_5.5.1_3.0_1738135082016.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_empai_finetuned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_empai_finetuned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_empai_finetuned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.4 MB|
+
+## References
+
+https://huggingface.co/LuangMV97/RoBERTa_EmpAI_FineTuned
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-roberta_ganda_cased_malay_ner_v3_full_en.md b/docs/_posts/ahmedlone127/2025-01-29-roberta_ganda_cased_malay_ner_v3_full_en.md
new file mode 100644
index 00000000000000..05aa8b2f02f4bd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-roberta_ganda_cased_malay_ner_v3_full_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_ganda_cased_malay_ner_v3_full RoBertaForTokenClassification from nxaliao
+author: John Snow Labs
+name: roberta_ganda_cased_malay_ner_v3_full
+date: 2025-01-29
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_ganda_cased_malay_ner_v3_full` is a English model originally trained by nxaliao.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_ganda_cased_malay_ner_v3_full_en_5.5.1_3.0_1738116831242.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_ganda_cased_malay_ner_v3_full_en_5.5.1_3.0_1738116831242.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("roberta_ganda_cased_malay_ner_v3_full","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_ganda_cased_malay_ner_v3_full", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_ganda_cased_malay_ner_v3_full|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/nxaliao/roberta-lg-cased-ms-ner-v3-full
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-roberta_ganda_cased_malay_ner_v3_full_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-roberta_ganda_cased_malay_ner_v3_full_pipeline_en.md
new file mode 100644
index 00000000000000..c01072456d9c73
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-roberta_ganda_cased_malay_ner_v3_full_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_ganda_cased_malay_ner_v3_full_pipeline pipeline RoBertaForTokenClassification from nxaliao
+author: John Snow Labs
+name: roberta_ganda_cased_malay_ner_v3_full_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_ganda_cased_malay_ner_v3_full_pipeline` is a English model originally trained by nxaliao.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_ganda_cased_malay_ner_v3_full_pipeline_en_5.5.1_3.0_1738116905525.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_ganda_cased_malay_ner_v3_full_pipeline_en_5.5.1_3.0_1738116905525.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_ganda_cased_malay_ner_v3_full_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_ganda_cased_malay_ner_v3_full_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_ganda_cased_malay_ner_v3_full_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/nxaliao/roberta-lg-cased-ms-ner-v3-full
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-roberta_tagalog_base_ft_udpos213_english_pipeline_tl.md b/docs/_posts/ahmedlone127/2025-01-29-roberta_tagalog_base_ft_udpos213_english_pipeline_tl.md
new file mode 100644
index 00000000000000..47c05ee04d3398
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-roberta_tagalog_base_ft_udpos213_english_pipeline_tl.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Tagalog roberta_tagalog_base_ft_udpos213_english_pipeline pipeline RoBertaForTokenClassification from iceman2434
+author: John Snow Labs
+name: roberta_tagalog_base_ft_udpos213_english_pipeline
+date: 2025-01-29
+tags: [tl, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: tl
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_tagalog_base_ft_udpos213_english_pipeline` is a Tagalog model originally trained by iceman2434.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_tagalog_base_ft_udpos213_english_pipeline_tl_5.5.1_3.0_1738117382426.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_tagalog_base_ft_udpos213_english_pipeline_tl_5.5.1_3.0_1738117382426.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("roberta_tagalog_base_ft_udpos213_english_pipeline", lang = "tl")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_tagalog_base_ft_udpos213_english_pipeline", lang = "tl")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_tagalog_base_ft_udpos213_english_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|tl|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/iceman2434/roberta-tagalog-base-ft-udpos213-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-roberta_tagalog_base_ft_udpos213_english_tl.md b/docs/_posts/ahmedlone127/2025-01-29-roberta_tagalog_base_ft_udpos213_english_tl.md
new file mode 100644
index 00000000000000..3eefd7a09788ea
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-roberta_tagalog_base_ft_udpos213_english_tl.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Tagalog roberta_tagalog_base_ft_udpos213_english RoBertaForTokenClassification from iceman2434
+author: John Snow Labs
+name: roberta_tagalog_base_ft_udpos213_english
+date: 2025-01-29
+tags: [tl, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: tl
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_tagalog_base_ft_udpos213_english` is a Tagalog model originally trained by iceman2434.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_tagalog_base_ft_udpos213_english_tl_5.5.1_3.0_1738117362033.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_tagalog_base_ft_udpos213_english_tl_5.5.1_3.0_1738117362033.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("roberta_tagalog_base_ft_udpos213_english","tl") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_tagalog_base_ft_udpos213_english", "tl")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_tagalog_base_ft_udpos213_english|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|tl|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/iceman2434/roberta-tagalog-base-ft-udpos213-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-scenario_tcr_4_data_cl_cardiff_eng_only_en.md b/docs/_posts/ahmedlone127/2025-01-29-scenario_tcr_4_data_cl_cardiff_eng_only_en.md
new file mode 100644
index 00000000000000..88de50896e6f2d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-scenario_tcr_4_data_cl_cardiff_eng_only_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English scenario_tcr_4_data_cl_cardiff_eng_only XlmRoBertaForSequenceClassification from haryoaw
+author: John Snow Labs
+name: scenario_tcr_4_data_cl_cardiff_eng_only
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scenario_tcr_4_data_cl_cardiff_eng_only` is a English model originally trained by haryoaw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/scenario_tcr_4_data_cl_cardiff_eng_only_en_5.5.1_3.0_1738126168023.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scenario_tcr_4_data_cl_cardiff_eng_only_en_5.5.1_3.0_1738126168023.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("scenario_tcr_4_data_cl_cardiff_eng_only","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("scenario_tcr_4_data_cl_cardiff_eng_only", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|scenario_tcr_4_data_cl_cardiff_eng_only|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|836.5 MB|
+
+## References
+
+https://huggingface.co/haryoaw/scenario-TCR-4_data-cl-cardiff_eng_only
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-scenario_tcr_4_data_cl_cardiff_eng_only_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-scenario_tcr_4_data_cl_cardiff_eng_only_pipeline_en.md
new file mode 100644
index 00000000000000..52c360482ce6c6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-scenario_tcr_4_data_cl_cardiff_eng_only_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English scenario_tcr_4_data_cl_cardiff_eng_only_pipeline pipeline XlmRoBertaForSequenceClassification from haryoaw
+author: John Snow Labs
+name: scenario_tcr_4_data_cl_cardiff_eng_only_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scenario_tcr_4_data_cl_cardiff_eng_only_pipeline` is a English model originally trained by haryoaw.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/scenario_tcr_4_data_cl_cardiff_eng_only_pipeline_en_5.5.1_3.0_1738126279308.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scenario_tcr_4_data_cl_cardiff_eng_only_pipeline_en_5.5.1_3.0_1738126279308.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("scenario_tcr_4_data_cl_cardiff_eng_only_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("scenario_tcr_4_data_cl_cardiff_eng_only_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|scenario_tcr_4_data_cl_cardiff_eng_only_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|836.5 MB|
+
+## References
+
+https://huggingface.co/haryoaw/scenario-TCR-4_data-cl-cardiff_eng_only
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-secretmodel_en.md b/docs/_posts/ahmedlone127/2025-01-29-secretmodel_en.md
new file mode 100644
index 00000000000000..7654660a6f157b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-secretmodel_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English secretmodel DistilBertForSequenceClassification from NhatPham
+author: John Snow Labs
+name: secretmodel
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`secretmodel` is a English model originally trained by NhatPham.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/secretmodel_en_5.5.1_3.0_1738110299748.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/secretmodel_en_5.5.1_3.0_1738110299748.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("secretmodel","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("secretmodel", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|secretmodel|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/NhatPham/secretModel
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-secretmodel_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-secretmodel_pipeline_en.md
new file mode 100644
index 00000000000000..a51eedc31c816e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-secretmodel_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English secretmodel_pipeline pipeline DistilBertForSequenceClassification from NhatPham
+author: John Snow Labs
+name: secretmodel_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`secretmodel_pipeline` is a English model originally trained by NhatPham.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/secretmodel_pipeline_en_5.5.1_3.0_1738110312662.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/secretmodel_pipeline_en_5.5.1_3.0_1738110312662.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("secretmodel_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("secretmodel_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|secretmodel_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/NhatPham/secretModel
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-sent_13_epoch_edu_model_finetuned_fintech_en.md b/docs/_posts/ahmedlone127/2025-01-29-sent_13_epoch_edu_model_finetuned_fintech_en.md
new file mode 100644
index 00000000000000..e600789cecf7c9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-sent_13_epoch_edu_model_finetuned_fintech_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_13_epoch_edu_model_finetuned_fintech BertSentenceEmbeddings from Pastushoc
+author: John Snow Labs
+name: sent_13_epoch_edu_model_finetuned_fintech
+date: 2025-01-29
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_13_epoch_edu_model_finetuned_fintech` is a English model originally trained by Pastushoc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_13_epoch_edu_model_finetuned_fintech_en_5.5.1_3.0_1738132648551.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_13_epoch_edu_model_finetuned_fintech_en_5.5.1_3.0_1738132648551.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_13_epoch_edu_model_finetuned_fintech","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_13_epoch_edu_model_finetuned_fintech","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_13_epoch_edu_model_finetuned_fintech|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|108.7 MB|
+
+## References
+
+https://huggingface.co/Pastushoc/13_epoch_edu_model-finetuned-fintech
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-sent_13_epoch_edu_model_finetuned_fintech_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-sent_13_epoch_edu_model_finetuned_fintech_pipeline_en.md
new file mode 100644
index 00000000000000..d615b607a2a1c9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-sent_13_epoch_edu_model_finetuned_fintech_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_13_epoch_edu_model_finetuned_fintech_pipeline pipeline BertSentenceEmbeddings from Pastushoc
+author: John Snow Labs
+name: sent_13_epoch_edu_model_finetuned_fintech_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_13_epoch_edu_model_finetuned_fintech_pipeline` is a English model originally trained by Pastushoc.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_13_epoch_edu_model_finetuned_fintech_pipeline_en_5.5.1_3.0_1738132654041.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_13_epoch_edu_model_finetuned_fintech_pipeline_en_5.5.1_3.0_1738132654041.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_13_epoch_edu_model_finetuned_fintech_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_13_epoch_edu_model_finetuned_fintech_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_13_epoch_edu_model_finetuned_fintech_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|109.2 MB|
+
+## References
+
+https://huggingface.co/Pastushoc/13_epoch_edu_model-finetuned-fintech
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-sent_all_minilm_l6_v2_personal_project_default_2024_05_31_en.md b/docs/_posts/ahmedlone127/2025-01-29-sent_all_minilm_l6_v2_personal_project_default_2024_05_31_en.md
new file mode 100644
index 00000000000000..ccc897ed480c82
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-sent_all_minilm_l6_v2_personal_project_default_2024_05_31_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_all_minilm_l6_v2_personal_project_default_2024_05_31 BertSentenceEmbeddings from brugmark
+author: John Snow Labs
+name: sent_all_minilm_l6_v2_personal_project_default_2024_05_31
+date: 2025-01-29
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_all_minilm_l6_v2_personal_project_default_2024_05_31` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_default_2024_05_31_en_5.5.1_3.0_1738132473812.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_default_2024_05_31_en_5.5.1_3.0_1738132473812.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_all_minilm_l6_v2_personal_project_default_2024_05_31","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_all_minilm_l6_v2_personal_project_default_2024_05_31","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_all_minilm_l6_v2_personal_project_default_2024_05_31|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|83.9 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-default-2024-05-31
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-sent_all_minilm_l6_v2_personal_project_default_2024_05_31_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-sent_all_minilm_l6_v2_personal_project_default_2024_05_31_pipeline_en.md
new file mode 100644
index 00000000000000..0c81dbf12ef4d5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-sent_all_minilm_l6_v2_personal_project_default_2024_05_31_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_all_minilm_l6_v2_personal_project_default_2024_05_31_pipeline pipeline BertSentenceEmbeddings from brugmark
+author: John Snow Labs
+name: sent_all_minilm_l6_v2_personal_project_default_2024_05_31_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_all_minilm_l6_v2_personal_project_default_2024_05_31_pipeline` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_default_2024_05_31_pipeline_en_5.5.1_3.0_1738132478164.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_default_2024_05_31_pipeline_en_5.5.1_3.0_1738132478164.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_all_minilm_l6_v2_personal_project_default_2024_05_31_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_all_minilm_l6_v2_personal_project_default_2024_05_31_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_all_minilm_l6_v2_personal_project_default_2024_05_31_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|84.5 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-default-2024-05-31
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_14_en.md b/docs/_posts/ahmedlone127/2025-01-29-sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_14_en.md
new file mode 100644
index 00000000000000..f94be0310fd6a0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_14_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_14 BertSentenceEmbeddings from brugmark
+author: John Snow Labs
+name: sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_14
+date: 2025-01-29
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_14` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_14_en_5.5.1_3.0_1738132460657.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_14_en_5.5.1_3.0_1738132460657.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_14","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_14","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_14|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|84.6 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-finetuned-2024-06-14
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_14_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_14_pipeline_en.md
new file mode 100644
index 00000000000000..e7962f37fccf3c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_14_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_14_pipeline pipeline BertSentenceEmbeddings from brugmark
+author: John Snow Labs
+name: sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_14_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_14_pipeline` is a English model originally trained by brugmark.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_14_pipeline_en_5.5.1_3.0_1738132465186.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_14_pipeline_en_5.5.1_3.0_1738132465186.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_14_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_14_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_all_minilm_l6_v2_personal_project_finetuned_2024_06_14_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|85.2 MB|
+
+## References
+
+https://huggingface.co/brugmark/all-MiniLM-L6-v2-personal-project-finetuned-2024-06-14
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-sent_bert_base_cased_marasaki_en.md b/docs/_posts/ahmedlone127/2025-01-29-sent_bert_base_cased_marasaki_en.md
new file mode 100644
index 00000000000000..4c7c54ad343f65
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-sent_bert_base_cased_marasaki_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_base_cased_marasaki BertSentenceEmbeddings from marasaki
+author: John Snow Labs
+name: sent_bert_base_cased_marasaki
+date: 2025-01-29
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_cased_marasaki` is a English model originally trained by marasaki.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_cased_marasaki_en_5.5.1_3.0_1738132570996.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_cased_marasaki_en_5.5.1_3.0_1738132570996.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_cased_marasaki","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_cased_marasaki","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_cased_marasaki|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/marasaki/bert_base_cased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-sent_bert_base_cased_marasaki_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-sent_bert_base_cased_marasaki_pipeline_en.md
new file mode 100644
index 00000000000000..96022564175b88
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-sent_bert_base_cased_marasaki_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_base_cased_marasaki_pipeline pipeline BertSentenceEmbeddings from marasaki
+author: John Snow Labs
+name: sent_bert_base_cased_marasaki_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_cased_marasaki_pipeline` is a English model originally trained by marasaki.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_cased_marasaki_pipeline_en_5.5.1_3.0_1738132591753.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_cased_marasaki_pipeline_en_5.5.1_3.0_1738132591753.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_base_cased_marasaki_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_cased_marasaki_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_cased_marasaki_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|404.2 MB|
+
+## References
+
+https://huggingface.co/marasaki/bert_base_cased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-sent_bert_small_finetuned_legal_definitions_longer_en.md b/docs/_posts/ahmedlone127/2025-01-29-sent_bert_small_finetuned_legal_definitions_longer_en.md
new file mode 100644
index 00000000000000..3e65a350856f54
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-sent_bert_small_finetuned_legal_definitions_longer_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_small_finetuned_legal_definitions_longer BertSentenceEmbeddings from muhtasham
+author: John Snow Labs
+name: sent_bert_small_finetuned_legal_definitions_longer
+date: 2025-01-29
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_small_finetuned_legal_definitions_longer` is a English model originally trained by muhtasham.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_small_finetuned_legal_definitions_longer_en_5.5.1_3.0_1738133188236.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_small_finetuned_legal_definitions_longer_en_5.5.1_3.0_1738133188236.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_small_finetuned_legal_definitions_longer","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_small_finetuned_legal_definitions_longer","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_small_finetuned_legal_definitions_longer|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|107.0 MB|
+
+## References
+
+https://huggingface.co/muhtasham/bert-small-finetuned-legal-definitions-longer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-sent_bert_small_finetuned_legal_definitions_longer_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-sent_bert_small_finetuned_legal_definitions_longer_pipeline_en.md
new file mode 100644
index 00000000000000..6d164d9847540d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-sent_bert_small_finetuned_legal_definitions_longer_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_small_finetuned_legal_definitions_longer_pipeline pipeline BertSentenceEmbeddings from muhtasham
+author: John Snow Labs
+name: sent_bert_small_finetuned_legal_definitions_longer_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_small_finetuned_legal_definitions_longer_pipeline` is a English model originally trained by muhtasham.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_small_finetuned_legal_definitions_longer_pipeline_en_5.5.1_3.0_1738133193717.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_small_finetuned_legal_definitions_longer_pipeline_en_5.5.1_3.0_1738133193717.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_bert_small_finetuned_legal_definitions_longer_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_small_finetuned_legal_definitions_longer_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_small_finetuned_legal_definitions_longer_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|107.5 MB|
+
+## References
+
+https://huggingface.co/muhtasham/bert-small-finetuned-legal-definitions-longer
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-sent_dummy_model2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-sent_dummy_model2_pipeline_en.md
new file mode 100644
index 00000000000000..9f36a4198048ba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-sent_dummy_model2_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_dummy_model2_pipeline pipeline BertSentenceEmbeddings from MindNetML
+author: John Snow Labs
+name: sent_dummy_model2_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_dummy_model2_pipeline` is a English model originally trained by MindNetML.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_dummy_model2_pipeline_en_5.5.1_3.0_1738132800497.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_dummy_model2_pipeline_en_5.5.1_3.0_1738132800497.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_dummy_model2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_dummy_model2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_dummy_model2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|404.2 MB|
+
+## References
+
+https://huggingface.co/MindNetML/dummy-model2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-sent_hubertmlm_en.md b/docs/_posts/ahmedlone127/2025-01-29-sent_hubertmlm_en.md
new file mode 100644
index 00000000000000..bcaf53d1de911e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-sent_hubertmlm_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_hubertmlm BertSentenceEmbeddings from SzegedAI
+author: John Snow Labs
+name: sent_hubertmlm
+date: 2025-01-29
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_hubertmlm` is a English model originally trained by SzegedAI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_hubertmlm_en_5.5.1_3.0_1738132433810.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_hubertmlm_en_5.5.1_3.0_1738132433810.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_hubertmlm","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_hubertmlm","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_hubertmlm|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|412.4 MB|
+
+## References
+
+https://huggingface.co/SzegedAI/HuBERTmlm
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-sent_hubertmlm_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-sent_hubertmlm_pipeline_en.md
new file mode 100644
index 00000000000000..f4f729ee767ffe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-sent_hubertmlm_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_hubertmlm_pipeline pipeline BertSentenceEmbeddings from SzegedAI
+author: John Snow Labs
+name: sent_hubertmlm_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_hubertmlm_pipeline` is a English model originally trained by SzegedAI.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_hubertmlm_pipeline_en_5.5.1_3.0_1738132455102.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_hubertmlm_pipeline_en_5.5.1_3.0_1738132455102.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_hubertmlm_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_hubertmlm_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_hubertmlm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|413.0 MB|
+
+## References
+
+https://huggingface.co/SzegedAI/HuBERTmlm
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-sent_magnesiumbert_en.md b/docs/_posts/ahmedlone127/2025-01-29-sent_magnesiumbert_en.md
new file mode 100644
index 00000000000000..e35b48a428bcdc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-sent_magnesiumbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_magnesiumbert BertSentenceEmbeddings from MADD123
+author: John Snow Labs
+name: sent_magnesiumbert
+date: 2025-01-29
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_magnesiumbert` is a English model originally trained by MADD123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_magnesiumbert_en_5.5.1_3.0_1738132460480.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_magnesiumbert_en_5.5.1_3.0_1738132460480.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_magnesiumbert","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_magnesiumbert","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_magnesiumbert|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|409.9 MB|
+
+## References
+
+https://huggingface.co/MADD123/MagnesiumBERT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-sent_magnesiumbert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-sent_magnesiumbert_pipeline_en.md
new file mode 100644
index 00000000000000..ed7cf6d4ff54af
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-sent_magnesiumbert_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_magnesiumbert_pipeline pipeline BertSentenceEmbeddings from MADD123
+author: John Snow Labs
+name: sent_magnesiumbert_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_magnesiumbert_pipeline` is a English model originally trained by MADD123.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_magnesiumbert_pipeline_en_5.5.1_3.0_1738132483000.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_magnesiumbert_pipeline_en_5.5.1_3.0_1738132483000.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_magnesiumbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_magnesiumbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_magnesiumbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.5 MB|
+
+## References
+
+https://huggingface.co/MADD123/MagnesiumBERT
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-sent_med_model_1_en.md b/docs/_posts/ahmedlone127/2025-01-29-sent_med_model_1_en.md
new file mode 100644
index 00000000000000..78b8e578328d4d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-sent_med_model_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_med_model_1 BertSentenceEmbeddings from kumarme072
+author: John Snow Labs
+name: sent_med_model_1
+date: 2025-01-29
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_med_model_1` is a English model originally trained by kumarme072.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_med_model_1_en_5.5.1_3.0_1738133183100.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_med_model_1_en_5.5.1_3.0_1738133183100.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_med_model_1","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_med_model_1","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_med_model_1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|486.3 MB|
+
+## References
+
+https://huggingface.co/kumarme072/med_model_1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-sent_med_model_1_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-sent_med_model_1_pipeline_en.md
new file mode 100644
index 00000000000000..5d793e4f94ae41
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-sent_med_model_1_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_med_model_1_pipeline pipeline BertSentenceEmbeddings from kumarme072
+author: John Snow Labs
+name: sent_med_model_1_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_med_model_1_pipeline` is a English model originally trained by kumarme072.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_med_model_1_pipeline_en_5.5.1_3.0_1738133211402.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_med_model_1_pipeline_en_5.5.1_3.0_1738133211402.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sent_med_model_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_med_model_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_med_model_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|486.8 MB|
+
+## References
+
+https://huggingface.co/kumarme072/med_model_1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-sentimientos_bullrich_es.md b/docs/_posts/ahmedlone127/2025-01-29-sentimientos_bullrich_es.md
new file mode 100644
index 00000000000000..9fbaf46fb05b36
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-sentimientos_bullrich_es.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Castilian, Spanish sentimientos_bullrich XlmRoBertaForSequenceClassification from natmarinn
+author: John Snow Labs
+name: sentimientos_bullrich
+date: 2025-01-29
+tags: [es, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: es
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentimientos_bullrich` is a Castilian, Spanish model originally trained by natmarinn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentimientos_bullrich_es_5.5.1_3.0_1738126947739.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentimientos_bullrich_es_5.5.1_3.0_1738126947739.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("sentimientos_bullrich","es") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("sentimientos_bullrich", "es")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sentimientos_bullrich|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|es|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/natmarinn/sentimientos-bullrich
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-sentimientos_bullrich_pipeline_es.md b/docs/_posts/ahmedlone127/2025-01-29-sentimientos_bullrich_pipeline_es.md
new file mode 100644
index 00000000000000..47157619d79e88
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-sentimientos_bullrich_pipeline_es.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Castilian, Spanish sentimientos_bullrich_pipeline pipeline XlmRoBertaForSequenceClassification from natmarinn
+author: John Snow Labs
+name: sentimientos_bullrich_pipeline
+date: 2025-01-29
+tags: [es, open_source, pipeline, onnx]
+task: Text Classification
+language: es
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentimientos_bullrich_pipeline` is a Castilian, Spanish model originally trained by natmarinn.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentimientos_bullrich_pipeline_es_5.5.1_3.0_1738126999323.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentimientos_bullrich_pipeline_es_5.5.1_3.0_1738126999323.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("sentimientos_bullrich_pipeline", lang = "es")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sentimientos_bullrich_pipeline", lang = "es")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sentimientos_bullrich_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|es|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/natmarinn/sentimientos-bullrich
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-smart_finetuned_ner_en.md b/docs/_posts/ahmedlone127/2025-01-29-smart_finetuned_ner_en.md
new file mode 100644
index 00000000000000..2dd2d801dffa7d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-smart_finetuned_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English smart_finetuned_ner DistilBertForSequenceClassification from Beehzod
+author: John Snow Labs
+name: smart_finetuned_ner
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`smart_finetuned_ner` is a English model originally trained by Beehzod.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/smart_finetuned_ner_en_5.5.1_3.0_1738131675755.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/smart_finetuned_ner_en_5.5.1_3.0_1738131675755.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("smart_finetuned_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("smart_finetuned_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|smart_finetuned_ner|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|246.0 MB|
+
+## References
+
+https://huggingface.co/Beehzod/smart-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-smart_finetuned_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-smart_finetuned_ner_pipeline_en.md
new file mode 100644
index 00000000000000..bc5cc4640a5346
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-smart_finetuned_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English smart_finetuned_ner_pipeline pipeline DistilBertForSequenceClassification from Beehzod
+author: John Snow Labs
+name: smart_finetuned_ner_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`smart_finetuned_ner_pipeline` is a English model originally trained by Beehzod.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/smart_finetuned_ner_pipeline_en_5.5.1_3.0_1738131689085.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/smart_finetuned_ner_pipeline_en_5.5.1_3.0_1738131689085.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("smart_finetuned_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("smart_finetuned_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|smart_finetuned_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|246.0 MB|
+
+## References
+
+https://huggingface.co/Beehzod/smart-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-smartbert_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-smartbert_pipeline_en.md
new file mode 100644
index 00000000000000..9fd7e05419573a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-smartbert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English smartbert_pipeline pipeline RoBertaEmbeddings from web3se
+author: John Snow Labs
+name: smartbert_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`smartbert_pipeline` is a English model originally trained by web3se.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/smartbert_pipeline_en_5.5.1_3.0_1738134786553.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/smartbert_pipeline_en_5.5.1_3.0_1738134786553.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("smartbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("smartbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|smartbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.0 MB|
+
+## References
+
+https://huggingface.co/web3se/SmartBERT
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-t5_small_finetuned_heart_failure_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-t5_small_finetuned_heart_failure_pipeline_en.md
new file mode 100644
index 00000000000000..6d42aeb7a8eb45
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-t5_small_finetuned_heart_failure_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_small_finetuned_heart_failure_pipeline pipeline T5Transformer from raflyr2024
+author: John Snow Labs
+name: t5_small_finetuned_heart_failure_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_finetuned_heart_failure_pipeline` is a English model originally trained by raflyr2024.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_finetuned_heart_failure_pipeline_en_5.5.1_3.0_1738136752596.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_finetuned_heart_failure_pipeline_en_5.5.1_3.0_1738136752596.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_small_finetuned_heart_failure_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_small_finetuned_heart_failure_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_finetuned_heart_failure_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|233.4 MB|
+
+## References
+
+https://huggingface.co/raflyr2024/t5-small-finetuned-heart-failure
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-t5_small_finetuned_question_tonga_tonga_islands_sql_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-t5_small_finetuned_question_tonga_tonga_islands_sql_pipeline_en.md
new file mode 100644
index 00000000000000..137f0fd33ef380
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-t5_small_finetuned_question_tonga_tonga_islands_sql_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English t5_small_finetuned_question_tonga_tonga_islands_sql_pipeline pipeline T5Transformer from Lexie1212
+author: John Snow Labs
+name: t5_small_finetuned_question_tonga_tonga_islands_sql_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t5_small_finetuned_question_tonga_tonga_islands_sql_pipeline` is a English model originally trained by Lexie1212.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/t5_small_finetuned_question_tonga_tonga_islands_sql_pipeline_en_5.5.1_3.0_1738136931365.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t5_small_finetuned_question_tonga_tonga_islands_sql_pipeline_en_5.5.1_3.0_1738136931365.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("t5_small_finetuned_question_tonga_tonga_islands_sql_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t5_small_finetuned_question_tonga_tonga_islands_sql_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t5_small_finetuned_question_tonga_tonga_islands_sql_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|272.0 MB|
+
+## References
+
+https://huggingface.co/Lexie1212/t5-small-finetuned-question-to-sql
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-tapas_kcbert_slerp2_en.md b/docs/_posts/ahmedlone127/2025-01-29-tapas_kcbert_slerp2_en.md
new file mode 100644
index 00000000000000..f14c5a7b8707ef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-tapas_kcbert_slerp2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English tapas_kcbert_slerp2 BertEmbeddings from H-du-kang
+author: John Snow Labs
+name: tapas_kcbert_slerp2
+date: 2025-01-29
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tapas_kcbert_slerp2` is a English model originally trained by H-du-kang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tapas_kcbert_slerp2_en_5.5.1_3.0_1738120185537.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tapas_kcbert_slerp2_en_5.5.1_3.0_1738120185537.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("tapas_kcbert_slerp2","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("tapas_kcbert_slerp2","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tapas_kcbert_slerp2|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|206.9 MB|
+
+## References
+
+https://huggingface.co/H-du-kang/TAPAS-KCBERT-slerp2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-tapas_kcbert_slerp2_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-tapas_kcbert_slerp2_pipeline_en.md
new file mode 100644
index 00000000000000..4b575182c71c17
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-tapas_kcbert_slerp2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English tapas_kcbert_slerp2_pipeline pipeline BertEmbeddings from H-du-kang
+author: John Snow Labs
+name: tapas_kcbert_slerp2_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tapas_kcbert_slerp2_pipeline` is a English model originally trained by H-du-kang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tapas_kcbert_slerp2_pipeline_en_5.5.1_3.0_1738120252274.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tapas_kcbert_slerp2_pipeline_en_5.5.1_3.0_1738120252274.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("tapas_kcbert_slerp2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("tapas_kcbert_slerp2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tapas_kcbert_slerp2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|206.9 MB|
+
+## References
+
+https://huggingface.co/H-du-kang/TAPAS-KCBERT-slerp2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-test_analysis_model_en.md b/docs/_posts/ahmedlone127/2025-01-29-test_analysis_model_en.md
new file mode 100644
index 00000000000000..37acc7f83ac2d2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-test_analysis_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English test_analysis_model DistilBertForSequenceClassification from FlickeringIRoam
+author: John Snow Labs
+name: test_analysis_model
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_analysis_model` is a English model originally trained by FlickeringIRoam.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_analysis_model_en_5.5.1_3.0_1738110618416.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_analysis_model_en_5.5.1_3.0_1738110618416.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("test_analysis_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("test_analysis_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_analysis_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/FlickeringIRoam/test-analysis-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-test_analysis_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-test_analysis_model_pipeline_en.md
new file mode 100644
index 00000000000000..cc6bb48bc349ee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-test_analysis_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English test_analysis_model_pipeline pipeline DistilBertForSequenceClassification from FlickeringIRoam
+author: John Snow Labs
+name: test_analysis_model_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_analysis_model_pipeline` is a English model originally trained by FlickeringIRoam.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_analysis_model_pipeline_en_5.5.1_3.0_1738110632991.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_analysis_model_pipeline_en_5.5.1_3.0_1738110632991.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("test_analysis_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("test_analysis_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_analysis_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/FlickeringIRoam/test-analysis-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-toxicbert_hatexplain_label_all_tokens_false_3epoch_en.md b/docs/_posts/ahmedlone127/2025-01-29-toxicbert_hatexplain_label_all_tokens_false_3epoch_en.md
new file mode 100644
index 00000000000000..614d3a203d67c0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-toxicbert_hatexplain_label_all_tokens_false_3epoch_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English toxicbert_hatexplain_label_all_tokens_false_3epoch BertForTokenClassification from troesy
+author: John Snow Labs
+name: toxicbert_hatexplain_label_all_tokens_false_3epoch
+date: 2025-01-29
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`toxicbert_hatexplain_label_all_tokens_false_3epoch` is a English model originally trained by troesy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/toxicbert_hatexplain_label_all_tokens_false_3epoch_en_5.5.1_3.0_1738112484328.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/toxicbert_hatexplain_label_all_tokens_false_3epoch_en_5.5.1_3.0_1738112484328.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("toxicbert_hatexplain_label_all_tokens_false_3epoch","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("toxicbert_hatexplain_label_all_tokens_false_3epoch", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|toxicbert_hatexplain_label_all_tokens_false_3epoch|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|409.9 MB|
+
+## References
+
+https://huggingface.co/troesy/toxicbert-hatexplain-label-all-tokens-False-3epoch
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-toxicbert_hatexplain_label_all_tokens_false_3epoch_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-toxicbert_hatexplain_label_all_tokens_false_3epoch_pipeline_en.md
new file mode 100644
index 00000000000000..aa7f6f8260f369
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-toxicbert_hatexplain_label_all_tokens_false_3epoch_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English toxicbert_hatexplain_label_all_tokens_false_3epoch_pipeline pipeline BertForTokenClassification from troesy
+author: John Snow Labs
+name: toxicbert_hatexplain_label_all_tokens_false_3epoch_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`toxicbert_hatexplain_label_all_tokens_false_3epoch_pipeline` is a English model originally trained by troesy.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/toxicbert_hatexplain_label_all_tokens_false_3epoch_pipeline_en_5.5.1_3.0_1738112508027.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/toxicbert_hatexplain_label_all_tokens_false_3epoch_pipeline_en_5.5.1_3.0_1738112508027.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("toxicbert_hatexplain_label_all_tokens_false_3epoch_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("toxicbert_hatexplain_label_all_tokens_false_3epoch_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|toxicbert_hatexplain_label_all_tokens_false_3epoch_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.0 MB|
+
+## References
+
+https://huggingface.co/troesy/toxicbert-hatexplain-label-all-tokens-False-3epoch
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-tune_bert_base_chinese_en.md b/docs/_posts/ahmedlone127/2025-01-29-tune_bert_base_chinese_en.md
new file mode 100644
index 00000000000000..8fe85dd78e26e7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-tune_bert_base_chinese_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English tune_bert_base_chinese BertForTokenClassification from jasonwenhuan
+author: John Snow Labs
+name: tune_bert_base_chinese
+date: 2025-01-29
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tune_bert_base_chinese` is a English model originally trained by jasonwenhuan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tune_bert_base_chinese_en_5.5.1_3.0_1738111667789.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tune_bert_base_chinese_en_5.5.1_3.0_1738111667789.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("tune_bert_base_chinese","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("tune_bert_base_chinese", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tune_bert_base_chinese|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|381.2 MB|
+
+## References
+
+https://huggingface.co/jasonwenhuan/tune-bert-base-chinese
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-tune_bert_base_chinese_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-tune_bert_base_chinese_pipeline_en.md
new file mode 100644
index 00000000000000..c59dbdda05b560
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-tune_bert_base_chinese_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English tune_bert_base_chinese_pipeline pipeline BertForTokenClassification from jasonwenhuan
+author: John Snow Labs
+name: tune_bert_base_chinese_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tune_bert_base_chinese_pipeline` is a English model originally trained by jasonwenhuan.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tune_bert_base_chinese_pipeline_en_5.5.1_3.0_1738111695435.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tune_bert_base_chinese_pipeline_en_5.5.1_3.0_1738111695435.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("tune_bert_base_chinese_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("tune_bert_base_chinese_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tune_bert_base_chinese_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|381.2 MB|
+
+## References
+
+https://huggingface.co/jasonwenhuan/tune-bert-base-chinese
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-tuned_model_en.md b/docs/_posts/ahmedlone127/2025-01-29-tuned_model_en.md
new file mode 100644
index 00000000000000..00b4a314e27807
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-tuned_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English tuned_model DistilBertForSequenceClassification from ghantaharsha
+author: John Snow Labs
+name: tuned_model
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tuned_model` is a English model originally trained by ghantaharsha.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tuned_model_en_5.5.1_3.0_1738131342247.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tuned_model_en_5.5.1_3.0_1738131342247.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("tuned_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("tuned_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tuned_model|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/ghantaharsha/tuned-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-tuned_model_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-tuned_model_pipeline_en.md
new file mode 100644
index 00000000000000..5deaa3f5b99271
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-tuned_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English tuned_model_pipeline pipeline DistilBertForSequenceClassification from ghantaharsha
+author: John Snow Labs
+name: tuned_model_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tuned_model_pipeline` is a English model originally trained by ghantaharsha.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tuned_model_pipeline_en_5.5.1_3.0_1738131355287.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tuned_model_pipeline_en_5.5.1_3.0_1738131355287.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("tuned_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("tuned_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tuned_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/ghantaharsha/tuned-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-twitter_roberta_base_jun2022_en.md b/docs/_posts/ahmedlone127/2025-01-29-twitter_roberta_base_jun2022_en.md
new file mode 100644
index 00000000000000..4d84ecc678181b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-twitter_roberta_base_jun2022_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English twitter_roberta_base_jun2022 RoBertaEmbeddings from cardiffnlp
+author: John Snow Labs
+name: twitter_roberta_base_jun2022
+date: 2025-01-29
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_roberta_base_jun2022` is a English model originally trained by cardiffnlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twitter_roberta_base_jun2022_en_5.5.1_3.0_1738134981197.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_roberta_base_jun2022_en_5.5.1_3.0_1738134981197.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("twitter_roberta_base_jun2022","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("twitter_roberta_base_jun2022","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|twitter_roberta_base_jun2022|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|466.1 MB|
+
+## References
+
+https://huggingface.co/cardiffnlp/twitter-roberta-base-jun2022
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-twitter_roberta_base_jun2022_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-twitter_roberta_base_jun2022_pipeline_en.md
new file mode 100644
index 00000000000000..3d8e42c535e7d3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-twitter_roberta_base_jun2022_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English twitter_roberta_base_jun2022_pipeline pipeline RoBertaEmbeddings from cardiffnlp
+author: John Snow Labs
+name: twitter_roberta_base_jun2022_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_roberta_base_jun2022_pipeline` is a English model originally trained by cardiffnlp.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twitter_roberta_base_jun2022_pipeline_en_5.5.1_3.0_1738135005264.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_roberta_base_jun2022_pipeline_en_5.5.1_3.0_1738135005264.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("twitter_roberta_base_jun2022_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("twitter_roberta_base_jun2022_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|twitter_roberta_base_jun2022_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.1 MB|
+
+## References
+
+https://huggingface.co/cardiffnlp/twitter-roberta-base-jun2022
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-twitter_xlm_roberta_base_sentiment_finetunned_huhu_local_en.md b/docs/_posts/ahmedlone127/2025-01-29-twitter_xlm_roberta_base_sentiment_finetunned_huhu_local_en.md
new file mode 100644
index 00000000000000..e2ce563ea31ed7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-twitter_xlm_roberta_base_sentiment_finetunned_huhu_local_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English twitter_xlm_roberta_base_sentiment_finetunned_huhu_local XlmRoBertaForSequenceClassification from csuazob
+author: John Snow Labs
+name: twitter_xlm_roberta_base_sentiment_finetunned_huhu_local
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_xlm_roberta_base_sentiment_finetunned_huhu_local` is a English model originally trained by csuazob.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twitter_xlm_roberta_base_sentiment_finetunned_huhu_local_en_5.5.1_3.0_1738125739377.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_xlm_roberta_base_sentiment_finetunned_huhu_local_en_5.5.1_3.0_1738125739377.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("twitter_xlm_roberta_base_sentiment_finetunned_huhu_local","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("twitter_xlm_roberta_base_sentiment_finetunned_huhu_local", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|twitter_xlm_roberta_base_sentiment_finetunned_huhu_local|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/csuazob/twitter-xlm-roberta-base-sentiment-finetunned-huhu-local
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-twitter_xlm_roberta_base_sentiment_finetunned_huhu_local_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-twitter_xlm_roberta_base_sentiment_finetunned_huhu_local_pipeline_en.md
new file mode 100644
index 00000000000000..cbac46cf46e582
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-twitter_xlm_roberta_base_sentiment_finetunned_huhu_local_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English twitter_xlm_roberta_base_sentiment_finetunned_huhu_local_pipeline pipeline XlmRoBertaForSequenceClassification from csuazob
+author: John Snow Labs
+name: twitter_xlm_roberta_base_sentiment_finetunned_huhu_local_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_xlm_roberta_base_sentiment_finetunned_huhu_local_pipeline` is a English model originally trained by csuazob.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twitter_xlm_roberta_base_sentiment_finetunned_huhu_local_pipeline_en_5.5.1_3.0_1738125791633.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_xlm_roberta_base_sentiment_finetunned_huhu_local_pipeline_en_5.5.1_3.0_1738125791633.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("twitter_xlm_roberta_base_sentiment_finetunned_huhu_local_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("twitter_xlm_roberta_base_sentiment_finetunned_huhu_local_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|twitter_xlm_roberta_base_sentiment_finetunned_huhu_local_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/csuazob/twitter-xlm-roberta-base-sentiment-finetunned-huhu-local
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-txsa_sentiment_distilbert_hpo_full_en.md b/docs/_posts/ahmedlone127/2025-01-29-txsa_sentiment_distilbert_hpo_full_en.md
new file mode 100644
index 00000000000000..06295b6cb21420
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-txsa_sentiment_distilbert_hpo_full_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English txsa_sentiment_distilbert_hpo_full DistilBertForSequenceClassification from JamesSpray
+author: John Snow Labs
+name: txsa_sentiment_distilbert_hpo_full
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`txsa_sentiment_distilbert_hpo_full` is a English model originally trained by JamesSpray.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/txsa_sentiment_distilbert_hpo_full_en_5.5.1_3.0_1738131476058.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/txsa_sentiment_distilbert_hpo_full_en_5.5.1_3.0_1738131476058.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("txsa_sentiment_distilbert_hpo_full","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("txsa_sentiment_distilbert_hpo_full", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|txsa_sentiment_distilbert_hpo_full|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/JamesSpray/txsa-sentiment-distilbert-HPO-full
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-txsa_sentiment_distilbert_hpo_full_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-txsa_sentiment_distilbert_hpo_full_pipeline_en.md
new file mode 100644
index 00000000000000..7c64bbcf25401d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-txsa_sentiment_distilbert_hpo_full_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English txsa_sentiment_distilbert_hpo_full_pipeline pipeline DistilBertForSequenceClassification from JamesSpray
+author: John Snow Labs
+name: txsa_sentiment_distilbert_hpo_full_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`txsa_sentiment_distilbert_hpo_full_pipeline` is a English model originally trained by JamesSpray.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/txsa_sentiment_distilbert_hpo_full_pipeline_en_5.5.1_3.0_1738131488987.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/txsa_sentiment_distilbert_hpo_full_pipeline_en_5.5.1_3.0_1738131488987.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("txsa_sentiment_distilbert_hpo_full_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("txsa_sentiment_distilbert_hpo_full_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|txsa_sentiment_distilbert_hpo_full_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/JamesSpray/txsa-sentiment-distilbert-HPO-full
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-va_german_en.md b/docs/_posts/ahmedlone127/2025-01-29-va_german_en.md
new file mode 100644
index 00000000000000..59e598e8facf82
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-va_german_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English va_german BertForTokenClassification from mschwab
+author: John Snow Labs
+name: va_german
+date: 2025-01-29
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`va_german` is a English model originally trained by mschwab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/va_german_en_5.5.1_3.0_1738112463190.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/va_german_en_5.5.1_3.0_1738112463190.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("va_german","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("va_german", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|va_german|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|409.9 MB|
+
+## References
+
+https://huggingface.co/mschwab/va_german
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-va_german_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-va_german_pipeline_en.md
new file mode 100644
index 00000000000000..0daf9ebdb57a03
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-va_german_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English va_german_pipeline pipeline BertForTokenClassification from mschwab
+author: John Snow Labs
+name: va_german_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`va_german_pipeline` is a English model originally trained by mschwab.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/va_german_pipeline_en_5.5.1_3.0_1738112483729.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/va_german_pipeline_en_5.5.1_3.0_1738112483729.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("va_german_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("va_german_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|va_german_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.9 MB|
+
+## References
+
+https://huggingface.co/mschwab/va_german
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-weak_ingredient_recognition_bert_base_cased_german_de.md b/docs/_posts/ahmedlone127/2025-01-29-weak_ingredient_recognition_bert_base_cased_german_de.md
new file mode 100644
index 00000000000000..e511507c152638
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-weak_ingredient_recognition_bert_base_cased_german_de.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: German weak_ingredient_recognition_bert_base_cased_german BertForTokenClassification from chefkoch24
+author: John Snow Labs
+name: weak_ingredient_recognition_bert_base_cased_german
+date: 2025-01-29
+tags: [de, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: de
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`weak_ingredient_recognition_bert_base_cased_german` is a German model originally trained by chefkoch24.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/weak_ingredient_recognition_bert_base_cased_german_de_5.5.1_3.0_1738112380346.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/weak_ingredient_recognition_bert_base_cased_german_de_5.5.1_3.0_1738112380346.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("weak_ingredient_recognition_bert_base_cased_german","de") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("weak_ingredient_recognition_bert_base_cased_german", "de")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|weak_ingredient_recognition_bert_base_cased_german|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|de|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/chefkoch24/weak-ingredient-recognition-bert-base-cased-german
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-weak_ingredient_recognition_bert_base_cased_german_pipeline_de.md b/docs/_posts/ahmedlone127/2025-01-29-weak_ingredient_recognition_bert_base_cased_german_pipeline_de.md
new file mode 100644
index 00000000000000..9a3ce81d495f36
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-weak_ingredient_recognition_bert_base_cased_german_pipeline_de.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: German weak_ingredient_recognition_bert_base_cased_german_pipeline pipeline BertForTokenClassification from chefkoch24
+author: John Snow Labs
+name: weak_ingredient_recognition_bert_base_cased_german_pipeline
+date: 2025-01-29
+tags: [de, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: de
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`weak_ingredient_recognition_bert_base_cased_german_pipeline` is a German model originally trained by chefkoch24.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/weak_ingredient_recognition_bert_base_cased_german_pipeline_de_5.5.1_3.0_1738112401997.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/weak_ingredient_recognition_bert_base_cased_german_pipeline_de_5.5.1_3.0_1738112401997.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("weak_ingredient_recognition_bert_base_cased_german_pipeline", lang = "de")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("weak_ingredient_recognition_bert_base_cased_german_pipeline", lang = "de")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|weak_ingredient_recognition_bert_base_cased_german_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|de|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/chefkoch24/weak-ingredient-recognition-bert-base-cased-german
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-withinapps_ndd_ppma_test_content_tags_en.md b/docs/_posts/ahmedlone127/2025-01-29-withinapps_ndd_ppma_test_content_tags_en.md
new file mode 100644
index 00000000000000..c3f8710ec4bac6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-withinapps_ndd_ppma_test_content_tags_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English withinapps_ndd_ppma_test_content_tags DistilBertForSequenceClassification from lgk03
+author: John Snow Labs
+name: withinapps_ndd_ppma_test_content_tags
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`withinapps_ndd_ppma_test_content_tags` is a English model originally trained by lgk03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/withinapps_ndd_ppma_test_content_tags_en_5.5.1_3.0_1738131694046.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/withinapps_ndd_ppma_test_content_tags_en_5.5.1_3.0_1738131694046.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("withinapps_ndd_ppma_test_content_tags","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("withinapps_ndd_ppma_test_content_tags", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|withinapps_ndd_ppma_test_content_tags|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/lgk03/WITHINAPPS_NDD-ppma_test-content_tags
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-withinapps_ndd_ppma_test_content_tags_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-withinapps_ndd_ppma_test_content_tags_pipeline_en.md
new file mode 100644
index 00000000000000..5b8fe2bd4ed788
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-withinapps_ndd_ppma_test_content_tags_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English withinapps_ndd_ppma_test_content_tags_pipeline pipeline DistilBertForSequenceClassification from lgk03
+author: John Snow Labs
+name: withinapps_ndd_ppma_test_content_tags_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`withinapps_ndd_ppma_test_content_tags_pipeline` is a English model originally trained by lgk03.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/withinapps_ndd_ppma_test_content_tags_pipeline_en_5.5.1_3.0_1738131706857.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/withinapps_ndd_ppma_test_content_tags_pipeline_en_5.5.1_3.0_1738131706857.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("withinapps_ndd_ppma_test_content_tags_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("withinapps_ndd_ppma_test_content_tags_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|withinapps_ndd_ppma_test_content_tags_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/lgk03/WITHINAPPS_NDD-ppma_test-content_tags
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-xlm_cita_en.md b/docs/_posts/ahmedlone127/2025-01-29-xlm_cita_en.md
new file mode 100644
index 00000000000000..599fab0a00e3f7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-xlm_cita_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_cita XlmRoBertaForSequenceClassification from phunganhsang
+author: John Snow Labs
+name: xlm_cita
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_cita` is a English model originally trained by phunganhsang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_cita_en_5.5.1_3.0_1738125985293.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_cita_en_5.5.1_3.0_1738125985293.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_cita","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_cita", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_cita|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|802.8 MB|
+
+## References
+
+https://huggingface.co/phunganhsang/XLM_CITA
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-xlm_cita_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-xlm_cita_pipeline_en.md
new file mode 100644
index 00000000000000..6c99fac6932176
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-xlm_cita_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_cita_pipeline pipeline XlmRoBertaForSequenceClassification from phunganhsang
+author: John Snow Labs
+name: xlm_cita_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_cita_pipeline` is a English model originally trained by phunganhsang.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_cita_pipeline_en_5.5.1_3.0_1738126105161.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_cita_pipeline_en_5.5.1_3.0_1738126105161.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_cita_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_cita_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_cita_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|802.8 MB|
+
+## References
+
+https://huggingface.co/phunganhsang/XLM_CITA
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-xlm_r_base_finetuned_after_mrp_v2_winter_morning_8_en.md b/docs/_posts/ahmedlone127/2025-01-29-xlm_r_base_finetuned_after_mrp_v2_winter_morning_8_en.md
new file mode 100644
index 00000000000000..e3e03f215caea8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-xlm_r_base_finetuned_after_mrp_v2_winter_morning_8_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_r_base_finetuned_after_mrp_v2_winter_morning_8 XlmRoBertaForSequenceClassification from haturusinghe
+author: John Snow Labs
+name: xlm_r_base_finetuned_after_mrp_v2_winter_morning_8
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_r_base_finetuned_after_mrp_v2_winter_morning_8` is a English model originally trained by haturusinghe.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_r_base_finetuned_after_mrp_v2_winter_morning_8_en_5.5.1_3.0_1738127741807.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_r_base_finetuned_after_mrp_v2_winter_morning_8_en_5.5.1_3.0_1738127741807.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_r_base_finetuned_after_mrp_v2_winter_morning_8","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_r_base_finetuned_after_mrp_v2_winter_morning_8", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_r_base_finetuned_after_mrp_v2_winter_morning_8|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|782.7 MB|
+
+## References
+
+https://huggingface.co/haturusinghe/xlm_r_base-finetuned_after_mrp-v2-winter-morning-8
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-xlm_r_base_finetuned_after_mrp_v2_winter_morning_8_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-xlm_r_base_finetuned_after_mrp_v2_winter_morning_8_pipeline_en.md
new file mode 100644
index 00000000000000..e171913816491e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-xlm_r_base_finetuned_after_mrp_v2_winter_morning_8_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_r_base_finetuned_after_mrp_v2_winter_morning_8_pipeline pipeline XlmRoBertaForSequenceClassification from haturusinghe
+author: John Snow Labs
+name: xlm_r_base_finetuned_after_mrp_v2_winter_morning_8_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_r_base_finetuned_after_mrp_v2_winter_morning_8_pipeline` is a English model originally trained by haturusinghe.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_r_base_finetuned_after_mrp_v2_winter_morning_8_pipeline_en_5.5.1_3.0_1738127881353.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_r_base_finetuned_after_mrp_v2_winter_morning_8_pipeline_en_5.5.1_3.0_1738127881353.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_r_base_finetuned_after_mrp_v2_winter_morning_8_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_r_base_finetuned_after_mrp_v2_winter_morning_8_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_r_base_finetuned_after_mrp_v2_winter_morning_8_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|782.7 MB|
+
+## References
+
+https://huggingface.co/haturusinghe/xlm_r_base-finetuned_after_mrp-v2-winter-morning-8
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-xlm_roberta_base_autext2024_09_12_2024_detection_en.md b/docs/_posts/ahmedlone127/2025-01-29-xlm_roberta_base_autext2024_09_12_2024_detection_en.md
new file mode 100644
index 00000000000000..807421911b591b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-xlm_roberta_base_autext2024_09_12_2024_detection_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_autext2024_09_12_2024_detection XlmRoBertaForSequenceClassification from ISEGURA
+author: John Snow Labs
+name: xlm_roberta_base_autext2024_09_12_2024_detection
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_autext2024_09_12_2024_detection` is a English model originally trained by ISEGURA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_autext2024_09_12_2024_detection_en_5.5.1_3.0_1738127979317.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_autext2024_09_12_2024_detection_en_5.5.1_3.0_1738127979317.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_autext2024_09_12_2024_detection","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_autext2024_09_12_2024_detection", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_autext2024_09_12_2024_detection|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|793.9 MB|
+
+## References
+
+https://huggingface.co/ISEGURA/xlm-roberta-base-autext2024_09-12-2024_detection
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-xlm_roberta_base_autext2024_09_12_2024_detection_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-xlm_roberta_base_autext2024_09_12_2024_detection_pipeline_en.md
new file mode 100644
index 00000000000000..fcc0f31c87592e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-xlm_roberta_base_autext2024_09_12_2024_detection_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_autext2024_09_12_2024_detection_pipeline pipeline XlmRoBertaForSequenceClassification from ISEGURA
+author: John Snow Labs
+name: xlm_roberta_base_autext2024_09_12_2024_detection_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_autext2024_09_12_2024_detection_pipeline` is a English model originally trained by ISEGURA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_autext2024_09_12_2024_detection_pipeline_en_5.5.1_3.0_1738128111015.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_autext2024_09_12_2024_detection_pipeline_en_5.5.1_3.0_1738128111015.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_autext2024_09_12_2024_detection_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_autext2024_09_12_2024_detection_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_autext2024_09_12_2024_detection_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|794.0 MB|
+
+## References
+
+https://huggingface.co/ISEGURA/xlm-roberta-base-autext2024_09-12-2024_detection
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-xlm_roberta_base_autext2024_attribution_en.md b/docs/_posts/ahmedlone127/2025-01-29-xlm_roberta_base_autext2024_attribution_en.md
new file mode 100644
index 00000000000000..e3f40af6cb6084
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-xlm_roberta_base_autext2024_attribution_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_autext2024_attribution XlmRoBertaForSequenceClassification from ISEGURA
+author: John Snow Labs
+name: xlm_roberta_base_autext2024_attribution
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_autext2024_attribution` is a English model originally trained by ISEGURA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_autext2024_attribution_en_5.5.1_3.0_1738127150247.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_autext2024_attribution_en_5.5.1_3.0_1738127150247.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_autext2024_attribution","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_autext2024_attribution", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_autext2024_attribution|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|824.9 MB|
+
+## References
+
+https://huggingface.co/ISEGURA/xlm-roberta-base-autext2024_attribution
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-xlm_roberta_base_autext2024_attribution_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-xlm_roberta_base_autext2024_attribution_pipeline_en.md
new file mode 100644
index 00000000000000..de9457656c09e3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-xlm_roberta_base_autext2024_attribution_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_autext2024_attribution_pipeline pipeline XlmRoBertaForSequenceClassification from ISEGURA
+author: John Snow Labs
+name: xlm_roberta_base_autext2024_attribution_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_autext2024_attribution_pipeline` is a English model originally trained by ISEGURA.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_autext2024_attribution_pipeline_en_5.5.1_3.0_1738127273002.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_autext2024_attribution_pipeline_en_5.5.1_3.0_1738127273002.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_roberta_base_autext2024_attribution_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_autext2024_attribution_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_autext2024_attribution_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|824.9 MB|
+
+## References
+
+https://huggingface.co/ISEGURA/xlm-roberta-base-autext2024_attribution
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-xlm_v_base_tweet_sentiment_arabic_trimmed_arabic_en.md b/docs/_posts/ahmedlone127/2025-01-29-xlm_v_base_tweet_sentiment_arabic_trimmed_arabic_en.md
new file mode 100644
index 00000000000000..de1854f7cb649f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-xlm_v_base_tweet_sentiment_arabic_trimmed_arabic_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_v_base_tweet_sentiment_arabic_trimmed_arabic XlmRoBertaForSequenceClassification from vocabtrimmer
+author: John Snow Labs
+name: xlm_v_base_tweet_sentiment_arabic_trimmed_arabic
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_v_base_tweet_sentiment_arabic_trimmed_arabic` is a English model originally trained by vocabtrimmer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_v_base_tweet_sentiment_arabic_trimmed_arabic_en_5.5.1_3.0_1738126623218.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_v_base_tweet_sentiment_arabic_trimmed_arabic_en_5.5.1_3.0_1738126623218.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_v_base_tweet_sentiment_arabic_trimmed_arabic","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_v_base_tweet_sentiment_arabic_trimmed_arabic", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_v_base_tweet_sentiment_arabic_trimmed_arabic|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|502.2 MB|
+
+## References
+
+https://huggingface.co/vocabtrimmer/xlm-v-base-tweet-sentiment-ar-trimmed-ar
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-xlm_v_base_tweet_sentiment_arabic_trimmed_arabic_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-xlm_v_base_tweet_sentiment_arabic_trimmed_arabic_pipeline_en.md
new file mode 100644
index 00000000000000..9972f40176a00e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-xlm_v_base_tweet_sentiment_arabic_trimmed_arabic_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_v_base_tweet_sentiment_arabic_trimmed_arabic_pipeline pipeline XlmRoBertaForSequenceClassification from vocabtrimmer
+author: John Snow Labs
+name: xlm_v_base_tweet_sentiment_arabic_trimmed_arabic_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_v_base_tweet_sentiment_arabic_trimmed_arabic_pipeline` is a English model originally trained by vocabtrimmer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_v_base_tweet_sentiment_arabic_trimmed_arabic_pipeline_en_5.5.1_3.0_1738126682888.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_v_base_tweet_sentiment_arabic_trimmed_arabic_pipeline_en_5.5.1_3.0_1738126682888.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_v_base_tweet_sentiment_arabic_trimmed_arabic_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_v_base_tweet_sentiment_arabic_trimmed_arabic_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_v_base_tweet_sentiment_arabic_trimmed_arabic_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|502.2 MB|
+
+## References
+
+https://huggingface.co/vocabtrimmer/xlm-v-base-tweet-sentiment-ar-trimmed-ar
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-xlm_v_base_tweet_sentiment_german_trimmed_german_en.md b/docs/_posts/ahmedlone127/2025-01-29-xlm_v_base_tweet_sentiment_german_trimmed_german_en.md
new file mode 100644
index 00000000000000..b6749ff370370b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-xlm_v_base_tweet_sentiment_german_trimmed_german_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_v_base_tweet_sentiment_german_trimmed_german XlmRoBertaForSequenceClassification from vocabtrimmer
+author: John Snow Labs
+name: xlm_v_base_tweet_sentiment_german_trimmed_german
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_v_base_tweet_sentiment_german_trimmed_german` is a English model originally trained by vocabtrimmer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_v_base_tweet_sentiment_german_trimmed_german_en_5.5.1_3.0_1738125532910.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_v_base_tweet_sentiment_german_trimmed_german_en_5.5.1_3.0_1738125532910.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_v_base_tweet_sentiment_german_trimmed_german","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_v_base_tweet_sentiment_german_trimmed_german", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_v_base_tweet_sentiment_german_trimmed_german|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|750.8 MB|
+
+## References
+
+https://huggingface.co/vocabtrimmer/xlm-v-base-tweet-sentiment-de-trimmed-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-xlm_v_base_tweet_sentiment_german_trimmed_german_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-xlm_v_base_tweet_sentiment_german_trimmed_german_pipeline_en.md
new file mode 100644
index 00000000000000..4f8e87e4735098
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-xlm_v_base_tweet_sentiment_german_trimmed_german_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_v_base_tweet_sentiment_german_trimmed_german_pipeline pipeline XlmRoBertaForSequenceClassification from vocabtrimmer
+author: John Snow Labs
+name: xlm_v_base_tweet_sentiment_german_trimmed_german_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_v_base_tweet_sentiment_german_trimmed_german_pipeline` is a English model originally trained by vocabtrimmer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_v_base_tweet_sentiment_german_trimmed_german_pipeline_en_5.5.1_3.0_1738125663207.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_v_base_tweet_sentiment_german_trimmed_german_pipeline_en_5.5.1_3.0_1738125663207.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_v_base_tweet_sentiment_german_trimmed_german_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_v_base_tweet_sentiment_german_trimmed_german_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_v_base_tweet_sentiment_german_trimmed_german_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|750.9 MB|
+
+## References
+
+https://huggingface.co/vocabtrimmer/xlm-v-base-tweet-sentiment-de-trimmed-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-xlm_v_base_tweet_sentiment_italian_trimmed_italian_en.md b/docs/_posts/ahmedlone127/2025-01-29-xlm_v_base_tweet_sentiment_italian_trimmed_italian_en.md
new file mode 100644
index 00000000000000..e2e151d2000de9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-xlm_v_base_tweet_sentiment_italian_trimmed_italian_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_v_base_tweet_sentiment_italian_trimmed_italian XlmRoBertaForSequenceClassification from vocabtrimmer
+author: John Snow Labs
+name: xlm_v_base_tweet_sentiment_italian_trimmed_italian
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_v_base_tweet_sentiment_italian_trimmed_italian` is a English model originally trained by vocabtrimmer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_v_base_tweet_sentiment_italian_trimmed_italian_en_5.5.1_3.0_1738127113524.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_v_base_tweet_sentiment_italian_trimmed_italian_en_5.5.1_3.0_1738127113524.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_v_base_tweet_sentiment_italian_trimmed_italian","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_v_base_tweet_sentiment_italian_trimmed_italian", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_v_base_tweet_sentiment_italian_trimmed_italian|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|656.7 MB|
+
+## References
+
+https://huggingface.co/vocabtrimmer/xlm-v-base-tweet-sentiment-it-trimmed-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-xlm_v_base_tweet_sentiment_italian_trimmed_italian_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-xlm_v_base_tweet_sentiment_italian_trimmed_italian_pipeline_en.md
new file mode 100644
index 00000000000000..90504ee75b1d10
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-xlm_v_base_tweet_sentiment_italian_trimmed_italian_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_v_base_tweet_sentiment_italian_trimmed_italian_pipeline pipeline XlmRoBertaForSequenceClassification from vocabtrimmer
+author: John Snow Labs
+name: xlm_v_base_tweet_sentiment_italian_trimmed_italian_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_v_base_tweet_sentiment_italian_trimmed_italian_pipeline` is a English model originally trained by vocabtrimmer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_v_base_tweet_sentiment_italian_trimmed_italian_pipeline_en_5.5.1_3.0_1738127217575.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_v_base_tweet_sentiment_italian_trimmed_italian_pipeline_en_5.5.1_3.0_1738127217575.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_v_base_tweet_sentiment_italian_trimmed_italian_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_v_base_tweet_sentiment_italian_trimmed_italian_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_v_base_tweet_sentiment_italian_trimmed_italian_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|656.7 MB|
+
+## References
+
+https://huggingface.co/vocabtrimmer/xlm-v-base-tweet-sentiment-it-trimmed-it
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-xlm_v_base_tweet_sentiment_spanish_trimmed_spanish_en.md b/docs/_posts/ahmedlone127/2025-01-29-xlm_v_base_tweet_sentiment_spanish_trimmed_spanish_en.md
new file mode 100644
index 00000000000000..5317fb8a591570
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-xlm_v_base_tweet_sentiment_spanish_trimmed_spanish_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_v_base_tweet_sentiment_spanish_trimmed_spanish XlmRoBertaForSequenceClassification from vocabtrimmer
+author: John Snow Labs
+name: xlm_v_base_tweet_sentiment_spanish_trimmed_spanish
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_v_base_tweet_sentiment_spanish_trimmed_spanish` is a English model originally trained by vocabtrimmer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_v_base_tweet_sentiment_spanish_trimmed_spanish_en_5.5.1_3.0_1738127262853.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_v_base_tweet_sentiment_spanish_trimmed_spanish_en_5.5.1_3.0_1738127262853.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_v_base_tweet_sentiment_spanish_trimmed_spanish","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_v_base_tweet_sentiment_spanish_trimmed_spanish", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_v_base_tweet_sentiment_spanish_trimmed_spanish|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|753.2 MB|
+
+## References
+
+https://huggingface.co/vocabtrimmer/xlm-v-base-tweet-sentiment-es-trimmed-es
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-xlm_v_base_tweet_sentiment_spanish_trimmed_spanish_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-xlm_v_base_tweet_sentiment_spanish_trimmed_spanish_pipeline_en.md
new file mode 100644
index 00000000000000..6d4d99768ed236
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-xlm_v_base_tweet_sentiment_spanish_trimmed_spanish_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_v_base_tweet_sentiment_spanish_trimmed_spanish_pipeline pipeline XlmRoBertaForSequenceClassification from vocabtrimmer
+author: John Snow Labs
+name: xlm_v_base_tweet_sentiment_spanish_trimmed_spanish_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_v_base_tweet_sentiment_spanish_trimmed_spanish_pipeline` is a English model originally trained by vocabtrimmer.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_v_base_tweet_sentiment_spanish_trimmed_spanish_pipeline_en_5.5.1_3.0_1738127396276.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_v_base_tweet_sentiment_spanish_trimmed_spanish_pipeline_en_5.5.1_3.0_1738127396276.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlm_v_base_tweet_sentiment_spanish_trimmed_spanish_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_v_base_tweet_sentiment_spanish_trimmed_spanish_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_v_base_tweet_sentiment_spanish_trimmed_spanish_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|753.2 MB|
+
+## References
+
+https://huggingface.co/vocabtrimmer/xlm-v-base-tweet-sentiment-es-trimmed-es
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-xlmr_pun_detection_en.md b/docs/_posts/ahmedlone127/2025-01-29-xlmr_pun_detection_en.md
new file mode 100644
index 00000000000000..0099dc966f4f78
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-xlmr_pun_detection_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlmr_pun_detection XlmRoBertaForSequenceClassification from likhithasapu
+author: John Snow Labs
+name: xlmr_pun_detection
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmr_pun_detection` is a English model originally trained by likhithasapu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmr_pun_detection_en_5.5.1_3.0_1738126081672.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmr_pun_detection_en_5.5.1_3.0_1738126081672.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlmr_pun_detection","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlmr_pun_detection", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmr_pun_detection|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|825.0 MB|
+
+## References
+
+https://huggingface.co/likhithasapu/xlmr-pun-detection
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-xlmr_pun_detection_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-xlmr_pun_detection_pipeline_en.md
new file mode 100644
index 00000000000000..20b2464c7b624e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-xlmr_pun_detection_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlmr_pun_detection_pipeline pipeline XlmRoBertaForSequenceClassification from likhithasapu
+author: John Snow Labs
+name: xlmr_pun_detection_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmr_pun_detection_pipeline` is a English model originally trained by likhithasapu.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlmr_pun_detection_pipeline_en_5.5.1_3.0_1738126170916.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmr_pun_detection_pipeline_en_5.5.1_3.0_1738126170916.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xlmr_pun_detection_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmr_pun_detection_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmr_pun_detection_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|825.0 MB|
+
+## References
+
+https://huggingface.co/likhithasapu/xlmr-pun-detection
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-xml_roberta_blame_v01_en.md b/docs/_posts/ahmedlone127/2025-01-29-xml_roberta_blame_v01_en.md
new file mode 100644
index 00000000000000..79330de0445e18
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-xml_roberta_blame_v01_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xml_roberta_blame_v01 XlmRoBertaForSequenceClassification from liserman
+author: John Snow Labs
+name: xml_roberta_blame_v01
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xml_roberta_blame_v01` is a English model originally trained by liserman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xml_roberta_blame_v01_en_5.5.1_3.0_1738126915335.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xml_roberta_blame_v01_en_5.5.1_3.0_1738126915335.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xml_roberta_blame_v01","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xml_roberta_blame_v01", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xml_roberta_blame_v01|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|851.0 MB|
+
+## References
+
+https://huggingface.co/liserman/xml-roberta-blame-v01
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-xml_roberta_blame_v01_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-xml_roberta_blame_v01_pipeline_en.md
new file mode 100644
index 00000000000000..ac217509c0e94f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-xml_roberta_blame_v01_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xml_roberta_blame_v01_pipeline pipeline XlmRoBertaForSequenceClassification from liserman
+author: John Snow Labs
+name: xml_roberta_blame_v01_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xml_roberta_blame_v01_pipeline` is a English model originally trained by liserman.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xml_roberta_blame_v01_pipeline_en_5.5.1_3.0_1738126980821.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xml_roberta_blame_v01_pipeline_en_5.5.1_3.0_1738126980821.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("xml_roberta_blame_v01_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xml_roberta_blame_v01_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xml_roberta_blame_v01_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|851.0 MB|
+
+## References
+
+https://huggingface.co/liserman/xml-roberta-blame-v01
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-yelp_review_classifier_en.md b/docs/_posts/ahmedlone127/2025-01-29-yelp_review_classifier_en.md
new file mode 100644
index 00000000000000..629faa1da480b3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-yelp_review_classifier_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English yelp_review_classifier DistilBertForSequenceClassification from kmack
+author: John Snow Labs
+name: yelp_review_classifier
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`yelp_review_classifier` is a English model originally trained by kmack.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/yelp_review_classifier_en_5.5.1_3.0_1738110486221.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/yelp_review_classifier_en_5.5.1_3.0_1738110486221.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("yelp_review_classifier","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("yelp_review_classifier", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|yelp_review_classifier|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/kmack/YELP-Review_Classifier
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-yelp_review_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-yelp_review_classifier_pipeline_en.md
new file mode 100644
index 00000000000000..6f136e9c00db70
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-yelp_review_classifier_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English yelp_review_classifier_pipeline pipeline DistilBertForSequenceClassification from kmack
+author: John Snow Labs
+name: yelp_review_classifier_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`yelp_review_classifier_pipeline` is a English model originally trained by kmack.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/yelp_review_classifier_pipeline_en_5.5.1_3.0_1738110501764.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/yelp_review_classifier_pipeline_en_5.5.1_3.0_1738110501764.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("yelp_review_classifier_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("yelp_review_classifier_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|yelp_review_classifier_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/kmack/YELP-Review_Classifier
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-zero_shot_soft_ware_project_xlmr_en.md b/docs/_posts/ahmedlone127/2025-01-29-zero_shot_soft_ware_project_xlmr_en.md
new file mode 100644
index 00000000000000..27b33bd27bf727
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-zero_shot_soft_ware_project_xlmr_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English zero_shot_soft_ware_project_xlmr XlmRoBertaForSequenceClassification from Blue7Bird
+author: John Snow Labs
+name: zero_shot_soft_ware_project_xlmr
+date: 2025-01-29
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`zero_shot_soft_ware_project_xlmr` is a English model originally trained by Blue7Bird.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/zero_shot_soft_ware_project_xlmr_en_5.5.1_3.0_1738127668340.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/zero_shot_soft_ware_project_xlmr_en_5.5.1_3.0_1738127668340.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("zero_shot_soft_ware_project_xlmr","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("zero_shot_soft_ware_project_xlmr", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|zero_shot_soft_ware_project_xlmr|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|655.1 MB|
+
+## References
+
+https://huggingface.co/Blue7Bird/Zero_shot_Soft_ware_project_XLMR
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2025-01-29-zero_shot_soft_ware_project_xlmr_pipeline_en.md b/docs/_posts/ahmedlone127/2025-01-29-zero_shot_soft_ware_project_xlmr_pipeline_en.md
new file mode 100644
index 00000000000000..5928c3ee9fe179
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2025-01-29-zero_shot_soft_ware_project_xlmr_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English zero_shot_soft_ware_project_xlmr_pipeline pipeline XlmRoBertaForSequenceClassification from Blue7Bird
+author: John Snow Labs
+name: zero_shot_soft_ware_project_xlmr_pipeline
+date: 2025-01-29
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`zero_shot_soft_ware_project_xlmr_pipeline` is a English model originally trained by Blue7Bird.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/zero_shot_soft_ware_project_xlmr_pipeline_en_5.5.1_3.0_1738127852825.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/zero_shot_soft_ware_project_xlmr_pipeline_en_5.5.1_3.0_1738127852825.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("zero_shot_soft_ware_project_xlmr_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("zero_shot_soft_ware_project_xlmr_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|zero_shot_soft_ware_project_xlmr_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|655.2 MB|
+
+## References
+
+https://huggingface.co/Blue7Bird/Zero_shot_Soft_ware_project_XLMR
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file